Gender & health in South-East Asia: regional factsheet

Gender & health in South-East Asia: regional factsheet Why does gender matter for health? Gender is a major determinant of health for women, men and people of diverse gender identities. Gender norms, roles and relations interact with biological factors, in turn influencing people’s exposure to disease and risks for ill health. Therefore, it is important for health policymakers to consider the different gender needs of all men and women. Tailoring health policies and programmes to take account of these differences and trends can improve their impact, reduce health inequities and advance the right to health for all 1 Unit: US$ Unit: US$ Catastrophic household health expenditure, WHO SE Asia Region4 and countries5 The proportion of households facing catastrophic expenditure on health has been rising in several countries as well as in the Region overall Unit: % Out-of-pocket expenditure, WHO SE Asia Region6 and countries7 Unit: % of current health expenditure The share of out-of-pocket expenditure in health has been declining in the Region. However, it remains unacceptably high in several countries 80 60 40 20 0 2017 2018 2019 74 76 57 55 49 40 39 21 13 12 8 8 13 19 17 18 36 35 46 55 55 58 58 77 76 74 73 37 910 40 47 8 25 20 15 10 5 0 2000 2005 2010 2015 2020 7 3 2 3 20 10 11 10 10 6 5 5 15 15 13 3 4 4 5 4 2 2 14 18 17 24 12 13 13 13 2 4 1414 25000 20000 15000 10000 5000 0 19217 18198 19210 18232 13442 13227 13632 14127 12904 11620 11129 12366 12311 12072 6972 6525 7334 4141 59955784 6613 4940 4345 4120 42613780 4418 20334 2018 2019 2020 2021 3997 5123 2017 2018 2019 500 250 0 670750 459 435 356 318 212 182 215 238 220 123 177 114 101 358 432 469 524 570 708 731 227 211 1669 1473 1640 1750 1500 171168 196 334 223 368 435 Gross domestic product per capita1 Current health expenditure per capita, WHO SE Asia Region2 and countries3 WHO SE Asia Region BAN BHU IND INO MAV MYA NEP SRL THA TLS Sex ratio at birth11 (2020) Income inequality has marginally increased in half of the countries Progress towards gender parity has slowed in recent years, with only four countries (Bangladesh, India, Indonesia and Sri Lanka) having improved since 2020. Bangladesh, Thailand and Timor-Leste lead regional performance, having closed over 70% of their gender gap Poverty level8,9 Although poverty levels have been declining, a significant proportion of people in the Region continue to live in poverty Unit: %*THA & MAV: US$ 5.50 a day, others: US$ 1.90 a day Unit: Men per 100 women BAN BHU IND INO MAV MYA NEP SRL THA TLS Gender gap closed, 2022 (%) BAN BHU IND INO MAV MYA NEP SRL THA TLS Unit: Scale of 0–100 with 0 being better Gini index10 50 40 30 20 2001 2005 2010 2015 2020 36 28 29 38 44 33 34 3938 31 29 37 3736 35 35 37 37 32 32 31 36 39 39 3836 35 33 BAN BHU IND INO MAV MYA NEP SRL THA TLS 110 105 100 50 40 30 20 10 0 2005 20102001 2015 2020 25 4039 37 22 43 19 158 2 8 6 6 2 14 3 2 1 2 2 3 23 33 3 5 2 110 105 104 105 107 103 107 104 106 105 Gender gap index12 BAN BHU IND INO MAV MYA NEP SRL THA TLS 100% 80% 60% 40% 20% 0% 0.040 0.020 0.000 -0.020 -0.040 -0.060 -0.080 71.40 0.012 -0.002 0.039 0.003 -0.002 -0.012 -0.012 0.010 -0.001 -0.068 63.70 62.90 69.70 64.80 67.70 69.20 67.00 70.90 73.00 Score change 2020–2022 1 2 The COVID-19 pandemic stalled the progress of human development globally in 2020–2021 and WHO SE Asia Region is no exception. Almost all countries in the Region experienced moderate decreases in their human development index (HDI) and inequality-adjusted human development index (IHDI) scores Human development index15 and inequality-adjusted human development index16 Unit: Index from 0 to 1HDI WomenHDI Men IHDI Gender development index13 Unit: Index from 0 to 1 BAN BHU IND INO MAV MYA NEP SRL THA TLS Gender inequality index14 Unit: Index from 0 to 1 with 0 being better 2019 2020 2021 0.531 0.509 0.491 0.498 0.486 0.493 0.490 0.423 0.531 0.530 0.6 0.5 0.4 0.3 0.422 0.415 0.3480.353 0.335 0.335 0.333 0.385 0.380 0.384 0.383 0.378 0.351 0.379 0.4440.447 0.457 0.454 0.454 0.452 BAN BHU IND INO MAV MYA NEP SRL THA TLS 1.013 0.960 0.956 0.949 0.941 0.955 0.949 0.944 1.013 1.012 1.05 1 0.95 0.9 0.85 0.8 2019 2020 2021 0.941 0.939 0.916 0.900 0.852 0.845 0.896 0.918 0.921 0.849 0.898 0.917 0.9250.937 0.9410.9420.941 0.947 0.959 0.937 0. 67 9 0. 57 9 0. 48 2 0. 67 7 0. 57 2 0. 48 1 0. 66 8 0. 56 7 0. 47 5 IND 2019 2020 2021 0. 73 6 0. 69 1 0. 59 3 0. 72 8 0. 68 5 0. 58 9 0. 72 3 0. 68 1 0. 58 5 INO 2019 2020 2021 0. 67 0 0. 60 3 0. 48 9 0. 68 2 0. 61 2 0. 48 9 0. 68 8 0. 61 7 0. 50 3 BAN 2019 2020 2021 0. 68 8 0. 64 8 0. 47 3 0 .6 86 0. 64 3 0. 47 1 0 .6 84 0. 64 1 0. 47 1 BHU 2019 2020 2021 0. 60 9 0. 58 4 0. 61 4 0. 58 2 0. 59 9 0. 56 5 MYA 2019 2020 2021 0. 62 7 0. 59 6 0. 45 4 0. 62 4 0. 58 7 0. 45 1 0. 62 1 0. 58 4 0. 44 9 NEP 2019 2020 2021 0. 79 0 0. 75 4 0. 67 2 0. 79 1 0. 75 5 0. 67 4 0. 79 5 0. 75 5 0. 67 6 2019 2020 2021 SRL 0. 76 9 0. 73 8 0. 59 9 0. 75 2 0. 69 3 0. 58 3 0. 76 6 0. 70 9 0. 59 4 MAV 2019 2020 2021 0. 79 9 0. 80 9 0. 68 7 0. 79 7 0. 80 8 0. 68 6 0. 79 6 0. 80 5 0. 68 6 2019 2020 2021 THA 0. 64 0 0. 58 7 0. 44 3 0. 64 0 0. 58 7 0. 44 4 0. 63 3 0. 58 0 0. 44 0 2019 2020 2021 TLS 3 Health is significantly determined by social, economic and environmental factors that lie beyond the health sector, such as poverty, education, employment and physical security. Gender inequality, an important determinant of health, remains a challenge. Women lag behind men in many indicators like literacy, tertiary education and access to mass media and mobile phones. Women’s lower labour force participation rate and their higher average hours per day spent in unpaid care work also reflect gender inequality. Data for gender-diverse people are generally unavailable Does gender influence access to determinants of health? Although literacy rates have improved steadily, women continue to lag behind men in most countries in the Region Literacy rate17 IND 2018 82 66 BAN 2018 2019 2020 77 71 77 72 78 72 BHU 2005 2012 2017 65 39 66 45 57 75 SRL 2018 2019 2020 93 91 93 92 93 92 THA 2013 2015 2018 95 92 95 91 95 92 TLS 2007 2010 2018 59 43 64 53 72 64 INO 2016 2018 2020 97 94 97 94 97 95 MAV 2014 2016 99 99 97 98 MYA 2016 2019 80 72 92 86 NEP 2011 2018 72 49 79 60 Primary Secondary Tertiary Primary Secondary Tertiary 2.0 1.5 1.0 0.5 BAN 2020 1.21 1.09 0.77 IND 2020 1.02 1.11 1.00 NEP 2020 0.99 1.03 1.04 THA 2020 0.98 1.00 MAV 2019 1.03 0.93 1.73 TLS 2019 0.98 1.09 BHU 2018 1.00 0.99 1.13 INO 2018 0.97 1.03 1.16 MYA 2018 0.96 1.29 1.09 SRL 2018 0.99 1.05 1.33 Gender parity index in school enrolment18 Unit: Ratio Unit: %Men Women 4 Girls are still highly under-represented in science, technology, engineering and mathematics (STEM) subjects. The proportion of girls graduating in STEM subjects ranges from one to six in every ten graduates across countries in the Region Unit: % Women graduates in STEM19 THA 2016 30 Women’s access to and use of mass media generally lags behind men across countries in the Region. Similarly, survey data on the use of the internet and ownership of mobile phones point to a significant digital gender divide that disadvantages women relative to men Access to mass media20 Unit: % NEWS Unit: % Use of internet21 BAN 2013 2017 8 18 75 IND 2017 2018 26 2511 15 MYA 2016 2017 37 24 29 19 INO 2019 2020 51 5745 51 THA 2019 2020 68 7966 77 MAV 2017 87 78 NEP 2016 2019 47 6123 4 SRL 2016 16 TLS 2016 28 22 2014 6553 2019 BAN 2016 6484 5774 2021 IND 2012 8690 88 2017 INO 2009 8999 9499 2017 MAV 2016 71 68 MYA 2016 7831 6737 2019 NEP 2006 8988 2016 SRL 2010 4760 4352 2016 TLS INO 2018 37 MYA 2018 61 IND 2018 43 MAV 2017 11 SRL 2018 41 BAN 2018 21 5 Unit: % Although ownership or control over financial and other productive assets tends to advance women’s empowerment, data from the Region point to significant gender inequalities in this regard. The proportion of women varies from fewer than one to nearly three in every ten agricultural landholders across countries in the Region Women agricultural landholders23 (2019) Ownership of mobile phones22 BAN 2018 47 NEP 2019 79 INO 2019 58 THA 2017 88 MYA 2017 57 IND 2017 43 MAV 2017 TLS 2016 66 Unit: % 7668697974 88919697 BAN 5 SRL 16 MYA 15 IND 13 INO 9 NEP 8 THA 27 Unit: % Similarly, the proportion of women with accounts in financial institutions lags behind men, ranging from 28% to 93% across countries in the Region, compared with 39% to 99% for men Account in a financial institution24 36.7 50.031.3 41.6 2014 2017 58.6 49.9 2021 NEP 82.2 73.983.1 73.4 2014 2017 89.3 89.3 2021 SRL 81.2 83.775.4 79.8 2014 2017 98.6 92.7 2021 THA 62.8 83.043.1 76.6 2014 2017 77.5 77.6 2021 IND 35.4 64.6 62.926.5 35.8 43.5 2014 2017 2021 BAN 39.0 27.7 2014 BHU 28.6 26.017.4 26.0 2014 2017 49.5 46.2 2021 MYA 34.6 46.337.5 51.4 2014 2017 51.2 52.3 2021 INO 85.5 74.2 2017 MAV 6 Unit: % Women’s persistent economic disempowerment is reflected in the fact that the proportion of women saying that they, alone or jointly, make major household decisions ranges from fewer than four to nearly nine in every ten married women across the Region Women’s participation in household decision-making25 BAN 2018 IND 2021 INO 2017 MAV 2017 MYA 2016 NEP 2016 SRL 2016 TLS 2016 Unit: Ratio (US$)Men Women Gap in earned income between men and women26 Data from the Region point to a persistent gender wage gap, with women earning only between US$ 2 and 8 for every US$ 10 made by men across countries in the Region, with the exception of Timor-Leste $ $ $ $ $ $ $ $ $ $ $$ $$ $ $ $ $ $ $$ $ $ $ $$ $ $ $ $ $ $ $ $ $$ $ $ $ $ $$ $ $ $ $ $ $ $ $ $ $ $ $ $$ $ $ $ $ $ $$ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $$ $ $ $ $ $ $ $$ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $$ $ $ $ $ $ $ $ $$ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $$ $ $ $ $ $ $ $ $$ $ $ $ $ $ $ $ $ BAN BHU IND INO MAV MYA NEP SRL THA TLS 20 20 20 21 20 22 20 20 20 21 20 22 20 20 20 21 20 22 20 20 20 21 20 22 20 20 20 21 20 22 20 20 20 20 20 21 20 21 20 22 20 22 20 20 20 21 20 22 20 20 20 21 20 22 20 18 20 20 20 21 $ $ $ $ $ $ $ $ $ $ $ $ $ $$ $$ 6 6 6 2 2 2 5 5 5 5 4 6 5 6 5 6 7 7 4 4 4 8 8 8 6 103 $ $ $ $ $ $ $ $ $ $ $ $ $$$ 4 4 4 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $$ $ $$ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ Though it has narrowed over time, a gender gap in labour force participation persists across the Region, with women lagging behind men by more than 50 percentage points in some countries. With the exception of Nepal, the proportion of women in the labour force ranges from three to eight for every ten men in the labour force Labour force participation rate27 Unit: %Men Women $ 59 73 68 80 65 38 77 87 BAN 2013 2015 2017 82 34 79 33 81 36 MAV 2014 2016 2019 83 48 76 44 79 51 THA 2018 2019 2020 77 60 76 59 75 59 IND 2018 2019 2020 75 21 74 22 76 26 NEP 2020 2021 2022 80 76 81 79 82 82 BHU 2018 2019 2020 70 56 72 61 73 64 MYA 2020 2021 2022 72 43 70 41 71 43 TLS 2010 2013 2016 56 27 65 44 73 61 INO 2019 2020 2021 83 54 82 53 80 52 SRL 2017 2018 2019 75 37 73 34 73 34 7 Informal sector participation28 Although women’s labour force participation is significantly lower than that for men, they are over-represented in the informal sector, often outnumbering their men counterparts Boys Girls Unit: % Unit: % BAN 2019 8.8 4.6 NEP 2014 20.3 23.1 BHU 2010 2.8 4.2 SRL 2016 0.9 0.6 IND 2005 11.6 11.9 THA 2006 9.3 9.2 INO 2009 7.9 5.8 TLS 2016 9.5 8.9 MYA 2015 10.2 9.7 Child labour is, unfortunately, still a reality in many countries Child labour29 Unit: % Women in managerial positions30 Women are largely absent from executive decision-making, with the proportion of women ranging from one to four in every ten managers across countries in the Region IND 2020 BHU 2020 BAN 2017 TLS 2016 SRL 2019 MYA 2020 MAV 2019 NEP 2017 THA 2020 INO 2021 Men Women 33 25 27 28 3218 11 19 13 39 THA 2016 2017 2018 55 475156 4954 MYA 2018 2019 2020 62 696359 6961 TLS 2010 2013 68 87 63 75 NEP 2017 6457 SRL 2017 2018 2019 55 545463 6465 BAN 2010 2013 2017 87 858080 8175 MAV 2016 2019 47 4248 29 IND 2018 2019 2020 81 827982 8180 INO 2017 2018 2019 86 5761 83 5458 8 Distribution of doctors31 Distribution of nurses32 A considerable gender imbalance exists in medical and nursing professions. Except in Indonesia, Nepal and Sri Lanka, men predominate among medical doctors Except for Myanmar, Nepal and Timor-Leste, women predominate among nurses across countries in the Region BAN 2020 58.4 41.6 SRL 2018 44.7 55.3 BHU 2020 60.8 39.2 THA 2019 54.1 45.9 INO 2020 40.1 59.9 TLS 2020 56.5 43.5 MAV 2020 59.9 40.1 MYA 2019 43.6 56.4 NEP 2020 33.3 66.7 Access to improved water sources has increased over time. Fewer than three per cent of households are now located more than half an hour from an improved water source across most countries in the Region, potentially freeing up precious time for women and girls, who are typically assigned the gender role of household water collection and management Households >30 minutes from water source33 Unit: % WomenMen Unit: % BAN 1.2 2011 2014 2019 1.6 0.5 BHU 0.7 2010 TLS 17 2010 2016 7.7 MAV 0.4 2009 2017 0.1 THA 0.1 2012 2016 2019 0.1 0.0 IND 4.3 2006 2016 2021 2.3 1.2 NEP 4.0 2006 2011 2016 2.9 1.9 MYA 2.0 2016 INO 1.2 2007 2012 2017 0.8 0.5 SRL 3.5 2006 2016 2.8 BAN 2020 90.010.0 NEP 2020 0.299.8 BHU 2020 55.444.6 SRL 2019 95.54.5 IND 2018 88.111.9 THA 2019 94.85.2 INO 2020 72.227.8 TLS 2020 38.761.3 MAV 2020 89.810.2 MYA 2019 3.496.6 Men Women Unit: % 9 Women and girls perform most of the unpaid work in households, spending two to five times more time daily doing such work than men across most countries. This highly unequal gender-based division of unpaid labour in homes contributes significantly to women’s time poverty, constraining them from playing their due roles in economic and political life Time spent on unpaid work34 Life expectancy and healthy life expectancy at birth, WHO SE Asia Region35 and countries36,37 Do men and women have similar life expectancies? Women have a better life expectancy and healthy life expectancy at birth than men. On average, women live three years longer than men in the Region and up to six years longer in some countries. Although they are likely to live longer, women spend a proportionately longer period of their lives facing ill health compared to men BAN Men 2015 Men 2019 Women 2015 Women 2019 72.5 74.8 73.0 75.6 63.8 63.7 64.2 64.4 MYA Men 2015 Men 2019 Women 2015 Women 2019 64.3 70.7 65.9 72.2 57.5 61.5 58.8 62.8 BHU Men 2015 Men 2019 Women 2015 Women 2019 71.1 73.5 72.0 74.4 62.5 62.7 63.2 63.5 NEP Men 2015 Men 2019 Women 2015 Women 2019 67.3 71.4 68.9 72.7 59.3 61.1 60.6 62.1 IND Men 2015 Men 2019 Women 2015 Women 2019 68.1 70.6 69.5 72.2 59.1 59.2 60.3 60.4 Men 2015 Men 2019 Women 2015 Women 2019 SRL 73.0 79.4 73.8 79.8 64.4 68.6 65.1 69.0 INO Men 2015 Men 2019 Women 2015 Women 2019 68.8 72.5 69.4 73.3 61.5 63.2 61.9 63.8 Men 2015 Men 2019 Women 2015 Women 2019 THA 74.1 80.7 74.4 81.0 65.7 70.3 65.9 70.6 MAV Men 2015 Men 2019 Women 2015 Women 2019 77.6 79.5 78.6 80.8 69.0 69.1 69.7 70.0 Men 2015 Men 2019 Women 2015 Women 2019 TLS 67.3 70.5 67.9 71.4 59.4 61.3 59.8 62.0 Unit: Years 2012 3.5 BAN 1.4 2021 5.8 0.8 2019BHU 3.6 1.5 2019IND 7.2 2.9 2016MAV 6.0 3.0 2012NEP 4.5 0.9 SRL 2017 6.5 2.6 2015 6.0 3.5 2009 5.8 3.1 2004THA 6.0 3.5 2007 3.7 2.9 2001TLS 5.5 3.2 Unit: Hours per day WHO SE Asia Region Men 2015 Women 2015 68.7 71.8 60.1 60.8 Healthy life expectancy Life expectancy Men 2019 Women 2019 69.9 73.1 61.1 61.9 10 Disease burdens are different between men and women in the Region. Cirrhosis of the liver and road injury feature in the ten leading causes of death among men, but not among women. Kidney diseases and asthma figure in the ten leading causes of death among women, but not among men The survival of children under five years of age has improved over time across countries in the Region Similarly, cirrhosis of the liver and road injury feature in the ten leading causes of DALYs lost among men, but not among women. Iron-deficiency anaemia and (other) musculoskeletal disorders feature in the ten leading causes of DALYs lost among women, but not among men Under-5 mortality rate by sex, WHO SE Asia Region42 and countries43 Unit: Per thousand live births Do gender, location of residence, education and income affect the health status of people in WHO SE Asia Region? The health status of women, men and people of diverse-genders in WHO SE Asia Region, as elsewhere, is determined by the interaction between social (gender) and biological (sex) differences. The differences in health status between men and women go beyond sexual and reproductive health. Besides gender, location of residence (urban/rural), education and income also affect health status. Data for gender and sexual minorities are generally unavailable Men Women Ischaemic heart disease26.53 Ischaemic heart disease22.14 Stroke15.28 Stroke18.03 Chronic obstructive pulmonary disease13.82 Chronic obstructive pulmonary disease12.69 Tuberculosis8.32 Diarrhoeal diseases12.56 Diarrhoeal diseases6.95 Lower respiratory infections7.24 Neonatal conditions6.46 Neonatal conditions6.93 Cirrhosis of the liver6.28 Tuberculosis6.52 Lower respiratory infections5.84 Diabetes mellitus6.25 Road injury5.41 Kidney diseases3.82 Diabetes mellitus5.09 Asthma3.82 10 leading causes of death among men38 and women39 Unit: Cause-specific death rates as % of ten leading causes 2019 2019 Men Women Ischaemic heart disease18.06 Neonatal conditions16.89 Tuberculosis11.29 Stroke10.26 Road injury9.50 Chronic obstructive pulmonary disease8.83 Diarrhoeal diseases7.34 Diabetes mellitus6.04 Lower respiratory infections6.01 Cirrhosis of the liver5.78 10 leading causes of DALYs lost among men40 and women41 Unit: Disease-specific DALYs lost as % of ten leading diseases Neonatal conditions18.69 Ischaemic heart disease13.44 Stroke11.55 Diarrhoeal diseases11.07 Tuberculosis10.37 Chronic obstructive pulmonary disease8.37 Lower respiratory infections7.26 Diabetes mellitus7.02 Iron-deficiency anaemia6.29 Other musculoskeletal disorders5.942019 2019 GirlsBoys MAV 2009 20 14 2017 24 16 TLS 2016 46 36 2010 69 58 THA 2020 10 8 2019 10 8 2018 10 8 SRL 2016 14 10 2006 26 19 NEP 2019 32 25 2016 36 41 2014 40 36 MYA 2016 56 44 BAN 2014 44 48 2018 48 41 2019 43 36 WHO SE Asia Region 2000 82 86 2005 66 69 2010 51 54 2015 40 40 2019 32 31 BHU 2010 79 58 IND 2006 70 79 2016 52 48 2021 44 40 INO 2007 53 35 2012 49 37 2017 37 26 11 Under-5 mortality rate by location of residence44 Under-5 mortality rate by household income quintile46 Under-5 mortality rate by mother’s education45 Unit: Per thousand live births Unit: Per thousand live births Unit: Per thousand live births BHU 2010 77 61 31 IND 2016 2021 68 62 27 60 48 25 SRL 2006 2016 44 29 23 19 14 12 6 INO 2012 2017 96 52 32 18 82 36 28 27 NEP 2014 2019 48 38 31 20 31 35 23 16 BAN 2014 2018 2019 50 45 27 55 47 31 50 45 38 27 IND 2016 72 57 46 35 23 $ 2021 $ 48 59 39 33 20 BHU 2010 $ 106 88 74 39 BAN 2014 2018 2019 $ $ 53 63 47 37 30 $ 55 43 44 45 36 $ 49 44 42 35 28 INO 2012 70 43 39 34 23 $ 2017 $ 53 33 29 31 24 SRL 2006 33 26 21 16 15 $ 2016 17 10 10 14 9 THA 2018 13 11 9 8 6 2019 13 10 9 8 5 2020 12 10 9 7 5 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ NEP 2014 57 42 31 31 22 $ 2019 $ 33 37 38 17 13 Similarly, children from the richest households have a three times higher chance of survival than children from the poorest households However, children from rural households generally tend to fare worse than their urban counterparts Children of mothers without any education have a two to three times higher risk of dying than children of highly educated mothers in countries across the Region Urban Rural Poorest Second Middle Fourth Richest Secondary HigherNo education Primary BAN 2014 37 49 2018 48 43 2019 35 41 BHU 2010 41 81 MYA 2016 34 55 IND 2006 52 82 2016 34 56 2021 32 46 INO 2007 32 53 2012 34 52 2017 31 33 NEP 2014 26 40 2016 34 44 2019 29 28 SRL 2006 19 23 2016 11 12 TLS 2010 46 69 2016 33 44 MAV 2009 15 18 2017 24 19 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $$$$ $ $ $ $ 12 13 BHU 33 34 2010 2015 18 25 2018 32 30 INO MYA 2016 31 27 TLS 53 47 2013 2020 52 47 BAN 37 35 31 31 2014 2018 2019 28 28 MAV 20 17 2009 2017 16 14 SRL 18 17 2006 2016 18 17 THA 16 16 12 9 2012 2016 2019 15 11 Nutritional status of children by sex47 Stunting Stunting Wasting Wasting Underweight The nutritional status of children under five years of age has improved over time across the Region. However, children from rural households, children of mothers with lower education and children from lower household income quintiles tend to fare worse than other children NEP 41 40 36 36 2011 2016 2019 33 30 Unit: % IND 48 48 2006 2016 2021 36 3539 38 BHU 6 6 2010 2015 5 4 2018 11 9 INO MYA 2016 8 6 TLS 13 9 2013 2020 9 6 BAN 15 14 22 22 2014 2018 2019 10 9 IND 21 19 22 20 2006 2016 2021 20 19 MAV 11 11 2009 2017 10 8 SRL 16 13 2006 2016 15 15 THA 7 6 6 5 2012 2016 2019 8 7 NEP 12 10 10 10 2011 2016 2019 14 10 Unit: % Unit: % Nutritional status of children by location of residence48 Unit: % Unit: % Boys Girls Boys Girls Boys Girls Urban Rural Urban Rural BHU 13 12 2010 2015 8 10 BAN 32 33 9 8 2014 2018 2019 22 23 IND 42 43 36 35 2006 2016 2021 33 31 BAN 2014 2018 2019 31 38 25 33 26 28 BHU 2010 2015 28 36 16 26 IND 2006 2016 2021 40 51 31 41 30 37 2018 19 17 INO MYA 2016 20 18 TLS 39 36 2013 2020 34 30 MAV 18 17 2009 2017 14 15 SRL 22 20 2006 2016 21 21 THA 10 8 8 6 2012 2016 2019 9 7 NEP 30 28 27 27 2011 2016 2019 25 24 INO 2018 27 35 TLS 2013 2020 39 55 53 40 MAV 2009 2017 16 20 13 16 SRL 2006 2016 14 16 15 17 MYA 2016 20 32 NEP 2011 2016 2019 27 42 32 40 29 36 THA 2012 2016 2019 13 18 10 11 14 13 INO 2018 10 11 MAV 2009 2017 7 12 10 9 MYA 2016 9 7 BAN 2014 2018 2019 26 35 19 23 9 10 BHU 2010 2015 7 6 3 5 IND 2006 2016 2021 17 21 20 21 19 20 NEP 2011 2016 2019 8 11 9 10 11 14 TLS 2013 2020 14 10 9 7 SRL 2006 2016 15 15 13 16 THA 2012 2016 2019 6 7 4 6 7 8 14 Unit: % Underweight Wasting Underweight Stunting Nutritional status of children by mother’s education49 47 41 31 23 2011 NEP 46 37 30 21 2016 2019 39 36 26 18 THA 34 17 16 13 2012 17 10 11 9 2016 2019 19 12 15 13 SRL 41 29 18 10 2006 2016 38 27 20 12 TLS 52 55 45 31 2020 Unit: % Unit: % Unit: % MYA 2016 8 7 7 9 Urban Rural No education SecondaryPrimary Higher No education SecondaryPrimary Higher No education SecondaryPrimary Higher INO 2018 16 20 MAV 2009 2017 11 20 15 15 MYA 2016 15 20 BAN 2014 2018 2019 12 15 9 8 19 24 BHU 2010 2015 11 14 6 12 IND 2006 2016 2021 33 46 29 38 27 34 NEP 2011 2016 2019 17 30 23 31 22 28 TLS 2013 2020 33 39 30 33 SRL 2006 2016 17 21 16 21 THA 2012 2016 2019 7 10 5 8 7 8 BHU 2010 37 31 23 2015 28 21 11 MYA 2016 39 32 23 17 BAN 47 44 31 20 43 39 29 15 2014 2018 2019 40 34 25 19 IND 57 49 38 19 51 44 33 21 2006 2016 2021 46 42 33 23 MAV 23 20 16 12 2009 2017 19 16 16 13 BHU 20152010 6 5 6 6 4 2 BAN 42 39 28 18 36 27 20 11 2014 2018 2019 13 11 10 7 IND 23 20 16 13 23 21 21 18 2006 2016 2021 22 20 19 17 MAV 16 12 9 10 2009 2017 0 12 10 6 BHU 2010 14 11 8 2015 11 10 5 MYA 2016 26 20 15 15 BAN 15 16 14 13 2014 12 9 8 6 2018 2019 33 27 21 14 IND 52 43 32 16 2006 47 40 31 19 2016 2021 42 37 30 21 MAV 27 21 12 14 2009 2017 3 19 15 12 NEP 38 26 18 9 2011 37 28 21 14 2016 2019 33 25 20 11 THA 14 10 9 7 2012 6 7 7 5 2016 2019 11 8 8 6 SRL 36 33 22 13 2006 2016 34 30 25 10 TLS 2020 35 34 30 22 NEP 13 12 6 12 2011 13 9 9 7 2016 2019 16 12 10 8 THA 9 6 7 7 2012 9 5 5 5 2016 2019 13 8 6 9 SRL 17 19 16 12 2006 2016 18 18 18 9 TLS 2020 8 8 8 7 15 Nutritional status of children by household income quintile50 Stunting Wasting TLS 20202013 57 55 53 46 35 59 57 53 47 39 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ THA 2012 2016 2019 23 20 16 11 11 16 15 12 11 14 $ $ $ $ $ $ $ 13 $ $ $ $ $ $ 11 $ $ $ $9 $ $ $ $ $8 $ 12 $ $ $ $ $ $ 46 40 34 28 23 60 54 49 41 25 51 44 37 29 22 IND 2021 $ $$ $$ 2006 $$$$$ 2016 $ $$$$ $ $$ $$$$$$$ $ $$$$ $ $ $ $$$$$$ $$ $ $ $$ $$$ $ $ $ $$$$$$ $$$$ $ $$ $ BHU 2010 $ $$ $$ 41 40 38 28 21 2015 $$ $$ 35 22 21 19 6 $ $ $$ $$ $ $$ $$ $ $ $ $ $$ $ $$$ $ $ MAV 2009 2017 22 18 23 1618 1515 1116 16 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ MYA 2016 38 32 29 21 16 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ NEP 2016 49 39 36 32 17 2019 44 32 32 28 18 2011 56 46 35 31 26 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ SRL 2006 28 20 16 13 8 2016 25 19 16 14 12 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $$ $ $ $ $ BHU 2010 5 7 6 6 6 2015 7 4 3 6 2 $ $$ $$ $$$ $$ IND 2021 $ $$ $ $$ $ 23 20 18 18 16 2006 $$$$ $ 25 22 19 17 13 2016 $ $$ $ $ $ 24 22 20 19 18 $ $$$$ $ $ $ $ $ $ $$ $ $ $$ BAN 2014 $$ $ $ $ $ $ $ $ $ $ $ $ 45 39 32 27 17 2018 $$ $ $ $ $ $ $ $ 29 26 20 21 13 2019 $ $ 12 12 9 8 8 $ $ $ $ $ $ $$ $ $ $ $ $ $ THA 2012 2016 2019 8 7 7 6 7 $ $ $ $ $ 6 6 7 4 4 $ $ $ $ $ 11 7 6 7 6 $ $ $ $$ $ SRL 2006 2016 $$ $ $$ 17 15 16 15 11 $ $ $ $$ 17 18 15 14 10$ $ $$$$ $ $$ NEP 2016 20192011 $ $ 9 9 11 11 7 $$ $$ 13 13 14 12 7 $$ 13 11 13 9 7 $ $ $$ $$ $$$ $$ $$ $$ $ MAV 2009 2017 $ $ 13 9 11 10 13 97 109 9 $$ $ $ $ $ $ $ $ $ $ MYA 2016 8 6 8 5 9 $ $ $ $$ Unit: %Poorest Second Middle Fourth Richest Unit: %Poorest Second Middle Fourth Richest BAN 2014 $ $$ $ 49 42 36 31 19 2018 $ $$ $ 40 37 30 27 17 2019 $$ $$ $ 38 31 26 24 20 $ $ $ $$ $ $ $$ $ $$ $$ $$ $ $ $ $ $$$$ $$ $ $$ $ $$ $ $ $ $ $$ $ TLS 2020 $ $$ $ $ 7 7 8 8 9 2013 $ $$ 11 11 9 9 13 $ $ $$ $ 16 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ BAN 2014 17 17 13 13 12 2018 10 8 8 9 7 2019 30 27 22 20 14 $ $ $ $ $ $ $ $ $ $ $ $ $ $ BHU 2010 16 16 14 10 7 2015 15 9 7 8 6 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ SRL 2006 29 25 22 18 11 2016 28 25 21 16 13 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ NEP 2016 33 28 33 24 12 2019 32 27 27 22 11 2011 40 32 29 23 10 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ MAV 2009 2017 24 1719 1519 1313 1611 12 $ $ $ $ $ $ $ $ $ $ $ MYA 2016 25 19 18 16 12 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ THA 2012 14 10 10 7 4 2016 10 7 6 5 5 2019 11 8 8 6 5 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ 2021 43 36 30 25 20 2006 57 49 41 34 20 2016 49 40 33 27 20 IND Underweight The total fertility rate has marginally decreased over time, with women from urban areas, those with better education and those from the richest households having fewer children on average than other women Total fertility rate by location of residence51 IND 2006 2016 2021 2.1 3.0 1.8 2.4 1.6 2.1 BAN 2014 2018 2019 2.0 2.4 2.0 2.3 2.0 2.3 MYA 2016 1.9 2.4 INO 2007 2012 2017 2.3 2.8 2.4 2.8 2.3 2.6 MAV 2009 2017 2.1 2.8 1.8 2.5 BHU 2010 2017 2.3 2.8 2.0 1.9 THA 2012 2016 2019 1.5 2.1 1.3 1.7 1.1 1.9 NEP 2011 2016 2019 1.6 2.8 2.0 2.9 1.9 2.4 TLS 2010 2016 4.9 6.0 3.5 4.6 SRL 2006 2.2 2.3 Unit: Average number of births per woman Unit: Average number of births per woman Total fertility rate by level of education52 Urban Rural No education Unit: %Poorest Second Middle Fourth Richest Secondary HigherNo education Primary BAN 2014 2.4 2.4 2.4 1.9 2018 2.6 2.5 2.3 2.1 2019 2.5 2.6 2.3 2.0 BHU 2010 2.9 2.5 3.0 IND 20162006 3.6 2.6 2.2 1.6 3.1 2.5 2.1 1.6 2021 2.8 2.3 2.0 1.7 INO 2007 2.4 2.8 2.6 2.7 2012 2.8 2.9 2.7 2.4 2017 2.7 2.9 2.5 2.3 NEP 2011 3.7 2.7 1.9 1.7 2016 3.3 2.7 2.1 1.8 2019 3.2 2.3 1.8 MAV 2009 2.8 2.7 2.6 2.7 2017 1.6 2.4 2.3 1.9 MYA 2016 3.6 2.6 2.0 1.5 THA 2012 1.1 2.9 2.1 1.2 2016 2.1 1.7 1.7 1.1 2019 1.5 2.4 1.6 1.2 SRL 2006 1.9 2.8 2.6 2.3 2016 1.6 2.3 2.4 2.0 TLS 2010 6.1 6.5 5.2 2.9 2016 4.8 4.7 4.3 3.3 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ TLS 2020 37 33 34 30 27 2013 44 43 37 35 32 17 Unit: Average number of births per woman Total fertility rate by household income quintile53 INO 2007 $ $ $ $ $ $ $ $ $ $ $ 3 2.5 2.8 2.5 2.7 2012 $ $ $ $ $ $ $ $ $ $ $ 3.2 2.7 2.5 2.4 2.2 2017 $ $ $ $ $ $ $ $ $ $ 2.9 2.6 2.3 2.3 2.1 $ $ $ $ $ $ $ $ $ $ $ $ $ $ MAV 2009 $ $ $ $ $ $ $ $ $ $ 2.8 2.9 2.7 2.4 2.1 2017 $ $ $ $ $ $ $ $ 2.5 2.6 2.3 1.9 1.7$ $ $ $ $ $ $ $ $ $ SRL 2006 $ $ $ $ $ $ $ $ $ $ 2.4 2.3 2.2 2.3 2.4 2016 $ $ $ $ $ $ $ $ $ 2.2 2.1 2 1.9 2.3 $ $ $ $ $ $ $ $ $ MYA 2016 $ $ $ $ $ $ $ $ $ 3.5 2.5 2.1 1.9 1.6 $ $ $ $ $ BHU 2010 $ $ $ $ $ $ $ $ $ $ $ $ 3.1 2.8 3 2.4 2 $ $ $ IND 2006 $ $ $ $ $ $ $ $ $ $ $ 3.9 3.2 2.6 2.2 1.8 2016 $ $ $ $ $ $ $ $ $ $ 3.2 2.5 2.1 1.8 1.5 2021 $ $ $ $ $ $ $ 2.6 2.1 1.9 1.7 1.6 $ $ $ $ $ $ $ $ $ $ $ $ $ $ BAN 2014 $ $ $ $ $ $ $ $ $ $ 2.8 2.4 2.2 2.1 2 2018 $ $ $ $ $ $ $ $ $ $ 2.6 2.5 2.1 2.1 2 2019 $ $ $ $ $ $ $ $ $ $ 2.8 2.4 2.1 2.1 2.1 $ $ $ $ $ $ $ $ $ $ $ $ $ THA 2012 $ $ $ $ $ $ $ $ 2.2 2.2 2.1 1.7 1.3 2016 $ $ $ $ $ 1.5 1.8 1.3 1.8 1.1 2019 $ $ $ $ $ $ 2.1 1.5 1.3 1.5 1.1$ $ $ $ $ $ $ $ $ $ $ $$ $$ NEP 2011 $ $ $ $ $ $ $ $ $ $ $ 4.1 3.1 2.7 2.1 1.5 2016 $ $ $ $ $ $ $ $ $ $ 3.2 2.5 2.5 2.1 1.6 2019 $ $ $ $ $ $ $ $ 2.9 2.3 2.1 1.8 1.4 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ TLS 2010 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ 7.3 6 6.1 5.3 4.2 2016 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ 5.2 4.7 4.3 3.9 3.4 $ $ $ $ $ $ $ $ $$ Fertility rates have declined more rapidly among adolescent women than among adult women, although inequities by location of residence, education and income persist across the Region Adolescent fertility rate, WHO SE Asia Region54 and countries55 Adolescent fertility rate by location of residence56 Unit: Per thousand women aged 15–19 years Unit: Per thousand women aged 15–19 years Poorest Second Middle Fourth Richest Urban Rural 2010 BHU 59 113 108 83 2014 2018 2019 BAN 150 100 50 0 2016 MYA 36 150 100 50 0 2009 2017 MAV 10 10 2010 2016 TLS 51 42 2006 2016 2021 IND 90 51 43 2011 2016 2019 NEP 81 88 63 2007 2012 2017 INO 51 48 36 2012 2016 2019 THA 60 51 23 2006 2016 SRL 28 21 2000–2005 2010–20152005–2010 2015–2020 70 60 50 40 30 20 61.5 49.6 37.6 26.1 WHO SE Asia Region 2014 BAN 98 120 2018 93 114 2019 70 87 BHU 2018 30 77 MAV 6 12 20172009 4 17 MYA 2016 36 37 IND 57 105 2016 35 59 2021 27 49 2006 INO 26 74 2012 32 70 2017 24 51 2007 NEP 42 87 20162011 66 125 2019 58 74 SRL 2006 24 28 TLS 35 57 20162010 19 55 THA 55 63 2016 44 56 2019 13 33 2012 18 Adolescent fertility rate by level of education57 Unit: Per thousand women aged 15–19 years Adolescent fertility rate by household income quintile58 NEP 2011 2016 2019 $ $ $ 31 $ $ $ $ $ 57 $ $ $ $ $ $ $ 73 $ $ $ $ $ $ $ 71 $ $ $ $ $ $ $ $ 83 $ $ $ 38 $ $ $ $ $ $ $ $ 84 $ $ $ $ $ $ $ $ $ $ 105 $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ $ $ 110 $ $ $ 32 $ $ $ $ $ $ $ 72 $ $ $ $ $ $ $ $ $ 95 $ $ $ $ $ $ $ $ $ $ $ 105 $ $ $ $ $ $ $ $ $ $ $ 103 $ $ $ $ $ $ $ $ $ $ $ THA 2012 2016 2019 4 $ 15 $ $ $ 32 $ $ 23 $ $ $ $ 49 $ $ $ $ $ 59 $ $ 16 $ $ $ $ $ $ 67 $ $ $ $ $ $ $ 74 $ $ $ $ $ $ $ $ 85 $ $ $ $ 43 $ $ $ 35 $ $ $ $ $ $ $ $ 82 $ $ $ $ $ $ $ 76 $ 12 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ TLS 20162010 $ $ $ $ $ $ 60 $ $ $ $ $ 51 $ $ $ $ $ $ $ 74 $ $ $ $ 48 $ $ $ 30 $ $ $ $ $ $ $ 73 $ $ $ $ $ $ 68 $ $ $ $ 46 $ $ 26 $ 19 $ $ $ $ $ $ $ $ INO 2007 $ $ $ $ 49 $ $ $ $ $ 50 $ $ $ $ $ $ $ 71 $ $ $ $ $ $ 63 $ $ $ $ $ 52 2012 $ $ $ $ $ $ $ $ $ 93 $ $ $ $ $ $ $ 72 $ $ $ $ 45 $ $ $ 35 $ 13 2017 $ $ $ $ $ $ $ 73 $ $ $ $ $ 50 $ $ $ 38 $ 17 $ 10 $ $ $ $ $ $ $ $ $ $ $ $ MAV 2009 $ 11 $ 12 $ 13 6 8 2017 $ $ 29 $ 10 7 $ 9$ $ $ $ $ $ $ MYA 2016 $ $ $ $ $ $ $ 70 $ $ $ 38 $ $ 24 $ $ $ 33 $ $ 22$ $ $ $ BHU 2010 $ $ $ $ $ $ $ $ $ $ $ 112 $ $ $ $ $ $ $ $ $ 95 $ $ $ $ $ $ $ $ $ 97 $ $ $ 36 $ 10 $ $ $ $ IND 2006 $ $ $ $ $ $ $ $ $ $ $ $ $ 134 $ $ $ $ $ $ $ $ $ $ $ $ 122 $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ 72 $ $ $ 33 2016 $ $ $ $ $ $ $ 72 $ $ $ $ $ $ 65 $ $ $ $ $ 56 $ $ $ $ 41 $ 19 2021 $ $ $ $ $ $ 63 $ $ $ $ $ 51 $ $ $ $ 45 $ $ $ 32 17 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ BAN 2014 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ 146 $ $ $ $ $ $ $ $ $ $ $ $ 119 $ $ $ $ $ $ $ $ $ $ $ 117 $ $ $ $ $ $ $ $ $ $ 102 $ $ $ $ $ $ $ $ $ 96 2018 $ $ $ $ $ $ $ $ $ $ $ $ $ $ 140 $ $ $ $ $ $ $ $ $ $ $ $ 127 $ $ $ $ $ $ $ $ $ $ 101 $ $ $ $ $ $ $ $ $ $ 104 $ $ $ $ $ $ $ 76 2019 $ $ $ $ $ $ $ $ $ $ 102 $ $ $ $ $ $ $ $ $ 96 $ $ $ $ $ $ $ 77 $ $ $ $ $ $ $ $ 80 $ $ $ $ $ $ 66 $ $ $ $ $ $ $ $ $ $ $ Poorest Second Middle Fourth Richest No education SecondaryPrimary Higher IND 2006 163 112 60 8 2016 114 92 47 10 2021 109 85 42 9 113 70 29 BHU 2010 BAN 2014 112 153 124 42 2018 196 163 111 58 2019 112 127 95 41 MAV 2009 33 9 2017 11 3 90 60 21 11 MYA 2016 INO 2007 86 98 35 32 2012 91 125 42 5 2017 130 35 3 NEP 2011 176 130 55 14 2016 178 148 82 28 2019 166 111 47 11 TLS 2009 2016 8791 35 10 100 35 74 THA 2012 2016 24 104 55 3 2019 59 7 224 12 4 130 Unit: Per thousand women aged 15–19 years 19 Do gender, location of residence, education and income affect the exposure to health risks and vulnerabilities in WHO SE Asia Region? Biological and gender-related factors interact to result in differences between men and women in WHO SE Asia Region in their exposure to health risks and vulnerabilities. Besides gender, location of residence (urban/rural), education and income also affect exposure to health risks and vulnerabilities Overweight among adults, WHO SE Asia Region61 and countries62 The higher prevalence of overweight and obesity among women than men and the lower prevalence of physical activity among women than men likely reflect gender differences in mobility, physical access to recreational facilities and perception of safety from crime and traffic. Thus, gender norms, roles and activities may provide the basis for higher exposure to the risk of noncommunicable diseases Unit: % Across the Region, mothers’ chances of dying during and after childbirth have reduced to less than half since 2000. Eight countries are on track to achieve the Sustainable Development Goal on maternal mortality, but significant challenges remain in the others Maternal mortality ratio, WHO SE Asia Region59 and countries60 Unit: Per thousand live birthsWHO SE Asia Region 2015 2016 2017 300 250 200 150 100 50 0 BAN BHU IND INO MAV MYA THASRLNEP TLS 200 186 173 203 193 183 158 150 145 184 177 54 53 54 246 250 236 186 36 3836 36 37 152 160 142 37 245 192 165 157 152 200 WomenMen INO 2003 27.0 31.0 2006 20.3 36.1 NEP 2007 7.3 7.1 2013 18.0 17.3 2019 20.2 19.8 SRL 2006 15.9 24.6 2015 21.0 25.9 THA 2014 22.5 24.6 2015 23.2 25.1 2016 23.9 25.6 TLS 2014 7.5 15.4 MAV 2004 31.9 34.3 2011 23.5 27.8 MYA 2009 13.5 22.0 2014 11.5 22.4 BAN 2010 11.1 17.0 2013 19.6 21.0 2018 16.0 25.6 BHU 2014 2019 22.8 31.9 31.7 35.5 IND 2004 2018 16.3 19.9 19.0 21.0 WHO SE Asia Region 2005 12.0 14.4 2016 15.917.7 2010 16.013.8 2000 12.9 10.2 20 Obesity among adults, WHO SE Asia Region63 and countries64 Physical activity among adults, WHO SE Asia Region65 and countries66 Unit: % Men Low physical activity Men Moderate physical activity Men Vigorous physical activity Women Low physical activity Women Moderate physical activity Women Vigorous physical activity Men Insufficient physical activity Women Insufficient physical activity Total Insufficient physical activity Unit: % WomenMen BAN 2010 41.3 25.0 33.7 10.5 14.6 74.9 SRL 2015 44.2 23.6 32.2 28.1 18.2 53.7 MAV 2011 39.1 14.8 46.1 52.4 26.1 21.5 TLS 2014 26.2 9.6 64.2 36.3 42.9 20.8 BAN 2010 2013 2018 2.2 4.9 4.1 6.0 2.3 8.6 BHU 2014 2019 4.5 8.5 8.4 14.9 IND 2004 2018 3.0 6.8 4.3 8.3 INO 2003 2006 6.7 9.1 1.9 2.8 2000 1.1 2.7 2005 1.5 3.6 2010 2.2 4.6 2016 3.3 6.1 WHO SE Asia Region NEP 2007 2013 2019 1.1 2.4 3.1 4.8 3.2 5.3 SRL 2006 2015 3.6 5.9 3.5 8.4 THA 2014 2015 2016 6.0 11.5 6.5 12.1 7.0 12.7 TLS 2014 0.7 1.3 MAV 2004 2011 8.7 17.6 8.6 14.5 MYA 2009 2014 4.3 8.4 2.6 8.4 22.9 38.3 30.5WHO SE Asia Region 2016 MYA 2014 21.1 20.6 58.2 14.3 13.8 72.0 BHU 2014 7.7 9.0 83.2 16.6 12.4 70.9 NEP 2013 4.5 2.4 11.9 83.6 11.3 86.3 INO 2006 28.7 14.3 21 Age-standardized tobacco use among adults67 Men predominate among consumers of tobacco and alcohol across countries in the Region, likely reflecting the influence of harmful male gender norms Unit: %Men Women Alcohol consumption among adults68 Unit: % Unit: % Overweight among adolescents69 Boys Girls Men Women BAN 2019 37.1 0.6 2020 36.4 0.6 MYA 2019 38.1 3.8 2020 37.2 3.5 BHU 2014 10.8 3.1 2019 15.2 3.7 NEP 2019 29.0 7.0 2020 28.5 6.4 IND 2019 15.6 1.6 2020 14.6 1.4 SRL 2019 25.1 0.2 2020 24.6 0.2 INO 2019 62.0 2.6 2020 61.9 2.5 THA 2019 37.8 1.6 2020 37.2 1.6 MAV 2019 45.3 3.1 2020 44.4 2.9 TLS 2019 59.7 5.2 2020 59.1 5.1 BAN 2014 9.6 6.8 BHU 2016 7.9 14.5 IND 2007 11.6 9.7 INO 2015 15.1 14.5 MAV 2014 17.8 13.7 MYA 2016 7.2 8.0 NEP 2015 7.0 5.3 SRL 2008 4.8 4.2 THA 2021 22.0 16.1 TLS 2015 3.9 4.9 TLS 2014 42.8 2.0 MAV 2011 1.6 0.2 BAN 2010 2018 0.01.5 0.1 2.9 MYA 2009 2014 31.2 1.5 38.1 1.5 BHU 2014 2019 50.0 32.8 50.1 34.9 IND 2006 2016 2021 31.9 2.2 29.2 1.2 19.9 1.3 NEP 2007 2013 2019 39.3 16.5 28.0 7.1 34.4 8.8 SRL 2006 2015 26.0 1.2 34.8 0.5 INO 2003 2006 0.0 6.0 0.3 2.9 22 Unit: % Obesity among adolescents70 Physical activity among adolescents71 As is the case in adults, the typically lower prevalence of physical activity among girls than boys may reflect the role of gender difference in mobility, access to recreational spaces and perceptions of safety from crime and traffic, contributing to a correspondingly higher risk of noncommunicable diseases Unit: % As for adults, boys predominate among adolescent users of tobacco, alcohol and marijuana, reflecting the influence of harmful male gender norms Alcohol consumption among adolescents72 Prevalence of tobacco use among adolescents73 Unit: % Unit: % Boys Girls Boys Girls Boys Girls Boys Girls BAN 2014 0.8 1.6 BHU 2016 1.9 2.1 IND 2007 2.5 1.5 INO 2015 5.4 3.8 MAV 2014 5.5 4.3 MYA 2016 2.3 1.6 NEP 2015 0.8 0.5 SRL 2008 0.4 0.6 THA 2021 8.7 4.7 TLS 2015 0.7 0.9 BAN 2014 42 40.2 BHU 2016 15.8 13.2 IND 2007 31 29.1 INO 2015 13.4 12.3 MAV 2009 23.5 17.4 MYA 2016 12.8 8.2 NEP 2015 17.4 13.4 SRL 2016 19.3 11.7 THA 2021 16.5 5.1 TLS 2015 14.5 5.3 BAN 2014 0.12.4 BHU 2016 33.4 16.1 INO 2015 7.2 1.6 MAV 2009 9.1 4.2 MYA 2016 8.3 1.4 NEP 2015 6.7 3.6 SRL 2016 5.5 1.0 THA 2021 27.2 29.2 TLS 2015 21.5 9.3 BAN 2007 9.1 5.1 2013 9.2 2.8 2014 13.2 2.1 BHU 2009 27.6 11.6 2013 39.0 23.2 2019 31.2 13.5 IND 2006 16.8 9.4 2009 19.0 8.3 2019 9.6 7.4 INO 2009 41.0 3.5 2014 36.2 4.3 2019 35.6 3.5 MAV 2007 8.5 3.4 2011 15.2 6.7 2019 48.0 43.2 MYA 2007 22.5 8.2 2011 30.0 6.8 2016 26.3 3.7 NEP 2007 13.0 5.3 2011 24.6 16.4 2015 9.5 4.8 SRL 2007 12.4 5.8 2011 15.7 5.4 2016 13.0 3.1 THA 2009 26.9 9.2 2015 21.8 8.1 2021 19.6 9.7 TLS 2009 39.7 23.8 2013 65.5 23.9 2019 42.0 20.9 23 Comprehensive knowledge about HIV/AIDS among adolescent girls has improved slightly, but still ranges from fewer than one to five in every ten adolescent girls across countries in the Region Violence against women and girls is a violation of their human rights. Its significant negative health consequences make it a priority public health issue too. More than one in every three women in the Region have experienced intimate partner violence (IPV) at least once in their lifetime Ever use of marijuana among adolescents74 Comprehensive knowledge of HIV/AIDS among adolescent girls75 Unit: % 10.6 BAN 2019 21.9 BHU 2010 17.9 IND 2021 12.4 INO 2017 26.9 MAV 2017 13.4 MYA 2016 26.1 NEP 2019 16.4 SRL 2016 49.2 THA 2019 5.9 TLS 2017 Unit: % Unit: % 50BAN 22BHU 35IND 22INO 19MAV 19MYA 24SRL 24THA Boys Girls 27NEP 38TLS Lifetime prevalence of intimate partner violence among women, WHO SE Asia Region76 and countries77 (2018) 33 WHO SE Asia Region BAN 2014 2.1 0.4 BHU 2016 28.3 5.3 INO 2015 2.2 0.6 NEP 2015 5.0 2.5 SRL 2016 4.6 0.8 THA 2021 11.2 3.1 MAV 2014 6.7 1.7 TLS 2015 6.0 3.8 24 Between one to five of every ten ever-partnered women have faced IPV in countries across the Region, with rural and uneducated women and those from the poorest households facing a significantly higher risk Intimate partner violence among ever-partnered women by location of residence78 Intimate partner violence among ever-partnered women by level of education79 Intimate partner violence among ever-partnered women by household income quintile80 Unit: % Unit: % Unit: % BAN 2007 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ 39 $ 59 $ 49 $ 59 $ 62 $ BHU 2017 $$ $$ $ 18 $ 16 $ 14 $ 15 $ 13 $ MAV 2016–2017 $$$ $ 12 $ 12 $ 8 $ 15 $ 15 $ MYA 2015–2016 $$ $$ $ $ 10 16 $ 12 $ 23 $ 19 $ SRL 2016 $$ $$ $ $ 12 $ 14 $ 13 $ 28 $ 18 $ TLS 2016 $ $ 26 $ $ $ $ 39 $ $ $ $ 33 $ $ $ $ $ 45 $ $ $ $ $ 48 $ NEP 2016 $$ $ $ $ $ $ $ $ 17 $ $ 30 25 $ 23 $ 27 $ IND 2019–2021 $$ $ $ $ $ $ $ $ $ $ $ 30 17 $ 24 $ 35 $ 38 $ Women and girls are exposed to household smoke from fuels while performing their assigned gender role of cooking. The proportion of the population across countries in the Region using clean fuel for cooking has significantly improved in the past decade. However, the share of households still using unclean fuel for cooking remains unacceptably high in many countries Unit: % Population using clean fuel for cooking, WHO SE Asia Region81 Households using clean fuel for cooking, countries82 2011 2014 2018 13.3 17.2 20.1 BAN 2018 2019 2020 78.3 79.4 80.2 BHU* 2006 2016 2021 25.5 43.8 58.6 IND 2007 2012 2017 11.0 52.3 72.3 INO WHO SE Asia Region 2009 2017 92.1 97.9 MAV 2016 22.9 MYA 2011 2016 2019 23.6 33.9 43.2 NEP 2006 2016 16.9 30.7 SRL 2019 77.9 THA 2010 2016 2.6 9.1 TLS Urban Rural Poorest Second Middle Fourth Richest No education SecondaryPrimary Higher BAN 2007 48 55 MYA 2015–2016 14 17 BHU 2017 15 15 NEP 2016 23 26 IND 2019–2021 25 31 SRL 2016 20 16 MAV 2016–2017 12 13 TLS 2016 29 42 BAN 2007 62 58 44 27 BHU 2017 16 17 12 17 IND 2019–2021 38 33 26 15 MAV 2016–2017 13 13 13 10 MYA 2015–2016 18 18 16 8 NEP 2016 32 26 16 12 SRL 2016 25 30 18 13 TLS 2016 46 43 34 23 2000 19.3 2005 25.2 2010 34.4 2015 47.6 2020 64.5 *Population 25 DTP3 vaccination rate by sex83 DTP3 vaccination rate by location of residence84 DTP3 vaccination rate by mother’s education85 Unit: % Unit: % Geographical, financial, sociocultural or other barriers may compound gender-related barriers to access to services. Women in WHO SE Asia Region report facing gender-related barriers such as lack of availability of a woman health provider, lack of access to household resources such as money, longer distances to the health facility, issues of transport and weak decision-making abilities Do gender, location of residence, education and income affect access to health services in WHO SE Asia Region? NEP 2011 92 91 2016 86 86 2019 82 81 SRL 2006 99 100 2016 97 95 2011 95 92 2014 90 92 2018 96 96 BAN IND 2006 57 53 2016 78 79 2021 87 86 INO 2007 66 68 2012 73 71 2017 76 78 MAV 2009 98 98 2017 85 85 MYA 2016 64 61 THA 2012 91 89 2016 90 88 2019 90 90 TLS 2010 69 64 2016 61 63 Unit: % Children from urban areas have a higher DTP vaccination rate than their rural counterparts, with a percentage difference as high as 17 points for some countries BAN 2011 2014 2018 94 93 94 90 95 96 IND 2006 2016 2021 69 50 80 78 86 87 INO 2007 2012 2017 75 61 77 67 80 74 MAV 2009 2017 98 98 87 84 MYA 2016 75 58 NEP 2011 2016 2019 95 91 86 86 80 84 THA 2012 2016 2019 88 91 90 88 86 92 SRL 2006 2016 99 100 92 97 TLS 2010 2016 71 65 66 60 Children of mothers with the highest levels of education have a higher rate of DTP vaccination than children of uneducated mothers and the difference ranges from four to 40 percentage points across countries in the Region Urban Rural No education SecondaryPrimary Higher Men Women BAN 2011 85 92 96 100 2014 80 88 95 98 2018 93 94 97 99 IND 2006 37 58 75 89 2016 68 78 83 87 2021 81 85 88 89 INO 2007 2012 2017 28 55 74 86 26 62 76 86 57 66 80 82 MAV 2009 2017 98 99 97100 84 84 88 MYA 2016 44 60 68 84 NEP 2011 2016 2019 86 95 97 100 80 85 88 96 69 83 87 85 SRL 2006 2016 89 98 100100 99 97 93 20192012 88 94 90 84 THA 2016 80 86 93 87 81 92 89 90 TLS 2010 2016 57 66 74 87 51 62 64 75 26 Antenatal care coverage by location of residence87 Although the proportion of women receiving antenatal care from a skilled provider has improved over time, inequities exist by their location of residence, educational level and household income Unit: % DTP3 vaccination rate by household income quintile86 BAN 2011 2014 2018 $ $ $ $ $ $ $ $ $ 90 $ $ $ $ $ $ $ $ $ 90 $ $ $ $ $ $ $ $ $ $ 93 $ $ $ $ $ $ $ $ $ $ 96 $ $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ 81 $ $ $ $ $ $ $ $ $ $ 93 $ $ $ $ $ $ $ $ $ $ 93 $ $ $ $ $ $ $ $ $ $ 94 $ $ $ $ $ $ $ $ $ $ 97 $ $ $ $ $ $ $ $ $ $ 95 $ $ $ $ $ $ $ $ $ $ 96 $ $ $ $ $ $ $ $ $ $ 96 $ $ $ $ $ $ $ $ $ $ 95 $ $ $ $ $ $ $ $ $ $ 98 $$ $ THA 2012 2016 2019 $ $ $ $ $ $ $ $ $ $ 93 $ $ $ $ $ $ $ $ $ $ 92 $ $ $ $ $ $ $ $ $ 89 $ $ $ $ $ $ $ $ $ $ 91 $ $ $ $ $ $ $ $ $ 85 $ $ $ $ $ $ $ $ $ 90 $ $ $ $ $ $ $ $ $ 87 $ $ $ $ $ $ $ $ $ 88 $ $ $ $ $ $ $ $ $ $ 94 $ $ $ $ $ $ $ $ $ 87 $ $ $ $ $ $ $ $ $ $ 92 $ $ $ $ $ $ $ $ $ $ 92 $ $ $ $ $ $ $ $ $ 89 $ $ $ $ $ $ $ $ $ 90 $ $ $ $ $ $ $ $ $ 86 $ $$ $ $ $$ $ $ TLS 2010 2016 $ $ $ $ $ $ 55 $ $ $ $ $ $ $ 63 $ $ $ $ $ $ $ 68 $ $ $ $ $ $ $ $ 76 $ $ $ $ $ $ $ $ 73 $ $ $ $ $ 48 $ $ $ $ $ $ 58 $ $ $ $ $ $ 60 $ $ $ $ $ $ $ 69 $ $ $ $ $ $ $ $ 72 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ SRL 2006 2016 $ $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ $ 96 $ $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ $ 97 $ $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ $ 92 MYA 2016 $ $ $ $ $ 49 $ $ $ $ $ 49 $ $ $ $ $ $ $ 67 $ $ $ $ $ $ $ $ 74 $ $ $ $ $ $ $ $ $ 84 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ MAV 2009 2017 $ $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 97 $ $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ $ 97 $ $ $ $ $ $ $ $ $ 83 $ $ $ $ $ $ $ $ $ 86 $ $ $ $ $ $ $ $ $ 85 $ $ $ $ $ $ $ $ $ $ 91 $ $ $ $ $ $ $ $ 80 $ $ $ $ $ NEP 2011 2016 2019 $ $ $ $ $ $ $ $ $ 88 $ $ $ $ $ $ $ $ $ 90 $ $ $ $ $ $ $ $ $ $ 91 $ $ $ $ $ $ $ $ $ $ 97 $ $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ 87 $ $ $ $ $ $ $ $ $ 85 $ $ $ $ $ $ $ $ $ 81 $ $ $ $ $ $ $ $ $ 90 $ $ $ $ $ $ $ $ $ 90 $ $ $ $ $ $ $ $ $ 83 $ $ $ $ $ $ $ $ 77 $ $ $ $ $ $ $ $ $ 81 $ $ $ $ $ $ $ $ $ 81 $ $ $ $ $ $ $ $ $ 86 $ $ $$ $ $ $$ $$ $$ $ IND 2006 2016 2021 $ $ $ 34 $ $ $ $ 47 $ $ $ $ $ 58 $ $ $ $ $ $ 69 $ $ $ $ $ $ $ $ 82 $ $ $ $ $ $ $ 70 $ $ $ $ $ $ $ $ 77 $ $ $ $ $ $ $ $ $ 81 $ $ $ $ $ $ $ $ $ 83 $ $ $ $ $ $ $ $ $ 85 $ $ $ $ $ $ $ $ $ 83 $ $ $ $ $ $ $ $ $ 86 $ $ $ $ $ $ $ $ $ 89 $ $ $ $ $ $ $ $ $ 88 $ $ $ $ $ $ $ $ $ 89 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $$ $ $ INO 2007 2012 2017 $ $ $ $ $ 45 $ $ $ $ $ $ 63 $ $ $ $ $ $ $ 67 $ $ $ $ $ $ $ $ 78 $ $ $ $ $ $ $ $ $ 81 $ $ $ $ $ $ 52 $ $ $ $ $ $ $ 69 $ $ $ $ $ $ $ $ 75 $ $ $ $ $ $ $ $ 80 $ $ $ $ $ $ $ $ $ 85 $ $ $ $ $ $ $ 67 $ $ $ $ $ $ $ $ 73 $ $ $ $ $ $ $ $ 80 $ $ $ $ $ $ $ $ $ 82 $ $ $ $ $ $ $ $ $ 82 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $$ $ $ Unit: % Urban Rural Poorest Second Middle Fourth Richest BAN 2014 2018 2019 79 59 90 79 87 72 MAV 2009 2017 100 99 99 99 BHU 2010 2015 99 97 100 97 IND 2006 2016 2021 89 67 89 75 92 83 INO 2007 2012 2017 98 90 98 93 99 97 MYA 2016 94 77 SRL 2006 2016 100 99 99 99 NEP 2011 2016 2019 88 55 87 80 91 85 THA 2012 2016 2019 98 98 98 99 99 99 TLS 2010 2016 93 84 92 81 27 Uneducated women have a lower antenatal care coverage rate than their highly educated counterparts, with a gap of more than 40 percentage points in some countries Antenatal care coverage by level of education88 Antenatal care coverage by household income quintile89 Unit: % Unit: % $ $ $ $ $ $ $ $$ $ $ TLS 2010 2016 $ $ $ $ $ $ $ $ $ $ 97 $ $ $ $ $ $ $ $ $ 88 $ $ $ $ $ $ $ $ $ 93 $ $ $ $ $ $ $ $ $ 79 $ $ $ $ $ $ $ $ 74 $ $ $ $ $ $ $ $ $ $ 95 $ $ $ $ $ $ $ $ $ 83 $ $ $ $ $ $ $ $ $ 90 $ $ $ $ $ $ $ $ 79 $ $ $ $ $ $ $ $ 74 THA 2012 2016 2019 $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ $ 97 $ $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ $ 96 $ $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 96 $ SRL 2006 2016 $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 98 $ $ $ INO 2007 2012 2017 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ 96 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 92 $ $ $ $ $ $ $ $ $ $ 82 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 96 $ $ $ $ $ $ $ $ $ $ 87 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ $ 92 $ $ $ $ $ $ $ $ MYA 2016 $ $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ 84 $ $ $ $ $ $ $ $ $ 90 $ $ $ $ $ $ $ $ 75 $ $ $ $ $ $ $ 67 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ NEP 2011 2016 2019 $ $ $ $ $ $ $ $ $ $ 92 $ $ $ $ $ $ 58 $ $ $ $ $ $ $ $ 78 $ $ $ $ $ 45 $ $ $ $ 33 $ $ $ $ $ $ $ $ $ $ 96 $ $ $ $ $ $ $ $ $ 83 $ $ $ $ $ $ $ $ $ 88 $ $ $ $ $ $ $ $ 80 $ $ $ $ $ $ $ $ 74 $ $ $ $ $ $ $ $ $ $ 97 $ $ $ $ $ $ $ $ $ 91 $ $ $ $ $ $ $ $ $ $ 93 $ $ $ $ $ $ $ $ $ $ 85 $ $ $ $ $ $ $ $ $ 81 MAV 2009 2017 $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 98 $ BHU 2010 2015 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 95 $ $ $ $ $ $ $ $ $ $ 96 $ $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 94 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ BAN 2014 $ $ $ $ $ $ $ $ $ 90 $ $ $ $ $ $ $ 65 $ $ $ $ $ $ $ $ 75 $ $ $ $ $ $ 56 $ $ $ $ 36 2018 $ $ $ $ $ $ $ $ $ $ 97 $ $ $ $ $ $ $ $ $ 84 $ $ $ $ $ $ $ $ $ 92 $ $ $ $ $ $ $ $ $ 74 $ $ $ $ $ $ $ 64 2019 $ $ $ $ $ $ $ $ $ $ 95 $ $ $ $ $ $ $ $ 78 $ $ $ $ $ $ $ $ $ 87 $ $ $ $ $ $ $ 67 $ $ $ $ $ 50 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $$ $ IND 2006 2016 2021 $ $ $ $ $ $ $ $ $ $ 96 $ $ $ $ $ $ $ $ 76 $ $ $ $ $ $ $ $ $ 88 $ $ $ $ $ $ $ 65 $ $ $ $ $ $ 52 $ $ $ $ $ $ $ $ $ $ 94 $ $ $ $ $ $ $ $ $ 86 $ $ $ $ $ $ $ $ $ 90 $ $ $ $ $ $ $ $ 76 $ $ $ $ $ $ 57 $ $ $ $ $ $ $ $ $ $ 94 $ $ $ $ $ $ $ $ $ 89 $ $ $ $ $ $ $ $ $ 92 $ $ $ $ $ $ $ $ $ $ 83 $ $ $ $ $ $ $ $ 72 No education SecondaryPrimary Higher Poorest Second Middle Fourth Richest BHU 2010 97 99 99 INO 2007 2012 2017 63 90 98 100 64 93 98 99 70 95 99 99 IND 2006 2016 2021 57 78 90 98 61 77 87 94 73 81 88 93 BAN 2018 60 74 96 2019 47 63 80 93 2014 39 55 89 MAV 2009 97 99 100100 2017 95 99 99 99 SRL 2006 2016 98 99 100 100 96 98 99 98 MYA 2016 56 80 90100 NEP 2011 2016 2019 42 56 76 94 73 83 88 96 78 89 92 99 TLS 2010 2016 76 86 93100 72 84 89 93 THA 2012 2016 2019 92 97 99 99 86 97 99 100 97 97 99 99 28 Despite a significant increase in skilled attendance at delivery over time in the Region, women from rural areas, those with lower education and those from poor households have lower rates of deliveries assisted by a skilled provider Skilled birth attendance, WHO SE Asia Region90 and countries91 Skilled birth attendance by location of residence92 Unit: % Unit: % Skilled birth attendance by level of education93 Unit: % Urban Rural No education SecondaryPrimary Higher 42 53 59 2014 2018 2019 BAN 100 75 50 25 0 48 77 87 2001–2007 2008–2014 2015–2021 WHO SE Asia Region 100 75 50 25 0 95 100 2009 2017 MAV 100 75 50 25 0 60 2016 MYA 36 58 77 2011 2016 2019 NEP 100 99 99 2012 2016 2019 THA 65 2010 BHU 46 81 89 2006 2016 2021 IND 73 83 91 2007 2012 2017 INO 30 57 2010 2016 TLS 99 100 2006 2016 SRL 73 32 68 47 83 66 NEP 2011 2016 2019 99 99 100 100 SRL 2006 2016 100 100 99 100 99 99 THA 2012 2016 2019 59 21 86 45 TLS 2010 2016 61 36 68 47 74 55 BAN 2014 2018 2019 73 36 90 78 94 88 IND 2006 2016 2021 90 54 BHU 2010 88 63 92 75 96 86 INO 2007 2012 2017 99 93 99 100 MAV 2009 2017 88 52 MYA 2016 BAN 2014 17 30 49 79 2018 2934 57 81 2019 30 41 63 85 INO 2007 31 57 86 98 2012 32 70 9097 2017 46 80 9598 IND 2006 25 45 71 96 2016 66 77 8996 BHU 2010 5462 94 MAV 2009 85 92 99 99 2017 100 100 99100 TLS 2010 14 23 47 88 2016 33 45 67 95 SRL 2006 949799 99 2016 100 100 100 100 NEP 2011 19 32 59 84 2016 38 50 72 89 2019 53 75 87 98 MYA 2016 28 56 9 95 THA 2012 97 99 2016 92 99 2019 99 98100100 100 100 100 100 29 Met need with modern methods, WHO SE Asia Region95 Unmet need for family planning, countries96 Skilled birth attendance by household income quintile94 Unit: % Unit: % Although the proportion of women satisfied with modern methods of family planning have improved over time in the Region, women from rural areas, with lower education and from poor households have a higher unmet need for family planning THA 2012 2016 2019 $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 98 $ SRL 2006 2016 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ $ 97 $ $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ $ 99 $ MAV 2009 2017 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ 95 $ $ $ $ $ $ $ $ $ $ 98 $ $ $ $ $ $ $ $ $ $ 93 $ $ $ $ $ $ $ $ $ $ 89 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ $ 100 $ $ $ $ $ $ $ $ $ $ 100 $$ BHU 2010 $ $ $ $ $ $ $ $ $ $ 95 $ $ $ $ $ $ $ 67 $ $ $ $ $ $ $ $ $ 81 $ $ $ $ $ 43 $ $ $ $ 34 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ MYA 2016 $ $ $ $ $ $ $ $ $ $ 97 $ $ $ $ $ $ $ 65 $ $ $ $ $ $ $ $ 80 $ $ $ $ $ 51 $ $ $ $ 36 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ INO 2007 2012 2017 $ $ $ $ $ $ $ $ $ $ 95 $ $ $ $ $ $ $ $ 79 $ $ $ $ $ $ $ $ $ 87 $ $ $ $ $ $ $ 66 $ $ $ $ 44 $ $ $ $ $ $ $ $ $ $ 97 $ $ $ $ $ $ $ $ $ 90 $ $ $ $ $ $ $ $ $ 93 $ $ $ $ $ $ $ $ $ $ 82 $ $ $ $ $ $ 58 $ $ $ $ $ $ $ $ $ $ 99 $ $ $ $ $ $ $ $ $ 95 $ $ $ $ $ $ $ $ $ $ 97 $ $ $ $ $ $ $ $ $ $ 90 $ $ $ $ $ $ $ $ $ 75 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ BAN 2014 $ $ $ $ $ $ $ $ 74 $ $ $ $ 39 $ $ $ $ $ $ 52 $ $ $ 30 $ $ 18 2018 $ $ $ $ $ $ 83 $ $ $ $ $ $ 52 $ $ $ $ $ $ $ 63 $ $ $ $ $ 41 $ $ $ 28 2019 $ $ $ $ $ $ $ 86 $ $ $ $ $ $ 59 $ $ $ $ $ $ $ 70 $ $ $ $ $ 47 $ $ $ $ 32 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ IND 2006 2016 2021 $ $ $ $ $ $ $ $ $ 89 $ $ $ $ $ 48 $ $ $ $ $ $ $ 67 $ $ $ 30 $ $ 18 $ $ $ $ $ $ $ $ $ $ 96 $ $ $ $ $ $ $ $ $ 87 $ $ $ $ $ $ $ $ $ 92 $ $ $ $ $ $ $ $ 78 $ $ $ $ $ $ 64 $ $ $ $ $ $ $ $ $ $ 97 $ $ $ $ $ $ $ $ $ 92 $ $ $ $ $ $ $ $ $ 95 $ $ $ $ $ $ $ $ $ $ 88 $ $ $ $ $ $ $ $ 79 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ NEP 2011 2016 2019 $ $ $ $ $ $ $ $ $ 82 $ $ $ $ 36 $ $ $ $ $ $ 53 $ $ $ 24 $ $ 11 $ $ $ $ $ $ $ $ $ 89 $ $ $ $ $ $ 59 $ $ $ $ $ $ $ 70 $ $ $ $ $ 48 $ $ $ $ 34 $ $ $ $ $ $ $ $ $ $ 94 $ $ $ $ $ $ $ $ $ 81 $ $ $ $ $ $ $ $ $ 87 $ $ $ $ $ $ $ $ 72 $ $ $ $ $ $ 58 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $$ TLS 2010 2016 $ $ $ $ $ $ $ 69 $ $ $ 22 $ $ $ $ 38 $ $ 14 $ $ 11 $ $ $ $ $ $ $ $ $ 90 $ $ $ $ $ $ 56 $ $ $ $ $ $ $ 74 $ $ $ $ 39 $ $ $ 26 $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ 12 12 14 2014 2018 2019 BAN 50 25 0 12 2010 BHU 14 13 9 2006 2016 2021 IND 13 11 11 2007 2012 2017 INO 50 25 0 16 2016 MYA 28 24 25 2011 2016 2019 NEP 7 6 8 2012 2016 2019 THA Poorest Second Middle Fourth Richest 29 31 2009 2017 MAV 7 8 2006 2016 SRL 31 25 2010 2016 TLS WHO SE Asia Region 2000 2005 2010 2015 2020 100 75 50 25 0 69 71 73 74 75 30 Unit: % Unmet need for family planning by location of residence97 Unmet need for family planning by level of education98 Unmet need for family planning by household income quintile99 Unit: % Unit: % SRL 2006 2016 87 787 97 868 $$ $$$ $$ $$$ THA 2012 2016 2019 78 775 66 675 97 888 $$ $$$ $$ $$$ $$ $$$ TLS 2010 2016 $ $ 28 $ $ $ 34 $ $ 28 $ $ $ 30 $ $ $ 35 $ $ 25 $ $ 23 $ $ 25 $ $ 27 $ $ 27 $ $ $ $ $$ $$$ $ INO 2007 2012 2017 $ 13 $ 13 $ 11 $ 13 $ 17 $ 12 $ 10 $ 11 $ 10 $ 14 $ 12 $ 10 $ 10 $ 10 $ 11 $ $ $ $ $ $ $ $ $ $ MAV 2009 2017 $ $ 27 $ $ 29 $ $ 29 $ $ $ 30 $ $ 29 $ $ 25 $ $ $ 33 $ $ $ 34 $ $ $ 32 $ $ $ 33 $$ $$ $ $ $$$ MYA 2016 $ 13 $ 16 $ 16 $ 17 $ $ 20 $$ $$ NEP 2011 2016 2019 $ $ 22 $ $ 29 $ $ 27 $ $ 29 $ $ $ 32 $ $ 21 $ $ 24 $ $ 24 $ $ 24 $ $ 27 $ $ 27 $ $ 25 $ $ 24 $ $ 22 $ $ 25 $$ $$ $ $$$ $ $$ $$$$ BAN 2014 $ 11 $ 12 $ 13 $ 11 $ 13 2018 $ 12 $ 13 $ 13 $ 12 $ 10 2019 $ 16 $ 14 $ 16 $ 10 $ 12 $$ $$$ $$ $$ $$ $$ BHU 2010 $ 12 $ 13 $ 10 $ 13 $ 11 $$$$ IND 2006 2016 2021 $ 10 $ 14 $ 12 $ 16 $ 19 $ 12 $ 12 $ 12 $ 13 $ 17 $ 9 $ 9 $ 9 $ 10 $ 11 $ $$ $$$$ $ $$ Poorest Second Middle Fourth Richest No education SecondaryPrimary Higher Urban Rural BAN 2014 2018 2019 10 13 9 13 12 14 MAV 2009 2017 27 29 30 33 BHU 2010 10 12 MYA 2016 13 17 IND 2006 2016 2021 11 15 12 13 8 10 SRL 2006 2016 10 7 11 7 NEP 2011 2016 2019 20 29 23 25 25 24 INO 2007 2012 2017 13 13 12 11 11 10 THA 2012 2016 2019 7 7 7 6 9 8 TLS 2010 2016 29 31 26 25 BHU 2010 11 13 15 IND 2006 2016 2021 15 13 14 11 11 11 14 17 7 8 10 13 BAN 2014 2018 2019 10 12 14 11 7 11 14 12 12 13 15 15 MAV 2009 24 27 33 26 2017 24 27 37 25 MYA 2016 24 17 14 8 INO 2007 2012 2017 19 14 12 9 13 12 10 12 12 11 11 10 NEP 2011 2016 2019 23 31 34 27 18 26 30 23 17 26 30 36 TLS 2010 2016 31 30 31 25 23 24 28 25 SRL 2006 2016 7 7 8 6 2 7 7 7 THA 2012 2016 2019 10 7 7 7 12 5 6 7 12 7 8 9 Compared with men, a higher proportion of women with raised blood glucose go untreated. This diagnosis and treatment gap is also seen for hypertension. Data on people of diverse genders are generally unavailable Treated and controlled Treated but uncontrolled Diagnosed but untreated Undiagnosed Treated and controlled Treated but uncontrolled Diagnosed but untreated Undiagnosed Diagnosis, treatment and control of blood sugar among adults100 Diagnosis, treatment and control of blood pressure among adults101 Unit: % Unit: % Men Women 25 16 25 12 1248 955BAN 2018 Men Women 1 1 0.4 4 395 294BAN 2018 Men Women 13 56 15 21 626 758BHU 2019 Men Women 12 7 7 4 2061 2069BHU 2019 Men Women 20 9 27 13 1061 852IND 2017 Men Women 11 7 5 6 1566 1277IND 2017 Men Women 28 20 20 7 1636 73MAV 2011 Men Women 16 10 109 9 1461 72MAV 2011 Men Women 23 5 17 5 764 573MYA 2014 Men Women 21 12 11 9 2345 1961MYA 2014 Men Women 14 5 15 7 477 870NEP 2019 Men Women 6 6 5 3 1375 1181NEP 2019 Men Women 32 23 22 21 441 1245SRL 2015 Men Women 20 13 11 10 1255 969SRL 2015 Men Women 35 25 24 22 239 449THA 2014 Men Women 22 37 17 22 635 754THA 2014 Men Women 1 3 2 2 194 195TLS 2014 Men Women 6 3 1 1 586 196TLS 2014 Cataract surgical coverage102 Cataract surgical coverage for men and women has increased over time in the Region, but women generally lag behind men Unit: % WomenMen BHU 2018 In persons <3/60 91 83 In persons <6/60 86 81 In persons <6/18 51 59 SRL 2015 In persons <3/60 86 85 THA 2015 In persons <3/60 92 87 In persons <6/60 82 87 In persons <6/18 43 49 TLS 2016 In persons <3/60 66 31 In persons <6/60 51 26 In persons <6/18 31 16 NEP 2012 In persons <3/60 88 83 In persons <6/60 72 69 In persons <6/18 56 54 MAV 2017 In persons <3/60 94 93 In persons <6/18 7167 In persons <6/60 9090 31 Ratification of treaties that include the right to health103 Ratified the treaty Signatory to the treaty Neither ratified nor signatory Treaties BAN BHU IND INO MAV MYA NEP SRL THA TLS International Covenant on Economic, Social and Cultural Rights          International Covenant on Civil and Political Rights         International Convention on the Elimination of All Forms of Racial Discrimination  *        Convention on the Elimination of All Forms of Discrimination against Women           Convention on the Rights of the Child           International Convention on the Protection of the Rights of All Migrant Workers and Members of Their Families     Convention on the Rights of Persons with Disabilities  *        Do gender, equity and human rights’ perspectives influence the institutional capacity and arrangements in WHO SE Asia Region? Constitutional provisions for equality and non-discrimination104 Bangladesh • “Ensures equality of opportunity of all citizens” (Article 19[1]). • “The state shall adopt effective measures to remove social inequality between man and man and to ensure the equitable distribution of wealth among citizens” (Article 19[2]). • “The state shall endeavour to ensure equality of opportunity and participation of women in all spheres of national life” (Article 19[3]). • “The state shall not discriminate against any citizen on grounds only of religion, race, caste, sex or place of birth” (Article 28[1]). • “Women shall have equal rights with men in all spheres of the state and of public life” (Article 28[2]). Bhutan • “All persons are equal before the law and are entitled to equal and effective protection of the law and shall not be discriminated against on the grounds of race, sex, language, religion, politics or other status” (Article 7). India • “The State shall not deny to any person equality before the law or the equal protection of the laws within the territory of India” (Article 14). • “The State shall not discriminate against any citizen on grounds only of religion, race, caste, sex, place of birth or any of them” (Article 15[1]). • “The State shall, in particular, strive to minimise the inequalities in income and endeavour to eliminate inequalities in status, facilities and opportunities, not only amongst individuals but also amongst groups of people residing in different areas or engaged in different vocations” (Article 38). Indonesia • “All citizens shall be equal before the law and the government and shall be required to respect the law and the government, with no exceptions” (Article 27). • “Every person shall have the right of recognition, guarantees, protection and certainty before a just law and of equal treatment before the law” (Article 28D). • “Every person shall have the right to receive facilitation and special treatment to have the same opportunity and benefit in order to achieve equality and fairness” (Article 28H). • “Every person shall have the right to be free from discriminative treatment based upon any grounds whatsoever and shall have the right to protection from such discriminative treatment” (Article 28I). Maldives • “All citizens are entitled to the rights and freedoms (…) without discrimination of any kind, including race, national origin, colour, sex, age, mental or physical disability, political or other opinion, property, birth or other status, or native island” (Article 17). • “Every individual is equal before and under the law and has the right to the equal protection and equal benefit of the law” (Article 20). • “The enumeration of rights and freedoms in this Chapter are guaranteed equally to female and male persons. …” (Article 62). Myanmar • “The Union shall guarantee any person to enjoy equal rights before the law and shall equally provide legal protection” (Article 347). • “Every citizen shall enjoy the right of equality, the right of liberty and the right of justice, as prescribed in this Constitution. The Union shall not discriminate any citizen of the Republic of the Union of Myanmar, based on race, birth, religion, official position, status, culture, sex and wealth” (Article 348). Nepal • “All citizens shall be equal before law. No person shall be denied the equal protection of law.” (Article 18[1]). • “There shall be no discrimination in the application of general laws on the grounds of origin, religion, race, caste, tribe, sex, physical conditions, disability, health condition, matrimonial status, pregnancy, economic condition, language or geographical region, or ideology or any other such grounds.” (Article 18[2]). • “The state shall not discriminate among citizens on grounds of origin, religion, race, caste, tribe, sex, economic condition, language or geographical region, ideology and such other matters.” (Article 18[3]). Sri Lanka • “All persons are equal before the law and are entitled to the equal protection of the law.” (Article 12[1]). • “No citizen shall be discriminated against on grounds of race, religion, language, caste, sex, political opinion, place of birth or anyone of such grounds.” (Article 12[2]). • “No person shall, on the grounds of race, religion, language, caste, sex or any one of such grounds, be subject to any disability, liability, restriction or condition with regard to access to shops, public restaurants, hotels, places of public entertainment and places of public worship of his own religion.” (Article 12[3]). • “Nothing in this Article shall prevent special provision being made, by law, subordinate legislation or executive action, for the advancement of women, children or disabled persons” (Article 12[4]). * 32 Thailand • “Human dignity, rights, liberties and equality of the people shall be protected. The Thai people shall enjoy equal protection under the Constitution” (Section 4, Chapter I). • “All persons are equal before the law and shall have rights and liberties and be protected equally under the law. Men and women shall enjoy equal rights. Unjust discrimination against a person on the grounds of differences in origin, race, language, sex, age, disability, physical or health condition, personal status, economic and social standing, religious belief, education, or political view which is not contrary to the provisions of the Constitution or on any other grounds, shall not be permitted.” (Section 27, Chapter III). Timor-Leste • “All citizens are equal before the law, shall exercise the same rights and shall be subject to the same duties” (Section 16[1]). • “No one shall be discriminated against on grounds of colour, race, marital status, gender, ethnical origin, language, social or economic status, political or ideological convictions, religion, education and physical or mental condition” (Section 16[2]). • “Women and men shall have the same rights and duties in all areas of family, political, economic, social and cultural life” (Section 17). • “The law shall promote equality in the exercise of civil and political rights and non-discrimination on the basis of gender for access to political positions” (Section 63). Legal arrangements related to inheritance, land ownership, divorce and protection from intimate partner violence105 Inheritance Land ownership Divorce Intimate partner violence BHU, SRL, THA MYA, NEP, TLS BHU, IND, MAV, NEP, THA INO, THA, TLS NEP IND BAN, INO, MYA, TLS IND BHU, IND, SRL, TLS SRL BHU, MYA, SRL BAN, INO, MAV, MYA, THA BAN, INO, MAV BAN, MAV, NEP 0 0.25 0.5 0.75 1 Widows and daughters enjoy the same rights as widowers and sons to inherit land and non-land assets. This applies to all groups of women. Customary, religious and traditional laws or practices do not discriminate against women’s inheritance rights. Widows and daughters enjoy the same rights as widowers and sons to inherit land and non-land assets. This applies to all groups of women. However, there are some customary, religious or traditional laws that discriminate against women’s inheritance rights. Widows and daughters enjoy the same rights as widowers and sons to inherit land and non-land assets. However, this does not apply to all groups of women. Widows or daughters do not enjoy the same rights as widowers and sons to inherit land and/or non-land assets. Widows and daughters do not enjoy the same rights as widowers and sons to inherit land and/or non-land assets. Women and men have the same legal rights and secure access to land assets, without legal exceptions regarding some groups of women. Customary, religious and traditional laws or practices do not discriminate against women’s legal rights. Women and men have the same legal rights and secure access to land assets, without legal exceptions regarding some groups of women. However, some customary, religious or traditional practices or laws discriminate against women’s legal rights. Women and men have the same legal rights and secure access to land assets. However, this does not apply to all groups of women. Women and men have the same legal rights to own land assets; but not to use, make decisions and/or use land assets as collateral. Women do not have the same legal rights as men to own land assets. Women have both the same rights to initiate divorce and the same requirements to finalise divorce or annulment as men, without negative repercussions on their parental authority. This applies to all groups of women. Customary, religious and traditional laws or practices do not discriminate against women’s rights regarding divorce or parental authority after divorce. Women have both the same rights to initiate divorce and the same requirements to finalise divorce or annulment as men, without negative repercussions on their parental authority. This applies to all groups of women. However, there are some customary, religious or traditional laws or practices that discriminate against women’s rights regarding divorce and/or parental authority after divorce. Women have both the same rights to initiate divorce and the same requirements to finalise divorce or annulment as men, without negative repercussions on their parental authority. However, this does not apply to all groups of women. Women do not have the same rights over divorce as men: either their rights to initiate divorce and/or the requirements to finalise divorce or annulment are unequal, or their parental authority after divorce is restricted. Women do not have the same rights over divorce as men: their rights to initiate divorce and/or the requirements to finalise divorce or annulment are unequal and their parental authority after divorce is restricted. The legal framework protects women from violence including intimate partner violence, rape and sexual harassment, without any legal exceptions and in a comprehensive approach. The legal framework protects women from violence including intimate partner violence, rape and sexual harassment, without any legal exceptions. However, the approach is not comprehensive. The legal framework protects women from violence including intimate partner violence, rape and sexual harassment. However, some legal exceptions occur. The legal framework protects women from some forms of violence including intimate partner violence, rape or sexual harassment but not all. The legal framework does not protect women from violence nor intimate partner violence nor rape and sexual harassment. Unit: Index from 0 to 1 with 0 being better 33 Although there is growing recognition of gender plurality, same-sex relationships and conduct are still not legally accepted by many countries, with same-sex marriages criminalized in most. Some countries have started including a third gender category in official statistics and national census in recent years Legal protection for all sexual orientations and gender identities107 Legal arrangements related to sexual and reproductive health rights BAN BHU IND INO MAV MYA NEP SRL THA TLS Legalization of same-sex marriage ** *** ** Decriminalization of same-sex sexual acts   *  ***   Recognition of gender identity        BAN BHU IND INO MAV MYA NEP SRL THA TLS Legal grounds for abortion108 At woman’s request without any justification   Woman’s physical or mental health     Rape or incest      Foetal impairment       Intellectual or cognitive disability of the woman  Potential threat to mother’s life           Direct support for family planning109           Policies are yet to recognize woman’s autonomy in sexual and reproductive health decisions. Most countries allow abortion only when the mother’s life is at risk due to pregnancy Legal minimum age for marriage106 BAN BHU IND INO MAV MYA NEP SRL THA TLS General minimum age of marriage (without parental consent) Men 21 18 21 21 18 18 20 18 20 17 Women 18 18 18 21 18 18 20 18 20 17 Minimum age of marriage (with exceptions: under religious and customary law, parental consent) Men 19 <18 18 17 16 Women <18 19 <18 <18 18 <18 17 16 Almost all countries have adopted policy measures to raise the minimum age at marriage. However, early/child marriages are often allowed under religious and customary law in many countries in the Region Bhutan and Thailand decriminalized same-sex marriages in 2021 and 2022, respectively; however, no legal protection was offered** Legal in some provinces* Legal Allowed Judicial verdicts in 2023 were in favour of legalization (Nepal) and decriminalization (Sri Lanka)*** Not legal Not allowed 34 Institutional arrangements and capacity BAN BHU IND INO MAV MYA NEP SRL THA TLS Gender mainstreaming mentioned in national development policy (and latest year)110  (2016)  (2020)  (2022)  (2015)  (2019)  (2018)  (2019)  (2017)  (2018)  (2011) Gender policy from national women’s machinery (and year introduced)111  (2011)  (2020)  (2016)  (2022)  (2013)  (2004)  (2016)  (2017) Gender- responsive budgeting112 Mention of gender-responsive budgeting in plans (year)  (2003)  (2012)  (2002)  (2010)  (2002)  (2017)  (2017)  (2008) Legislation for gender-responsive budgeting  National plan/strategy for gender- responsive budgeting (year)  (2016)  (2012)  (2005)  (2012)  (2019)  (2017)  (2019) Gender focal points in government113          Gender policy/strategy in the Ministry of Health114     N/A Gender training for Ministry of Health staff115       N/A N/A Gender analysis by the Ministry of Health116   N/A     N/A All countries in the Region have adopted the concept of gender mainstreaming in their national plans, with many having specific policies for gender equality. However, the institutional capacity to implement these strategies needs strengthening Conclusion Recommendations Forward-looking policies, if effectively implemented through appropriate institutional mechanisms and adequate capacity, support the mainstreaming of gender, equity and human rights perspectives in health and enable change towards greater equity • Given the influence of gender on health in WHO SE Asia Region, putting a gender perspective into health interventions is essential. When applying a gender lens to health interventions, it is important to remember that gender interacts with other forms of social exclusion, such as ethnicity, age and socioeconomic position • Several tools are available for gender analysis, assessment and planning or programming, which can help to identify gender issues and inequalities in health and tailor the design, implementation and monitoring of health policies and programmes to take account of these differences for improved outcomes. These tools include the WHO gender analysis matrix (GAM) and gender analysis questions (GAQ), the WHO gender responsive assessment scale (GRAS) and gender analysis tool (GAT), the WHO gender and health planning and programming checklist and the WHO gender responsive log-frame117 • The Innov8 approach118 and Human Rights and Gender Equality in Health Sector Strategies: how to assess policy coherence119 are tools that support the development of equity-enhancing, gender-responsive and human rights-based national health policies, programmes and strategies. Additionally, using a human rights framework in health planning and policymaking can help identify and adequately address the biological and sociocultural factors that differentially influence the health of men and women Not adoptedAdopted N/A Information not available 35 Index of indicators Why does gender matter for health? .......................1 Gross domestic product per capita ........................................1 Current health expenditure per capita, WHO SE Asia Region and countries ........................................................................1 Catastrophic household health expenditure, WHO SE Asia Region and countries .......................................1 Out-of-pocket expenditure, WHO SE Asia Region and countries ........................................................................1 Poverty level .........................................................................2 Gini index ..............................................................................2 Sex ratio at birth ....................................................................2 Gender gap index ..................................................................2 Gender development index.....................................................3 Gender inequality index..........................................................3 Human development index and inequality-adjusted human development index .....................................................3 Does gender influence access to determinants of health? ................................................................4 Literacy rate ..........................................................................4 Gender parity index in school enrolment.................................4 Women graduates in STEM ...................................................5 Access to mass media ..........................................................5 Use of internet .......................................................................5 Ownership of mobile phones .................................................6 Women agricultural landholders .............................................6 Account in a financial institution ............................................6 Women’s participation in household decision-making ............7 Gap in earned income between women and men ...................7 Labour force participation rate ...............................................7 Informal sector participation ..................................................8 Child labour ...........................................................................8 Women in managerial positions .............................................8 Distribution of doctors ...........................................................9 Distribution of nurses ............................................................9 Households more than 30 minutes from water source ...........9 Time spent on unpaid work .................................................10 Do men and women have similar life expectancies? .......................................................10 Life expectancy and health life expectancy at birth, WHO SE Region and countries .............................................10 Do gender, location of residence, education and income affect the health status of people in WHO Se Asia Region? ...........................................11 10 leading causes of death among men and women ............11 10 leading causes of DALYs lost among men and women ....11 Under-5 mortality rate by sex, WHO SE Asia Region and countries ......................................................................11 Under-5 mortality rate by location of residence ....................12 Under-5 mortality rate by mother’s education ......................12 Under-5 mortality rate by household income quintile ............12 Nutritional status of children by sex .....................................13 Stunting ...........................................................................13 Wasting ............................................................................13 Underweight .....................................................................13 Nutritional status of children by location of residence ...........13 Stunting ...........................................................................13 Wasting ............................................................................13 Underweight .....................................................................14 Nutritional status of children by mother’s education .............14 Stunting ...........................................................................14 Wasting ............................................................................14 Underweight .....................................................................14 Nutritional status of children by household income quintile ...15 Stunting ...........................................................................15 Wasting ............................................................................15 Underweight .....................................................................16 Total fertility rate by location of residence ............................16 Total fertility rate by level of education .................................16 Total fertility rate by household income quintile ....................17 Adolescent fertility rate, WHO SE Asia Region and countries ......................................................................17 Adolescent fertility rate by location of residence ...................17 Adolescent fertility rate by level of education ........................18 Adolescent fertility rate by household income quintile ..........18 Maternal mortality ratio, WHO SE Asia Region and countries ......................................................................19 Do gender, location of residence, education and income affect the exposure to health risks and vulnerabilities in WHO SE Asia Region? ...............19 Overweight among adults, WHO SE Asia Region and counties .......................................................................19 Obesity among adults, WHO SE Asia Region and counties .......................................................................20 Physical activity among adults, WHO SE Asia Region and counties .......................................................................20 Age-standardized tobacco use among adults .......................21 Alcohol consumption among adults .....................................21 Overweight among adolescents ...........................................21 Obesity among adolescents .................................................22 Physical activity among adolescents ....................................22 (continued) 36 Alcohol consumption among adolescents ............................22 Prevalence of tobacco use among adolescents ....................22 Ever use of marijuana among adolescents ...........................23 Comprehensive knowledge of HIV/AIDS among adolescent girls ...................................................................23 Lifetime prevalence of intimate partner violence among women, WHO SE Asia Region and countries ........................23 Intimate partner violence among ever-partnered women by location of residence ......................................................24 Intimate partner violence among ever-partnered women by level of education ...........................................................24 Intimate partner violence among ever-partnered women by household income quintile ..............................................24 Population using clean fuel for cooking, WHO SE Asia Region ...........................................................24 Households using clean fuel for cooking, countries ..............24 Do gender, location of residence, education and income affect access to health services in WHO SE Asia Region? ..........................................25 DTP3 vaccination rate by sex ...............................................25 DTP3 vaccination rate by location of residence ....................25 DTP3 vaccination rate by mother’s education ......................25 DTP3 vaccination rate by household income quintile ............26 Antenatal care coverage by location of residence .................26 Antenatal care coverage by level of education ......................27 Antenatal care coverage by household income quintile .........27 Skilled birth attendance, WHO SE Asia Region and countries ......................................................................28 Skilled birth attendance by location of residence ..................28 Skilled birth attendance by level of education .......................28 Skilled birth attendance by household income quintile ..........29 Met need with modern methods, WHO SE Asia Region ........29 Unmet need for family planning, countries ...........................29 Unmet need for family planning by location of residence ......30 Unmet need for family planning by level of education ...........30 Unmet need for family planning by household income quintile ....................................................................30 Diagnosis, treatment and control of blood sugar among adults ......................................................................31 Diagnosis, treatment and control of blood pressure among adults ......................................................................31 Cataract surgical coverage ..................................................31 Do gender, equity and human rights’ perspectives influence the institutional capacity and arrangements in WHO SE Asia region?.................32 Ratification of treaties that include the right to health ............32 Constitutional provisions for equality and non-discrimination ..............................................................32 Legal arrangements related to inheritance, land ownership, divorce and protection from intimate partner violence ..........33 Legal minimum age for marriage .........................................34 Legal protection for all sexual orientations and gender identities ..................................................................34 Legal arrangements related to sexual and reproductive health rights ........................................................................34 Institutional arrangements and capacity ...............................35 Acronyms BAN Bangladesh BHU Bhutan DTP diphtheria, tetanus, pertussis HDI Human development index IHDI Inequality-adjusted human development index IPV intimate partner violence IND India INO Indonesia MAV Maldives MYA Myanmar NEP Nepal SE South-east SRL Sri Lanka STEM science, technology engineering and mathematics THA Thailand TLS Timor-Leste WHO World Health Organization (continued) 37 Endnotes 1. Gross domestic product per capita, PPP (current international $): data by country. In: World Development Indicators [database]. Washington D.C., World Bank, Development Data Group. International Comparison Program; 2022 (https://databank.worldbank. org/reports.aspx?source=2&series=NY.GDP.PCAP.PP.CD&country=#, accessed 22 August 2022). 2. Current health expenditure per capita, PPP (current international $): data by WHO region. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://apps.who.int/gho/data/view.main. GHEDCHEpcPPPSHA2011v, accessed 22 August 2022). 3. Current health expenditure per capita, PPP (current international $): data by country. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://apps.who.int/gho/data/view.main. GHEDCHEpcPPPSHA2011v, accessed 22 August 2022). 4. Catastrophic household health expenditure on health as a share of total household consumption or income: data by WHO region. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://apps.who. int/gho/data/view.main.FINANCIALPROTECTIONWHOREG01v?lang=en, accessed 22 August 2022). 5. Catastrophic household health expenditure on health as a share of total household consumption or income: data by country. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://apps.who.int/gho/data/ view.main.UHCFINANCIALPROTECTION01v?lang=en, accessed 22 August 2022). 6. Out-of-pocket health spending: data by WHO region. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://apps.who.int/ gho/data/view.main.GHEDOOPSCHESHA2011REGv?lang=en, accessed 22 August 2022). 7. Out-of-pocket health spending: data by country. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://apps.who.int/ gho/data/view.main.GHEDOOPSCHESHA2011v?lang=en, accessed 22 August 2022). 8. Poverty headcount ratio at $1.90 a day. In: World Bank Development Research Group [database]. Washington D.C., World Bank; 2022 (https://databank.worldbank.org/ reports.aspx?source=2&series=SI.POV.DDAY&country=, accessed 22 August 2022). 9. Poverty headcount ratio at $5.50 a day. In: World Bank Development Research Group [database]. Washington D.C., World Bank; 2022 (https://databank.worldbank.org/ reports.aspx?source=2&series=SI.POV.DDAY&country=, accessed 22 August 2022). 10. Gini index (World Bank Estimate). In: World Bank Development Research Group [database]. Washington D.C., World Bank; 2022 (https:// databank.worldbank.org/reports.aspx?source=2&series=SI.POV. GINI&country=BGD,BHU,PRK,IND,IDN,MDV,MMR,NPL,THA,TLS,LKA, accessed 22 August 2022). 11. World Population Prospects 2019 Volume II: Demographic Profiles. New York: United Nations, Department of Social Affairs; 2019 (https://population.un.org/wpp/Publications/ Files/WPP2019_Volume-II-Demographic-Profiles.pdf, accessed 22 August 2022). 12. Time to gender parity. In: Global Gender Gap Report [website]. Geneva: World Economic Forum; 2022 (https://www.weforum.org/reports/global-gender-gap- report-2022/in-full/economy-profiles-5b89d90ea5, accessed 28 August 2022). 13. Gender development index. In: Human Development Reports [website]. New York: United Nations Development Programme; 2022 (https://hdr.undp.org/data-center/ specific-country-data#/countries/, accessed 10 September 2022). 14. Gender inequality index. In: Human Development Reports [website]. New York: United Nations Development Programme; 2022 (https://hdr.undp.org/data-center/specific- country-data#/countries/, accessed 10 September 2022). 15. Human development index. In: Human Development Reports [website]. New York: United Nations Development Programme; 2022 (https://hdr.undp.org/data-center/ specific-country-data#/countries/, accessed 10 September 2022). 16. Inequality-adjusted human development index. In: Human Development Reports [website]. New York: United Nations Development Programme; 2022 (https://hdr.undp. org/data-center/specific-country-data#/countries/, accessed 10 September 2022). 17. Adult literacy rate, by sex. In: UIS.Stat [database]. Montreal: UNESCO Institute of Statistics; 2022 (http://sdg4-data.uis.unesco.org/, [From dropdown menu for indicators on the left side, select SDGs SDG 4 Target 4.6 Indicator 4.6.2 Youth/adult literacy rate], accessed 28 August 2022). 18. Gender parity index of the gross enrolment ratios in primary, secondary and tertiary education. In: UIS.Stat [database]. Montreal: UNESCO Institute; 2022 (http://data. uis.unesco.org [From dropdown menu for indicators on the left side, select Other policy relevant indicators: Gross enrolment ratio by level of education, GPI], accessed 28 August 2022. 19. Share of female science, technology, engineering and mathematics graduates at tertiary level. In: World Bank Gender Data Portal [database]. Washington D.C., World Bank, Development Data Group; 2022 (https://genderdata.worldbank.org/indicators/ se-ter-grad-fe-zs/?fieldOfStudy=Science%2C%20Technology%2C%20Engineering%20 and%20Mathematics%20%28STEM%29&geos=IDN_MMR_THA_TLS_BGD_BHU_ MDV_LKA_NPL_IND&view=bar, accessed 26 August 2022). 20. Bangladesh Demographic and Health Survey 2011. Dhaka, Bangladesh and Calverton, Maryland, USA: National Institute of Population Research and Training, Mitra and Associates and ICF International; 2013 (https://dhsprogram.com/pubs/pdf/fr265/fr265. pdf, accessed 20 August 2022), Bangladesh Demographic and Health Survey 2014. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Mitra and Associates and ICF International; 2016 (https:// dhsprogram.com/pubs/pdf/-FR311/FR311.pdf, accessed 28 August 2022), Progotir Pathey Multiple Indicator Cluster Survey 2019. Survey findings report. Dhaka: Bangladesh Bureau of Statistics (BBS); 2019 (https://reliefweb.int/sites/reliefweb.int/ files/resources/Bangladesh-MICS-2019-SFR_English.pdf, accessed 20 August 2022), National Family Health Survey (NFHS-3), 2005–2006. Mumbai, India: International Institute for Population Sciences, IIPS/India and Macro international; 2007 (https:// dhsprogram.com/publications/publication-FRIND3-DHS-Final-Reports.cfm, accessed 22 August 2022), National Family Health Survey (NFHS-4), 2015–2016. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2017 (https://dhsprogram.com/publications/publication-FR339-DHS-Final-Reports.cfm, accessed 22 August 2022), National Family Health Survey (NFHS-5), 2019–2021. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2022 (https://dhsprogram.com/pubs/pdf/FR375/FR375.pdf, accessed 22 August 2022), Indonesia Demographic and Health Survey 2007. Calverton, Maryland, USA: Statistics Indonesia-Badan Pusat Statistik-BPS and Macro International; 2008 (https:// dhsprogram.com/publications/publication-fr218-dhs-final-reports.cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey 2012. Jakarta, Indonesia: Statistics Indonesia-Badan Pusat Statistik-BPS, National Population and Family Planning Board-BKKBN/Indonesia, Ministry of Health/Indonesia and ICF International; 2013 (https://www.dhsprogram.com/publications/publication-FR275-DHS-Final-Reports. cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey, 2017. Jakarta, Indonesia: National Population and Family Planning Board, Statistics Indonesia, Ministry of Health and ICF; 2018 (https://dhsprogram.com/publications/publication- fr342-dhs-final-reports.cfm, accessed 20 August 2022), Maldives Demographic and Health Survey 2009. Malé, Maldives and Calverton, Maryland: Ministry of Health and Family and ICF Macro; 2010 (https://dhsprogram.com/pubs/pdf/FR237/FR237.pdf, accessed 18 July 2022), Maldives Demographic and Health Survey 2016–2017. Malé, Maldives and Maryland, USA: Ministry of Health and ICF; 2018 (https://dhsprogram. com/pubs/pdf/FR349/FR349.pdf, accessed 28 August 2022), Myanmar Demographic and Health Survey 2015–2016. Naypyitaw, Myanmar: Ministry of Health and Sports- MoHS and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR324/FR324.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2011. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/Nepal and ICF; 2012 (https://dhsprogram. com/pubs/pdf/fr257/fr257%5B13april2012%5D.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2016. Kathmandu, Nepal: Ministry of Health-MoH/ Nepal, New ERA/Nepal and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR336/ FR336.pdf, accessed 28 August 2022), Nepal Multiple Indicator Cluster Survey 2019. Kathmandu, Nepal: Central Bureau of Statistics and UNICEF Nepal; 2020 (https:// mics-surveys-prod.s3.amazonaws.com/MICS6/South%20Asia/Nepal/2019/Survey%20 findings/Nepal-MICS%202019SFR_English.pdf, accessed 28 August 2022), Sri Lanka Demographic and Health Survey 2006–2007. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health care and Nutrition; 2009 (http://www. statistics.gov.lk/Health/StaticalInformation/FinalReport, accessed 18 July 2022), Sri Lanka Demographic and Health Survey 2016. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health, Nutrition and Indigenous Medicine; 2017 (http://www.statistics.gov.lk/Health/StaticalInformation/DemographicAndHealthSurvey- 2016FullReport, accessed 28 August 2022), Timor-Leste Demographic and Health Please note that the data used in this document from ILOSTAT, Global Health Observatory database, World Development Indicators database and UNESCO Institute of Statistics are correct as of August–September 2022 38 Survey 2009–2010. Dili, Timor-Leste: National Statistics Directorate, Ministry of Finance/Timor-Leste and ICF Macro; 2010 (https://dhsprogram.com/pubs/pdf/FR235/ FR235.pdf, accessed 26 July 2022) and Timor-Leste Demographic and Health Survey 2016. Dili, Timor-Leste and Rockville, Maryland, USA: General Directorate of Statistics, Ministry of Finance/Timor-Leste and ICF; 2018 (https://dhsprogram.com/pubs/pdf/ FR329/FR329.pdf, accessed 28 August 2022). 21. Proportion of individuals who have used internet, by sex. In: Minimum set of gender indicators [website]. New York: United Nations, Department of Social Affairs; 2022 (https://gender-data-hub-2-undesa.hub.arcgis.com/datasets/ c0d827909751424a90c4e8c9f2d03741/explore, accessed 28 August 2022), After access survey, 2017. Gender gap in the global south. DIRSI, LIRNEasia, Research ICT Africa; 2018 (https://afteraccess.net/wp-content/uploads/2018-After-Access- Understanding-the-gender-gap-in-the-Global-South.pdf, accessed 28 August 2022), Maldives Demographic and Health Survey 2016–2017. Malé, Maldives and Maryland, USA: Ministry of Health and ICF; 2018 (https://dhsprogram.com/pubs/pdf/FR349/ FR349.pdf, accessed 28 August 2022), Myanmar Demographic and Health Survey 2015–2016. Naypyitaw, Myanmar: Ministry of Health and Sports-MoHS and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR324/FR324.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2016. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/Nepal and ICF; 2017 (https://dhsprogram.com/pubs/pdf/ FR336/FR336.pdf, accessed 28 August 2022), Multiple Indicator Cluster Survey 2019. Kathmandu, Nepal: Central Bureau of Statistics and UNICEF Nepal; 2020 (https://mics- surveys-prod.s3.amazonaws.com/MICS6/South%20Asia/Nepal/2019/Survey%20 findings/Nepal-MICS%202019SFR_English.pdf, accessed 28 August 2022), Sri Lanka Demographic and Health Survey 2016. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health, Nutrition and Indigenous Medicine; 2017 (http:// www.statistics.gov.lk/Health/StaticalInformation/DemographicAndHealthSurvey- 2016FullReport, accessed 28 August 2022) and Timor-Leste Demographic and Health Survey 2016. Dili, Timor-Leste and Rockville, Maryland, USA: General Directorate of Statistics, Ministry of Finance/Timor-Leste and ICF; 2018 (https://dhsprogram.com/ pubs/pdf/FR329/FR329.pdf, accessed 28 August 2022). 22. Proportion of individuals who own a mobile telephone, by sex. In: Minimum set of gender indicators [website]. New York: United Nations, Department of Social Affairs; 2022 (https://gender-data-hub-2-undesa.hub.arcgis.com/ datasets/4967cb2e128f49ccaf12cd7714c85882/explore, accessed 28 August 2022), After access survey, 2017. Gender gap in the global south. DIRSI, LIRNEasia, Research ICT Africa; 2018 (https://afteraccess.net/wp-content/uploads/2018- After-Access-Understanding-the-gender-gap-in-the-Global-South.pdf, accessed 28 August 2022), Mobile phones, internet and gender in Myanmar. London, United Kingdom: GSMA Connected Women and LIRNEasia; 2015 (https://www.gsma.com/ mobilefordevelopment/wp-content/uploads/2016/02/GSMA_Myanmar_Gender_ Web_Singles, accessed 28 August 2022), Maldives Demographic and Health Survey 2016–2017. Malé, Maldives and Maryland, USA: Ministry of Health and ICF; 2018 (https://dhsprogram.com/pubs/pdf/FR349/FR349.pdf, accessed 28 August 2022), Myanmar Demographic and Health Survey 2015–2016. Naypyitaw, Myanmar: Ministry of Health and Sports-MoHS and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR324/ FR324.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2016. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/Nepal and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR336/FR336.pdf, accessed 28 August 2022), Multiple Indicator Cluster Survey 2019. Kathmandu, Nepal: Central Bureau of Statistics and UNICEF Nepal; 2020 (https://mics-surveys-prod.s3.amazonaws.com/MICS6/ South%20Asia/Nepal/2019/Survey%20findings/Nepal-MICS%202019SFR_English.pdf, accessed 28 August 2022), Sri Lanka Demographic and Health Survey 2016. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health, Nutrition and Indigenous Medicine; 2017 (http://www.statistics.gov.lk/Health/StaticalInformation/ DemographicAndHealthSurvey-2016FullReport, accessed 28 August 2022) and Timor- Leste Demographic and Health Survey 2016. Dili, Timor-Leste and Rockville, Maryland, USA: General Directorate of Statistics, Ministry of Finance/Timor-Leste and ICF; 2018 (https://dhsprogram.com/pubs/pdf/FR329/FR329.pdf, accessed 28 August 2022). 23. Women’s share among agricultural holders. In: Gender, Institutions and Development Database (GID-DB) 2019, OECD.Stat [database]. Paris: Organization for Economic Co- operation and Development; 2022 (https://stats.oecd.org/index.aspx?queryid=54757, [See: Data by themes Social Protection and Well-being: Gender: Gender, Institutions and Development Database (GID-DB) 2019: Restricted Access to Productive and Financial Resources: Secure Access to Land Assets], accessed 26 August 2022). 24. Account in a financial institution, by sex. In: Global Findex Database [database]. Washington D.C., World Bank, Development Data Group. 2022 (https://www. worldbank.org/en/publication/globalfindex/Data, accessed 28 August 2022). 25. Bangladesh Demographic and Health Survey 2011. Dhaka, Bangladesh and Calverton, Maryland, USA: National Institute of Population Research and Training, Mitra and Associates and ICF International; 2013 (https://dhsprogram.com/pubs/pdf/fr265/fr265. pdf, accessed 20 August 2022), Bangladesh Demographic and Health Survey 2014. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Mitra and Associates and ICF International; 2016 (https:// dhsprogram.com/pubs/pdf/-FR311/FR311.pdf, accessed 28 August 2022), Bangladesh Demographic and Health Survey 2017–2018. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Ministry of Health and Family Welfare and ICF International; 2020 (https://dhsprogram.com/pubs/pdf/ FR344/FR344.pdf, accessed 28 August 2022), National Family Health Survey (NFHS-3), 2005–2006. Mumbai, India: International Institute for Population Sciences, IIPS/India and Macro international; 2007 (https://dhsprogram.com/publications/publication- FRIND3-DHS-Final-Reports.cfm, accessed 22 August 2022), National Family Health Survey (NFHS-4), 2015–2016. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2017 (https://dhsprogram.com/publications/publication- FR339-DHS-Final-Reports.cfm, accessed 22 August 2022), National Family Health Survey (NFHS-5), 2019–2021. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2022 (https://dhsprogram.com/pubs/pdf/FR375/FR375. pdf, accessed 22 August 2022), Indonesia Demographic and Health Survey 2007. Calverton, Maryland, USA: Statistics Indonesia-Badan Pusat Statistik-BPS and Macro International; 2008 (https://dhsprogram.com/publications/publication-fr218-dhs-final- reports.cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey 2012. Jakarta, Indonesia: Statistics Indonesia-Badan Pusat Statistik-BPS, National Population and Family Planning Board-BKKBN/Indonesia, Ministry of Health/Indonesia and ICF International; 2013 (https://www.dhsprogram.com/publications/publication- FR275-DHS-Final-Reports.cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey, 2017. Jakarta, Indonesia: National Population and Family Planning Board, Statistics Indonesia, Ministry of Health and ICF; 2018 (https://dhsprogram. com/publications/publication-fr342-dhs-final-reports.cfm, accessed 20 August 2022), Maldives Demographic and Health Survey 2009. Malé, Maldives and Calverton, Maryland: Ministry of Health and Family and ICF Macro; 2010 (https://dhsprogram. com/pubs/pdf/FR237/FR237.pdf, accessed 18 July 2022), Maldives Demographic and Health Survey 2016–2017. Malé, Maldives and Maryland, USA: Ministry of Health and ICF; 2018 (https://dhsprogram.com/pubs/pdf/FR349/FR349.pdf, accessed 28 August 2022), Myanmar Demographic and Health Survey 2015–2016. Naypyitaw, Myanmar: Ministry of Health and Sports-MoHS and ICF; 2017 (https://dhsprogram.com/pubs/pdf/ FR324/FR324.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2011. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/Nepal and ICF; 2012 (https://dhsprogram.com/pubs/pdf/fr257/fr257%5B13april2012%5D.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2016. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/Nepal and ICF; 2017 (https://dhsprogram.com/ pubs/pdf/FR336/FR336.pdf, accessed 28 August 2022), Nepal Multiple Indicator Cluster Survey 2019. Kathmandu, Nepal: Central Bureau of Statistics and UNICEF Nepal; 2020 (https://mics-surveys-prod.s3.amazonaws.com/MICS6/South%20Asia/Nepal/2019/ Survey%20findings/Nepal-MICS%202019SFR_English.pdf, accessed 28 August 2022), Sri Lanka Demographic and Health Survey 2016. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health, Nutrition and Indigenous Medicine; 2017 (http://www.statistics.gov.lk/Health/StaticalInformation/DemographicAndHealthSurvey- 2016FullReport, accessed 28 August 2022), Timor-Leste Demographic and Health Survey 2009–2010. Dili, Timor-Leste: National Statistics Directorate, Ministry of Finance/Timor-Leste and ICF Macro; 2010 (https://dhsprogram.com/pubs/pdf/FR235/ FR235.pdf, accessed 26 July 2022) and Timor-Leste Demographic and Health Survey 2016. Dili, Timor-Leste and Rockville, Maryland, USA: General Directorate of Statistics, Ministry of Finance/Timor-Leste and ICF; 2018 (https://dhsprogram.com/pubs/pdf/ FR329/FR329.pdf, accessed 28 August 2022). 26. Estimated gap in earned income between men and women. In: Global Gender Gap Report [website]. Geneva: World Economic Forum; 2022 (https://www.weforum. org/reports/global-gender-gap-report-2022/in-full/economy-profiles-5b89d90ea5, accessed 28 August 2022). 27. Labour force participation of persons aged 15+, by sex. In: ILOSTAT explorer [database]. Geneva: International Labour Organization; 2022 (https://www.ilo.org/ shinyapps/bulkexplorer6/?lang=en&segment=indicator&id=EAP_DWAP_SEX_AGE_ RT_A, accessed 28 August 2022). 28. Informal sector participation, by sex. In: ILOSTAT explorer [database]. Geneva: International Labour Organization; 2022 (https://www.ilo.org/shinyapps/ bulkexplorer8/?lang=en&segment=indicator&id=EMP_PIFL_SEX_AGE_RT_A, accessed 28 August 2022). 29. Proportion of children engaged in child labour, by sex. In: UNICEF Child Labour [database]. New York: United Nations Children’s Fund; 2022 (https://data. unicef.org/resources/data_explorer/unicef_f/?ag=UNICEF&df=GLOBAL_ DATAFLOW&ver=1.0&dq=BGD+BHU+IDN+MDV+MMR+NPL+LKA+THA+TLS. PT_CHLD_5-17_LBR_ECON-HC&startPeriod=1998&endPeriod=2022, accessed 28 August 2022) and National Family Health Survey NFHS-3, 2005–2006. Mumbai, India: International Institute for Population Sciences, IIPS/India and Macro international; 2007 (http://rchiips.org/nfhs/NFHS-3%20Data/VOL-1/Chapter%2002.pdf, accessed 28 August 2022). 39 30. Female share of employment in managerial positions. In: ILOSTAT explorer [database]. Geneva: International Labour Organization; 2022 (https://www.ilo.org/shinyapps/ bulkexplorer2/?lang=en&segment=indicator&id=SDG_0552_OCU_RT_A, accessed 22 August 2022). 31. Distribution of doctors, by sex. In: National Health Workforce Accounts Data Portal [database]. Geneva: World Health Organization; 2022 (https://apps.who.int/nhwaportal/ Home/Index, accessed 29 August 2022). 32. Distribution of nurses, by sex. In: National Health Workforce Accounts Data Portal [database]. Geneva: World Health Organization; 2022 (https://apps.who.int/nhwaportal/ Home/Index, accessed 29 August 2022). 33. Bangladesh Demographic and Health Survey 2011. Dhaka, Bangladesh and Calverton, Maryland, USA: National Institute of Population Research and Training, Mitra and Associates and ICF International; 2013 (https://dhsprogram.com/pubs/pdf/fr265/fr265. pdf, accessed 20 August 2022), Bangladesh Demographic and Health Survey 2014. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Mitra and Associates and ICF International; 2016 (https:// dhsprogram.com/pubs/pdf/-FR311/FR311.pdf, accessed 28 August 2022), Progotir Pathey Multiple Indicator Cluster Survey 2019. Survey findings report. Dhaka: Bangladesh Bureau of Statistics (BBS); 2019 (https://reliefweb.int/sites/reliefweb. int/files/resources/Bangladesh-MICS-2019-SFR_English.pdf, accessed 20 August 2022), Bhutan Multiple Indicator Survey 2010. Thimphu, Bhutan: National Statistics Bureau; 2011 (https://mics-surveys-prod.s3.amazonaws.com/MICS4/South%20 Asia/Bhutan/2010/Final/Bhutan%202010%20MICS_English.pdf, accessed 20 August 2022), National Family Health Survey (NFHS-3), 2005–2006. Mumbai, India: International Institute for Population Sciences, IIPS/India and Macro international; 2007 (https://dhsprogram.com/publications/publication-FRIND3-DHS-Final-Reports.cfm, accessed 22 August 2022), National Family Health Survey (NFHS-4), 2015–2016. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2017 (https://dhsprogram.com/publications/publication-FR339-DHS-Final-Reports.cfm, accessed 22 August 2022), National Family Health Survey (NFHS-5), 2019–2021. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2022 (https://dhsprogram.com/pubs/pdf/FR375/FR375.pdf, accessed 22 August 2022), Indonesia Demographic and Health Survey 2007. Calverton, Maryland, USA: Statistics Indonesia-Badan Pusat Statistik-BPS and Macro International; 2008 (https:// dhsprogram.com/publications/publication-fr218-dhs-final-reports.cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey 2012. Jakarta, Indonesia: Statistics Indonesia-Badan Pusat Statistik-BPS, National Population and Family Planning Board-BKKBN/Indonesia, Ministry of Health/Indonesia and ICF International; 2013 (https://www.dhsprogram.com/publications/publication-FR275-DHS-Final-Reports. cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey, 2017. Jakarta, Indonesia: National Population and Family Planning Board, Statistics Indonesia, Ministry of Health and ICF; 2018 (https://dhsprogram.com/publications/publication- fr342-dhs-final-reports.cfm, accessed 20 August 2022), Maldives Demographic and Health Survey 2009. Malé, Maldives and Calverton, Maryland: Ministry of Health and Family and ICF Macro; 2010 (https://dhsprogram.com/pubs/pdf/FR237/FR237.pdf, accessed 18 July 2022), Maldives Demographic and Health Survey 2016–2017. Malé, Maldives and Maryland, USA: Ministry of Health and ICF; 2018 (https://dhsprogram. com/pubs/pdf/FR349/FR349.pdf, accessed 28 August 2022), Myanmar Demographic and Health Survey 2015–2016. Naypyitaw, Myanmar: Ministry of Health and Sports- MoHS and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR324/FR324.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2011. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/Nepal and ICF; 2012 (https://dhsprogram. com/pubs/pdf/fr257/fr257%5B13april2012%5D.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2016. Kathmandu, Nepal: Ministry of Health-MoH/ Nepal, New ERA/Nepal and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR336/ FR336.pdf, accessed 28 August 2022), Nepal Multiple Indicator Cluster Survey 2019. Kathmandu, Nepal: Central Bureau of Statistics and UNICEF Nepal; 2020 (https:// mics-surveys-prod.s3.amazonaws.com/MICS6/South%20Asia/Nepal/2019/Survey%20 findings/Nepal-MICS%202019SFR_English.pdf, accessed 28 August 2022), Sri Lanka Demographic and Health Survey 2006–2007. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health care and Nutrition; 2009 (http://www. statistics.gov.lk/Health/StaticalInformation/FinalReport, accessed 18 July 2022), Sri Lanka Demographic and Health Survey 2016. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health, Nutrition and Indigenous Medicine; 2017 (http://www.statistics.gov.lk/Health/StaticalInformation/DemographicAndHealthSurvey- 2016FullReport, accessed 28 August 2022), Thailand Multiple Indicator Cluster Survey 2012. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2013 (https://mics-surveys-prod.s3.amazonaws.com/MICS4/East%20Asia%20 and%20the%20Pacific/Thailand/2012–2013/Summary/Thailand%202012%20MICS% 20Summary_English.pdf, accessed 16 July 2022), Thailand Multiple Indicator Cluster Survey 2015–2016, Final Report. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2016 (https://mics-surveys-prod.s3.amazonaws. com/MICS5/East%20Asia%20and%20the%20Pacific/Thailand/2015–2016/Final/ Thailand%202015–2016%20MICS_En glish.pdf.pdf, accessed 18 July 2022), Thailand Multiple Indicator Cluster Survey 2019, Survey findings report. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2020 (https://mics- surveys-prod.s3.amazonaws.com/MICS6/East%20Asia%20and%20the%20Pacific/ Thailand/2019/Survey%20findings/Thailand%202019%20MICS%20Survey%20 Findings%20Report_National%20%28English%29.pdf, accessed 18 July 2022), Timor-Leste Demographic and Health Survey 2009–2010. Dili, Timor-Leste: National Statistics Directorate, Ministry of Finance/Timor-Leste and ICF Macro; 2010 (https:// dhsprogram.com/pubs/pdf/FR235/FR235.pdf, accessed 26 July 2022) and Timor- Leste Demographic and Health Survey 2016. Dili, Timor-Leste and Rockville, Maryland, USA: General Directorate of Statistics, Ministry of Finance/Timor-Leste and ICF; 2018 (https://dhsprogram.com/pubs/pdf/FR329/FR329.pdf, accessed 28 August 2022). 34. Time Use Pilot Survey 2012. Dhaka: Bangladesh Bureau of Statistics; 2013 (http://bbs.portal.gov.bd/sites/default/files/files/bbs.portal.gov.bd/page/ 96220c5a_5763_4628_9494_950862accd8c/TUSReport2012.pdf, accessed 20 August 2022), Time Use Survey 2021. Dhaka: Bangladesh Bureau of Statistics; 2022 (hard copy), Accounting for unpaid care work in Bhutan. Thimphu, Bhutan: National Commission for Women and Children; 2019 (https://www.ncwc.gov.bt/ publications/UNPAID_CARE_WORK_IN_BHUTAN%20_20191570788312.pdf, accessed 20 August 2022), Time-use in India 2019. New Delhi: Ministry of Statistics and Programme Implementation and National Statistical Office, Government of India; 2020 (https://mospi.gov.in/documents/213904/301563//Report_-TUS_2019_0%20 (1)1605596723155.pdf/625f95d9-d49d-cfe3-b5d6-ee13b893aac7?q=RPCAT, accessed 18 August 2022), Household Income and Expenditure Survey (HIES) Analytical Report III: Employment 2016. Malé’, Maldives: National Bureau of Statistics; 2018 (http://statisticsmaldives.gov.mv/nbs/wp-content/uploads/2018/10/HIES-Report- 2016-Employment-Update-6112018-1.pdf, accessed 18 August 2022), Nesbitt- Ahmed Z, Chopra D. Unpaid care work programme: Nepal progress report (2012–13). Brighton, United Kingdom: Institute of Development Studies; 2014 (https://opendocs. ids.ac.uk/opendocs/bitstream/handle/20.500.12413/3527/ER54.pdf?sequence=1, accessed 18 August 2022), Sri Lanka Time-Use Survey 2017. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Finance, Economy and Policy Development, Government of Sri Lanka; 2020 (http://www.statistics.gov.lk/Resource/ en/LabourForce/Bulletins/TUSBulletin2017.pdf, accessed 12 August 2022), The Time Use Survey in Thailand (2004, 2009 & 2015). Bangkok, Thailand: National Statistical Office; 2016 (http://www.nso.go.th/sites/2014en/Pages/Statistical%20Themes/ Population-Society/Population-Housing/Timeuse.aspx, accessed 20 August 2022) and Final statistical abstract-Timor-Leste survey of living standards 2007. Dili, Timor-Leste: Ministry of Finance; 2008 (http://www.statistics.gov.tl/wp-content/uploads/2013/12/ Timor-Leste-Survey-of-Living-Standards-2007.pdf, accessed 18 August 2022). 35. Life expectancy and healthy life expectancy at birth by sex: data by WHO region. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://apps.who.int/gho/data/view.main. SDG2016LEXREGv?lang=en, accessed 24 August 2022). 36. Life expectancy and healthy life expectancy at birth by sex: data by country. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://apps.who.int/gho/data/view.main.SDG2016LEXv?lang=en, accessed 24 August 2022). 37. Ibid. 38. Cause specific mortality, by sex 2019. In: Disease burden and mortality estimates. Health statistics and information systems. Geneva: World Health Organization; 2022 (https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe- leading-causes-of-death, accessed 24 August 2022). 39. Ibid. 40. Disease specific DALY estimates, by sex 2019. In: Disease burden and mortality estimates. Health statistics and information systems. Geneva: World Health Organization; 2022 (https://www.who.int/data/gho/data/themes/mortality-and-global- health-estimates/global-health-estimates-leading-causes-of-dalys, accessed 24 August 2022). 41. Ibid. 42. Under-five mortality rate: data by WHO region. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://www.who.int/ data/gho/data/indicators/indicator-details/GHO/under-five-mortality-rate-(probability-of- dying-by-age-5-per-1000-live-births), accessed 24 August 2022). 43. Bangladesh Demographic and Health Survey 2014. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Mitra and Associates and ICF International; 2016 (https://dhsprogram.com/pubs/pdf/-FR311/ FR311.pdf, accessed 28 August 2022), Bangladesh Demographic and Health Survey 2017–2018. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Ministry of Health and Family Welfare and ICF 40 International; 2020 (https://dhsprogram.com/pubs/pdf/FR344/FR344.pdf, accessed 28 August 2022), Progotir Pathey Multiple Indicator Cluster Survey 2019. Survey findings report. Dhaka: Bangladesh Bureau of Statistics (BBS); 2019 (https://reliefweb.int/ sites/reliefweb.int/files/resources/Bangladesh-MICS-2019-SFR_English.pdf, accessed 20 August 2022), Bhutan Multiple Indicator Survey 2010. Thimphu, Bhutan: National Statistics Bureau; 2011 (https://mics-surveys-prod.s3.amazonaws.com/MICS4/ South%20Asia/Bhutan/2010/Final/Bhutan%202010%20MICS_English.pdf, accessed 20 August 2022), National Family Health Survey (NFHS-3), 2005–2006. Mumbai, India: International Institute for Population Sciences, IIPS/India and Macro international; 2007 (https://dhsprogram.com/publications/publication-FRIND3-DHS-Final-Reports. cfm, accessed 22 August 2022), National Family Health Survey (NFHS-4), 2015–2016. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2017 (https://dhsprogram.com/publications/publication-FR339-DHS-Final-Reports.cfm, accessed 22 August 2022), National Family Health Survey (NFHS-5), 2019–2021. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2022 (https://dhsprogram.com/pubs/pdf/FR375/FR375.pdf, accessed 22 August 2022), Indonesia Demographic and Health Survey 2007. Calverton, Maryland, USA: Statistics Indonesia-Badan Pusat Statistik-BPS and Macro International; 2008 (https:// dhsprogram.com/publications/publication-fr218-dhs-final-reports.cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey 2012. Jakarta, Indonesia: Statistics Indonesia-Badan Pusat Statistik-BPS, National Population and Family Planning Board-BKKBN/Indonesia, Ministry of Health/Indonesia and ICF International; 2013 (https://www.dhsprogram.com/publications/publication-FR275-DHS-Final- Reports.cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey, 2017. Jakarta, Indonesia: National Population and Family Planning Board, Statistics Indonesia, Ministry of Health and ICF; 2018 (https://dhsprogram.com/publications/ publication-fr342-dhs-final-reports.cfm, accessed 20 August 2022), Maldives Demographic and Health Survey 2009. Malé, Maldives and Calverton, Maryland: Ministry of Health and Family and ICF Macro; 2010 (https://dhsprogram.com/pubs/ pdf/FR237/FR237.pdf, accessed 18 July 2022), Maldives Demographic and Health Survey 2016–2017. Malé, Maldives and Maryland, USA: Ministry of Health and ICF; 2018 (https://dhsprogram.com/pubs/pdf/FR349/FR349.pdf, accessed 28 August 2022), Myanmar Demographic and Health Survey 2015–2016. Naypyitaw, Myanmar: Ministry of Health and Sports-MoHS and ICF; 2017 (https://dhsprogram.com/pubs/ pdf/FR324/FR324.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2014. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/Nepal and UNICEF Nepal; 2015 (https://mics-surveys-prod.s3.amazonaws.com/MICS5/South%20 Asia/Nepal/2014/Final/Nepal%202014%20MICS_English.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2016. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/Nepal and ICF; 2017 (https://dhsprogram.com/pubs/pdf/ FR336/FR336.pdf, accessed 28 August 2022), Nepal Multiple Indicator Cluster Survey 2019. Kathmandu, Nepal: Central Bureau of Statistics and UNICEF Nepal; 2020 (https:// mics-surveys-prod.s3.amazonaws.com/MICS6/South%20Asia/Nepal/2019/Survey%20 findings/Nepal-MICS%202019SFR_English.pdf, accessed 28 August 2022), Sri Lanka Demographic and Health Survey 2006–2007. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health care and Nutrition; 2009 (http://www. statistics.gov.lk/Health/StaticalInformation/FinalReport, accessed 18 July 2022), Sri Lanka Demographic and Health Survey 2016. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health, Nutrition and Indigenous Medicine; 2017 (http://www.statistics.gov.lk/Health/StaticalInformation/DemographicAndHealthSurvey- 2016FullReport, accessed 28 August 2022), Thailand Multiple Indicator Cluster Survey 2012. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2013 (https://mics-surveys-prod.s3.amazonaws.com/MICS4/East%20Asia%20 and%20the%20Pacific/Thailand/2012–2013/Summary/Thailand%202012%20MICS% 20Summary_English.pdf, accessed 16 July 2022), Thailand Multiple Indicator Cluster Survey 2015–2016, Final Report. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2016 (https://mics-surveys-prod.s3.amazonaws. com/MICS5/East%20Asia%20and%20the%20Pacific/Thailand/2015–2016/Final/ Thailand%202015–2016%20MICS_En glish.pdf.pdf, accessed 18 July 2022), Thailand Multiple Indicator Cluster Survey 2019, Survey findings report. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2020 (https://mics- surveys-prod.s3.amazonaws.com/MICS6/East%20Asia%20and%20the%20Pacific/ Thailand/2019/Survey%20findings/Thailand%202019%20MICS%20Survey%20 Findings%20Report_National%20%28English%29.pdf, accessed 18 July 2022), Timor-Leste Demographic and Health Survey 2009–2010. Dili, Timor-Leste: National Statistics Directorate, Ministry of Finance/Timor-Leste and ICF Macro; 2010 (https:// dhsprogram.com/pubs/pdf/FR235/FR235.pdf, accessed 26 July 2022) and Timor- Leste Demographic and Health Survey 2016. Dili, Timor-Leste and Rockville, Maryland, USA: General Directorate of Statistics, Ministry of Finance/Timor-Leste and ICF; 2018 (https://dhsprogram.com/pubs/pdf/FR329/FR329.pdf, accessed 28 August 2022). 44. Ibid. 45. Ibid. 46. Ibid. 47. Bangladesh Demographic and Health Survey 2014. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Mitra and Associates and ICF International; 2016 (https://dhsprogram.com/pubs/pdf/-FR311/ FR311.pdf, accessed 28 August 2022), Bangladesh Demographic and Health Survey 2017–2018. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Ministry of Health and Family Welfare and ICF International; 2020 (https://dhsprogram.com/pubs/pdf/FR344/FR344.pdf, accessed 28 August 2022), Progotir Pathey Multiple Indicator Cluster Survey 2019. Survey findings report. Dhaka: Bangladesh Bureau of Statistics (BBS); 2019 (https://reliefweb. int/sites/reliefweb.int/files/resources/Bangladesh-MICS-2019-SFR_English.pdf, accessed 20 August 2022), Bhutan Multiple Indicator Survey 2010. Thimphu, Bhutan: National Statistics Bureau; 2011 (https://mics-surveys-prod.s3.amazonaws.com/ MICS4/South%20Asia/Bhutan/2010/Final/Bhutan%202010%20MICS_English.pdf, accessed 20 August 2022), National Nutrition Survey (NNS) 2015. Thimpu, Bhutan: Nutrition Programme, Department of Public Health, Ministry of Health; 2016 (http:// maternalnutritionsouthasia.com/wp-content/uploads/Bhutan-NNS-2015.pdf, accessed 20 August 2022), National Family Health Survey (NFHS-3), 2005–2006. Mumbai, India: International Institute for Population Sciences, IIPS/India and Macro international; 2007 (https://dhsprogram.com/publications/publication-FRIND3-DHS-Final-Reports. cfm, accessed 22 August 2022), National Family Health Survey (NFHS-4), 2015–2016. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2017 (https://dhsprogram.com/publications/publication-FR339-DHS-Final-Reports.cfm, accessed 22 August 2022), National Family Health Survey (NFHS-5), 2019–2021. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2022 (https://dhsprogram.com/pubs/pdf/FR375/FR375.pdf, accessed 22 August 2022), The 2018 Indonesia Basic Health Survey. Jakarta, Indonesia: National Institute of Health Research and Development, Ministry of Health; 2019 (https://www.litbang.kemkes. go.id/laporan-riset-kesehatan-dasar-riskesdas/, accessed 30 August 2022), Maldives Demographic and Health Survey 2009. Malé, Maldives and Calverton, Maryland: Ministry of Health and Family and ICF Macro; 2010 (https://dhsprogram.com/pubs/pdf/ FR237/FR237.pdf, accessed 18 July 2022), Maldives Demographic and Health Survey 2016–2017. Malé, Maldives and Maryland, USA: Ministry of Health and ICF; 2018 (https://dhsprogram.com/pubs/pdf/FR349/FR349.pdf, accessed 28 August 2022), Myanmar Demographic and Health Survey 2015–2016. Naypyitaw, Myanmar: Ministry of Health and Sports-MoHS and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR324/ FR324.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2011. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/Nepal and ICF; 2012 (https://dhsprogram.com/pubs/pdf/fr257/fr257%5B13april2012%5D.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2016. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/Nepal and ICF; 2017 (https://dhsprogram. com/pubs/pdf/FR336/FR336.pdf, accessed 28 August 2022), Nepal Multiple Indicator Cluster Survey 2019. Kathmandu, Nepal: Central Bureau of Statistics and UNICEF Nepal; 2020 (https://mics-surveys-prod.s3.amazonaws.com/MICS6/South%20Asia/ Nepal/2019/Survey%20findings/Nepal-MICS%202019SFR_English.pdf, accessed 28 August 2022), Sri Lanka Demographic and Health Survey 2006–2007. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health care and Nutrition; 2009 (http://www.statistics.gov.lk/Health/StaticalInformation/FinalReport, accessed 18 July 2022), Sri Lanka Demographic and Health Survey 2016. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health, Nutrition and Indigenous Medicine; 2017 (http://www.statistics.gov.lk/Health/StaticalInformation/ DemographicAndHealthSurvey-2016FullReport, accessed 28 August 2022), Thailand Multiple Indicator Cluster Survey 2012. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2013 (https://mics-surveys-prod.s3.amazonaws. com/MICS4/East%20Asia%20and%20the%20Pacific/Thailand/2012–2013/Summary/ Thailand%202012%20MICS% 20Summary_English.pdf, accessed 16 July 2022), Thailand Multiple Indicator Cluster Survey 2015–2016, Final Report. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2016 (https:// mics-surveys-prod.s3.amazonaws.com/MICS5/East%20Asia%20and%20the%20 Pacific/Thailand/2015–2016/Final/Thailand%202015–2016%20MICS_En glish.pdf. pdf, accessed 18 July 2022), Thailand Multiple Indicator Cluster Survey 2019, Survey findings report. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2020 (https://mics-surveys-prod.s3.amazonaws.com/MICS6/East%20 Asia%20and%20the%20Pacific/Thailand/2019/Survey%20findings/Thailand%20 2019%20MICS%20Survey%20Findings%20Report_National%20%28English%29.pdf, accessed 18 July 2022), Timor-Leste Food and Nutrition Survey 2013. Dilli, Timore- Leste: Ministry of Health; 2015 (https://dl.tufts.edu/pdfviewer/ng451v34w/cz30q4797, accessed 13 July 2023) and Timor-Leste Food and Nutrition Survey 2020. Dilli, Timore-Leste: Ministry of Health; 2022 (https://www.unicef.org/timorleste/media/4606/ file/Digital_Eng_TL%20Food%20Nutrition%20Survey%202020_FINAL_20%204%20 2022.pdf, accessed 13 July 2023). 48. Ibid. 49. Ibid. 50. Ibid. 41 51. Bangladesh Demographic and Health Survey 2014. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Mitra and Associates and ICF International; 2016 (https://dhsprogram.com/pubs/pdf/-FR311/ FR311.pdf, accessed 28 August 2022), Bangladesh Demographic and Health Survey 2017–2018. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Ministry of Health and Family Welfare and ICF International; 2020 (https://dhsprogram.com/pubs/pdf/FR344/FR344.pdf, accessed 28 August 2022), Progotir Pathey Multiple Indicator Cluster Survey 2019. Survey findings report. Dhaka: Bangladesh Bureau of Statistics (BBS); 2019 (https:// reliefweb.int/sites/reliefweb.int/files/resources/Bangladesh-MICS-2019-SFR_English. pdf, accessed 20 August 2022), Bhutan Multiple Indicator Survey 2010. Thimphu, Bhutan: National Statistics Bureau; 2011 (https://mics-surveys-prod.s3.amazonaws. com/MICS4/South%20Asia/Bhutan/2010/Final/Bhutan%202010%20MICS_English. pdf, accessed 20 August 2022), National Family Health Survey (NFHS-3), 2005–06. Mumbai, India: International Institute for Population Sciences, IIPS/India and Macro international; 2007 (https://dhsprogram.com/publications/publication-FRIND3- DHS-Final-Reports.cfm, accessed 22 August 2022), National Family Health Survey (NFHS-4), 2015–2016. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2017 (https://dhsprogram.com/publications/publication-FR339- DHS-Final-Reports.cfm, accessed 22 August 2022), National Family Health Survey (NFHS-5), 2019–2021. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2022 (https://dhsprogram.com/pubs/pdf/FR375/FR375.pdf, accessed 22 August 2022), Indonesia Demographic and Health Survey 2007. Calverton, Maryland, USA: Statistics Indonesia-Badan Pusat Statistik-BPS and Macro International; 2008 (https://dhsprogram.com/publications/publication-fr218-dhs-final- reports.cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey 2012. Jakarta, Indonesia: Statistics Indonesia-Badan Pusat Statistik-BPS, National Population and Family Planning Board-BKKBN/Indonesia, Ministry of Health/Indonesia and ICF International; 2013 (https://www.dhsprogram.com/publications/publication- FR275-DHS-Final-Reports.cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey, 2017. Jakarta, Indonesia: National Population and Family Planning Board, Statistics Indonesia, Ministry of Health and ICF; 2018 (https://dhsprogram. com/publications/publication-fr342-dhs-final-reports.cfm, accessed 20 August 2022), Maldives Demographic and Health Survey 2009; Malé, Maldives and Calverton, Maryland: Ministry of Health and Family and ICF Macro; 2010 (https://dhsprogram. com/pubs/pdf/FR237/FR237.pdf, accessed 18 July 2022), Maldives Demographic and Health Survey 2016–2017. Malé, Maldives and Maryland, USA: Ministry of Health and ICF; 2018 (https://dhsprogram.com/pubs/pdf/FR349/FR349.pdf, accessed 28 August 2022), Myanmar Demographic and Health Survey 2015–2016. Naypyitaw, Myanmar: Ministry of Health and Sports-MoHS and ICF; 2017 (https://dhsprogram.com/pubs/ pdf/FR324/FR324.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2011. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/Nepal and ICF; 2012 (https://dhsprogram.com/pubs/pdf/fr257/fr257%5B13april2012%5D.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2016. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/Nepal and ICF; 2017 (https:// dhsprogram.com/pubs/pdf/FR336/FR336.pdf, accessed 28 August 2022), Nepal Multiple Indicator Cluster Survey 2019. Kathmandu, Nepal: Central Bureau of Statistics and UNICEF Nepal; 2020 (https://mics-surveys-prod.s3.amazonaws.com/MICS6/ South%20Asia/Nepal/2019/Survey%20findings/Nepal-MICS%202019SFR_English.pdf, accessed 28 August 2022), Sri Lanka Demographic and Health Survey 2006–2007. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health care and Nutrition; 2009 (http://www.statistics.gov.lk/Health/StaticalInformation/ FinalReport, accessed 18 July 2022), Thailand Multiple Indicator Cluster Survey 2012. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2013 (https://mics-surveys-prod.s3.amazonaws.com/MICS4/East%20Asia%20 and%20the%20Pacific/Thailand/2012–2013/Summary/Thailand%202012%20MICS% 20Summary_English.pdf, accessed 16 July 2022), Thailand Multiple Indicator Cluster Survey 2015–2016, Final Report. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2016 (https://mics-surveys-prod.s3.amazonaws. com/MICS5/East%20Asia%20and%20the%20Pacific/Thailand/2015–2016/Final/ Thailand%202015–2016%20MICS_En glish.pdf.pdf, accessed 18 July 2022), Thailand Multiple Indicator Cluster Survey 2019, Survey findings report. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2020 (https://mics-surveys-prod.s3.amazonaws.com/MICS6/East%20Asia%20and%20 the%20Pacific/Thailand/2019/Survey%20findings/Thailand%202019%20MICS%20 Survey%20Findings%20Report_National%20%28English%29.pdf, accessed 18 July 2022), Timor-Leste Demographic and Health Survey 2009–2010. Dili, Timor-Leste: National Statistics Directorate, Ministry of Finance/Timor-Leste and ICF Macro; 2010 (https://dhsprogram.com/pubs/pdf/FR235/FR235.pdf, accessed 26 July 2022) and Timor-Leste Demographic and Health Survey 2016. Dili, Timor-Leste and Rockville, Maryland, USA: General Directorate of Statistics, Ministry of Finance/Timor-Leste and ICF; 2018 (https://dhsprogram.com/pubs/pdf/FR329/FR329.pdf, accessed 28 August 2022). 52. Ibid. 53. Ibid. 54. Adolescent fertility rate: data by WHO region. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://www.who. int/data/gho/data/indicators/indicator-details/GHO/adolescent-birth-rate-(per-1000- women-aged-15-19-years), accessed 24 August 2022). 55. Bangladesh Demographic and Health Survey 2014. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Mitra and Associates and ICF International; 2016 (https://dhsprogram.com/pubs/pdf/-FR311/ FR311.pdf, accessed 28 August 2022), Bangladesh Demographic and Health Survey 2017–2018. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Ministry of Health and Family Welfare and ICF International; 2020 (https://dhsprogram.com/pubs/pdf/FR344/FR344.pdf, accessed 28 August 2022), Progotir Pathey Multiple Indicator Cluster Survey 2019. Survey findings report. Dhaka: Bangladesh Bureau of Statistics (BBS); 2019 (https://reliefweb.int/ sites/reliefweb.int/files/resources/Bangladesh-MICS-2019-SFR_English.pdf, accessed 20 August 2022), Bhutan Multiple Indicator Survey 2010. Thimphu, Bhutan: National Statistics Bureau; 2011 (https://mics-surveys-prod.s3.amazonaws.com/MICS4/ South%20Asia/Bhutan/2010/Final/Bhutan%202010%20MICS_English.pdf, accessed 20 August 2022), National Family Health Survey (NFHS-3), 2005–2006. Mumbai, India: International Institute for Population Sciences, IIPS/India and Macro international; 2007 (https://dhsprogram.com/publications/publication-FRIND3-DHS-Final-Reports. cfm, accessed 22 August 2022), National Family Health Survey (NFHS-4), 2015–2016. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2017 (https://dhsprogram.com/publications/publication-FR339-DHS-Final-Reports.cfm, accessed 22 August 2022), National Family Health Survey (NFHS-5), 2019–2021. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2022 (https://dhsprogram.com/pubs/pdf/FR375/FR375.pdf, accessed 22 August 2022), Indonesia Demographic and Health Survey 2007. Calverton, Maryland, USA: Statistics Indonesia-Badan Pusat Statistik-BPS and Macro International; 2008 (https:// dhsprogram.com/publications/publication-fr218-dhs-final-reports.cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey 2012. Jakarta, Indonesia: Statistics Indonesia-Badan Pusat Statistik-BPS, National Population and Family Planning Board-BKKBN/Indonesia, Ministry of Health/Indonesia and ICF International; 2013 (https://www.dhsprogram.com/publications/publication-FR275-DHS-Final-Reports.cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey, 2017. Jakarta, Indonesia: National Population and Family Planning Board, Statistics Indonesia, Ministry of Health and ICF; 2018 (https://dhsprogram.com/publications/publication-fr342- dhs-final-reports.cfm, accessed 20 August 2022), Maldives Demographic and Health Survey 2009. Malé, Maldives and Calverton, Maryland: Ministry of Health and Family and ICF Macro; 2010 (https://dhsprogram.com/pubs/pdf/FR237/FR237.pdf, accessed 18 July 2022), Maldives Demographic and Health Survey 2016–2017. Malé, Maldives and Maryland, USA: Ministry of Health and ICF; 2018 (https://dhsprogram.com/pubs/ pdf/FR349/FR349.pdf, accessed 28 August 2022), Myanmar Demographic and Health Survey 2015–2016. Naypyitaw, Myanmar: Ministry of Health and Sports-MoHS and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR324/FR324.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2011. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/Nepal and ICF; 2012 (https://dhsprogram.com/pubs/pdf/ fr257/fr257%5B13april2012%5D.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2016. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/ Nepal and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR336/FR336.pdf, accessed 28 August 2022), Nepal Multiple Indicator Cluster Survey 2019. Kathmandu, Nepal: Central Bureau of Statistics and UNICEF Nepal; 2020 (https://mics-surveys-prod. s3.amazonaws.com/MICS6/South%20Asia/Nepal/2019/Survey%20findings/Nepal- MICS%202019SFR_English.pdf, accessed 28 August 2022), Sri Lanka Demographic and Health Survey 2006–2007. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health care and Nutrition; 2009 (http://www.statistics.gov. lk/Health/StaticalInformation/FinalReport, accessed 18 July 2022), Thailand Multiple Indicator Cluster Survey 2012. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2013 (https://mics-surveys-prod.s3.amazonaws. com/MICS4/East%20Asia%20and%20the%20Pacific/Thailand/2012–2013/Summary/ Thailand%202012%20MICS% 20Summary_English.pdf, accessed 16 July 2022), Thailand Multiple Indicator Cluster Survey 2015–2016, Final Report. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2016 (https:// mics-surveys-prod.s3.amazonaws.com/MICS5/East%20Asia%20and%20the%20 Pacific/Thailand/2015–2016/Final/Thailand%202015–2016%20MICS_En glish.pdf. pdf, accessed 18 July 2022), Thailand Multiple Indicator Cluster Survey 2019, Survey findings report. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2020 (https://mics-surveys-prod.s3.amazonaws.com/MICS6/East%20 Asia%20and%20the%20Pacific/Thailand/2019/Survey%20findings/Thailand%20 2019%20MICS%20Survey%20Findings%20Report_National%20%28English%29.pdf, accessed 18 July 2022), Timor-Leste Demographic and Health Survey 2009–2010. Dili, Timor-Leste: National Statistics Directorate, Ministry of Finance/Timor-Leste and ICF Macro; 2010 (https://dhsprogram.com/pubs/pdf/FR235/FR235.pdf, accessed 26 42 July 2022) and Timor-Leste Demographic and Health Survey 2016. Dili, Timor-Leste and Rockville, Maryland, USA: General Directorate of Statistics, Ministry of Finance/ Timor-Leste and ICF; 2018 (https://dhsprogram.com/pubs/pdf/FR329/FR329.pdf, accessed 28 August 2022). 56. Ibid. 57. Ibid. 58. Ibid. 59. Trends in maternal mortality ratio: data by WHO region. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://apps. who.int/gho/data/view.main.1370?lang=en, accessed 24 August 2022). 60. Trends in maternal mortality ratio: data by country. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://apps.who.int/ gho/data/node.main.15, accessed 24 August 2022). 61. Prevalence of overweight among adults: data by WHO region. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://www.who.int/data/gho/data/indicators/indicator-details/GHO/prevalence-of- overweight-among-adults-bmi-=-25-(age-standardized-estimate)-(-), accessed 24 August 2022). 62. Noncommunicable disease risk factor survey, Bangladesh 2010. Dhaka: World Health Organization Country Office for Bangladesh, Directorate General of Health Services and Ministry of Health and Family Welfare; 2011 (https://www.who.int/ncds/surveillance/ steps/2010_STEPS_Report_Bangladesh.pdf, accessed 28 July 2022), Zaman MM, Bhuiyan MR, Karim MN, Zaman M, Rahman MM, et al. Clustering of noncommunicable disease risk factors in Bangladeshi adults: an analysis of STEPS survey 2013. BMC Public Health 2015; 15:659. doi:10.1186/s12889-015-1938-4 (https://www.ncbi.nlm. nih.gov/pmc/articles/PMC4501055/, accessed 28 July 2022), National STEPS survey for noncommunicable disease risk factors in Bangladesh 2018. Dhaka: World Health Organization Country Office for Bangladesh, Directorate General of Health Services and Ministry of Health and Family Welfare; 2019 (https://cdn.who.int/media/docs/ default-source/ncds/ncd-surveillance/data-reporting/bangladesh/steps-ban-2018-eng. pdf?sfvrsn=964a03f7_1&download=true, accessed 28 July 2022), National survey for noncommunicable disease risk factors and mental health using WHO STEPS approach in Bhutan 2014. New Delhi: WHO Regional Office for South-East Asia; 2015 (https://www.who.int/ncds/surveillance/steps/Bhutan_2014_STEPS_Report. pdf, accessed 27 August 2022), Noncommunicable disease risk factors: Bhutan STEPS survey report 2019. Thimpu: Ministry of Health, Royal Government of Bhutan; 2020 (https://cdn.who.int/media/docs/default-source/searo/ncd/noncommunicable- disease-risk-factors-bhutan-steps-survey-report-2019.pdf, accessed 27 August 2022), ICMR-WHO multi-centric study on risk factors for noncommunicable diseases based on STEP-wise approach 2004. New Delhi: WHO India office; 2006 (https://www. who.int/ncds/surveillance/steps/IndiaSTEPSReport_6Centers.pdf; accessed 28 July 2022), National noncommunicable disease monitoring survey (NNMS) 2017–2018. Bengaluru, New Delhi: NCDIR, ICMR and Ministry of Health & Family Welfare; 2020 (https://cdn.who.int/media/docs/default-source/ncds/ncd-surveillance/data-reporting/ india/india-nnms-2017–2018-factsheet.pdf?sfvrsn=a3c7547b_1&download=true, accessed 28 July 2022), Integrated community-based intervention on major NCDs in Depok municipality baseline survey 2003. Jakarta, Indonesia: NIHRD Ministry of Health, Republic of Indonesia and WHO; 2003 (https://www.who.int/ncds/surveillance/ steps/IndonesiaSTEPSReport2003.PDF?ua=1; accessed 19 July 2022), Monitoring and evaluation of the integrated community-based intervention for the prevention of NCD in Depok, West Java, Indonesia 2005–2006. Jakarta, Indonesia: NIHRD Ministry of Health, Republic of Indonesia and WHO; 2006 (https://www.who.int/ ncds/surveillance/steps/STEPS_Report_Indonesia_Depok_2006.pdf, accessed 19 July 2022), Survey on noncommunicable disease risk factors Maldives, 2004. Malé. Maldives: Ministry of Health; 2005 (https://www.who.int/ncds/surveillance/steps/ MaldivesSTEPSReport2004.pdf, accessed 27 July 2022), WHO STEPS survey on risk factors for noncommunicable diseases Maldives, 2011. New Delhi, India: WHO Regional Office for South-East Asia; 2014 (https://www.who.int/ncds/surveillance/ steps/MaldivesSTEPSReport2011.pdf, accessed 27 July 2022), Noncommunicable disease risk factor survey 2009. New Delhi: WHO Regional Office for South-East Asia; 2011 (https://www.who.int/ncds/surveillance/steps/2009_STEPS_Survey_Myanmar. pdf, accessed 21 July 2022), Report on national survey on diabetes mellitus and risk factors for noncommunicable diseases in Myanmar 2014. Naypyitaw, Myanmar: Ministry of Health; 2014 (https://www.who.int/chp/steps/Myanmar_2014_STEPS_ FactSheet.pdf?ua=1, accessed 21 July 2022), Nepal noncommunicable disease risk factor survey 2007/08. Kathmandu, Nepal: Ministry of Health and Population, Government of Nepal, Society for Local Integrated Development Nepal (SOLID Nepal) and WHO; 2009 (https://www.who.int/chp/-steps/Nepal_2007_STEPS_Report. pdf?ua=1, accessed 15 July 2022), Noncommunicable diseases risk factors, STEPS survey Nepal 2012–2013. Kathmandu, Nepal: Nepal Health Research Council; 2014 (https://www.who.int/chp/steps/2012–2013_Nepal_STEPS_Report.pdf?ua=1, accessed 15 July 2022), Report of noncommunicable disease risk factors: STEPS survey Nepal 2019. Kathmandu: Nepal Health Research Council; 2020 (https:// extranet.who.int/ncdsmicrodata/index.php/catalog/771/download/5377, accessed 15 July 2022), National noncommunicable disease risk factor survey 2006. Colombo, Sri Lanka: Ministry of Health care and Nutrition; 2008 (https://www.who.int/ncds/ surveillance/steps/2006_STEPS_Survey_SriLanka.pdf, accessed 12 July 2022), Noncommunicable disease risk factor survey 2015. Colombo, Sri Lanka: Ministry of Health, Nutrition and Indigenous Medicine; 2015 (https://www.who.int/ncds/ surveillance/steps/STEPS-report-2015-Sri-Lanka.pdf, accessed 12 July 2022), National survey for noncommunicable disease risk factors and injuries using WHO STEPS approach in Timor-Leste-2014. New Delhi, India: Regional Office for South-East Asia, World Health Organization; 2015 (https://www.who.int/ncds/surveillance/steps/ Timor-Leste_2014_STEPS_Report.pdf, accessed 24 July 2022) and prevalence of overweight among adults, by sex: data by country. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://www.who. int/data/gho/data/indicators/indicator-details/GHO/prevalence-of-overweight-among- adults-bmi-=-25-(age-standardized-estimate)-(-), accessed 25 July 2022). 63. Prevalence of obesity among adults: data by WHO region. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://www. who.int/data/gho/data/indicators/indicator-details/GHO/prevalence-of-obesity-among- adults-bmi-=-30-(age-standardized-estimate)-(-), accessed 24 August 2022). 64. Noncommunicable disease risk factor survey, Bangladesh 2010. Dhaka: World Health Organization Country Office for Bangladesh, Directorate General of Health Services and Ministry of Health and Family Welfare; 2011 (https://www.who.int/ncds/surveillance/ steps/2010_STEPS_Report_Bangladesh.pdf, accessed 28 July 2022), Zaman MM, Bhuiyan MR, Karim MN, Zaman M, Rahman MM, et al. Clustering of noncommunicable disease risk factors in Bangladeshi adults: an analysis of STEPS survey 2013. BMC Public Health 2015; 15:659. doi:10.1186/s12889-015-1938-4 (https://www.ncbi.nlm. nih.gov/pmc/articles/PMC4501055/, accessed 28 July 2022), National STEPS survey for noncommunicable disease risk factors in Bangladesh 2018. Dhaka: World Health Organization Country Office for Bangladesh, Directorate General of Health Services and Ministry of Health and Family Welfare; 2019 (https://cdn.who.int/media/docs/ default-source/ncds/ncd-surveillance/data-reporting/bangladesh/steps-ban-2018-eng. pdf?sfvrsn=964a03f7_1&download=true, accessed 28 July 2022), National survey for noncommunicable disease risk factors and mental health using WHO STEPS approach in Bhutan 2014. New Delhi: WHO Regional Office for South-East Asia; 2015 (https://www.who.int/ncds/surveillance/steps/Bhutan_2014_STEPS_Report. pdf, accessed 27 August 2022), Noncommunicable disease risk factors: Bhutan STEPS survey report 2019. Thimpu: Ministry of Health, Royal Government of Bhutan; 2020 (https://cdn.who.int/media/docs/default-source/searo/ncd/noncommunicable- disease-risk-factors-bhutan-steps-survey-report-2019.pdf, accessed 27 August 2022), ICMR-WHO multi-centric study on risk factors for noncommunicable diseases based on STEP-wise approach 2004. New Delhi: WHO India office; 2006 (https://www. who.int/ncds/surveillance/steps/IndiaSTEPSReport_6Centers.pdf; accessed 28 July 2022), National noncommunicable disease monitoring survey (NNMS) 2017–2018. Bengaluru, New Delhi: NCDIR, ICMR and Ministry of Health & Family Welfare; 2020 (https://cdn.who.int/media/docs/default-source/ncds/ncd-surveillance/data-reporting/ india/india-nnms-2017–2018-factsheet.pdf?sfvrsn=a3c7547b_1&download=true, accessed 28 July 2022), Integrated community-based intervention on major NCDs in Depok municipality baseline survey 2003. Jakarta, Indonesia: NIHRD Ministry of Health, Republic of Indonesia and WHO; 2003 (https://www.who.int/ncds/surveillance/ steps/IndonesiaSTEPSReport2003.PDF?ua=1; accessed 19 July 2022), Monitoring and evaluation of the integrated community-based intervention for the prevention of NCD in Depok, West Java, Indonesia 2005–2006. Jakarta, Indonesia: NIHRD Ministry of Health, Republic of Indonesia and WHO; 2006 (https://www.who.int/ ncds/surveillance/steps/STEPS_Report_Indonesia_Depok_2006.pdf, accessed 19 July 2022), Survey on noncommunicable disease risk factors Maldives, 2004. Malé. Maldives: Ministry of Health; 2005 (https://www.who.int/ncds/surveillance/steps/ MaldivesSTEPSReport2004.pdf, accessed 27 July 2022), WHO STEPS survey on risk factors for noncommunicable diseases Maldives, 2011. New Delhi, India: WHO Regional Office for South-East Asia; 2014 (https://www.who.int/ncds/surveillance/ steps/MaldivesSTEPSReport2011.pdf, accessed 27 July 2022), Noncommunicable disease risk factor survey 2009. New Delhi: WHO Regional Office for South-East Asia; 2011 (https://www.who.int/ncds/surveillance/steps/2009_STEPS_Survey_Myanmar. pdf, accessed 21 July 2022), Report on national survey on diabetes mellitus and risk factors for noncommunicable diseases in Myanmar 2014. Naypyitaw, Myanmar: Ministry of Health; 2014 (https://www.who.int/chp/steps/Myanmar_2014_STEPS_ FactSheet.pdf?ua=1, accessed 21 July 2022), Nepal noncommunicable disease risk factor survey 2007/08. Kathmandu, Nepal: Ministry of Health and Population, Government of Nepal, Society for Local Integrated Development Nepal (SOLID Nepal) and WHO; 2009 (https://www.who.int/chp/-steps/Nepal_2007_STEPS_Report. pdf?ua=1, accessed 15 July 2022), Noncommunicable diseases risk factors, STEPS survey Nepal 2012–2013. Kathmandu, Nepal: Nepal Health Research Council; 2014 43 (https://www.who.int/chp/steps/2012–2013_Nepal_STEPS_Report.pdf?ua=1, accessed 15 July 2022), Report of noncommunicable disease risk factors: STEPS survey Nepal 2019. Kathmandu: Nepal Health Research Council; 2020 (https:// extranet.who.int/ncdsmicrodata/index.php/catalog/771/download/5377, accessed 15 July 2022), National noncommunicable disease risk factor survey 2006. Colombo, Sri Lanka: Ministry of Health care and Nutrition; 2008 (https://www.who.int/ncds/ surveillance/steps/2006_STEPS_Survey_SriLanka.pdf, accessed 12 July 2022), Noncommunicable disease risk factor survey 2015. Colombo, Sri Lanka: Ministry of Health, Nutrition and Indigenous Medicine; 2015 (https://www.who.int/ncds/ surveillance/steps/STEPS-report-2015-Sri-Lanka.pdf, accessed 12 July 2022), National survey for noncommunicable disease risk factors and injuries using WHO STEPS approach in Timor-Leste-2014. New Delhi, India: Regional Office for South-East Asia, World Health Organization; 2015 (https://www.who.int/ncds/surveillance/steps/ Timor-Leste_2014_STEPS_Report.pdf, accessed 24 July 2022) and prevalence of obesity among adults, by sex: data by country. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://www.who.int/ data/gho/data/indicators/indicator-details/GHO/prevalence-of-obesity-among-adults- bmi-=-30-(age-standardized-estimate)-(-), accessed 25 July 2022). 65. Prevalence of insufficient physical activity among adults: data by WHO region. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://apps.who.int/gho/data/view.main.2482?lang=en, accessed 24 August 2022). 66. Noncommunicable disease risk factor survey, Bangladesh 2010. Dhaka: World Health Organization Country Office for Bangladesh, Directorate General of Health Services and Ministry of Health and Family Welfare; 2011 (https://www.who.int/ ncds/surveillance/steps/2010_STEPS_Report_Bangladesh.pdf, accessed 28 July 2022), National survey for noncommunicable disease risk factors and mental health using WHO STEPS approach in Bhutan 2014. New Delhi: WHO Regional Office for South-East Asia; 2015 (https://www.who.int/ncds/surveillance/steps/ Bhutan_2014_STEPS_Report.pdf, accessed 27 August 2022), Monitoring and evaluation of the integrated community-based intervention for the prevention of NCD in Depok, West Java, Indonesia 2005–2006. Jakarta, Indonesia: NIHRD Ministry of Health, Republic of Indonesia and WHO; 2006 (https://www.who.int/ncds/surveillance/ steps/STEPS_Report_Indonesia_Depok_2006.pdf, accessed 19 July 2022), WHO STEPS survey on risk factors for noncommunicable diseases Maldives, 2011. New Delhi, India: WHO Regional Office for South-East Asia; 2014 (https://www.who.int/ ncds/surveillance/steps/MaldivesSTEPSReport2011.pdf, accessed 27 July 2022), Report on national survey on diabetes mellitus and risk factors for noncommunicable diseases in Myanmar 2014. Naypyitaw, Myanmar: Ministry of Health; 2014 (https:// www.who.int/chp/steps/Myanmar_2014_STEPS_FactSheet.pdf?ua=1, accessed 21 July 2022), Noncommunicable diseases risk factors, STEPS survey Nepal 2012–2013. Kathmandu, Nepal: Nepal Health Research Council; 2014 (https://www.who.int/ chp/steps/2012–2013_Nepal_STEPS_Report.pdf?ua=1, accessed 15 July 2022), Noncommunicable disease risk factor survey 2015. Colombo, Sri Lanka: Ministry of Health, Nutrition and Indigenous Medicine; 2015 (https://www.who.int/ncds/ surveillance/steps/STEPS-report-2015-Sri-Lanka.pdf, accessed 12 July 2022) and National survey for noncommunicable disease risk factors and injuries using WHO STEPS approach in Timor-Leste-2014. New Delhi, India: Regional Office for South-East Asia, World Health Organization; 2015 (https://www.who.int/ncds/surveillance/steps/ Timor-Leste_2014_STEPS_Report.pdf, accessed 24 July 2022). 67. Age-standardized prevalence of current tobacco use among adults, by sex: data by country. In: Global Health Observatory data repository [database]. Geneva, World Health Organization; 2022 (https://apps.who.int/gho/data/node.main. TOBAGESTDCURR?lang=en, accessed 25 August 2022), National survey for noncommunicable disease risk factors and mental health using WHO STEPS approach in Bhutan 2014. New Delhi: WHO Regional Office for South-East Asia; 2015 (https:// www.who.int/ncds/surveillance/steps/Bhutan_2014_STEPS_Report.pdf, accessed 27 August 2022) and Noncommunicable disease risk factors: Bhutan STEPS Survey Report 2019. Thimpu: Ministry of Health, Royal Government of Bhutan; 2020 (https:// cdn.who.int/media/docs/default-source/searo/ncd/noncommunicable-disease-risk- factors-bhutan-steps-survey-report-2019.pdf, accessed 27 August 2022). 68. Noncommunicable disease risk factor survey, Bangladesh 2010. Dhaka: World Health Organization Country Office for Bangladesh, Directorate General of Health Services and Ministry of Health and Family Welfare; 2011 (https://www.who.int/ncds/surveillance/ steps/2010_STEPS_Report_Bangladesh.pdf, accessed 28 July 2022), Zaman MM, Bhuiyan MR, Karim MN, Zaman M, Rahman MM, et al. Clustering of noncommunicable disease risk factors in Bangladeshi adults: an analysis of STEPS survey 2013. BMC Public Health 2015; 15:659. doi:10.1186/s12889-015-1938-4 (https://www.ncbi. nlm.nih.gov/pmc/articles/PMC4501055/, accessed 28 July 2022), National STEPS survey for noncommunicable disease risk factors in Bangladesh 2018. Dhaka: World Health Organization Country Office for Bangladesh, Directorate General of Health Services and Ministry of Health and Family Welfare; 2019 (https://cdn.who. int/media/docs/default-source/ncds/ncd-surveillance/data-reporting/bangladesh/ steps-ban-2018-eng.pdf?sfvrsn=964a03f7_1&download=true, accessed 28 July 2022), National survey for noncommunicable disease risk factors and mental health using WHO STEPS approach in Bhutan 2014. New Delhi: WHO Regional Office for South-East Asia; 2015 (https://www.who.int/ncds/surveillance/steps/ Bhutan_2014_STEPS_Report.pdf, accessed 27 August 2022), Noncommunicable Disease Risk Factors: Bhutan STEPS Survey Report 2019. Thimpu: Ministry of Health, Royal Government of Bhutan; 2020 (https://cdn.who.int/media/docs/default-source/ searo/ncd/noncommunicable-disease-risk-factors-bhutan-steps-survey-report-2019. pdf, accessed 27 August 2022), National Family Health Survey (NFHS-3), 2005–2006. Mumbai, India: International Institute for Population Sciences, IIPS/India and Macro international; 2007 (https://dhsprogram.com/publications/publication-FRIND3- DHS-Final-Reports.cfm, accessed 22 August 2022), National Family Health Survey (NFHS-4), 2015–2016. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2017 (https://dhsprogram.com/publications/publication-FR339- DHS-Final-Reports.cfm, accessed 22 August 2022), National Family Health Survey (NFHS-5), 2019–2021. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2022 (https://dhsprogram.com/pubs/pdf/FR375/FR375.pdf, accessed 22 August 2022), Integrated community-based intervention on major NCDs in Depok municipality baseline survey 2003. Jakarta, Indonesia: NIHRD Ministry of Health, Republic of Indonesia and WHO; 2003 (https://www.who.int/ncds/surveillance/ steps/IndonesiaSTEPSReport2003.PDF?ua=1; accessed 19 July 2022), Monitoring and evaluation of the integrated community-based intervention for the prevention of NCD in Depok, West Java, Indonesia 2005–2006. Jakarta, Indonesia: NIHRD Ministry of Health, Republic of Indonesia and WHO; 2006 (https://www.who.int/ncds/ surveillance/steps/STEPS_Report_Indonesia_Depok_2006.pdf, accessed 19 July 2022), Survey on Noncommunicable Disease Risk Factors Maldives, 2004. Malé. Maldives: Ministry of Health; 2005 (https://www.who.int/ncds/surveillance/steps/ MaldivesSTEPSReport2004.pdf, accessed 27 July 2022), WHO STEPS survey on risk factors for noncommunicable diseases Maldives, 2011. New Delhi, India: WHO Regional Office for South-East Asia; 2014 (https://www.who.int/ncds/surveillance/ steps/MaldivesSTEPSReport2011.pdf, accessed 27 July 2022), Noncommunicable disease risk factor survey 2009. New Delhi: WHO Regional Office for South-East Asia; 2011 (https://www.who.int/ncds/surveillance/steps/2009_STEPS_Survey_Myanmar. pdf, accessed 21 July 2022), Report on national survey on diabetes mellitus and risk factors for noncommunicable diseases in Myanmar 2014. Naypyitaw, Myanmar: Ministry of Health; 2014 (https://www.who.int/chp/steps/Myanmar_2014_STEPS_ FactSheet.pdf?ua=1, accessed 21 July 2022), Nepal noncommunicable disease risk factor survey 2007/08. Kathmandu, Nepal: Ministry of Health and Population, Government of Nepal, Society for Local Integrated Development Nepal (SOLID Nepal) and WHO; 2009 (https://www.who.int/chp/-steps/Nepal_2007_STEPS_Report. pdf?ua=1, accessed 15 July 2022), Noncommunicable diseases risk factors, STEPS survey Nepal 2012–2013. Kathmandu, Nepal: Nepal Health Research Council; 2014 (https://www.who.int/chp/steps/2012–2013_Nepal_STEPS_Report.pdf?ua=1, accessed 15 July 2022), Report of noncommunicable disease risk factors: STEPS survey Nepal 2019. Kathmandu: Nepal Health Research Council; 2020 (https:// extranet.who.int/ncdsmicrodata/index.php/catalog/771/download/5377, accessed 15 July 2022), National noncommunicable disease risk factor survey 2006. Colombo, Sri Lanka: Ministry of Health care and Nutrition; 2008 (https://www.who.int/ncds/ surveillance/steps/2006_STEPS_Survey_SriLanka.pdf, accessed 12 July 2022), Noncommunicable disease risk factor survey 2015. Colombo, Sri Lanka: Ministry of Health, Nutrition and Indigenous Medicine; 2015 (https://www.who.int/ncds/ surveillance/steps/STEPS-report-2015-Sri-Lanka.pdf, accessed 12 July 2022) and National survey for noncommunicable disease risk factors and injuries using WHO STEPS approach in Timor-Leste-2014. New Delhi, India: Regional Office for South-East Asia, World Health Organization; 2015 (https://www.who.int/ncds/surveillance/steps/ Timor-Leste_2014_STEPS_Report.pdf, accessed 24 July 2022). 69. Global school-based student health survey. Bangladesh fact sheet 2014. Atlanta and Geneva: World Health Organization and Centres for Disease Control and Prevention; 2018 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/485, accessed 16 July 2022), Global school-based student health survey. Bhutan fact sheet 2016. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health Organization; 2017 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/643, accessed 17 July 2022), Global school-based student health survey: India fact sheet 2007. Atlanta and Geneva: Centers for Disease Control and Prevention and World health Organization; 2008 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/41, accessed 17 July 2022), Global school-based student health survey: Indonesia fact sheet 2015. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health organization; 2016 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/489, accessed 09 August 2022), Global school-based student health survey: Maldives fact sheet 2014. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health organization; 2015 (https://extranet.who.int/ncdsmicrodata/index. php/catalog/546, accessed 17 July 2022), Global school-based student health survey: Myanmar fact sheet 2016. Atlanta and Geneva: Centers for Disease Control 44 and Prevention and World Health organization; 2017 (https://extranet.who.int/ ncdsmicrodata/index.php/catalog/650, accessed 21 July 2022), Global school-based student health survey: Nepal fact sheet 2015. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health organization; 2016 (https://extranet.who. int/ncdsmicrodata/index.php/catalog/655, accessed 15 July 2022), Global school- based student health survey: Sri Lanka fact sheet 2008. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health Organization; 2009 (https:// extranet.who.int/ncdsmicrodata/index.php/catalog/30, accessed 18 July 2022), Global school-based student health survey: Thailand fact sheet 2021. Atlanta and Geneva: Centers for Disease Control and Prevention and World health Organization; 2022 (https://cdn.who.int/media/docs/default-source/ncds/ncd-surveillance/data-reporting/ thailand/2021_thailand_gshs_fact_sheetada1f3cd-2ee4-4258-a01f-b40873aaf988. pdf?sfvrsn=be5c3553_1&download=true, accessed 26 July 2022) and Global school-based student health survey: Timor-Leste fact sheet 2015. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health Organization; 2015 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/659/related-materials, accessed 04 August 2022). 70. Ibid. 71. Global school-based student health survey. Bangladesh fact sheet 2014. Atlanta and Geneva: World Health Organization and Centres for Disease Control and Prevention; 2018 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/485/related-materials, accessed 16 July 2022), Global school-based student health survey. Bhutan fact sheet 2016. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health Organization; 2017 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/643/ related-materials, accessed 17 July 2022), Global school-based student health survey: India fact sheet 2007. Atlanta and Geneva: Centers for Disease Control and Prevention and World health Organization; 2008 (https://extranet.who.int/ncdsmicrodata/index.php/ catalog/41/related-materials, accessed 17 July 2022), Global school-based student health survey: Indonesia fact sheet 2015. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health organization; 2016 (https://extranet.who.int/ ncdsmicrodata/index.php/catalog/489/related-materials, accessed 09 August 2022), Global school-based student health survey: Maldives fact sheet 2009. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health organization; 2010 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/195/related-materials, accessed 17 July 2022), Global school-based student health survey: Myanmar fact sheet 2016. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health organization; 2017 (https://extranet.who.int/ncdsmicrodata/index.php/ catalog/650/related-materials, accessed 21 July 2022), Global school-based student health survey: Nepal fact sheet 2015. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health organization; 2016 (https://extranet.who. int/ncdsmicrodata/index.php/catalog/655/related-materials, accessed 15 July 2022), Global school-based student health survey: Sri Lanka fact sheet 2016. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health Organization; 2017 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/648/related-materials, accessed 18 July 2022), Global school-based student health survey: Thailand fact sheet 2021. Atlanta and Geneva: Centers for Disease Control and Prevention and World health Organization; 2022 (https://cdn.who.int/media/docs/default-source/ncds/ ncd-surveillance/data-reporting/thailand/2021_thailand_gshs_fact_sheetada1f3cd- 2ee4-4258-a01f-b40873aaf988.pdf?sfvrsn=be5c3553_1&download=true, accessed 26 July 2022) and Global school-based student health survey: Timor-Leste fact sheet 2015. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health Organization; 2015 (https://extranet.who.int/ncdsmicrodata/index.php/ catalog/659/related-materials, accessed 04 August 2022). 72. Global school-based student health survey. Bangladesh fact sheet 2014. Atlanta and Geneva: World Health Organization and Centres for Disease Control and Prevention; 2018 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/485/related-materials, accessed 16 July 2022), Global school-based student health survey. Bhutan fact sheet 2016. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health Organization; 2017 (https://extranet.who.int/ncdsmicrodata/index.php/ catalog/643/related-materials, accessed 17 July 2022), Global school-based student health survey: Indonesia fact sheet 2015. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health organization; 2016 (https://extranet.who.int/ ncdsmicrodata/index.php/catalog/489/related-materials, accessed 09 August 2022), Global school-based student health survey: Maldives fact sheet 2009. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health organization; 2010 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/195/related-materials, accessed 17 July 2022), Global school-based student health survey: Myanmar fact sheet 2016. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health organization; 2017 (https://extranet.who.int/ncdsmicrodata/index.php/ catalog/650/related-materials, accessed 21 July 2022), Global school-based student health survey: Nepal fact sheet 2015. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health organization; 2016 (https://extranet.who. int/ncdsmicrodata/index.php/catalog/655/related-materials, accessed 15 July 2022), Global school-based student health survey: Sri Lanka fact sheet 2016. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health Organization; 2017 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/648/related-materials, accessed 18 July 2022), Global school-based student health survey: Thailand fact sheet 2021. Atlanta and Geneva: Centers for Disease Control and Prevention and World health Organization; 2022 (https://cdn.who.int/media/docs/default-source/ncds/ ncd-surveillance/data-reporting/thailand/2021_thailand_gshs_fact_sheetada1f3cd- 2ee4-4258-a01f-b40873aaf988.pdf?sfvrsn=be5c3553_1&download=true, accessed 26 July 2022) and Global school-based student health survey: Timor-Leste fact sheet 2015. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health Organization; 2015 (https://extranet.who.int/ncdsmicrodata/index.php/ catalog/659/related-materials, accessed 04 August 2022). 73. Global youth tobacco survey (GYTS), Bangladesh 2007. New Delhi: World Health Organization Regional Office for South-East Asia; 2008 (https://extranet.who.int/ ncdsmicrodata/index.php/catalog/767/related-materials, accessed 19 July 2022), Global youth tobacco survey (GYTS), Bangladesh 2013. New Delhi: World Health Organization Regional Office for South-East Asia; 2015 (https://extranet.who.int/ ncdsmicrodata/index.php/catalog/232/related-materials, accessed 19 July 2022), Global school-based student health survey. Bangladesh fact sheet 2014. Atlanta and Geneva: World Health Organization and Centres for Disease Control and Prevention; 2018 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/485/related-materials, accessed 16 July 2022), Global youth tobacco survey (GYTS), Bhutan 2009. New Delhi, India: World Health Organization, Regional Office for South-East Asia; 2010 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/242/related-materials, accessed 19 July 2022), Global school-based student health survey. Bhutan fact sheet 2016. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health Organization; 2017 (https://extranet.who.int/ncdsmicrodata/index.php/ catalog/643, accessed 17 July 2022), Global youth tobacco survey (GYTS), Bhutan 2019. New Delhi, India: World Health Organization, Regional Office for South-East Asia; 2020 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/925/related- materials, accessed 19 July 2022), Global youth tobacco survey (GYTS), India 2006. New Delhi: World Health Organization Regional Office for South-East Asia; 2007 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/264/related-materials, accessed 19 July 2022), Global youth tobacco survey (GYTS), India 2009. New Delhi: World Health Organization Regional Office for South-East Asia; 2010 (https:// extranet.who.int/ncdsmicrodata/index.php/catalog/241/related-materials, accessed 19 July 2022), Global youth tobacco survey (GYTS), India 2019. Mumbai and New Delhi: International Institute for Population Sciences and Ministry of Health and Family Welfare; 2020 (https://ntcp.nhp.gov.in/assets/document/National_Fact_Sheet_of_ fourth_round_of_Global_Youth_Tobacco_Survey_GYTS-4.pdf, accessed 19 July 2022), Global youth tobacco survey (GYTS), Indonesia 2009. New Delhi: World Health Organization Regional Office for South-East Asia; 2010 (https://extranet.who. int/ncdsmicrodata/index.php/catalog/240/related-materials, accessed 19 July 2022), Global youth tobacco survey (GYTS), Indonesia 2014. New Delhi: World Health Organization Regional Office for South-East Asia; 2015 (https://extranet.who.int/ ncdsmicrodata/index.php/catalog/227/related-materials, accessed 19 July 2022), Global youth tobacco survey (GYTS), Indonesia 2019. New Delhi: World Health Organization Regional Office for South-East Asia; 2020 (https://cdn.who.int/media/ docs/default-source/searo/tobacco/global-youth-tobacco-survey/gyts-indonesia- extended-factsheet.pdf?sfvrsn=d202f34f_3, accessed 19 July 2022), Global youth tobacco survey (GYTS), Maldives 2007. New Delhi: World Health Organization Regional Office for South-East Asia; 2008 (https://extranet.who.int/ncdsmicrodata/index.php/ catalog/245/related-materials, accessed 19 July 2022), Global youth tobacco survey (GYTS), Maldives 2011. New Delhi: World Health Organization Regional Office for South-East Asia; 2012 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/237/ related-materials, accessed 19 July 2022), Global youth tobacco survey (GYTS), Maldives 2019. New Delhi: World Health Organization Regional Office for South- East Asia; 2020 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/928/ related-materials, accessed 19 July 2022), Global youth tobacco survey (GYTS), Myanmar 2007. New Delhi: World Health Organization Regional Office for South-East Asia; 2008 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/244/related- materials, accessed 19 July 2022), Global youth tobacco survey (GYTS), Myanmar 2011. New Delhi: World Health Organization Regional Office for South-East Asia; 2012 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/236/related-materials, accessed 19 July 2022), Global youth tobacco survey (GYTS), Myanmar 2016. New Delhi: World Health Organization Regional Office for South-East Asia; 2018 (https:// extranet.who.int/ncdsmicrodata/index.php/catalog/224/related-materials, accessed 19 July 2022), Global youth tobacco survey (GYTS), Nepal 2007. New Delhi: World Health Organization Regional Office for South-East Asia; 2008 (https://extranet. who.int/ncdsmicrodata/index.php/catalog/235/related-materials, accessed 19 July 2022), Global youth tobacco survey (GYTS), Nepal 2011. New Delhi: World Health Organization Regional Office for South-East Asia; 2012 (https://extranet.who.int/ ncdsmicrodata/index.php/catalog/234/related-materials, accessed 19 July 2022), Global school-based student health survey: Nepal fact sheet 2015. Atlanta and Geneva: 45 Centers for Disease Control and Prevention and World Health organization; 2016 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/655/related-materials, accessed 15 July 2022), Global youth tobacco survey (GYTS), Global youth tobacco survey (GYTS), Sri Lanka 2007. New Delhi: World Health Organization Regional Office for South-East Asia; 2008 (https://extranet.who.int/ncdsmicrodata/index. php/catalog/243/related-materials, accessed 19 July 2022), Global youth tobacco survey (GYTS), Sri Lanka 2011. New Delhi: World Health Organization Regional Office for South-East Asia; 2012 (https://extranet.who.int/ncdsmicrodata/index.php/ catalog/233/related-materials, accessed 19 July 2022), Global school-based student health survey: Sri Lanka fact sheet 2016. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health Organization; 2017 (https://extranet.who. int/ncdsmicrodata/index.php/catalog/648, accessed 18 July 2022), Global youth tobacco survey (GYTS), Thailand 2009. New Delhi: World Health Organization Regional Office for South-East Asia; 2010 (https://extranet.who.int/ncdsmicrodata/ index.php/catalog/239/related-materials, accessed 19 July 2022), Global youth tobacco survey (GYTS), Thailand 2015. New Delhi: World Health Organization Regional Office for South-East Asia; 2016 (https://extranet.who.int/ncdsmicrodata/ index.php/catalog/225/related-materials, accessed 19 July 2022), Global school- based student health survey: Thailand fact sheet 2021. Atlanta and Geneva: Centers for Disease Control and Prevention and World health Organization; 2022 (https:// cdn.who.int/media/docs/default-source/ncds/ncd-surveillance/data-reporting/ thailand/2021_thailand_gshs_fact_sheetada1f3cd-2ee4-4258-a01f-b40873aaf988. pdf?sfvrsn=be5c3553_1&download=true, accessed 26 July 2022), Global youth tobacco survey (GYTS), Timor-Leste 2009. New Delhi: World Health Organization Regional Office for South-East Asia; 2010 (https://extranet.who.int/ncdsmicrodata/ index.php/catalog/238/related-materials, accessed 19 July 2022), Global youth tobacco survey (GYTS), Timor-Leste 2013. New Delhi: World Health Organization Regional Office for South-East Asia; 2015 (https://extranet.who.int/ncdsmicrodata/ index.php/catalog/228/related-materials, accessed 19 July 2022) and Global youth tobacco survey (GYTS), Timor-Leste 2019. New Delhi: World Health Organization Regional Office for South-East Asia; 2020 (https://extranet.who.int/ncdsmicrodata/ index.php/catalog/927/related-materials, accessed 19 July 2022). 74. Global school-based student health survey. Bangladesh fact sheet 2014. Atlanta and Geneva: World Health Organization and Centres for Disease Control and Prevention; 2018 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/485/related-materials, accessed 16 July 2022), Global school-based student health survey. Bhutan fact sheet 2016. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health Organization; 2017 (https://extranet.who.int/ncdsmicrodata/index.php/ catalog/643/related-materials, accessed 17 July 2022), Global school-based student health survey: Indonesia fact sheet 2015. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health organization; 2016 (https://extranet.who.int/ ncdsmicrodata/index.php/catalog/489/related-materials, accessed 09 August 2022), Global school-based student health survey: Maldives fact sheet 2014. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health organization; 2015 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/546/related-materials, accessed 17 July 2022), Global school-based student health survey: Nepal fact sheet 2015. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health organization; 2016 (https://extranet.who.int/ncdsmicrodata/index.php/ catalog/655/related-materials, accessed 15 July 2022), Global school-based student health survey: Sri Lanka fact sheet 2016. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health Organization; 2017 (https://extranet.who. int/ncdsmicrodata/index.php/catalog/648/related-materials, accessed 18 July 2022), Global school-based student health survey: Thailand fact sheet 2021. Atlanta and Geneva: Centers for Disease Control and Prevention and World health Organization; 2022 (https://cdn.who.int/media/docs/default-source/ncds/ncd-surveillance/ data-reporting/thailand/2021_thailand_gshs_fact_sheetada1f3cd-2ee4-4258-a01f- b40873aaf988.pdf?sfvrsn=be5c3553_1&download=true, accessed 26 July 2022) and Global school-based student health survey: Timor-Leste fact sheet 2015. Atlanta and Geneva: Centers for Disease Control and Prevention and World Health Organization; 2015 (https://extranet.who.int/ncdsmicrodata/index.php/catalog/659/related-materials, accessed 04 August 2022). 75. Bangladesh Demographic and Health Survey 2014. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Mitra and Associates and ICF International; 2016 (https://dhsprogram.com/pubs/pdf/-FR311/ FR311.pdf, accessed 28 August 2022), Bangladesh Demographic and Health Survey 2017–2018. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Ministry of Health and Family Welfare and ICF International; 2020 (https://dhsprogram.com/pubs/pdf/FR344/FR344.pdf, accessed 28 August 2022), Progotir Pathey Multiple Indicator Cluster Survey 2019. Survey findings report. Dhaka: Bangladesh Bureau of Statistics (BBS); 2019 (https://reliefweb.int/ sites/reliefweb.int/files/resources/Bangladesh-MICS-2019-SFR_English.pdf, accessed 20 August 2022), Bhutan Multiple Indicator Survey 2010. Thimphu, Bhutan: National Statistics Bureau; 2011 (https://mics-surveys-prod.s3.amazonaws.com/MICS4/ South%20Asia/Bhutan/2010/Final/Bhutan%202010%20MICS_English.pdf, accessed 20 August 2022), National Family Health Survey (NFHS-3), 2005–2006. Mumbai, India: International Institute for Population Sciences, IIPS/India and Macro international; 2007 (https://dhsprogram.com/publications/publication-FRIND3-DHS-Final-Reports. cfm, accessed 22 August 2022), National Family Health Survey (NFHS-4), 2015–2016. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2017 (https://dhsprogram.com/publications/publication-FR339-DHS-Final-Reports.cfm, accessed 22 August 2022), National Family Health Survey (NFHS-5), 2019–2021. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2022 (https://dhsprogram.com/pubs/pdf/FR375/FR375.pdf, accessed 22 August 2022), Indonesia Demographic and Health Survey 2007. Calverton, Maryland, USA: Statistics Indonesia-Badan Pusat Statistik-BPS and Macro International; 2008 (https:// dhsprogram.com/publications/publication-fr218-dhs-final-reports.cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey 2012. Jakarta, Indonesia: Statistics Indonesia-Badan Pusat Statistik-BPS, National Population and Family Planning Board-BKKBN/Indonesia, Ministry of Health/Indonesia and ICF International; 2013 (https://www.dhsprogram.com/publications/publication-FR275-DHS-Final-Reports.cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey, 2017. Jakarta, Indonesia: National Population and Family Planning Board, Statistics Indonesia, Ministry of Health and ICF; 2018 (https://dhsprogram.com/publications/publication-fr342- dhs-final-reports.cfm, accessed 20 August 2022), Maldives Demographic and Health Survey 2009. Malé, Maldives and Calverton, Maryland: Ministry of Health and Family and ICF Macro; 2010 (https://dhsprogram.com/pubs/pdf/FR237/FR237.pdf, accessed 18 July 2022), Maldives Demographic and Health Survey 2016–17. Malé, Maldives and Maryland, USA: Ministry of Health and ICF; 2018 (https://dhsprogram.com/pubs/ pdf/FR349/FR349.pdf, accessed 28 August 2022), Myanmar Demographic and Health Survey 2015–2016. Naypyitaw, Myanmar: Ministry of Health and Sports-MoHS and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR324/FR324.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2011. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/Nepal and ICF; 2012 (https://dhsprogram.com/pubs/pdf/ fr257/fr257%5B13april2012%5D.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2016. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/ Nepal and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR336/FR336.pdf, accessed 28 August 2022), Nepal Multiple Indicator Cluster Survey 2019. Kathmandu, Nepal: Central Bureau of Statistics and UNICEF Nepal; 2020 (https://mics-surveys-prod.s3.amazonaws. com/MICS6/South%20Asia/Nepal/2019/Survey%20findings/Nepal-MICS%202019SFR_ English.pdf, accessed 28 August 2022), Sri Lanka Demographic and Health Survey 2006–2007. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health care and Nutrition; 2009 (http://www.statistics.gov.lk/Health/StaticalInformation/ FinalReport, accessed 18 July 2022), Thailand Multiple Indicator Cluster Survey 2012. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2013 (https://mics-surveys-prod.s3.amazonaws.com/MICS4/East%20Asia%20 and%20the%20Pacific/Thailand/2012–2013/Summary/Thailand%202012%20MICS% 20Summary_English.pdf, accessed 16 July 2022), Thailand Multiple Indicator Cluster Survey 2015–2016, Final Report. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2016 (https://mics-surveys-prod.s3.amazonaws.com/ MICS5/East%20Asia%20and%20the%20Pacific/Thailand/2015–2016/Final/Thailand%20 15–2016%20MICS_En glish.pdf.pdf, accessed 18 July 2022), Thailand Multiple Indicator Cluster Survey 2019, Survey findings report. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2020 (https://mics-surveys-prod. s3.amazonaws.com/MICS6/East%20Asia%20and%20the%20Pacific/Thailand/2019/ Survey%20findings/Thailand%202019%20MICS%20Survey%20Findings%20Report_ National%20%28English%29.pdf, accessed 18 July 2022), Timor-Leste Demographic and Health Survey 2009–2010. Dili, Timor-Leste: National Statistics Directorate, Ministry of Finance/Timor-Leste and ICF Macro; 2010 (https://dhsprogram.com/pubs/pdf/FR235/ FR235.pdf, accessed 26 July 2022) and Timor-Leste Demographic and Health Survey 2016. Dili, Timor-Leste and Rockville, Maryland, USA: General Directorate of Statistics, Ministry of Finance/Timor-Leste and ICF; 2018 (https://dhsprogram.com/pubs/pdf/ FR329/FR329.pdf, accessed 28 August 2022). 76. Intimate partner violence prevalence among ever-partnered women in their lifetime: data by WHO region. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://www.who.int/data/gho/data/indicators/ indicator-details/GHO/intimate-partner-violence-lifetime, accessed 24 August 2022). 77. Intimate partner violence prevalence among ever-partnered women in their lifetime: data by country. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://www.who.int/data/gho/data/indicators/ indicator-details/GHO/intimate-partner-violence-lifetime, accessed 24 August 2022). 78. Bangladesh Demographic and Health Survey 2007. Bangladesh and Calverton, Maryland, USA: National Institute of Population Research and Training, Mitra and Associates and Macro International; 2009 (https://dhsprogram.com/-pubs/pdf/FR207/ FR207[April-10-2009].pdf, accessed 28 July 2022), National survey on women’s health and life experiences 2017: a survey on violence against women and girls in Bhutan. Thimphu, Bhutan: National Commission for Women and Children; 2017 (https:// 46 asiapacific.unfpa.org/sites/default/-files/pub-pdf/Bhutan%20VAW%20study%202017. pdf, accessed 28 August 2022), National Family Health Survey (NFHS-5), 2019–2021. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2022 (https://dhsprogram.com/pubs/pdf/FR375/FR375.pdf, accessed 22 August 2022), Maldives Demographic and Health Survey 2016–2017. Malé, Maldives and Maryland, USA: Ministry of Health and ICF; 2018 (https://dhsprogram.com/pubs/pdf/FR349/ FR349.pdf, accessed 28 August 2022), Myanmar Demographic and Health Survey 2015–2016. Naypyitaw, Myanmar: Ministry of Health and Sports-MoHS and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR324/FR324.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2016. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/Nepal and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR336/FR336.pdf, accessed 28 August 2022), Sri Lanka Demographic and Health Survey 2016. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health, Nutrition and Indigenous Medicine; 2017 (http://www.statistics.gov.lk/Health/StaticalInformation/ DemographicAndHealthSurvey-2016FullReport, accessed 28 August 2022), Timor-Leste Demographic and Health Survey 2016. Dili, Timor-Leste and Rockville, Maryland, USA: General Directorate of Statistics, Ministry of Finance/Timor-Leste and ICF; 2018 (https:// dhsprogram.com/pubs/pdf/FR329/FR329.pdf, accessed 28 August 2022). 79. Ibid. 80. Ibid. 81. Proportion of population with primary reliance on clean fuels and technologies for cooking: data by WHO region. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://www.who.int/data/gho/ data/indicators/indicator-details/GHO/gho-phe-primary-reliance-on-clean-fuels-and- technologies-proportion, accessed 24 August 2022). 82. Bangladesh Demographic and Health Survey 2014. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Mitra and Associates and ICF International; 2016 (https://dhsprogram.com/pubs/pdf/-FR311/ FR311.pdf, accessed 28 August 2022), Bangladesh Demographic and Health Survey 2017–2018. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Ministry of Health and Family Welfare and ICF International; 2020 (https://dhsprogram.com/pubs/pdf/FR344/FR344.pdf, accessed 28 August 2022), Progotir Pathey Multiple Indicator Cluster Survey 2019. Survey findings report. Dhaka: Bangladesh Bureau of Statistics (BBS); 2019 (https://reliefweb.int/sites/ reliefweb.int/files/resources/Bangladesh-MICS-2019-SFR_English.pdf, accessed 20 August 2022), National Family Health Survey (NFHS-3), 2005–2006. Mumbai, India: International Institute for Population Sciences, IIPS/India and Macro international; 2007 (https://dhsprogram.com/publications/publication-FRIND3-DHS-Final-Reports.cfm, accessed 22 August 2022), National Family Health Survey (NFHS-4), 2015–2016. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2017 (https://dhsprogram.com/publications/publication-FR339-DHS-Final-Reports.cfm, accessed 22 August 2022), National Family Health Survey (NFHS-5), 2019–2021. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2022 (https://dhsprogram.com/pubs/pdf/FR375/FR375.pdf, accessed 22 August 2022), Indonesia Demographic and Health Survey 2007. Calverton, Maryland, USA: Statistics Indonesia-Badan Pusat Statistik-BPS and Macro International; 2008 (https:// dhsprogram.com/publications/publication-fr218-dhs-final-reports.cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey 2012. Jakarta, Indonesia: Statistics Indonesia-Badan Pusat Statistik-BPS, National Population and Family Planning Board-BKKBN/Indonesia, Ministry of Health/Indonesia and ICF International; 2013 (https://www.dhsprogram.com/publications/publication-FR275-DHS-Final-Reports.cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey, 2017. Jakarta, Indonesia: National Population and Family Planning Board, Statistics Indonesia, Ministry of Health and ICF; 2018 (https://dhsprogram.com/publications/publication-fr342- dhs-final-reports.cfm, accessed 20 August 2022), Maldives Demographic and Health Survey 2009. Malé, Maldives and Calverton, Maryland: Ministry of Health and Family and ICF Macro; 2010 (https://dhsprogram.com/pubs/pdf/FR237/FR237.pdf, accessed 18 July 2022), Maldives Demographic and Health Survey 2016–2017. Malé, Maldives and Maryland, USA: Ministry of Health and ICF; 2018 (https://dhsprogram.com/pubs/ pdf/FR349/FR349.pdf, accessed 28 August 2022), Myanmar Demographic and Health Survey 2015–2016. Naypyitaw, Myanmar: Ministry of Health and Sports-MoHS and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR324/FR324.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2011. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/Nepal and ICF; 2012 (https://dhsprogram.com/pubs/pdf/ fr257/fr257%5B13april2012%5D.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2016. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/ Nepal and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR336/FR336.pdf, accessed 28 August 2022), Nepal Multiple Indicator Cluster Survey 2019. Kathmandu, Nepal: Central Bureau of Statistics and UNICEF Nepal; 2020 (https://mics-surveys-prod. s3.amazonaws.com/MICS6/South%20Asia/Nepal/2019/Survey%20findings/Nepal- MICS%202019SFR_English.pdf, accessed 28 August 2022), Sri Lanka Demographic and Health Survey 2006–2007. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health care and Nutrition; 2009 (http://www.statistics.gov. lk/Health/StaticalInformation/FinalReport, accessed 18 July 2022), Thailand Multiple Indicator Cluster Survey 2019, Survey findings report. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2020 (https://mics-surveys-prod. s3.amazonaws.com/MICS6/East%20Asia%20and%20the%20Pacific/Thailand/2019/ Survey%20findings/Thailand%202019%20MICS%20Survey%20Findings%20Report_ National%20%28English%29.pdf, accessed 18 July 2022), Timor-Leste Demographic and Health Survey 2009–2010. Dili, Timor-Leste: National Statistics Directorate, Ministry of Finance/Timor-Leste and ICF Macro; 2010 (https://dhsprogram.com/pubs/ pdf/FR235/FR235.pdf, accessed 26 July 2022), Timor-Leste Demographic and Health Survey 2016. Dili, Timor-Leste and Rockville, Maryland, USA: General Directorate of Statistics, Ministry of Finance/Timor-Leste and ICF; 2018 (https://dhsprogram.com/ pubs/pdf/FR329/FR329.pdf, accessed 28 August 2022) and proportion of population with primary reliance on clean fuels and technologies for cooking: data by country. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://www.who.int/data/gho/data/indicators/indicator-details/ GHO/gho-phe-primary-reliance-on-clean-fuels-and-technologies-proportion, accessed 24 August 2022). 83. Bangladesh Demographic and Health Survey 2011. Dhaka, Bangladesh and Calverton, Maryland, USA: National Institute of Population Research and Training, Mitra and Associates and ICF International; 2013 (https://dhsprogram.com/pubs/pdf/fr265/fr265. pdf, accessed 20 August 2022), Bangladesh Demographic and Health Survey 2014. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Mitra and Associates and ICF International; 2016 (https:// dhsprogram.com/pubs/pdf/-FR311/FR311.pdf, accessed 28 August 2022), Bangladesh Demographic and Health Survey 2017–2018. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Ministry of Health and Family Welfare and ICF International; 2020 (https://dhsprogram.com/pubs/ pdf/FR344/FR344.pdf, accessed 28 August 2022), National Family Health Survey (NFHS-3), 2005–2006. Mumbai, India: International Institute for Population Sciences, IIPS/India and Macro international; 2007 (https://dhsprogram.com/publications/ publication-FRIND3-DHS-Final-Reports.cfm, accessed 22 August 2022), National Family Health Survey (NFHS-4), 2015–2016. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2017 (https://dhsprogram.com/publications/ publication-FR339-DHS-Final-Reports.cfm, accessed 22 August 2022), National Family Health Survey (NFHS-5), 2019–2021. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2022 (https://dhsprogram.com/pubs/ pdf/FR375/FR375.pdf, accessed 22 August 2022), Indonesia Demographic and Health Survey 2007. Calverton, Maryland, USA: Statistics Indonesia-Badan Pusat Statistik-BPS and Macro International; 2008 (https://dhsprogram.com/publications/ publication-fr218-dhs-final-reports.cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey 2012. Jakarta, Indonesia: Statistics Indonesia-Badan Pusat Statistik-BPS, National Population and Family Planning Board-BKKBN/Indonesia, Ministry of Health/Indonesia and ICF International; 2013 (https://www.dhsprogram. com/publications/publication-FR275-DHS-Final-Reports.cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey, 2017. Jakarta, Indonesia: National Population and Family Planning Board, Statistics Indonesia, Ministry of Health and ICF; 2018 (https://dhsprogram.com/publications/publication-fr342-dhs-final-reports. cfm, accessed 20 August 2022), Maldives Demographic and Health Survey 2009. Malé, Maldives and Calverton, Maryland: Ministry of Health and Family and ICF Macro; 2010 (https://dhsprogram.com/pubs/pdf/FR237/FR237.pdf, accessed 18 July 2022), Maldives Demographic and Health Survey 2016–2017. Malé, Maldives and Maryland, USA: Ministry of Health and ICF; 2018 (https://dhsprogram.com/pubs/pdf/FR349/ FR349.pdf, accessed 28 August 2022), Myanmar Demographic and Health Survey 2015–2016. Naypyitaw, Myanmar: Ministry of Health and Sports-MoHS and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR324/FR324.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2011. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/Nepal and ICF; 2012 (https://dhsprogram.com/ pubs/pdf/fr257/fr257%5B13april2012%5D.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2016. Kathmandu, Nepal: Ministry of Health-MoH/ Nepal, New ERA/Nepal and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR336/ FR336.pdf, accessed 28 August 2022), Nepal Multiple Indicator Cluster Survey 2019. Kathmandu, Nepal: Central Bureau of Statistics and UNICEF Nepal; 2020 (https:// mics-surveys-prod.s3.amazonaws.com/MICS6/South%20Asia/Nepal/2019/Survey%20 findings/Nepal-MICS%202019SFR_English.pdf, accessed 28 August 2022), Sri Lanka Demographic and Health Survey 2006–2007. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health care and Nutrition; 2009 (http://www. statistics.gov.lk/Health/StaticalInformation/FinalReport, accessed 18 July 2022), Sri Lanka Demographic and Health Survey 2016. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health, Nutrition and Indigenous Medicine; 2017 (http://www.statistics.gov.lk/Health/StaticalInformation/DemographicAndHealthSurvey- 2016FullReport, accessed 28 August 2022), Thailand Multiple Indicator Cluster Survey 2012. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2013 (https://mics-surveys-prod.s3.amazonaws.com/MICS4/East%20Asia%20 47 and%20the%20Pacific/Thailand/2012–2013/Summary/Thailand%202012%20MICS% 20Summary_English.pdf, accessed 16 July 2022), Thailand Multiple Indicator Cluster Survey 2015–2016, Final Report. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2016 (https://mics-surveys-prod.s3.amazonaws. com/MICS5/East%20Asia%20and%20the%20Pacific/Thailand/2015–2016/Final/ Thailand%202015–2016%20MICS_En glish.pdf.pdf, accessed 18 July 2022), Thailand Multiple Indicator Cluster Survey 2019, Survey findings report. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2020 (https://mics- surveys-prod.s3.amazonaws.com/MICS6/East%20Asia%20and%20the%20Pacific/ Thailand/2019/Survey%20findings/Thailand%202019%20MICS%20Survey%20 Findings%20Report_National%20%28English%29.pdf, accessed 18 July 2022), Timor-Leste Demographic and Health Survey 2009–2010. Dili, Timor-Leste: National Statistics Directorate, Ministry of Finance/Timor-Leste and ICF Macro; 2010 (https:// dhsprogram.com/pubs/pdf/FR235/FR235.pdf, accessed 26 July 2022) and Timor- Leste Demographic and Health Survey 2016. Dili, Timor-Leste and Rockville, Maryland, USA: General Directorate of Statistics, Ministry of Finance/Timor-Leste and ICF; 2018 (https://dhsprogram.com/pubs/pdf/FR329/FR329.pdf, accessed 28 August 2022). 84. Ibid. 85. Ibid. 86. Ibid. 87. Bangladesh Demographic and Health Survey 2014. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Mitra and Associates and ICF International; 2016 (https://dhsprogram.com/pubs/pdf/-FR311/ FR311.pdf, accessed 28 August 2022), Bangladesh Demographic and Health Survey 2017–2018. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Ministry of Health and Family Welfare and ICF International; 2020 (https://dhsprogram.com/pubs/pdf/FR344/FR344.pdf, accessed 28 August 2022), Progotir Pathey Multiple Indicator Cluster Survey 2019. Survey findings report. Dhaka: Bangladesh Bureau of Statistics (BBS); 2019 (https://reliefweb. int/sites/reliefweb.int/files/resources/Bangladesh-MICS-2019-SFR_English.pdf, accessed 20 August 2022), Bhutan Multiple Indicator Survey 2010. Thimphu, Bhutan: National Statistics Bureau; 2011 (https://mics-surveys-prod.s3.amazonaws.com/ MICS4/South%20Asia/Bhutan/2010/Final/Bhutan%202010%20MICS_English.pdf, accessed 20 August 2022), National Nutrition Survey (NNS) 2015. Thimpu, Bhutan: Nutrition Programme, Department of Public Health, Ministry of Health; 2016 (http:// maternalnutritionsouthasia.com/wp-content/uploads/Bhutan-NNS-2015.pdf, accessed 20 August 2022), National Family Health Survey (NFHS-3), 2005–2006. Mumbai, India: International Institute for Population Sciences, IIPS/India and Macro international; 2007 (https://dhsprogram.com/publications/publication-FRIND3-DHS-Final-Reports. cfm, accessed 22 August 2022), National Family Health Survey (NFHS-4), 2015–2016. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2017 (https://dhsprogram.com/publications/publication-FR339-DHS-Final-Reports.cfm, accessed 22 August 2022), National Family Health Survey (NFHS-5), 2019–2021. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2022 (https://dhsprogram.com/pubs/pdf/FR375/FR375.pdf, accessed 22 August 2022), Indonesia Demographic and Health Survey 2007. Calverton, Maryland, USA: Statistics Indonesia-Badan Pusat Statistik-BPS and Macro International; 2008 (https:// dhsprogram.com/publications/publication-fr218-dhs-final-reports.cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey 2012. Jakarta, Indonesia: Statistics Indonesia-Badan Pusat Statistik-BPS, National Population and Family Planning Board-BKKBN/Indonesia, Ministry of Health/Indonesia and ICF International; 2013 (https://www.dhsprogram.com/publications/publication-FR275-DHS-Final-Reports. cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey, 2017. Jakarta, Indonesia: National Population and Family Planning Board, Statistics Indonesia, Ministry of Health and ICF; 2018 (https://dhsprogram.com/publications/publication- fr342-dhs-final-reports.cfm, accessed 20 August 2022), Maldives Demographic and Health Survey 2009. Malé, Maldives and Calverton, Maryland: Ministry of Health and Family and ICF Macro; 2010 (https://dhsprogram.com/pubs/pdf/FR237/FR237.pdf, accessed 18 July 2022), Maldives Demographic and Health Survey 2016–2017. Malé, Maldives and Maryland, USA: Ministry of Health and ICF; 2018 (https://dhsprogram. com/pubs/pdf/FR349/FR349.pdf, accessed 28 August 2022), Myanmar Demographic and Health Survey 2015–2016. Naypyitaw, Myanmar: Ministry of Health and Sports- MoHS and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR324/FR324.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2011. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/Nepal and ICF; 2012 (https://dhsprogram. com/pubs/pdf/fr257/fr257%5B13april2012%5D.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2016. Kathmandu, Nepal: Ministry of Health-MoH/ Nepal, New ERA/Nepal and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR336/ FR336.pdf, accessed 28 August 2022), Nepal Multiple Indicator Cluster Survey 2019. Kathmandu, Nepal: Central Bureau of Statistics and UNICEF Nepal; 2020 (https:// mics-surveys-prod.s3.amazonaws.com/MICS6/South%20Asia/Nepal/2019/Survey%20 findings/Nepal-MICS%202019SFR_English.pdf, accessed 28 August 2022), Sri Lanka Demographic and Health Survey 2006–2007. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health care and Nutrition; 2009 (http://www. statistics.gov.lk/Health/StaticalInformation/FinalReport, accessed 18 July 2022), Sri Lanka Demographic and Health Survey 2016. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health, Nutrition and Indigenous Medicine; 2017 (http://www.statistics.gov.lk/Health/StaticalInformation/DemographicAndHealthSurvey- 2016FullReport, accessed 28 August 2022), Thailand Multiple Indicator Cluster Survey 2012. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2013 (https://mics-surveys-prod.s3.amazonaws.com/MICS4/East%20Asia%20 and%20the%20Pacific/Thailand/2012–2013/Summary/Thailand%202012%20MICS% 20Summary_English.pdf, accessed 16 July 2022), Thailand Multiple Indicator Cluster Survey 2015–2016, Final Report. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2016 (https://mics-surveys-prod.s3.amazonaws. com/MICS5/East%20Asia%20and%20the%20Pacific/Thailand/2015–2016/Final/ Thailand%202015–2016%20MICS_En glish.pdf.pdf, accessed 18 July 2022), Thailand Multiple Indicator Cluster Survey 2019, Survey findings report. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2020 (https://mics- surveys-prod.s3.amazonaws.com/MICS6/East%20Asia%20and%20the%20Pacific/ Thailand/2019/Survey%20findings/Thailand%202019%20MICS%20Survey%20 Findings%20Report_National%20%28English%29.pdf, accessed 18 July 2022), Timor-Leste Demographic and Health Survey 2009–2010. Dili, Timor-Leste: National Statistics Directorate, Ministry of Finance/Timor-Leste and ICF Macro; 2010 (https:// dhsprogram.com/pubs/pdf/FR235/FR235.pdf, accessed 26 July 2022) and Timor- Leste Demographic and Health Survey 2016. Dili, Timor-Leste and Rockville, Maryland, USA: General Directorate of Statistics, Ministry of Finance/Timor-Leste and ICF; 2018 (https://dhsprogram.com/pubs/pdf/FR329/FR329.pdf, accessed 28 August 2022). 88. Ibid. 89. Ibid. 90. Births attended by a skilled health personnel: data by WHO region. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://www.who.int/data/gho/data/indicators/indicator-details/GHO/births-attended- by-skilled-health-personnel-(-), accessed 24 August 2022). 91. Bangladesh Demographic and Health Survey 2014. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Mitra and Associates and ICF International; 2016 (https://dhsprogram.com/pubs/pdf/-FR311/ FR311.pdf, accessed 28 August 2022), Bangladesh Demographic and Health Survey 2017–2018. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Ministry of Health and Family Welfare and ICF International; 2020 (https://dhsprogram.com/pubs/pdf/FR344/FR344.pdf, accessed 28 August 2022), Progotir Pathey Multiple Indicator Cluster Survey 2019. Survey findings report. Dhaka: Bangladesh Bureau of Statistics (BBS); 2019 (https://reliefweb. int/sites/reliefweb.int/files/resources/Bangladesh-MICS-2019-SFR_English.pdf, accessed 20 August 2022), Bhutan Multiple Indicator Survey 2010. Thimphu, Bhutan: National Statistics Bureau; 2011 (https://mics-surveys-prod.s3.amazonaws.com/ MICS4/South%20Asia/Bhutan/2010/Final/Bhutan%202010%20MICS_English.pdf, accessed 20 August 2022), National Nutrition Survey (NNS) 2015. Thimpu, Bhutan: Nutrition Programme, Department of Public Health, Ministry of Health; 2016 (http:// maternalnutritionsouthasia.com/wp-content/uploads/Bhutan-NNS-2015.pdf, accessed 20 August 2022), National Family Health Survey (NFHS-3), 2005–2006. Mumbai, India: International Institute for Population Sciences, IIPS/India and Macro international; 2007 (https://dhsprogram.com/publications/publication-FRIND3-DHS-Final-Reports. cfm, accessed 22 August 2022), National Family Health Survey (NFHS-4), 2015–2016. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2017 (https://dhsprogram.com/publications/publication-FR339-DHS-Final-Reports.cfm, accessed 22 August 2022), National Family Health Survey (NFHS-5), 2019–2021. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2022 (https://dhsprogram.com/pubs/pdf/FR375/FR375.pdf, accessed 22 August 2022), Indonesia Demographic and Health Survey 2007. Calverton, Maryland, USA: Statistics Indonesia-Badan Pusat Statistik-BPS and Macro International; 2008 (https:// dhsprogram.com/publications/publication-fr218-dhs-final-reports.cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey 2012. Jakarta, Indonesia: Statistics Indonesia-Badan Pusat Statistik-BPS, National Population and Family Planning Board-BKKBN/Indonesia, Ministry of Health/Indonesia and ICF International; 2013 (https://www.dhsprogram.com/publications/publication-FR275-DHS-Final-Reports. cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey, 2017. Jakarta, Indonesia: National Population and Family Planning Board, Statistics Indonesia, Ministry of Health and ICF; 2018 (https://dhsprogram.com/publications/publication-fr342- dhs-final-reports.cfm, accessed 20 August 2022), Maldives Demographic and Health Survey 2009. Malé, Maldives and Calverton, Maryland: Ministry of Health and Family and ICF Macro; 2010 (https://dhsprogram.com/pubs/pdf/FR237/FR237.pdf, accessed 18 July 2022), Maldives Demographic and Health Survey 2016–2017. Malé, Maldives and Maryland, USA: Ministry of Health and ICF; 2018 (https://dhsprogram.com/pubs/ 48 pdf/FR349/FR349.pdf, accessed 28 August 2022), Myanmar Demographic and Health Survey 2015–2016. Naypyitaw, Myanmar: Ministry of Health and Sports-MoHS and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR324/FR324.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2011. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/Nepal and ICF; 2012 (https://dhsprogram.com/pubs/pdf/ fr257/fr257%5B13april2012%5D.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2016. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/ Nepal and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR336/FR336.pdf, accessed 28 August 2022), Nepal Multiple Indicator Cluster Survey 2019. Kathmandu, Nepal: Central Bureau of Statistics and UNICEF Nepal; 2020 (https://mics-surveys-prod.s3.amazonaws. com/MICS6/South%20Asia/Nepal/2019/Survey%20findings/Nepal-MICS%202019SFR_ English.pdf, accessed 28 August 2022), Sri Lanka Demographic and Health Survey 2006–2007. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health care and Nutrition; 2009 (http://www.statistics.gov.lk/Health/StaticalInformation/ FinalReport, accessed 18 July 2022), Sri Lanka Demographic and Health Survey 2016. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health, Nutrition and Indigenous Medicine; 2017 (http://www.statistics.gov.lk/Health/StaticalInformation/ DemographicAndHealthSurvey-2016FullReport, accessed 28 August 2022), Thailand Multiple Indicator Cluster Survey 2012. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2013 (https://mics-surveys-prod.s3.amazonaws. com/MICS4/East%20Asia%20and%20the%20Pacific/Thailand/2012–2013/Summary/ Thailand%202012%20MICS% 20Summary_English.pdf, accessed 16 July 2022), Thailand Multiple Indicator Cluster Survey 2015–2016, Final Report. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2016 (https://mics- surveys-prod.s3.amazonaws.com/MICS5/East%20Asia%20and%20the%20Pacific/ Thailand/2015–2016/Final/Thailand%202015–2016%20MICS_En glish.pdf.pdf, accessed 18 July 2022), Thailand Multiple Indicator Cluster Survey 2019, Survey findings report. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2020 (https://mics-surveys-prod.s3.amazonaws.com/MICS6/East%20Asia%20and%20the%20 Pacific/Thailand/2019/Survey%20findings/Thailand%202019%20MICS%20Survey%20 Findings%20Report_National%20%28English%29.pdf, accessed 18 July 2022), Timor-Leste Demographic and Health Survey 2009–2010. Dili, Timor-Leste: National Statistics Directorate, Ministry of Finance/Timor-Leste and ICF Macro; 2010 (https:// dhsprogram.com/pubs/pdf/FR235/FR235.pdf, accessed 26 July 2022) and Timor-Leste Demographic and Health Survey 2016. Dili, Timor-Leste and Rockville, Maryland, USA: General Directorate of Statistics, Ministry of Finance/Timor-Leste and ICF; 2018 (https:// dhsprogram.com/pubs/pdf/FR329/FR329.pdf, accessed 28 August 2022). 92. Ibid. 93. Ibid. 94. Ibid. 95. Need for family planning satisfied with modern methods: data by WHO region. In: Global Health Observatory data repository [database]. Geneva: World Health Organization; 2022 (https://www.who.int/data/gho/data/indicators/indicator-details/ GHO/married-or-in-union-women-of-reproductive-age-who-have-their-need-for-family- planning-satisfied-with-modern-methods-(-), accessed 24 August 2022). 96. Bangladesh Demographic and Health Survey 2014. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Mitra and Associates and ICF International; 2016 (https://dhsprogram.com/pubs/pdf/-FR311/ FR311.pdf, accessed 28 August 2022), Bangladesh Demographic and Health Survey 2017–2018. Dhaka, Bangladesh and Rockville, Maryland, USA: National Institute of Population Research and Training, Ministry of Health and Family Welfare and ICF International; 2020 (https://dhsprogram.com/pubs/pdf/FR344/FR344.pdf, accessed 28 August 2022), Progotir Pathey Multiple Indicator Cluster Survey 2019. Survey findings report. Dhaka: Bangladesh Bureau of Statistics (BBS); 2019 (https://reliefweb. int/sites/reliefweb.int/files/resources/Bangladesh-MICS-2019-SFR_English.pdf, accessed 20 August 2022), Bhutan Multiple Indicator Survey 2010. Thimphu, Bhutan: National Statistics Bureau; 2011 (https://mics-surveys-prod.s3.amazonaws.com/ MICS4/South%20Asia/Bhutan/2010/Final/Bhutan%202010%20MICS_English.pdf, accessed 20 August 2022), National Nutrition Survey (NNS) 2015. Thimpu, Bhutan: Nutrition Programme, Department of Public Health, Ministry of Health; 2016 (http:// maternalnutritionsouthasia.com/wp-content/uploads/Bhutan-NNS-2015.pdf, accessed 20 August 2022), National Family Health Survey (NFHS-3), 2005–2006. Mumbai, India: International Institute for Population Sciences, IIPS/India and Macro international; 2007 (https://dhsprogram.com/publications/publication-FRIND3-DHS-Final-Reports. cfm, accessed 22 August 2022), National Family Health Survey (NFHS-4), 2015–2016. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2017 (https://dhsprogram.com/publications/publication-FR339-DHS-Final-Reports. cfm, accessed 22 August 2022), National Family Health Survey (NFHS-5), 2019–21. Mumbai, India: International Institute for Population Sciences, IIPS/India and ICF; 2022 (https://dhsprogram.com/pubs/pdf/FR375/FR375.pdf, accessed 22 August 2022), Indonesia Demographic and Health Survey 2007. Calverton, Maryland, USA: Statistics Indonesia-Badan Pusat Statistik-BPS and Macro International; 2008 (https:// dhsprogram.com/publications/publication-fr218-dhs-final-reports.cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey 2012. Jakarta, Indonesia: Statistics Indonesia-Badan Pusat Statistik-BPS, National Population and Family Planning Board-BKKBN/Indonesia, Ministry of Health/Indonesia and ICF International; 2013 (https://www.dhsprogram.com/publications/publication-FR275-DHS-Final-Reports. cfm, accessed 18 August 2022), Indonesia Demographic and Health Survey, 2017. Jakarta, Indonesia: National Population and Family Planning Board, Statistics Indonesia, Ministry of Health and ICF; 2018 (https://dhsprogram.com/publications/publication-fr342- dhs-final-reports.cfm, accessed 20 August 2022), Maldives Demographic and Health Survey 2009. Malé, Maldives and Calverton, Maryland: Ministry of Health and Family and ICF Macro; 2010 (https://dhsprogram.com/pubs/pdf/FR237/FR237.pdf, accessed 18 July 2022), Maldives Demographic and Health Survey 2016–2017. Malé, Maldives and Maryland, USA: Ministry of Health and ICF; 2018 (https://dhsprogram.com/pubs/ pdf/FR349/FR349.pdf, accessed 28 August 2022), Myanmar Demographic and Health Survey 2015–2016. Naypyitaw, Myanmar: Ministry of Health and Sports-MoHS and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR324/FR324.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2011. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/Nepal and ICF; 2012 (https://dhsprogram.com/pubs/pdf/ fr257/fr257%5B13april2012%5D.pdf, accessed 28 August 2022), Nepal Demographic and Health Survey 2016. Kathmandu, Nepal: Ministry of Health-MoH/Nepal, New ERA/ Nepal and ICF; 2017 (https://dhsprogram.com/pubs/pdf/FR336/FR336.pdf, accessed 28 August 2022), Nepal Multiple Indicator Cluster Survey 2019. Kathmandu, Nepal: Central Bureau of Statistics and UNICEF Nepal; 2020 (https://mics-surveys-prod.s3.amazonaws. com/MICS6/South%20Asia/Nepal/2019/Survey%20findings/Nepal-MICS%202019SFR_ English.pdf, accessed 28 August 2022), Sri Lanka Demographic and Health Survey 2006–2007. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health care and Nutrition; 2009 (http://www.statistics.gov.lk/Health/StaticalInformation/ FinalReport, accessed 18 July 2022), Sri Lanka Demographic and Health Survey 2016. Colombo, Sri Lanka: Department of Census and Statistics and Ministry of Health, Nutrition and Indigenous Medicine; 2017 (http://www.statistics.gov.lk/Health/StaticalInformation/ DemographicAndHealthSurvey-2016FullReport, accessed 28 August 2022), Thailand Multiple Indicator Cluster Survey 2012. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2013 (https://mics-surveys-prod.s3.amazonaws. com/MICS4/East%20Asia%20and%20the%20Pacific/Thailand/2012–2013/Summary/ Thailand%202012%20MICS% 20Summary_English.pdf, accessed 16 July 2022), Thailand Multiple Indicator Cluster Survey 2015–2016, Final Report. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2016 (https://mics- surveys-prod.s3.amazonaws.com/MICS5/East%20Asia%20and%20the%20Pacific/ Thailand/2015–2016/Final/Thailand%202015–2016%20MICS_En glish.pdf.pdf, accessed 18 July 2022), Thailand Multiple Indicator Cluster Survey 2019, Survey findings report. Bangkok, Thailand: National Statistical Office and United Nations Children’s Fund; 2020 (https://mics-surveys-prod.s3.amazonaws.com/MICS6/East%20Asia%20and%20the%20 Pacific/Thailand/2019/Survey%20findings/Thailand%202019%20MICS%20Survey%20 Findings%20Report_National%20%28English%29.pdf, accessed 18 July 2022), Timor-Leste Demographic and Health Survey 2009–2010. Dili, Timor-Leste: National Statistics Directorate, Ministry of Finance/Timor-Leste and ICF Macro; 2010 (https:// dhsprogram.com/pubs/pdf/FR235/FR235.pdf, accessed 26 July 2022) and Timor-Leste Demographic and Health Survey 2016. Dili, Timor-Leste and Rockville, Maryland, USA: General Directorate of Statistics, Ministry of Finance/Timor-Leste and ICF; 2018 (https:// dhsprogram.com/pubs/pdf/FR329/FR329.pdf, accessed 28 August 2022). 97. Ibid. 98. Ibid. 99. Ibid. 100. Diagnosis, treatment and control of blood sugar and blood pressure among adults. SE Asia Region calculations based on different WHO STEPS surveys or equivalent population-based surveys. Geneva and New Delhi: World Health Organization; 2014–2019. 101. Ibid. 102. Summary of report–Rapid assessment of avoidable blindness, Bhutan 2018. In: International Agency for the Prevention of Blindness [website]. London: International Agency for the Prevention of Blindness; 2020 (https://www.iapb.org/learn/resources/ summary-report-of-rapid-assessment-of-avoidable-blindness-bhutan-2018/, accessed 29 July 2022), Thoufeeq U, Das T, Limburg H, Maitra M, Panda L, Sil A, et al. First rapid assessment of avoidable blindness survey in the Maldives: prevalence and causes of blindness and cataract surgery. Asia-Pac J Ophthalmol 2017; 6:0–0. doi:10.22608/ APO.2017332 (https://www.iapb.org/wp-content/uploads/First_Rapid_Assessment_ of_Avoidable_Blindness_Survey_in_the_Maldives__Prevalence_and_Causes_of_ Blindness_and_Cataract_Surgery.pdf, accessed 29 July 2022), Epidemiology of blindness in Nepal. Kathmandu, Nepal: Nepal Netra Jyoti Sangh; 2012 (https://www. iapb.org/wp-content/uploads/2020/09/Epidemiology-of-Blindness-Nepal.pdf, accessed 29 July 2022), National survey of blindness, visual impairment, ocular morbidity 49 and disability in Sri Lanka 2014–2015. Colombo, Sri Lanka: Vision 2020 Secretariat, Ministry of Health & London, United Kingdom: London School of Hygiene and Tropical Medicine; 2016 (https://www.iapb.org/learn/resources/national-survey-of-blindness- and-vi-sri-lanka-2014–2015/, accessed 29 July 2022), Gray Z, Ackland P. Cataract surgical coverage. London WC1E 7HT: International Agency for the Prevention of Blindness; 2015 (https://www.iapb.org/wp-content/uploads/2020/09/IAPB_CSR_ Report_V2.pdf, accessed 29 July 2022) and Summary of report-Rapid assessment of avoidable blindness Timor-Leste, 2016. Dili, Timor-Leste: Ministry of Health, Government of Timor-Leste; 2017 (https://www.iapb.org/wp-content/uploads/2020/10/ Timor-RAAB-survey-report.pdf, accessed 29 July 2022). 103. Ratification of treaties that include the right to health. In: UN Treaty Body Database [database]. Geneva: Office of the United Nations High Commissioner for Human Rights; 2022 (https://tbinternet.ohchr.org/_layouts/15/TreatyBodyExternal/Treaty.aspx?, accessed 30 August 2022). 104. Constitutional provisions for equality and non-discrimination. In: Global Gender Equality Constitutional Database [database]. New York: UN Women; 2022 (https://constitutions. unwomen.org/en/dashboard, accessed 10 September 2022). 105. Legal arrangements related to inheritance, land ownership and divorce. In: Gender, Institutions and Development Database (GID-DB) 2019, OECD.Stat [database]. Paris: Organisation for Economic Co-operation and Development; 2022 (https://stats.oecd. org/Index.aspx?DataSetCode=GIDDB2019#, accessed 30 August 2022). 106. Legal age for marriage. In: Regions and countries [website]. London: Girls Not Brides; 2022 (https://www.girlsnotbrides.org/learning-resources/child-marriage-atlas/regions- and-countries/?country=bangladesh&country=bhutan&country=india&country=indo nesia&country=maldives&country=myanmar&country=nepal&country=sri-lanka&co untry=thailand&country=timor-leste, accessed 10 September 2022). 107. Mendos LR, Botha K, Lelis RC, de la Pena EL, Savelev I and Tan D. State-sponsored homophobia 2020: global legislation overview update. Geneva: International Lesbian, Gay, Bisexual, Trans and Intersex Association (ILGA); 2020 (https://ilga.org/downloads/ ILGA_World_State_Sponsored_Homophobia_report_global_legislation_overview_ update_December_2020.pdf, accessed 10 September 2022), Human rights watch country profiles: sexual orientation and gender identity. In: Human Rights Watch [website]. New York: Human Rights Watch; 2022 (https://www.hrw.org/video- photos/interactive/2022/05/19/2022-country-profiles-sexual-orientation-and-gender, accessed 10 September 2022), Nepal: court orders recognition of same-sex spouse. New York: Human Rights Watch; 2023 (https://www.hrw.org/news/2023/05/02/ nepal-court-orders-recognition-same-sex-spouse, accessed 04 July 2023) and Sri Lanka: ICJ welcomes the Supreme Court’s determinantion that the proposed amendment decriminalizing consensual same-sex sexual relations between adults is constitutional. New York: International Commission of Jurists; 2023 (https://www.icj. org/sri-lanka-icj-welcomes-the-supreme-courts-determination-that-the-proposed- amendment-decriminalizing-consensual-same-sex-sexual-relations-between-adults-is- constitutional/, accessed 05 July 2023). 108. Legal grounds for abortion. In: Global Abortion Policies Database [database]. Geneva: Human Reproduction Programme; 2022 (https://abortion- policies.srhr.org/countries/?r%5B%5D=c59&r%5B%5D=c60&r%5B%5D =c1000963&r%5B%5D=c68&r%5B%5D =c80&r%5B%5D=c82&r%5B%5D=c 83&r%5B%5D=c91&r%5B%5D=c94&r%5B%5D=c95&wr%5B%5D=0&f%5B0% 5D%5B%5D=1&f%5B0%5D%5B%5D=2&f%5B0%5D%5B%5D=3&f%5B0%5D% 5B%5D= 4&f%5B0%5D%5B%5D=5&f%5B0%5D%5B%5D=6&f%5B0%5D%5B% 5D=7&f%5B0%5D%5B%5D=8&f%5B0%5D%5B%5D=9&f%5B0%5D%5B%5D= 10&hrt=&co=&pia=, accessed 10 September 2022). 109. Reproductive health policies 2017: data booklet (ST/ESA/ SER.A/396). New York: United Nations, Department of Economic and Social Affairs, Population Division; 2017 (https://www.un.org/en/development/desa/population/publications/pdf/policy/ reproductive_health_policies_2017_data_booklet.pdf, accessed 10 September 2022). 110. Development planning in Bangladesh: 7th five-year plan and SDG implementation. Dhaka: General Economic Division, Planning Commission, Government of the People’s Republic of Bangladesh; 2016 (https://erd.portal.gov.bd/sites/default/files/files/erd. portal.gov.bd/page/2f97258a_6f25_479a_8545_a498c65783f2/Development%20 Planning%20 7FYP%20&%20SDG.pdf, accessed 12 August 2022), Climate change policy of the Kingdom of Bhutan 2020. Thimphu: National Environment Commission, Royal Government of Bhutan; 2020 (https://www.gnhc.gov.bt/en/wp-content/ uploads/2020/02/Climate-Change-Policy.pdf, accessed 12 August 2022), Gender mainstreaming in governance. New Delhi: Development Monitoring and Evaluation Office, NITI Aayog; 2022 (https://dmeo.gov.in/sites/default/files/2022–2006/ Thematic_Paper_Gender_Mainstreaming_220622.pdf, accessed 12 August 2022), National Medium Term Development Plan 2015–2019. Jakarta, Indonesia: National Development Planning Agency; 2014 (http://www.bpkp.go.id/sesma/konten/2254/ buku-i-ii-dan-iii-rpjmn-2015–2019; accessed 12 August 2022), Strategic action plan 2019–2023. Malé, Maldives: Government of Maldives; 2019 (https://storage. googleapis.com/presidency.gov.mv/Documents/SAP2019–2023.pdf, accessed 12 August 2022), Myanmar Sustainable Development Plan (2018–2030). Naypyitaw, Myanmar: Ministry of Planning and Finance; 2018 (https://themimu.info/sites/themimu. info/-files/documents/Core_Doc_Myanmar_Sustainable_Development_Plan_2018_- _2030_Aug2018.pdf, accessed 13 August 2022), 15th five-year development plan (2019/2020–2023/24). Kathmandu: National Planning Commission, Government of Nepal; 2020 (https://npc.gov.np/images/category/15th_plan_English_Version.pdf, accessed 13 August 2022), National action plan for the protection and promotion of human rights 2017–2021. Colombo: Government of Sri Lanka; 2017 (https://drive. google.com/file/d/1q1NE4cD39E53TMn7Ew-bcFvgstjxCp5e/view, accessed 13 August 2022), National strategy 2018–2037 (Summary). Bangkok, Thailand: National Strategy Secretariat Office; 2017 (https://data.thailand.opendevelopmentmekong.net/ laws_record/256BHU2580/resource/71078328-facBHU4cd5-a718-c342cfa49ae7, accessed 14 August 2022) and Timor-Leste strategic development plan 201BHU2030. Dili, Timor-Leste: Government of Timor-Leste; 2010 (https://www.adb.org/sites/default/ files/linked-documents/cobp-tim-2016–2018-sd-02.pdf, accessed 14 August 2022). 111. National women development policy 2011. Dhaka: Ministry of Women and Child Affairs; 2011 (https://mowca.gov.bd/sites/default/files/files/mowca.portal.gov. bd/policies/64238d39_0ecd_ 4a56_b00c_b834cc54f88d/National-Women%20 Development%20Policy-2011English.pdf, accessed 15 August 2022), National gender equality policy 2020. Thimphu: National Commission for Women and Children, Royal Government of Bhutan; 2020 (https://www.ncwc.gov.bt/publications/National%20 Gender%20Equality%20Policy1604395993.pdf, accessed 15 August 2022), National policy for women 2016 [draft]. New Delhi: Ministry of Women and Child Development, Government of India; 2016 (https://wcd.nic.in/sites/default/files/draft%20national%20 policy%20for%20women%202016_0.pdf, accessed 15 August 2022), National gender equality action plan 2022–2026. Malé: Ministry of Gender, Family and Social Services, Republic of Maldives; 2022 (gender.gov.mv/en/wp-content/uploads/sites/1/2022/03/ GEAPFinal.pdf, accessed 16 August 2022), National strategic plan for the advancement of women (2013–2022). Yangon: Ministry of Social Welfare, Relief and Resettlement; 2013 (https://myanmar.unfpa.org/sites/default/files/pub-pdf/NSPAW2013–2022_0.pdf, accessed 16 August 2022), Policy framework and national plan of action to address Sexual and Gender-based Violence (SGBV) in Sri Lanka 2016–2020. Colombo, Sri Lanka: Ministry of Women and Child Affairs, Government of Sri Lanka; 2016 (http:// gbvforum.lk/r-library/document/SGBV%20National%20Action%20Plan.pdf, accessed 18 August 2022) and National women’s development strategy (2017–2021). Bangkok: Ministry of Social Development and Human Security; 2018. 112. Gender responsive budgeting in the Asia-Pacific region: a status report. New York: Un Women; 2016 (https://www2.unwomen.org/-/media/field%20office%20eseasia/ docs/publications/2016/12/grb_report-for-web-s.pdf?la=en&vs=1520%20but%20 rather%20finance, accessed 15 August 2022), Gender responsive budgeting guideline for the health sector, 2019. Nepal: Ministry of Health and Population, Government of Nepal; 2019 (https://www.nhssp.org.np/Resources/GESI/Gender%20Responsive%20 Budget%20Guideline%202019.pdf, accessed 04 July 2023), Sri Lanka: Manual on gender mainstreaming and gender-responsive budgeting. Colombo, Sri Lanka: Ministry of Women & Child Affairs and Dry Zone Development; 2019 (http://www. childwomenmin.gov.lk/storage/app/media/combinedPDF.pdf, accessed 30 August 2022) and Thailand: gender-budgeting action plan. Paris, France: Organization for Economic Co-operation and Development; 2019 (http://www.oecd.org/gov/budgeting/ gender-budgeting-action-plan-thailand.pdf, accessed 15 August 2022). 113. Gender responsive budgeting in the Asia-Pacific region: a status report. New York: Un Women; 2016 (https://www2.unwomen.org/-/media/field%20office%20eseasia/ docs/publications/2016/12/grb_report-for-web-s.pdf?la=en&vs=1520%20but%20 rather%20finance, accessed 15 August 2022) and information from World Health Organization country offices. 114. Information from World Health Organization country offices. 115. Ibid. 116. Ibid. 117. Gender mainstreaming for health managers: a practical approach. Geneva: World Health Organization; 2011 (https://apps.who.int/iris/bitstream/handle/10665/44516/ 9789241501071_eng.pdf;jsessionid=10DAC334CCC4C0221AA4FC F7B1D4CCC0?sequence=1, accessed 30 August 2022). 118. Innov8 approach for reviewing national health programmes. In: World Health Organization [website]. Geneva: World Health Organization; 2020 (https://www.who.int/ life-course/partners/innov8/en/, accessed 30 August 2022). 119. Human rights and gender equality in health sector strategies: how to assess policy coherence. Geneva: World Health Organization; 2011 (https://apps.who.int/iris/ bitstream/handle/10665/44438/9789241564083_eng.pdf?sequence=1&isAllowed=y, accessed 30 August 2022). 50

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