Gender and noncommunicable diseases in Belarus: analysis of STEPS data

GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS Analysis of STEPS data

GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS Analysis of STEPS data ABSTRACT This report is part of the gender and noncommunicable diseases (NCDs) initiative launched by the WHO Regional Office for Europe, which aims to strengthen the response to NCDs through a gender approach. It is part of a series of country profiles and a synthesis report. The country profile of Belarus presents a gender analysis of the WHO STEPwise survey (STEPS) data to support international commitments to reducing the burden of NCDs with evidence and knowledge exchange. A gender analysis of STEPS NCD risk-factor survey data describes how risk factors for chronic diseases differ between and among men and women by exploring and tracking the direction and magnitude of trends in risk factors and accessing services by sociodemographic variables. Important differences hide even in sex-disaggregated data that need to be unpacked through sociodemographic characteristics, because men and women are not homogenous groups. The report also recognizes gaps in evidence and calls for further analysis of the impact of gender-based inequalities. KEYWORDS NONCOMMUNICABLE DISEASES GENDER SOCIOECONOMIC FACTORS RISK FACTORS HEALTHY DIET ALCOHOL TOBACCO USE OBESITY BLOOD PRESSURE BELARUS WHO/EURO:2020-1666-41417-56459 © World Health Organization 2020 Some rights reserved. This work is available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO licence (CC BY-NC-SA 3.0 IGO; https:// creativecommons.org/licenses/by-nc-sa/3.0/igo). Under the terms of this licence, you may copy, redistribute and adapt the work for non-commercial purposes, provided the work is appropriately cited, as indicated below. In any use of this work, there should be no suggestion that WHO endorses any specific organization, products or services. 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The responsibility for the interpretation and use of the material lies with the reader. In no event shall WHO be liable for damages arising from its use. iii ACKNOWLEDGMENTS iv EXECUTIVE SUMMARY v INTRODUCTION 1 NCDS CONSTITUTE THE MAIN BURDEN OF DISEASE FOR BOTH WOMEN AND MEN, BUT THERE ARE IMPORTANT DIFFERENCES 4 DIFFERENCES IN BEHAVIOURAL AND BIOLOGICAL RISK FACTORS 5 SIGNIFICANT DIFFERENCES BETWEEN MEN AND WOMEN 6 PREVALENCE OF THREE OR MORE RISK FACTORS 7 MORTALITY RATES AMONG MEN AND WOMEN 8 DIFFERENCES IN SPECIFIC RISK FACTORS AMONG MEN AND WOMEN BETWEEN AGE GROUPS 9 DIFFERENCES IN THE WAY MEN AND WOMEN ACCESS SERVICES 19 DIFFERENCES IN MEN AND WOMEN NOT MEASURED FOR RISK FACTORS 20 LIFESTYLE ADVICE GIVEN BY A HEALTH-CARE PROFESSIONAL 24 CONCLUSIONS 27 REFERENCES 31 ANNEX 1. SUPPLEMENTARY TABLES 35 CONTENTS iv This report is part of a series developed by the WHO Regional Office for Europe within a collaboration between the Gender and Human Rights programme and the WHO European Office for the Prevention and Control of Noncommunicable Diseases to accelerate progress towards reducing the burden of noncommunicable diseases using a gender approach. The editors of the series and of this report are Isabel Yordi Aguirre and Ivo Rakovac from the WHO Regional Office for Europe. They conceptualized the series’ publications, defined content, provided overall input, and reviewed and amended the content of the report to ensure alignment with overall WHO policy and guidance documents. The authors of the report are Brett J. Craig, WHO Regional Office for Europe, and Vital Pisaryk and Irina Novik, Republican Scientific and Practical Centre of Medical Technologies, Informatization, Management and Economics of Public Health, Belarus. Overall support and leadership for this initiative was provided by João Breda, Head of the WHO European Office for Prevention and Control of Noncommunicable Diseases, Nino Berdzuli, Director of the Division of Country Health Programmes, and Natasha Azzopardi- Muscat, Director of the Division of Country Health Policies and Systems, WHO Regional Office for Europe. Input was provided by: Rosemary Morgan, Johns Hopkins Bloomberg School of Public Health, United States of America; and Åsa Nihlén, Jill Farrington, Juan Tello and Enrique Loyola, WHO Regional Office for Europe. The work to create the country profile was made possible by the generous support of the governments of the Russian Federation and Germany. ACKNOWLEDGEMENTS vThis country profile for Belarus presents an analysis of sex-disaggregated data linked with other variables, such as education and income, gathered through the WHO STEPwise (STEPS) survey as part of the WHO Regional Office for Europe’s gender and noncommunicable diseases (NCDs) initiative to improve the response to NCDs in the WHO European Region through a gender approach. It is the first gender analysis of NCD risk-factor data for adults in Belarus and makes an important contribution to, and serves as an evidence base for, international commitments on NCDs in accelerating action towards reducing the NCD burden and ensuring universal health coverage. It also contributes to raising awareness and building capacity among country-based researchers and policy-makers on the rationale for applying a gender analysis to health data. A gender analysis of STEPS NCD risk-factor survey data describes how risk factors for chronic diseases differ between and among men and women by exploring and tracking the direction and magnitude of trends in risk factors and accessing services. It enables better planning and/or evaluation of gender-responsive health promotion or preventive campaigns and gender-responsive interventions. The analysis in this country profile examined differences in risk factors and accessing services between men and women overall by age group, education and income level. Important differences hide even in sex-disaggregated data that need to be unpacked by including sociodemographic characteristics, because men and women are not homogenous groups. Globally, more than 100 countries have collected data through the STEPS surveys, but this is the first time a more in-depth analysis from a gender perspective has been conducted. The following findings of the gender analysis therefore can be used to address specific needs and policy opportunities for Belarus. • Significantly higher percentages of men than women in most age groups engage in the behavioural risk factors for NCDs (like tobacco-smoking, alcohol consumption, insufficient levels of physical activity, insufficient intake of fruit and vegetables, adding salt to the diet and frequent consumption of processed foods), and higher percentages of women than men in the older age groups are found with most of the biological risk factors (overweight and obestiy, and raised blood pressure, glucose and cholesterol). • Prevalence of risk factors has different pathways for men and women across the life-course. Prevalence of biological risk factors is higher among women than men in the older age groups but is lower among women than men in the younger age groups. • While the percentage of men with multiple risk factors nearly triples from the 18–29 age group to the 60–69 group, the percentage of women is more than six times greater between comparable age groups. • An analysis of biological risk factors by geographic location shows that urban and rural areas are not associated with the same risk factors for men and women. • Prevalence of behavioural risk factors is higher for men in rural settings than for those in urban, and prevalence of biological risk factors is higher for women in rural settings than urban. EXECUTIVE SUMMARY vi • The prevelence of behavioral risk factors for men and women varies by education level, depending on the risk factor and whether it is men or women in that level. Prevalence of all biological risk factors is higher for women with medium and low education, but this is not the case for men. • More employed men and women engage in tobacco and alcohol use than those who are unemployed or not in the labour force, while prevalence of all biological risk factors is higher for women who are unemployed or not in the labour force. • In some areas, there are gaps between exposure to risk and response from health services: a higher percentage of men than women have not been measured for biological risk factors and have not received lifestyle advice from a health-care professional on most behavioural risk factors. • Fewer men and women in rural areas than urban have been measured for risk factors. The percentages of rural women not measured generally are not significantly lower than the percentages of men in rural and urban areas not measured. • Women and (especially) men with low education levels are being measured for risk factors less than those with high education. • No differences in being measured for risk factors are found between employed men and women, but men who are unemployed or not in the labour force have a higher percentage of not being measured and women who are unemployed or not in the labour force have a lower percentage. • Significant differences in behavioural risk factors by marital status are found among men but not among women. • Improving access to services for women and men may require that additional attention is paid to the following groups: men, starting in the middle-age groups, women in rural areas, men in the low education level, men who are unemployed or not part of the labour force and employed women (for raised cholesterol), and single men. • Studies that specifically examine gender and social norms and gender inequality in these contexts can be used to complement this analysis by identifying driving and constraining factors for men and women in exposure to risk and access to services. In addressing the areas identified in this report, cost-effective interventions like best-buy and other interventions recommended by WHO should be prioritized and tailored to the country-specific context to ensure uptake and efficiency. This would greatly contribute to the achievement of universal health coverage and the health-related Sustainable Development Goals. INTRODUCTION 2GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS The WHO Regional Office for Europe launched a gender and noncommunicable diseases (NCDs) initiative in 2019 to improve the response to NCDs in the WHO European Region through a gender approach. Gender and rights-based approaches are imperative to accelerate transformative and sustainable progress towards achievement of the United Nations Sustainable Development Goals (SDGs). The strategy on women’s health and well-being in the WHO European Region (1) and the strategy on the health and well-being of men in the WHO European Region (2) strengthen the links between SDGs 3 and 5 in the Region while providing a comprehensive working framework for improving health and well-being in Europe through gender- responsive approaches. Commitments by Member States of the WHO European Region to accelerate actions towards reducing NCDs build on the Action Plan for the Prevention and Control of Noncommunicable Diseases in the WHO European Region 2016–2025 (3) and high-level meetings, in particular Health Systems Respond to NCDs: Experience in the European Region (Sitges, Spain, 16–18 April 2018) (4) and the WHO European High-level Conference on Noncommunicable Diseases: Time to Deliver – Meeting Noncommunicable Disease Targets to Achieve the Sustainable Development Goals in Europe (Ashgabat, Turkmenistan, 9 April 2019) (5). To support these commitments with evidence and knowledge exchange, country profiles of Armenia, Belarus, Georgia, Kyrgyzstan, the Republic of Moldova , Turkey, Ukraine and Uzbekistan have been created using a gender analysis on data gathered through the WHO STEPwise Approach to Surveillance (STEPS) NCD risk-factor survey. This country profile for Belarus presents an analysis of sex-disaggregated data linked with other variables, such as geographic location, education, employment and marital status, gathered through the STEPS survey. The analysis allows identification of the main gender-based differences and highlights some of the areas that need further gender analysis. Evidence generated within the country profiles in the series is intended to provide an evidence base and rationale for countries to strengthen health systems and whole- of-government responses to prevent, detect, manage and control NCDs, particularly at primary-care levels, through gender-responsive actions (Fig. 1). Source: WHO (6). Gender unequal Perpetuates inequalities Gender blind Ignores gender norms Gender sensitive Acknowledges but does not address inequalities Gender specific Considers women’s and men’s specific needs Gender transformative Aims at transforming harmful gender norms, roles and relations GENDER-RESPONSE POLICY Considers genders, norms, roles and relations Takes active measures to reduce harmful e­ects Fig. 1. WHO gender-response assessment scale GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS 3 INTRODUCTION The analysis follows the key elements identified by the WHO Regional Office for Europe in the policy brief on gender and NCDs (7). A gender analysis considers socially constructed norms, roles, behaviours and attributes that a given society considers appropriate for women and men and how this implies differential degrees of power between and among women and men. It recognizes that women and men are not homogenous groups and that their health opportunities and risks vary according to social, economic, environmental and cultural influences throughout their lifetime, while also considering how gender intersects with other factors behind social inequalities, such as age, employment, education, ethnicity or place of residence. The STEPS surveys (8) gather information on NCD risk factors to help plan and evaluate programmes and interventions by collecting standardized, high-quality risk-factor data to enable comparisons while allowing flexibility. The STEPS surveys consist of interviews (STEP 1), physical measurements such as blood pressure, weight and height (STEP 2) and biochemical measurements like blood glucose and cholesterol (STEP 3). An integrated approach is used, allowing an analysis of multiple risk factors simultaneously in a cost-efficient manner. WHO provides countries with a reference methodology for NCD surveillance and technical support for implementation. A gender analysis of STEPS NCD risk-factor survey data describes how risk factors for chronic diseases differ between and among men and women by exploring and tracking the direction and magnitude of trends in risk factors and how these differ between and among women and men. It enables better planning and/or evaluation of gender-responsive health promotion or preventive campaigns and gender-responsive interventions. At the same time, data reveal important differences between men and women in relation to health services access. The survey in Belarus was carried out from October 2016 to February 2017. A cluster sample design was used to produce nationally representative data for the age range of 18–69 years in Belarus. The overall response rate was 87%, with 5010 adults participating in the survey. The data were weighted for complex survey design, non-response rate and population distribution by age and sex. The analysis examined differences between and among men and women in risk factors and accessing services. In addition to looking at overall differences between men and women in risk factors, the analysis examined differences in groups of behavioural and biological risk factors. Differences among men and among women were then analysed by age group and other sociodemographic variables for both individual risk factors and groups of risk factors. Overall and within-group differences were also analysed by sociodemographic variables for accessing services. Examining sex-disaggregated data not only for overall differences between men and women but also for differences within these groups across the life-course is necessary, because men and women are not homogenous groups. There are important differences hiding even in sex-disaggregated data that need to be unpacked by including sociodemographic characteristics. The country profiles in this series are the first steps in mainstreaming gender, which is explained and further elaborated in the WHO manual Gender mainstreaming for health managers: a practical approach (6) (Fig. 2). 4GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS NCDs constitute the main burden of disease for both women and men, but there are important differences NCDs are the leading cause of death, disease and disability in the WHO European Region, and they are the greatest burden of disease in Belarus. NCDs are estimated to account for 91% of all deaths in Belarus (9), with cardiovascular diseases accounting for approximately 63% of all deaths in the country. Though improvements have been made, further action is needed to address the expected increase in the overall burden of NCDs (10). According to the STEPS survey of 2016 (11), it is estimated that 44.9% of the adult population has raised blood pressure, 25.4% are obese, 29.6% smoke tobacco, 13.2% are physically inactive, 20.3% use alcohol harmfully and 7.6% have raised blood glucose. Belarus has made specialized care and treatment for cardiovascular diseases a priority in recent years in an effort to address this disease burden (12). The prevalence of risk factors that account for NCDs differ between and among men and women, however, and there are important differences in the ways men and women access health services. Source: WHO (6). ACCOUNTABILITY Sex disaggregated data + Gender analysis + Gender-responsive action ST EP S Fig. 2. Gender mainstreaming steps GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS DIFFERENCES IN BEHAVIOURAL AND BIOLOGICAL RISK FACTORS 6GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS For behavioural risk factors, the STEPS data focus specifically on tobacco use, harmful alcohol consumption, unhealthy diet (low fruit and vegetable consumption, diet high in salt and/or processed foods) and insufficient physical activity, and, for biological risk factors, overweight/obesity, raised blood pressure, raised blood glucose and raised cholesterol. Highlighting where the highest differences exist will help to uncover where inequitable gender norms, roles, behaviours and attributes are likely to have the greatest effect on risk factors. Significant differences between men and women The prevalence of these risk factors for men and women was examined and tested for significant differences (Fig. 3 and Annex 1, Table A1.1). While prevalence among men is significantly higher than for women in nearly all the behavioural risk factors (current tobacco use, alcohol and diet), the same trend is not found for the biological risk factors. Prevalence is significantly higher for women in obesity and raised cholesterol, and there is no significant difference between men and women in overweight, raised blood pressure and raised blood glucose. The prevalence of raised blood pressure without medication is the only biological risk factor for which men are significantly higher than women. BMI: body mass index. * Statistically significant dierence. 0 10 20 30 40 50 60 70 80 90 Current tobacco use* Alcohol* Alcohol (heavy episodic)* Unhealthy diet ( < 5 fruit/veg per day)* Unhealthy diet (add salt)* Unhealthy diet (processed food)* InsuŠcient physical activity Overweight (BMI ≥ 25) Obesity (BMI ≥ 30)* Raised blood pressure (or on medication) Raised blood pressure NOT on medication* Raised blood glucose (or on medication) Raised cholesterol (or on medication)* Behavioural risk factors Biological risk factors Men Women Fig. 3. Prevalence of risk factors across countries with dierences between men and women (%) GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS 7 DIFFERENCES IN BEHAVIOURAL AND BIOLOGICAL RISK FACTORS Prevalence of three or more risk factors Differences between men and women in the prevalence of NCD risk factors are also found in those more at risk due to the prevalence of multiple risk factors. In accordance with the STEPS methodology, selected risk factors were used to examine the prevalence of three or more risk factors in the population. These combined risk factors are: • current daily smokers; • less than five servings of fruit and vegetables per day; • insufficient physical activity (< 150 minutes of moderate-intensity activity per week, or equivalent); • overweight (body mass index (BMI) ≥ 25 kg/m2); and • raised blood pressure (BP) (systolic BP ≥ 140 and/or diastolic BP ≥ 90 mmHg or currently on medication). Overall, a significantly higher percentage of men (47.9%) have three or more risk factors compared to women (33.7%). A significantly lower percentage of men (2.5%) than women (8.4%) do not have any risk factors. In addition to overall differences between men and women in multiple risk factors, prevalence through the life-course is different for men and women. As expected, the percentage of men and women with three or more risk factors is higher in older than in younger age groups. Significantly higher percentages of both men and women in each age group have three or more risk factors than the preceding age group, and in each age group the prevalence for men is significantly higher than for women. While the percentage of men steadily increases with each age group, the increase in percentage of women is more drastic, causing the difference in percentage between men and women to lessen with each ascending age group. The most significant narrowing of this gap can be seen between age groups 30–44 and 45–59. The accumulation of risk factors in women is more dramatic: while the percentage of men with three or more risk factors nearly triples from the 18–29 age group to the 60–69 group, from 25.1% to 71.8%, the percentage of women is more than six times greater between comparable age groups, from 9.4% to 59.8% (Fig. 4 and Annex 1, Table A1.2). These combined risk factors, however, do not include all risk factors, such as alcohol consumption or raised cholesterol. Additionally, risk factors have different impacts on NCD morbidity and mortality. For example, the risk associated with smoking is higher at individual level than the risk associated with eating fewer than five servings of fruit and vegetables (13): further analysis therefore is warranted to examine differences in these risk factors between men and women as well as among men and women. 8GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS Mortality rates among men and women Though difficult to calculate, there is probably an influence of mortality rates on prevalence of risk factors in the population when examining differences between men and women through the life-course. The mortality rate for men is significantly higher than for women and increases in the older age groups (Fig. 5 and Annex 1, Table A1.3) (14). 0 10 20 30 40 50 60 70 80 18–29 30–44 45–59 60–69 Men Women Fig. 4. Prevalence with three or more risk factors by age group (%) 0 10 20 30 40 18–29 30–44 45–59 60–69 Men Women Fig. 5. Total mortality per 1000 GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS 9 DIFFERENCES IN BEHAVIOURAL AND BIOLOGICAL RISK FACTORS Examining the causes of mortality among men and women by age group provides further insight into the differences in risk factors of men and women in the older age groups (Fig. 6 and Annex 1, Table A1.4). The higher mortality rates for men may account for some fo the lessening of the gap observed between men and women with three or more risk factors in the older age groups. Differences in specific risk factors among men and women between age groups Not only do men and women experience multiple risk factors differently through the life-course, but their experience with individual risk factors is also different. Examining the differences between men and women in more detail and by age group regarding risk factors reveals further the importance of a gender analysis. The difference between age groups for either sex in each behavioural risk factor shows how many more men than women engage in nearly all risk factors across age groups (Fig. 7 and Annex 1, Table A1.5). Men and women do not engage in behavioural risk factors through the life-course in the same way. In nearly every risk factor, the age group with the highest prevalence for both men and women is the 30–44 group, and the 60–69 group has the lowest prevalence, except for physical activity. Prevalence in each risk factor varies, however, between age groups and by sex. For example, where differences between age groups among women may be more pronounced, such as with alcohol consumption, the differences are less for men. The story for biological risk factors and age is quite different. The percentages of men and women with biological risk factors is significantly higher with each advancing age group (Fig. 8 and Annex 1, Table A1.6). More important is that prevalence for men starts higher in the youngest age group, but for women is higher for every biological risk factor in the older age groups (except for those with high blood pressure not on medication). Diseases of the circulatory system Neoplasms External causes of morbidity and mortality Diseases of the digestive system Diseases of the respiratory system Diseases of the nervous system 0 2 4 6 8 10 12 14 16 2018 Men Women 18–29 30–44 45–59 60–69 Fig. 6. Mortality per 1000 by age group 10 GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS These data show that prevalence of biological risk factors for women increases with older age groups more dramatically than with men. This applies not only to the population with multiple risk factors, but also to each individual risk factor. For example, though the prevalence of overweight for men is not significanlty higher than for women overall, prevalence for men in the 18–29 age group is significantly higher (40.0%) than for women (23.6%). In the 60–69 age group, however, prevalence is significantly higher for women (83.8%) than for men (77.7%). With obesity, prevalence is not significantly different between men and women in the 18–29 age group (7.0% men, 6.7% women), but is nearly double for women (50.1%) than it is for men (29.5%) in the 60–69 age group. Current tobacco use Alcohol Alcohol (heavy episodic) Unhealthy diet ( < 5 fruit/veg per day) Unhealthy diet (add salt) Unhealthy diet (processed food) Insucient physical activity 0 10 20 30 40 50 60 70 80 10090 Men Women 18–29 30–44 45–59 60–69 Fig. 7. Prevalence of behavioural risk factors by age group (%) Overweight (BMI ≥ 25) Obesity (BMI ≥ 30) Raised blood pressure (or on medication) Raised blood pressure NOT on medication Raised blood glucose (or on medication) Raised cholesterol (or on medication) 0 10 20 30 40 50 60 70 80 10090 Men Women 18–29 30–44 45–59 60–69 Fig. 8. Prevalence of biological risk factors by age group (%) Prevalence of women with biological risk factors starts lower than men but ends higher More men than women engage in behavioural risk factors through the life-course GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS 11 DIFFERENCES IN BEHAVIOURAL AND BIOLOGICAL RISK FACTORS While differences between men and women are apparent across the life-course, disaggregating data reveals additional differences among men and among women. Disaggregation by age group reveals specific groups of men and women who are more at risk and differences by sex. Other demographic categorizations, such as geographic location, education level, marital status and employment status, further help identify differences between men and women and also differences within these groups. GEOGRAPHIC LOCATION – URBAN AND RURAL The geographic location of the population can be used to further examine the differences in risk factors not only between, but also among, men and women. Data on geographic location collected in the STEPS survey have been categorized into urban and rural for the purposes of analysis. While some differences between men and women in urban and rural areas are observed, the differences are not consistent across the risk factors (Fig. 9 and Annex 1, Table A1.7). For example, a significant difference in prevalence of current tobacco use is found for men (54.1% in rural, 43.3% in urban), whereas significant differences in prevalence between urban and rural settings for women are found in relation to alcohol consumption (35.4% in rural, 46.7% in urban) and added salt (33.5% in rural, 23.6% in urban). An analysis of biological risk factors by geographic location shows that the associations with risk factors by urban and rural area are not the same for men and women (Fig. 10 and Annex 1, Table A1.8). The prevalence of obesity for women is significantly higher in rural areas (35.7%) than urban (26.0%), but for men there is no significant difference (20.0% in rural, 20.3% in urban). The prevalence of overweight is significantly different for both men and women between urban and rural areas. For men, however, the prevalence is higher in urban areas (65.5% in urban, 57.0% in rural), while for women the association is the opposite (65.1% in rural, 55.9% in urban). Because of this opposite association, prevalence of overweight in men and women is significantly different in both urban and rural areas. Current tobacco use Alcohol Alcohol (heavy episodic) Unhealthy diet ( < 5 fruit/veg per day) Unhealthy diet (add salt) Unhealthy diet (processed food) Insucient physical activity 0 10 20 30 40 50 60 70 80 10090 Men Women Rural Urban Fig. 9. Prevalence of behavioural risk factors by geographic location (%) Association of geographic location and behavioural risk factors are different for men than for women 12 GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS As is seen with disaggregation by age group and geographic location, important differences between men and women are hiding in the aggregated percentages of risk factors for men and women. EDUCATION LEVEL The education level of the population can be used to examine further the differences in risk factors not only between men and women, but also within the groups of men and women. Belarus has extremely high literacy rates (99.8% for men, 99.7% for women) and high enrolment in primary (95.1% for boys, 94.8% for girls) and secondary education (95.1% for males, 96.2% for females). A significant difference is visible only at tertiary level (80.2% for males, 95.1% for females) (15). Data on education level, determined by the highest level of education completed, were collected in the STEPS survey using country-specific categories. These categories have been matched to the levels of the International Standard Classification of Education (ISCED) (16) then condensed to reflect the three levels of low, medium and high (Table 1 and 2). Overweight (BMI ≥ 25) Obesity (BMI ≥ 30) Raised blood pressure (or on medication) Raised blood pressure NOT on medication Raised blood glucose (or on medication) Raised cholesterol (or on medication) 0 10 20 30 40 50 60 70 80 10090 Men Women Rural Urban Fig. 10. Prevalence of biological risk factors by geographic location (%) Geographic location can affect biological risk factors differently for men than for women STEPS survey categories ISCED levels 1 = no formal schooling ISCED 0 = early childhood education 2 = primary school completed ISCED 1 = primary education 3 = secondary school completed ISCED 2 = lower-secondary education 4 = college completed ISCED 4 = post-secondary non-tertiary education ISCED 5 = short-cycle tertiary education 5 = high school completed ISCED 3 = upper secondary education 6 = college/university completed ISCED 6 = bachelor’s degree or equivalent tertiary education 7 = postgraduate degree ISCED 7 = master’s degree or equivalent tertiary education ISCED 8 = doctoral degree or equivalent tertiary education Table 1. STEPS survey categories and ISCED levels GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS 13 DIFFERENCES IN BEHAVIOURAL AND BIOLOGICAL RISK FACTORS The prevelence of behavioral risk factors for men and women varies by education level, depending on the risk factor and whether it is men or women in that level (Fig. 11 and Annex 1, Table A1.9). For example, current tobacco use in the high education level for men and women is significantly lower than other education levels, but alcohol consumption for both men and women in the low education level is actually significanlty lower than for other education levels. For women and alcohol-related risk factors, however, the education level reveals differences in behaviours. With regular alcohol consumption, prevalence in the high education level is significantly higher (46.1%) than in the low education level (33.8%), but with heavy episodic drinking it is the low education level where prevalence is significanlty higher (10.2%) than in the high (4.5%). Additional differences in education levels are observed between and among men and women in relation to biological risk factors. Overall, the prevalence of biological factors for women tends to be lower in the high education group, which is not necessarily the case for men with high-level education (Fig. 12 and Annex 1, Table A1.10). Education level for analysis STEPS survey categories ISCED levels Low level of education 1 = no formal schooling 2 = primary school completed 3 = secondary school completed ISCED 0–2 Medium level of education 4 = college completed 5 = high school completed ISCED 3–5 High level of education 6 = college/university completed 7 = postgraduate degree ISCED 6–8 Table 2. Education level for analysis Current tobacco use Alcohol Alcohol (heavy episodic) Unhealthy diet ( < 5 fruit/veg per day) Unhealthy diet (add salt) Unhealthy diet (processed food) Insucient physical activity 0 10 20 30 40 50 60 70 80 10090 Men Women Low Medium High Fig. 11. Prevalence of behavioural risk factors by education level (%) Behavioural risk factors for both men and women are not necessarily lower in the higher education groups 14 GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS With overweight, obesity and raised blood pressure, prevalence is lowest among the high education level for women and tends to be similar in the low and medium education levels. Prevalence among men in these same risk factors follows a different pattern, with prevalence varying by education level across risk factors. Additional differences that are not apparent in the overall differences in biological risk factors are observed when comparing education levels between men and women. While the prevalence of overweight, for example, is significantly lower in the high education group for women, for men the prevelence at high education level is actually significantly higher. Prevalence of obesity is not significantly different across education levels for men, but for women the high education level is significantly lower and is comparable to the prevalence of obesity among all groups of men. The significant difference in prevalence of obesity between men and women overall is driven by women in the medium and low education levels. The prevalence of both raised blood pressure risk factors is also significantly lower in the high education level for women, showing that women in this level tend to have the lowest prevalence. Differences in prevalence of risk factors between men and women are often dependent on prevalence in groups among men and among women. EMPLOYMENT STATUS Unemployed people represent a particularly vulnerable group, and the impact of unemployment can be different for men and women. In Belarus, the estimated average annual earned income per capita for women is approximately 63% of that of men (the equivalent of Int$ 13 900 for women and Int$ 22 200 for men). Participation in the labour force is 80.4% of men and 74.7% of women. Those not currently employed but seeking work are 5.9% of men and 3.6% of women, though a higher percentage of women are part- time workers (23.8%) than men (8.0%) and woman engage in unpaid work more than twice as much as men (15). Overweight (BMI ≥ 25) Obesity (BMI ≥ 30) Raised blood pressure (or on medication) Raised blood pressure NOT on medication Raised blood glucose (or on medication) Raised cholesterol (or on medication) 0 10 20 30 40 50 60 70 80 10090 Men Women Low Medium High Fig. 12. Prevalence of biological risk factors by education level (%) High education level is lower in biological risk factors for women, but not always for men GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS 15 DIFFERENCES IN BEHAVIOURAL AND BIOLOGICAL RISK FACTORS Data on employment status were collected in the STEPS survey, and the categories have been condensed for analysis into employed (government employee, nongovernment employee, self-employed, industrialist/ farmer) and unemployed or not in the labour force (student, homemaker, retired, unemployed (able or unable to work)). Disaggregating the STEPS survey data by employment levels and sex reveals how the prevalence of behavioural risk factors varies in some groups and not in others (Fig. 13 and Annex 1, Table A1.11). Employed men and women engage in most behavioural risk factors more than those who are unemployed or not in the labour force. Alcohol consumption is significantly higher for both men (68.8%) and women (46.3%) who are employed than those who are unemployed or not in the labour force (54.0% for men, 33.0% for women). While risk factors related to diet show no significant differences by employment status among men and women (except for processed food for women), the prevalence of insufficient physical activity is significantly higher for both men and women who are unemployed or not in the labour force. These behaviours, particularly tobacco and alcohol use, may be higher due to affordability among those who are employed. With biological risk factors and employment status, however, more differences are found among groups of women than among men, with prevalence being generally higher for women who are unemployed or not in the labour force (Fig. 14 and Annex 1, Table A1.12). While the prevalence of raised blood pressure is significantly higher for both men (57.0%) and women (61.1%) who are unemployed or not in the labour force than employed men (41.6%) and women (35.6%), there are no other significant differences for men by employment status. For women, however, prevalence is significantly higher among those who are unemployed or not in the labour force in all other risk factors. Current tobacco use Alcohol Alcohol (heavy episodic) Unhealthy diet ( < 5 fruit/veg per day) Unhealthy diet (add salt) Unhealthy diet (processed food) Insucient physical activity 0 10 20 30 40 50 60 70 80 10090 Men Women Employed Unemployed Fig. 13. Prevalence of behavioural risk factors by employment status (%) Employed men and women engage in behavioural risk factors more than unemployed (or not in the labour force) 16 GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS MARITAL STATUS The marital status of both men and women provides another possible area of difference, as social and familial influences can affect health behaviours differently for men and women. Data on marital status were collected in the STEPS survey, and the categories have been condensed for analysis into single (including never married, separated, divorced or widowed) and joined (currently married or cohabitating). Significant differences in behavioural risk factors by marital status are found among men but not among women (Fig. 15 and Annex 1, Table A1.13). The prevalence of current tobacco use, alcohol consumption and insufficient physical activity are significantly different between single and joined men. Marital status is not consistent in its association between risk factors and men, however. More single men use tobacco, but more joined men consume alcohol and do not get enough physical activity. Among women, there are no significant differences in any of the behavioural risk factors by marital status. Overweight (BMI ≥ 25) Obesity (BMI ≥ 30) Raised blood pressure (or on medication) Raised blood pressure NOT on medication Raised blood glucose (or on medication) Raised cholesterol (or on medication) 0 10 20 30 40 50 60 70 80 10090 Men Women Employed Unemployed Fig. 14. Prevalence of biological risk factors by employment status (%) Prevalence of biological risk factors is higher for women who are unemployed or not in the labour force, but not necessarily for men Current tobacco use Alcohol Alcohol (heavy episodic) Unhealthy diet ( < 5 fruit/veg per day) Unhealthy diet (add salt) Unhealthy diet (processed food) Insucient physical activity 0 10 20 30 40 50 60 70 80 10090 Men Women Single Joined Fig. 15. Prevalence of behavioural risk factors by marital status (%) Marital status affects some differences in behavioural risk factors for men, but not for women GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS 17 DIFFERENCES IN BEHAVIOURAL AND BIOLOGICAL RISK FACTORS Differences in biological risk factors are significant for both men and women. Overall, higher prevalence is found with joined men and women than with single. This does not, however, take into account the possibility that the average age among the joined men and women may be older, which may affect the prevalence of biological risk factors. With some biological risk factors, such as overweight and obesity, higher prevalence is found among joined men and women. With raised blood pressure and raised cholesterol, however, a significant difference is observed between single and joined men, but not for women. Prevalence of raised blood pressure (not on medication) is significantly higher for joined (41.0%) than single men (27.0%), and prevalence for single men is not significantly higher than joined (27.1%) and single women (22.5%). The difference in raised blood pressure (not on medication) between men and women overall has driven the higher prevalence for single men (Fig. 16 and Annex 1, Table A1.14). Similarly, the prevalence of raised cholesterol for joined men is significantly higher (39.9%) than for single men (22.0%) but not significantly lower than prevalence for joined (43.6%) or single women (41.0%). These data show that while fewer single men are at risk from raised cholesterol, prevalence for joined men is just as high as for women. Furthermore, prevalence among women is consistently high across groups, revealing that women’s risk does not vary by marital status. Overweight (BMI ≥ 25) Obesity (BMI ≥ 30) Raised blood pressure (or on medication) Raised blood pressure NOT on medication Raised blood glucose (or on medication) Raised cholesterol (or on medication) 0 10 20 30 40 50 60 70 80 10090 Men Women Single Joined Fig. 16. Prevalence of biological risk factors by marital status (%) Biological risk factors are higher for both joined men and women

DIFFERENCES IN THE WAY MEN AND WOMEN ACCESS SERVICES 20 GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS In addition to the differences observed between and among men and women in NCD risk factors, significant differences are also found between men and women in accessing services for NCDs. A significantly higher percentage of men report never having had their blood pressure, blood glucose and cholesterol measured by a health-care professional, although figures are low (Fig. 17 and Annex 1, Table A1.15). Differences in men and women not measured for risk factors The groups can be examined further to identify target populations that may be facing barriers to accessing services (Fig. 18 and Annex 1, Table A1.16). 0 5 10 15 20 25 Blood pressure not measured Blood glucose not measured Cholesterol not measured Men Women Fig. 17. Percentage not measured for risk factors by a health-care professional Blood pressure not measured Blood glucose not measured Cholesterol not measured 0 10 20 30 40 50 Men Women 18–29 30–44 45–59 60–69 Fig. 18. Percentage not measured for risk factors by age group Percentages of men and women who have not been measured begins to significantly diverge in the 30–44 age group GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS 21 DIFFERENCES IN THE WAY MEN AND WOMEN ACCESS SERVICES It is not surprising that the percentages of men and women who have not been measured for these risk factors decreases with each age group. The benefit of this analysis, however, is to expose the significant differences between men and women at each age group and to identify which age groups are significantly different for both men and women. This reveals that the trends in accessing services differ between men and women across the life-course. For example, while the percentage of men and women who have not had their blood glucose measured is not different in the 18–29 age group (16.4% for men, 15.7% for women), and the percentage decreases with each age group for both, the decrease is more significant for women than men by the next age group. The percentage of women in the 30–44 age group who have not been measured (9.7%) is as low as the lowest groups for men (10.6% for 45–59, 10.1% for 60–69). This means that the percentages of men and women who have not been measured begins to diverge significantly in the 30–44 age group. GEOGRAPHIC LOCATION – URBAN AND RURAL Further differences can be seen when those not being measured for risk factors are examined by geographic location. Higher percentages of both men and women in rural areas have not been measured for risk factors than those in urban areas (Fig. 19 and Annex 1, Table A1.17). Additionally, the difference between urban and rural areas for women is greater with blood glucose and cholesterol than it is for men. The percentages of women in rural areas not measured for blood glucose (13.1%) and cholesterol (22.6%) are not significantly lower than for men not measured in rural (14.2% glucose, 25.1% cholesterol) and urban areas (11.7% glucose, 21.8% cholesterol). More women in urban areas have been measured for glucose and cholesterol, which explains why more women have been measured than men overall. While overall higher percentages of men than women are not being measured for risk factors, when disaggregated by geographic location it becomes apparent that the percentages of rural women who have not been measured are not higher than the percentages of rural and urban men. Only urban women are being measured more than men. Blood pressure not measured Blood glucose not measured Cholesterol not measured 0 10 20 30 40 50 Men Women Rural Urban Fig. 19. Percentage not measured for risk factors by geographic location Men and women in rural areas are measured less for risk factors than those in urban 22 GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS EDUCATION LEVEL Men and women with different education levels have not been measured for risk factors to the same extent. While men and women in the low education level have higher percentages of not having been measured than the other levels, for men the difference is more pronounced (Fig. 20 and Annex 1, Table A1.18). The percentages of men in the low education level not measured for blood glucose and cholesterol are significantly higher than for men in other levels and for women in all education levels. As with geographic location, disaggregation by education level reveals that it is a subgroup, in this case men in the low education level, that is driving the overall difference observed between men and women in accessing services. EMPLOYMENT STATUS Just as education level can present barriers in accessing services for men and women, employment status may also play a role due to its association with accessing resources. Overall, higher percentages of men who are unemployed or not in the labour force have not been measured for risk factors, while this is not the case for women. There are, however, more specific differences that require attention (Fig. 21 and Annex 1, Table A1.19). More variation is seen by employment status than in analyses by other demographic variables. A significant difference is observed for blood pressure between men (5.4%) and women (3.3%) who are unemployed or not in the labour force, but there is no significant difference between employed men (0.9%) and employed women (0.7%). With blood glucose, employed men (10.8%) and women (9.7%) again are not significantly different, but there is a significant difference between men (19.3%) and women (7.6%) who are unemployed or not in the labour force. The same goes for cholesterol, where employed men (21.9%) are not significantly higher than employed women (20.0%), but men (25.1%) and women (7.1%) who are unemployed or not in the labour force are significantly different. Blood pressure not measured Blood glucose not measured Cholesterol not measured 0 10 20 30 40 50 Men Women Low Medium High Fig. 20. Percentage not measured for risk factors by education level Men in the low education level are being measured for risk factors least GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS 23 DIFFERENCES IN THE WAY MEN AND WOMEN ACCESS SERVICES There are no significant differences between men and women who are employed and being measured for risk factors. This may be due to employed men and women experiencing similar opportunities, such as access to financial resources, and similar barriers, such as taking time away from work to be measured. Men and women in the unemployed or not in the labour force groups, however, are not similar. Higher percentages of men not being measured are found in this group, while the percentages for women who are unemployed or not in the labour force tend to be lower than those among employed women. While employed men and women may face similar barriers and are not different in accessing services, there appear to be barriers associated with unemployment or not being in the labour force for men that may not exist for women. There might also be differences in age and other determinants between men and women who are unemployed or not in the labour force. MARITAL STATUS Marital status allows for additional examinations of subgroups among men and women accessing services. While marital status has no apparent association for women being measured for risk factors, for men there are significant differences (Fig. 22 and Annex 1, Table A1.20). Blood pressure not measured Blood glucose not measured Cholesterol not measured 0 10 20 30 40 50 Men Women Employed Unemployed Fig. 21. Percentage not measured for risk factors by employment status Differences between men and women are driven by unemployed groups Blood pressure not measured Blood glucose not measured Cholesterol not measured 0 10 20 30 40 50 Men Women Single Joined Fig. 22. Percentage not measured for risk factors by marital status Single men are driving the differences between men and women in being measured for risk factors 24 GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS A significantly higher percentage of currently single men have not been measured for these risk factors than joined men. The significant overall differences between men and women in not being measured can be observed to predominantly be influenced by single men. Joined men are not significantly different than both single and joined women. Again, differences in the average age between single and joined may also account for some of the differences observed. Lifestyle advice given by a health-care professional Men and women access services differently, and the responses they receive when they access services can also differ. The STEPS survey gathered information on whether men and women had been given lifestyle advice when they had visited a health-care professional. The topics under lifestyle advice can be compared with the prevalence of related risk factors (Table 3) to examine more differences between sexes. In one lifestyle topic (avoiding tobacco use), a significantly higher percentage of men than women have been given advice, while a significantly higher percentage of women have been given advice on three of the topics (eating more fruit and vegetables, doing more physical activity and managing body weight). On tobacco use, a significantly higher percentage of men (43.6%) than women (20.7%) report having received advice, and this percentage is near that of men who currently use tobacco (48.4%). Women, however, report being given advice at nearly twice the percentage of the prevalence of the risk factor of current tobacco use (12.6%) (Fig. 23 and Annex 1, Table A1.21). This may be due to primary health-care protocols addressing women’s health that require the provider to discuss tobacco use, or it may be due to women accessing services more than men. The percentages of those receiving lifestyle advice are in all cases lower than the prevalence of the related risk factors. The difference in lifestyle advice given to men and women, and the corresponding prevalence of the related risk factors, warrants further analysis. Lifestyle advice topic Related risk factor Quit using tobacco or don’t start Current tobacco use Reduce salt in your diet Unhealthy diet (added salt) Eat at least five servings of fruit and/or vegetables each day Unhealthy diet (< 5 fruit/veg) Start or do more physical activity Insufficient physical activity Maintain a healthy body weight or lose weight Overweight (BMI ≥ 25) Table 3. Lifestyle advice topics and prevalence of related risk factors GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS 25 DIFFERENCES IN THE WAY MEN AND WOMEN ACCESS SERVICES 0 20 40 60 80 100 Tobacco Diet (fruit/veg) Diet (salt) Body weightPhysical activity Advice given to men Related risk factor for men Related risk factor for women Advice given to women Fig. 23. Percentage of lifestyle advice given for related risk factors A higher percentage of women are given lifestyle advice than men on most risk factors

CONCLUSIONS 28 GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS This country profile presents the first gender analysis of NCD risk factor data for adults in Belarus. It makes an important contribution to, and serves as an evidence base for, enabling achievement of the SDGs, women’s and men’s health strategies (1,2), the European Action Plan for the Prevention and Control of Noncommunicable Diseases (3) and other international commitments on NCDs, and promoting improved use of disaggregated data for better health outcomes, gender equality and human rights. It is also an important tool in accelerating action towards reducing the NCD burden and ensuring universal health coverage by unpacking inequalities by sociodemographic determinants in NCD risk factors and health system response, and contributes to raising awareness and building capacity among country-based researchers and policy-makers on the rationale for applying a gender analysis to health data. Globally, more than 100 countries have collected data through the STEPS surveys, but this is the first time a more in-depth analysis from a gender perspective has been conducted. The following findings of the gender analysis therefore can be used to address specific needs and policy opportunities for Belarus. Significantly higher percentages of men than women engage in all but one of the behavioural risk factors (insufficient physical activity) in most age groups, and significantly higher percentages of women than men are found with most of the biological risk factors in the older age groups. The percentage of men and women with multiple risk factors increases with each age group, but the increase for women is more drastic, causing the difference in percentage between men and women to lessen with each ascending age group. While the percentage of men nearly triples from the 18–29 age group to the 60–69 group, the increase in the percentage of women is more than six times greater between comparable age groups. High prevalence of behavioural and biological risk factors for both men and women is concerning, but the greater prevalence for women in the older age groups, despite lower prevalence in behavioural risk factors, demands attention. Men and women not only engage differently in behavioural risk factors, but also have different risk factor trajectories for both behavioural and biological risk factors over the life-course. Most notably, higher prevalence in biological risk factors is observed among women in the older age groups than men, while there is generally lower prevalence in the younger age groups among women than men. The importance of disaggregation by sex and age becomes apparent when significant differences are found to be hiding in the aggregated percentages of risk factors for men and women. Higher levels of male premature mortality could also contribute to lower prevalence of risk factors among male survivors at older ages, but additional causes of difference in risk factors between men and women should also be explored. The analysis shows that prevalence of both behavioural and biological risk factors can vary in subgroups of men and women, and these subgroups are not equal in their relation to the risk factors. Identifying groups most at risk necessarily requires disaggregation of data and a gender analysis that links sex with age and other relevant sociodemographic variables. The additional analysis by geographic location, education, employment and marital status further showcases the differences across behavioural and biological risk factors not only between, but also among, men and women. GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS 29 CONCLUSIONS The prevalence of behavioural risk factors is higher for men in rural areas, while the prevalence of biological risk factors is higher for women in rural areas. A high education level for men and women does not equate with lower prevalence in behavioural risk factors, as it varies from risk factor to risk factor. With biological risk factors, differences show significantly higher prevalence among medium- and low education women, but this is not the case for men. More employed men and women engage in tobacco and alcohol use than those unemployed or not in the labour force, and higher prevalence is found across all biological risk factors among women who are unemployed or not in the labour force. Higher prevalence of raised blood pressure among men who are unemployed or not in the labour force is the only significant difference in biological risk factors for men by employment status. Observed variation by marital status appears to be less than for other sociodemographic variables, but several significant differences were found among men in biological risk factors. Important differences are also observed in accessing services. A significantly higher percentage of men are not being measured for biological risk factors, while a significantly higher percentage of women than men are being given lifestyle advice on most behavioural risk factors. Despite accessing services more, the prevalence of biological risk factors as measured during the STEPS survey is still higher for women than men, or they are not significantly different. This may in part be due to the differences in accessing services among men and women as observed through disaggregation by age, geographic location, education, employment and marital status. Though higher percentages of men and women have been measured for biological risk factors in the older age groups, the trends in accessing services over the life-course are different between men and women. Fewer men have been measured for risk factors than women overall, but it is seen that the difference by age begins in the 30–44 age group and continues to diverge. While fewer men and women in rural areas have been measured for risk factors than in urban, women in rural areas are not being measured at virtually the same rate as men in rural and urban areas. Both men and women in the low education level are being measured for risk factors less than in the high education level. There is more variance between education levels for men than women, and it is men in the low education level who are driving the overall higher percentage of not being measured compared to women. Employed men and women are being measured at virtually the same rate, but men and women who are unemployed or not in the labour force are accessing services differently. Higher percentages of employed men have been measured, while higher percentages of employed women have not been measured. There appears to be no association between marital status and accessing services for women, but the higher percentages of single men not having been measured makes the overall difference between men and women who have not been measured. Improving access to services for women and men may therefore require that additional attention is paid to the following groups: men, starting in the middle-age groups, women in rural areas, men in the low education level, men who are unemployed or not in the labour force and employed women, and single men. 30 GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS Significantly higher percentages of lifestyle advice given to women could be influenced by numerous factors, including higher frequency of interaction of women with health-care services, higher proportion of women with biological risk factors, especially in the older age groups, and cultural and gender norms, among others. There is a need to identify gender-specific norms and barriers to access and lifestyle change. Barriers are both gender- and disease-specific, with men and women experiencing them differently depending on the risk factor and sociodemographic characteristics (17). These barriers can be identified and explored through studies that engage specific sociodemographic groups through quantitative and qualitative approaches. Such approaches could also explore possible influences, such as the presence of implicit bias in provider counselling, the sex of the health-care professional and social norms regarding social interactions between men and women. The impact of gender norms on men’s behaviour and access to services needs to be included in the gender analysis. Gender and culturally appropriate responses would then facilitate behavioural change, access and use of services. An analysis of the impact of gender inequalities requires further quantitative and qualitative information that cannot be retrieved from the STEPS data. Findings presented in this report highlight the importance of an in-depth gender analysis of existing sex-disaggregated data together with other variables in identifying NCD risk-factor differences not only between men and women, but also among men and among women. The analysis will further reveal specific needs and opportunities in prevention and management of NCDs among different population groups that can then be addressed through tailored interventions. Accompanying this country profile is a synthesis report with key findings and commonalities across the initial six country profiles. The gender analysis is being extended to other available surveys (including the global adult and youth tobacco surveys, the Health Behaviour in School-aged Children study and the WHO European Childhood Obesity Surveillance Initiative) to obtain more comprehensive insights. Studies that specifically examine gender and social norms in these contexts can be used to complement these surveys by identifying driving and constraining factors for behaviours causing differences between and among men and women. In addressing the areas identified in this report, cost-effective interventions like best-buy and other interventions recommended by WHO (18) should be prioritized and tailored to the country-specific context to ensure uptake and efficiency. This would greatly contribute to the achievement of universal health coverage and the health-related SDGs. GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS REFERENCES1 1 All weblinks accessed 28 July 2020. 32 GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS 1. Strategy on women’s health and well-being in the WHO European Region. Copenhagen: WHO Regional Office for Europe; 2016 (http://www.euro.who.int/en/health-topics/health-determinants/gender/publications/2016/strategy-on-womens- health-and-well-being-in-the-who-european-region-2016). 2. Strategy on the health and well-being of men in the WHO European Region. Copenhagen: WHO Regional Office for Europe; 2018 (http://www.euro.who.int/en/health-topics/health-determinants/gender/publications/2018/strategy-on-the-health- and-well-being-of-men-in-the-who-european-region-2018). 3. Action plan for the prevention and control of noncommunicable diseases in the WHO European Region 2016–2025. Copenhagen: WHO Regional Office for Europe; 2016 (http://www.euro.who.int/en/health-topics/noncommunicable- diseases/pages/policy/action-plan-for-the-prevention-and-control-of-noncommunicable-diseases-in-the-who-european- region-20162025). 4. WHO high-level regional meeting. Health Systems Respond to NCDs: Experience in the European Region, 16–18 April 2018, Sitges, Spain. Copenhagen: WHO Regional Office for Europe; 2018 (http://www.euro.who.int/en/media-centre/events/ events/2018/04/high-level-regional-meeting-health-systems-respond-to-ncds-experience-in-the-european-region/ documentation). 5. WHO European High-level Conference on Noncommunicable Diseases: Time to Deliver – Meeting Noncommunicable Disease Targets to Achieve the Sustainable Development Goals in Europe (Ashgabat, Turkmenistan, 9 April 2019). Copenhagen: WHO Regional Office for Europe; 2019 (https://www.who.int/news-room/events/detail/2019/04/09/default-calendar/ who-european-high-level-conference-on-noncommunicable-diseases). 6. Gender mainstreaming for health managers: a practical approach. Geneva: World Health Organization; 2011 (https://www.who.int/gender-equity-rights/knowledge/health_managers_guide/en/). 7. Why using a gender approach can accelerate noncommunicable disease prevention and control in the WHO European Region. Copenhagen: WHO Regional Office for Europe; 2019 (http://www.euro.who.int/en/health-topics/health-determinants/ gender/publications/2019/why-using-a-gender-approach-can-accelerate-noncommunicable-disease-prevention-and- control-in-the-who-european-region-2019). 8. The WHO STEPwise approach to noncommunicable disease risk factor surveillance. Geneva: World Health Organization; 2017 (https://www.who.int/ncds/surveillance/steps/manual/en/). 9. Belarus. In: Noncommunicable diseases (NCD) country profiles 2018. Geneva: World Health Organization; 2018:43 (https://apps.who.int/iris/handle/10665/274512). 10. Sharphedinsdottir M, Mantingh F, Jurgutis A, Johansen AS, Elmanova T, Zaitsev E. Better noncommunicable disease outcomes: challenges and opportunities for health systems. Belarus: country assessment. Copenhagen: WHO Regional Office for Europe; 2017 (http://www.euro.who.int/en/countries/belarus/publications/better-noncommunicable-disease- outcomes-challenges-and-opportunities-for-health-systems-belarus-country-assessment-2016). 11. Prevalence of noncommunicable disease risk factors in Belarus. STEPS 2016. Copenhagen: WHO Regional Office for Europe; 2018 (http://www.euro.who.int/ru/countries/belarus/publications/prevalence-of-noncommunicable-disease-risk-factors- in-republic-of-belarus.-steps-2016-2017). 12. Prevention and control of noncommunicable diseases in Belarus: the case for investment. Copenhagen: WHO Regional Office for Europe; 2018 (https://www.euro.who.int/en/countries/belarus/publications/prevention-and-control-of-ncds-in- belarus-the-case-for-investment-2018). 13. Stanaway JD, Afshin A, Gakidou E, Lim SS, Abate D, Abate KH et al. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018;392(10159): 1923–94. doi:10.1016/S0140-6736(18)32225-6. 14. Belstat [website]. Minsk: National Statistical Committee of the Republic of Belarus; 2020 (https://www.belstat.gov.by/en/). 15. Global gender gap report 2020. Geneva: World Economic Forum; 2020 (http://www3.weforum.org/docs/WEF_GGGR_2020.pdf). GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS 33 REFERENCES 16. International Standard Classification of Education. ISCED 2012. Paris: United Nations Educational, Scientific and Cultural Organization; 2011 (http://uis.unesco.org/en/topic/international-standard-classification-education-isced). 17. Breaking barriers: towards more gender-responsive and equitable health systems. 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ANNEX 1. SUPPLEMENTARY TABLES 36 GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS Table A1.1. Prevalence of risk factors, men and women Risk factors Men% (CI 95%) Women % (CI 95%) Behavioural Current tobacco use 48.4 (45.5–51.3) 12.6 (11.1–14.0) Alcohol consumption Currently drink 64.9 (61.6–68.3) 41.8 (38.6–44.9) Heavy episodic drinking 35.0 (31.8–38.1) 6.9 (5.6–8.2) Unhealthy diet < 5 fruit or vegetables per day 77.9 (74.3–81.5) 68.4 (64.7–72.0) Always or often add salt 35.8 (31.9–39.7) 28.0 (24.5–31.4) Always or often eat processed foods 43.6 (40.4–46.8) 28.5 (25.9–31.1) Insufficient physical activity 12.8 (10.7–14.9) 13.5 (11.5–15.5) Biological Overweight (BMI ≥ 25) 61.5 (58.7–64.2) 60.0 (57.3–62.4) Obesity (BMI ≥ 30) 20.2 (17.9–22.4) 30.2 (27.9–32.5) Raised blood pressure (BP) Raised BP (or on medication for raised BP) 45.6 (42.7–48.6) 44.2 (41.9–46.5) Raised BP (NOT on medication) 35.3 (32.1–38.4) 25.2 (22.9–27.6) Raised blood glucose (or on medication) 3.2 (2.3–4.1) 3.9 (2.9–5.0) Raised cholesterol (or on medication) 33.4 (30.6–36.2) 42.6 (40.0–45.2) CI: confidence interval. Table A1.2. Prevalence of three or more risk factors Age group Men% (CI 95%) Women % (CI 95%) 18–29 25.1 (20.2–30.0) 9.4 (5.5–13.2) 30–44 46.4 (41.6–51.3) 22.8 (19.5–26.2) 45–59 57.5 (53.4–61.6) 45.2 (41.3–49.1) 60–69 71.8 (66.6–77.0) 59.8 (54.9–64.8) CI: confidence interval. Table A1.3. Total mortality per 1000 Age group Men Women 18–29 1.03 0.36 30–44 3.45 1.15 45–59 12.99 4.02 60–69 34.55 11.32 Table A1.4. Mortality per 1000 by cause and age group Cause Age group 18–29 30–44 45–59 60–69 Total Diseases of the circulatory system Men 0.13 0.88 5.49 19.1 25.6 Women 0.03 0.21 1.38 5.99 7.61 Neoplasms Men 0.06 0.34 3.05 9.02 12.47 Women 0.06 0.33 1.44 3.39 5.22 External causes of morbidity and mortality Men 0.71 1.43 2.51 2.44 7.09 Women 0.15 0.29 0.44 0.49 1.37 37 GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS ANNEX Table A1.6. Prevalence of biological risk factors by age group Risk factor Aged 18–29% (CI 95%) Aged 30–44 % (CI 95%) Aged 45–59 % (CI 95%) Aged 60–69 % (CI 95%) Overweight (BMI ≥ 25) Men 40.0 (33.7–46.2) 62.6 (57.7–67.4) 70.7 (66.9–74.6) 77.7 (72.9–82.5) Women 23.6 (18.3–29.0) 49.3 (45.2–53.5) 80.1 (77.3–82.9) 83.8 (80.4–87.1) Obesity (BMI ≥ 30) Men 7.0 (4.0–9.9) 18.3 (14.8–21.8) 28.8 (24.8–32.7) 29.5 (24.0–35.1) Women 6.7 (3.4–10.0) 21.1 (17.7–24.5) 43.0 (39.4–46.7) 50.1 (45.4–54.9) Raised blood pressure (or on medication) Men 17.0 (12.4–21.5) 35.1 (30.2–40.0) 64.4 (60.0–68.8) 81.8 (77.0–86.6) Women 10.3 (7.1–13.4) 24.4 (20.8–28.0) 63.4 (60.1–66.7) 84.8 (81.6–88.1) Raised blood pressure (NOT on medication) Men 13.9 (9.5–18.4) 30.5 (25.7–35.3) 53.6 (48.5–58.8) 66.8 (58.9–74.7) Women 8.0 (5.0–11.0) 17.1 (13.8–20.3) 43.3 (38.9–47.8) 58.5 (51.1–65.8) Raised blood glucose (or on medication) Men 0.5 (0.0–1.2) 1.1 (0.3–1.9) 5.7 (3.3–8.1) 7.4 (4.4–10.4) Women 0.7 (0.0–1.4) 2.1 (0.8–3.3) 4.3 (2.8–5.7) 10.6 (7.2–14.1) Raised cholesterol (or on medication) Men 7.4 (4.1–10.8) 32.9 (28.2–37.6) 44.9 (40.5–49.3) 48.5 (41.9–55.1) Women 15.2 (10.7–19.8) 30.7 (27.0–34.5) 57.0 (53.3–60.8) 66.5 (62.0–71.1) CI: confidence interval. Table A1.5. Prevalence of behavioural risk factors by age group Risk factor Aged 18–29% (CI 95%) Aged 30–44 % (CI 95%) Aged 45–59 % (CI 95%) Aged 60–69 % (CI 95%) Current tobacco users Men 47.7 (41.7–53.7) 53.0 (48.0–58.0) 47.8 (43.7–51.9) 39.7 (33.5–45.9) Women 14.0 (10.1–17.9) 17.4 (14.5–20.3) 11.2 (8.8–13.6) 4.9 (3.0–6.8) Alcohol Men 58.3 (51.4–65.3) 71.5 (66.6–76.4) 65.8 (61.7–69.9) 59.2 (52.8–65.6) Women 38.3 (31.9–44.7) 50.1 (45.4–54.8) 44.6 (40.5–48.7) 26.4 (22.1–30.7) Alcohol (heavy episodic) Men 25.0 (19.6–30.4) 42.6 (37.5–47.7) 36.1 (31.6–40.6) 32.3 (26.4–38.1) Women 4.9 (2.3–7.5) 9.2 (6.7–11.7) 7.7 (5.6–9.7) 4.0 (2.2–5.8) Unhealthy diet (< 5 fruit/ veg per day) Men 79.7 (73.4–86.0) 78.7 (74.1–83.4) 76.5 (72.1–80.8) 76.0 (70.5–81.4) Women 66.7 (59.3–74.1) 69.8 (64.9–74.6) 68.2 (63.6–72.8) 68.2 (63.4–73.0) Unhealthy diet (add salt) Men 35.3 (29.3–42.3) 37.4 (31.6–43.1) 35.9 (31.4–40.5) 32.9 (27.0–38.8) Women 27.7 (21.4–34.1) 29.2 (24.5–33.9) 27.9 (23.8–32.0) 26.2 (21.5–30.8) Unhealthy diet (processed foods) Men 39.7 (33.2–46.3) 50.7 (45.4–56.0) 42.2 (37.9–46.5) 36.6 (30.9–42.2) Women 31.5 (25.4–37.6) 30.5 (26.4–34.6) 30.1 (26.6–33.6) 18.1 (14.5–21.7) Insufficient physical activity Men 7.7 (4.9–10.5) 10.5 (7.5–13.6) 13.2 (10.3–16.1) 27.1 (20.2–34.1) Women 11.8 (7.6–15.9) 12.3 (9.7–14.9) 11.6 (9.0–14.2) 20.8 (16.4–25.3) CI: confidence interval. Table A1.4 contd Cause Age group 18–29 30–44 45–59 60–69 Total Diseases of the digestive system Men 0.02 0.27 0.63 1.1 2.02 Women 0.03 0.1 0.32 0.5 0.95 Diseases of the respiratory system Men 0.02 0.1 0.44 0.96 1.53 Women 0.01 0.0 0.06 0.1 0.2 Diseases of the nervous system Men 0.04 0.1 0.21 0.88 1.18 Women 0.02 0.0 0.11 0.35 0.52 38 GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS Table A1.7. Prevalence of behavioural risk factors by geographic location Risk factor Rural% (CI 95%) Urban % (CI 95%) Current tobacco users Men 54.1 (49.4–58.8) 43.3 (39.8–46.7) Women 11.7 (9.4–14.0) 13.2 (11.3–15.2) Alcohol Men 63.8 (59.5–68.2) 65.9 (60.9–71.0) Women 35.4 (30.6–40.1) 46.7 (42.6–50.9) Alcohol (heavy episodic) Men 35.9 (31.1–40.6) 34.1 (29.9–38.4) Women 7.7 (5.5–9.9) 6.3 (4.8–7.8) Unhealthy diet (< 5 fruit/veg per day) Men 77.3 (71.6–83.0) 78.4 (73.9–83.0) Women 66.5 (60.4–72.6) 69.8 (65.4–74.2) Unhealthy diet (add salt) Men 39.0 (33.7–44.2) 33.0 (27.3–38.8) Women 33.5 (28.0–39.0) 23.6 (19.3–28.0) Unhealthy diet (processed foods) Men 47.6 (43.3–51.9) 40.0 (35.6–44.5) Women 32.0 (27.8–36.2) 25.7 (22.5–28.9) Insufficient physical activity Men 11.0 (8.2–13.8) 14.4 (11.4–17.4) Women 13.6 (10.3–16.9) 13.4 (10.9–15.8) CI: confidence interval. Table A1.8. Prevalence of biological risk factors by geographic location Risk factor Rural% (CI 95%) Urban % (CI 95%) Overweight (BMI ≥ 25) Men 57.0 (53.1–60.8) 65.5 (61.6–69.4) Women 65.1 (61.3–68.8) 55.9 (52.5–59.3) Obesity (BMI ≥ 30) Men 20.0 (16.9–23.1) 20.3 (17.1–23.4) Women 35.7 (32.2–39.2) 26.0 (23.0–29.0) Raised blood pressure (or on medication) Men 50.6 (46.3–54.9) 41.1 (37.2–45.1) Women 49.8 (46.2–53.3) 39.9 (36.8–43.0) Raised blood pressure (NOT on medication) Men 40.9 (36.2–45.6) 30.2 (26.2–34.2) Women 30.7 (26.7–34.7) 21.2 (18.3–24.2) Raised blood glucose (or on medication) Men 2.8 (1.7–3.8) 3.6 (2.1–5.0) Women 4.2 (2.6–5.9) 3.7 (2.4–5.0) Raised cholesterol (or on medication) Men 32.3 (28.1–36.5) 34.5 (30.8–38.1) Women 41.9 (37.9–46.0) 43.2 (39.8–46.5) CI: confidence interval. Table A1.9. Prevalence of behavioural risk factors by education level Risk factor Low% (CI 95%) Medium % (CI 95%) High % (CI 95%) Current tobacco users Men 49.4 (44.1–54.6) 53.7 (50.2–57.2) 32.1 (26.8–37.3) Women 16.0 (12.0–20.0) 13.3 (11.4–15.2) 9.2 (6.9–11.5) Alcohol Men 56.1 (50.5–61.7) 68.4 (64.3–72.5) 65.2 (59.1–71.3) Women 33.8 (28.0–39.7) 42.2 (38.5–45.8) 46.1 (41.4–50.8) Alcohol (heavy episodic) Men 31.1 (25.7–36.6) 38.1 (34.1–42.2) 30.3 (24.7–35.8) Women 10.2 (6.9–13.5) 7.1 (5.3–9.0) 4.5 (2.8–6.2) 39 GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS ANNEX Table A1.10. Prevalence of biological risk factors by education level Risk factor Low% (CI 95%) Medium % (CI 95%) High % (CI 95%) Overweight (BMI ≥ 25) Men 53.4 (48.0–58.8) 62.8 (59.2–66.4) 66.8 (61.0–72.6) Women 61.2 (55.8–66.6) 66.6 (63.4–69.7) 48.3 (43.9–52.6) Obesity (BMI ≥ 30) Men 19.6 (15.5–23.6) 19.9 (16.9–22.9) 21.5 (16.5–26.6) Women 35.0 (30.3–39.6) 35.2 (32.2–38.3) 19.2 (16.3–22.1) Raised blood pressure (or on medication) Men 50.3 (44.6–56.0) 45.4 (41.6–49.1) 40.8 (35.0–46.6) Women 54.5 (49.0–60.1) 48.4 (45.3–51.5) 31.0 (27.4–34.5) Raised blood pressure (NOT on medication) Men 40.4 (34.3–46.6) 35.3 (31.4–39.2) 29.3 (23.2–35.4) Women 32.9 (26.8–39.0) 29.0 (25.9–32.2) 15.9 (12.7–19.1) Raised blood glucose (or on medication) Men 4.2 (2.4–6.0) 2.8 (1.9–3.8) 2.9 (1.3–4.6) Women 7.0 (4.0–9.9) 3.8 (2.6–5.0) 2.2 (1.0–3.4) Raised cholesterol (or on medication) Men 33.0 (27.4–38.6) 33.7 (30.3–37.1) 33.0 (27.9–38.2) Women 45.0 (39.3–50.7) 43.1 (39.7–46.4) 40.3 (36.2–44.4) CI: confidence interval. Table A1.9 contd Risk factor Low% (CI 95%) Medium % (CI 95%) High % (CI 95%) Unhealthy diet (< 5 fruit/veg per day) Men 75.4 (69.4–81.4) 79.3 (75.4–83.2) 76.8 (71.2–82.4) Women 71.2 (65.7–76.6) 68.3 (63.9–72.8) 66.6 (61.9–71.3) Unhealthy diet (add salt) Men 40.7 (34.9–46.6) 35.4 (30.7–40.0) 31.6 (25.8–37.3) Women 35.8 (29.7–41.9) 28.3 (24.0–32.6) 22.5 (17.9–27.1) Unhealthy diet (processed foods) Men 42.8 (36.4–49.1) 45.8 (41.7–49.9) 38.1 (32.3–43.9) Women 28.8 (23.6–34.0) 30.2 (26.7–33.7) 25.4 (21.5–29.3) Insufficient physical activity Men 12.6 (9.0–16.1) 10.5 (8.2–12.8) 19.7 (15.1–24.3) Women 16.4 (11.4–21.4) 10.7 (8.6–12.7) 16.1 (12.7–19.5) CI: confidence interval. Table A1.11. Prevalence of behavioural risk factors by employment status Risk factor Employed% (CI 95%) Unemployed or not in the labour force % (CI 95%) Current tobacco users Men 50.2 (47.0–53.4) 43.3 (38.2–48.4) Women 13.7 (11.9–15.5) 10.3 (7.7–12.9) Alcohol Men 68.8 (65.2–72.4) 54.0 (48.5–59.5) Women 46.3 (42.8–49.7) 33.0 (28.6–37.3) Alcohol (heavy episodic) Men 37.0 (33.4–40.6) 29.1 (23.9–34.3) Women 7.6 (6.0–9.3) 5.5 (3.9–7.1) Unhealthy diet (< 5 fruit/veg per day) Men 78.0 (74.2–81.8) 77.7 (72.3–83.0) Women 68.0 (63.8–72.1) 69.1 (64.8–73.3) Unhealthy diet (add salt) Men 35.8 (31.6–39.9) 36.1 (30.5–41.6) Women 27.5 (24.0–31.1) 28.8 (24.1–33.6) Unhealthy diet (processed foods) Men 45.4 (41.9–48.9) 38.2 (33.2–43.3) Women 31.2 (28.0–34.3) 23.2 (19.6–26.7) Insufficient physical activity Men 9.8 (7.9–11.7) 21.2 (16.5–26.0) Women 11.4 (9.4–13.4) 17.6 (14.3–20.8) CI: confidence interval. 40 GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS Table A1.12. Prevalence of biological risk factors by employment status Risk factor Employed% (CI 95%) Unemployed or not in the labour force % (CI 95%) Overweight (BMI ≥ 25) Men 62.7 (59.6–65.9) 57.8 (52.6–63.0) Women 56.5 (53.5–59.4) 66.5 (62.2–70.9) Obesity (BMI ≥ 30) Men 20.0 (17.5–22.5) 20.6 (16.8–24.4) Women 26.8 (24.1–29.4) 37.0 (33.1–41.0) Raised blood pressure (or on medication) Men 41.6 (38.5–44.7) 57.0 (51.5–62.4) Women 35.6 (33.0–38.2) 61.1 (56.7–65.4) Raised blood pressure (NOT on medication) Men 33.1 (29.8–36.4) 42.3 (35.9–48.8) Women 21.4 (18.8–23.9) 35.6 (30.7–40.4) Raised blood glucose (or on medication) Men 2.5 (1.5–3.6) 5.0 (3.1–6.9) Women 2.5 (1.7–3.3) 6.8 (4.8–8.8) Raised cholesterol (or on medication) Men 34.1 (31.0–37.2) 31.4 (26.9–36.0) Women 38.3 (35.3–41.2) 51.0 (46.8–55.3) CI: confidence interval. Table A1.13. Prevalence of behavioural risk factors by marital status Risk factor 1 = single (never married, separated, divorced or widowed) % (CI 95%) 2 = joined (currently married or cohabiting) % (CI 95%) Current tobacco users Men 52.4 (48.0–56.8) 46.0 (42.7–49.3) Women 14.4 (11.9–17.0) 11.3 (9.5–13.2) Alcohol Men 59.3 (53.7–65.0) 68.3 (64.7–71.8) Women 41.5 (37.1–46.0) 41.9 (38.4–45.4) Alcohol (heavy episodic) Men 32.8 (27.9–37.8) 36.2 (32.7–39.8) Women 6.9 (5.1–8.8) 6.9 (5.3–8.5) Unhealthy diet (< 5 fruit/veg per day) Men 76.6 (71.1–82.1) 78.7 (75.2–82.2) Women 70.0 (65.1–74.9) 67.3 (63.3–71.2) Unhealthy diet (add salt) Men 37.9 (31.5–44.3) 34.6 (30.7–38.5) Women 29.2 (24.9–33.4) 27.2 (23.3–31.0) Unhealthy diet (processed foods) Men 45.5 (39.8–51.2) 42.4 (38.9–46.0) Women 28.3 (24.7–31.9) 28.6 (25.5–31.6) Insufficient physical activity Men 9.4 (6.7–12.1) 14.8 (12.2–17.5) Women 13.2 (10.5–15.8) 13.7 (11.2–16.1) CI: confidence interval. Table A1.14. Prevalence of biological risk factors by marital status Risk factor 1 = single (never married, separated, divorced or widowed) % (CI 95%) 2 = joined (currently married or cohabiting) % (CI 95%) Overweight (BMI ≥ 25) Men 50.6 (45.6–55.5) 67.9 (64.9–71.0) Women 52.7 (49.2–56.2) 64.6 (61.6–67.6) Obesity (BMI ≥ 30) Men 12.5 (9.9–15.1) 24.7 (21.8–27.5) Women 24.4 (21.4–27.3) 34.1 (31.3–36.9) Raised blood pressure (or on medication) Men 32.4 (27.9–36.9) 53.4 (50.2–56.7) Women 41.9 (38.5–45.2) 45.7 (42.7–48.8) 41 GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS ANNEX Table A1.14 contd Risk factor 1 = single (never married, separated, divorced or widowed) % (CI 95%) 2 = joined (currently married or cohabiting) % (CI 95%) Raised blood pressure (NOT on medication) Men 27.0 (22.7–31.4) 41.0 (37.2–44.8) Women 22.5 (19.5–25.4) 27.1 (23.9–30.2) Raised blood glucose (or on medication) Men 2.0 (1.0–3.0) 3.9 (2.6–5.2) Women 3.6 (2.4–4.9) 4.1 (2.9–5.4) Raised cholesterol (or on medication) Men 22.0 (18.5–25.6) 39.9 (36.6–43.2) Women 41.0 (37.2–44.8) 43.6 (40.6–46.7) CI: confidence interval. Table A1.15. Percentages not measured for risk factors by a health-care professional Risk factor measurement Men% (CI 95%) Women % (CI 95%) Blood pressure not measured 2.1 (1.4–2.9) 1.0 (0.4–1.5) Blood glucose not measured 12.9 (10.2–15.6) 9.7 (7.6–11.8) Cholesterol not measured 23.4 (20.1–26.7) 19.1 (16.4–21.9) CI: confidence interval. Table A1.16. Percentages not measured for risk factors by age group Risk factor Aged 18–29% (CI 95%) Aged 30–44 % (CI 95%) Aged 45–59 % (CI 95%) Aged 60–69 % (CI 95%) Blood pressure not measured Men 3.9 (1.7–6.1) 1.4 (0.5–2.3) 1.8 (0.8–2.8) 1.1 (0.1–2.2) Women 2.5 (0.3–4.8) 0.6 (0.0–1.1) 0.5 (0.0–1.0) 0.6 (0.0–1.3) Blood glucose not measured Men 16.4 (11.3–21.5) 13.5 (9.6–17.5) 10.6 (7.5–13.8) 10.1 (6.4–13.7) Women 15.7 (11.0–20.4) 9.7 (6.9–12.6) 7.9 (5.5–10.2) 5.8 (3.6–8.0) Cholesterol not measured Men 35.3 (28.2–42.5) 24.1 (19.4–28.9) 16.1 (12.4–19.7) 15.8 (11.4–20.2) Women 36.4 (29.6–43.1) 20.0 (16.0–24.0) 13.3 (10.4–16.1) 7.3 (4.9–9.7) CI: confidence interval. Table A1.17. Percentages not measured for risk factors by geographic location Risk factor Rural % (CI 95%) Urban % (CI 95%) Blood pressure not measured Men 2.6 (1.4–3.9) 1.6 (0.8–2.5) Women 0.8 (0.2–1.4) 1.1 (0.2–2.0) Blood glucose not measured Men 14.2 (10.0–18.5) 11.7 (8.2–15.3) Women 13.1 (9.3–16.9) 7.1 (4.8–9.4) Cholesterol not measured Men 25.1 (20.3–29.8) 21.8 (17.3–26.4) Women 22.6 (18.3–26.9) 16.5 (12.9–20.0) CI: confidence interval. 42 GENDER AND NONCOMMUNICABLE DISEASES IN BELARUS Table A1.18. Percentages not measured for risk factors by education level Risk factor Low% (CI 95%) Medium % (CI 95%) High % (CI 95%) Blood pressure not measured Men 3.7 (1.8–5.6) 1.2 (0.5–1.9) 3.0 (0.9–5.1) Women 1.4 (0.0–2.9) 0.8 (0.2–1.4) 0.9 (0.1–1.7) Blood glucose not measured Men 17.7 (12.6–22.8) 11.2 (8.5–13.9) 12.2 (7.8–16.5) Women 12.7 (8.6–16.9) 9.8 (7.4–12.2) 7.7 (5.0–10.4) Cholesterol not measured Men 28.6 (22.9–34.3) 22.0 (18.4–25.6) 21.3 (16.1–26.5) Women 22.0 (16.5–27.6) 19.0 (15.9–22.1) 17.5 (13.5–21.5) CI: confidence interval. Table A1.19. Percentages not measured for risk factors by employment status Risk factor Employed% (CI 95%) Unemployed or not in the labour force % (CI 95%) Blood pressure not measured Men 0.9 (0.4–1.5) 5.4 (0.5–10.3) Women 0.7 (0.2–1.2) 3.3 (0.0–8.5) Blood glucose not measured Men 10.8 (8.1–13.4) 19.3 (9.2–29.4) Women 9.7 (7.5–12.0) 7.6 (0.0–16.1) Cholesterol not measured Men 21.9 (18.5–25.3) 25.1 (13.9–36.4) Women 20.0 (16.9–23.0) 7.1 (0.0–15.4) CI: confidence interval. Table A1.20. Percentages not measured for risk factors by marital status Risk factor Single% (CI 95%) Joined % (CI 95%) Blood pressure not measured Men 3.9 (2.2–5.6) 1.1 (0.5–1.6) Women 1.8 (0.6–3.1) 0.4 (0.0–0.8) Blood glucose not measured Men 15.7 (11.8–19.5) 11.3 (8.5–14.0) Women 10.2 (7.6–12.8) 9.4 (7.0–11.8) Cholesterol not measured Men 29.2 (24.0–34.4) 19.9 (16.6–23.2) Women 18.5 (15.0–22.1) 19.5 (16.4–22.6) CI: confidence interval. Table A1.21. Percentages of lifestyle advice given for related risk factors Advice given % (CI 95%) Prevalence of related risk factor % (CI 95%) Tobacco Men 43.6 (40.0–47.1) 48.4 (42.8–48.6) Women 20.7 (17.6–23.9) 12.6 (8.9–11.6) Diet – added salt Men 42.3 (38.5–46.2) 35.8 (31.9–39.7) Women 41.7 (37.8–45.6) 28.0 (24.5–31.4) Diet – fruit and vegetables Men 38.9 (34.5–43.3) 77.9 (74.3–81.5) Women 42.7 (38.8–46.7) 68.4 (64.7–72.0) Physical activity Men 38.6 (34.4–42.7) 12.8 (10.7–14.9) Women 43.2 (39.5–46.9) 13.5 (11.5–15.5) Body weight Men 38.2 (34.1–42.3) 61.5 (58.7–64.2) Women 46.8 (43.1–50.5) 60.0 (57.3–62.4) CI: confidence interval. 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