坦桑尼亚西北地区成年人死亡对儿童健康的影响

POLICY RESEARCH WORKING PAPER 2266 The Impact of Adult Deaths In Tanzania, a poor country experiencing a severe AIDS on unildren's Health in epidemic, the children whose Northwestern Tanzania health is hit hardest by the death of a parent or other adult are those in the poorest Martha Ainsworth households, those with Innocent Semali uneducated parents, and those with the least access to health care. Three important health interventions mitigate the impact of adult deaths: immunization against measles, ora! rehydration salts, and access to health care. The World Bank Development Research Group Poverty and Human Resources January 2000  [ ot,ICY RFSFARCH WORKING P APER 2266 Summary findings T'he AIDS epidemic is dramatically increasing mortality measles, oral rehydration salts, and access to health cate of adults in many Sub-Saharan African countries, with can do to nmitigate the impact of adu]t mor tality. potentially severe consequences for surviving family These programs disproportionately improve health members. Until now, most of these impacts had not been outcomes among the poorest children and, within that quantified. group, among children affected by adult mortality. Ainsworth and Semali examine the impact of adult In Tanzania there is so much poverty and child health mortaLity in Tanzania on three measures of health amrong indicators are so low that these interventions should be chiidren under five: morbidity, height for age, and targeted as much as possible to the poorest households, weight for height. The children hit hardest by the death whlere the children bit hardest by adult mortality are of a parent or other adult are those in the poorest most likely to be found. (Conceivably, the targeting households, those with uneducated parents, and those strategy for middle-income countries with severe AIDS with the least access to health care. ep.demics, such as Thailand, or countries with less Ainsworth and Semali also show how much three poverty and better child health indicators might be important health interventions - immunization against different.) This paper - a product of Poverty and Human Resources, Development Research Group - is part of a larger research project on "The Economic Impact of Fatal Adult Illness due to AIDS and Other Causes in Sub-Saharan Africa" (RPO 675-71). The study was funded by the Bank's Research Support Budget. Copies of this paper are available free from the World Bank, 1818 H Street, NW, Washington, DC 20433. Please contact Sheila Fallon, room MC3-558, telephone 202- 473-8009, fax 202-522-1153, email address sfallon@2worldbank.org. Policy Research Working Papers are also posted on the Web at www.worldbank.org/research/workingpapers. The authors may be contacted at mainsworth(2worldbank.org or isemali@muchs.ac.tz. January 2000. (35 pages) Th5e Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries they represent. Produced by the Policy Research Dissernination Center  The Impact of Adult Deaths on Children's Health in Northwestern Tau-zania by Martha Ainsworth Development Research Group, World Bank, Washington, DC, USA and Innocent Semali Muhimbili University College of Health Sciences, Dar es Salaam, Tanzania This paper is one of several outputs of the research project on "The economic impact of fatal adult illness due to AIDS and other causes in Sub-Saharan Africa", sponsored by the World Bank, USAID, and DANIDA. The opinions expressed in this paper are those of the authors and do not necessarily represent the positions of the World Bank or its members. We are grateful to Harold Alderman, Paurvi Bhatt, David Bishai, Julia Dayton, Deon Filmer, Peter Heywood, Emmanuel Jimenez, Kristen Marsh, and Adarn Wagstaff for comments on an earlier draft and to Kathleen Beegle, Susmita Ghosh, and Vajeera Dorabawila for their assistance in data cleaning and analysis.   I. Introduction The health of children in developing countries has improved dramatically over the past decades. Between 1960 and 1990, infant mortality declined by half-from 226 to 106 per thousand-as a result of rising incomes, improved health care, increases in female education, and better nutrition (World Bank 1993). There is also evidence from many developing countries that children are taller and less wasted than in the past (Alderman 1990, Den Besten and others 1995). These trends represent not only improved welfare now, but greater productivity when these children reach adulthood. Malnutrition leads to delayed intellectual development (Brown and Pollitt 1996). Better nutrition in early childhood can improve cognitive achievement and affect subsequent schooling decisions (Behrman 1993). Better nourished children have higher educational achievement, even after controlling for the home environment and parents' tastes (Glewwe and others 1998). Taller adults earn higher wages, even after controlling for education, and this effect is particularly pronounced in low-income countries (Strauss and Thomas 1998). The AIDS epidemic in Sub-Saharan Africa is already slowing if not reversing this trend (Timaeus 1998). In 15 countries, 5 percent or more of pregnant women attending prenatal clinics are infected with HIV, and in Southern Africa, maternal infection is as high as 30-40 percent (World Bank 1999). Children of HIV-positive mothers have higher prematurity, higher intra-uterine growth retardation, and higher incidence of low birthweight, compared to children of HIV-negative mothers (Taha et al 1995).1 Mortality rates of children born to HIV-positive mothers are 3-10 times higher than for children born to HIV- negative mothers (Boerma et al 1998, Lallemont et al 1989, Taha et al 1995).2 Some of the increased mortality of children of HIV-positive mothers is due to mother-to-child transmission of HIV. Without any intervention, 13-48 percent of all newborns contract HIV from their HIV-infected mothers in utero, at birth, or via breastfeeding (World Bank 1997). There is no cure for HIV/AIDS once the child has acquired it. Stunting, nutritional wasting, acute, chronic and persistent diarrhea, failure to thrive, pneumonia, thrush, and neurological abnormnalities are all associated with HWV infection in young children (Bailey et al 1999; Bobat et al 1998, 1999; Lepage et al 1996; Taha et al 1 These findings have not been universal, however. Lallemant et al (1989), for example, found no difference in the rate of stillbirths, gestational age, or birth weight among babies born to HlV-positive and HIV-negative mothers. Part of the reason for the diverse findings may be due to differences in methodology. Some are studies of HIV-positive and negative mothers that are "matched" on different characteristics, while others are prospective studies of HIV-positive and HIV-negative women and their children, in which socioeconomic and other characteristics are controlled for in multivariate analysis. 2 In a prospective study of HIV-positive and HIV-negative mothers in urban Malawi, the mortality rate at 30 months was three times higher for the children born to HIV-positive mothers (36%) than for HIV-negative mothers (12%) (Taha et al 1995). In a study that matched HIV-positive and HIV-negative mothers on age, date of delivery, and place of residence in Brazzaville, Congo, the survival rate at 12.5 months was 97% for children of 1  1999;Thea et al 1993). Treatment with AZT before, dujring, and after birth, and substitution of bottled for breastmilk can reduce mother-to-child transnission rates by half to two-thirds in controlled clinical trials, but are still expensive to implement successfully in resource-scarce settings. More recently, a single dose of nevirapine for mothers during labor and children after birth has been shown equally if not more effective and far less costly (Marseille et al 1999). The only intervention that completely protects children from mother to child transmission is prevention of HIV in the mother. Clearly, public policy on AIDS prevention will have an important role in reducing the impact of the epidemic on malnutrition, morbidity, and mortality of young children. The worsening of child health outcomes due to the AIDS epidemic reaches beyond the effects of mother-to-child transmission, however. Children not infected with HIV may have higher morbidity and lower nutritional status in a household with an AIDS patient because they are exposed to other infectious agents. Dayton (1999) finds a positive relation between parents' morbidity and low weight for height in children under 10 in the same sample of Tanzanian children studied here. The increased mortality of prime aged adults may also have important consequences for the health of orphaned children and other co- resident youngsters, through its economic impact. Producing healthy and well-nourished children requires key inputs, such as food and nutrients, health care, and the time of caretakers. The loss of productive adults reduces household income, indirectly redlucing the ability to purchase or produce these inputs and directly reducing the adult time available to transform them into improved child health. In addition, if investmnents in child quality are linked to some anticipated future return in terms of old age security for parents, and if other adults do not expect these returns from children who are not their own, then the loss of a parent will lead to lower investments in health care and schooling for orphaned children. To date, there is very little evidence about the magnitude of the impact of adult deaths on child health through channels other than mother-to-child transmission of HIV. In a study in Blantyre, Malawi, Taha et al (1996) found that, controlling for household socioeconomic characteristics, the child's gender, birthweight, first-born status, and the age and EIIV status of the mother, young children whose mothers died were 3.3 times more likely to die themselves, compared to the children of mothers who didn't die. In contrast, in Zaire, Ryder et al (1994) found ino difference in morbidity or indicators of social and economic well-being among HIV-negative AIDS orphans and age-matched children of HIV-positive and HIV-negative mothers alive at the time of the case mother's death. The authors concluded that "..the presence of a concerned extended family appeared to minimiize any adverse health and socioeconomic effects experienced by orphan children". In a large study in Bangladesh that was not related to the AIDS HIV-negative mothers but only 61% for children of HIV-positive mothers (Lallemant et al 1989). 2  epidemic and in which it can be presumed from the timing of the study (1983-89) that HIV infection was not a factor, Strong (1998) found higher mortality for both sons and daughters who lost their mothers but not for those who lost their fathers. There was also higher mortality among girls when a woman who was not the mother died, but the death rates for boys and girls were not affected by other adult deaths (age 15- 59). However, in a multivariate analysis of a subset of these children observed from age 12-83 months, deaths of other adults also significantly affected the child's survival probabilities. This paper uses longitudinal socioeconomic data collected from households in the Kagera Region of Northwestern Tanzania in 1991-94 to address two questions. First, what will be the impact of the loss of adults and parents on the health of young children? We consider both the effect of orphanhood and the effect of the loss of other productive adults in the household on the morbidity, height, and weight of children under five years of age. We know of no other studies of child health that have been able to examine these impacts: prime-aged adult deaths are rare and studying their impact would require a very large sample. The survey we use took place in a region with elevated adult mortality due to the AIDS epidemic, and was conducted in a random sample of households stratified on indicators predictive of adult mortality, increasing the probability of observing an adult death. In addition, many studies of the health status of children exclude from the analysis orphans and children living away from their parents because the characteristics of their parents are unknown (e.g., Alderman 1990, Sahn 1990, Strauss 1988). However, these children may be at greatest risk of poor health outcomes and are the focus of this study. The second issue we address is policies to reduce the impact of adult mortality on child health. There are many individual, household, community, and health-service factors that can affect child health outcomes. We identify the characteristics of children at greatest risk of poorer health as a result of adult deaths and the program inputs in the community and at the nearest health facilities that show the greatest positive relationship with child health. The next section discusses the economic model of the demand for child health that guides the choice of exogenous explanatory variables that are included as determinants of the reduced-form health demand equations. The third section describes the dataset and variables. The fourth section presents estimates of the reduced-form demand equations for current illness, height for age, and weight for height. In the final section we summarize the results and the main policy conclusions. 3  II. Analytic framework Child health outcomes are the result of numerous decisions by the household concerning food consumption, the use of medical care, the amount of time spent caring for children,3 and other "inputs" into childrearing. Exogenous factors also play a role-such as the child's (unobserved) frailty, disease vectors in the community, sanitation levels, food prices, the availability, quality and price of medical care, cultural practices, and social support structures. These affect child health either directly or indirectly by affecting household decisions on child health inputs. The characteristics of household members (such as their age, sex, or education)-particularly the mother's education-may affect the efficiency with which various inputs are used to produce childl health and the quality of those inputs, like child care time. Finally, individual characteristics such as the child's age and gender affect growth through biological channels. We posit that child health is produced at home according to equation (1), which expresses health outcomes of child i at time t as a function of three main household inputs: nutrient intake (Ni,); medical care (MIT); and the time input of adults (Ta'.). The efficiency of transforming these inputs into good health outcomes is mediated by parents' education (Efi"). Finally, the production of child health is conditioned on the child's individual endowments (CQ), household endowments (Chj), and community characteristics (Cj). (1) Hit = H (Nit, Mit, Tait E,fin;, Cit, Cho, Cyt, ei,) where h denotes the household, j denotes the community, and ei represents unobserved factors at the individual, household and community level that affect child health (see, for example, Behrnan and Deolalikar 1988, Schultz 1984). Child endowments include age and gender, household endowments include physical assets and human capital of household members, and community characteristics include the availability and price of medical care, food prices, disease vectors, wages, rainfall, and other exogenous community attributes. The death of a parent or adult in the household can be thought of as an exogenous shock to the child health production function. It will have a direct impact on household income, which conditions the purchase of child health services and food, as well as on the amount of adult time available to transform or 3 Child care includes time spent feeding, bathing, seeking medical care, and stimulating a child's cognitive development (Engle 1995). We expect that not only the availability of time for child care but the type of interaction will have important effects on child health. However, information on these specific behaviors are not available. 4  process these inputs into better child health outcomes. However, household structure and composition in these households are dynamic (Ainsworth et al 1995, Ainsworth 1989). The impact of adult deaths through income and time shocks on child health is likely to be transitory as surviving household members remarry, join, or leave the household. In much of Sub-Saharan Africa, children live in extended households that include multiple generations, aunts, uncles, and adult siblings. Thus, the death of an adult in the household does not necessarily imply that a child has lost his/her parent. The impact of these non-parental adult deaths may be thought of as transitory shocks to the production of child health. The death of a parent may have a more permanent effect, however. Other household members may not be good substitutes for a mother, for example, when children are very young and being breastfed. Parents, who have more intimate knowledge of their children's behavior and endowments, may be more efficient at transforming health and food inputs into child health. Further, the health of their children may hold greater weight in their own utility function than other children in the household. One's own children are a long-term source of income and old-age security in many societies; thus, a child's well-being is likely to be of concern to a parent, even if they must live apart. An adult in the household can be replaced, but the loss of the special attention given a child by a parent, especially early in life, is likely to have long-lasting implications. The first three arguments in the production function-nutrient intake, medical care, and adult time-are endogenous, representing household decisions about the use of inputs. Estimating equation (1) would reveal important technical relationships between child health outcomes and these key inputs. However, in practice, these production functions are very difficult to estimate because the inputs and outcomes are jointly determined (Cebu study team 1991). If we assume that households maximize the utility of their members over consumption, leisure, and child health, subject to a budget constraint and to the production function for child nutrition (1), we can solve for a reduced-form equation of the demand for child health, in which all of the explanatory variables are exogenous: (2) Hit = H ( EVi,Ct Cht, Cjt, Pjt, WV, Iht, Dht, error11), where Pj, and Wjt are community-level prices and wages, Ih, is exogenous household unearned income, and Dh, is a measure of recent adult death in the household. A child's "orphan status" (the survival of his/her parents) is part of Ci, his/her individual endowment. 5  In this reduced form model, adult deaths and parents' deaths are expected to worsen child health through their negative impact on household incorne and the availability of adult time for production of child health. Educated parents should have healthier children by marshalling information and other inputs more efficiently to affect child health. Higher prices of medical care and food are expected to worsen child health by reducing the demand for health care and nutrients/purchased food, while better access to medical care and child health services in particular should be associated with better health outcomes. Higher wage rates for adults and children in the community are posited to raise the opportunity cost of time of care givers, prompting them to reduce the time spent producing child health. However, to the extent that these opportunities also raise income, higher wages could have a net positive effect on child health. Household wealth or assets should be associated with better health through the ability to buy more medical care and to purchase more and better quality food. Health is multidimensional (Strauss and Thomas 1998). We estimate equation (2) for three related dimensions of child health: morbidity on the day of the interview; height for age; and weight for height. Low height in relation to a child's age is often reierred to as "stunting" and low weight for height as "wasting". Both stunting and wasting reflect nutritional status, but there is no necessary relation between stunting and wasting at a given point in time: "... stuntirng is the product of a cumulative history of episodes of stress that led to reduced growth rates and that were not later made up by catch-up growth during more favorable periods. ... wasting reflecis the presence or absence of stress at the time of measurement. These episodes of stress can be caused by chronic factors and/or by acute factors" (Martorell and Habicht 1986, p. 245). As noted by Waterlow (1992), weight deficits can be reversed quickly, while height deficits are slower to develop and slower to recover. Height for age should be thought of as reflecting a chronic process rather than chronic malnutrition. "...statistically, the two states of being wasted and stunted are not significantly associated" (Waterlow 1992, p. 195) Morbidity and malnutrition have a synergistic relationship. Illnesses such as tuberculosis, diarrhea, and measles, have well-documented biological effects on worsening children's nutritional status, while severely malnourished children have higher morbidity and mortality (Pelletier 1994, Waterlow 1992). Evidence of the impact of moderate malnutrition on the risk of morbidity and mortality of HIW-negative children is inconsistent and seems to depend on the setting (Chen et al 1980, :Pelletier 1994, Schroeder and Brown 1994, Waterlow 1992). In the case of children with HIV/AIDS, there is a clear relation between morbidity and anthropometric measures: HI-infected children are more likely to be stunted, underweight, and wasted compared to uninfected children of the same age, even when the mothers of the uninfected children are HIV-positive (Bailey et al 1999). 6  HII. Data and descriptive statistics The data for this analysis come from a longitudinal living standards survey of households conducted in the Kagera region of Northwestern Tanzania from 1991-94. Kagera is located to the west of Lake Victoria and borders the Rakai district of Uganda to the north, the countries of Rwanda and Burundi to the west, and Mwanza, Shinyanga, and Kigoma regions of Tanzania to the south. As of the 1988 census, about 1.3 million people lived in Kagera region. More than 80 percent of the population lives in rural areas, most of them involved in agriculture-tree crops in the north (bananas and coffee) and annual crops and livestock in the south. Because of its location next to Lake Victoria, which was settled by missionaries, the level of education in Kagera was one of the highest in Tanzania. Based on the dataset used for this analysis, household consumption expenditure per capita in the region was about $217 per capita in 1991, with a range of US$118 to $337 across the six districts. The impact of the mortality of prime aged adults is difficult to measure because mortality of adults 15-50 is a rare event. In Kagera, however, adult mortality is higher than would be expected because of the early spread of HIV/AIDS in the area around Lake Victoria. The first case of AIDS in Tanzania was identified in Kagera in 1983, although HIV was probably present in the area at least a decade earlier. The area is at a crossroads for long-range commerce between the East African coast and central Africa, and was also heavily affected by the war between Tanzania and Uganda in 1978-79. More recently, it has been the site of refugee camps for those fleeing from conflicts in Rwanda and Burundi. Thus, it is not surprising that HIV spread early and quickly in Kagera region and the surrounding areas. A population- based survey in Kagera in 1987 found that roughly a quarter of prime-aged adults in the regional capital of Bukoba were infected with HIV, as were 10 percent of prime-aged adults in the surrounding rural areas in the northern and eastern part of the region near Lake Victoria (Killewo and others 1990). However, there was also variation in infection across the region, with a 5 percent infection rate among adults in the west and less than one percent infection rate in the south. The dataset used here is the Kagera Health and Development Survey (KHDS), which interviewed 816 households over four passages at 7-month intervals between 1991 and 1994. The objective of the KHDS was to measure the economic impact of adult mortality on surviving household members. The household sample was random, stratified on geography, community adult mortality rates (as measured in the 1988 census and a subsequent enumeration for the survey), and indicators at the household level that were thought to be predictive of future adult deaths (see Over and Ainsworth 1989, Ainsworth and others 1992, KHDS research team 1999). A household was defined as a group of persons living and sharing meals together in the same dwelling for at least 3 of the past 12 months. The KHDS collected extensive, 7  detailed information on household income, consumption expenditure, and individual health status, including the height and weight of all household mnembers. In addition, a great deal of detail was obtained on the mortality of household members. The KHDS did not perform any medical tests to determine the HIV status of respondents. For the present analysis, we use health outcome measures from a maximum of 1,108 children under the age of 60 months, interviewed or measured from 14 times during the course of the survey, and for whom there were non-rnsing values of the dependent and explanatory variables.4 Over the four passages of the longitudinal survey, we have 2,679 total observations to analyze from these children. Table 1 defines the variables used in the analysis and provides descriptive statistics on the sample. Dependent variables Our first measure of child health is whether the child was reported to be ill or injured on the day of the interview. By this measure, more than a quarter of the children in the sample (29.3 percent) were sick.5 The most frequently reported symptoms were fever (26 percent) and diarrhea (15 percent). Parents or caregivers believed the children were suffering from: the cormnon cold (32 percent); malaria (11 percent); diarrhea (5 percent); parasites (5 percent); and measles (1 percent). In 41 percent of the cases "other illnesses" were cited. These assessments were based on their own observation or that of a health professional, if one was consulted. None of the parents or caregivers reported that a child was suffering from AIDS. This is not surprising, however, since few parents would be aware of their children's HIV status, and AIDS presents itself as a series of common childhood illnesses and symptoms. Of the 784 children reported sick on the day of the interview, 20 were suffering from 3 common AIDS symptoms and 4 were suffering from all four symptoms, although these could also be attributed to other severe illness.6 4298 were interviewed four times, 208 three times, 261 two times, and 341 one time. Descriptive statistics in the text pertain to the pooled sample of children, which includes observations from more than one time period for many of them. 5 There were several other measures of morbidity that could have been used, including: acute illness in the past 4 weeks; chronic illness lasting 6 months or more; chronic diarrhea or other symptoms of AIDS. We decided to use acute morbidity on the day of the interview as less subject to "telescoping" and recall biases than reported illness over a longer period (Behrman and Deolalikar 1988). Nevertheless, some bias in the reporting of child illness may remain and could be correlated with the socioeconomic characteristics of the household or the availability of health care (Sindelar and Thomas 1991, Strauss and Thomas 1998). 6 The four main symptoms of AIDS about which all respondents were queried are: chronic diarrhea; severe weight loss; chronic fever; and skin rash. 8  The second two indicators of child health are measurements of child height (or recumbent length) and weight. The nutrition indicators compare the weight and height of children in the KHDS sample with an international "reference" population of well-nourished children defined by the U.S. National Center for Health Statistics (NCHS) (WHO 1995). Researchers have found that well-nourished children in developing countries approach the mean nutritional status of the international reference population; environmental rather than genetic factors account for most differences in nutritional status (Habicht and others 1974, Martorell and Habicht 1986, Waterlow 1992). Each child's nutritional status can be described by the number of standard deviations of his/her height for age and weight for height from the median of the reference population, also called the "z- score". For example, the height of a child with a height/age z-score of zero is the same as the height of the median child of the same age in the reference population. The height of a child with a height/age z- score of -1 is one standard deviation (SD) below the median height of children of the same age in the reference population. The average child under five in the KHDS sample was short for his/her age but not thin. The mean height-for-age z-score was 1.7 standard deviations below the median of the reference population, while that for weight for height was only 0.26 standard deviations below the reference median. The conimnon cut-off point for identifying severely malnourished children is a measurement more than 2 SD below the median of the reference population. Children 2 SD below the median in height/age are "stunted", while those 2 SD below the median in weight/height are "wasted". In the NCHS reference population, only 2.3 percent of children would be classified as stunted or wasted. According to this definition, 37 percent of the children in the Kagera sample were stunted, 2 percent were wasted, one percent were both stunted and wasted, and 59 percent were neither stunted nor wasted. These levels of malnutrition are lower than was found in the 1991-92 Tanzania Demographic and Health Survey.7 Explanatory variables The explanatory variables in Table 1 are classified according to the factors in equation (2) that they represent. Individual endowments. These include the child's gender and age in months, his or her parents' education, and whether or not the child is an orphan. About half of the children were girls and the mean 7 The 1991-92 Tanzania Demographic and Health Survey found 47 percent of children under five stunted and 5.5 percent wasted, in a national sample (Bureau of Statistics 1993). 9  age was 29.8 months. Their mothers had 5 years of schooling, on average, and their fathers 6 years.8 In very young children, it is relatively rare to have lost a parent, particularly the mother. Over all of the observations in the sample, 4 percent had lost their mother and 11 percent their father: 2.9 percent had lost their mother only, 10.0 percent had lost their father only, and 1.3 percent had lost both parents. The rate of orphanhood increases by age: maternal orphan rates rise from 0.8 percent among children under two to 6.4 percent among children aged 2-4 years (not shown). Paternal orphan rates are usually higher than maternal rates because fathers are generally older. They ranged from 5.9 percent to 14.8 percent for children under 2 and aged 2-4, respectively. Adult tine. The time spent producing child health and the quality of that time was not available from the survey and, in any event, would be endogenous. Thus, we use three household composition variables as indicative of the potential availability of adult time in the production of child health: the number of female adults aged 15-50; the number of girls aged 7-14; and whether or not the head of the household is female. Controlling for other factors, we expect that households with more female caregivers will have better health outcomes and that female-headed households may be more cognizant of or attentive to child health problems but perhaps more constrained for time inputs into child care. There were about 1.8 female adults and one girl aged 7-14 in the household of the average child; 23 percent lived in female- headed households. 8 Other analyses of the determinants of child health have dropped children whose parents are not in the household (including orphans) because they are missing variables like mother's height and age (Alderman 1990, Sahn 1990, Strauss 1988). Others have retained parentless children by including a dummy variable for the absence of the parent, but this doesn't solve the problem of not being able to control for these variables in the most affected children. In this analysis, we do not control for parents' height, age, or other variables not available for children with missing parents. Parents' schooling can be included, however, because it was collected for all children, even if the parent was deceased or non-resident. 10  Table 1. Definition of variables and descripdve statistics (n=2,679 observations on 1,108 children) Variable Defimition Mean Std. Dev. D_pe n ill now Equals 1 if child was ill on the day of the survey, 0 .293 .455 otherwise. ht_age Height-for-age z-scorea -1.66 1.41 wt_ht Weight-for-height z-scoreb -.261 1.03 girl Equals 1 if child is female, 0 otherwise. .478 .500 months Child's age in months, entered in a quartic specification 29.8 17.4 (months, months squared/10, months cubed/100, months4/1000). momdead Equals 1 if child's mother is dead, 0 otherwise. .042 .201 daddead Equals 1 if child's father is dead, 0 otherwise. .113 .317 mgrade Years of completed schooling of mother.a 4.94 2.95 fgrade Years of completed schooling of father.a 5.91 2.88 female head Equals 1 if household head is female, 0 otherwise. .228 .420 female adults Number of adult females 15-50 in the household 1.78 1.28 female teens Number of females 7-14 in the household .968 1.08 good water Equals 1 if household drinking water source is piped or .198 .399 protected, 0 otherwise latrine Equals 1 if household has a pit latrine, 0 otherwise .956 .205 no toilet Equals 1 if household has no toilet or latrine, 0 otherwise .037 .189 coffee Equals I if household grows coffee, 0 otherwise .776 .417 good floor Equals 1 if floor of dwelling is other than dirt or mud, 0 .169 .375 otherwise. durables/adult Value of durable goods per adult/100 Tshs 165 946 distance Kilometers to the nearest health facility. 2.82 2.93 malnutrition Equals 1 if nearest health facility-offers child malnutrition .547 .498 services, 0 otherwisec ors Equals 1 if oral rehydration salts (used in the treatment of .739 .439 diarrhea) were in stock at the nearest health facility on the day of the interview, 0 otherwisec measles 35 Proportion of children 0-35 months who have been .695 .206 vaccinated against measles in other households of the same cluster. epidemic Equals 1 if community respondents reported an epidemic .176 .381 since the last interview or in the last year (for first interview), 0 otherwise aids Equals 1 if community respondents named AIDS as the .487 .500 11  #1 cause of adult death, 0 otherwise urban Equals 1 if urban commumity, 0 otherwise .264 .441 adult mortality rate Number of deaths of adults > 14 per 1000 total 14.8 8.01 population in the primary sampling unit enumerated in 1991 more rain Equals 1 if more rain this year than same time last year, 0 .328 .470 otherwise less rain Equals 1 if less rain this year than same time last year, 0 .114 .318 otherwise a market distance Distance to the nearest periodic market, in kilometers 3.92 5.79 road impassable Equals 1 if road to cluster is ever impassable during the .462 .499 year, 0 otherwise child labor Equals 1 if child wage cited for the cluster, 0 otherwise .483 .500 child wage Daily child wage in Tshs (set to zero if no child labor) 70.9 88.9 male labor Equals 1 if adult male wage cited for the cluster, 0 .914 .281 otherwise male wage Daily adult male wage in Tshs (set to zero if no adult 262 358 male labor) price index Cluster-level, time-varying price index. 1.20 .264 A~h .,t ,!i~tIls in =i~e _ elp7d adult death Equals 1 if an adult 15-50 died in the household since the .038 .192 last passage or (for the first passage) in the past 6 months, 0 otherwise adult death 0-3 Equals 1 if an adult 15-50 died in the household 0-3 .017 .130 months before the interview, 0 olherwise adult death 4-6 Equals 1 if an adult 15-50 died in the household 4-6 .019 .138 months before the intervilew, 0 olherwise adult death 7-9 Equals 1 if an adult 15-50 died in, the household 7-9 .015 .120 months before the interview, 0 olherwise a. Based on a sample of 1,085 children, with 2,641 observations. b. Based on a sample of 1,076 children, with 2,6:19 observations. c. The mean for all observations. For the three percent of child observations that could not be linked to the nearest health facility, the value has been set equal to zero. Among those observations that could be matched, the mean for the malnutrition variable is 0.564 and for the ORS variable is .762. Household sanition. Safe drinking water and sanitary waste disposal are thought to be important determinants of child morbidity, especially diarrhea (Tonglet et al 1992). Nearly a fifth of the children lived in households that had piped or protected drinking water sources-that is, inside taps, outside private or public standpipes, protected wells (with pumps), or water tanker trucks. Almost all of the children (95.6 %) lived in households with pit latrines, 3.7 % lived in households with no toilet, and the balance (< 1 %) had flush toilets. Perhaps because of the lack of variation in waste disposal among the households, the toilet and latrine variables were never statistically significant in any of the regressions; they were subsequently dropped. 12  Household assets. We use measures of assets instead of a measure of permanent household income, such as consumption expenditure, because the latter would directly include endogenous spending on health care and food. Coffee is the major cash crop in Kagera region, grown by the households of more than three-quarters of the children. Thus, coffee as a perennial tree crop not only signals an enduring asset (unlikely to vary much in the short run), it is also a proxy for the availability of cash income. The type of flooring of the household's dwelling is another indicator of wealth-17 percent of the children lived in dwellings with a concrete, wooden, tile, or parquet floor, while the rest lived in houses with mud or dirt floors.9 Finally, we include as a third asset variable the value of the household's durable goods (radios, bicycles, TV sets, and so forth) per adult. Nearly half (48%) of the children were in households that reported zero durable goods; the mean value of durable goods per adult across all children was 16,500 Tshs, or $49. Among those with any assets the mean was 31,800 Tshs, or $94. Health services. The KHDS conducted interviews at the nearest health facilities to each cluster of households, from which information on the availability of services could be obtained-in this case, whether the facility offered nutritional rehabilitation services and whether oral rehydration salts (ORS, for treating dehydration linked to diarrhea) were in stock the day of the interview. The distance between survey clusters and the nearest facilities was measured by the research team in the field. Child health should be negatively affected by greater distance to a health facility, but positively affected by the availability of these services. Community health indicators. Measles is a prime killer of children in Subsaharan Africa. It can reduce appetite for several weeks and lead to severe protein-energy malnutrition (Waterlow 1992). Measles vaccination among Bangladeshi children under five has been credited for a reduction in child mortality of 36-45 percent (Koenig et al 1990, 1991). The immunization rate for measles was computed from among children under three years of age in households of the same cluster, excluding the household of the reference child. The variables measuring whether or not there was a recent epidemic in the community and whether AIDS is reported as the prime cause of adult deaths come from a community questionnaire. Nearly half of the children were living in communities where AIDS was cited as the major cause of adult deaths, and one-fifth were in urban areas. The community adult mortality rate (age 15 and older) assigned to each child is based on the results of a house-to-house enumeration conducted for sampling purposes in 1991 in each primary sampling unit. The overall adult mortality rate of roughly 15/1000 is about three times higher than we would have expected in the absence of AIDS, although it is 9 Aside from being a measure of low wealth, a dirt floor may also affect young children's exposure to bacteria, 13  somewhat inflated by the inclusion of people over 50. We cannot predict a priori the relation between urban residence and morbidity; it may capture improved access to and quality of health and other services in urban areas. However, sanitation problems can also be more extreme in poor urban areas, with a higher concentration of people, and urban rates of HIV infection are higher. Community economic variables. The dummy variables for more or less rain than the same period last year, for whether the road is impassable, and for child and adult wages come from responses to the community questionnaire completed every passage in each of the 51 survey clusters. Market distances were measured by the field teams. The price index is based on a separate survey of market prices conducted contemporaneously with the household interviews. The questionnaire included prices for 26 food and 5 non-food items. These results were synthesized into a cluster-level, spatial and time-varying price index.'