Jocelyn E. Finlay

Demographic and health surveys: a profile

Demographic and Health Surveys (DHS) are comparable nationally representative household surveys that have been conducted in more than 85 countries worldwide since 1984. The DHS were initially designed to expand on demographic, fertility and family planning data collected in the World Fertility Surveys and Contraceptive Prevalence Surveys, and continue to provide an important resource for the monitoring of vital statistics and population health indicators in low- and middle-income countries. The DHS collect a wide range of objective and self-reported data with a strong focus on indicators of fertility, reproductive health, maternal and child health, mortality, nutrition and self-reported health behaviours among adults. Key advantages of the DHS include high response rates, national coverage, high quality interviewer training, standardized data collection procedures across countries and consistent content over time, allowing comparability across populations cross-sectionally and over time. Data from DHS facilitate epidemiological research focused on monitoring of prevalence, trends and inequalities. A variety of robust observational data analysis methods have been used, including cross-sectional designs, repeated cross-sectional designs, spatial and multilevel analyses, intra-household designs and cross-comparative analyses. In this profile, we present an overview of the DHS along with an introduction to the potential scope for these data in contributing to the field of micro- and macro-epidemiology. DHS datasets are available for researchers through MEASURE DHS at www.measuredhs.com.

The association of maternal age with infant mortality, child anthropometric failure, diarrhoea and anaemia for first births: evidence from 55 low- and middle-income countries.

Objective To examine the association between maternal age at first birth and infant mortality, stunting, underweight, wasting, diarrhoea and anaemia in children in low- and middle-income countries. Design Cross-sectional analysis of nationally representative household samples. A modified Poisson regression model is used to estimate unadjusted and adjusted RR ratios. Setting Low- and middle-income countries. Population First births to women aged 12–35 where this birth occurred 12–60 months prior to interview. The sample for analysing infant mortality is comprised of 176 583 children in 55 low- and middle-income countries across 118 Demographic and Health Surveys conducted between 1990 and 2008. Main outcome measures Infant mortality in children under 12 months and stunting, underweight, wasting, diarrhoea and anaemia in children under 5 years. Results The investigation reveals two salient findings. First, in the sample of women who had their first birth between the ages of 12 and 35, the risk of poor child health outcome is lowest for women who have their first birth between the ages of 27 and 29. Second, the results indicate that both biological and social mechanisms play a role in explaining why children of young mothers have poorer outcomes. Conclusions The first-born children of adolescent mothers are the most vulnerable to infant mortality and poor child health outcomes. Additionally, first time mothers up to the age of 27 have a higher risk of having a child who has stunting, diarrhoea and moderate or severe anaemia. Maternal and child health programs should take account of this increased risk even for mothers in their early 20s. Increasing the age at first birth in developing countries may have large benefits in terms of child health.

Association between economic growth and early childhood undernutrition: evidence from 121 Demographic and Health Surveys from 36 low-income and middle-income countries

BACKGROUND Economic growth is widely regarded as a necessary, and often sufficient, condition for the improvement of population health. We aimed to assess whether macroeconomic growth was associated with reductions in early childhood undernutrition in low-income and middle-income countries. METHODS We analysed data from 121 Demographic and Health Surveys from 36 countries done between Jan 1, 1990, and Dec 31, 2011. The sample consisted of nationally representative cross-sectional surveys of children aged 0-35 months, and the outcome variables were stunting, underweight, and wasting. The main independent variable was per-head gross domestic product (GDP) in constant prices and adjusted for purchasing power parity. We used logistic regression models to estimate the association between changes in per-head GDP and changes in child undernutrition outcomes. Models were adjusted for country fixed effects, survey-year fixed effects, clustering, and demographic and socioeconomic covariates for the child, mother, and household. FINDINGS Sample sizes were 462,854 for stunting, 485,152 for underweight, and 459,538 for wasting. Overall, 35·6% (95% CI 35·4-35·9) of young children were stunted (ranging from 8·7% [7·6-9·7] in Jordan to 51·1% [49·1-53·1] in Niger), 22·7% (22·5-22·9) were underweight (ranging from 1·8% [1·3-2·3] in Jordan to 41·7% [41·1-42·3] in India), and 12·8% (12·6-12·9) were wasted (ranging from 1·2% [0·6-1·8] in Peru to 28·8% [27·5-30·0] in Burkina Faso). At the country level, no association was seen between average changes in the prevalence of child undernutrition outcomes and average growth of per-head GDP. In models adjusted only for country and survey-year fixed effects, a 5% increase in per-head GDP was associated with an odds ratio (OR) of 0·993 (95% CI 0·989-0·995) for stunting, 0·986 (0·982-0·990) for underweight, and 0·984 (0·981-0·986) for wasting. ORs after adjustment for the full set of covariates were 0·996 (0·993-1·000) for stunting, 0·989 (0·985-0·992) for underweight, and 0·983 (0·979-0·986) for wasting. These findings were consistent across various subsamples and for alternative variable specifications. Notably, no association was seen between per-head GDP and undernutrition in young children from the poorest household wealth quintile. ORs for the poorest wealth quintile were 0·997 (0·990-1·004) for stunting, 0·999 (0·991-1·008) for underweight, and 0·991 (0·978-1·004) for wasting. INTERPRETATION A quantitatively very small to null association was seen between increases in per-head GDP and reductions in early childhood undernutrition, emphasising the need for direct health investments to improve the nutritional status of children in low-income and middle-income countries. FUNDING None.

Population Aging and Economic Growth in Asia

The decline in the total fertility rate between 1960 and 2005, coupled with an increase in life expectancy and the dynamic evolution of past variation in birth and death rates, is producing a significant shift in age structure in Asia. The age distribution has shifted from one with a high youth-age population share to one with a high old-age population share. We illustrate the role of these separate forces in shaping the age distribution. We also argue that the economic consequences of population aging depend on behavioral responses to the shift in age structure: the female labor force participation response to the decline in fertility, child quality/quantity trade-off in the face of the fertility decline, savings adjustments to an increase in life expectancy, and social security distortions insofar as the pace of life expectancy improvements is faster than the pace of policy adjustments. We estimate the association between old- and youth-age population shares and economic growth. The results suggest that population aging may not significantly impede economic performance in Asia in the long run.

Height of Nations: A Socioeconomic Analysis of Cohort Differences and Patterns among Women in 54 Low- to Middle-Income Countries

Background Adult height is a useful biological measure of long term population health and well being. We examined the cohort differences and socioeconomic patterning in adult height in low- to middle-income countries. Methods/Findings We analyzed cross-sectional, representative samples of 364538 women aged 25-49 years drawn from 54 Demographic and Health Surveys (DHS) conducted between 1994 and 2008. Linear multilevel regression models included year of birth, household wealth, education, and area of residence, and accounted for clustering by primary sampling units and countries. Attained height was measured using an adjustable measuring board. A yearly change in birth cohorts starting with those born in 1945 was associated with a 0.0138 cm (95% CI 0.0107, 0.0169) increase in height. Increases in heights in more recent birth year cohorts were largely concentrated in women from the richer wealth quintiles. 35 of the 54 countries experienced a decline (14) or stagnation (21) in height. The decline in heights was largely concentrated among the poorest wealth quintiles. There was a strong positive association between height and household wealth; those in two richest quintiles of household wealth were 1.988 cm (95% CI 1.886, 2.090) and 1.018 cm (95% CI 0.916, 1.120) taller, compared to those in the poorest wealth quintile. The strength of the association between wealth and height was positive (0.05 to 1.16) in 96% (52/54) countries. Conclusions Socioeconomic inequalities in height remain persistent. Height has stagnated or declined over the last decades in low- to middle-income countries, particularly in Africa, suggesting worsening nutritional and environmental circumstances during childhood.

The poor stay thinner: stable socioeconomic gradients in BMI among women in lower- and middle-income countries

BACKGROUND Recent studies have shown a strong positive association between individual BMI (in kg/m(2)) or overweight prevalence and socioeconomic status (SES) in low- and middle-income countries (LMICs). However, it is not clear whether this association is weakening or reversing over time. OBJECTIVE With the use of nationally representative data collected at 2 time points in 37 LMICs, we compared the associations of SES with BMI and of SES with overweight between the earlier surveys and the later surveys. DESIGN We conducted a cross-sectional analysis of nationally representative samples of 547,056 ever-married nonpregnant women aged 15-49 y: 208,570 women in the earlier round of surveys conducted between 1991 and 2003 and 338,486 women in the later round conducted between 1998 and 2008. We used linear and modified Poisson analyses with a country fixed effect to obtain a pooled estimate and a country-stratified analysis for country-specific estimates. RESULTS In adjusted models, BMI was 2.32 units higher (95% CI: 2.23, 2.41 units) among women in the wealthiest quintile compared with women in the poorest quintile in the earlier surveys and was 3.00 units higher (95% CI: 2.92, 3.07 units) in the later surveys. The association between BMI and wealth was positive in 37 countries in the earlier round of surveys and in 36 countries in the later round. Patterns were similar for overweight prevalence. CONCLUSION The association between SES and BMI or overweight is positive in most LMICs and has not weakened over time. It appears that the burden of overweight is consistently greater among wealthier populations within LMICs.

Global Burden of Double Malnutrition: Has Anyone Seen It?

Background Low- to middle-income countries (LMICs) are believed to be characterized by the coexistence of underweight and overweight. It has also been posited that such coexistence is appearing among the low socioeconomic status (SES) groups. Methods We conducted a cross-sectional analysis of nationally representative samples of 451321 women aged 20–49 years drawn from 57 Demographic and Health Surveys conducted between 1994 and 2008. Body Mass Index (BMI in kg/m2), was used to define underweight and overweight following conventional cut-points. Covariates included age, household wealth, education, and residence. We estimated multinomial multilevel models to assess the extent to which underweight (BMI<18.5 kg/m2) and overweight (BMI≥25.0 kg/m2) correlate at the country-level, and at the neighborhood-level within each country. Results In age-adjusted models, there was a strong negative correlation between likelihood of being underweight and overweight at country- (r = −0.79, p<0.001), and at the neighborhood-level within countries (r = −0.51, P<0.001). Negative correlations ranging from −0.11 to −0.90 were observed in 46 of the 57 countries at the neighborhood-level and 29/57 were statistically significant (p≤0.05). Similar negative correlations were observed in analyses restricted to low SES groups. Finally, the negative correlations across countries, and within-countries, appeared to be stable over time in a sub-set of 36 countries. Conclusion The explicitly negative correlations between prevalence of underweight and overweight at the country-level and at neighborhood-level suggest that the hypothesized coexistence of underweight and overweight has not yet occurred in a substantial manner in a majority of LMICs.

Consequences of maternal mortality on infant and child survival: a 25-year longitudinal analysis in Butajira Ethiopia (1987-2011)

AbstractaBackgroundMaternal mortality remains the leading cause of death and disability for reproductive-age women in resource-poor countries. The impact of a mother’s death on child outcomes is likely severe but has not been well quantified. This analysis examines survival outcomes for children whose mothers die during or shortly after childbirth in Butajira, Ethiopia.MethodsThis study uses data from the Butajira Health and Demographic Surveillance System (HDSS) site. Child outcomes were assessed using statistical tests to compare survival trajectories and age-specific mortality rates for children who did and did not experience a maternal death. The analyses leveraged the advantages of a large, long-term longitudinal dataset with a high frequency of data collection; but used a strict date-based method to code maternal deaths (as occurring within 42 or 365 days of childbirth), which may be subject to misclassification or recall bias.ResultsBetween 1987 and 2011, there were 18189 live births to 5119 mothers; and 73 mothers of 78 children died within the first year of their child’s life, with 45% of these (n=30) classified as maternal deaths due to women dying within 42 days of childbirth. Among the maternal deaths, 81% of these infants also died. Children who experienced a maternal death within 42 days of their birth faced 46 times greater risk of dying within one month when compared to babies whose mothers survived (95% confidence interval 25.84-81.92; or adjusted ratio, 57.24 with confidence interval 25.31-129.49).ConclusionsWhen a woman in this study population experienced a maternal death, her infant was much more likely to die than to survive—and the survival trajectory of these children is far worse than those of mothers who do not die postpartum. This highlights the importance of investigating how clinical care and socio-economic support programs can better address the needs of orphans, both throughout the intra- and post-partum periods as well as over the life course.

Fertility response to natural disasters : the case of three high mortality earthquakes

The event of a natural disaster, and being directly affected by it, brings a large shock to life-cycle outcomes. In addition to the replacement effects of higher fertility following a disaster that caused high mortality, a positive fertility response may be induced as children can be used to supplement household income. This paper analyzes three high mortality earthquakes: Gujarat, India, in 2001; North-West Frontier, Pakistan, in 2005; and Izmit, Turkey, in 1999. There is evidence of a positive fertility response to exposure to these large-scale natural disasters in addition to the response to child mortality. The results in this study are consistent with those of other studies that also find a positive fertility response following exposure to a disaster.

Weight of communities: A multilevel analysis of body mass index in 32,814 neighborhoods in 57 low- to middle-income countries (LMICs)

The extent to which body mass index (BMI) varies between small areas or neighborhoods in low- to middle-income countries (LMICs) remains unknown. Further, whether such variation is reflective of characteristics of individuals living in these neighborhoods is also not clear. We estimated the extent to which there is variation in BMI is attributable to neighborhoods in 57 LMICs. The data were from non-pregnant women of reproductive age (20-49 y) participating in Demographic and Health Surveys conducted in 57 countries between 1994 and 2008. Body mass index (BMI, weight [in kg] divided by height squared [in m(2)]) was used to assess weight status. Height and weight were measured objectively by trained field investigators. Age, household wealth, education were included as individual covariates and place of residence (urban or rural) as a neighborhood-level covariate. We conducted a multilevel analysis of 451,321 women (aged 20-49 y) from 32,814 neighborhoods and 57 countries. We used linear and multinomial models to partition the variation in BMI (in kg/m(2)), underweight (BMI <18.5 kg/m(2)) and overweight (BMI ≥25.0 kg/m(2)) at the level of neighborhoods and countries. We also explored the heterogeneity in neighborhood variation by socioeconomic status (SES). Of the total variation in BMI 17.6% was attributable to countries (Standard Deviation [SD] 2.0, 95% credible interval [CI] 1.7, 2.4) and 10.6% (SD 1.56, 95% CI 1.54, 1.58) was attributable to neighborhoods in age-adjusted models. Adjusting for individual- and neighborhood-level covariates reduced the SD attributable to countries and neighborhoods to 1.9, and 1.17, respectively. Between-country variation was 13.4% (SD 0.75, 95% CI 0.62-0.90) for underweight and 18.9% (SD 0.92, 95% CI 0.76-1.10) for overweight, and between-neighborhood variation was 7.7% (SD 0.57, 95% CI 0.55-0.58) for underweight and 7.1% (SD 0.56, 95% CI 0.55-0.58) for overweight in the fully-adjusted multinomial model. In country-specific models, the neighborhood variation in BMI ranged from 0.4 SD in Central African Republic to 2.7 SD in Sierra Leone in fully-adjusted models. Our results demonstrate a considerable range in neighborhood variation in BMI. In countries with greater neighborhood variation it is possible that BMI is being influenced by local conditions more than others with lesser neighborhood variation.