Demographic And Health Surveys Datasets Research Articles

Antenatal care coverage and early childhood mortality in Zimbabwe: new interpretations from nationally representative household surveys.

Zimbabwe has implemented universal antenatal care (ANC) policies since 1980 that have significantly contributed to improvements in ANC access and early childhood mortality rates. However, Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), two of Zimbabwe's main sources of health data and evidence, often provide seemingly different estimates of ANC coverage and under-five mortality rates. This creates confusion that can result in disparate policies and practices, with potential negative impacts on mother and child health in Zimbabwe. We conducted a comparability analysis of multiple DHS and MICS datasets to enhance the understanding of point estimates, temporal changes, rural-urban differences and reliability of estimates of ANC coverage and neonatal, infant and under-five mortality rates (NMR, IMR and U5MR, separately) from 2009 to 2019 in Zimbabwe. Our two samples z-tests revealed that both DHS and MICS indicated significant increases in ANC coverage and declines in IMR and U5MR but only from 2009 to 2015. NMR neither increased nor declined from 2009 to 2019. Rural-urban differences were significant for ANC coverage (2009-15 only) but not for NMR, IMR and U5MR. We found that there is a need for more precise DHS and MICS estimates of urban ANC coverage and all estimates of NMR, IMR and U5MR, and that shorter recall periods provide more reliable estimates of ANC coverage in Zimbabwe. Our findings represent new interpretations and clearer insights into progress and gaps around ANC coverage and under-five mortality rates that can inform the development, implementation, monitoring and evaluation of policy and practice responses and further research in Zimbabwe.

Predicting stunting in Rwanda using artificial neural networks: a demographic health survey 2020 analysis

Background Stunting is a serious public health concern in Rwanda, affecting around 33.3% of children under the age of five in 2020. Several examples of research have employed machine learning algorithms to predict stunting in Rwanda; however, no study used artificial neural networks (ANNs), despite their strong capacity to predict stunting. The purpose of this study was to predict stunting in Rwanda using ANNs and the most recent Demographic and Health Survey (DHS) data from 2020. Methods We used a multilayer perceptron (MLP) architecture to train and test the ANN model on a subset of the DHS dataset. The input variables for the model included child, parental and socio-demographic’s characteristics. The output variable was a binary indicator of stunting status (stunted vs. not stunted). Results An overall accuracy of 72.0% on the test set was observed, with an area under the receiver operating characteristic curve (AUC-ROC) of 0.84, indicating the model’s good performance. Several factors appear as important contributors to the probability of stunting among the negative value aspects. First and foremost, the mother’s height is important, as a lower height suggests an increased risk of stunting in children. Positive value characteristics, on the other hand, emphasie elements that reduce the likelihood of stunting. The timing of the initiation of breastfeeding stands out as a crucial factor, showing that early breastfeeding initiation has been linked with a decreased risk of stunting. Conclusions Our findings suggest that ANNs can be a useful tool for predicting stunting in Rwanda and identifying the most important associated factors for stunting. These insights can inform targeted interventions to reduce the burden of stunting in Rwanda and other low- and middle-income countries.

Exposure to interparental violence and risk of intimate partner violence among women in sexual unions in sub-Saharan Africa.

Intimate partner violence (IPV) has emerged as a serious human rights issue as well as a public health concern globally. We examined the association between exposure to interparental violence and experience of intimate partner violence (IPV) among women in sub-Saharan Africa (SSA) using Demographic and Health Survey (DHS) data. We included 96 782 women in 23 countries with a recent DHS dataset conducted from 2012 to 2020. We employed multivariable multinomial logistic regression to examine the association between exposure to interparental violence and experience of IPV. Overall, women who were exposed to interparental violence were more likely to experience physical (adjusted OR [aOR]=2.17, 95% CI 2.07 to 2.28), emotional (aOR=1.87, 95% CI 1.78 to 1.96) and sexual violence (aOR=2.02, 95% CI 1.90 to 2.15) than those who were not exposed. In all countries except Comoros, women exposed to interparental violence had higher odds of physical and emotional violence than those who were not exposed. Experience of sexual violence was higher among women exposed to interparental violence from all countries except for Liberia, Rwanda and Sierra Leone. Women's exposure to interparental violence increases their risk of experiencing IPV. Policies should focus on women or young girls who who witness IPV to reduce their likelihood of experiencing it. Special support can be provided for women who were exposed to interparental violence and are currently experiencing IPV.

Malaria prevalence and forest cover change in Kenya: a geospatial analysis

BackgroundThe relationship between forest cover loss and infectious disease risk needs further investigation, particularly in sub-Saharan Africa, and with regards to the effect to vulnerable populations—namely, children. The proposed research investigates the links between forest cover change and malaria. We aimed to identify spatiotemporal associations between deforestation and key children's health outcomes in sub-Saharan Africa nations affected by deforestation. Key aims were identifying: the amount of forest cover change most associated with malaria incidence changes; how these factors affect particularly vulnerable populations; what the most notable mechanisms were linking forest cover change to malaria incidence changes; how these findings informed the current theoretical understanding of the relationship between forest cover change and infectious disease risk; and identifying policy solutions that could avert any observed negative outcomes. MethodsWe propose regression analyses to investigate forest cover data and malaria incidence and paediatric (aged 2–10 years) prevalence data from selected US Agency for International Development's Demographic and Health Survey (DHS) datasets to assess the association between malaria disease and forest cover change. The research will use DHS-derived cluster sites along the human–wildlife interface in Kenya as geographical variables. The anticipated outcomes would show the relationship between forest cover change and malaria incidence and paediatric prevalence, while allowing for further mechanistic investigation. To measure forest cover change, a Normalized Vegetation Index and Enhanced Vegetation Index will be used. Malaria incidence and paediatric prevalence by cluster site is quantified in the DHS dataset. We plan to run logistical, multiple, and longitudinal regression analyses plotting forest cover change versus malaria incidence and paediatric prevalence at the cluster level at 5-year time points from 2000 to 2020. FindingsThis study is in the process of being completed, thus the findings are currently incomplete, bbut preliminary data will be available at the Planetary Health Alliance Annual Meeting in October 2022. We expect to show an association between substantial forest cover loss and higher malaria burden. The expected results would provide a basis and further opportunity for research to explore the causal relationship between these data. InterpretationThe relationship between forest cover loss and human health in areas along the human–wildlife interface is poorly understood. This research proposes an investigation into ecological determinants of of malarial disease. Although the connection between deforestation and infectious diseases is becoming more clear, additional data that expounds upon the ecological burden of disease for malaria in Kenya, and children as a vulnerable population, is needed in the literature. Understanding the relationship between forest cover and malarial disease might allow for the investigation of mechanistic properties that could further the evidence for a casual relationship between specific factors. FundingNational Academy of the Sciences, University of Wisconsin-Madison Global Health Institute Graduate Research Award.

The Double Burden of Overweight/Obesity and Anaemia Among Adult Women Living in Low–And Middle-Income Countries: A Secondary Analysis of Demographic and Health Surveys

ObjectivesThis study aimed to 1) quantify the magnitude and inequalities of the double burden of malnutrition (DBM), defined as the co-occurrence of overweight/obesity and anaemia, among adult women (20–49 years old) living in LMICs and 2) document trends in its magnitude and distribution over the past two decades. MethodsWe used all available data from the Demographic and Health Surveys (DHS) with anthropometric and haemoglobin level measures (n = 51 LMICs). The DBM magnitude and distribution (i.e., stratified estimates by wealth, education, and area of residence) were calculated using the most recent dataset for every country. Regional and overall pooled estimates were generated using a random-effects model. The trends analysis was conducted by use of 95 DHS datasets from 33 LMICs between 2000 and 2019. We computed DBM trends for all LMICs and by WHO region through multilevel regression models to estimate the average annual rate of change (AARC). ResultsThe pooled prevalence of concurrent overweight/obesity and anaemia was 12.4% (95% confidence interval (CI): 11.1, 13.7), ranging from 1.7% in Ethiopia to 33.6% in Maldives. The regional pooled prevalence ranged from 11.1% (95% CI: 9.2, 13.0) in the African region to 23.8% (95% CI: 17.0, 30.7) in the Eastern Mediterranean region. Overall, the highest burden of DBM was concentrated among women in the wealthiest quintiles, highest education levels and urban residents; although with some variation across countries and WHO regions. In the past two decades, there was a significant modest increase in DBM prevalence (AARC = 0.17pp; 95% CI: 0.07, 0.27; p-value = 0.001). The DBM increased fastest among women in the three middle wealth quintiles (AARC = 0.19pp (Q2), 0.18pp (Q3 and Q4)), lowest level of education (AARC = 0.16pp), and those living in rural areas (AARC = 0.18pp) and capital cities (AARC = 0.16pp). ConclusionsThe co-occurrence of overweight/obesity and anaemia is common among adult women and emulates the distribution of overweight/obesity in LMICs. A rising trend in DBM might indicate that efforts to reduce anaemia among women living with overweight/obesity need to be revisited. Funding SourcesNational Institute for Health Research (NIHR) Global Health Research Unit on Improving Health in Slums.

Significance of context, metrics and datasets in assessment of multidimensional energy poverty: A case study of Tajikistan

We applied the multidimensional energy poverty index (MEPI) to Tajikistan, using the Demographic and Health Survey (DHS) datasets to assess energy poverty at the national and sub-national levels, along the urban-rural gradient, and over time. The results showed very low energy poverty levels across the board. However, using the Khalon region survey, and applying the original index, we found substantially higher energy poverty levels. Whereas the MEPI results from DHS datasets were 0.15 for 2012 and 0.04 for 2017 for rural areas of Khatlon, the MEPI result from Khatlon dataset was 0.53. This is higher by about 253% against 2012 and a whopping 1225% against 2017 estimates. Modifying the indicators and weights and applying this modified index to the Khatlon dataset showed a higher result (0.54), but still in the moderate energy poverty category. Furthermore, we conducted assessment at the sub-regional level and by access to grid electricity in both the original and modified indices based on the Khatlon dataset, and found differences ranging from 0.47 to 0.80, i.e. moderate to acute energy poverty. Therefore, low results found using the DHS dataset likely underestimate the actual state of energy poverty in Tajikistan, whereas the Khatlon dataset showed substantially higher energy poverty levels that are closer to reality. These results offer valuable insights for policymakers and practitioners to investigate the actual state of energy poverty and explore measures to address this issue. We propose eight recommendations for future research into energy poverty measurement, focusing on study design and choice of indicators.

Women's Participation in Household Decision Making and Justification of Wife Beating: A Secondary Data Analysis from Pakistan's Demographic and Health Survey.

Introduction: Globally, women’s empowerment is one of the important factors impacting the development of the nation. However, several women in developing countries, including Pakistan, experience a high level of gender discrimination and inequity. In this study, data from the Demographic and Health Survey (DHS) were used to measure empowerment and its predictors among women in Pakistan. Methods: Pakistan’s 2017–2018 DHS dataset was used to measure women’s empowerment using two indicators, i.e., participation in decision making and views on wife beating among 4216 married women. The determinants of empowerment, such as age, place of residence, regions, wealth index, education, partner’s education, partner’s occupation, number of children, consanguinity, the age difference between husband and wife, house and land ownership, and house inheritance, are reported as prevalence ratios (PRs) with a 95% confidence intervals (CI). Multivariate regression models were used to produce covariate-adjusted PRs and 95% CIs. Results: More than half of all women were empowered (52.5%). Upon multivariate analysis, we identified that women from the province of Punjab (adjusted PR (aPR), 1.44; 95% CI, 1.20–1.73), Sindh (aPR, 1.62; 95% CI, 1.35–1.96), and KPK (aPR, 1.09; 95% CI, 0.91–1.31) compared to those living in Baluchistan; from the richest quantile (aPR, 1.65; 95% CI, 1.37–1.99), followed by the richer quantile (aPR, 1.54; 95% CI, 1.28–1.84), the middle quantile (aPR, 1.52; 95% CI, 1.28–1.81), and the poorer quantile (aPR, 1.24; 95% CI, 1.04–1.47) compared to women who were from the poorest quantile; who were highly educated (aPR, 1.45; 95% CI, 1.25–1.67), followed by those who had a secondary education (aPR, 1.32; 95% CI, 1.16–1.50) and a primary education (aPR, 1.17; 95% CI, 1.02–1.35) compared to women who were not educated; and had exposure to mass media (aPR, 1.20; 95% CI, 1.06–1.36) compared to those who had no exposure were more empowered. Conclusion: To conclude, women’s empowerment in Pakistan is affected by various socioeconomic factors, as well as exposure to mass media. Targeted strategies are needed to improve access to education, employment, and poverty alleviation among women, particularly those living in rural areas. Various mass media advertisements should be practiced, targeting community norms and supporting women’s empowerment.

Using DHS and MICS data to complement or replace NGO baseline health data: an exploratory study

Background: Non-government organizations (NGOs) spend substantial time and resources collecting baseline data in order to plan and implement health interventions with marginalized populations. Typically interviews with households, often mothers, take over an hour, placing a burden on the respondents. Meanwhile, estimates of numerous health and social indicators in many countries already exist in publicly available datasets, such as the Demographic and Health Surveys (DHS) and the Multiple Indicator Cluster Surveys (MICS), and it is worth considering whether these could serve as estimates of baseline conditions. The objective of this study was to compare indicator estimates from non-governmental organizations (NGO) health projects’ baseline reports with estimates calculated using the Demographic and Health Surveys (DHS) or the Multiple Indicator Cluster Surveys (MICS), matching for location, year, and season of data collection. Methods: We extracted estimates of 129 indicators from 46 NGO baseline reports, 25 DHS datasets and three MICS datasets, generating 1,996 pairs of matched DHS/MICS and NGO indicators. We subtracted NGO from DHS/MICS estimates to yield difference and absolute difference, exploring differences by indicator. We partitioned variance of the differences by geographical level, year, and season using ANOVA. Results: Differences between NGO and DHS/MICS estimates were large for many indicators but 33% fell within 5% of one another. Differences were smaller for indicators with prevalence <15% or >85%. Difference between estimates increased with increasing year and geographical level differences. However, <1% of the variance of the differences was explained by year, geographical level, and season. Conclusions: There are situations where publicly available data could complement NGO baseline survey data, most importantly when the NGO has tolerance for estimates of low or unknown accuracy.

Characterization of immunization secondary analyses using demographic and health surveys (DHS) and multiple indicator cluster surveys (MICS), 2006\u20132018

BackgroundInfant immunization coverage worldwide has plateaued at about 85%. Using existing survey data to conduct analyses beyond estimating coverage may help immunization programmes better tailor strategies to reach un- and under-immunized children. The Demographic and Health Survey (DHS) and the Multiple Indicators Cluster Survey (MICS), routinely conducted in low and middle-income countries (LMICs), collect immunization data, yet vaccination coverage is often the only indicator reported and used. We conducted a review of published immunization-related analyses to characterize and quantify immunization secondary analyses done using DHS and MICS databases.MethodsWe conducted a systematic search of the literature, of immunization-related secondary analyses from DHS or MICS published between 2006 and August 2018. We searched 15 electronic databases without language restrictions. For the articles included, relevant information was extracted and analyzed to summarize the characteristics of immunization-related secondary analyses. Results are presented following the PRISMA guidelines.ResultsAmong 1411 papers identified, 115 met our eligibility criteria; additionally, one article was supplemented by the Pan American Health Organization. The majority were published since 2012 (77.6%), and most (68.9%) had a first or corresponding author affiliated with institutions in high-income countries (as opposed to LMICs where these surveys are conducted). The median delay between survey implementation and publication of the secondary analysis was 5.4 years, with papers with authors affiliated to institutions in LMIC having a longer median publication delay (p < 0.001). Over 80% of the published analyses looked at factors associated with a specific vaccine or with full immunization. Quality proxies, such as reporting percent of immunization data from cards vs recall; occurrence and handling of missing data; whether survey analyses were weighted; and listing of potential biases or limitations of the original survey or analyses, were infrequently mentioned.ConclusionOur review suggests that more needs to be done to increase the increase the utilization of existing DHS and MICS datasets and improve the quality of the analyses to inform immunization programmes. This would include increasing the proportion of analyses done in LMICs, reducing the time lag between survey implementation and publication of additional analyses, and including more qualitative information about the survey in the publications to better interpret the results.

Using DHS and MICS data to complement or replace NGO baseline health data: an exploratory study.

Background: Non-government organizations (NGOs) spend substantial time and resources collecting baseline data in order to plan and implement health interventions with marginalized populations. Typically interviews with households, often mothers, take over an hour, placing a burden on the respondents. Meanwhile, estimates of numerous health and social indicators in many countries already exist in publicly available datasets, such as the Demographic and Health Surveys (DHS) and the Multiple Indicator Cluster Surveys (MICS), and it is worth considering whether these could serve as estimates of baseline conditions. The objective of this study was to compare indicator estimates from non-governmental organizations (NGO) health projects' baseline reports with estimates calculated using the Demographic and Health Surveys (DHS) or the Multiple Indicator Cluster Surveys (MICS), matching for location, year, and season of data collection. Methods: We extracted estimates of 129 indicators from 46 NGO baseline reports, 25 DHS datasets and three MICS datasets, generating 1,996 pairs of matched DHS/MICS and NGO indicators. We subtracted NGO from DHS/MICS estimates to yield difference and absolute difference, exploring differences by indicator. We partitioned variance of the differences by geographical level, year, and season using ANOVA. Results: Differences between NGO and DHS/MICS estimates were large for many indicators but 33% fell within 5% of one another. Differences were smaller for indicators with prevalence <15% or >85%. Difference between estimates increased with increasing year and geographical level differences. However, <1% of the variance of the differences was explained by year, geographical level, and season. Conclusions: There are situations where publicly available data could complement NGO baseline survey data, most importantly when the NGO has tolerance for estimates of low or unknown accuracy.

Vaccination assessments using the Demographic and Health Survey, 2005–2018: a scoping review

ObjectiveTo characterise studies which have used Demographic and Health Survey (DHS) datasets to evaluate vaccination status.DesignScoping review.Data sourcesElectronic databases including PubMed, EBSCOhost and POPLINE, from 2005 to 2018.Study selectionAll English...

Prenatal care coverage and correlates of HIV testing in sub-Saharan Africa: Insight from demographic and health surveys of 16 countries.

Prenatal screening of pregnant women for HIV is central to eliminating mother-to-child-transmission (MTCT) of HIV. While some countries in sub-Saharan Africa (SSA) have scaled up their prevention of MTCT programmes, ensuring a near-universal prenatal care HIV testing, and recording a significant reduction in new infection among children, several others have poor outcomes due to inadequate testing. We conducted a multi-country analysis of demographic and health surveys (DHS) to assess the coverage of HIV testing during pregnancy and also examine the factors associated with uptake. We analysed data of 64,933 women from 16 SSA countries with recent DHS datasets (2015-2018) using Stata version 16. Adjusted and unadjusted logistic regression models were used to examine correlates of prenatal care uptake of HIV testing. Statistical significance was set at p<0.05. Progress in scaling up of prenatal care HIV testing was uneven across SSA, with only 6.1% of pregnant women tested in Chad compared to 98.1% in Rwanda. While inequality in access to HIV testing among pregnant women is pervasive in most SSA countries and particularly in West and Central Africa sub-regions, a few countries, including Rwanda, South Africa, Zimbabwe, Malawi and Zambia have managed to eliminate wealth and rural-urban inequalities in access to prenatal care HIV testing. Our findings highlight the between countries and sub-regional disparities in prenatal care uptake of HIV testing in SSA. Even though no country has universal coverage of prenatal care HIV testing, East and Southern African regions have made remarkable progress towards ensuring no pregnant woman is left untested. However, the West and Central Africa regions had low coverage of prenatal care testing, with the rich and well educated having better access to testing, while the poor rarely tested. Addressing the inequitable access and coverage of HIV testing among pregnant women is vital in these sub-regions.

Assessing the impact of geographical access to health facilities on maternal healthcare utilization: evidence from the Burkina Faso demographic and health survey 2010

BackgroundImproving maternal and child health (MCH) remains a serious challenge for many developing countries. Geographical accessibility from a residence to the nearest health facility is suspected to be an important obstacle hampering the use of appropriate services for MCH especially in Sub-Sharan African countries. In Burkina Faso, a landlocked country in the Sahel region of West Africa, women’s use of proper healthcare services during pregnancy and childbirth is still low. This study therefore assessed the impact of geographical access to health facilities on maternal healthcare utilization in Burkina Faso.MethodsWe used the Burkina Faso demographic and health survey (DHS) 2010 dataset, with its sample of 10,364 mothers aged 15–49 years. Distance from residential areas to the closest health facility was measured by merging the DHS dataset with Geographic Information System data on the location of health centers in Burkina Faso. Multivariate logistic regressions were conducted to estimate the effects of distance on maternal healthcare utilization.ResultsRegression results revealed that the longer the distance to the closest health center, the less likely it is that a woman will receive appropriate maternal healthcare services. The estimates show that one kilometer increase in distance to the closest health center reduces the odds that a woman will receive four or more antenatal care by 0.05 and reduces by 0.267 the odds that she will deliver her baby with the assistance of a skilled birth attendant.ConclusionsImproving geographical access to health facilities increases the use of appropriate healthcare services during pregnancy and childbirth. Investment in transport infrastructure should be a prioritized target for further improvement in MCH in Burkina Faso.

Vaccination timeliness and co-administration among Kenyan children

BackgroundTimely administration of recommended vaccines requires children to have multiple vaccines co-administered in the first year of life. The objectives of this study were to estimate the proportion of timely vaccinations and the proportion of co-administered vaccines, and to assess the relationship between vaccine co-administration and vaccine timeliness in Kenyan children. MethodsUsing the 2014 Kenyan Demographic and Health Survey (DHS), we calculated the proportion of children who received co-administered and timely vaccine doses. Co-administration was defined as doses administered on the same day with dates recorded on vaccination cards. Vaccines were considered timely if given within four days before to four weeks after the recommended interval for administration. Results10,385 children aged 1–4 years in the Kenyan 2014 DHS dataset had vaccination cards which comprised the study sample. Analysis revealed wide a range for receipt of timely doses, from 90.2% for OPV0 to 56.0% for Measles. Co-administration of the 6-week dose was associated with 2.81 times higher odds of a timely Penta dose 1 (95% CI: 2.28, 3.46) and birth-dose co-administration was associated with a substantial increase in timely BCG vaccination: AOR 7.43 (95% CI: 6.31, 8.75). ConclusionsThough vaccine coverage in Kenya was high, timely vaccination was markedly low, with resultant implications for population immunity and potential spread of communicable diseases in unvaccinated infants. Co-administration of vaccines, place of residence, wealth index, and child age were consistently related to the odds of timely vaccine receipt. These relationships reinforce the importance of dedicating resources to programs that educate low socio-economic groups about the importance of vaccine co-administration.

The Rise of Female Sterilization: A Closer Look at Colombia.

Objective In the 1970s, OCPs and IUDs were the most popular contraceptive methods in Colombia. According to data from the most recent Demographic and Health Survey (DHS), sterilization has become the most common form of birth control in Colombia. This study aims to examine the characteristics of Colombian women desiring long-acting contraception. Methods This study uses the 2005 and 2010 Colombian DHS dataset. Women who choose long-acting contraception were divided into those using female sterilization and those using long-acting reversible contraception (LARC). A multivariate logistic regression model was used to compare demographic and social determinants of contraceptive choice among reproductive age women seeking long-acting contraception between the years 2005 and 2010. Results Among women using a long-acting contraceptive method in 2010, compared to 2005, women were significantly more likely to be sterilized (1.14 OR, 95% CI 1.09-1.18) and less likely to use LARC (0.88 OR, 95% CI 0.85-0.92). Of women seeking long-acting contraception, those exposed to a family planning provider were less likely to undergo sterilization (0.54 OR, 95% CI 0.51-0.58) and more likely to use LARC (1.84 OR, 95% CI 1.73-1.96). When compared to all contraceptive users, younger women and women with less than two children were more likely to use LARC than sterilization. Conclusion Between 2005 and 2010, an increase in the proportion of contracepting women being sterilized in Colombia occurred. Our findings suggest that exposure to a family planning provider and appropriate contraceptive counseling appears to be key determinants of long-acting contraceptive choice. To improve use of long-acting, effective contraception, efforts should be made to increase access to family planning providers.

Measurement of health literacy to advance global health research: a study based on Demographic and Health Surveys in 14 sub-Saharan countries

Abstract Background Education and literacy are key determinants of health, but these do not ensure health literacy. A definition of health literacy from the US Institute of Medicine (IOM) is widely accepted, but there is no consensus on the traits by which health literacy can be measured. Some questions in Demographic and Health Surveys (DHS) represent domains of health literacy as defined by the IOM (ie, the capacity to interpret, obtain, and understand health information; and the ability to make appropriate health decisions), and could be a valuable untapped resource for the measurement of health literacy. Building on pilot work in Zambia, we aimed to derive a measure of health literacy from information recorded in the DHS that aligned with the IOM definition. Methods We accessed data from surveys conducted between 2006 and 2015 in 14 sub-Saharan African countries: Cameroon, Democratic Republic of the Congo, Ethiopia, Ghana, Guinea, Cote d'Ivoire, Lesotho, Rwanda, Niger, Namibia, Sierra Leone, Swaziland, Togo, and Zambia. Surveys were the same in all countries, but translated to local languages as appropriate. We used factor analysis to extract one measure of health literacy and assessed its reliability and validity. We reclassified the continuous measure into tertiles and collapsed observations in the lower two groups to derive a dichotomous indicator. We then used χ 2 tests to assess whether the prevalence of (high) health literacy varied by demographics and country, accounting for sample weights. Findings We included 259 684 survey respondents aged 15–49 years. We identified eight survey questions that corresponded to elements of the four domains of IOM-defined health literacy. The questions addressed school and reading comprehension (capacity to interpret); reading magazines or listening to the radio or TV (capacity to obtain); learning family planning information (capacity to understand); and knowledge of a place to get an HIV test or acquire condoms (make appropriate health decisions). The derived continuous measure of health literacy demonstrated internal consistency (Cronbach's α = 0·72), and good content validity. Using the dichotomous indicator, overall prevalence of health literacy was 35·2% (95%CI 34·9–36·6%). Health literacy varied by sex (women 34·1% vs men 39·2%, p Interpretation Our study derives a robust indicator of IOM-defined health literacy in a large population in sub-Saharan Africa. Researchers could use this indicator with DHS datasets to measure health literacy in other countries, and ultimately examine how health literacy relates to health behaviour and outcomes, including for HIV/AIDS and domestic violence. Funding None.

Fertility Transitions in Ghana and Kenya: Trends, Determinants, and Implications for Policy and Programs

As a continent with 54 independent states Africa’s diversity is often highlighted but frequently forgotten when fertility is discussed. Fifty and more years ago to consider that all African countries and societies had a single fertility pattern (large numbers of children) and single trend (unchanging over time) was a valid characterization. Since the 1960s however that uniformity has disappeared replaced by substantial inter- and intra-country differences in fertility patterns and trends that render previous perceptions of continent-wide homogeneity obsolete. In this chapter we consider two African countries—Ghana and Kenya—whose fertility patterns and trends and their determinants have been well documented (Bongaarts 2008; Garenne 2008; Machiyama 2010; Shapiro and Gebreselassie 2008; Sneeringer 2009). Both countries have benefited from regularWorld Fertility Surveys (WFS) and Demographic and Health Surveys (DHS) that record trends in fertility family planning (FP) and other relevant indicators. The recently introduced Performance Monitoring and Accountability 2020 (PMA2020) surveys monitor progress since 2012 for the FP2020 initiative and occasional Situation Analysis and Service Provision Assessment surveys have also detailed the readiness of the health system in both countries to make quality FP services available. Ghana and Kenya share some common history: both have relatively strong health system legacies from the period of British colonialization; both were among the earliest countries to achieve independence; they were the first two African countries that developed policies to address population growth in the 1960s; and both have received substantial and sustained resources over several decades from many external donors and technical assistance organizations explicitly intended to increase the availability and quality of family planning services. However they are composed of cultures that are both diverse within each country and markedly different in many ways between the two countries. The two countries demonstrate remarkably different pathways in fertility and family planning patterns and trends from the 1970s to the present. We highlight some of the key differences and similarities explain why they have occurred and identify insights that could inform a wider understanding of fertility transitions and the role of family planning in other African countries. (excerpt)

Health literacy assessment in developing countries: a case study in Zambia.

Education and literacy are key determinants of health but do not necessarily ensure health literacy (HL). The Institute of Medicine's (IOM) definition of HL is widely accepted, but there is no consensus over its constituent parts. Developing a practical measure of HL is a priority, but challenging. We aimed to derive a measure of HL in data from the Demographic and Health Surveys (DHS) Program administered by the United States Agency for International Development (USAID), which includes items representing domains of HL as defined by the IOM. We accessed data from the DHS conducted in Zambia in 2007. We applied factor analysis methods to eight survey questions that corresponded to elements of the IOM definition. We derived a single indicator and evaluated for reliability and validity. The derived dichotomous measure of HL demonstrated reliability (Cronbach's α = 0.68), good content validity, and importantly was composed of the elements described by the IOM including capacity to obtain, interpret and understand health information, and make appropriate health decisions. Only 46.5% of males and 24.5% of females had high literacy. HL varied considerably across other subgroups. This is the first study to derive a robust indicator of HL following the IOM definition in a large national sample. By applying and evaluating this method in future studies, researchers can use this approach in other DHS datasets to measure HL in additional countries, and ultimately test how HL relates to health outcomes.

The Relationship between Livestock Ownership and Child Stunting in Three Countries in Eastern Africa Using National Survey Data.

Livestock ownership has the potential to improve child nutrition through various mechanisms, although direct evaluations of household livestock and child stunting status are uncommon. We conducted an analysis of Demographic and Health Survey (DHS) datasets from Ethiopia (2011), Kenya (2008–2009), and Uganda (2010) among rural children under 5 years of age to compare stunting status across levels of livestock ownership. We classified livestock ownership by summing reported household numbers of goats, sheep, cattle and chickens, as well as calculating a weighted score to combine multiple species. The primary association was assessed separately by country using a log-binomial model adjusted for wealth and region, which was then stratified by child diarrheal illness, animal-source foods intake, sub-region, and wealth index. This analysis included n = 8079 children from Ethiopia, n = 3903 children from Kenya, and n = 1645 from Uganda. A ten-fold increase in household livestock ownership had significant association with lower stunting prevalence in Ethiopia (Prevalence Ratio [PR] 0.95, 95% CI 0.92–0.98) and Uganda (PR 0.87, 95% CI 0.79–0.97), but not Kenya (PR 1.01, 95% CI 0.96–1.07). The weighted livestock score was only marginally associated with stunting status. The findings varied slightly by region, but not by wealth, diarrheal disease, or animal-source food intake. This analysis suggested a slightly beneficial effect of household livestock ownership on child stunting prevalence. The small effect size observed may be related to limitations of the DHS dataset or the potentially complicated relationship between malnutrition and livestock ownership, including livestock health and productivity.

Birth Weight and Early Childhood Physical Health: Evidence from a Sample of Latin American Twins

Birth Weight and Early Childhood Physical Health:Evidence from a Sample of Latin American Twins Victor Saldarriaga (bio) Low birth weight is considered one of the leading causes of infant mortality and adverse health conditions during childhood and throughout life. Most developed countries have therefore implemented health policies related to the improvement of birth weight of newborns. Examples include Medicaid and the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), both in the United States. Most of the existing literature evaluating the effects of nutritional programs targeted to pregnant and nursing women in developed countries emphasizes their positive effects on birth outcomes and the physical development of children, yet developing countries are still resistant to implementing social welfare programs aiming to enhance the nutritional status and prenatal care of pregnant women in order to improve the health of their babies.1 There is, however, an open discussion on whether birth weight is important in determining health status profiles and labor productivity later in adulthood or if this indicator of early nutritional status (arguably, in utero nutritional condition) captures other unobservable factors. Moreover, empirical evidence [End Page 161] is based on data sets linking clinical birth records with outcomes later in life, potentially introducing additional biases such as attrition and selection caused by the survival condition of individuals, reinforcing skepticism about the results. Altogether, these facts call into question the role of birth weight as a key indicator for the design of health-related policies and the effectiveness of government policies attempting to improve the healthcare of expectant mothers to reduce the prevalence of low birth weight. This paper focuses on determining the causal effect of birth weight on physical health for a sample of children in developing countries and contributes to the empirical literature regarding the effects of birth weight throughout the life span in three different ways. First, in contrast to previous empirical studies focusing on adult outcomes, this paper examines the effects of birth weight on the physical development of children under age five. Early developmental stages can have long-term effects on health, educational, and labor market outcomes, which can mediate the birth weight and educational or labor market gradients during adulthood.2 Second, in contrast to the existing literature focusing solely on developed countries, the paper provides evidence for ten Latin American countries using data from Demographic and Health Surveys (DHS). Finally, information included in the data set allows testing whether postnatal health investments (namely, breastfeeding and vaccination) can potentiate health and nutritional investments made by parents during periods prior to the birth of their children. One particular concern is that the effect of birth weight on the physical health of infants might be spurious due to omitted unobservable factors. In this regard, children’s birth weight and physical growth are mutually determined by genetics, environmental conditions to which the mother was exposed during pregnancy, family background, and socioeconomic status, among other factors. For this reason, cross-sectional estimates of the effects of birth weight on physical growth may contain confounding factors. To isolate the effects of variations of birth weight from unobservable factors, I use twin-pair fixed effects from a sample of twins born in ten Latin American countries. Information on twins’ weight at birth and physical health is obtained from a pooled sample of different years from the DHS data sets of each country. Since twins are exposed to the same conditions during pregnancy and the very moment of birth (for example, maternal stress, length of pregnancy, and institutionalized delivery), twin-based estimates successfully [End Page 162] identify the effect of physical growth under age five. The key insight of this approach is to assume that differences in birth weight between twins are purely due to nutritional intake within the womb, which depends on either the fetal position or the connection between the umbilical cord and the placenta, both of which are determined by nature. There are five important findings. First, consistent with previous empirical studies, cross-sectional estimates indeed overstate the effect of birth weight on children’s physical growth relative to twin-based estimates. Second, results arising from twin comparisons suggest that increasing birth weight significantly increases the height...