Association Between Schistosoma haematobium Exposure and Human Immunodeficiency Virus Infection Among Females in Mozambique

Recent evidence suggests an association between human immunodeficiency virus (HIV) and female genital schistosomiasis (FGS) in sub-Saharan Africa, especially in Mozambique, South Africa, Tanzania, and Zimbabwe. Women with FGS have increased numbers of HIV target cells and cell receptors in genital and blood compartments, potentially increasing the risk of HIV transmission per sexual exposure, and the association may explain the high female:male ratio of HIV prevalence unique to sub-Saharan Africa. We investigate this association in Mozambique by linking two georeferenced, high-quality secondary data sources on HIV prevalence and Schistosoma haematobium: the AIDS Indicator Survey, and the Global Neglected Tropical Diseases (GNTD) open-source database, respectively. We construct a schistosomiasis exposure covariate indicating women reporting “unimproved” daily drinking water sources and living no more than 2–5 km from high-endemic global positioning system (GPS) coordinates in the GNTD. In logistic regression analyses predicting HIV-positive status, we show that exposure increases the odds of HIV-positive status by three times, controlling for demographic and sexual risk factors

Three Essays on Wealth and Income Inequality and Population Health in Global and Domestic Contexts

Essay 1 investigates the contextual effect of community-level wealth inequality on HIV serostatus using DHS data pooled from six sub-Saharan African countries. Multilevel logistic regressions relate the binary dependent variable HIV positive serostatus and two weighted aggregate predictors generated from the DHS Wealth Index. A 1-point increase in the cluster-level Gini coefficient and cluster-level wealth ratio is associated with a 2.35 and 1.3 times increased likelihood of being HIV positive, respectively, controlling for individual-level demographic predictors, with larger effects in males. The association is partially mediated by more extramarital partners. Essay 2 uses multiple cohorts of the National Longitudinal Mortality Study (NLMS) to quantify the absolute income effect on mortality in the United States. Multivariate logistic regressions assess the impact on mortality rate ratios of two hypothetical interventions: lifting everyone living on an equivalized household income at or below the U.S. poverty line in 2000 to the income category just above, and shifting everyone’s income by 10–40% to the mean household income, equivalent to reducing the Gini coefficient by the same percentage. The absolute income effect is in the range of a three to four percent reduction in mortality for a 10% reduction in the Gini coefficient. Larger mortality reductions result from larger reductions in the Gini, but with diminishing returns. Inequalities in estimated mortality rates are reduced by a larger percentage than overall estimated mortality rates under the same counterfactual redistributions. Essay 3 uses multiple NLMS cohorts and multilevel Cox proportional hazards regressions to estimate the contextual effect of state-level income inequality on premature mortality in the United States. It uses six different measures of state income inequality, controls for inflation-adjusted, equivalized family income, and adjusts for eight individual-level socioeconomic and demographic variables, and for state-level percentage black and percentage in poverty. The contextual effect varies markedly by inequality measure, gender, and regression method. Effect sizes are generally in the range of a one to five percent increase in the likelihood of premature death for a one standard deviation increase in income inequality. The contextual effect may cause a sizeable number of premature deaths, especially among males.Doctor of Philosoph

AN ASSOCIATION BETWEEN NEIGHBOURHOOD WEALTH INEQUALITY AND HIV PREVALENCE IN SUB-SAHARAN AFRICA

This paper investigates whether community-level wealth inequality predicts HIV serostatus, using DHS household survey and HIV biomarker data for men and women ages 15-59 pooled from six sub-Saharan African countries with HIV prevalence rates exceeding five percent. The analysis relates the binary dependent variable HIV positive serostatus and two weighted aggregate predictors generated from the DHS Wealth Index: the Gini coefficient, and the ratio of the wealth of households in the top 20% wealth quintile to that of those in the bottom 20%. In separate multilevel logistic regression models, wealth inequality is used to predict HIV prevalence within each SEA, controlling for known individual-level demographic predictors of HIV serostatus. Potential individual-level sexual behavior mediating variables are added to assess attenuation, and ordered logit models investigate whether the effect is mediated through extramarital sexual partnerships. Both the cluster-level wealth Gini coefficient and wealth ratio significantly predict positive HIV serostatus: a 1 point increase in the cluster-level Gini coefficient and in the cluster-level wealth ratio is associated with a 2.35 and 1.3 times increased likelihood of being HIV positive, respectively, controlling for individual-level demographic predictors, and associations are stronger in models including only males. Adding sexual behavior variables attenuates the effects of both inequality measures. Reporting 11 plus lifetime sexual partners increases the odds of being HIV positive over five-fold. The likelihood of having more extramarital partners is significantly higher in clusters with greater wealth inequality measured by the wealth ratio. Disaggregating logit models by sex indicates important risk behavior differences. Household wealth inequality within DHS clusters predicts HIV serostatus, and the relationship is partially mediated by more extramarital partners. These results emphasize the importance of incorporating higher-level contextual factors, investigating behavioral mediators, and disaggregating by sex in assessing HIV risk in order to uncover potential mechanisms of action and points of preventive interventio

Millennium development goal 6 and HIV infection in Zambia : what can we learn from successive household surveys?

Background: Geographic location represents an ecological measure of HIV status and is a strong predictor of HIV prevalence. Given the complex nature of location effects, there is limited understanding of their impact on policies to reduce HIV prevalence. Methods: Participants were 3949 and 10 874 respondents from two consecutive Zambia Demographic and Health Surveys from 2001/2007 (mean age for men and women: 30.3 and 27.7 years, HIV prevalence 14.3% in 2001/2002; 30.3 and 28.0 years, HIV prevalence of 14.7% in 2007). A Bayesian geo-additive mixed model based on Markov Chain Monte Carlo techniques was used to map the change in the spatial distribution of HIV/AIDS prevalence at the provincial level during the 6-year period, accounting for important risk factors. Results: Overall HIV/AIDS prevalence changed little over the 6-year period, but the mapping of residual spatial effects at the provincial level suggested different regional patterns. A pronounced change in odds ratios in Lusaka and Copperbelt provinces in 2001/2002 and in Lusaka and Central provinces in 2007 was observed following adjustment for spatial autocorrelation. Western province went from a lower prevalence area in 2001 (13.4%) to a higher prevalence area in 2007 (17.3%). Southern province went from the highest prevalence area in 2001 (17.3%) to a lower prevalence area in 2007 (15.9%). Conclusion: Findings from two consecutive surveys corroborate the Zambian government's effort to achieve Millennium Developing Goal (MDG) 6. The novel finding of increased prevalence in Western province warrants further investigation. Spatially adjusted provincial-level HIV/AIDS prevalence maps are a useful tool for informing policies to achieve MDG 6 in Zambia. (C) 2011 Wolters Kluwer Health vertical bar Lippincott Williams & Wilkin

AN ASSOCIATION BETWEEN ETHNIC DIVERSITY AND HIV PREVALENCE IN SUB-SAHARAN AFRICA

This paper investigates whether ethnic diversity at the Demographic and Health Surveys (DHS) cluster level predicts HIV serostatus in three sub-Saharan African countries (Kenya, Malawi, and Zambia), using DHS household survey and HIV biomarker data for men and women ages 15–59 collected since 2006.. The analysis relates a binary dependent variable (HIV positive serostatus) and a weighted aggregate predictor variable representing the number of different ethnic groups within a DHS Statistical Enumeration Area (SEA) or cluster, which roughly corresponds to a neighborhood. Multilevel logistic regression is used to predict HIV prevalence within each SEA, controlling for known demographic, social, and behavioral and predictors of HIV serostatus. The key finding was that the cluster-level ethnic diversity measure was a significant predictor of HIV serostatus in Malawi and Zambia but not in Kenya. Additional results reflected the heterogeneity of the epidemics: male gender, marriage (Kenya), number of extramarital partners in the past year (Kenya and Malawi, but likely confounded with younger age), and Muslim religion (Zambia) were associated with lower odds of positive HIV serostatus. Condom use at last intercourse (a spurious result likely reflecting endogeneity), STD in the past year, number of lifetime sexual partners, age (Malawi and Zambia), education (Zambia), urban residence (Malawi and Zambia), and employment (Kenya and Malawi) were associated with higher odds of positive serostatus. Future studies might continue to employ multilevel models and incorporate additional, more robust controls for individual behavioral risk factors and for higher-level social and economic factors, in order to verify and further clarify the association between neighborhood ethnic diversity and HIV serostatus

A Regional Multilevel Analysis: Can Skilled Birth Attendants Uniformly Decrease Neonatal Mortality?

Globally 40% of deaths to children under-five occur in the very first month of life with three-quarters of these deaths occurring during the first week of life. The promotion of delivery with a skilled birth attendant (SBA) is being promoted as a strategy to reduce neonatal mortality. This study explored whether SBAs had a protective effect against neonatal mortality in three different regions of the world

Postnatal care by provider type and neonatal death in sub-Saharan Africa: a multilevel analysis

Abstract Background Globally postnatal care (PNC) of the newborn is being promoted as a strategy to reduce neonatal deaths, yet few studies have looked at associations between early PNC and neonatal outcomes in sub-Saharan Africa. In this study we look at the associations of PNC provided on day 1 and by day 7 of life by type of provider – skilled (doctor, midwife or nurse or unskilled (traditional birth attendant or community health worker) on neonatal death on days 2 to 7 and days 2 to 28. Methods Data from 10 African countries with recent (from 2009 onwards) Demographic and Health Surveys are pooled and used in a multilevel logistic regression analysis to study associations between the PNC variables with the mortality outcomes after controlling for relevant socioeconomic and maternal factors (including antenatal care, skilled delivery, tetanus immunization and ever breastfed). Results Findings indicate that PNC, whether provided by a skilled or unskilled provider, is protective against both neonatal death outcomes. Unskilled PNC on day 1was associated with a 32% decrease in the probability of death (compared to no PNC on day 1) during days 2 to 28 after controlling for other factors (OR: 0.68; 95% CI: 0.48, 0.97). Both skilled and unskilled PNC by day 7 were associated with reduced neonatal death during days 2 to 7 (Skilled: OR: 0.40; 95% CI 0.18, 0.88; Unskilled: OR 0.34; 95% CI 0.23, 0.52) and days 2 to 28 (Skilled: OR: 0.51; 95% CI 0.35, 0.75; Unskilled: OR 0.34; 95% CI 0.30, 0.38). There were also significant associations between four or more antenatal care visits and ever breastfed with both outcomes. Conclusion PNC is an important strategy to reduce neonatal death. While postnatal care by a skilled provider is a preferred strategy, PNC provided by unskilled providers can also serve as an intermediate implementation approach as countries strive to reach more newborns and save more lives

Gender Equality as a Means to Improve Maternal and Child Health in Africa

In this paper we examine whether measures of gender equality, household decision-making and attitudes toward gender-based violence are associated with maternal and child health outcomes in Africa. We pooled Demographic and Health Surveys (DHS) data from eight African countries and used multilevel logistic regression on two maternal health outcomes (low body mass index and facility delivery) and two child health outcomes (immunization status and treatment for an acute respiratory infection). We found protective associations between the gender equality measures and the outcomes studied, indicating that gender equality is a potential strategy to improve maternal and child health in Africa

The importance of skin–to–skin contact for early initiation of breastfeeding in Nigeria and Bangladesh

Skin–to–skin contact (SSC) between mother and newborn offers numerous protective effects, however it is an intervention that has been under–utilized. Our objectives are to understand which newborns in Bangladesh and Nigeria receive SSC and whether SSC is associated with the early initiation of breastfeeding

Postnatal care for newborns in Bangladesh: The importance of health–related factors and location

Bangladesh achieved Millennium Development Goal 4, a two thirds reduction in under–five mortality from 1990 to 2015. However neonatal mortality remains high, and neonatal deaths now account for 62% of under–five deaths in Bangladesh. The objective of this paper is to understand which newborns in Bangladesh are receiving postnatal care (PNC), a set of interventions with the potential to reduce neonatal mortality