Objectives. Using a sample of elementary and middle school students, we examined the associations between body mass index (BMI), obesity, and measures of the proximity of fast food and full service restaurants to students' residences. We controlled for socioeconomic status using a novel proxy measure based on housing values. Methods. We used BMI and obesity measures based on height and weight data collected as part of a school health assessment along with geocoded data on addresses of residences and food establishments. We constructed a proxy measure of socioeconomic status from public records of residential property assessments. These data were used to estimate logistic regression models of overweight and ordinary least squares models of BMI. Results. Students residing in homes with higher assessment values were significantly less likely to be obese, and had significantly lower BMIs. Upon controlling for socioeconomic status and other characteristics, the associations of BMI and obesity with proximity to food service establishments were reduced. Nonetheless, students who resided within one-tenth or one-quarter of a mile from a fast food restaurant had significantly higher values of BMI. The proximity of full service restaurants to residences did not have a significant positive association with either BMI or overweight. Conclusion. Public health efforts to limit access to fast food among nearby residents could have beneficial effects on child obesity. Public data on property value assessments may serve as useful approximations for socioeconomic status when address data are available.

ObjectiveCross-national studies provide inconclusive results as to the effectiveness of foreign health aid. We highlight a novel application of using subnational data to evaluate aid impacts, using Malawi as a case study.DesignWe employ two rounds of nationally representative household surveys (2004/2005 and 2010/2011) and geo-referenced foreign aid data. We examine the determinants of Malawi's traditional authorities receiving aid according to health, environmental risk, socioeconomic and political factors. We use two approaches to estimate the impact of aid on reducing malaria prevalence and increasing healthcare quality: difference-in-difference models, which include traditional authority and month-of-interview fixed effects and control for individual and household level time-varying factors, and entropy balancing, where models balance on health-related and socioeconomic baseline characteristics. General health aid and four specific health aid sectors are examined.ResultsTraditional authorities with greater proportions of individuals living in urban areas, more health facilities and greater proportions of those in major ethnic groups were more likely to receive aid. Difference-in-difference models show health infrastructure and parasitic disease control aid reduced malaria prevalence by 1.20 (95% CI −0.36 to 2.76) and 2.20 (95% CI 0.43 to 3.96) percentage points, respectively, and increased the likelihood of individuals reporting healthcare as more than adequate by 12.1 (95% CI 1.51 to 22.68) and 14.0 (95% CI 0.11 to 28.11) percentage points. Entropy balancing shows similar results.ConclusionsAid was targeted to areas with greater existing health infrastructure rather than areas most in need, but still effectively reduced malaria prevalence and enhanced self-reported healthcare quality.

Despite heterogeneity in income levels, countries implemented similarly strict containment and closure policies to mitigate the COVID-19 pandemic. This research assesses the effectiveness of these containment and closure policies, which we defined as larger decreases in mobility and smaller COVID-19 case and death growth rates. Using daily data for 113 countries on mobility and cumulative COVID-19 case and death counts over the 130 days between February 15, 2020 and June 23, 2020, we examined changes in mobility, morbidity, and mortality growth rates across the World Bank’s income group classifications. Containment policies correlated with the largest declines in mobility in higher income countries. High-income countries also achieved lower COVID-19 case and death growth rates than low-income countries. This study finds better epidemiological outcomes of containment and closure policies for higher income countries than lower income countries. These findings urge policymakers to consider contextual differences, including levels of economic activity and the structure of the economy, when crafting policies in response to public health emergencies.

Objective To test the impact of a nationwide Long-Lasting Insecticidal Nets [LLINs] distribution program in the Democratic Republic of Congo [DRC] on all-cause under-five child mortality exploiting subnational variation in malaria endemicity and the timing in the scale-up of the program across provinces. Design Geospatial Impact Evaluation using a difference-in-differences approach. Setting Democratic Republic of the Congo. Participants 52,656 children sampled in the 2007 and 2013/2014 DRC Demographic and Health Surveys. Interventions The analysis provides plausibly causal estimates of both average treatment effects of the LLIN distribution campaign and geospatial heterogeneity in these effects based on malaria endemicity. It compares the under-five, all-cause mortality for children pre- and post-LLIN campaign relative to children in those areas that had not yet been exposed to the campaign using a difference-in-differences model and controlling for year- and province-fixed effects, and province-level trends in mortality. Results We find that the campaign led to a 41% decline [3.7 percentage points, 95% CI 1.3 to 6.0] in under-5 mortality risk among children living in rural areas with malaria ecology above the sample median. Results were robust to controlling for household assets and the presence of other health aid programs. No effect was detected in children living in areas with malaria ecology below the median. Conclusion The findings of this paper make important contributions to the evidence base for the effectiveness of large scale-national LLIN campaigns against malaria. We found that the program was effective in areas of the DRC with the highest underlying risk of malaria. Targeting bednets to areas with greatest underlying risk for malaria may help to increase the efficiency of increasingly limited malaria resources but should be balanced against other malaria control concerns.