Association between light at night and the risk of child death in sub-saharan Africa: a cross-sectional analysis based on DHS data.

BACKGROUND: The high under-five mortality rate (U5MR) in Africa is a significant public health concern. Previous studies have found that satellite retrieved light at night (LAN) data with long-term and global coverage can be used as a proxy for socio-economic development and urbanization. Currently, few studies on the effects of LAN on child mortality have been conducted in Africa, a region with varying levels of urbanization between countries. OBJECTIVE: To quantify the correlation between risk of child mortality and LAN as an indicator of urbanization and economic development in Africa. METHODS: Using data from the Demographic and Health Survey (DHS) database conducted in 15 African countries out of 46 countries from 2005 to 2013, this study estimated LAN levels for children based on their year of birth and residential addresses. This study used Cox proportional hazards models to assess the association between LAN and the risk of child mortality in Africa. RESULTS: The mean U5MR was 95 per 1,000 livebirths among the 15 African countries during 2005-2013. After adjusting for covariates, each 10-unit increment in LAN was associated with a 5.3% reduction in the risk of U5MR. The effect estimates were more pronounced in areas with lower LAN. CONCLUSION: In Africa, the risk of U5MR decreased with increasing LAN, especially in areas with lower LAN. The results suggest that the development of urbanization and socio-economic conditions may be beneficial to child health, especially in regions with low LAN. The use of LAN as a proxy may offer an intriguing approach for identifying areas requiring targeted development in urbanization and socio-economic conditions.

Flood exposure and pregnancy loss in 33 developing countries.

Floods have affected billions worldwide. Yet, the indirect health impacts of floods on vulnerable groups, particularly women in the developing world, remain underexplored. Here, we evaluated the risk of pregnancy loss for women exposed to floods. We analyzed 90,465 individual pregnancy loss records from 33 developing countries, cross-referencing each with spatial-temporal flood databases. We found that gestational flood exposure is associated with increased pregnancy loss with an odds ratio of 1.08 (95% confidence interval: 1.04 - 1.11). This risk is pronounced for women outside the peak reproductive age range (<21 or >35) or during the mid and late-stage of pregnancy. The risk escalated for women dependent on surface water, with lower income or education levels. We estimated that, over the 2010s, gestational flood events might be responsible for approximately 107,888 (CIs: 53,944 - 148,345) excess pregnancy losses annually across 33 developing countries. Notably, there is a consistent upward trend in annual excess pregnancy losses from 2010 to 2020, and was more prominent over Central America, the Caribbean, South America, and South Asia. Our findings underscore the disparities in maternal and child health aggravated by flood events in an evolving climate.

Association of Ambient Temperature With the Prevalence of Intimate Partner Violence Among Partnered Women in Low- and Middle-Income South Asian Countries.

Importance: Intimate partner violence (IPV), including physical, sexual, and emotional violence, constitutes a critical public health problem, particularly in low- and middle-income countries. While climate change could escalate violent events, data quantifying its possible association with IPV are scant. Objective: To evaluate the association of ambient temperature with the prevalence of IPV among partnered women in low- and middle-income countries in South Asia, and to estimate the association of future climate warming with IPV. Design, Setting, and Participants: This cross-sectional study used data from the Demographic and Health Survey and included 194 871 ever-partnered women aged 15 to 49 years from 3 South Asian countries (India, Nepal, and Pakistan). The study applied the mixed-effect multivariable logistic regression model to investigate the association of ambient temperature with IPV prevalence. The study further modeled the change in IPV prevalence under various future climate change scenarios. The data included in the analyses were collected from October 1, 2010, to April 30, 2018, and the current analyses were performed from January 2, 2022, to July 11, 2022. Exposure: Annual ambient temperature exposure for each woman, estimated based on an atmospheric reanalysis model of the global climate. Main Outcomes and Measures: The prevalence of IPV and its types (physical, sexual, and emotional violence) were assessed based on self-reported questionnaires from October 1, 2010, to April 30, 2018, and the changes in the prevalence with climate changes were estimated through the 2090s. Results: The study included 194 871 ever-partnered women aged 15 to 49 years (mean [SD] age, 35.4 [7.6] years; overall IPV prevalence, 27.0%) from 3 South Asian countries. The prevalence of physical violence was highest (23.0%), followed by emotional (12.5%), and sexual violence (9.5%). The annual temperature ranges were mostly between 20 °C and 30 °C. A significant association was found between high ambient temperature and the prevalence of IPV against women, with each 1 °C increase in the annual mean temperature associated with a mean increase in IPV prevalence of 4.49% (95% CI, 4.20%-4.78%). According to the study's projections under the unlimited emissions scenarios (SSPs [shared socioeconomic pathways], as defined by the Intergovernmental Panel on Climate Change] 5-8.5), IPV prevalence would increase by 21.0% by the end of the 21st century, while it would only moderately increase under increasingly stricter scenarios (SSP2-4.5 [9.8%] and SSP1-2.6 [5.8%]). In addition, the projected increases in the prevalence of physical (28.3%) and sexual (26.1%) violence were greater than that of emotional violence (8.9%). In the 2090s, India was estimated to experience the highest IPV prevalence increase (23.5%) among the 3 countries, compared with Nepal (14.8%) and Pakistan (5.9%). Conclusions and Relevance: This cross-sectional, multicountry study provides ample epidemiological evidence to support that high ambient temperature may be associated with the risk of IPV against women. These findings highlight the vulnerabilities and inequalities of women experiencing IPV in low- and middle-income countries in the context of global climate warming.

Global warming may significantly increase childhood anemia burden in sub-Saharan Africa.

Childhood anemia constitutes a global public health problem, especially in low- and middle-income countries (LMICs). However, it remains unknown whether global warming has an impact on childhood anemia. Here, we examined the association between annual temperatures and childhood anemia prevalence in sub-Saharan Africa and then projected childhood anemia burden attributable to climate change. Each 1°C increment in annual temperature was associated with increased odds of childhood anemia (odd ratio = 1.138, 95% confidence interval: 1.134-1.142). Compared with the baseline period (1985-2014), the attributable childhood anemia cases would increase by 7,597 per 100,000 person-years under a high-emission scenario in the 2090s, which would be almost 2-fold and over 3-fold more than those projected in moderate- and low-emission scenarios. Our results reveal the vulnerabilities and inequalities of children for the excess burden of anemia due to climate warming and highlight the importance of climate mitigation and adaptation strategies in LMICs.

Maternal exposure to fine particulate matter and preterm birth and low birth weight in Africa.

BACKGROUND: Fine particulate matter (PM2.5) exposure has been reported to adversely affect birth outcomes, but the evidence is limited, particularly in low- and middle-income countries (LMICs). We assessed the associations between maternal PM2.5 exposure and low birth weight (LBW) and preterm birth (PTB) in Africa. METHODS: We used standard Demographic and Health Surveys (DHS) data (2005-2015) from 15 countries in Africa to conduct a cross-sectional study. The study population was composed of 131,594 births with detailed information on maternal and household variables. LBW was defined as a birth weight of < 2500 g after 37 weeks, and PTB was defined as live birth occurring before 37 weeks of gestation. Average exposure to PM2.5 during pregnancy was estimated using satellite-based models. Multivariable logistic regression models were constructed, and analyses of data by region (Western, Eastern, Central, and Southern Africa) and data stratified by potential effect modifiers were conducted. RESULTS: A total of 13,214 (10%) LBW and 4,377 (3.3%) PTB cases were identified. An interquartile range (IQR) (33.9 µg/m3) increase in PM2.5 during pregnancy was associated with increased odds of LBW and PTB, with odds ratios (ORs) of 1.28 (95% CI: 1.23, 1.34) and 1.08 (95% CI: 1.01, 1.16), respectively. Region-specific analyses revealed significant associations between PM2.5 and LBW in all regions, and significant associations between PM2.5 and PTB in Western and Southern Africa. Subgroup analyses revealed that the association between PM2.5 and LBW was present in all subgroups, and stronger associations were observed in female infants, while the association between PM2.5 and PTB was larger in subgroups of older individuals living in urban areas. CONCLUSION: This multicountry study in Africa demonstrated significant associations between maternal exposure to PM2.5 and higher odds of LBW and PTB. Our findings may facilitate air quality control strategies that address adverse birth outcomes in LMICs.

Fine particulate matter constituents and infant mortality in Africa: A multicountry study.

BACKGROUND: Few studies have investigated the association between exposure to fine particulate matter (PM2.5) and infant mortality in developing countries, especially for the health effects of specific PM2.5 constituents. OBJECTIVE: We aimed to examine the association of long-term exposure to specific PM2.5 constituents with infant mortality in 15 African countries from 2005 to 2015. METHODS: Based on the Demographic and Health Surveys (DHS) dataset, we included birth history records from 15 countries in Africa and conducted a multicountry cross-sectional study to examine the associations between specific PM2.5 constituents and infant mortality. We estimated annual residential exposure using satellite-derived PM2.5 for mass and a chemical transport model (GEOS-Chem) for its six constituents, including organic matter (OM), black carbon (BC), sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and soil dust (DUST). Multivariable logistic regression analysis was employed by fitting single-constituent models, the constituent-PM2.5 models, and the constituent-residual models. We also conducted stratified analyses by potential effect modifiers and examined the specific associations for each country. RESULTS: We found positive and significant associations between PM2.5 total mass and most of its constituents with infant mortality. In the single-constituent model, for an IQR increase in pollutant concentrations, the odds ratio (OR) of infant mortality was 1.03 (95 %CI; 1.01, 1.06) for PM2.5 total mass, and was 1.04 (95 %CI: 1.02, 1.06), 1.04 (95 %CI: 1.02, 1.05), 1.02 (95 %CI: 1.00, 1.03), 1.04 (1.01, 1.06) for BC, OM, SO42-, and DUST, respectively. The associations of BC, OM, and SO42- remained significant in the other two models. We observed larger estimates in subgroups with older maternal age, living in urban areas, using unclean cooking energy, and with access to piped water. The associations varied among countries, and by different constituents. CONCLUSIONS: The carbonaceous fractions and sulfate play a major important role among PM2.5 constituents on infant mortality. Our findings have certain policy implications for implementing effective measures for targeted reduction in specific sources (fossil fuel combustion and biomass burning) of PM2.5 constituents against the risk of infant mortality.

Fine particulate matter constituents and sub-clinical outcomes of cardiovascular diseases: A multi-center study in China.

BACKGROUND: Limited evidence is available on the associations of long-term exposure to various fine particulate matter (PM2.5) constituents with sub-clinical outcomes of cardiovascular disease (CVD) in China. OBJECTIVES: We aimed to explore the associations of PM2.5 and its constituents with blood pressure (BP), fasting glucose, and cardiac electrophysiological (ECG) properties based on a national survey of 5852 Chinese adults, who participated in the Sub-Clinical Outcome of Polluted Air study, from July 2017 to March 2019. METHODS: Annual residential exposure to PM2.5 and its constituents of each subject was predicted by a satellite-based mode. We assessed the associations between five main constituents [organic matter (OM), black carbon (BC), sulfate (SO42-), nitrate (NO3-), ammonium (NH4+)] of PM2.5 and systolic BP (SBP), diastolic BP (DBP), fasting glucose, and ECG measurements (PR, QRS, QT, and QTc interval) using multivariable linear regression models. RESULTS: Long-term PM2.5 exposure was significantly associated with increased levels of fasting glucose, DBP, and ECG measurements. An IQR increase in OM (8.2 µg/m3) showed considerably stronger associations with an elevated fasting glucose of 0.39 mmol/L (95%CI confidence interval: 0.28, 0.49) compared with other PM2.5 constituents. Meanwhile, an IQR increase in NO3-, NH4+ and OM had stronger associations with DBP and ECG parameters compared with BC and SO42-. CONCLUSIONS: This nationwide multi-center study in China indicated that some constituents (i.e., OM, NO3-, and NH4+) might be mainly responsible for the association of PM2.5 with sub-clinical outcomes of CVD including BP, fasting glucose, and ECG measurements.

Necessity of personal sampling for exposure assessment on specific constituents of PM2.5: Results of a panel study in Shanghai, China.

Many epidemiological studies have evaluated the health risks of ambient fine particulate matter (PM2.5). However, few studies have investigated the potential exposure misclassification caused by using ambient PM2.5 concentrations as proxy for individual exposure to PM2.5 in regions with high-level of air pollution. This study aimed to compare the differences between personal and ambient PM2.5 constituent concentrations, and to predict the personal exposure of sixteen PM2.5 constituents. We collected 141 72-h personal exposure filter samples from a panel of 36 healthy non-smoking college students in Shanghai, China. We then used the liner mixed effects models to predict personal constituent-specific exposure using ambient observations and several possible influencing factors including time-activity patterns, temporal variables, and meteorological conditions. The final model of each component was further evaluated by determination coefficient (R2) and root mean square error (RMSE) from leave-one-out-cross-validation (LOOCV). We observed ambient concentrations were higher than personal concentrations for all PM2.5 components except for Mn, Fe, Ca, and V. Especially, ambient NH4+, As, and NO3- concentrations were 3.65, 5.65 and 7.33-fold higher than their corresponding personal concentrations, respectively. The ambient level was the strongest predictor of their corresponding personal PM2.5 components with the highest marginal R2 (RM2: 0.081 ~ 0.901), meteorological conditions (RM2: 0.000 ~ 0.357), time-activity pattern (RM2: 0.000 ~ 0.083) and temporal indicators (RM2: 0.031 ~ 0.562) were also important predictors. Our final models predicted at least 50% of the variance of all personal PM2.5 constituents and even over 90% for K, Pb, and SO42-. LOOCV analysis showed that R2 and RMSE ranged from 0.251 to 0.907 and 0.000 to 0.092 µg/m3, respectively. Our results showed that ambient concentration of most PM2.5 constituents along with time-activity patterns, temporal variables, and meteorological conditions, could adequately predict personal exposure concentration. Prediction models of individual PM2.5 constituent may help to improve the accuracy of exposure measurement in future epidemiological studies.