Do dietary practices and household environmental quality mediate socio-economic inequalities in child undernutrition risk in West Africa?

OBJECTIVE: We investigated the relationship between socio-economic status and child undernutrition in West Africa (WA), and further examined the mediating role of dietary practices (measured as minimum dietary diversity (MDD), minimum meal frequency (MMF) and minimum acceptable diet (MAD)) and household environmental quality (HEQ) in the observed relationship. DESIGN: Thirteen countries were included in the study. We leveraged the most recent Demographic and Health Surveys datasets ranging from 2010 to 2019. Poisson regression model with robust standard errors was used to estimate prevalence ratios and their corresponding 95 % CI. Structural equation modelling was used to conduct the mediation analysis. SETTING: West Africa. PARTICIPANTS: 132 448 under-five children born within 5 years preceding the survey were included. RESULTS: Overall, 32·5 %, 8·2 %, 20·1 % and 71·7 % of WA children were stunted, wasted, underweight and anaemic, respectively. Prevalence of undernutrition decreased with increasing maternal education and household wealth (Trend P-values < 0·001). Secondary or higher maternal education and residence in rich households were associated with statistically significant decrease in the prevalence of stunting, wasting, underweight and anaemia among children in WA. MAD was found to mediate the association of low maternal education and poor household wealth with childhood stunting and underweight by 35·9 % to 44·5 %. MDD, MMF and HEQ did not mediate the observed relationship. CONCLUSIONS: The study findings enables an evaluation and improvement of existing intervention strategies through a socio-economic lens to help address the high burden of child undernutrition in WA and other developing regions.

Association between PM2.5 and respiratory hospitalization in Rio Branco, Brazil: Demonstrating the potential of low-cost air quality sensor for epidemiologic research.

BACKGROUND: There is currently a scarcity of air pollution epidemiologic data from low- and middle-income countries (LMICs) due to the lack of air quality monitoring in these countries. Additionally, there is limited capacity to assess the health effects of wildfire smoke events in wildfire-prone regions like Brazil's Amazon Basin. Emerging low-cost air quality sensors may have the potential to address these gaps. OBJECTIVES: We investigated the potential of PurpleAir PM2.5 sensors for conducting air pollution epidemiologic research leveraging the United States Environmental Protection Agency's United States-wide correction formula for ambient PM2.5. METHODS: We obtained raw (uncorrected) PM2.5 concentration and humidity data from a PurpleAir sensor in Rio Branco, Brazil, between 2018 and 2019. Humidity measurements from the PurpleAir sensor were used to correct the PM2.5 concentrations. We established the relationship between ambient PM2.5 (corrected and uncorrected) and daily all-cause respiratory hospitalization in Rio Branco, Brazil, using generalized additive models (GAM) and distributed lag non-linear models (DLNM). We used linear regression to assess the relationship between daily PM2.5 concentrations and wildfire reports in Rio Branco during the wildfire seasons of 2018 and 2019. RESULTS: We observed increases in daily respiratory hospitalizations of 5.4% (95%CI: 0.8%, 10.1%) for a 2-day lag and 5.8% (1.5%, 10.2%) for 3-day lag, per 10 µg/m3 PM2.5 (corrected values). The effect estimates were attenuated when the uncorrected PM2.5 data was used. The number of reported wildfires explained 10% of daily PM2.5 concentrations during the wildfire season. DISCUSSION: Exposure-response relationships estimated using corrected low-cost air quality sensor data were comparable with relationships estimated using a validated air quality modeling approach. This suggests that correcting low-cost PM2.5 sensor data may mitigate bias attenuation in air pollution epidemiologic studies. Low-cost sensor PM2.5 data could also predict the air quality impacts of wildfires in Brazil's Amazon Basin.

Secular trends in low birth weight and child undernutrition in West Africa: evidence from complex nationwide surveys, 1985-2019.

OBJECTIVE: We present prevalence estimates and secular trends of stunting, wasting, underweight, and anaemia among children under 5 years of age and low birth weight (LBW) over the period 1985-2019 in West Africa (WA). DESIGN: Analysis of Demographic and Health Survey (DHS) and World Bank data. DerSimonian-Laird random effect model with the Knapp-Hartung adjustment to the standard error was used to derive overall prevalence estimates. We used fixed effect ordinary least square regression models with cluster robust standard error to conduct time trends analyses. SETTING: West Africa. PARTICIPANTS: Children aged 0 to 59 months. RESULTS: Three distinct periods (1986-1990, 1993-1996 and 1997-2000) of sharp increases in prevalence of all outcomes was observed. After the year 2000, prevalence of all outcomes except LBW started to decline with some fluctuations. LBW prevalence showed a steady increase after 2000. We observed a decline in prevalence of stunting (ß = -0·20 %; 95 % CI -0·43 %, 0·03 %), log-wasting (ß = -0·02 %; 95 % CI -0·02 %, -0·01 %), log-underweight (ß = -0·02 %; 95 % CI -0·03 %, -0·01 %) anaemia (ß = -0·44; 95 % CI -0·55 %, -0·34 %), and an increase in LBW (ß = 0·06 %; 95 % CI -0·10 %, 0·22 %) in WA over the period. Pooled prevalence of stunting, wasting, underweight, anaemia and LBW in WA for the period 1985-2019 was 26·1 %, 16·4 %, 22·7 %, 76·2 % and 11·3 %, respectively. CONCLUSIONS: Child undernutrition prevalence varied greatly between countries and the year cohorts. We observed marginal reductions in prevalence of all outcomes except anaemia where the reductions were quite striking and LBW where an increase was noted. There is the need for more rigorous and sustained targeted interventions in WA.

A land use regression model using machine learning and locally developed low cost particulate matter sensors in Uganda.

The application of land use regression (LUR) modeling for estimating air pollution exposure has been used only rarely in sub-Saharan Africa (SSA). This is generally due to a lack of air quality monitoring networks in the region. Low cost air quality sensors developed locally in sub-Saharan Africa presents a sustainable operating mechanism that may help generate the air monitoring data needed for exposure estimation of air pollution with LUR models. The primary objective of our study is to investigate whether a network of locally developed low-cost air quality sensors can be used in LUR modeling for accurately predicting monthly ambient fine particulate matter (PM2.5) air pollution in urban areas of central and eastern Uganda. Secondarily, we aimed to explore whether the application of machine learning (ML) can improve LUR predictions compared to ordinary least squares (OLS) regression. We used data for the entire year of 2020 from a network of 23 PM2.5 low-cost sensors located in urban municipalities of eastern and central Uganda. Between January 1, 2020 and December 31, 2020, these sensors collected highly time-resolved measurement data of PM2.5 air concentrations. We used monthly-averaged PM2.5 concentration data for LUR prediction modeling of monthly PM2.5 concentrations. We used eight different ML base-learner algorithms as well as ensemble modeling. We applied 5-fold cross validation (80% training/20% test random splits) to evaluate the models with resampling and Root mean squared error (RMSE). The relative explanatory power and accuracy of the ML algorithms were evaluated by comparing coefficient of determination (R2) and RMSE, using OLS as the reference approach. The overall average PM2.5 concentration during the study period was 52.22 µg/m3 (IQR: 38.11, 62.84 µg/m3)-well above World Health Organization PM2.5 ambient air guidelines. From the base-learner and ensemble models, RMSE and R2 values ranged between 7.65 µg/m3 - 16.85 µg/m3 and 0.24-0.84, respectively. Extreme gradient boosting (xgbTree) performed best out of the base learner algorithms (R2 = 0.84; RMSE = 7.65 µg/m3). Model performance from ensemble modeling with Lasso and Elastic-Net Regularized Generalized Linear Models (glmnet) did not outperform xgbTree, but prediction performance was comparable to that of xgbTree. The most important temporal and spatial predictors of monthly PM2.5 levels were monthly precipitation, percent of the population using solid fuels for cooking, distance to Lake Victoria, and greenspace (NDVI) within a 500-m buffer of air monitors. In conclusion, data from locally developed low-cost PM sensors provide evidence that they can be used for spatio-temporal prediction modeling of air pollution exposures in Uganda. Moreover, the non-parametric ML and ensemble approaches to LUR modeling clearly outperformed OLS regression algorithm for the prediction of monthly PM2.5 concentrations. Deploying low-cost air quality sensors in concert with implementation of data quality control measures, can help address the critical need for expanding and improving air quality monitoring in resource-constrained settings of sub-Saharan Africa. These low-cost sensors, in conjunction with non-parametric ML algorithms, may provide a rapid path forward for PM2.5 exposure assessment and to spur air pollution epidemiology research in the region.

Short-term prenatal exposure to ambient air pollution and risk of preterm birth - A population-based cohort study in Finland.

BACKGROUND: Previous studies have provided evidence that prenatal exposure to low-level air pollution increases the risk of preterm birth (PTB), but the findings of the effects of short-term exposure have been inconclusive. Moreover, there is little knowledge on potential synergistic effects of different combinations of air pollutants. OBJECTIVES: To assess independent and joint effects of prenatal exposure to air pollutants during the week prior to the delivery on the risk of PTB. METHODS: The study population included 2568 members of the Espoo Cohort Study, living in the City of Espoo, Finland, born between 1984 and 1990. We assessed individual-level prenatal exposure to ambient air pollutants of interest based on maternal residential addresses, while taking into account their residential mobility. We used both regional-to-city-scale dispersion modelling and land-use regression-based method to estimates the pollutant concentrations. We contrasted the risk of PTB in the highest quartile (Q4) of exposure to the lower exposure quartiles (Q1-Q3) during the specific periods of pregnancy. We applied Poisson regression analysis to estimate the adjusted risk ratios (RRs) with their 95% confidence intervals (CI), adjusting for season of birth, maternal age, sex of the baby, family's socioeconomic status, maternal smoking, and exposure to environmental tobacco smoke during pregnancy, single parenthood, and exposure to other air pollutants (this in multi-pollutant models). RESULTS: The risk of PTB was related to exposures to PM2.5, PM10 and NO2 during the week prior to the delivery with adjusted RRs of 1.67 (95%CI: 1.14, 2.46), 1.60 (95% CI: 1.09, 2.34) and 1.65 (95% CI: 1.14, 2.37), from three-pollutant models respectively. There were no significant joint effects for these different air pollutants (during the week prior to the delivery). CONCLUSION: Our results provide evidence that exposure to fairly low-level air pollution may trigger PTB, but synergistic effects of different pollutants are not likely.

Synergistic effects of prenatal exposure to fine particulate matter (PM2.5) and ozone (O3) on the risk of preterm birth: A population-based cohort study.

BACKGROUND: There is some evidence that prenatal exposure to low-level air pollution increases the risk of preterm birth (PTB), but little is known about synergistic effects of different pollutants. OBJECTIVES: We assessed the independent and joint effects of prenatal exposure to air pollution during the entire duration of pregnancy. METHODS: The study population consisted of the 2568 members of the Espoo Cohort Study, born between 1984 and 1990, and living in the City of Espoo, Finland. We assessed individual-level prenatal exposure to ambient air pollutants of interest at all the residential addresses from conception to birth. The pollutant concentrations were estimated both by using regional-to-city-scale dispersion modelling and land-use regression-based method. We applied Poisson regression analysis to estimate the adjusted risk ratios (RRs) with their 95% confidence intervals (CI) by comparing the risk of PTB among babies with the highest quartile (Q4) of exposure during the entire duration of pregnancy with those with the lower exposure quartiles (Q1-Q3). We adjusted for season of birth, maternal age, sex of the baby, family's socioeconomic status, maternal smoking during pregnancy, maternal exposure to environmental tobacco smoke during pregnancy, single parenthood, and exposure to other air pollutants (only in multi-pollutant models) in the analysis. RESULTS: In a multi-pollutant model estimating the effects of exposure during entire pregnancy, the adjusted RR was 1.37 (95% CI: 0.85, 2.23) for PM2.5 and 1.64 (95% CI: 1.15, 2.35) for O3. The joint effect of PM2.5 and O3 was substantially higher, an adjusted RR of 3.63 (95% CI: 2.16, 6.10), than what would have been expected from their independent effects (0.99 for PM2.5 and 1.34 for O3). The relative risk due to interaction (RERI) was 2.30 (95% CI: 0.95, 4.57). DISCUSSION: Our results strengthen the evidence that exposure to fairly low-level air pollution during pregnancy increases the risk of PTB. We provide novel observations indicating that individual air pollutants such as PM2.5 and O3 may act synergistically potentiating each other's adverse effects.

Association of Sunlight Exposure and Consumption of Vitamin D-Rich Foods During Pregnancy with Adverse Birth Outcomes in an African Population.

BACKGROUND: Our objective was to assess whether dietary vitamin D (vitD) intake and sunlight exposure during pregnancy is associated with birth outcomes in a healthy Ghanaian population. METHODS: A population-based cross-sectional study that included 703 mother-infant pairs accessing postnatal services at the five main health facilities in Cape Coast, Ghana was conducted in 2016. Information on sunlight exposure practices and consumption of vitD-rich foods during pregnancy was collected. RESULTS: A 1 µg increase in vitD intake resulted in a statistically significant 0.00505 weeks increase in gestational age (95% confidence interval [CI]: 0.00005, 0.01004). Mothers classified in the first quartile of vitD intake had 37% (prevalence ratio = 1.37, 95% CI: 1.10, 1.69) increased risk of preterm birth (PTB) compared to their counterparts classified in the fourth quartile. Decreased vitD intake was also associated with low-to-moderate Apgar score. CONCLUSION: Nutrition education of mothers on the importance of screening for vitD deficiency during early months of pregnancy is recommended.

Dietary Polycyclic Aromatic Hydrocarbon (PAH) Consumption and Risk of Adverse Birth Outcomes: A Systematic Review and Meta-Analysis.

BACKGROUND: There is suggestive epidemiological evidence that maternal dietary polycyclic aromatic hydrocarbons (PAH) may increase the risk of adverse birth outcomes. We sought to summarize the available evidence on the effect of dietary PAH exposure on birth outcomes. METHODS: PubMed and Scopus databases were systematically searched from inception up to November 2022. Studies were included if they were original articles, were conducted in a human population, assessed dietary PAH consumption, and investigated the relationship between dietary PAH consumption and any adverse birth outcomes. Risk of bias in the included studies was assessed qualitatively and quantitatively. A random effects model was used to compute summary effect estimates in the meta-analysis. RESULTS: Six observational studies (five prospective cohort studies, and one prevalence case-control study) were included. The included studies assessed dietary PAH exposure using dietary questionnaires. Information on the outcomes of interest was obtained from medical records. Three of the included studies were rated as good quality with the remaining three studies rated as fair quality. One study was considered as having low risk of bias for selection, information and confounding bias. Dietary PAH consumption was associated with 5.65g [95% confidence interval (CI): -16.36, 5.06] and 0.04cm (95% CI: -0.08, 0.01) reductions in birth weight and birth length, respectively, and an increase in head circumference [effect size (ES)=0.001; 95% CI: -0.003, 0.005]. The CI of all the summary effect estimates, however, included the null value. In the sensitivity analysis that included only studies that assessed dietary PAH exposure as the primary exposure of interest, dietary PAH consumption was associated with much higher reductions in birth weight (ES=-14.61; 95% CI: -21.07, -8.15) and birth length (ES=-0.06; 95% CI: -0.1, -0.03). High statistical heterogeneity was observed in the birth weight and birth length analysis and in the head circumference sensitivity analysis. DISCUSSION: The body of epidemiological evidence suggests that maternal dietary PAH exposure is associated with reduced fetal growth, measured as birth weight and length. There was considerable heterogeneity in the measurement of PAH exposure among the included studies. Also, nonstandardized and validated dietary questionnaires were employed by a majority of the included studies with potential exposure misclassification. These issues are likely to impact the summary effect estimates computed and underscores the need for high-quality epidemiological studies with improved exposure assessment and adequate confounding control to strengthen the evidence base. https://doi.org/10.1289/EHP12922.

Fruits and vegetables intake improves birth outcomes of women with gestational diabetes mellitus and hypertensive disorders of pregnancy.

BACKGROUND: Disorders of pregnancy such as hypertensive disorders of pregnancy (HDP) and gestational diabetes mellitus (GDM) have been associated with adverse birth outcomes. However, the ameliorating role of maternal nutrition in the relationship between disorders of pregnancy and adverse birth outcomes has received very little attention. We investigated the relationship between HDP and GDM, and adverse birth outcomes in a Ghanaian population and evaluated the effect modifying role of fruits and vegetables consumption in the relationship. METHODS: We conducted a cross-sectional study among 799 mothers who had recently delivered singletons in the Cape Coast Metropolis, Ghana. Information on HDP, GDM and birth outcomes were retrieved from the maternal health book of the mothers. A food frequency questionnaire was used to assess fruits and vegetables intake during pregnancy. Modified Poisson regression was used to investigate the association between pregnancy disorders, and preterm birth (PTB) and low birth weight (LBW). Stratified analysis was used to assess the effect modifying role of fruits and vegetables consumption in the relationship. RESULTS: The proportion of mothers with HDP and GDM was 11.3% and 7.5%, respectively. The proportion of the mothers with both conditions was 0.9%. The prevalence of PTB and LBW in the population was 27.9 and 7.3%, respectively. These disorders of pregnancy were associated with increased risk of PTB (Adjusted Prevalence Ration [APR] = 3.02; 95% CI: 2.42, 3.77) and LBW (APR = 5.32; 95% CI: 3.19, 8.88). In the stratified analysis, risk of PTB was higher among mothers classified in tertile I compared to mothers classified in tertiles II and III. For LBW, the risk increased with increasing fruits and vegetables consumption. The interaction p values were 0.0043 and 0.1604 for PTB and LBW, respectively. CONCLUSIONS: We found mothers who were diagnosed with GDM and HDP to have increased risk of delivering a PTB and LBW baby. We also found fruits and vegetables consumption to modify the observed relationship. Mothers diagnosed with GDM and HDP should be advised during antenatal care visits to increase intake of fruits and vegetable consumption to help safeguard their health and that of the developing foetus.

Socio-demographic and neighbourhood factors influencing urban green space use and development at home: A population-based survey in Accra, Ghana.

In Sub-Saharan Africa and other developing regions, there has been very little systematic attempt to document the uses and perceived health benefits of urban green spaces in cities and the factors influencing usage. We therefore sought to establish the availability, accessibility and use of urban green spaces, and the perceived health benefits in an African population. We also ascertained the factors influencing use and development of green spaces at home. A population-based survey was conducted in Accra, the capital city of Ghana, spanning 11 Municipal and 3 Sub-Metropolitan areas. Multivariable binary logistic regression adjusting for potential confounders was used to establish the association between green space use and development at home, and socio-demographic, neighbourhood and health factors. Odds ratios and their corresponding 95% confidence intervals were estimated from the models. Several socio-demographic (gender, age, marital status, occupation, ethnicity, religion) and district-level (population density, income level, neighbourhood greenness) factors were associated with use of green spaces and development of green spaces at home in Accra. Residents who were worried about depletion of green spaces in their community were more likely to develop green spaces at home. In neighbourhoods with moderate and high level of greenness, residents were less likely to develop green spaces at home. Five-percent and 47% of green space users in Accra reported witnessing an improvement in their physical and mental health, respectively, from use of green spaces. The study findings can inform policy action for promoting use and development of green spaces in African cities and for mitigating depletion and degradation of the limited urban greenery.

Limited Air Pollution Research on the African Continent: Time to Fill the Gap.

Air pollution is a major threat to human health and well-being, and improving air quality is necessary to achieve the sustainable development goals [...].

Harmonization of Epidemiologic Research Methods to Address the Environmental and Social Determinants of Urban Slum Health Challenges in Sub-Saharan Africa.

Sub-Saharan Africa (SSA) has a significant proportion of populations living in urban slum conditions, where exposure to multiple environmental stressors and social inequalities is ubiquitous. This commentary synthesizes commonalities in recent environmental health studies from urban cities in East and West Africa, presented during a symposium sponsored by the Africa Chapter of the International Society of Environmental Epidemiology (ISEE) in August 2020. A key takeaway from this symposium is the need for harmonization of epidemiologic and exposure data collection in three domains tailored to the SSA context: (1) improvements in socioeconomic status (SES) measurement through harmonization in the conceptualization and operationalization of SES indicators; (2) improvements in air pollution exposure assessment in resource-constrained contexts by better integration, validation, and harmonization of exposure data of air pollution and mitigating factors; and (3) harmonization in the assessment of health outcomes and biomonitoring of contaminants. Focusing on these three domains would galvanize environmental epidemiologists in SSA around shared data collection instruments and shared data platforms and facilitate the pooling of data across the continent. Fostering this collaborative research will enable researchers and decision-makers to glean new insights and develop robust environmental health interventions and policies for SSA urban slums and for improved population health.

Particulate matter pollution at traffic hotspots of Accra, Ghana: levels, exposure experiences of street traders, and associated respiratory and cardiovascular symptoms.

BACKGROUND: There are limited studies on the health effects of street trading in spite of common knowledge that individuals engaged in the trade are exposed to high levels of traffic-related air pollution per their mode of operation, and also the fact that the venture is a dominant occupation in cities of Sub-Saharan Africa (SSA) and other developing regions. OBJECTIVE: We characterized particulate matter (PM) pollution levels at traffic hotspots of Accra, Ghana during the dry and wet seasons, and assessed exposure experiences of street traders. METHODS: A cross-sectional study was conducted among 236 street traders operating along six selected traffic routes of Accra and a comparison group of 186 office workers. PurpleAir PA-II monitors were used to measure PM levels at the selected traffic routes. We estimated annual PM2.5 exposure of street traders using assigned seasonal PM2.5 levels, and information collected in a structured questionnaire on their activity patterns. Outcomes investigated were self-reported respiratory and cardiovascular symptoms. RESULTS: PM levels at Accra traffic hotspots were high in both seasons. 1 ug/m3 increase in PM2.5 exposure increased respiratory, cardiovascular, and overall symptoms by a factor of 0.00027 (95% CI: 0.00012, 0.00041), 0.00022 (95% CI: 0.00007, 0.00036), and 0.00048 (95% CI: 0.00023, 0.00073), respectively. Compared to office workers, high PM2.5 exposure among street traders was associated with increased odds of coughing, catarrh (postnasal drip), sneezing, rapid heart beating, irregular heartbeat, sharp chest pains, fainting spells, headaches, and dizziness. Low and medium PM2.5 exposure was associated with increased odds of dermatitis, rapid heart beating, and irregular heartbeat, and sharp chest pains, respectively. CONCLUSIONS: We found consistent evidence that PM2.5 exposure among street traders increases the occurrence of respiratory and cardiovascular symptoms. We also provide indicative measurements of PM levels at traffic hotspots of a rapidly growing SSA city with heavy vehicular traffic and yet, limited air quality monitoring capacity.

Cadmium exposure and risk of adverse pregnancy and birth outcomes: a systematic review and dose-response meta-analysis of cohort and cohort-based case-control studies.

BACKGROUND: There are several inconsistencies in the epidemiological literature on the strength of the association between cadmium exposure and adverse pregnancy and birth outcomes, and the threshold dose of adverse effect. OBJECTIVES: We therefore conducted a systematic review and dose-response meta-analysis to evaluate the available evidence to influence clinical decision making and better tailor public health interventions. METHODS: PubMed and Scopus databases were searched up to January, 2019. Eighteen prospective studies satisfied the inclusion criteria. Random effects model was used to compute summary-effect estimates. RESULTS: Cadmium exposure resulted in 42.11 g (95% confidence interval [CI]: -69.03, -15.18) reduction in birth weight, and 0.105 cm (95% CI: -0.181, -0.029) reduction in head circumference per 1 µg/l increment in blood/urine cadmium levels. Cadmium exposure also resulted in 21% (RR = 1.21; 95% CI: 1.02, 1.43), 32% (RR = 1.32; 95% CI: 1.05, 1.67) and 10% (RR = 1.10; 95% CI: 0.96, 1.27) increased risk of low birth weight (LBW), preterm birth (PTB), and small-for-gestational age (SGA), respectively. Risk for all outcomes decreased with decreasing exposure. In fixed effects dose-response meta-regression analyses, we found no evidence of association of cadmium exposure with LBW and SGA. For PTB, a 1 µg/l increment in cadmium exposure corresponded to 0.5% (OR = 1.005, 95% CI: 1.003, 1.007) increase in PTB risk. CONCLUSIONS: Cadmium exposure was associated with risk of adverse birth outcomes. Regarding PTB, the formal dose-response meta-analyses suggests a causal association.

Improving Child Survival in Sub-Saharan Africa: Key Environmental and Nutritional Interventions.

Many countries in Sub-Saharan Africa (SSA), did not achieve the Millennium Development Goal 4 target of reducing under-five mortality by two-thirds between 1990 and 2015. A large proportion of under-five deaths in SSA and other developing regions have been attributed to undernutrition and poor household environmental conditions. Failure to address nutritional deficit and household environmental pollution in SSA will therefore likely result in many countries not meeting the Sustainable Development Goal (SDG) 3.2 target which aims to reduce under-five mortality to less than 25 deaths per 1000 livebirths by 2030. This paper pinpoints the nutritional and environmental threats to child health in SSA, and identify interventions that will work best to improve child survival in countries. It is important to broaden the spectrum of interventions for improving child survival beyond health systems strengthening to enable countries meet the SDG 3.2 target. The following interventions are thus proposed: strengthening child welfare clinics through digital technologies; investment in school feeding programmes; addressing household air pollution; and improving water, sanitation and hygiene (WASH) services in basic schools. There are certainly barriers to effective implementation of the proposed interventions in countries but are surmountable with strong political will and involvement of the private sector.

Association of biomass fuel use with reduced body weight of adult Ghanaian women.

The association of biomass fuel use with body weight has never been investigated. We therefore examined the effect of biomass fuel use on body weight of adult Ghanaian women. Data from the 2014 Ghana Demographic and Health Survey, a nationally representative population-based survey was analysed for this study. A total of 4751 women who had anthropometric (height and weight) data qualified for inclusion in this study. In linear regression modelling, charcoal use resulted in 3.08 kg (95% CI: 2.04, 4.12) and 0.81 kg/m2 (95%CI: 0.29, 1.33) reduction in weight and body mass index (BMI), respectively, compared to clean fuel (electricity, liquefied petroleum gas and natural gas) use. Use of wood resulted in much higher reduction in weight and BMI. In modified Poisson regression, charcoal users had 19% (Adjusted Prevalence Ratio [aPR] = 0.81; 95%CI: 0.71, 0.92) and 29% (aPR = 0.71; 95%CI: 0.61, 0.83) decreased risk of overweight and obesity, respectively, compared to clean fuel users. Wood users had much higher decreased risk of overweight and obesity. In conclusion, biomass fuel use was associated with reduced body weight and BMI of Ghanaian women and is the first report on the relationship. However, it is important that our findings are confirmed and the biological mechanisms elucidated through rigorous study designs.

Proliferation of low-cost sensors. What prospects for air pollution epidemiologic research in Sub-Saharan Africa?

Addressing the worsening urban air quality situation in Sub-Saharan Africa (SSA) is proving increasingly difficult owing to paucity of data on air pollution levels and also, lack of local evidence on the magnitude of the associated health effects. There is therefore the urgent need to expand air quality monitoring (AQM) networks in SSA to enable the conduct of high quality epidemiologic studies to help inform policies aimed at addressing air pollution and the associated health effects. In this commentary, I explore the prospects that the proliferation of low-cost sensors in recent times holds for air pollution epidemiologic research in SSA. This commentary is timely because most SSA governments do not see investments in air pollution control that requires assembling a network of sophisticated and prohibitively expensive instrumentation for AQM as necessary for improving and protecting public health. I conclude that, in a region that is bereft of air pollution data, the growing influx of low-cost sensors represents an excellent opportunity for bridging the data gap to inform air pollution control policies and regulations for public health protection. However, it is essential that only the most promising sensor technologies that performs creditably well in the harsh environmental conditions of the region are promoted.