Burden of headaches, eye irritation and respiratory symptoms among females stacking LPG with polluting cooking fuels: Modelling from peri-urban Cameroon, Ghana & Kenya.

Introduction: Liquefied petroleum gas (LPG) is a clean cooking fuel that emits less household air pollution (HAP) than polluting cooking fuels (e.g. charcoal, wood). While switching from polluting fuels to LPG can reduce HAP and improve health, the impact of 'stacking' (concurrent use of polluting fuels and LPG) on adverse health symptoms (e.g. headaches, eye irritation, cough) among female cooks is uncertain. Methods: Survey data from the CLEAN-Air(Africa) study was collected on cooking patterns and health symptoms over the last 12 months (cough, wheezing, chest tightness, shortness of breath, eye irritation, headaches) from approximately 400 female primary cooks in each of three peri­urban communities in sub-Saharan Africa: Mbalmayo, Cameroon; Obuasi, Ghana; and Eldoret, Kenya. Random effects Poisson regression, adjusted for socioeconomic and health-related covariates, assessed the relationship between primary and secondary cooking fuel type and self-reported health symptoms. Results: Among 1,147 participants, 10 % (n = 118) exclusively cooked with LPG, 45 % (n = 509) stacked LPG and polluting fuels and 45 % (n = 520) exclusively cooked with polluting fuels. Female cooks stacking LPG and polluting fuels had significantly higher odds of shortness of breath (OR 2.16, 95 %CI:1.04-4.48) compared with those exclusively using LPG. In two communities, headache prevalence was 30 % higher among women stacking LPG with polluting fuels (Mbalmayo:82 %; Eldoret:65 %) compared with those exclusively using LPG (Mbalmayo:53 %; Eldoret:33 %). Women stacking LPG and polluting fuels (OR 2.45, 95 %CI:1.29-4.67) had significantly higher odds of eye irritation than women cooking exclusively with LPG. Second-hand smoke exposure was significantly associated with higher odds of chest tightness (OR 1.92, 95 % CI:1.19-3.11), wheezing (OR 1.76, 95 % CI:1.06-2.91) and cough (OR 1.78, 95 %CI:1.13-2.80). Conclusions: In peri­urban sub-Saharan Africa, women exclusively cooking with LPG had lower odds of several health symptoms than those stacking LPG and polluting fuels. Promoting a complete transition to LPG in these communities may likely generate short-term health benefits for primary cooks.

The association of short-term increases in ambient PM2.5 and temperature exposures with stillbirth: racial/ethnic disparities among Medicaid recipients.

Racial/ethnic disparities in the association between short-term (e.g. days, weeks) ambient fine particulate matter (PM2.5) and temperature exposures and stillbirth in the US have been understudied. A time-stratified, case-crossover design using a distributed lag non-linear model (0 to 6-day lag) estimated stillbirth odds due to short-term increases in average daily PM2.5 and temperature exposures among 118,632 Medicaid recipients from 2000-2014. Disparities by maternal race/ethnicity (Black, White, Hispanic, Asian, American Indian) and zip-code level socioeconomic status (SES) were assessed. In the temperature-adjusted model, a 10 µg/m3 increase in PM2.5 concentration was marginally associated with increased stillbirth odds at lag 1 (0.68% 95%CI:[-0.04,1.40]) and lag 2 (0.52% 95%CI:[-0.03,1.06]), but not lag 0-6 (2.80% 95%CI:[-0.81,6.45]). An association between daily PM2.5 concentrations and stillbirth odds was found among Black individuals at the cumulative lag (0-6 days: 9.26% 95%CI:[3.12,15.77]), but not among other races/ethnicities. A stronger association between PM2.5 concentrations and stillbirth odds existed among Black individuals living in zip codes with the lowest median household income (lag0-6:14.13% 95%CI:[4.64,25.79]). Short-term temperature increases were not associated with stillbirth risk among any race/ethnicity. Black Medicaid enrollees, and especially those living in lower SES areas, may be more vulnerable to stillbirth due to short-term increases in PM2.5 exposure.

Association between density of food retailers and fitness centers and gestational diabetes mellitus in Eastern Massachusetts, USA: population-based study.

Background: Few studies have investigated the relationship between the food and physical activity environment and odds of gestational diabetes mellitus (GDM). This study quantifies the association between densities of several types of food establishments and fitness centers with the odds of having GDM. Methods: The density of supermarkets, fast-food restaurants, full-service restaurants, convenience stores and fitness centers at 500, 1000 and 1500 m (m) buffers was counted at residential addresses of 68,779 pregnant individuals from Eastern Massachusetts during 2000-2016. The 'healthy food index' assessed the relative availability of healthy (supermarkets) vs unhealthy (fast-food restaurants, convenience stores) food retailers. Multivariable logistic regression quantified the cross-sectional association between exposure variables and the odds of having GDM, adjusting for individual and area-level characteristics. Effect modification by area-level socioeconomic status (SES) was assessed. Findings: In fully adjusted models, pregnant individuals living in the highest density tertile of fast-food restaurants had higher GDM odds compared to those living in the lowest density tertile (500 m: odds ratio (OR):1.17 95% CI: [1.04, 1.31]; 1000 m: 1.33 95% CI: [1.15, 1.53]); 1500 m: 1.18 95% CI: [1.01, 1.38]). Greater residential density of supermarkets was associated with lower odds of GDM (1000 m: 0.86 95% CI: [0.74, 0.99]; 1500 m: 0.86 95% CI: [0.72, 1.01]). Similarly, living in the highest fitness center density tertile was associated with decreased GDM odds (500 m:0.87 95% CI: [0.76, 0.99]; 1500 m: 0.89 95% CI: [0.79, 1.01]). There was no evidence of effect modification by SES and no association found between the healthy food index and GDM odds. Interpretation: In Eastern Massachusetts, living near a greater density of fast-food establishments was associated with higher GDM odds. Greater residential access to supermarkets and fitness centers was associated with lower the odds of having GDM. Funding: NIH.

Household concentrations and female and child exposures to air pollution in peri-urban sub-Saharan Africa: measurements from the CLEAN-Air(Africa) study.

BACKGROUND: Relatively clean cooking fuels such as liquefied petroleum gas (LPG) emit less fine particulate matter (PM2·5) and carbon monoxide (CO) than polluting fuels (eg, wood, charcoal). Yet, some clean cooking interventions have not achieved substantial exposure reductions. This study evaluates determinants of between-community variability in exposures to household air pollution (HAP) across sub-Saharan Africa. METHODS: In this measurement study, we recruited households cooking primarily with LPG or exclusively with wood or charcoal in peri-urban Cameroon, Ghana, and Kenya from previously surveyed households. In 2019-20, we conducted monitoring of 24 h PM2·5 and CO kitchen concentrations (n=256) and female cook (n=248) and child (n=124) exposures. PM2·5 measurements used gravimetric and light scattering methods. Stove use monitoring and surveys on cooking characteristics and ambient air pollution exposure (eg, walking time to main road) were also administered. FINDINGS: The mean PM2·5 kitchen concentration was five times higher among households cooking with charcoal than those using LPG in the Kenyan community (297 µg/m3, 95% CI 216-406, vs 61 µg/m3, 49-76), but only 4 µg/m3 higher in the Ghanaian community (56 µg/m3, 45-70, vs 52 µg/m3, 40-68). The mean CO kitchen concentration in charcoal-using households was double the WHO guideline (6·11 parts per million [ppm]) in the Kenyan community (15·81 ppm, 95% CI 8·71-28·72), but below the guideline in the Ghanaian setting (1·77 ppm, 1·04-2·99). In all communities, mean PM2·5 cook exposures only met the WHO interim-1 target (35 µg/m3) among LPG users staying indoors and living more than 10 min walk from a road. INTERPRETATION: Community-level variation in the relative difference in HAP exposures between LPG and polluting cooking fuel users in peri-urban sub-Saharan Africa might be attributed to differences in ambient air pollution levels. Thus, mitigation of indoor and outdoor PM2·5 sources will probably be critical for obtaining significant exposure reductions in rapidly urbanising settings of sub-Saharan Africa. FUNDING: UK National Institute for Health and Care Research.

Short-Term Increases in NO2 and O3 Concentrations during Pregnancy and Stillbirth Risk in the U.S.: A Time-Stratified Case-Crossover Study.

Associations between gaseous pollutant exposure and stillbirth have focused on exposures averaged over trimesters or gestation. We investigated the association between short-term increases in nitrogen dioxide (NO2) and ozone (O3) concentrations and stillbirth risk among a national sample of 116 788 Medicaid enrollees from 2000 to 2014. A time-stratified case-crossover design was used to estimate distributed (lag 0-lag 6) and cumulative lag effects, which were adjusted for PM2.5 concentration and temperature. Effect modification by race/ethnicity and proximity to hydraulic fracturing (fracking) wells was assessed. Short-term increases in the NO2 and O3 concentrations were not associated with stillbirth in the overall sample. Among American Indian individuals (n = 1694), a 10 ppb increase in NO2 concentrations was associated with increased stillbirth odds at lag 0 (5.66%, 95%CI: [0.57%, 11.01%], p = 0.03) and lag 1 (4.08%, 95%CI: [0.22%, 8.09%], p = 0.04) but not lag 0-6 (7.12%, 95%CI: [-9.83%, 27.27%], p = 0.43). Among participants living in zip codes within 15 km of active fracking wells (n = 9486), a 10 ppb increase in NO2 concentration was associated with increased stillbirth odds in single-day lags (2.42%, 95%CI: [0.37%, 4.52%], p = 0.02 for lag 0 and 1.83%, 95%CI: [0.25%, 3.43%], p = 0.03 for lag 1) but not the cumulative lag (lag 0-6) (4.62%, 95%CI: [-2.75%, 12.55%], p = 0.22). Odds ratios were close to the null in zip codes distant from fracking wells. Future studies should investigate the role of air pollutants emitted from fracking and potential racial disparities in the relationship between short-term increases in NO2 concentrations and stillbirth.

Deepened socioeconomic inequality in clean cooking fuel use in India from 2005-2006 to 2015-2016.

Uptake of clean cooking fuels (CCF), such as liquefied petroleum gas (LPG), in place of traditional cooking fuels such as wood, charcoal, and kerosene can improve public health by reducing household air pollution exposures. Though studies have cross-sectionally examined socioeconomic determinants of cooking fuel adoption, little is known about socioeconomic disparities in CCF use over time. Data from the third (2005-06) and fourth (2015-16) rounds of the National Family Health Survey covering 109,041 and 601,509 households, respectively, were used to examine inequities in CCF use in India. While CCF use in India increased nationally from 25% in 2005-06 to 44% in 2015-16, the adoption of CCF varied widely across states and socio-economic groups. Approximately 2% of households in the poorest wealth quintile gained access to LPG during the study period, compared with an increase of 10% or more among households in the middle or richer wealth quintiles; the LPG access gap between the low (0.2%) and middle class (19.2%) was 19% in 2005-06 and nearly doubled to 35% (2.5% vs. 37.4%, respectively) in 2015-16. At the state level, there was a four-fold difference in the uptake of CCF over the two survey periods. The use of CCF increased by less than 10% in Himachal Pradesh, Bihar, Assam, Manipur, Mizoram, and Meghalaya as compared to the increases of at least 30% in Tamil Nadu (42%), undivided Andhra Pradesh (34%), and Kerala (30%). Further, in wealthier states (Delhi, Goa, Punjab, Haryana, Tamil Nadu, Kerala, and undivided Andhra Pradesh), CCF use increased by more than 20% among the poorest individuals compared with less than 1% among the poorest families in lower income states (Tripura, Meghalaya, Madhya Pradesh, Jharkhand, Chhattisgarh, Bihar). To promote a more equitable clean energy transition, poorer and rural Indian households should be prioritized for CCF promotion programs.

Complex dynamics in sustaining clean cooking and food access through a pandemic: A COVID-19 impact study in peri-urban Cameroon.

Access to clean energy for cooking is central to achieving Sustainable Development Goal 7. Latest predictions suggest that this goal will not be met by 2030, with further setbacks due to the COVID-19 pandemic. We investigated the impacts of COVID-19 restrictions on household cooking fuel, practices and dietary behaviours in a peri-urban community in Central Cameroon. Using surveys (n = 333) and qualitative semi-structured interviews (n = 12), we found negative financial impacts and high levels of food insecurity, with 83 % and 56 % of households reporting reduced income and insufficient food, respectively. Households reduced food intake and cooking frequency and relied more heavily on local sources (e.g., farmland) to feed their families. Changes in primary cooking fuel were less pronounced and fuel choice was inherently linked to cooking behaviours, with some households utilising LPG more often for simple tasks, such as reheating food. Local systems were key in sustaining food and fuel access and households demonstrated resilience by employing numerous mechanisms to overcome challenges. Our findings underline the vulnerability of households in maintaining sufficient food intake and sustaining clean cooking, highlighting how policy needs to take a nuanced approach considering food-energy dynamics and strengthening local systems to ensure access to clean energy is resistant to system shocks.

Personal and household PM2.5 and black carbon exposure measures and respiratory symptoms in 8 low- and middle-income countries.

BACKGROUND: Household air pollution (HAP) from cooking with solid fuels has been associated with adverse respiratory effects, but most studies use surveys of fuel use to define HAP exposure, rather than on actual air pollution exposure measurements. OBJECTIVE: To examine associations between household and personal fine particulate matter (PM2.5) and black carbon (BC) measures and respiratory symptoms. METHODS: As part of the Prospective Urban and Rural Epidemiology Air Pollution study, we analyzed 48-h household and personal PM2.5 and BC measurements for 870 individuals using different cooking fuels from 62 communities in 8 countries (Bangladesh, Chile, China, Colombia, India, Pakistan, Tanzania, and Zimbabwe). Self-reported respiratory symptoms were collected after monitoring. Associations between PM2.5 and BC exposures and respiratory symptoms were examined using logistic regression models, controlling for individual, household, and community covariates. RESULTS: The median (interquartile range) of household and personal PM2.5 was 73.5 (119.1) and 65.3 (91.5) µg/m3, and for household and personal BC was 3.4 (8.3) and 2.5 (4.9) x10-5 m-1, respectively. We observed associations between household PM2.5 and wheeze (OR: 1.25; 95%CI: 1.07, 1.46), cough (OR: 1.22; 95%CI: 1.06, 1.39), and sputum (OR: 1.26; 95%CI: 1.10, 1.44), as well as exposure to household BC and wheeze (OR: 1.20; 95%CI: 1.03, 1.39) and sputum (OR: 1.20; 95%CI: 1.05, 1.36), per IQR increase. We observed associations between personal PM2.5 and wheeze (OR: 1.23; 95%CI: 1.00, 1.50) and sputum (OR: 1.19; 95%CI: 1.00, 1.41). For household PM2.5 and BC, associations were generally stronger for females compared to males. Models using an indicator variable of solid versus clean fuels resulted in larger OR estimates with less precision. CONCLUSIONS: We used measurements of household and personal air pollution for individuals using different cooking fuels and documented strong associations with respiratory symptoms.

Multiple aspects of energy poverty are associated with lower mental health-related quality of life: A modelling study in three peri-urban African communities.

Objective: Over 900 million people in sub-Saharan Africa (SSA) live in energy poverty, relying on cooking polluting fuels (e.g. wood, charcoal). The association between energy poverty and mental/physical health-related quality of life (HRQoL) among women in SSA, who are primarily tasked with cooking, is unknown. Methods: Females (n â€‹= â€‹1,150) from peri-urban Cameroon, Kenya and Ghana were surveyed on their household energy use and mental/physical health status using the standardized Short-Form 36 (SF-36) questionnaire. Random effects linear regression linked household energy factors to SF-36 mental (MCS) and physical component summary (PCS) scores. A binary outcome of 'likely depression' was derived based on participants' MCS score. Random effects Poisson regression with robust error variance assessed the relationship between household energy factors and odds of likely depression. Results: The prevalence of likely depression varied by a factor of four among communities (36%-Mbalmayo, Cameroon; 20%-Eldoret, Kenya; 9%-Obuasi, Ghana). In the Poisson model (coefficient of determination (R2) â€‹= â€‹0.28), females sustaining 2 or more cooking-related burns during the previous year had 2.7 (95%CI:[1.8,4.1]) times the odds of likely depression as those not burned. Females cooking primarily with charcoal and wood had 1.6 times (95%CI:[0.9,2.7]) and 1.5 times (95%CI:[0.8,3.0]) the odds of likely depression, respectively, as those primarily using liquefied petroleum gas. Women without electricity access had 1.4 (95%CI:[1.1,1.9]) times the odds of likely depression as those with access. In the MCS model (R2 â€‹= â€‹0.23), longer time spent cooking was associated with a lower average MCS score in a monotonically increasing manner. In the PCS model (R2 â€‹= â€‹0.32), women injured during cooking fuel collection had significantly lower (-4.8 95%CI:[-8.1,-1.4]) PCS scores. Conclusion: The burden of energy poverty in peri-urban communities in SSA extends beyond physical conditions. Experiencing cooking-related burns, using polluting fuels for cooking or lighting and spending more time cooking are potential risk factors for lower mental HRQoL among women.

Multinational prediction of household and personal exposure to fine particulate matter (PM2.5) in the PURE cohort study.

INTRODUCTION: Use of polluting cooking fuels generates household air pollution (HAP) containing health-damaging levels of fine particulate matter (PM2.5). Many global epidemiological studies rely on categorical HAP exposure indicators, which are poor surrogates of measured PM2.5 levels. To quantitatively characterize HAP levels on a large scale, a multinational measurement campaign was leveraged to develop household and personal PM2.5 exposure models. METHODS: The Prospective Urban and Rural Epidemiology (PURE)-AIR study included 48-hour monitoring of PM2.5 kitchen concentrations (n = 2,365) and male and/or female PM2.5 exposure monitoring (n = 910) in a subset of households in Bangladesh, Chile, China, Colombia, India, Pakistan, Tanzania and Zimbabwe. PURE-AIR measurements were combined with survey data on cooking environment characteristics in hierarchical Bayesian log-linear regression models. Model performance was evaluated using leave-one-out cross validation. Predictive models were applied to survey data from the larger PURE cohort (22,480 households; 33,554 individuals) to quantitatively estimate PM2.5 exposures. RESULTS: The final models explained half (R2 = 54%) of the variation in kitchen PM2.5 measurements (root mean square error (RMSE) (log scale):2.22) and personal measurements (R2 = 48%; RMSE (log scale):2.08). Primary cooking fuel type, heating fuel type, country and season were highly predictive of PM2.5 kitchen concentrations. Average national PM2.5 kitchen concentrations varied nearly 3-fold among households primarily cooking with gas (20 µg/m3 (Chile); 55 µg/m3 (China)) and 12-fold among households primarily cooking with wood (36 µg/m3 (Chile)); 427 µg/m3 (Pakistan)). Average PM2.5 kitchen concentration, heating fuel type, season and secondhand smoke exposure were significant predictors of personal exposures. Modeled average PM2.5 female exposures were lower than male exposures in upper-middle/high-income countries (India, China, Colombia, Chile). CONCLUSION: Using survey data to estimate PM2.5 exposures on a multinational scale can cost-effectively scale up quantitative HAP measurements for disease burden assessments. The modeled PM2.5 exposures can be used in future epidemiological studies and inform policies targeting HAP reduction.