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.

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.

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.

Modeling approaches and performance for estimating personal exposure to household air pollution: A case study in Kenya.

This study assessed the performance of modeling approaches to estimate personal exposure in Kenyan homes where cooking fuel combustion contributes substantially to household air pollution (HAP). We measured emissions (PM2.5 , black carbon, CO); household air pollution (PM2.5 , CO); personal exposure (PM2.5 , CO); stove use; and behavioral, socioeconomic, and household environmental characteristics (eg, ventilation and kitchen volume). We then applied various modeling approaches: a single-zone model; indirect exposure models, which combine person-location and area-level measurements; and predictive statistical models, including standard linear regression and ensemble machine learning approaches based on a set of predictors such as fuel type, room volume, and others. The single-zone model was reasonably well-correlated with measured kitchen concentrations of PM2.5 (R2  = 0.45) and CO (R2  = 0.45), but lacked precision. The best performing regression model used a combination of survey-based data and physical measurements (R2  = 0.76) and a root mean-squared error of 85 µg/m3 , and the survey-only-based regression model was able to predict PM2.5 exposures with an R2 of 0.51. Of the machine learning algorithms evaluated, extreme gradient boosting performed best, with an R2 of 0.57 and RMSE of 98 µg/m3 .

Energy poverty influences urban outdoor air pollution levels during COVID-19 lockdown in south-central Chile.

The effect of COVID-19 lockdowns on ambient air pollution levels in urban south-central Chile, where outdoor air pollution primarily originates indoors from wood burning for heating, may differ from trends in cities where transportation and industrial emission sources dominate. This quasi-experimental study compared hourly fine (PM2.5) and coarse (PM10) particulate matter measurements from six air monitors (three beta attenuation monitors; three low-cost sensors) in commercial and low/middle-income residential areas of Temuco, Chile between 2019 and 2020. The potential impact of varying annual meterological conditions on air quality was also assessed. During COVID-19 lockdown, average monthly ambient PM2.5 concentrations in a commercial and middle-income residential neighborhood of Temuco were up to 50% higher (from 12 to 18 µg/m3) and 59% higher (from 22 to 35 µg/m3) than 2019 levels, respectively. Conversely, PM2.5 levels decreased by up to 52% (from 43 to 21 µg/m3) in low-income areas. The fine fraction of PM10 in April 2020 was 48% higher than in April 2017-2019 (from 50% to 74%) in a commercial area. These changes did not appear to result from meterological differences between years. During COVID-19 lockdown, higher outdoor PM2.5 pollution from wood heating existed in more affluent areas of Temuco, while PM2.5 concentrations declined among poorer households refraining from wood heating. To reduce air pollution and energy poverty in south-central Chile, affordability of clean heating fuels (e.g. electricity) should be a policy priority.

Pay-as-you-go liquefied petroleum gas supports sustainable clean cooking in Kenyan informal urban settlement during COVID-19 lockdown.

Approximately 2.8 billion people rely on polluting fuels (e.g. wood, kerosene) for cooking. With affordability being a key access barrier to clean cooking fuels, such as liquefied petroleum gas (LPG), pay-as-you-go (PAYG) LPG smart meter technology may help resource-poor households adopt LPG by allowing incremental fuel payments. To understand the potential for PAYG LPG to facilitate clean cooking, objective evaluations of customers' cooking and spending patterns are needed. This study uses novel smart meter data collected between January 2018-June 2020, spanning COVID-19 lockdown, from 426 PAYG LPG customers living in an informal settlement in Nairobi, Kenya to evaluate stove usage (e.g. cooking events/day, cooking event length). Seven semi-structured interviews were conducted in August 2020 to provide context for potential changes in cooking behaviours during lockdown. Using stove monitoring data, objective comparisons of cooking patterns are made with households using purchased 6 kg cylinder LPG in peri-urban Eldoret, Kenya. In Nairobi, 95% of study households continued using PAYG LPG during COVID-19 lockdown, with consumption increasing from 0.97 to 1.22 kg/capita/month. Daily cooking event frequency also increased by 60% (1.07 to 1.72 events/day). In contrast, average days/month using LPG declined by 75% during lockdown (17 to four days) among seven households purchasing 6 kg cylinder LPG in Eldoret. Interviewed customers reported benefits of PAYG LPG beyond fuel affordability, including safety, time savings and cylinder delivery. In the first study assessing PAYG LPG cooking patterns, LPG use was sustained despite a COVID-19 lockdown, illustrating how PAYG smart meter technology may help foster clean cooking access.

Analysis of black carbon on filters by image-based reflectance.

Black carbon (BC) is an important contributor to global particulate matter emissions. BC is associated with adverse health effects, and an important short-lived climate pollutant. Here, we describe a low cost method of analysis that utilizes images of PTFE filters taken with a digital camera to estimate BC content on filters. This method is compared with two existing optical methods for analyzing BC (Smokestain Reflectance and Hybrid Integrating Plate and Sphere System) as well as the standard chemical analysis method for determining elemental carbon (Thermal-Optical Reflectance). In comparisons of aerosol generated under controlled conditions (using an inverted diffusion flame burner to cover a range of mass loading and reflectance levels) (N=12) and in field samples collected from residential solid fuel combustion in China and India (N=50), the image-based method was found to correlate well (normalized RMSE <10% for all comparisons) with existing methods. A correlational analysis of field samples between the optical methods and Fourier-transform infrared spectroscopy indicated that the same functional groups were predominantly responsible for light attenuation in each optical method. This method offers reduced equipment cost, rapid analysis time, and is available at no cost, which may facilitate more measurement of BC where PM2.5 mass concentrations are already measured, especially in low income countries or other sampling efforts with limited resources.

Prevalence of chronic pain among individuals with neurological conditions.

BACKGROUND: The prevalence of pain among people with a variety of individual neurological conditions has been estimated. However, information is limited about chronic pain among people with neurological conditions overall, and about the conditions for which chronic pain is most prevalent. To fill these information gaps, a common method of pain assessment is required. DATA AND METHODS: The data are from the Survey on Living with Neurological Conditions in Canada, a cross-sectional national survey. Based on self-reports, chronic pain was assessed for 16 neurological conditions. Multivariable logistic regression was used to produce odds ratios and 95% confidence intervals (CIs). RESULTS: Close to 1.5 million individuals aged 15 or older who lived in private households reported having been diagnosed with a neurological condition. The overall prevalence of chronic pain for the 16 neurological conditions combined was 36% (95% CI: 31% to 42%). The odds of chronic pain were significantly elevated among individuals with spinal cord trauma. DISCUSSION: Chronic pain is highly prevalent among people with neurological conditions, particularly those with spinal cord trauma. These results suggest a need to target health services and direct research to improved pain management, and thereby reduce the burden of neurological disease.

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.

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.

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.

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.

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.

Measuring and predicting personal and household Black Carbon levels from 88 communities in eight countries.

Black Carbon (BC) is an important component of household air pollution (HAP) in low- and middle- income countries (LMICs), but levels and drivers of exposure are poorly understood. As part of the Prospective Urban and Rural Epidemiological (PURE) study, we analyzed 48-hour BC measurements for 1187 individual and 2242 household samples from 88 communities in 8 LMICs (Bangladesh, Chile, China, Colombia, India, Pakistan, Tanzania, and Zimbabwe). Light absorbance (10-5 m-1) of collected PM2.5 filters, a proxy for BC concentrations, was calculated via an image-based reflectance method. Surveys of household/personal characteristics and behaviors were collected after monitoring. The geometric mean (GM) of personal and household BC measures was 2.4 (3.3) and 3.5 (3.9)·10-5 m-1, respectively. The correlation between BC and PM2.5 was r = 0.76 for personal and r = 0.82 for household measures. A gradient of increasing BC concentrations was observed for cooking fuels: BC increased 53% (95%CI: 30, 79) for coal, 142% (95%CI: 117, 169) for wood, and 190% (95%CI: 149, 238) for other biomass, compared to gas. Each hour of cooking was associated with an increase in household (5%, 95%CI: 3, 7) and personal (5%, 95%CI: 2, 8) BC; having a window in the kitchen was associated with a decrease in household (-38%, 95%CI: -45, -30) and personal (-31%, 95%CI: -44, -15) BC; and cooking on a mud stove, compared to a clean stove, was associated with an increase in household (125%, 95%CI: 96, 160) and personal (117%, 95%CI: 71, 117) BC. Male participants only had slightly lower personal BC (-0.6%, 95%CI: -1, 0.0) compared to females. In multivariate models, we were able to explain 46-60% of household BC variation and 33-54% of personal BC variation. These data and models provide new information on exposure to BC in LMICs, which can be incorporated into future exposure assessments, health research, and policy surrounding HAP and BC.

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.

COVID-19 impacts on household energy & food security in a Kenyan informal settlement: The need for integrated approaches to the SDGs.

This longitudinal study presents the joint effects of a COVID-19 community lockdown on household energy and food security in an informal settlement in Nairobi, Kenya. Randomly administered surveys were completed from December 2019-March 2020 before community lockdown (n = 474) and repeated in April 2020 during lockdown (n = 194). Nearly universal (95%) income decline occurred during the lockdown and led to 88% of households reporting food insecurity. During lockdown, a quarter of households (n = 17) using liquefied petroleum gas (LPG), a cleaner cooking fuel typically available in pre-set quantities (e.g. 6 kg cylinders), switched to polluting cooking fuels (kerosene, wood), which could be purchased in smaller amounts or gathered for free. Household size increases during lockdown also led to participants' altering their cooking fuel, and changing their cooking behaviors and foods consumed. Further, households more likely to switch away from LPG had lower consumption prior to lockdown and had suffered greater income loss, compared with households that continued to use LPG. Thus, inequities in clean cooking fuel access may have been exacerbated by COVID-19 lockdown. These findings demonstrate the complex relationship between household demographics, financial strain, diet and cooking patterns, and present the opportunity for a food-energy nexus approach to address multiple Sustainable Development Goals (SDGs): achieving zero hunger (SDG 2) and universal affordable, modern and clean energy access (SDG 7) by 2030. Ensuring that LPG is affordable, accessible and meets the dietary and cooking needs of families should be a policy priority for helping improve food and energy security among the urban poor.

Health and Climate Impacts of Scaling Adoption of Liquefied Petroleum Gas (LPG) for Clean Household Cooking in Cameroon: A Modeling Study.

BACKGROUND: The Cameroon government has set a target that, by 2030, 58% of the population will be using Liquefied Petroleum Gas (LPG) as a cooking fuel, in comparison with less than 20% in 2014. The National LPG Master Plan (Master Plan) was developed for scaling up the LPG sector to achieve this target. OBJECTIVES: This study aimed to estimate the potential impacts of this planned LPG expansion (the Master Plan) on population health and climate change mitigation, assuming primary, sustained use of LPG for daily cooking. METHODS: We applied existing and developed new mathematical models to calculate the health and climate impacts of expanding LPG primary adoption for household cooking in Cameroon over two periods: a) short-term (2017-2030): Comparing the Master Plan 58% target with a counterfactual LPG adoption of 32% in 2030, in line with current trends; and b) long-term (2031-2100, climate modeling only), assuming Cameroon will become a mature and saturated LPG market by 2100 (73% adoption, based on Latin American countries). We compared this with a counterfactual adoption of 41% by 2100, in line with current trends. RESULTS: By 2030, successful implementation of the Master Plan was estimated to avert about 28,000 (minimum=22,000, maximum=35,000) deaths and 770,000 (minimum=580,000 maximum=1 million) disability-adjusted life years. For the same period, we estimated reductions in pollutant emissions of more than a third in comparison with the counterfactual, leading to a global cooling of -0.1 milli °C in 2030. For 2100, a cooling impact from the Master Plan leading to market saturation (73%) was estimated to be -0.70 milli °C in comparison with to the counterfactual, with a range of -0.64 to -0.93 milli °C based on different fractions of nonrenewable biomass. DISCUSSION: Successful implementation of the Master Plan could have significant positive impacts on population health in Cameroon with no adverse impacts on climate. https://doi.org/10.1289/EHP4899.

Digital Proxy of a Bio-Reactor (DIYBOT) combines sensor data and data analytics to improve greywater treatment and wastewater management systems.

Technologies to treat wastewater in decentralized systems are critical for sustainable development. Bioreactors are suitable for low-energy removal of inorganic and organic compounds, particularly for non-potable applications where a small footprint is required. One of the main problems associated with bioreactor use is sporadic spikes of chemical toxins, including nanoparticles. Here, we describe the development of DIYBOT (Digital Proxy of a Bio-Reactor), which enables remote monitoring of bioreactors and uses the data to inform decisions related to systems management. To test DIYBOT, a household-scale membrane aerated bioreactor with real-time water quality sensors was used to treat household greywater simulant. After reaching steady-state, silver nanoparticles (AgNP) representative of the mixture found in laundry wastewater were injected into the system to represent a chemical contamination. Measurements of carbon metabolism, effluent water quality, biofilm sloughing rate, and microbial diversity were characterized after nanoparticle exposure. Real-time sensor data were analyzed to reconstruct phase-space dynamics and extrapolate a phenomenological digital proxy to evaluate system performance. The management implication of the stable-focus dynamics, reconstructed from observed data, is that the bioreactor self-corrects in response to contamination spikes at AgNP levels below 2.0 mg/L. DIYBOT may help reduce the frequency of human-in-the-loop corrective management actions for wastewater processing.

Household and personal air pollution exposure measurements from 120 communities in eight countries: results from the PURE-AIR study.

BACKGROUND: Approximately 2·8 billion people are exposed to household air pollution from cooking with polluting fuels. Few monitoring studies have systematically measured health-damaging air pollutant (ie, fine particulate matter [PM2·5] and black carbon) concentrations from a wide range of cooking fuels across diverse populations. This multinational study aimed to assess the magnitude of kitchen concentrations and personal exposures to PM2·5 and black carbon in rural communities with a wide range of cooking environments. METHODS: As part of the Prospective Urban and Rural Epidemiological (PURE) cohort, the PURE-AIR study was done in 120 rural communities in eight countries (Bangladesh, Chile, China, Colombia, India, Pakistan, Tanzania, and Zimbabwe). Data were collected from 2541 households and from 998 individuals (442 men and 556 women). Gravimetric (or filter-based) 48 h kitchen and personal PM2·5 measurements were collected. Light absorbance (10-5m-1) of the PM2·5 filters, a proxy for black carbon concentrations, was calculated via an image-based reflectance method. Surveys of household characteristics and cooking patterns were collected before and after the 48 h monitoring period. FINDINGS: Monitoring of household air pollution for the PURE-AIR study was done from June, 2017, to September, 2019. A mean PM2·5 kitchen concentration gradient emerged across primary cooking fuels: gas (45 µg/m3 [95% CI 43-48]), electricity (53 µg/m3 [47-60]), coal (68 µg/m3 [61-77]), charcoal (92 µg/m3 [58-146]), agricultural or crop waste (106 µg/m3 [91-125]), wood (109 µg/m3 [102-118]), animal dung (224 µg/m3 [197-254]), and shrubs or grass (276 µg/m3 [223-342]). Among households cooking primarily with wood, average PM2·5 concentrations varied ten-fold (range: 40-380 µg/m3). Fuel stacking was prevalent (981 [39%] of 2541 households); using wood as a primary cooking fuel with clean secondary cooking fuels (eg, gas) was associated with 50% lower PM2·5 and black carbon concentrations than using only wood as a primary cooking fuel. Similar average PM2·5 personal exposures between women (67 µg/m3 [95% CI 62-72]) and men (62 [58-67]) were observed. Nearly equivalent average personal exposure to kitchen exposure ratios were observed for PM2·5 (0·79 [95% 0·71-0·88] for men and 0·82 [0·74-0·91] for women) and black carbon (0·64 [0·45-0·92] for men and 0·68 [0·46-1·02] for women). INTERPRETATION: Using clean primary fuels substantially lowers kitchen PM2·5 concentrations. Importantly, average kitchen and personal PM2·5 measurements for all primary fuel types exceeded WHO's Interim Target-1 (35 µg/m3 annual average), highlighting the need for comprehensive pollution mitigation strategies. FUNDING: Canadian Institutes for Health Research, National Institutes of Health.