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Introduction: Use of polluting cooking fuels generates household air pollution (HAP) containing health-damaging levels of fine particulate matter (PM 2.5 ). Many global epidemiological studies rely on categorical HAP exposure indicators, which are poor surrogates of measured PM 2.5 levels. To quantitatively characterize HAP levels on a large scale, a multinational measurement campaign was leveraged to develop household and personal PM 2.5 exposure models., Methods: The Prospective Urban and Rural Epidemiology (PURE)-AIR study included 48-hour monitoring of PM 2.5 kitchen concentrations (n = 2,365) and male and/or female PM 2.5 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 PM 2.5 exposures., Results: The final models explained half (R 2  = 54%) of the variation in kitchen PM 2.5 measurements (root mean square error (RMSE) (log scale):2.22) and personal measurements (R 2  = 48%; RMSE (log scale):2.08). Primary cooking fuel type, heating fuel type, country and season were highly predictive of PM 2.5 kitchen concentrations. Average national PM 2.5 kitchen concentrations varied nearly 3-fold among households primarily cooking with gas (20 μg/m 3 (Chile); 55 μg/m 3 (China)) and 12-fold among households primarily cooking with wood (36 μg/m 3 (Chile)); 427 μg/m 3 (Pakistan)). Average PM 2.5 kitchen concentration, heating fuel type, season and secondhand smoke exposure were significant predictors of personal exposures. Modeled average PM 2.5 female exposures were lower than male exposures in upper-middle/high-income countries (India, China, Colombia, Chile)., Conclusion: Using survey data to estimate PM 2.5 exposures on a multinational scale can cost-effectively scale up quantitative HAP measurements for disease burden assessments. The modeled PM 2.5 exposures can be used in future epidemiological studies and inform policies targeting HAP reduction., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

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., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 The Author(s).)

Background: Exposure to household air pollution (HAP) from cooking with dirty fuels is a leading health risk factor within Asia, Africa and Central/South America. The concentration of particulate matter of diameter ≤ 2.5 μm (PM 2.5 ) is an important metric to evaluate HAP risk, however epidemiological studies have demonstrated significant variation in HAP-PM 2.5 concentrations at household, community and country levels. To quantify the global risk due to HAP exposure, novel estimation methods are needed, as financial and resource constraints render it difficult to monitor exposures in all relevant areas., Methods: A Bayesian, hierarchical HAP-PM 2.5 global exposure model was developed using kitchen and female HAP-PM 2.5 exposure data available in peer-reviewed studies from an updated World Health Organization Global HAP database. Cooking environment characteristics were selected using leave-one-out cross validation to predict quantitative HAP-PM 2.5 measurements from 44 studies. Twenty-four hour HAP-PM 2.5 kitchen concentrations and male, female and child exposures were estimated for 106 countries in Asia, Africa and Latin America., Results: A model incorporating fuel/stove type (traditional wood, improved biomass, coal, dung and gas/electric), urban/rural location, wet/dry season and socio-demographic index resulted in a Bayesian R 2 of 0.57. Relative to rural kitchens using gas or electricity, the mean global 24-hour HAP-PM 2.5 concentrations were 290 μg/m 3 higher (range of regional averages: 110, 880) for traditional stoves, 150 μg/m 3 higher (range of regional averages: 50, 290) for improved biomass stoves, 850 μg/m 3 higher (range of regional averages: 310, 2600) for animal dung stoves, and 220 μg/m 3 higher (range of regional averages: 80, 650) for coal stoves. The modeled global average female/kitchen exposure ratio was 0.40. Average modeled female exposures from cooking with traditional wood stoves were 160 μg/m 3 in rural households and 170 μg/m 3 in urban households. Average male and child rural area exposures from traditional wood stoves were 120 μg/m 3 and 140 μg/m 3 , respectively; average urban area exposures were identical to average rural exposures among both sub-groups., Conclusions: A Bayesian modeling approach was used to generate unique HAP-PM 2.5 kitchen concentrations and personal exposure estimates for all countries, including those with little to no available quantitative HAP-PM 2.5 exposure data. The global exposure model incorporating type of fuel-stove combinations can add specificity and reduce exposure misclassification to enable an improved global HAP risk assessment., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Background: Household air pollution (HAP) from combustion of solid fuels is an important contributor to disease burden in low- and middle-income countries (LIC, and MIC). However, current HAP disease burden estimates are based on integrated exposure response curves that are not currently informed by quantitative HAP studies in LIC and MIC. While there is adequate evidence supporting causal relationships between HAP and respiratory disease, large cohort studies specifically examining relationships between quantitative measures of HAP exposure with cardiovascular disease are lacking., Objective: We aim to improve upon exposure proxies based on fuel type, and to reduce exposure misclassification by quantitatively measuring exposure across varying cooking fuel types and conditions in diverse geographies and socioeconomic settings. We leverage technology advancements to estimate household and personal PM 2.5 (particles below 2.5 μm in aerodynamic diameter) exposure within the large (N~250,000) multi-country (N~26) Prospective Urban and Rural Epidemiological (PURE) cohort study. Here, we detail the study protocol and the innovative methodologies being used to characterize HAP exposures, and their application in epidemiologic analyses., Methods/design: This study characterizes HAP PM 2.5 exposures for participants in rural communities in ten PURE countries with >10% solid fuel use at baseline (Bangladesh, Brazil, Chile, China, Colombia, India, Pakistan, South Africa, Tanzania, and Zimbabwe). PM 2.5 monitoring includes 48-h cooking area measurements in 4500 households and simultaneous personal monitoring of male and female pairs from 20% of the selected households. Repeat measurements occur in 20% of households to assess impacts of seasonality. Monitoring began in 2017, and will continue through 2019. The Ultrasonic Personal Aerosol Sampler (UPAS), a novel, robust, and inexpensive filter based monitor that is programmable through a dedicated mobile phone application is used for sampling. Pilot study field evaluation of cooking area measurements indicated high correlation between the UPAS and reference Harvard Impactors (r = 0.91; 95% CI: 0.84, 0.95; slope = 0.95). To facilitate tracking and to minimize contamination and analytical error, the samplers utilize barcoded filters and filter cartridges that are weighed pre- and post-sampling using a fully automated weighing system. Pump flow and pressure measurements, temperature and RH, GPS coordinates and semi-quantitative continuous particle mass concentrations based on filter differential pressure are uploaded to a central server automatically whenever the mobile phone is connected to the internet, with sampled data automatically screened for quality control parameters. A short survey is administered during the 48-h monitoring period. Post-weighed filters are further analyzed to estimate black carbon concentrations through a semi-automated, rapid, cost-effective image analysis approach. The measured PM 2.5 data will then be combined with PURE survey information on household characteristics and behaviours collected at baseline and during follow-up to develop quantitative HAP models for PM 2.5 exposures for all rural PURE participants (~50,000) and across different cooking fuel types within the 10 index countries. Both the measured (in the subset) and the modelled exposures will be used in separate longitudinal epidemiologic analyses to assess associations with cardiopulmonary mortality, and disease incidence., Discussion: The collected data and resulting characterization of cooking area and personal PM 2.5 exposures in multiple rural communities from 10 countries will better inform exposure assessment as well as future epidemiologic analyses assessing the relationships between quantitative estimates of chronic HAP exposure with adult mortality and incident cardiovascular and respiratory disease. This will provide refined and more accurate exposure estimates in global CVD related exposure-response analyses., (Copyright © 2018 Elsevier Ltd. All rights reserved.)