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In 2017 an estimated 3 billion people used polluting fuels and technologies as their primary cooking solution, with 3.8 million deaths annually attributed to household exposure to the resulting fine particulate matter air pollution. Currently, health burdens are calculated by using aggregations of fuel types, e.g. solid fuels, as country level estimates of the use of specific fuel types, e.g. wood and charcoal, are unavailable. To expand the knowledge base about effects of household air pollution on health, we develop and implement a novel Bayesian hierarchical model, based on generalized Dirichlet–multinomial distributions, that jointly estimates non-linear trends in the use of eight key fuel types, overcoming several data-specific challenges including missing or combined fuel use values. We assess model fit by using within-sample predictive analysis and an out-of-sample prediction experiment to evaluate the model's forecasting performance.

The UN-led discussion about the post-2015 sustainable development agenda provides an opportunity to develop indicators and targets that show the importance of health as a precondition for and an outcome of policies to promote sustainable development. Health as a precondition for development has received considerable attention in terms of achievement of health-related Millennium Development Goals (MDGs), addressing growing challenges of non-communicable diseases, and ensuring universal health coverage. Much less attention has been devoted to health as an outcome of sustainable development and to indicators that show both changes in exposure to health-related risks and progress towards environmental sustainability. We present a rationale and methods for the selection of health-related indicators to measure progress of post-2015 development goals in non-health sectors. The proposed indicators show the ancillary benefits to health and health equity (co-benefits) of sustainable development policies, particularly those to reduce greenhouse gas emissions and increase resilience to environmental change. We use illustrative examples from four thematic areas: cities, food and agriculture, energy, and water and sanitation. Embedding of a range of health-related indicators in the post-2015 goals can help to raise awareness of the probable health gains from sustainable development policies, thus making them more attractive to decision makers and more likely to be implemented than before.

Household air pollution generated from the use of polluting cooking fuels and technologies is a major source of disease and environmental degradation in low- and middle-income countries. Using a novel modelling approach, we provide detailed global, regional and country estimates of the percentages and populations mainly using 6 fuel categories (electricity, gaseous fuels, kerosene, biomass, charcoal, coal) and overall polluting/clean fuel use – from 1990-2020 and with urban/rural disaggregation. Here we show that 53% of the global population mainly used polluting cooking fuels in 1990, dropping to 36% in 2020. In urban areas, gaseous fuels currently dominate, with a growing reliance on electricity; in rural populations, high levels of biomass use persist alongside increasing use of gaseous fuels. Future projections of observed trends suggest 31% will still mainly use polluting fuels in 2030, including over 1 billion people in Sub-Saharan African by 2025. Household air pollution derived from cooking fuels is a major source of health and environmental problems. Here, the authors provide detailed global, regional and country estimates of cooking fuel usage from 1990 to 2030 and project that 31% of people will still be mainly using polluting fuels in 2030.

Globally, approximately 3 billion primarily cook using inefficient and poorly vented combustion devices, leading to unsafe levels of household air pollution (HAP) in and around the home. Such exposures contribute to nearly 4 million deaths annually (WHO 2018a, 2018b ). Characterizing the effectiveness of interventions for reducing HAP concentration and exposure is critical for informing policy and programmatic decision-making on which cooking solutions yield the greatest health benefits. This review synthesizes evidence of in-field measurements from four cleaner cooking technologies and three clean fuels, using field studies aimed at reducing HAP concentration and personal exposure to health damaging pollutants (particulate matter (PM 2.5 ) and carbon monoxide (CO)). Fifty studies from Africa, Asia, South and Latin America, provided 168 estimates synthesized through meta-analysis. For PM 2.5 kitchen concentrations, burning biomass more cleanly through improved combustion stoves (ICS) with ( n = 29; 63% reduction) or without ( n = 12; 52%) venting (through flue or chimney) and through forced-draft combustion ( n = 9; 50%) was less effective than cooking with clean fuels including ethanol ( n = 4; 83%), liquefied petroleum gas (LPG) ( n = 11; 83%) and electricity ( n = 6; 86%). Only studies of clean fuels consistently achieved post-intervention kitchen PM 2.5 levels at or below the health-based WHO interim target level 1 (WHO-IT1) of 35 μ g m −3 . None of the advanced combustion stoves (gasifiers) achieved WHO-IT1, although no evidence was available for pellet fuelled stoves. For personal exposure to PM 2.5, none of the ICS ( n = 11) were close to WHO-IT1 whereas 75% ( n = 6 of 8) of LPG interventions were at or below WHO-IT1. Similar patterns were observed for CO, although most post-intervention levels achieved the WHO 24 h guideline level. While clean cooking fuel interventions (LPG, electric) significantly reduce kitchen concentrations and personal exposure to PM 2.5 in household settings, stove stacking and background levels of ambient air pollution, have likely prevented most clean fuel interventions from approaching WHO-IT1. In order to maximize health gains, a wholistic approach jointly targeting ambient and HAP should be followed in lower-and-middle income countries.

Cooking with polluting and inefficient fuels and technologies is responsible for a large set of global harms, ranging from health and time losses among the billions of people who are energy poor, to environmental degradation at a regional and global scale. This paper presents a new decision-support model–the BAR-HAP Tool–that is aimed at guiding planning of policy interventions to accelerate transitions towards cleaner cooking fuels and technologies. The conceptual model behind BAR-HAP lies in a framework of costs and benefits that is holistic and comprehensive, allows consideration of multiple policy interventions (subsidies, financing, bans, and behavior change communication), and realistically accounts for partial adoption and use of improved cooking technology. It incorporates evidence from recent efforts to characterize the relevant set of parameters that determine those costs and benefits, including those related to intervention effectiveness. Practical aspects of the tool were modified based on feedback from a pilot testing workshop with multisectoral users in Nepal. To demonstrate the functionality of the BAR-HAP tool, we present illustrative calculations related to several cooking transitions in the context of Nepal. In accounting for the multifaceted nature of the issue of household air pollution, the BAR-HAP model is expected to facilitate cross-sector dialogue and problem-solving to address this major health, environment and development challenge.

Exposure to household air pollution results in a substantial global health burden. The World Health Organization (WHO) Guidelines for Indoor Air Quality: Household Fuel Combustion stipulate emission rates for household energy devices should meet air quality guidelines and protect health. Liquefied petroleum gas (LPG), biogas, natural gas (NG), and alcohol fuels are considered clean for health due to their low emissions at the point of use. In light of the ongoing energy transition and increasing emphasis on these fuels, it is imperative to provide an updated synthesis of the impacts of these fuels on health. A systematic review was completed on the health effects of liquid and gaseous fuels for household energy use for cooking, heating, and lighting across high-, middle- and low-income countries. Comprehensive searches were undertaken in 12 international databases and selected studies were compiled into a new publicly available WHO Health Effects of Household Liquid & Gaseous Fuels Database, containing key study characteristics including pollutants and/or health outcomes measured. This database was then mapped to understand the breadth of evidence and potential gaps. From 48 130 search results, 587 studies were extracted for inclusion in the database on completion of the full-text review. Studies represented low-, middle- and high-income countries (HICs) over several decades - there has been a substantial increase in evidence from low- and middle-income countries (LMICs) published in the last decade, particularly in Asia. Most evidence focused on LPG for cooking in LMICs or NG used in HICs for cooking and heating. Women were the most studied demographic, with self-reported health outcomes and symptoms being the most common assessment method. Particulate matter and nitrogen oxides were the most monitored pollutants. A wide array of health symptoms and disease and injury outcomes were assessed, and most concerned respiratory health. This is the first time that evidence on the health effects of liquid and gaseous fuels for household energy use has been systematically catalogued and mapped. Most evidence concerned cooking and heating, with a paucity of information on the health effects from lighting. Limited evidence was available on the health effects of liquid fuels (such as alcohol fuels), with most studies concerning gaseous fuels. The WHO Health Effects of Household Liquid & Gaseous Fuels Database represents a valuable resource to enable the examination of the positive and negative health effects from these fuels.

Many people strive to improve the world around them, but few have impacted millions of lives the way the late Professor Kirk Robert Smith has. From championing the right of the poorest populations to have a clean stove for cooking, to building knowledge and inspiring students, researchers and policy-makers to address environmental health risks (particularly air pollution and climate change), Smith was a true public health champion and leader.

Exposure to household air pollution from cooking with solid fuels in simple stoves is a major health risk. Modeling reliable estimates of solid fuel use is needed for monitoring trends and informing policy. In order to revise the disease burden attributed to household air pollution for the Global Burden of Disease 2010 project and for international reporting purposes, we estimated annual trends in the world population using solid fuels. We developed a multilevel model based on national survey data on primary cooking fuel. The proportion of households relying mainly on solid fuels for cooking has decreased from 62% (95% CI: 58, 66%) to 41% (95% CI: 37, 44%) between 1980 and 2010. Yet because of population growth, the actual number of persons exposed has remained stable at around 2.8 billion during three decades. Solid fuel use is most prevalent in Africa and Southeast Asia where > 60% of households cook with solid fuels. In other regions, primary solid fuel use ranges from 46% in the Western Pacific, to 35% in the Eastern Mediterranean and < 20% in the Americas and Europe. Multilevel modeling is a suitable technique for deriving reliable solid-fuel use estimates. Worldwide, the proportion of households cooking mainly with solid fuels is decreasing. The absolute number of persons using solid fuels, however, has remained steady globally and is increasing in some regions. Surveys require enhancement to better capture the health implications of new technologies and multiple fuel use.

Annette Prüss-Ustün and colleagues consider the role of air pollution and other environmental risks in non-communicable diseases and actions to reduce them

Zeenah Haddad and colleagues call for an expansion of data on household energy use routinely collected through national surveys to gauge the health effects by gender