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Enregistrement W2560796017 · doi:10.1016/s0140-6736(16)32506-5

Household energy and health: where next for research and practice?

2016· letter· en· W2560796017 sur OpenAlexaff
Majid Ezzati, Jill Baumgartner

Notice bibliographique

RevueThe Lancet · 2016
Typeletter
Langueen
DomaineEnvironmental Science
ThématiqueEnergy and Environment Impacts
Établissements canadiensMcGill University
Organismes subventionnairesMedical Research CouncilSanofiWellcome TrustGlaxoSmithKlineAstraZeneca
Mots-clésEnvironmental healthMedicine

Résumé

récupéré en direct d'OpenAlex

Cooking and home heating with coal and biomass fuels (wood, crop residues, animal dung, and charcoal) are ideal subjects for well intentioned epidemiology. Cooking and heating with such fuels generate large amounts of pollutants that can harm people's health throughout the lifecourse, a risk that largely affects poor communities. In a simple world, epidemiology would investigate the hazardous effects and test the benefits of any interventions, and rational individuals and policy bodies would use this information to initiate positive change. The world, however, is not simple when we study something as central to daily life as household energy. In the 1970s, an Australian respiratory epidemiologist studying adult lung disease in Papua New Guinea documented the positive association between domestic woodsmoke and children's respiratory infections.1Anderson HR Respiratory abnormalities in Papua New Guinea children: the effects of locality and domestic wood smoke pollution.Int J Epidemiol. 1978; 7: 63-72Crossref PubMed Scopus (59) Google Scholar Subsequent studies documented the hazardous role of smoke from biomass and coal in the development of childhood pneumonia and other adverse clinical outcomes. Using this early evidence, the Comparative Risk Assessment Study2Ezzati M Lopez AD Rodgers A Vander Hoorn S Murray CJ Selected major risk factors and global and regional burden of disease.Lancet. 2002; 360: 1347-1360Summary Full Text Full Text PDF PubMed Scopus (2800) Google Scholar attributed 1·6 million annual deaths to biomass and coal use in the early 2000s (attributable deaths [with inclusion of other outcomes] have since been estimated at about 3·5 million).3Lim SS Theo Vos T Flaxman AD et al.A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010.Lancet. 2012; 380: 2224-2260Summary Full Text Full Text PDF PubMed Scopus (8582) Google Scholar In the late 1990s and early 2000s, two directions were advocated for epidemiological research on so-called household air pollution to help develop appropriate public health and policy responses: observational research with measurement of personal exposure to better characterise the exposure–response relationship, which would then be used to determine pollution reductions needed to achieve health benefits;4Ezzati M Kammen DM The health impacts of exposure to indoor air pollution from solid fuels in developing countries: knowledge, gaps, and data needs.Environ Health Perspect. 2002; 110: 1057-1068Crossref PubMed Scopus (337) Google Scholar, 5Ezzati M Kammen D Indoor air pollution from biomass combustion and acute respiratory infections in Kenya: an exposure-response study.Lancet. 2001; 358: 619-624Summary Full Text Full Text PDF PubMed Scopus (364) Google Scholar and randomised trials free of confounding to measure the pure intervention effects.6Smith KR McCracken JP Weber MW et al.Effect of reduction in household air pollution on childhood pneumonia in Guatemala (RESPIRE): a randomised controlled trial.Lancet. 2011; 378: 1717-1726Summary Full Text Full Text PDF PubMed Scopus (395) Google Scholar Over the past two decades, neither type of research has been as informative as hoped. Exposure–response studies have been limited by the difficulties in measuring personal exposure to pollutants. Trials have so far not implemented interventions that substantially reduce exposure while functionally replacing the traditional biomass and coal stoves, and are scalable in a community setting. In The Lancet, Kevin Mortimer and colleagues7Mortimer K Ndamala CB Naunje AW et al.A cleaner burning biomass-fuelled cookstove intervention to prevent pneumonia in children under 5 years old in rural Malawi (the Cooking and Pneumonia Study): a cluster randomised controlled trial.Lancet. 2016; (published online Dec 6.)http://dx.doi.org/10.1016/S0140-6736(16)32507-7PubMed Google Scholar report the Cooking and Pneumonia Study (CAPS) cluster randomised controlled trial done in two rural districts of Malawi. CAPS tested an alternative biomass stove, comparing it with existing cooking methods (typically open fires). Each household in the intervention group received two stoves (both Philips HD4012LS), a solar panel, and user training, while the control group continued to use their existing cooking method. New stoves were repaired and replaced as needed, with 13 192 repairs or replacements for stoves (3·1 per intervention household) and 5259 (1·2 per intervention household) for solar panels. By the second year of the follow-up, the subset of stoves that were objectively monitored were used for only 0·34 cooking events per day. The primary outcome was WHO Integrated Management of Childhood Illness (IMCI)-defined pneumonia episodes diagnosed through routine visits to local health facilities. The stove intervention had no effect on the primary outcome (the facility-diagnosed IMCI pneumonia incidence rate in the intervention group was 15·76 [95% CI 14·89–16·63] per 100 child-years and in the control group 15·58 [14·72–16·45] per 100 child-years; intervention vs control group incidence rate ratio [IRR] of 1·01 [0·91–1·13]; p=0·80). There was a borderline significant increase in the risk of severe pneumonia in the intervention group (intervention vs control group IRR for severe pneumonia episodes was 1·30 [95% CI 0·99–1·71]; p=0·06). The strength of CAPS is its large sample size with 10 750 children from 8626 households across 150 clusters enrolled, and 10 543 children from 8470 households contributing 15 991 child-years of follow-up data to the intention-to-treat analysis. CAPS also has disadvantages, such as a reliance on health facilities for identifying pneumonia cases instead of active case finding used in previous studies,5Ezzati M Kammen D Indoor air pollution from biomass combustion and acute respiratory infections in Kenya: an exposure-response study.Lancet. 2001; 358: 619-624Summary Full Text Full Text PDF PubMed Scopus (364) Google Scholar, 6Smith KR McCracken JP Weber MW et al.Effect of reduction in household air pollution on childhood pneumonia in Guatemala (RESPIRE): a randomised controlled trial.Lancet. 2011; 378: 1717-1726Summary Full Text Full Text PDF PubMed Scopus (395) Google Scholar and not reporting information about impacts on home concentrations and personal exposure to pollutants, and on pathogen-specific pneumonia, both of which were presented in the earlier RESPIRE trial.6Smith KR McCracken JP Weber MW et al.Effect of reduction in household air pollution on childhood pneumonia in Guatemala (RESPIRE): a randomised controlled trial.Lancet. 2011; 378: 1717-1726Summary Full Text Full Text PDF PubMed Scopus (395) Google Scholar, 8Smith KR McCracken JP Thompson L et al.Personal child and mother carbon monoxide exposures and kitchen levels: methods and results from a randomized trial of woodfired chimney cookstoves in Guatemala (RESPIRE).J Expo Sci Environ Epidemiol. 2010; 20: 406-416Crossref PubMed Scopus (112) Google Scholar This information is needed to understand the reasons for null effect and to inform intervention choices (ie, no or insufficient reduction in pollution or personal exposure vs absence of an aetiological relationship between exposure and pneumonia). Largely overlooked in the CAPS trial, as well as in many epidemiological studies on household energy, are other insights and contexts highlighted by scholarly work in energy policy and social sciences: the macroeconomic (fuel prices and their variability) and infrastructure (reliability of supply of any specific form of energy) factors that, together with personal preferences, influence the choice of household energy sources and energy use behaviours.4Ezzati M Kammen DM The health impacts of exposure to indoor air pollution from solid fuels in developing countries: knowledge, gaps, and data needs.Environ Health Perspect. 2002; 110: 1057-1068Crossref PubMed Scopus (337) Google Scholar, 9Agarwal B Diffusion of rural innovations: some analytical issues and the case of wood-burning stoves.World Dev. 1983; 11: 359-376Crossref Scopus (82) Google Scholar These works, including evaluations of large-scale stove programmes, have overwhelmingly found that laboratory tests of stoves—the basis for selecting the specific intervention used in the CAPS trial—have little relation to their actual performance in community settings, with the community effectiveness often substantially worse than the laboratory results and, at times, than the traditional stoves.9Agarwal B Diffusion of rural innovations: some analytical issues and the case of wood-burning stoves.World Dev. 1983; 11: 359-376Crossref Scopus (82) Google Scholar, 10Sinton J Smith K Peabody J et al.An assessment of programs to promote improved household stoves in China.Energy Sustain Dev. 2004; 8: 33-52Crossref Scopus (176) Google Scholar, 11Manibog FR Improved cooking stoves in developing countries: problems and opportunities.Ann Rev Energy. 1984; 9: 199-227Crossref Scopus (68) Google Scholar, 12Zhou Z Jin Y Liu F et al.Community effectiveness of stove and health education interventions for reducing exposure to indoor air pollution from solid fuels in four Chinese provinces.Environ Res Lett. 2006; 1: 014010Crossref Scopus (16) Google Scholar Taken in the context of this body of work, the lack of impact, lack of regular use, and frequent malfunctioning of the stove used in CAPS could have been anticipated, and probably would have been revealed in field testing of the intervention stove at much lower cost than the trial. What should the scientific and policy communities do to avoid ad-hoc trials and intervention delivery programmes related to household energy that provide little benefit to the intended beneficiaries and limited policy guidance? First, at the most basic level, practitioners, researchers, funders, and ethics committees need to develop rigorous processes and criteria for testing household energy interventions in the community setting before clinical outcome studies are done—in the same way that a clinical trial of a vaccine, medication, or food product is unlikely to proceed without layers of efficacy and safety testing beyond laboratory tests, simply because these items are promoted by non-governmental organisations. Second, it is increasingly clear that that the above-mentioned macroeconomic, infrastructure, and behavioural factors lead to dynamic use of multiple sources of energy by the same household for different purposes (eg, cooking different foods, boiling water, heating, lighting; figure).13Smith KR In praise of power.Science. 2014; 345: 603Crossref PubMed Scopus (21) Google Scholar Therefore, the basic idea of intervention should become more nuanced, and take into account the community's energy environment, the purposes of energy use, and energy use behaviours. Finally, an increasing share of biomass and coal users live in or near urban centres, and are affected by air pollution from community and regional sources—including other people's fuel use, burning of solid waste, traffic, and industrial emissions—as much as or more than their own fuel use.14Zhou Z Dionisio KL Arku RE et al.Household and community poverty, biomass use, and air pollution in Accra, Ghana.Proc Natl Acad Sci U S A. 2011; 108: 11028-11033Crossref PubMed Scopus (64) Google Scholar, 15Zhou Z Dionisio KL Verissimo TG et al.Chemical characterization and source apportionment of household fine particulate matter in rural, peri-urban, and urban West Africa.Environ Sci Technol. 2014; 48: 1343-1351Crossref PubMed Scopus (36) Google Scholar Regional sources are even an important determinant of air pollution exposure in rural residents.16Huang W Baumgartner J Zhang Y Wang Y Schauer JJ Source apportionment of air pollution exposures of rural Chinese women cooking with biomass fuels.Atmos Environ. 2015; 104: 79-87Crossref Scopus (49) Google Scholar Therefore, interventions that target only household level sources are likely to have limited impact, in the same way that point-of-use water treatment has limited impact on faecal–oral transmission where water is scarce and there is inadequate household and community sanitation.17Curtis V Cairncross S Yonli R Review: domestic hygiene and diarrhoea—pinpointing the problem.Trop Med Int Health. 2000; 5: 22-32Crossref PubMed Scopus (257) Google Scholar All of these factors suggest that the time has come for research and practice to move on from a focus on only stove interventions, and possibly from household-level interventions, and envision more complex, contextualised, and realistic interventions, be it randomised, quasi-randomised, or observational studies, that can inform policy and practice by taking into account the broader macroeconomic, infrastructure, environmental, and behavioural factors, as we see in other areas of public health including air pollution regulation, tobacco control, sanitation, and nutrition. ME reports a charitable grant from the Youth Health Programme of AstraZeneca, outside the submitted work. JCB reports no competing interests. We thank Ther Aung for the photograph used in the Figure. We thank Sumi Mehta for valuable feedback on an earlier draft of this Comment. A cleaner burning biomass-fuelled cookstove intervention to prevent pneumonia in children under 5 years old in rural Malawi (the Cooking and Pneumonia Study): a cluster randomised controlled trialWe found no evidence that an intervention comprising cleaner burning biomass-fuelled cookstoves reduced the risk of pneumonia in young children in rural Malawi. Effective strategies to reduce the adverse health effects of household air pollution are needed. Full-Text PDF Open Access

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,046
Score d'incertitude au seuil0,406

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,235
Tête enseignante GPT0,363
Écart entre enseignants0,128 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations50
Publié2016
Routes d'admission1
Résumé présentoui

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