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Record W4284988244 · doi:10.1016/s2542-5196(22)00122-x

Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM2·5 air pollution, 1990–2019: an analysis of data from the Global Burden of Disease Study 2019

2022· article· en· W4284988244 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Lancet Planetary Health · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsnot available
FundersDaiichi Sankyo EuropeFaculty of Medicine and Health, University of SydneyCentre for Heart Rhythm Disorders, University of AdelaideInstituto de Salud Carlos IIIMenzies Centre for Australian Studies, King's College London, University of LondonMedical Research CouncilUniversidad de Ciencias Aplicadas y AmbientalesGeorge Institute for Global HealthWestern Sydney UniversityCentral University of KeralaUniversity Of Nigeria NsukkaNational Center of Neurology and PsychiatryWuhan UniversityUniversitair Medisch Centrum GroningenNovo NordiskLa Trobe UniversityGeorg-August-Universität GöttingenIdorsia PharmaceuticalsWuhan University of Science and TechnologyInstitute for Health Metrics and EvaluationKosin UniversityAlborz University of Medical SciencesAin Shams UniversityInternational Centre for Diarrhoeal Disease Research, BangladeshDanoneRijksuniversiteit GroningenNanyang Technological UniversityNational Institute for Health and Care ResearchChest Research FoundationSwedish Orphan BiovitrumAstellas PharmaFresenius Medical Care North AmericaAmerican Association for the Study of Liver DiseasesIran University of Medical SciencesSociety for Surgery of the Alimentary TractMcMaster UniversityUniversitat de ValènciaUniversity College LondonWellcome TrustNational Institutes of HealthUniversity of HullLilly DeutschlandFederation University AustraliaBill and Melinda Gates FoundationUniversity of WashingtonMashhad University of Medical SciencesUniversità di BolognaAstraZenecaLee Kong Chian School of Medicine, Nanyang Technological UniversityAmarin CorporationUniversity of New South WalesAlexion PharmaceuticalsKing Saud UniversityTeva Pharmaceutical IndustriesKing's College LondonAmicus TherapeuticsDepartment of Biotechnology, Ministry of Science and Technology, IndiaCase Western Reserve UniversitySanofiUniversity of Central FloridaGlaxoSmithKlineShahid Beheshti University of Medical SciencesNovartis PharmaUniwersytet Jagielloński Collegium MedicumEli Lilly and CompanyTaipei Medical UniversityInternational Society for Infectious DiseasesUniversitas Negeri SemarangAmgen
KeywordsAttributable riskMedicineEnvironmental healthType 2 diabetesPopulationIncidence (geometry)Relative riskDisease burdenConfidence intervalDemographyAir pollutionEpidemiologyCohort studyDiabetes mellitusInternal medicineMathematics

Abstract

fetched live from OpenAlex

Background Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM 2·5 originating from ambient and household air pollution. Methods We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM 2·5 ) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM 2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM 2·5 -attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. Findings In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM 2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South America. Since 1990, the attributable burden has increased by 50%, driven largely by population growth and ageing. Globally, the impact of reductions in household air pollution was largely offset by increased ambient PM 2·5 . Interpretation Air pollution is a major risk factor for diabetes. We estimated that about a fifth of the global burden of type 2 diabetes is attributable PM 2·5 pollution. Air pollution mitigation therefore might have an essential role in reducing the global disease burden resulting from type 2 diabetes. Funding Bill & Melinda Gates Foundation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.209
Threshold uncertainty score0.787

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.054
GPT teacher head0.334
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it