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Record W2003090561 · doi:10.1371/journal.pone.0055014

Increased Childhood Mortality and Arsenic in Drinking Water in Matlab, Bangladesh: A Population-Based Cohort Study

2013· article· en· W2003090561 on OpenAlexaff
Mahfuzar Rahman, Nazmul Sohel, Mohammad Yunus, Mahbub Elahi Chowdhury, Samar Kumar Hore, Khalequ Zaman, Abbas Bhuiya, Peter Kim Streatfield

Bibliographic record

VenuePLoS ONE · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicArsenic contamination and mitigation
Canadian institutionsMcMaster University
FundersUniversity of ChicagoStyrelsen för Internationellt UtvecklingssamarbeteWorld Health OrganizationDepartment for International DevelopmentInternational Centre for Diarrhoeal Disease Research, BangladeshUnited States Agency for International Development
KeywordsMedicineHazard ratioConfidence intervalCohort studyCohortPopulationCause of deathDemographyProportional hazards modelInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Arsenic in drinking water was associated with increased risk of all-cause, cancer, and cardiovascular death in adults. However, the extent to which exposure is related to all-cause and deaths from cancer and cardiovascular condition in young age is unknown. Therefore, we prospectively assessed whether long-term and recent arsenic exposures are associated with all-cause and cancer and cardiovascular mortalities in Bangladeshi childhood population. METHODS AND FINDINGS: We assembled a cohort of 58406 children aged 5-18 years from the Health and Demographic Surveillance System of icddrb in Bangladesh and followed during 2003-2010. There were 185 non-accidental deaths registered in-about 0.4 million person-years of observation. We calculated hazard ratios for cause-specific death in relation to exposure at baseline (µg/L), time-weighted lifetime average (µg/L) and cumulative concentration (µg-years/L). After adjusting covariates, hazard ratios (HRs) for all-cause childhood deaths comparing lifetime average exposure 10-50.0, 50.1-150.0, 150.1-300.0 and ≥300.1µg/L were 1.37 (95% confidence interval [CI], 0.74-2.57), 1.44 (95% CI, 0.88-2.38), 1.22 (95% CI, 0.75-1.98) and 1.88 (95% CI, 1.14-3.10) respectively. Significant increased risk was also observed for baseline (P for trend = 0.023) and cumulative exposure categories (P for trend = 0.036). Girls had higher mortality risk compared to boys (HR for girls 1.79, 1.21, 1.64, 2.31; HR for boys 0.52, 0.53, 1.14, 0.99) in relation to baseline exposure. For all cancers and cardiovascular deaths combined, multivariable adjusted HRs amounted to 1.53 (95% CI 0.51-4.57); 1.29 (95% CI 0.43-3.87); 2.18 (95%CI 1.15-4.16) for 10.0-50.0, 50.1-150.0, and ≥150.1, comparing lowest exposure as reference (P for trend = 0.009). Adolescents had higher mortality risk compared to children (HRs = 1.53, 95% CI 1.03-2.28 vs. HRs = 1.30, 95% CI 0.78-2.17). CONCLUSIONS: Arsenic exposure was associated with substantial increased risk of deaths at young age from all-cause, and cancers and cardiovascular conditions. Girls and adolescents (12-18 years) had higher risk compared to boys and child.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.047
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.214
Teacher spread0.197 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations71
Published2013
Admission routes1
Has abstractyes

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