Evidence mapPaperPMID 42528962Full record

ArticleFrontiers in public health2026

Ambient temperature as a proxy indicator for carbon monoxide poisoning risk: deriving exploratory reference points for public health monitoring in Chengdu, China.

Nan Du, Dan Kuang, Xufang Gao, Jingwen Sun, Li Luo, Xiaochen Wang, Cheng Wang, Rong Lu

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Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Nan DuChengdu Center for Disease Control and Prevention (Chengdu Institute of Health Supervision), Chengdu, Sichuan, China.
Dan KuangChengdu Center for Disease Control and Prevention (Chengdu Institute of Health Supervision), Chengdu, Sichuan, China.
Xufang GaoChengdu Center for Disease Control and Prevention (Chengdu Institute of Health Supervision), Chengdu, Sichuan, China.
Jingwen SunChengdu Center for Disease Control and Prevention (Chengdu Institute of Health Supervision), Chengdu, Sichuan, China.
Li LuoChengdu Center for Disease Control and Prevention (Chengdu Institute of Health Supervision), Chengdu, Sichuan, China.
Xiaochen WangChengdu Center for Disease Control and Prevention (Chengdu Institute of Health Supervision), Chengdu, Sichuan, China.
Cheng WangChengdu Center for Disease Control and Prevention (Chengdu Institute of Health Supervision), Chengdu, Sichuan, China.
Rong LuChengdu Center for Disease Control and Prevention (Chengdu Institute of Health Supervision), Chengdu, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Low ambient temperature is associated with increased carbon monoxide (CO) poisoning incidents, likely through behavioral pathways such as heating device use and reduced ventilation. This study examines the association between daily mean temperature and CO poisoning emergency medical service (EMS) responses in Chengdu, explores potential population susceptibility, estimates the attributable burden, and proposes exploratory temperature reference points for public health monitoring. Methods: CO poisoning EMS records from Chengdu (January 1, 2013-December 31, 2025; 4,352 cases across 1,894 days) were matched with daily meteorological and air pollutant data. A time-stratified case-crossover design combined with distributed lag nonlinear models (DLNMs; max lag = 5 days) was employed. Models adjusted for relative humidity, PM Results: A reverse "J"-shaped association was observed, with a cumulative lag 0-5 days minimum morbidity temperature (MMT) of 14.9 °C. Extreme cold (2.9 °C, 2.5th percentile) vs. reference was associated with a cumulative RR of 5.12 (95% CI: 1.74-15.09), peaking at lag 0 (RR = 1.79, 95% CI: 1.47-2.17). Subgroup analyses suggested potential vulnerability among adults aged 20-39 and ≥60 years. Wind speed stratification indicated a 69% higher extreme cold risk on low-wind days (RR ratio = 1.69), though formal interaction testing was non-significant ( Conclusion: Low ambient temperature serves as a measurable proxy indicator for conditions associated with elevated CO poisoning risk in Chengdu. The proposed exploratory temperature reference points (7.3 °C and 6.0 °C) may inform targeted safety messaging during winter, though prospective validation is required before operational implementation in warning systems.

Indexed as

Carbon Monoxide PoisoningPublic HealthTemperatureAdultChinaEmergency Medical ServicesEnvironmental MonitoringFemaleHumansMaleMiddle AgedSeasonscarbon monoxide poisoningChengdudistributed lag nonlinear modelhealth risk communicationrisk reference pointtemperaturetime-stratified case-crossover design

Identifiers

PMID42528962
PMCPMC13415786

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.