Evidence map›Paper›PMID 39350136›Full record

ArticleBMC public health2024

Diurnal temperature range and hypertension: cross-sectional and longitudinal findings from the China Health and Retirement Longitudinal Study (CHARLS).

Tiange Yan, Qilin Song, Ming Yao, Xingyuan Zhang, Yaxiong He

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Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Tiange Yan *Department of Cardiology, Renmin Hospital of Xiangzhou District, Xiangyang City, China.
Qilin Song *Department of Cardiology, Renmin Hospital of Xiangzhou District, Xiangyang City, China.
Ming YaoState Key Laboratory of New Drug Discovery and Development for Major Diseases, Gannan Medical University, Ganzhou, China.
Xingyuan ZhangSchool of Basic Medical Sciences, Wuhan University, 115 Donghu Road, Wuhan, 430060, China. 2019203010073@whu.edu.cn.
Yaxiong HeDepartment of Cardiology, Renmin Hospital of Xiangzhou District, Xiangyang City, China. heyaxiong200901@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundResearch indicates a positive association between short-term diurnal temperature range (DTR) exposure and hypertension. However, the impact of long-term DTR exposure has not been thoroughly studied in population-based cohort research.

methodsThis study conducted cross-sectional (including 16,690 participants) and longitudinal analyses (including 9,650 participants) based on the China Health and Retirement Longitudinal Study (CHARLS). Daily temperature data was sourced from the National Scientific Data of the Qinghai-Tibet Plateau. We calculated the moving average of DTR exposure of all the participants in CHARLS with exposure windows of 30-day, 60-day, 180-day, 1-year, and 2-year before the interview month of CHARLS Wave1 (2011). Logistic regression and age-stratified Cox proportional hazards models were employed in our analysis.

resultsIn the cross-sectional study, 6,572 (39.4%) participants had hypertension. We found higher DTR is associated with a higher prevalence of hypertension across different exposure windows. The effect was strongest when the exposure window of DTR was 180-day, with an adjusted odds ratio (OR) of 1.261 (95% confidence interval (CI): 1.124-1.416 [highest tertile DTR vs. lowest tertile DTR]). In the cohort study, 3,020 (31.3%) participants developed hypertension during 83 months of follow-up. A higher level of DTR (hazard ratio (HR): 1.224, 95% CI: 1.077-1.391) was associated with a higher risk of incident hypertension. We found significant interactions between DTR and age (P interaction: <0.001) and residence (P interaction: 0.045).

conclusionWe found significant positive associations between DTR and prevalent and incident hypertension. Individuals younger than 65 and those living in rural areas are at an elevated risk of developing hypertension due to DTR.

Indexed as

Environmental ExposureHypertensionRetirementSurveys and QuestionnairesTemperatureAgedChinaCross-Sectional StudiesDisease SusceptibilityFemaleHumansIncidenceLogistic ModelsLongitudinal StudiesMaleMiddle AgedDiurnal temperature rangeHypertensionIncidencePrevalence

Identifiers

PMID39350136
PMCPMC11440652

What Socratic holds

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LicenceCC BY-NC-ND
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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.