Evidence map›Paper›PMID 38822317›Full record

ArticleBMC public health2024

Household air pollution and urinary incontinence symptoms among older adults in LASI: a large-scale population-based study.

Xiaoyang Liu, Kai Ma, Shengzhuo Liu, Pan Song, Luchen Yang, Zhenghuan Liu, Jing Zhou, Linchun Wang, Xin Yan, Yunfei Yu and 1 more

Abstract read
In one paragraph

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 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Association between long-term PMBMC public health · 2026
    Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

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

11 authors.

Xiaoyang LiuDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.
Kai MaDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.
Shengzhuo LiuDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.
Pan SongDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.
Luchen YangDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.
Zhenghuan LiuDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.
Jing ZhouDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.
Linchun WangDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.
Xin YanDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.
Yunfei YuDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.
Qiang DongDepartment of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China. dongqiang@scu.edu.cn.

Funding

Integrting Information About Aging SurveysR01AG030153 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Sara Adar, Alden L. Gross · 2007 to 2026
$41.7M
Mega Meta Data Set of the Health and Retirement Surveys Around the WorldRC2AG036619 · NIA · RAND CORPORATION · PI KAPTEYN, ARIE · 2009 to 2010
$2.0M
Archiving & Creating User Friendly Data: the Longitudinal Aging Survey in IndiaR03AG043052 · NIA · RAND CORPORATION · PI LEE, JINKOOK · 2012 to 2012
$95k
National Key Research and Development Program of China 2021YFC2009304NIA NIH HHS R01 AG030153NIA NIH HHS R03 AG043052NIA NIH HHS RC2 AG036619Project of Science and Technology Department of Sichuan Province 2021YFS0117
6 · The paper itself

Abstract

backgroundThe effects of household air pollution on urinary incontinence (UI) symptoms and stress urinary incontinence (SUI) symptoms have not been studied. This study seeks to investigate the correlation between household air pollution and UI/SUI symptoms among middle-aged and elderly adults in India.

methodsWe employed data derived from individuals aged 45 years and older who participated in the inaugural wave (2017-2018) of the Longitudinal Aging Study in India (LASI). The assessment of household air pollution exposure and the occurrence of UI/SUI symptoms relied on self-reported data. The analytical approach adopted was cross-sectional in nature and encompassed a cohort of 64,398 participants. To explore relationships, we utilized multivariate logistic regression analysis, incorporating subgroup analysis and interaction tests.

results1,671 (2.59%) participants reported UI symptoms and 4,862 (7.55%) participants reported SUI symptoms. Also, the prevalence of UI/SUI symptoms is much higher among middle-aged and elderly adults who use solid polluting fuels (UI: 51.23% vs. 48.77%; SUI: 54.50% vs. 45.50%). The results revealed a noteworthy correlation between household air pollution and the probability of experiencing UI/SUI symptoms, persisting even after adjusting for all conceivable confounding variables (UI: OR = 1.552, 95% CI: 1.377-1.749, p < 0.00001; SUI: OR: 1.459, 95% CI: 1.357-1.568, p < 0.00001). Moreover, significant interaction effects were discerned for age, education level, tobacco consumption, alcohol consumption, and physical activity (p for interaction < 0.05).

conclusionsThe results of our study indicate that the utilization of solid fuels in the home increases the likelihood of developing urinary incontinence and stress urinary incontinence. As a result, we argue that there is an immediate need to reform the composition of cooking fuel and raise public awareness about the adverse effects of air pollution in the home.

Indexed as

Air Pollution, IndoorAgedCross-Sectional StudiesEnvironmental ExposureFemaleHumansIndiaLongitudinal StudiesMaleMiddle AgedPrevalenceUrinary IncontinenceUrinary Incontinence, StressIndiaIndoor pollutionSolid fuel useUrinary incontinence

Identifiers

PMID38822317
PMCPMC11143701

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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 OpenQuestion graph.