Lara Stucki, Staffan Betnér, Jenny Selander, M. Lõhmus, A. Åkesson, C. Eriksson
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Generalized estimating equations were used to compute beta-coefficients (β) and 95% confidence intervals (95% CI) for associations between sociodemographic and lifestyle variables and spatial-temporal modeled particulate matter (PM2.5, PM10), nitrogen dioxide (NO2), road traffic noise and greenness. All models were additionally stratified by urbanization type. Results: Urban area residency was the most important predictor of high exposure to air pollution and noise, and to low greenness. For instance, β for NO2 was −2.92 (95% CI = −3.00, −2.83) and −3.10 (95% CI = −3.18, −3.01) µg/m3 in suburban and rural areas, respectively, compared with urban areas. For greenness, the opposite held true with corresponding β of 0.059 (95% CI = 0.056, 0.062) and 0.095 (95% CI = 0.092, 0.098). Within urban areas, elderly, unmarried and well-educated women had the highest environmental burden. However, less pronounced, and even reversed associations were found in suburban and rural areas. Conclusion: This study provides evidence of a mixed pattern of environmental health inequalities across sociodemographic groups in urban areas.","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":null,"pages":null},"PeriodicalIF":3.3000,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sociodemographic inequalities in long-term exposure to air pollution, road traffic noise, and greenness: A population-based cohort study of women\",\"authors\":\"Lara Stucki, Staffan Betnér, Jenny Selander, M. Lõhmus, A. Åkesson, C. Eriksson\",\"doi\":\"10.1097/EE9.0000000000000279\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: Recent evidence suggests environmental health inequalities both within and between European countries and socially deprived groups may be more susceptible to pollution. However, evidence is still inconclusive and additional studies are warranted. This study aims to investigate sociodemographic inequalities in long-term residential exposure to air pollution, road traffic noise, and greenness, taking lifestyle and degree of urbanization into account. Methods: In total 20,407 women, born 1914–48 residing in Uppsala County, Sweden, were followed between 1997 and 2017. Time-varying sociodemographic variables were obtained from registers, and questionnaires provided lifestyle information. Generalized estimating equations were used to compute beta-coefficients (β) and 95% confidence intervals (95% CI) for associations between sociodemographic and lifestyle variables and spatial-temporal modeled particulate matter (PM2.5, PM10), nitrogen dioxide (NO2), road traffic noise and greenness. All models were additionally stratified by urbanization type. Results: Urban area residency was the most important predictor of high exposure to air pollution and noise, and to low greenness. For instance, β for NO2 was −2.92 (95% CI = −3.00, −2.83) and −3.10 (95% CI = −3.18, −3.01) µg/m3 in suburban and rural areas, respectively, compared with urban areas. For greenness, the opposite held true with corresponding β of 0.059 (95% CI = 0.056, 0.062) and 0.095 (95% CI = 0.092, 0.098). Within urban areas, elderly, unmarried and well-educated women had the highest environmental burden. However, less pronounced, and even reversed associations were found in suburban and rural areas. 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引用次数: 0
摘要
背景:最近的证据表明,欧洲国家内部和国家之间以及社会贫困群体之间的环境卫生不平等可能更容易受到污染的影响。然而,证据仍然不确定,需要进一步的研究。本研究的目的是在考虑生活方式和城市化程度的情况下,调查长期居住暴露于空气污染、道路交通噪音和绿化方面的社会人口不平等。方法:在1997年至2017年期间,共有20,407名女性,出生于1914 - 1948年,居住在瑞典乌普萨拉县。随时间变化的社会人口变量从登记册中获得,调查问卷提供生活方式信息。使用广义估计方程计算社会人口学和生活方式变量与时空模拟颗粒物(PM2.5、PM10)、二氧化氮(NO2)、道路交通噪声和绿化之间的关联的β系数(β)和95%置信区间(95% CI)。所有模型均按城市化类型进行分层。结果:城区居住是空气污染和噪声高暴露和绿化低的最重要预测因子。例如,与城市地区相比,郊区和农村地区NO2的β分别为- 2.92 (95% CI = - 3.00, - 2.83)和- 3.10 (95% CI = - 3.18, - 3.01)µg/m3。对于绿色,相反的情况是正确的,相应的β为0.059 (95% CI = 0.056, 0.062)和0.095 (95% CI = 0.092, 0.098)。在城市地区,老年、未婚和受过良好教育的妇女的环境负担最重。然而,在郊区和农村地区发现的关联不那么明显,甚至是相反的。结论:本研究提供了城市地区不同社会人口群体环境卫生不平等混合模式的证据。
Sociodemographic inequalities in long-term exposure to air pollution, road traffic noise, and greenness: A population-based cohort study of women
Background: Recent evidence suggests environmental health inequalities both within and between European countries and socially deprived groups may be more susceptible to pollution. However, evidence is still inconclusive and additional studies are warranted. This study aims to investigate sociodemographic inequalities in long-term residential exposure to air pollution, road traffic noise, and greenness, taking lifestyle and degree of urbanization into account. Methods: In total 20,407 women, born 1914–48 residing in Uppsala County, Sweden, were followed between 1997 and 2017. Time-varying sociodemographic variables were obtained from registers, and questionnaires provided lifestyle information. Generalized estimating equations were used to compute beta-coefficients (β) and 95% confidence intervals (95% CI) for associations between sociodemographic and lifestyle variables and spatial-temporal modeled particulate matter (PM2.5, PM10), nitrogen dioxide (NO2), road traffic noise and greenness. All models were additionally stratified by urbanization type. Results: Urban area residency was the most important predictor of high exposure to air pollution and noise, and to low greenness. For instance, β for NO2 was −2.92 (95% CI = −3.00, −2.83) and −3.10 (95% CI = −3.18, −3.01) µg/m3 in suburban and rural areas, respectively, compared with urban areas. For greenness, the opposite held true with corresponding β of 0.059 (95% CI = 0.056, 0.062) and 0.095 (95% CI = 0.092, 0.098). Within urban areas, elderly, unmarried and well-educated women had the highest environmental burden. However, less pronounced, and even reversed associations were found in suburban and rural areas. Conclusion: This study provides evidence of a mixed pattern of environmental health inequalities across sociodemographic groups in urban areas.