危地马拉、印度、秘鲁和卢旺达农村地区妇女身体质量指数与家庭空气污染的暴露-反应关系:家庭空气污染干预网络试验

IF 3.6 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Adolphe Ndikubwimana, William Checkley, Yunyun Chen, Thomas Clasen, Carmen Lucía Contreras, Anaite Diaz-Artiga, Ephrem Dusabimana, Lisa de Las Fuentes, Shirin Jabbarzadeh, Michael Johnson, Egide Kalisa, Patrick Karakwende, Miles Kirby, Amy E Lovvorn, John P McCracken, Florien Ndagijimana, Theoneste Ntakirutimana, Jean Dieu Ntivuguruzwa, Jennifer L Peel, Ajay Pillarisetti, Victor G Dávila-Román, Ghislaine Rosa, Sarada S Garg, Lisa Thompson, Lance A Waller, Jiantong Wang, Maggie L Clark, Bonnie N Young
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引用次数: 0

摘要

背景:燃烧生物质材料(低收入和中等收入国家的主要烹饪燃料)造成的家庭空气污染可能与代谢功能障碍有关。我们评估了家庭空气污染与身体质量指数(BMI)之间的横断面关联,期望看到污染浓度越高,BMI越高。方法:我们分析了414名年龄在40至79岁之间的妇女的数据,她们居住在使用生物质燃料的家庭中,并参加了多国家庭空气污染干预网络(HAPIN)试验。我们通过调整潜在混杂因素(即年龄、社会经济指标、教育程度、饮食多样性、二手烟暴露、酒精和粮食消费)的单一污染物线性和logistic模型,探讨了24小时个人平均暴露于细颗粒物(PM2.5)、黑碳(BC)和一氧化碳(CO)与BMI的关系。敏感性分析将空气污染物作为四分位数,将其他变量作为潜在的混杂因素,如体育活动、登记地点和饮食项目。我们考察了研究地点对关联的影响。结果:我们在线性回归中观察到家庭空气污染与BMI之间存在混合关联的证据。与BMI和PM 2没有关联。₅(对数变换PM₂增加1单位。₅估计为0.02 kg/m2 [95% CI: -0.51, 0.54])或CO(对数变换CO增加1个单位估计为0.42 kg/m2 [95% CI -0.31, 1.14])。然而,log-transformed BC增加1个单位显示了与假设相反方向的关联(BC估计为-0.59 kg/m2 [95% CI -1.17, -0.003])。使用逻辑回归模型,我们发现只有CO显著增加超重/肥胖的几率:对数转换后的CO每增加1个单位,其比值比为1.66 (95% CI: 1.10, 2.51)。在秘鲁,效应修正显示BC暴露与BMI呈负相关。结论:有证据表明,CO暴露与超重/肥胖几率增加之间存在显著关联,而PM2.5和BC对BMI的影响为零或呈负相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exposure-response relationship of household air pollution on body mass index among women in rural areas of Guatemala, India, Peru and Rwanda: household air pollution intervention network trial.

Background: Household air pollution from burning biomass materials, the main cooking fuel in low- and middle-income countries, may be linked to metabolic dysfunction. We assessed cross-sectional associations between household air pollution and body mass index (BMI), expecting to see increased BMI with higher pollution concentrations.

Methods: We analyzed data from 414 women aged 40 to 79 years who resided in the households using biomass fuel and were enrolled in the multi-country Household Air Pollution Intervention Network (HAPIN) Trial. We explored associations of 24-h average personal exposure to fine particulate matter (PM2.5), black carbon (BC), and carbon monoxide (CO) with BMI through single pollutant linear and logistic models adjusted for potential confounders (i.e., age, socioeconomic indicators, education, dietary diversity, secondhand smoke exposure, alcohol and grain consumption).Sensitivity analyses explored air pollutants as quartiles, and other variables as potential confounders, such as physical activity, enrollment site, and dietary items. We examined effect modification of research site on the associations.

Results: We observed mixed evidence of associations between household air pollution and BMI in linear regression. There was no association with BMI and PM₂.₅ (1-unit increase in log-transformed PM₂.₅ estimate 0.02 kg/m2 [95% CI: -0.51, 0.54]) or CO (1-unit increase in log-transformed CO estimate 0.42 kg/m2 [95% CI -0.31, 1.14]). However, a 1-unit increase in log-transformed BC showed an association in the opposite direction as hypothesized (BC estimate -0.59 kg/m2 [95% CI -1.17, -0.003]). Using logistic regression models, we found that only CO significantly increased the odds of overweight/obesity: a 1-unit increase in log-transformed CO led to an odds ratio of 1.66 (95% CI: 1.10, 2.51). Effect modification showed inverse association between BC exposure and BMI in Peru.

Conclusions: Evidence suggests a significant association between CO exposure and increased odds of being overweight/obese, whereas impacts of PM2.5 and BC on BMI had null or inverse effects.

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来源期刊
BMC Public Health
BMC Public Health 医学-公共卫生、环境卫生与职业卫生
CiteScore
6.50
自引率
4.40%
发文量
2108
审稿时长
1 months
期刊介绍: BMC Public Health is an open access, peer-reviewed journal that considers articles on the epidemiology of disease and the understanding of all aspects of public health. The journal has a special focus on the social determinants of health, the environmental, behavioral, and occupational correlates of health and disease, and the impact of health policies, practices and interventions on the community.
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