在两个快速转型的土著居民中,建筑环境比生活方式的其他方面更能预测心脏代谢健康状况

Marina Watowich, Audrey M Arner, Selina Wang, Echwa John, John C Kahumbu, Patricia Kinyua, Anjelina Lopurudoi, Francis Lotukoi, Charles M Mwai, Benjamin Muhoya, Boniface Mukoma, Kar Lye Tam Tam, Tan Bee Ting A/P Tan Boon Huat, Michael Gurven, Yvonne AL Lim, Dino Martins, Sospeter Njeru, Ng Kee Seong, Vivek V Venkataraman, Ian J Wallace, Julien F Ayroles, Thomas S Kraft, Amanda J Lea
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引用次数: 0

摘要

背景:世界各地许多仅能维持生存的社会和土著社会正在迅速经历城市化、营养转型和融入市场经济,导致心脏代谢疾病明显增加。确定改变健康状况的最有力和最普遍的驱动因素,对于识别脆弱社区和制定有效政策以应对不同社会环境下慢性病风险的增加至关重要。然而,关于不同生活方式特征如何影响正在经历生活方式转变的人群健康的比较测试仍然很少见,这需要在不同背景下收集可比较的、综合的人类学和健康数据:方法:我们制定了九个量表来量化生活方式的不同方面(如城市基础设施、市场一体化、文化适应),这九个量表针对的是两个土著居民,他们目前正处于自给自足的转型期,在非常不同的生态和社会政治背景下经历着快速的变化:他们分别是肯尼亚西北部的图尔卡纳牧民(n = 3,692)和马来西亚半岛的奥朗阿斯利混合生计群体(n = 688)。我们测试了这些生活方式量表对 16 项心脏代谢健康指标的预测程度,并比较了每个量表在两个人群中的通用性。我们使用因子分析将全面的生活方式数据分解为无监督的突出轴,使用敏感性分析了解多维量表中哪些成分最重要,使用性别分层分析了解生活方式变化的各个方面如何对男性和女性的心脏代谢健康产生不同影响:与包含饮食、流动性或文化适应性的指标相比,量化城市基础设施和市场衍生物质财富的指标对心脏代谢健康的预测效果最好,而且这些结果在不同人群和性别中高度一致。因子分析结果在图尔卡纳人和奥朗阿斯利人之间也高度一致,并揭示了生活方式的变化可分解为两个不同的轴--建筑环境和饮食--这两个轴的变化速度不同,与健康的关系也不同:我们对东非和东南亚土著居民的可比数据进行了分析,发现了令人惊讶的普遍性:在这两种情况下,与饮食等看似更接近健康的生活方式的其他方面相比,当地基础设施和建筑环境的衡量标准始终更能预测心脏代谢健康。我们假设,这是因为建筑环境影响着未测量的近似驱动因素,如体育锻炼、压力增加和更广泛地获得市场商品,并可作为社区融入市场时间长短的替代物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The built environment is more predictive of cardiometabolic health than other aspects of lifestyle in two rapidly transitioning Indigenous populations
Background: Many subsistence-level and Indigenous societies around the world are rapidly experiencing urbanization, nutrition transition, and integration into market-economies, resulting in marked increases in cardiometabolic diseases. Determining the most potent and generalized drivers of changing health is essential for identifying vulnerable communities and creating effective policies to combat increased chronic disease risk across socio-environmental contexts. However, comparative tests of how different lifestyle features affect the health of populations undergoing lifestyle transitions remain rare, and require comparable, integrated anthropological and health data collected in diverse contexts. Methods: We developed nine scales to quantify different facets of lifestyle (e.g., urban infrastructure, market-integration, acculturation) in two Indigenous, transitioning subsistence populations currently undergoing rapid change in very different ecological and sociopolitical contexts: Turkana pastoralists of northwest Kenya (n = 3,692) and Orang Asli mixed subsistence groups of Peninsular Malaysia (n = 688). We tested the extent to which these lifestyle scales predicted 16 measures of cardiometabolic health and compared the generalizability of each scale across the two populations. We used factor analysis to decompose comprehensive lifestyle data into salient axes without supervision, sensitivity analyses to understand which components of the multidimensional scales were most important, and sex-stratified analyses to understand how facets of lifestyle variation differentially impacted cardiometabolic health among males and females. Findings: Cardiometabolic health was best predicted by measures that quantified urban infrastructure and market-derived material wealth compared to metrics encompassing diet, mobility, or acculturation, and these results were highly consistent across both populations and sexes. Factor analysis results were also highly consistent between the Turkana and Orang Asli and revealed that lifestyle variation decomposes into two distinct axes-the built environment and diet-which change at different paces and have different relationships with health. Interpretation: Our analysis of comparable data from Indigenous peoples in East Africa and Southeast Asia revealed a surprising amount of generalizability: in both contexts, measures of local infrastructure and built environment are consistently more predictive of cardiometabolic health than other facets of lifestyle that are seemingly more proximate to health, such as diet. We hypothesize that this is because the built environment impacts unmeasured proximate drivers like physical activity, increased stress, and broader access to market goods, and serves as a proxy for the duration of time that communities have been market-integrated.
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