生活在农村社区的老年人的生物和社会因素对死亡率的影响。

IF 3 Q1 PRIMARY HEALTH CARE
Oscar H Del Brutto, Robertino M Mera, Denisse A Rumbea, Mark J Sedler
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引用次数: 0

摘要

背景:有关偏远地区死亡率增加因素的信息十分有限。本研究旨在估算几个因素对厄瓜多尔农村地区老年人死亡风险的独立作用和共同作用:研究对象选自先前针对研究人群死亡风险因素进行研究的社区老年人。利用广义结构方程模型(GSEM)评估先前的因果假设,重新绘制因果联系,并引入有助于解释独立重要变量与死亡率之间关系的潜在变量:研究对象包括 590 人(平均年龄:67.9 ± 7.3 岁;57% 为女性),随访时间中位数为 8.2 年。死亡率为每 100 人年 3.4 例。我们利用之前研究的独立多变量泊松模型和 Cox 模型建立了一个暂定的因果结构。包含所有变量的 GSEM 显示,年龄、抑郁症状、高社会风险、高空腹血糖、明显中风史和颈围与死亡率直接相关。引入了两个潜变量,一个代表生物因素的影响,另一个代表社会因素对死亡率的影响。社会变量对生物变量的影响很大,而生物变量对死亡率的直接影响最大:结论:研究人群的死亡风险由多种因素造成,其中最重要的是生物因素,而生物因素又受到社会因素的高度影响。高社会风险与生物变量相互作用,对死亡风险起着重要作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Impact of Biological and Social Factors on Mortality in Older Adults Living in Rural Communities.

Background: Information on factors that increase mortality in remote settings is limited. This study aims to estimate the independent and joint role of several factors on mortality risk among older adults living in rural Ecuador.

Methods: Participants were selected from community-dwelling older adults who were included in previous studies targeting mortality risk factors in the study population. Generalized structural equation modeling (GSEM) was utilized to evaluate prior causal assumptions, to redraw causal links, and to introduce latent variables that may help to explain how the independently significant variables are associated with mortality.

Results: The study included 590 individuals (mean age: 67.9 ± 7.3 years; 57% women), followed for a median of 8.2 years. Mortality rate was 3.4 per 100 person-years. Prior work on separate multivariate Poisson and Cox models was used to build a tentative causal construct. A GSEM containing all variables showed that age, symptoms of depression, high social risk, high fasting glucose, a history of overt stroke, and neck circumference were directly associated with mortality. Two latent variables were introduced, 1 representing the impact of biological factors and another, the impact of social factors on mortality. The social variable significantly influenced the biological variable which carried most of the direct effect on mortality.

Conclusions: Several factors contributed to mortality risk in the study population, the most significant being biological factors which are highly influenced by social factors. High social risk interact with biological variables and play an important role in mortality risk.

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来源期刊
CiteScore
4.80
自引率
2.80%
发文量
183
审稿时长
15 weeks
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