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Creation and validation of a polysocial score for mortality among community-dwelling older adults in the USA: the health and retirement study
Age and Ageing ( IF 6.0 ) Pub Date : 2021-08-03 , DOI: 10.1093/ageing/afab174
Yongjing Ping 1 , Michelle C Oddén 2 , Robert S Stawski 3 , Hoda S Abdel Magid 2 , Chenkai Wu 1
Affiliation  

Background the interrelatedness between social determinants of health impedes researchers to identify important social factors for health investment. A new approach is needed to quantify the aggregate effect of social factors and develop person- centred social interventions. Methods participants ([n = 7,383], 54.5% female) were aged 65 years or above who complete an additional psychosocial questionnaire in the health and retirement study in 2006 or 2008. Social determinants of health encompassed five social domains: economic stability, neighbourhood and physical environment, education, community and social context, and healthcare system. We used the forward stepwise logistic regression to derive a polysocial score model for 5-year mortality. Indices of goodness-of-fit, discrimination and reclassification were used to assess model performance. We used logistic regression to identify the association between polysocial score and mortality. Subgroup analyses were conducted to examine sex- and race-specific association. Results polysocial score was created using 14 social determinants of health. In the training cohort, the C-statistic was 0.71 for the reference model (only age, sex and race/ethnicity) and increased to 0.75 for the continuous and categorical polysocial score. Compared with the reference model, the integrated discrimination index for adding the continuous or categorical polysocial score was both 0.03 (P values < 0.001). Participants with an intermediate (odds ratio [OR] = 0.69; 95% confidence interval [CI], 0.51–0.82) or high (OR = 0.48; 95% CI, 0.38–0.60) polysocial score had lower odds of death than those in the low category in the fully adjusted model, respectively. Conclusions the polysocial approach may offer possible solutions to monitor social environments and suggestions for older people to improve their social status for specific health outcomes.

中文翻译:

美国社区老年人死亡率多社会评分的创建和验证:健康和退休研究

背景 健康的社会决定因素之间的相互关联性阻碍了研究人员确定健康投资的重要社会因素。需要一种新的方法来量化社会因素的综合影响并制定以人为本的社会干预措施。方法 参与者([n = 7,383],54.5% 女性)年龄在 65 岁或以上,他们在 2006 年或 2008 年的健康和退休研究中完成了额外的社会心理问卷。健康的社会决定因素包括五个社会领域:经济稳定性、邻里和物理环境、教育、社区和社会环境以及医疗保健系统。我们使用前向逐步逻辑回归推导出 5 年死亡率的多社会评分模型。拟合优度、区分度和重新分类指数用于评估模型性能。我们使用逻辑回归来确定多社会评分与死亡率之间的关联。进行亚组分析以检查性别和种族特异性关联。结果 多元社会评分是使用 14 个健康的社会决定因素创建的。在训练队列中,参考模型(仅年龄、性别和种族/民族)的 C 统计量为 0.71,而连续和分类多社会得分的 C 统计量增加到 0.75。与参考模型相比,添加连续或分类多社会分数的综合辨别指数均为0.03(P值<0.001)。具有中等(优势比 [OR] = 0.69;95% 置信区间 [CI],0.51–0.82)或高(OR = 0.48;95% CI,0.38–0.60)多社会评分的参与者的死亡几率低于完全调整模型中的低类别,分别。
更新日期:2021-08-03
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