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预测新发共病。

Predicting Incident Multimorbidity.

机构信息

University of Exeter Medical School, St Luke's Campus, Exeter, Devon, United Kingdom.

Faculty of Psychology, University of Murcia, Murcia, Spain.

出版信息

Ann Fam Med. 2018 Jul;16(4):322-329. doi: 10.1370/afm.2271.

Abstract

PURPOSE

Multimorbidity is associated with adverse outcomes, yet research on the determinants of its incidence is lacking. We investigated which sociodemographic, health, and individual lifestyle (eg, physical activity, smoking behavior, body mass index) characteristics predict new cases of multimorbidity.

METHODS

We used data from 4,564 participants aged 50 years and older in the English Longitudinal Study of Aging that included a 10-year follow-up period. Discrete time-to-event (complementary log-log) models were constructed for exploring the associations of baseline characteristics with outcomes between 2002-2003 and 2012-2013 separately for participants with no initial conditions (n = 1,377) developing multimorbidity, any increase in conditions within 10 years regardless of initial conditions, and the impact of individual conditions on incident multimorbidity.

RESULTS

The risks of developing multimorbidity were positively associated with age, and they were greater for the least wealthy, for participants who were obese, and for those who reported the lowest levels of physical activity or an external locus of control (believing that life events are outside of one's control) for all groups regardless of baseline conditions (all linear trends <.05). No significant associations were observed for sex, educational attainment, or social detachment. For participants with any increase in conditions (n = 4,564), a history of smoking was the only additional predictor. For participants with a single baseline condition (n = 1,534), chronic obstructive pulmonary disease (COPD), asthma, and arrhythmia showed the strongest associations with subsequent multimorbidity.

CONCLUSIONS

Our findings support the development and implementation of a strategy targeting the prevention of multimorbidity for susceptible groups. This approach should incorporate behavior change addressing lifestyle factors and target health-related locus of control.

摘要

目的

多种疾病与不良结局相关,但关于其发病的决定因素的研究却很缺乏。我们调查了哪些社会人口学、健康和个体生活方式(如身体活动、吸烟行为、体重指数)特征可以预测多种疾病的新发病例。

方法

我们使用了英国老龄化纵向研究中 4564 名年龄在 50 岁及以上的参与者的数据,该研究包括 10 年的随访期。分别为基线无初始疾病(n=1377)的参与者、10 年内任何疾病增加的参与者(无论基线条件如何)以及个体疾病对新发多种疾病的影响,构建了离散时间事件(互补对数-log)模型,以探索基线特征与 2002-2003 年和 2012-2013 年结果之间的关联。

结果

发生多种疾病的风险与年龄呈正相关,对于最不富裕的人群、肥胖人群以及报告身体活动水平最低或外部控制源(认为生活事件不受个人控制)的人群,无论基线条件如何,风险都更高(所有线性趋势<0.05)。对于男性、教育程度或社会疏离,没有观察到显著的相关性。对于任何疾病增加的参与者(n=4564),吸烟史是唯一的额外预测因素。对于基线有单一疾病的参与者(n=1534),慢性阻塞性肺疾病(COPD)、哮喘和心律失常与随后的多种疾病有最强的关联。

结论

我们的研究结果支持为易感人群制定和实施预防多种疾病的策略。这种方法应该包含针对生活方式因素的行为改变,并以健康相关的控制源为目标。

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Predicting Incident Multimorbidity.预测新发共病。
Ann Fam Med. 2018 Jul;16(4):322-329. doi: 10.1370/afm.2271.

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