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Clinical, socioeconomic, and behavioural factors at age 50 years and risk of cardiometabolic multimorbidity and mortality: A cohort study

机译:一项队列研究:50岁时的临床,社会经济和行为因素以及心脏代谢多发和死亡的风险

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Background Multimorbidity is increasingly common and is associated with adverse health outcomes, highlighting the need to broaden the single-disease framework that dominates medical research. We examined the role of midlife clinical characteristics, socioeconomic position, and behavioural factors in the development of cardiometabolic multimorbidity (at least 2 of diabetes, coronary heart disease, and stroke), along with how these factors modify risk of mortality. Methods and findings Data on 8,270 men and women were drawn from the Whitehall II cohort study, with mean follow-up of 23.7 years (1985 to 2017). Three sets of risk factors were assessed at age 50 years, each on a 5-point scale: clinical profile (hypertension, hypercholesterolemia, overweight/obesity, family history of cardiometabolic disease), occupational position, and behavioural factors (smoking, alcohol consumption, diet, physical activity). The outcomes examined were cardiometabolic disease (diabetes, coronary heart disease, stroke), cardiometabolic multimorbidity, and mortality. We used multi-state models to examine the role of risk factors in 5 components of the cardiometabolic disease trajectory: from healthy state to first cardiometabolic disease, from first cardiometabolic disease to cardiometabolic multimorbidity, from healthy state to death, from first cardiometabolic disease to death, and from cardiometabolic multimorbidity to death. A total of 2,501 participants developed 1 of the 3 cardiometabolic diseases, 511 developed cardiometabolic multimorbidity, and 1,406 died. When behavioural and clinical risk factors were considered individually, only smoking was associated with all five transitions. In a model containing all 3 risk factor scales, midlife clinical profile was the strongest predictor of first cardiometabolic disease (hazard ratio for the least versus most favourable profile: 3.74; 95% CI: 3.14–4.45) among disease-free participants. Among participants with 1 cardiometabolic disease, adverse midlife socioeconomic (1.54; 95% CI: 1.10–2.15) and behavioural factors (2.00; 95% CI: 1.40–2.85), but not clinical characteristics, were associated with progression to cardiometabolic multimorbidity. Only midlife behavioural factors predicted mortality among participants with cardiometabolic disease (2.12; 95% CI: 1.41–3.18) or cardiometabolic multimorbidity (3.47; 95% CI: 1.81–6.66). A limitation is that the study was not large enough to estimate transitions between each disease and subsequent outcomes and between all possible pairs of diseases. Conclusions The importance of specific midlife factors in disease progression, from disease-free state to single disease, multimorbidity, and death, varies depending on the disease stage. While clinical risk factors at age 50 determine the risk of incident cardiometabolic disease in a disease-free population, midlife socioeconomic and behavioural factors are stronger predictors of progression to multimorbidity and mortality in people with cardiometabolic disease.
机译:背景技术多发病率越来越普遍,并与不良健康后果相关联,这突出表明有必要扩大主导医学研究的单一疾病框架。我们检查了中年临床特征,社会经济地位和行为因素在心脏代谢多发病(至少2例糖尿病,冠心病和中风)发展中的作用,以及这些因素如何改变死亡风险。方法和发现来自Whitehall II队列研究的8,270名男性和女性数据,平均随访23.7年(1985年至2017年)。在50岁时评估了三组风险因素,每项以5分制进行评估:临床概况(高血压,高胆固醇血症,超重/肥胖,心脏代谢疾病的家族史),职业状况和行为因素(吸烟,饮酒,饮食,体育锻炼)。检查的结果是心脏代谢疾病(糖尿病,冠心病,中风),心脏代谢多发性疾病和死亡率。我们使用多状态模型检查了危险因素在心脏代谢疾病轨迹中的5个组成部分中的作用:从健康状态到第一心脏代谢疾病,从第一心脏代谢疾病到心脏代谢多发病,从健康状态到死亡,从第一心脏代谢疾病到死亡,以及从心脏代谢异常到死亡。共有2,501名参与者发展了3种心脏代谢疾病中的1种,有511种发展了心脏代谢疾病,并导致1,406例死亡。当单独考虑行为和临床危险因素时,只有吸烟与这五个转变有关。在包含所有3种危险因素量表的模型中,无病参与者中年临床特征是首次心脏代谢疾病的最强预测因子(最小与最有利特征的危险比:3.74; 95%CI:3.14-4.45)。在患有1种心脏代谢疾病的参与者中,不良的中年社会经济状况(1.54; 95%CI:1.10–2.15)和行为因素(2.00; 95%CI:1.40–2.85)与心律失常多发性相关。只有中年行为因素才能预测患有心脏代谢疾病(2.12; 95%CI:1.41-3.18)或心脏代谢多发病(3.47; 95%CI:1.81-6.66)的参与者的死亡率。局限性在于该研究规模不足以估计每种疾病与后续结果之间以及所有可能的疾病对之间的转变。结论特定中年因素在疾病进展中的重要性,从无病状态到单一疾病,多发病和死亡,取决于疾病阶段。尽管50岁时的临床风险因素决定了无病人群发生心血管疾病的风险,但中年的社会经济和行为因素更能预测心血管疾病患者多发病和死亡的进展。

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