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首页> 外文期刊>Preventive Medicine: An International Journal Devoted to Practice and Theory >Leading determinants for multimorbidity in middle-aged Australian men and women: A nine-year follow-up cohort study
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Leading determinants for multimorbidity in middle-aged Australian men and women: A nine-year follow-up cohort study

机译：中年澳大利亚男女多元化的主要决定因素：九年后续队列研究

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Although socioeconomic, behavioural, psychological, and biological factors have been individually linked to multimorbidity, data on the importance of these factors are limited. Our study aimed to determine the leading predictors for multimorbidity of chronic conditions in middle-aged Australian adults using machine learning methods. We included 53,867 participants aged 45-64 years from the 45 and Up Study who were free of eleven predefined chronic conditions at baseline (2006-2009) in the analysis. Incident multimorbidity was defined by the co-existence of >= 2, >= 3, or >= 4 conditions during follow-up until December 31, 2016. The five leading predictors for multimorbidity in men were age (7.2-20.5% of total variance), body mass index (6.5-15.4%), smoking (4.0-8.3%), chicken intake (3.6-7.5%), and red meat intake (4.6-6.3%) across the three definitions. Leading predictors varied across the three definitions in women, but the four common ones were body mass index (6.3-20.1%), age (6.2-16.4%), chicken intake (4.1-8.3%), and red meat intake (4.2-4.7%). The ten leading modifiable health factors accounted for 39.4-46.1% of total variance across the three definitions. Men with 6-10 health factors had 46-54% lower risks for multimorbidity compared with those reporting <= 2. The corresponding percentage for women was 45-52%. Non-behavioural factors including psychological distress, low education and income and high relative economic disadvantage were among the leading risk factors for multimorbidity. In conclusion, modifications on behavioural factors including diets, physical activity, smoking, alcohol consumption may reduce the risk of multimorbidity in middle-aged adults, whereas individuals with low socioeconomic status or psychological distress are at the highest priority for intervention.
机译：尽管社会经济、行为、心理和生物因素与多发病率有着各自的联系，但关于这些因素重要性的数据有限。我们的研究旨在使用机器学习方法确定澳大利亚中年成年人慢性病多发病率的主要预测因素。我们纳入了来自45岁及以上研究的53867名年龄在45-64岁之间的参与者，他们在基线检查时（2006-2009年）没有11种预先定义的慢性病。在2016年12月31日之前的随访期间，事件多发病率定义为>=2、>=3或>=4种情况并存。在这三个定义中，男性多发病率的五个主要预测因素是年龄（占总方差的7.2-20.5%）、体重指数（6.5-15.4%）、吸烟（4.0-8.3%）、鸡肉摄入量（3.6-7.5%）和红肉摄入量（4.6-6.3%）。女性的主要预测因素在三个定义中有所不同，但四个常见的预测因素是体重指数（6.3-20.1%）、年龄（6.2-16.4%）、鸡肉摄入量（4.1-8.3%）和红肉摄入量（4.2-4.7%）。十个主要的可修改健康因素占三个定义总方差的39.4-46.1%。与报告小于等于2的男性相比，健康因素为6-10的男性多发病风险降低46-54%。女性的相应比例为45-52%。非行为因素包括心理困扰、低教育和低收入以及较高的相对经济劣势是多发病的主要风险因素。总之，改变行为因素，包括饮食、体育活动、吸烟、饮酒，可能会降低中年人多发病的风险，而社会经济地位低或心理困扰的个人是干预的最高优先事项。

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