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The dynamic association of body mass index and all-cause mortality in multiple cohorts and its impacts

机译：多组人群体重指数与全因死亡率之间的动态关联及其影响

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Background In the literature, different shapes of associations have been found between body mass index (BMI) and mortality and some of the findings were opposite to each other. The association of BMI and mortality in a single cohort has been found to be dynamic that can lead to different findings under different settings. The identified dynamic features were consistent with the heterogeneity in the literature. It is meaningful to find out whether such dynamic associations exist in other populations. Methods Data of six different cohorts were used for analysis and comparison. The proportional hazards assumptions for BMI in Cox models were tested to identify dynamic associations in each cohort. Time-dependent covariates Cox model was used to model the association of BMI and mortality risk as functions of follow-up time. The Cox model was applied to the pooled data with survival times censored at 5 to 40 years to show the potential impact of the dynamic association on traditional Meta-analysis. Results and discussion Dynamic associations were identified in six models (4 for men and 2 for women), four of which showed the same changing pattern: the elevated mortality risk for low BMI decreased while that for high BMI increased with follow-up time. When the Cox model was applied to the pooled data excluding the largest and also the shortest cohort, low BMI was but high BMI was not associated with high mortality for men with censoring at 5 years but the association for low BMI became weaker and that for high BMI became much stronger when censoring time was at 40 years. The dynamic association indicated that shorter studies tend to obtain inverse associations between BMI and mortality while longer studies tend to obtain J-shaped associations. Conclusions Different or even opposite results about body weight and mortality in the literature may be in part due to the underlying dynamic association of BMI and mortality. The dynamic features need to be taken into consideration in future studies.
机译：背景技术在文献中，人们发现体重指数（BMI）与死亡率之间存在不同的联系形式，其中一些发现是相反的。单个队列中的BMI与死亡率之间的关系是动态的，可以在不同的情况下导致不同的发现。所确定的动态特征与文献中的异质性是一致的。找出其他人群中是否存在这种动态联系是有意义的。方法使用六个不同队列的数据进行分析和比较。测试了Cox模型中BMI的比例风险假设，以识别每个队列中的动态关联。时间相关协变量Cox模型用于建模BMI与死亡风险之间的关联，作为随访时间的函数。将Cox模型应用于合并数据，将生存时间检查在5至40年，以显示动态关联对传统Meta分析的潜在影响。结果与讨论在六个模型中确定了动态关联（男性4个，女性2个），其中四个模型显示出相同的变化模式：随着随访时间的延长，低BMI死亡率升高的风险降低，而高BMI死亡率升高的风险增加。当将Cox模型应用于汇总数据（不包括最大队列和最短队列）时，低BMI是但高BMI与5岁检查的男性高死亡率无关，但低BMI与高死亡率的相关性较弱。审查时间为40年时，BMI变得更加强大。动态关联表明，较短的研究趋向于获得BMI与死亡率之间的反向关联，而较长的研究趋向于获得J形关联。结论文献中有关体重和死亡率的不同甚至相反的结果可能部分归因于BMI与死亡率之间的潜在动态联系。在以后的研究中需要考虑动态特性。

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