目的 分析职业人群不健康生活方式对糖脂代谢异常的影响及关键影响因素，为糖脂代谢异常的预防提供科学依据。 方法 基于2021年中国铁路成都局集团有限公司西南职业人群队列的基线数据和随访数据。糖脂代谢异常以糖尿病伴1项或多项血脂异常判断，不健康生活方式根据吸烟、饮酒、不健康膳食模式、低体力活动和BMI异常进行评分。通过多因素logistic回归模型分析不健康生活方式得分与糖脂代谢异常之间的关系，采用网络分析探索影响糖脂代谢的主要生活方式。 结果 共纳入25 631名研究对象。不健康生活方式得分为2、3分人群患糖尿病伴≥1项血脂异常的风险分别为0分的1.93（95%CI：1.31~2.86）倍和2.37（95%CI：1.60~3.50）倍；不健康生活方式得分为1、2、3分人群患糖尿病伴≥2项血脂异常的风险分别为0分的1.98（95%CI：1.08~3.61）倍、2.87（95%CI：1.60~5.14）倍和3.95（95%CI：2.22~7.06）倍。网络分析发现BMI异常和HDL-C是连接不健康生活方式与糖脂代谢异常的“桥接节点”。 结论 不健康生活方式得分越高，患糖脂代谢异常的风险越大，BMI异常和HDL-C是关联不健康生活方式和糖脂代谢异常的关键因素。 Objective To understand the influence of unhealthy lifestyle on diabetic dyslipidemia and the key influencing factors in occupational population and provided scientific evidence for the prevention of diabetic dyslipidemia. Methods Based on baseline data and follow-up data of Southwest Occupational Population Cohort from China Railway Chengdu Group Co., Ltd. during 2021. Diabetic dyslipidemia was defined as diabetes plus one or more forms of dyslipidemia, and unhealthy lifestyle factors included smoking, alcohol consumption, unhealthy dietary patterns, low physical activity, and abnormal BMI. Multivariate logistic regression model was used to analyze the relationship between unhealthy lifestyle scores and diabetic dyslipidemia, network analysis was used to find and explore the key lifestyles influencing glycolipid metabolism. Results A total of 25 631 subjects were included. People with unhealthy lifestyle score 2 and 3 were 1.93 (95%CI: 1.31-2.86) times and 2.37 (95%CI: 1.60-3.50) times more likely to have diabetes with ≥1 forms of dyslipidemia than those with scores of 0 People with unhealthy lifestyle score 1, 2 and 3 were 1.98 (95%CI: 1.08-3.61) times, 2.87 (95%CI: 1.60-5.14) times and 3.95 (95%CI: 2.22-7.06) times more likely to have diabetes with ≥2 forms of dyslipidemia than those with score 0. Network analysis found that abnormal BMI and HDL-C were the "bridge nodes" that link unhealthy lifestyles with diabetic dyslipidemia. Conclusion The higher the score of unhealthy lifestyle, the higher the risk for diabetic dyslipidemia, abnormal BMI and HDL-C are key factors influencing the association between unhealthy lifestyle and diabetic dyslipidemia.
Abstract
Objective To understand the influence of unhealthy lifestyle on diabetic dyslipidemia and the key influencing factors in occupational population and provided scientific evidence for the prevention of diabetic dyslipidemia. Methods Based on baseline data and follow-up data of Southwest Occupational Population Cohort from China Railway Chengdu Group Co., Ltd. during 2021. Diabetic dyslipidemia was defined as diabetes plus one or more forms of dyslipidemia, and unhealthy lifestyle factors included smoking, alcohol consumption, unhealthy dietary patterns, low physical activity, and abnormal BMI. Multivariate logistic regression model was used to analyze the relationship between unhealthy lifestyle scores and diabetic dyslipidemia, network analysis was used to find and explore the key lifestyles influencing glycolipid metabolism. Results A total of 25 631 subjects were included. People with unhealthy lifestyle score 2 and 3 were 1.93 (95%CI: 1.31-2.86) times and 2.37 (95%CI: 1.60-3.50) times more likely to have diabetes with ≥1 forms of dyslipidemia than those with scores of 0 People with unhealthy lifestyle score 1, 2 and 3 were 1.98 (95%CI: 1.08-3.61) times, 2.87 (95%CI: 1.60-5.14) times and 3.95 (95%CI: 2.22-7.06) times more likely to have diabetes with ≥2 forms of dyslipidemia than those with score 0. Network analysis found that abnormal BMI and HDL-C were the "bridge nodes" that link unhealthy lifestyles with diabetic dyslipidemia. Conclusion The higher the score of unhealthy lifestyle, the higher the risk for diabetic dyslipidemia, abnormal BMI and HDL-C are key factors influencing the association between unhealthy lifestyle and diabetic dyslipidemia.
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