摘要目的:分析新疆南疆居民心血管代谢性共病（CMM）的关联因素其累积效应。方法:采用分层随机整群抽样方法，于2016年在新疆第三师51团进行问卷调查、体格检查和实验室检测。采用多因素logistic回归、多因素线性回归、非限制性立方样条和网络分析的方法，研究生活方式（吸烟、饮酒、体育活动），社会经济（职业、受教育程度、婚姻状况）和临床因素（腰围、BMI、家族史）与CMM的关联。结果:共纳入12 773 名研究对象。新疆南疆居民心血管代谢疾病患病率52.49%，其中血脂异常、高血压、冠心病、糖尿病、脑卒中患病率依次为31.14%、29.95%、6.78%、6.26%、2.47%，CMM患病率为19.06%。多因素logistic回归分析显示，临床因素和社会经济因素与CMM患病的关联随着评分的增加，其 OR值分别从1分的1.75和1.07上升到3分的4.41和1.93；生活方式因素与CMM患病的关联仅在较高评分中存在（ OR=1.26，95% CI：1.07~1.62）。将各分组得分作为连续性变量带入模型进行趋势性检验显示，患病风险随临床因素、社会经济因素和生活方式因素数量的上升而增加（均 P<0.05）。限制性立方样条分析显示，关联因素总数量与CMM患病存在非线性关系（ P总体<0.05、 P非线性<0.05）。网络分析显示，高血压（强度=0.42）为5种疾病的“核心节点”；分析3类影响因素时，高血压（强度=0.68）、血脂异常（强度=0.47）、冠心病（强度=0.37）、临床因素（强度=0.53）为网络中的“核心节点”；分析9 种关联因素时，腰围异常（强度=0.90），BMI异常（强度=0.84）为网络中的“关键因素”，高血压（强度=0.68）、血脂异常（强度=0.52）为网络中的“关键疾病”。 结论:南疆居民CMM患病率高且多种因素存在累积效应；共病网络中高血压，血脂异常为关键疾病，BMI异常，腰围异常为关键关联因素。

abstractsObjective:To analyze the associated factors and cumulative effects of cardiometabolic multimorbidity (CMM) among residents in southern Xinjiang.Methods:A stratified random cluster sampling method was used to conduct questionnaire surveys, physical examinations and laboratory tests among the personnel of the 51st Brigade, 3rd Division, Xinjiang, in 2016. The multivariate logistic regression, multivariate linear regression, restricted cubic spline, and network analysis methods were used to study the association of lifestyle (smoking, alcohol consumption and physical activity), socioeconomic (occupation, education and marital status) and clinical factors (waist circumference, body mass index and family history) with CMM.Results:A total of 12 773 study subjects were included. The prevalence of cardiovascular metabolic diseases among residents in southern Xinjiang was 52.49%. Specifically, the prevalence rates of dyslipidemia, hypertension, coronary heart disease, diabetes, and stroke were 31.14%, 29.95%, 6.78%, 6.26%, and 2.47%, respectively, and the prevalence of CMM was 19.06%. Multivariate logistic regression analysis revealed that the associations between clinical and socioeconomic factors and CMM significantly increased with higher scores. Specifically, the OR rose from 1.75 (clinical factors) and 1.07 (socioeconomic factors) on a score of 1 to 4.41 and 1.93 on a score of 3, respectively. The association between lifestyle factors and CMM was only observed at higher scores ( OR=1.26, 95% CI:1.07~1.62). The trend test using the scores of each group as continuous variables in the model showed that the risk of disease increased with the accumulation of clinical, socioeconomic and lifestyle factors (all P<0.05). Restricted cubic spline analysis demonstrated a non-linear relationship between the total number of associated factors and CMM ( Poverall<0.05 and Pnon-linear<0.05). Network analysis identified hypertension (strength=0.42) as the “core node” among the five diseases. When analyzing the three types of influencing factors, hypertension (strength=0.68), dyslipidemia (strength=0.47), coronary heart disease (strength=0.37), and clinical factors (strength=0.53) emerged as “core nodes”. In the network of nine associated factors, abnormal waist circumference and BMI (strength=0.90 and 0.84) were identified as “key factors”, while hypertension (strength=0.68) and dyslipidemia (strength=0.52) were identified as “key diseases”. Conclusion:The prevalence of CMM among residents in southern Xinjiang is high, and there is a cumulative effect of multiple factors. Hypertension and dyslipidemia are key diseases in the multimorbidity network, while abnormal BMI and waist circumference are key associated factors.