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Abstract：
BACKGROUND: Obesity is a worldwide health concern with serious clinical effects, including myocardial infarction (MI), stroke, cardiovascular diseases (CVDs), and all-cause mortality. The present study aimed to assess the association of obesity phenotypes and different CVDs and mortality in males and females by simultaneously considering the longitudinal and survival time data.
METHODS: In the Tehran Lipid and Glucose Study (TLGS), participants older than three years were selected by a multi-stage random cluster sampling method and followed for about 19 years. In the current study, individuals aged over 40 years without a medical history of CVD, stroke, MI, and coronary heart disease were included. Exclusions comprised those undergoing treatment for CVD and those with more than 30% missing information or incomplete data. Joint modeling of longitudinal binary outcome and survival time data was applied to assess the dependency and the association between the changes in obesity phenotypes and time to occurrence of CVD, MI, stroke, and CVD mortality. To account for any potential sex-related confounding effect on the association between the obesity phenotypes and CVD outcomes, sex-specific analysis was carried out. The analysis was performed using packages (JMbayes2) of R software (version 4.2.1).
RESULTS: Overall, 6350 adults above 40 years were included. In the joint modeling of CVD outcome among males, literates and participants with a family history of diabetes were at lower risk of CVD compared to illiterates and those with no family history of diabetes in the Bayesian Cox model. Current smokers were at higher risk of CVD compared to non-smokers. In a logistic mixed effects model, odds of obesity phenotype was higher among participants with low physical activity, family history of diabetes and older age compared to males with high physical activity, no family history of diabetes and younger age. In females, based on the results of the Bayesian Cox model, participants with family history of diabetes, family history of CVD, abnormal obesity phenotype and past smokers had a higher risk of CVD compared to those with no history of diabetes, CVD and nonsmokers. In the obesity varying model, odds of obesity phenotype was higher among females with history of diabetes and older age compared to those with no history of diabetes and who were younger. There was no significant variable associated with MI among males in the Bayesian Cox model. Odds of obesity phenotype was higher in males with low physical activity compared to those with high physical activity in the obesity varying model, whereas current smokers were at lower odds of obesity phenotype than nonsmokers. In females, risk of MI was higher among those with family history of diabetes compared to those with no history of diabetes in the Bayesian Cox model. In the logistic mixed effects model, a direct and significant association was found between age and obesity phenotype. In males, participants with history of diabetes, abnormal obesity phenotype and older age were at higher risk of stroke in the Bayesian Cox model compared to males with no history of diabetes, normal obesity phenotype and younger persons. In the obesity varying model, odds of obesity phenotype was higher in males with low physical activity, family history of diabetes and older age compared to those with high physical activity, no family history of diabetes and who were younger. Smokers had a lower odds of obesity phenotype than nonsmokers. In females, past smokers and those with family history of diabetes were at higher risk of stroke compared to nonsmokers and females with no history of diabetes in the Bayesian Cox model. In the obesity varying model, females with family history of diabetes and older ages had a higher odds of obesity phenotype compared to those with no family history of diabetes and who were younger. Among males, risk of CVD mortality was lower in past smokers compared to nonsmokers in the survival model. A direct and significant association was found between age and CVD mortality. Odds of obesity phenotype was higher in males with a history of diabetes than in those with no family history of diabetes in the logistic mixed effects model.
CONCLUSIONS: It seems that modifications to metabolic disorders may have an impact on the heightened incidence of CVDs. Based on this, males with obesity and any type of metabolic disorder had a higher risk of CVD, stroke and CVD mortality (excluding MI) compared to those with a normal body mass index (BMI) and no metabolic disorders. Females with obesity and any type of metabolic disorder were at higher risk of CVD(, MI and stroke compared to those with a normal BMI and no metabolic disorders suggesting that obesity and metabolic disorders are related. Due to its synergistic effect on high blood pressure, metabolic disorders raise the risk of CVD.
METHODS: In the Tehran Lipid and Glucose Study (TLGS), participants older than three years were selected by a multi-stage random cluster sampling method and followed for about 19 years. In the current study, individuals aged over 40 years without a medical history of CVD, stroke, MI, and coronary heart disease were included. Exclusions comprised those undergoing treatment for CVD and those with more than 30% missing information or incomplete data. Joint modeling of longitudinal binary outcome and survival time data was applied to assess the dependency and the association between the changes in obesity phenotypes and time to occurrence of CVD, MI, stroke, and CVD mortality. To account for any potential sex-related confounding effect on the association between the obesity phenotypes and CVD outcomes, sex-specific analysis was carried out. The analysis was performed using packages (JMbayes2) of R software (version 4.2.1).
RESULTS: Overall, 6350 adults above 40 years were included. In the joint modeling of CVD outcome among males, literates and participants with a family history of diabetes were at lower risk of CVD compared to illiterates and those with no family history of diabetes in the Bayesian Cox model. Current smokers were at higher risk of CVD compared to non-smokers. In a logistic mixed effects model, odds of obesity phenotype was higher among participants with low physical activity, family history of diabetes and older age compared to males with high physical activity, no family history of diabetes and younger age. In females, based on the results of the Bayesian Cox model, participants with family history of diabetes, family history of CVD, abnormal obesity phenotype and past smokers had a higher risk of CVD compared to those with no history of diabetes, CVD and nonsmokers. In the obesity varying model, odds of obesity phenotype was higher among females with history of diabetes and older age compared to those with no history of diabetes and who were younger. There was no significant variable associated with MI among males in the Bayesian Cox model. Odds of obesity phenotype was higher in males with low physical activity compared to those with high physical activity in the obesity varying model, whereas current smokers were at lower odds of obesity phenotype than nonsmokers. In females, risk of MI was higher among those with family history of diabetes compared to those with no history of diabetes in the Bayesian Cox model. In the logistic mixed effects model, a direct and significant association was found between age and obesity phenotype. In males, participants with history of diabetes, abnormal obesity phenotype and older age were at higher risk of stroke in the Bayesian Cox model compared to males with no history of diabetes, normal obesity phenotype and younger persons. In the obesity varying model, odds of obesity phenotype was higher in males with low physical activity, family history of diabetes and older age compared to those with high physical activity, no family history of diabetes and who were younger. Smokers had a lower odds of obesity phenotype than nonsmokers. In females, past smokers and those with family history of diabetes were at higher risk of stroke compared to nonsmokers and females with no history of diabetes in the Bayesian Cox model. In the obesity varying model, females with family history of diabetes and older ages had a higher odds of obesity phenotype compared to those with no family history of diabetes and who were younger. Among males, risk of CVD mortality was lower in past smokers compared to nonsmokers in the survival model. A direct and significant association was found between age and CVD mortality. Odds of obesity phenotype was higher in males with a history of diabetes than in those with no family history of diabetes in the logistic mixed effects model.
CONCLUSIONS: It seems that modifications to metabolic disorders may have an impact on the heightened incidence of CVDs. Based on this, males with obesity and any type of metabolic disorder had a higher risk of CVD, stroke and CVD mortality (excluding MI) compared to those with a normal body mass index (BMI) and no metabolic disorders. Females with obesity and any type of metabolic disorder were at higher risk of CVD(, MI and stroke compared to those with a normal BMI and no metabolic disorders suggesting that obesity and metabolic disorders are related. Due to its synergistic effect on high blood pressure, metabolic disorders raise the risk of CVD.
摘要：
背景：肥胖是全球范围内的健康问题，具有严重的临床影响，包括心肌梗死（MI），中风,心血管疾病（CVDs），和全因死亡率。本研究旨在通过同时考虑纵向和生存时间数据来评估肥胖表型和不同CVD与男性和女性死亡率的关联。
方法：在德黑兰脂质和葡萄糖研究（TLGS）中，3岁以上的参与者采用多阶段随机整群抽样方法,随访约19年.在目前的研究中,40岁以上没有心血管疾病病史的人，中风,MI,包括冠心病。排除包括那些正在接受CVD治疗的患者以及那些信息缺失或数据不完整的患者。应用纵向二元结果和生存时间数据的联合建模来评估肥胖表型变化与CVD发生时间之间的依赖性和相关性。MI,中风,和CVD死亡率。为了解释肥胖表型和CVD结局之间的任何潜在的性别相关混杂效应，进行了性别特异性分析.使用R软件(4.2.1版)的软件包(JMbayes2)进行分析。
结果：总体而言，包括6350名40岁以上的成年人。在男性心血管疾病结局的联合建模中，在贝叶斯Cox模型中,与文盲和无糖尿病家族史者相比,有糖尿病家族史者和有糖尿病家族史者的CVD风险较低.与非吸烟者相比，目前吸烟者患CVD的风险更高。在逻辑混合效应模型中，肥胖表型的几率在低体力活动的参与者中更高，与高体力活动的男性相比，糖尿病家族史和年龄较大，无糖尿病家族史，年龄较小。在女性中，基于贝叶斯Cox模型的结果，有糖尿病家族史的参与者，心血管疾病家族史,与没有糖尿病史的人相比，肥胖表型异常和既往吸烟者患CVD的风险更高。CVD和不吸烟者。在肥胖变化模型中，与无糖尿病史和年龄较小的女性相比,有糖尿病史和年龄较大的女性肥胖表型的几率更高.在贝叶斯Cox模型中，男性之间没有与MI相关的显着变量。与肥胖变化模型中体力活动较多的男性相比，体力活动较少的男性肥胖表型的几率较高。而目前吸烟者患肥胖表型的几率低于不吸烟者.在女性中，在贝叶斯Cox模型中,有糖尿病家族史的患者的MI风险高于无糖尿病史的患者.在Logistic混合效应模型中，发现年龄和肥胖表型之间存在直接和显著的关联.在男性中，有糖尿病史的参与者，在贝叶斯Cox模型中，与没有糖尿病史的男性相比，肥胖表型异常和年龄较大的卒中风险更高。正常肥胖表型和年轻人。在肥胖变化模型中，低体力活动的男性肥胖表型的几率更高，糖尿病家族史和年龄与那些有高体力活动的人相比，无糖尿病家族史，且年龄较小。吸烟者患肥胖表型的几率低于不吸烟者。在女性中，在贝叶斯Cox模型中,与不吸烟者和无糖尿病史的女性相比,既往吸烟者和有糖尿病家族史的女性卒中风险较高.在肥胖变化模型中，与无糖尿病家族史且年龄较小的女性相比,有糖尿病家族史且年龄较大的女性患肥胖表型的几率更高.在男性中，生存模型中,与不吸烟者相比,既往吸烟者的CVD死亡率风险较低.发现年龄和CVD死亡率之间存在直接和显著的关联。在逻辑混合效应模型中，有糖尿病史的男性肥胖表型的几率高于无糖尿病家族史的男性。
结论：似乎代谢紊乱的改变可能对CVD的发病率增加有影响。基于此,患有肥胖和任何类型代谢紊乱的男性患CVD的风险较高，与体重指数（BMI）正常且无代谢紊乱的人群相比，卒中和CVD死亡率（不包括MI）。患有肥胖和任何类型代谢紊乱的女性患CVD的风险较高(，与BMI正常且无代谢紊乱者相比，MI和卒中提示肥胖与代谢紊乱有关。由于其对高血压的协同作用，代谢紊乱会增加CVD的风险.
方法：在德黑兰脂质和葡萄糖研究（TLGS）中，3岁以上的参与者采用多阶段随机整群抽样方法,随访约19年.在目前的研究中,40岁以上没有心血管疾病病史的人，中风,MI,包括冠心病。排除包括那些正在接受CVD治疗的患者以及那些信息缺失或数据不完整的患者。应用纵向二元结果和生存时间数据的联合建模来评估肥胖表型变化与CVD发生时间之间的依赖性和相关性。MI,中风,和CVD死亡率。为了解释肥胖表型和CVD结局之间的任何潜在的性别相关混杂效应，进行了性别特异性分析.使用R软件(4.2.1版)的软件包(JMbayes2)进行分析。
结果：总体而言，包括6350名40岁以上的成年人。在男性心血管疾病结局的联合建模中，在贝叶斯Cox模型中,与文盲和无糖尿病家族史者相比,有糖尿病家族史者和有糖尿病家族史者的CVD风险较低.与非吸烟者相比，目前吸烟者患CVD的风险更高。在逻辑混合效应模型中，肥胖表型的几率在低体力活动的参与者中更高，与高体力活动的男性相比，糖尿病家族史和年龄较大，无糖尿病家族史，年龄较小。在女性中，基于贝叶斯Cox模型的结果，有糖尿病家族史的参与者，心血管疾病家族史,与没有糖尿病史的人相比，肥胖表型异常和既往吸烟者患CVD的风险更高。CVD和不吸烟者。在肥胖变化模型中，与无糖尿病史和年龄较小的女性相比,有糖尿病史和年龄较大的女性肥胖表型的几率更高.在贝叶斯Cox模型中，男性之间没有与MI相关的显着变量。与肥胖变化模型中体力活动较多的男性相比，体力活动较少的男性肥胖表型的几率较高。而目前吸烟者患肥胖表型的几率低于不吸烟者.在女性中，在贝叶斯Cox模型中,有糖尿病家族史的患者的MI风险高于无糖尿病史的患者.在Logistic混合效应模型中，发现年龄和肥胖表型之间存在直接和显著的关联.在男性中，有糖尿病史的参与者，在贝叶斯Cox模型中，与没有糖尿病史的男性相比，肥胖表型异常和年龄较大的卒中风险更高。正常肥胖表型和年轻人。在肥胖变化模型中，低体力活动的男性肥胖表型的几率更高，糖尿病家族史和年龄与那些有高体力活动的人相比，无糖尿病家族史，且年龄较小。吸烟者患肥胖表型的几率低于不吸烟者。在女性中，在贝叶斯Cox模型中,与不吸烟者和无糖尿病史的女性相比,既往吸烟者和有糖尿病家族史的女性卒中风险较高.在肥胖变化模型中，与无糖尿病家族史且年龄较小的女性相比,有糖尿病家族史且年龄较大的女性患肥胖表型的几率更高.在男性中，生存模型中,与不吸烟者相比,既往吸烟者的CVD死亡率风险较低.发现年龄和CVD死亡率之间存在直接和显著的关联。在逻辑混合效应模型中，有糖尿病史的男性肥胖表型的几率高于无糖尿病家族史的男性。
结论：似乎代谢紊乱的改变可能对CVD的发病率增加有影响。基于此,患有肥胖和任何类型代谢紊乱的男性患CVD的风险较高，与体重指数（BMI）正常且无代谢紊乱的人群相比，卒中和CVD死亡率（不包括MI）。患有肥胖和任何类型代谢紊乱的女性患CVD的风险较高(，与BMI正常且无代谢紊乱者相比，MI和卒中提示肥胖与代谢紊乱有关。由于其对高血压的协同作用，代谢紊乱会增加CVD的风险.
