探討國軍代謝症候群發生率及其影響因素

Abstract

本研究目的藉由分析北、北、基、宜國軍體檢資料，以瞭解國軍人員代謝症候群盛行率、危險因子數量變化情形、主要影響因子及相關危險因子預測代謝症候群發之預測。藉對此議題的審視，作為未來國軍衛生機關或醫院，規劃並調整適宜的健康照護政策之參考，以促進國軍人員自我照護行為，提升軍人健全體格，減少醫療資源的耗用。 本研究採回溯性(Retrospective)，次級資?的縱貫研究(Longitudinal Study)分析法。運用北、北、基、宜區域國軍體檢資料，分析100年到107年期間軍人的體檢報告資料，主要以連續三次在同一場所進行國軍年度體檢者為研究對象。收集體檢資料內容包含:個人屬性、個人疾病史、健康行為、理學檢查、生化檢查。針對國軍人員代謝症候群盛行率情形加以分析探討，並運用廣義估計方程式連續三次體檢變化差異之比較。另以羅吉斯迴歸探討國軍人員代謝症候群主要影響因子及相關危險因子預測代謝症候群發預測之模型的品質。 本研究結果：1.分析的受試者總共有12, 719人，年齡介於30-58歲。發現其代謝症候群盛行率為16.6%，男性14.6%，女性4.8%；隨著年齡增加，盛行率增加。代謝症候群危險因子中，以收縮壓過高之盛行率最高約69.0%。2.GEE統計分析，發現五項診斷危險因子除了舒張壓和尿酸外，三次體檢腰圍、收縮壓、三酸甘油脂、高密度脂蛋白、空腹血糖數值的改變是有統計差異的(p<0.001)。3.影響30-58歲連續3次體檢者，代謝症候群前五名危險因子，為BMI(肥胖) (OR= 5.0)、高密度脂蛋白過低(OR =3.60)、三酸甘油脂( OR =2.61)、空腹血糖( OR =2.38)、腰圍( OR =2.25)。運用邏輯斯迴歸分析，正確預測率達86.4%。4.影響30-58歲連續3次體檢且有健康問卷資料者(N=5,428)，代謝症候群前五名危險因子，為BMI(肥胖) (OR= 4.57)高密度脂蛋白過低(OR =3.92)、三酸甘油脂( OR =2.34)、空腹血糖( OR =2.28)、有高血脂病史( OR =2.11)。運用邏輯斯迴歸分析，正確預測率達86.5%。 本研究結論：國軍人員之代謝症候群盛行率比一般成人低。盛行率男性大於女性，且隨著年齡增加盛行率增加。代謝症候群危險因子中，以收縮壓過高之盛行率最高。連續3次體檢影響代謝症候群前五名危險因子為為BMI(肥胖)、高密度脂蛋白過低、三酸甘油脂過高、空腹血糖過高、腰圍過大。Objective: To understand the prevalence of metabolic syndrome, changes in the number of risk factors, majorriskfactors and prediction model for the metabolic syndrome in military personnel by analyzing the military physical examination database from Taipei, New Taipei City, Keelung and Yilancounty.Based on theresults, themilitary organizations and hospitalscould set upappropriate health care policies to promote the self-care behaviors, improve the physical integrity of military personnel and reduce the consumption of medical resources. Methods:This is a retrospective, longitudinal study of a secondary database. The subjects were the military personnel who received physical check-up at the same place for three consecutive years in Taipei, New Taipei City, Keelung and Yilan countybetweenyear 2011 to 2018. The following data including demographic data, personal history, health behavior, physical examination, biochemical datawere collected. The prevalence rate of metabolic syndrome in military personnel was analyzed, and the changes of the data between three consecutive physical examinations were compared by generalized estimation equation (GEE). In addition, logistic regression is used to develop a prediction model that can predict the occurrence of metabolic syndrome in military personnel. Results: A total of 12,719 personnel were included. The age ranged from 30-58. The prevalence of metabolic syndrome was 16.6%; males were 14.6% and females were 4.8%. The prevalence of metabolic syndrome increased with age. The most prevalent risk factor of metabolic syndrome is high systolic blood pressure (69.0%). GEE analysis found that among the risk factors, the changes in waist circumference, systolic blood pressure, triglyceride, high-density lipoprotein, and fasting blood glucose values showed statistically difference ??between three consecutive physical examinations (p<0.001). The top five risk factors of metabolic syndrome are high BMI (obesity)(OR=5.0), low value of high-density-lipoprotein (OR=3.60), high value of triglyceride (OR=2.61), high value of fasting blood glucose (OR=2.38), and increasedwaist circumference (OR=2.25). Using logistic regression analysis, the correct prediction rate reached 86.4%. Among those with health questionnaire (n=5, 428), the top five risk factors of metabolic syndrome are high BMI (obesity) (OR=4.57), low value of high-density-lipoprotein (OR=3.92), high value of triglyceride (OR=2.34), high value of fasting blood glucose (OR=2.28), and history of hyperlipidemia (OR=2.11). Using logistic regression analysis, the correct prediction rate reached 86.5%. Conclusion: The prevalence of metabolic syndrome of military personnel is lower than that of general adults. The prevalence was higher in men than in women. The prevalence increased with age. Among the risk factors of metabolic syndrome, the most prevalent one was high systolic blood pressure. The top five risk factors of metabolic syndrome are high BMI (obesity), low value of high-density lipoprotein, high value of triglycerides and fasting blood glucose, and history of hyperlipidemia.