目的:以前的流行病学研究发现局部体脂与抑郁症状之间的关联尚不清楚。我们旨在根据国家健康与营养调查(NHANES)的数据确定不同地区的体脂与抑郁症状之间的关联。
方法:这项研究包括2011-2018年NHANES中年龄≥20岁的3393名参与者。使用患者健康问卷-9评估抑郁症状。用双能X线吸收法测定不同区域的脂肪量(FM),后备箱FM,臂FM,腿FM通过将以千克为单位的FM除以以米为单位的身体高度的平方来获得FM指数(FMI)。根据分析指南计算加权数据。使用线性逻辑回归模型来量化区域FMI与抑郁症状之间的关联。还进行了单变量和分层分析。
结果:这项研究的参与者包括2066名男性和1327名女性。有404名(11.91%)参与者有抑郁症状,年龄为40.89±11.74岁,体重指数为30.07±7.82kg/m²。发现总FMI与抑郁症状之间存在显着关联。在完全调整的多元回归模型中,较高的总FMI(比值比=2.18,95%置信区间[CI]=1.08-4.39)与较高的抑郁症状风险相关,而总FMI增加(β=1.55,95%CI=0.65-2.44,p=0.001),树干FMI(β=0.57,95%CI=0.04-1.10,p=0.036),和手臂FMI(β=0.96,95%CI=0.33-1.59,p=0.004)与PHQ-9(患者健康问卷-9)得分显着相关,而腿部FMI没有(p=0.102)。总FMI和抑郁症状之间的加权关联在大多数亚群之间没有显着差异(相互作用的所有p值>0.05)。非西班牙裔白人患抑郁症的风险更高,吸烟者,饮酒者,肥胖,并且患有糖尿病和甲状腺问题(p<0.05)。
结论:这些发现表明,区域FMI较高的人群更容易出现抑郁症状,特别是在那些也有增加的总FMI。这种关联在吸烟者中更为明显,饮酒者,肥胖,还有糖尿病和甲状腺问题.
OBJECTIVE: The findings from previous epidemiological studies of the association between regional body fat and depressive symptoms have been unclear. We aimed to determine the association between the body fat in different regions and depressive symptoms based on data from the National Health and Nutrition Examination Survey (NHANES).
METHODS: This study included 3393 participants aged ≥ 20 years from the NHANES performed during 2011-2018. Depressive symptoms were assessed using the Patient Health Questionnaire-9. The fat mass (FM) was measured in different regions using dual-energy X-ray absorptiometry to determine the total FM, trunk FM, arm FM, and leg FM. The FM index (FMI) was obtained by dividing the FM in kilograms by the square of the body height in meters. Weighted data were calculated in accordance with analytical guidelines. Linear logistic regression models were used to quantify the association between regional FMI and depressive symptoms. Univariate and stratified analyses were also performed.
RESULTS: The participants in this study comprised 2066 males and 1327 females. There were 404 (11.91%) participants with depressive symptoms, who were aged 40.89 ± 11.74 years and had a body mass index of 30.07 ± 7.82 kg/m². A significant association was found between total FMI and depressive symptoms. In the fully adjusted multivariate regression model, a higher total FMI (odds ratio = 2.18, 95% confidence interval [CI] = 1.08-4.39) was related to a higher risk of depressive symptoms, while increased total FMI (β = 1.55, 95% CI = 0.65-2.44, p = 0.001), trunk FMI (β = 0.57, 95% CI = 0.04-1.10, p = 0.036), and arm FMI (β = 0.96, 95% CI = 0.33-1.59, p = 0.004) were significantly associated with PHQ-9 (Patient Health Questionnaire-9) scores, whereas the leg FMI was not (p = 0.102). The weighted association between total FMI and depressive symptoms did not differ significantly between most of the subpopulations (all p values for interaction > 0.05). The risk of having depression was higher in individuals who were non-Hispanic Whites, smokers, drinkers, obese, and had diabetes and thyroid problems (p < 0.05).
CONCLUSIONS: These findings suggest that the population with a higher regional FMI is more likely to have depressive symptoms, especially in those who also have an increased total FMI. The association is more pronounced in individuals who are smokers, drinkers, obese, and have diabetes and thyroid problems.