Visceral Adiposity Index Is a Measure of the Likelihood of Developing Depression Among Adults in the United States

Lei, Jun; Luo, Yaoyue; Xie, Yude; Wang, Xiaoju

doi:10.3389/fpsyg.2022.772556

Cited by 19 publications

(10 citation statements)

References 34 publications

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“…When the daily fat intake reaches 54g, the risk of depression can be reduced to 5.887 according to the formula, while the scale score can reduce to 8.7. This result shows that after receiving fat intake, the level of depression has reached mild depression (PHQ9= [5][6][7][8][9]).…”

Section: Discussionmentioning

confidence: 97%

“…The cut-off point of mild depression for the PHQ-9 was recommended as ve [12]. The sensitivity and speci city of major depression are 88% and 88%, respectively, and different ranges de ned the symptoms of depression of varying severity ( [5][6][7][8][9], [10][11][12][13][14], [15][16][17][18][19], [20][21][22][23][24][25][26][27]) to distinguish [13]. It is a simple, fast, and reliable tool to screen and assess the severity of depression [12].…”

Section: Depression Datamentioning

confidence: 99%

“…Nevertheless, the relationship between dietary fat intake and depression remains unclear. Numerous studies have linked gut microbiome, brain metabolome, NPY system, and DPP-4-like activity to fat-like depression [8], but the relation between dietary fat content and depression has not been con rmed [9]. So, we established this study to nd the relationship between dietary fat and depression.…”

Section: Introductionmentioning

confidence: 99%

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The Relationship between Dietary Fat Intake and Depression: A Cross-sectional Study from NHANES 2007–2018

Yang

Dong

Xie

et al. 2023

Preprint

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Background Depression is a serious public mental health problem, and the mechanism of depression is not unequivocal. Previous studies show a detrimental relationship between trans fatty acid intake and depression risk. Furthermore, it is still unclear how diet-related fat intake and depression are related. Consequently, this study aimed to create a formula and scale to forecast the association between diet-related fat intake and depression. Methods A total of 5,746 samples from the National Health and Nutrition Examination Survey (NHANES) were included in the study. Fat intake was assessed by 24h dietary recalls and summed for two days to prevent data bias. Depression was assessed using the Patient Health Questionnaire-9 (PHQ9). Multivariate logistic regression and the generalized additive model (GAM) were used to analyze the relationship between dietary fat intake and depression. Results It was negatively correlated with a segmented regression model, and the threshold was 155.45 [β= -0.0077 (-0.0115, -0.0039), p < 0.0001]. After re-selecting the data (fat intake < 155.45 g/2 days) according to the inflection point (n = 3,391), the formula was y = y0 + Ae^(2x/t) (R-Square was 0.72967). The y is the PHQ9, and x is the dietary fat intake (g/day). The difference between the scale value and the actual PHQ9 score was not statistically significant in this investigation, which used a scale based on the Polychoric correlation (p=0.22499). Conclusions This study illustrates a negative association between fat intake and depression. Moreover, this negative association was explored in terms of quantitative relationships. The fitted formulas and scales were reasonable consistency, and both can be used for the dietary evaluation of depressed patients. By adjusting the diet, we can provide nutritional advice to depressed patients and reduce the risk of medication and the psychological stress of patients. Although Proper fat intake can reduce the severity of depression, we need to be alert to other problems caused by excessive fat intake, such as hypertension, diabetes, or atherosclerosis.

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Section: Discussionmentioning

confidence: 97%

Section: Depression Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Relationship between Dietary Fat Intake and Depression: A Cross-sectional Study from NHANES 2007–2018

Yang

Dong

Xie

et al. 2023

Preprint

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“…However, only female T2DM patients showed positive correlation between PHQ-9 with VAI, LAPI, and CI which were partially in agreement with a very recent study conducted by Lei et al in United states on apparently healthy individuals since they investigated only VAI but not other adiposity indices. 20 Moreover, they did not mention if there was any difference in findings with respect to gender.…”

Section: Discussionmentioning

confidence: 99%

Predictive value of adiposity index in identifying depression in individuals with type 2 diabetes mellitus in Indian population

Singh,

Nain

et al. 2023

JLP

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Objectives Type 2 diabetes mellitus (T2DM) patients are four times more prone to develop depression. Common subjective tool to evaluate depression is Patient Health Questionnaire-9 (PHQ-9). Depression in T2DM remains unaddressed because of lack of objective tools resulting in poor treatment compliance. Both obesity and metabolic disturbances could influence mental health status. Therefore, this study was designed to determine the better adiposity index to predict depression in T2DM. Subjects and Methods In this clinic-based cross-sectional study, 400 individuals (260 = T2DM and 140 = healthy) were recruited. Based on PHQ-9, T2DM patients were divided into T2DM + Dep (PHQ-9 ≥ 10) and T2DM-Dep (PHQ-9 < 10). The relationship between the PHQ-9 score and adiposity indices was examined by Pearson's/ Spearman's correlation. The receiver-operating characteristic curve analysis was used to identify the cutoff value. Results Female diabetic patients showed significant correlation only in lipid accumulation product index (LAPI) and visceral adiposity index (VAI) (r = 0.206 and r = 0.0.237, respectively), while male diabetic patients did not show any significant association. Interestingly, T2DM + Dep group showed significant association between LAPI (r = 0.248) with PHQ-9 score, while T2DM-Dep group did not show significant association. VAI had maximum area under the curve in T2DM patients (0.619, p = 0.002) as well as in female diabetic patients (0.684, p = 0.002). The cutoff value for identifying depression among diabetic individuals was 5.60, with 70.3% sensitivity and 48.2% specificity, while in diabetic females, it was 6.612, with 70% sensitivity and 61.4% specificity. Conclusion VAI might be the best adiposity index to predict depression among diabetic individuals.

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“…Potential confounders for depression were selected based on previous studies, such as gender, age, race, education level, marital status, family poverty income ratio (PIR), body mass index (BMI), diabetes, failing kidneys, heart failure, coronary heart disease, emphysema, chronic bronchitis, and cancer or malignancy ( 13 ). Race was self-reported, and participants were categorized into Mexican American, non-Hispanic black, non-Hispanic white, Hispanic, and other races.…”

Section: Methodsmentioning

confidence: 99%

A cross-sectional study of smoking and depression among US adults: NHANES (2005–2018)

Zhao

et al. 2023

Front. Public Health

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BackgroundThe relationship between smoking and depression remains controversial. This study aimed to investigate the association between smoking and depression from three aspects: smoking status, smoking volume, and smoking cessation.MethodsData from adults aged ≥20 who participated in the National Health and Nutrition Examination Survey (NHANES) between 2005 and 2018 were collected. The study gathered information about the participants' smoking status (never smokers, previous smokers, occasional smokers, daily smokers), smoking quantity per day, and smoking cessation. Depressive symptoms were assessed using the Patient Health Questionnaire (PHQ-9), with a score ≥10 indicating the presence of clinically relevant symptoms. Multivariable logistic regression was conducted to evaluate the association of smoking status, daily smoking volume, and smoking cessation duration with depression.ResultsPrevious smokers [odds ratio (OR) = 1.25, 95% confidence interval (CI): 1.05–1.48] and occasional smokers (OR = 1.84, 95% CI: 1.39–2.45) were associated with a higher risk of depression compared with never smokers. Daily smokers had the highest risk of depression (OR = 2.37, 95% CI: 2.05–2.75). In addition, a tendency toward a positive correlation was observed between daily smoking volume and depression (OR = 1.65, 95% CI: 1.24–2.19) (P for trend < 0.05). Furthermore, the longer the smoking cessation duration, the lower the risk of depression (OR = 0.55, 95% CI: 0.39–0.79) (P for trend < 0.05).ConclusionsSmoking is a behavior that increases the risk of depression. The higher the smoking frequency and smoking volume, the higher the risk of depression, whereas smoking cessation is associated with decreased risk of depression, and the longer the smoking cessation duration, the lower the risk of depression.

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Visceral Adiposity Index Is a Measure of the Likelihood of Developing Depression Among Adults in the United States

Cited by 19 publications

References 34 publications

The Relationship between Dietary Fat Intake and Depression: A Cross-sectional Study from NHANES 2007–2018

The Relationship between Dietary Fat Intake and Depression: A Cross-sectional Study from NHANES 2007–2018

Predictive value of adiposity index in identifying depression in individuals with type 2 diabetes mellitus in Indian population

A cross-sectional study of smoking and depression among US adults: NHANES (2005–2018)

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