European journal of medical research · 2026
Shaped association between cardiometabolic index and depressive symptoms: a population-based cross section study of U.S. adults.
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Yu Zhihong, Li Wei, Wang Meng, Wang Shu, Yu Chao
Аннотация
BACKGROUND: Research reports on the relationship between cardiometabolic index (CMI) and depressive symptoms are limited. This study aimed to evaluate the possible relationship between CMI and depressive symptoms.
METHODS: We conducted a cross-sectional analysis of adults from the National Health and Nutrition Examination Survey (NHANES). Participants aged ≥ 18 years with complete data on CMI and depressive symptoms from the 2007-2018 cycles were included (n = 7965). Depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9) with a score ≥ 10 as the cut-off. Multivariable logistic regression models were used to assess the association. Restricted cubic splines (RCS) and logistic regression were employed to explore nonlinearity and identify inflection points. Subgroup analyses were performed to examine effect modification.
RESULTS: Of 7965 individuals, 637 (8%) had depressive symptoms, while hypertension and stroke are present in 3039 (38.15%) and 216 (2.71%), respectively. A multivariable logistic regression model observed that When LnCMI is employed as a classification variable, no significant association between them can be observed. A dose-response fitting curve find that there is a nonlinear J-shaped association between LnCMI and depressive symptoms. A two-piecewise logistic regression model to analyze their relationship, which we observed that CMI on the left side of the cut-off point was not associated with depressive symptoms prevalence. However, among patients with LnCMI ≥ -2, there was a positive association between LnCMI and depressive symptoms prevalence (OR 1.92; 95% CI 1.40-2.64). Subgroup analysis revealed that only BMI had a moderating effect on the association between CMI and depressive symptoms (OR:2.37,95% CI 1.53-3.67; P for interaction = 0.017).
CONCLUSION: Our research findings suggest a strong association between higher CMI levels and increased prevalence of depressive symptoms, particularly among American adults with BMI ≥ 25 kg/m2. We further revealed a turning point by threshold effect analysis.
METHODS: We conducted a cross-sectional analysis of adults from the National Health and Nutrition Examination Survey (NHANES). Participants aged ≥ 18 years with complete data on CMI and depressive symptoms from the 2007-2018 cycles were included (n = 7965). Depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9) with a score ≥ 10 as the cut-off. Multivariable logistic regression models were used to assess the association. Restricted cubic splines (RCS) and logistic regression were employed to explore nonlinearity and identify inflection points. Subgroup analyses were performed to examine effect modification.
RESULTS: Of 7965 individuals, 637 (8%) had depressive symptoms, while hypertension and stroke are present in 3039 (38.15%) and 216 (2.71%), respectively. A multivariable logistic regression model observed that When LnCMI is employed as a classification variable, no significant association between them can be observed. A dose-response fitting curve find that there is a nonlinear J-shaped association between LnCMI and depressive symptoms. A two-piecewise logistic regression model to analyze their relationship, which we observed that CMI on the left side of the cut-off point was not associated with depressive symptoms prevalence. However, among patients with LnCMI ≥ -2, there was a positive association between LnCMI and depressive symptoms prevalence (OR 1.92; 95% CI 1.40-2.64). Subgroup analysis revealed that only BMI had a moderating effect on the association between CMI and depressive symptoms (OR:2.37,95% CI 1.53-3.67; P for interaction = 0.017).
CONCLUSION: Our research findings suggest a strong association between higher CMI levels and increased prevalence of depressive symptoms, particularly among American adults with BMI ≥ 25 kg/m2. We further revealed a turning point by threshold effect analysis.