Higher atherogenic index of plasma is associated with increased major depressive disorder: insights from a nationally representative study

Emerging studies reveal a shared pathophysiological underpinning for metabolic problems and mental illnesses. The present study aimed to determine the association between atherogenic index of plasma (AIP) and the incidence of major depressive disorder (MDD). 7,951 subjects of US adults were collecte...

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Published inFrontiers in psychiatry Vol. 15; p. 1441119
Main Authors Tao, Shiyi, Yu, Lintong, Li, Jun, Huang, Xuanchun, Xue, Tiantian, Yang, Deshuang, Tan, Yuqing
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 10.10.2024
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ISSN1664-0640
1664-0640
DOI10.3389/fpsyt.2024.1441119

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Abstract Emerging studies reveal a shared pathophysiological underpinning for metabolic problems and mental illnesses. The present study aimed to determine the association between atherogenic index of plasma (AIP) and the incidence of major depressive disorder (MDD). 7,951 subjects of US adults were collected from the National Health and Nutrition Examination Survey (NHANES) 2005-2018. MDD was evaluated through the Patient Health Questionnaire (PHQ-9). Multivariate logistic regression, sensitivity analysis, and spline smoothing plot method were used to identify the relationship between AIP and MDD. The cut-off point was calculated using recursive partitioning analysis when segmenting effects emerged. The area under the receiver operating characteristic (ROC) curve (AUC) and Hosmer-Lemeshow test were conducted to evaluate the performance of AIP in identifying MDD. Subgroup analyses and interaction tests were used to explore whether the association was stable in different populations. A positive correlation between AIP and PHQ-9 score and MDD was both observed in 7,951 subjects included in the study, with a significant threshold of -0.42 determined using recursive partitioning analysis. In the fully adjusted model, a positive association between AIP and PHQ-9 score and MDD was observed (β=0.46, 95% CI 0.14~0.78; OR=1.42, 95% CI 1.04~1.93). Individuals in the highest AIP quartile had a 0.39-unit higher PHQ-9 score (β=0.39, 95% CI 0.12~0.66) and a significantly 33% greater risk of MDD than those in the lowest AIP quartile (OR=1.33, 95% CI 1.02~1.73). Spline smoothing plot analysis further confirmed the positive and non-linear association between AIP and PHQ-9 and MDD. ROC analysis (AUC=0.771) and the Hosmer-Lemeshow test (χ = 14.239, =0.076) suggested an excellent performance and goodness-of-fit of the relatively optimal model. DCA and CIC analysis also revealed a favorable overall net benefit and clinical impact of the model. Subgroup analyses and interaction tests revealed that the association between AIP and PHQ-9 score and MDD remained consistent across different subgroups and was not modified by other covariates, and this positive correlation was more pronounced in those with diabetes or hypertension. An elevated AIP is linked to a higher chance of MDD, especially in those with diabetes or hypertension. Resolving dyslipidemia and managing comorbidities may help reduce the likelihood of developing MDD.
AbstractList Emerging studies reveal a shared pathophysiological underpinning for metabolic problems and mental illnesses. The present study aimed to determine the association between atherogenic index of plasma (AIP) and the incidence of major depressive disorder (MDD).BackgroundEmerging studies reveal a shared pathophysiological underpinning for metabolic problems and mental illnesses. The present study aimed to determine the association between atherogenic index of plasma (AIP) and the incidence of major depressive disorder (MDD).7,951 subjects of US adults were collected from the National Health and Nutrition Examination Survey (NHANES) 2005-2018. MDD was evaluated through the Patient Health Questionnaire (PHQ-9). Multivariate logistic regression, sensitivity analysis, and spline smoothing plot method were used to identify the relationship between AIP and MDD. The cut-off point was calculated using recursive partitioning analysis when segmenting effects emerged. The area under the receiver operating characteristic (ROC) curve (AUC) and Hosmer-Lemeshow test were conducted to evaluate the performance of AIP in identifying MDD. Subgroup analyses and interaction tests were used to explore whether the association was stable in different populations.Methods7,951 subjects of US adults were collected from the National Health and Nutrition Examination Survey (NHANES) 2005-2018. MDD was evaluated through the Patient Health Questionnaire (PHQ-9). Multivariate logistic regression, sensitivity analysis, and spline smoothing plot method were used to identify the relationship between AIP and MDD. The cut-off point was calculated using recursive partitioning analysis when segmenting effects emerged. The area under the receiver operating characteristic (ROC) curve (AUC) and Hosmer-Lemeshow test were conducted to evaluate the performance of AIP in identifying MDD. Subgroup analyses and interaction tests were used to explore whether the association was stable in different populations.A positive correlation between AIP and PHQ-9 score and MDD was both observed in 7,951 subjects included in the study, with a significant threshold of -0.42 determined using recursive partitioning analysis. In the fully adjusted model, a positive association between AIP and PHQ-9 score and MDD was observed (β=0.46, 95% CI 0.14~0.78; OR=1.42, 95% CI 1.04~1.93). Individuals in the highest AIP quartile had a 0.39-unit higher PHQ-9 score (β=0.39, 95% CI 0.12~0.66) and a significantly 33% greater risk of MDD than those in the lowest AIP quartile (OR=1.33, 95% CI 1.02~1.73). Spline smoothing plot analysis further confirmed the positive and non-linear association between AIP and PHQ-9 and MDD. ROC analysis (AUC=0.771) and the Hosmer-Lemeshow test (χ2 = 14.239, P=0.076) suggested an excellent performance and goodness-of-fit of the relatively optimal model. DCA and CIC analysis also revealed a favorable overall net benefit and clinical impact of the model. Subgroup analyses and interaction tests revealed that the association between AIP and PHQ-9 score and MDD remained consistent across different subgroups and was not modified by other covariates, and this positive correlation was more pronounced in those with diabetes or hypertension.ResultsA positive correlation between AIP and PHQ-9 score and MDD was both observed in 7,951 subjects included in the study, with a significant threshold of -0.42 determined using recursive partitioning analysis. In the fully adjusted model, a positive association between AIP and PHQ-9 score and MDD was observed (β=0.46, 95% CI 0.14~0.78; OR=1.42, 95% CI 1.04~1.93). Individuals in the highest AIP quartile had a 0.39-unit higher PHQ-9 score (β=0.39, 95% CI 0.12~0.66) and a significantly 33% greater risk of MDD than those in the lowest AIP quartile (OR=1.33, 95% CI 1.02~1.73). Spline smoothing plot analysis further confirmed the positive and non-linear association between AIP and PHQ-9 and MDD. ROC analysis (AUC=0.771) and the Hosmer-Lemeshow test (χ2 = 14.239, P=0.076) suggested an excellent performance and goodness-of-fit of the relatively optimal model. DCA and CIC analysis also revealed a favorable overall net benefit and clinical impact of the model. Subgroup analyses and interaction tests revealed that the association between AIP and PHQ-9 score and MDD remained consistent across different subgroups and was not modified by other covariates, and this positive correlation was more pronounced in those with diabetes or hypertension.An elevated AIP is linked to a higher chance of MDD, especially in those with diabetes or hypertension. Resolving dyslipidemia and managing comorbidities may help reduce the likelihood of developing MDD.ConclusionAn elevated AIP is linked to a higher chance of MDD, especially in those with diabetes or hypertension. Resolving dyslipidemia and managing comorbidities may help reduce the likelihood of developing MDD.
BackgroundEmerging studies reveal a shared pathophysiological underpinning for metabolic problems and mental illnesses. The present study aimed to determine the association between atherogenic index of plasma (AIP) and the incidence of major depressive disorder (MDD).Methods7,951 subjects of US adults were collected from the National Health and Nutrition Examination Survey (NHANES) 2005-2018. MDD was evaluated through the Patient Health Questionnaire (PHQ-9). Multivariate logistic regression, sensitivity analysis, and spline smoothing plot method were used to identify the relationship between AIP and MDD. The cut-off point was calculated using recursive partitioning analysis when segmenting effects emerged. The area under the receiver operating characteristic (ROC) curve (AUC) and Hosmer-Lemeshow test were conducted to evaluate the performance of AIP in identifying MDD. Subgroup analyses and interaction tests were used to explore whether the association was stable in different populations.ResultsA positive correlation between AIP and PHQ-9 score and MDD was both observed in 7,951 subjects included in the study, with a significant threshold of -0.42 determined using recursive partitioning analysis. In the fully adjusted model, a positive association between AIP and PHQ-9 score and MDD was observed (β=0.46, 95% CI 0.14~0.78; OR=1.42, 95% CI 1.04~1.93). Individuals in the highest AIP quartile had a 0.39-unit higher PHQ-9 score (β=0.39, 95% CI 0.12~0.66) and a significantly 33% greater risk of MDD than those in the lowest AIP quartile (OR=1.33, 95% CI 1.02~1.73). Spline smoothing plot analysis further confirmed the positive and non-linear association between AIP and PHQ-9 and MDD. ROC analysis (AUC=0.771) and the Hosmer-Lemeshow test (χ2 = 14.239, P=0.076) suggested an excellent performance and goodness-of-fit of the relatively optimal model. DCA and CIC analysis also revealed a favorable overall net benefit and clinical impact of the model. Subgroup analyses and interaction tests revealed that the association between AIP and PHQ-9 score and MDD remained consistent across different subgroups and was not modified by other covariates, and this positive correlation was more pronounced in those with diabetes or hypertension.ConclusionAn elevated AIP is linked to a higher chance of MDD, especially in those with diabetes or hypertension. Resolving dyslipidemia and managing comorbidities may help reduce the likelihood of developing MDD.
Emerging studies reveal a shared pathophysiological underpinning for metabolic problems and mental illnesses. The present study aimed to determine the association between atherogenic index of plasma (AIP) and the incidence of major depressive disorder (MDD). 7,951 subjects of US adults were collected from the National Health and Nutrition Examination Survey (NHANES) 2005-2018. MDD was evaluated through the Patient Health Questionnaire (PHQ-9). Multivariate logistic regression, sensitivity analysis, and spline smoothing plot method were used to identify the relationship between AIP and MDD. The cut-off point was calculated using recursive partitioning analysis when segmenting effects emerged. The area under the receiver operating characteristic (ROC) curve (AUC) and Hosmer-Lemeshow test were conducted to evaluate the performance of AIP in identifying MDD. Subgroup analyses and interaction tests were used to explore whether the association was stable in different populations. A positive correlation between AIP and PHQ-9 score and MDD was both observed in 7,951 subjects included in the study, with a significant threshold of -0.42 determined using recursive partitioning analysis. In the fully adjusted model, a positive association between AIP and PHQ-9 score and MDD was observed (β=0.46, 95% CI 0.14~0.78; OR=1.42, 95% CI 1.04~1.93). Individuals in the highest AIP quartile had a 0.39-unit higher PHQ-9 score (β=0.39, 95% CI 0.12~0.66) and a significantly 33% greater risk of MDD than those in the lowest AIP quartile (OR=1.33, 95% CI 1.02~1.73). Spline smoothing plot analysis further confirmed the positive and non-linear association between AIP and PHQ-9 and MDD. ROC analysis (AUC=0.771) and the Hosmer-Lemeshow test (χ = 14.239, =0.076) suggested an excellent performance and goodness-of-fit of the relatively optimal model. DCA and CIC analysis also revealed a favorable overall net benefit and clinical impact of the model. Subgroup analyses and interaction tests revealed that the association between AIP and PHQ-9 score and MDD remained consistent across different subgroups and was not modified by other covariates, and this positive correlation was more pronounced in those with diabetes or hypertension. An elevated AIP is linked to a higher chance of MDD, especially in those with diabetes or hypertension. Resolving dyslipidemia and managing comorbidities may help reduce the likelihood of developing MDD.
Author Li, Jun
Yu, Lintong
Tan, Yuqing
Tao, Shiyi
Yang, Deshuang
Huang, Xuanchun
Xue, Tiantian
AuthorAffiliation 3 Department of Integrative Cardiology, China-Japan Friendship Hospital , Beijing , China
2 Graduate School, Beijing University of Chinese Medicine , Beijing , China
1 Department of Cardiology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences , Beijing , China
AuthorAffiliation_xml – name: 1 Department of Cardiology, Guang'anmen Hospital, China Academy of Chinese Medical Sciences , Beijing , China
– name: 2 Graduate School, Beijing University of Chinese Medicine , Beijing , China
– name: 3 Department of Integrative Cardiology, China-Japan Friendship Hospital , Beijing , China
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  givenname: Lintong
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Keywords atherogenic index of plasma
NHANES
major depressive disorder
PHQ-9
dyslipidemia
Language English
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dyslipidemia
major depressive disorder
NHANES
PHQ-9
Psychiatry
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