Metabolic syndrome patterns by gender in major depressive disorder

Major depressive disorder (MDD) and metabolic syndrome (MetS) are significant health challenges, with distinct gender-specific manifestations. This suggests that the clinical presentation of MetS within the MDD cohort may also vary by gender. The objective of this study is to explore these gender-specific clinical patterns in the co-occurrence of MetS among hospitalized MDD patients, thereby offering insights and guidance for targeted interventions aimed at managing MetS in this demographic. The study included 1,281 first hospitalization MDD patients. Data were collected on socio-demographic characteristics and general clinical profiles. Metabolic parameters, routine biochemical markers, and psychological symptoms were measured and analyzed. The prevalence of MetS was 8.21% in male patients and 10.34% in female patients, with no significant difference between genders. Gender-specific risk factors were identified: in males, age and anxiety symptoms were significant predictors of MetS, while in females, age at onset and married were linked to the development of MetS. Additionally, MetS severity was influenced by age at onset in males and by both age at onset and married in females. This study found no gender-specific prevalence of MetS in hospitalized MDD patients. However, gender-specific factors influencing MetS development and severity highlight the need for focused management in older, married females and older males with high anxiety symptoms.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2024-12-04
DOI
https://doi.org/10.1371/journal.pone.0313629
Citations
3
Primary Topic
Cardiac Health and Mental Health
Type
article
Field-Weighted Citation Impact
1.21
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Metabolic syndrome patterns by gender in major depressive disorder

Lin Zhang, Li Lü, Ling Xiong, Zhihua Liu
3 citations
PLoS ONE
Cardiac Health and Mental Health
1.21
article

Metabolic syndrome patterns by gender in major depressive disorder

Lin Zhang, Li Lü, Ling Xiong, Zhihua Liu
article en
3 citations

Abstract

Major depressive disorder (MDD) and metabolic syndrome (MetS) are significant health challenges, with distinct gender-specific manifestations. This suggests that the clinical presentation of MetS within the MDD cohort may also vary by gender. The objective of this study is to explore these gender-specific clinical patterns in the co-occurrence of MetS among hospitalized MDD patients, thereby offering insights and guidance for targeted interventions aimed at managing MetS in this demographic. The study included 1,281 first hospitalization MDD patients. Data were collected on socio-demographic characteristics and general clinical profiles. Metabolic parameters, routine biochemical markers, and psychological symptoms were measured and analyzed. The prevalence of MetS was 8.21% in male patients and 10.34% in female patients, with no significant difference between genders. Gender-specific risk factors were identified: in males, age and anxiety symptoms were significant predictors of MetS, while in females, age at onset and married were linked to the development of MetS. Additionally, MetS severity was influenced by age at onset in males and by both age at onset and married in females. This study found no gender-specific prevalence of MetS in hospitalized MDD patients. However, gender-specific factors influencing MetS development and severity highlight the need for focused management in older, married females and older males with high anxiety symptoms.

PLoS ONEVol. 19(12)
Hubei University of Chinese Medicine (CN), The Fourth People's Hospital (CN)
Good health and well-being
Openalex Percentile: Top 17%
Cardiac Health and Mental Health
1.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.