Latent depressive profiles and associated factors among overweight/obese individuals based on the socio-ecological model: a cross-sectional national survey in China
BackgroundOverweight/obesity is associated with an increased risk of depression, which compromises the mental health of affected individuals. This study aimed to identify distinct depressive subtypes among overweight/obese individuals and examine associated multilevel factors based on the socio-ecol...
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| Format: | Article |
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Frontiers Media S.A.
2025-08-01
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| Series: | Frontiers in Psychology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyg.2025.1644701/full |
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| author | Xiaoping Yang Miaomiao Chen Xiaohui Liu Lijun Wang Yanyun Wang Yingjie Zheng Shailing Ma |
| author_facet | Xiaoping Yang Miaomiao Chen Xiaohui Liu Lijun Wang Yanyun Wang Yingjie Zheng Shailing Ma |
| author_sort | Xiaoping Yang |
| collection | DOAJ |
| description | BackgroundOverweight/obesity is associated with an increased risk of depression, which compromises the mental health of affected individuals. This study aimed to identify distinct depressive subtypes among overweight/obese individuals and examine associated multilevel factors based on the socio-ecological model (SEM), for guiding interventions enhancing mental health in this population.MethodsData were derived from the Psychology and Behavior Investigation of Chinese Residents in 2021 (PBICR 2021). Assessment instruments included a General Information Questionnaire, the Patient Health Questionnaire-9, the Eating Behavior Scale-Short Form, the Family Health Scale-Short Form, and the Perceived Social Support Scale. Latent profile analysis (LPA) was employed to identify depressive subtypes, and multinomial logistic regression was used to examine associated multilevel factors across the identified subtypes. Analyses were conducted using SPSS 24.0 and Mplus 8.3.ResultsThis study included 2,588 participants classified into low-level (52.3%), moderate-level (36.6%), and high-level depression (11.1%) groups. Compared to the low-level group, high-level depression was significantly associated with age (18–45 years), current medication count (≥3, excl. supplements), out-of-pocket medical expenditures, higher abnormal eating behavior scores, and lower family health and social support scores. Similarly, moderate-level depression showed significant associations with female gender, age (18–45 years), having chronic conditions, current medication count (≥3, excl. supplements), out-of-pocket medical expenditures, higher abnormal eating behavior scores, and lower family health and social support scores.ConclusionDepression demonstrates significant heterogeneity in overweight/obese individuals, with three distinct latent profiles identified. These findings highlight the need for future primary healthcare to prioritize personalized, depression subtype-specific interventions for overweight/obese individuals, guided by multidimensional factors identified through SEM, to improve mental health. |
| format | Article |
| id | doaj-art-4a86a8d4e99b49aeb35230b6aa14dcda |
| institution | Kabale University |
| issn | 1664-1078 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychology |
| spelling | doaj-art-4a86a8d4e99b49aeb35230b6aa14dcda2025-08-20T03:43:54ZengFrontiers Media S.A.Frontiers in Psychology1664-10782025-08-011610.3389/fpsyg.2025.16447011644701Latent depressive profiles and associated factors among overweight/obese individuals based on the socio-ecological model: a cross-sectional national survey in ChinaXiaoping Yang0Miaomiao Chen1Xiaohui Liu2Lijun Wang3Yanyun Wang4Yingjie Zheng5Shailing Ma6General Hospital of Ningxia Medical University, Yinchuan, Ningxia, ChinaSchool of Nursing, Ningxia Medical University, Yinchuan, Ningxia, ChinaSchool of Nursing, Ningxia Medical University, Yinchuan, Ningxia, ChinaSchool of Nursing, Ningxia Medical University, Yinchuan, Ningxia, ChinaGeneral Hospital of Ningxia Medical University, Yinchuan, Ningxia, ChinaSchool of Nursing, Ningxia Medical University, Yinchuan, Ningxia, ChinaSchool of Nursing, Ningxia Medical University, Yinchuan, Ningxia, ChinaBackgroundOverweight/obesity is associated with an increased risk of depression, which compromises the mental health of affected individuals. This study aimed to identify distinct depressive subtypes among overweight/obese individuals and examine associated multilevel factors based on the socio-ecological model (SEM), for guiding interventions enhancing mental health in this population.MethodsData were derived from the Psychology and Behavior Investigation of Chinese Residents in 2021 (PBICR 2021). Assessment instruments included a General Information Questionnaire, the Patient Health Questionnaire-9, the Eating Behavior Scale-Short Form, the Family Health Scale-Short Form, and the Perceived Social Support Scale. Latent profile analysis (LPA) was employed to identify depressive subtypes, and multinomial logistic regression was used to examine associated multilevel factors across the identified subtypes. Analyses were conducted using SPSS 24.0 and Mplus 8.3.ResultsThis study included 2,588 participants classified into low-level (52.3%), moderate-level (36.6%), and high-level depression (11.1%) groups. Compared to the low-level group, high-level depression was significantly associated with age (18–45 years), current medication count (≥3, excl. supplements), out-of-pocket medical expenditures, higher abnormal eating behavior scores, and lower family health and social support scores. Similarly, moderate-level depression showed significant associations with female gender, age (18–45 years), having chronic conditions, current medication count (≥3, excl. supplements), out-of-pocket medical expenditures, higher abnormal eating behavior scores, and lower family health and social support scores.ConclusionDepression demonstrates significant heterogeneity in overweight/obese individuals, with three distinct latent profiles identified. These findings highlight the need for future primary healthcare to prioritize personalized, depression subtype-specific interventions for overweight/obese individuals, guided by multidimensional factors identified through SEM, to improve mental health.https://www.frontiersin.org/articles/10.3389/fpsyg.2025.1644701/fullbody mass indexdepressiondepressive subtypesmultilevel factorsmental health |
| spellingShingle | Xiaoping Yang Miaomiao Chen Xiaohui Liu Lijun Wang Yanyun Wang Yingjie Zheng Shailing Ma Latent depressive profiles and associated factors among overweight/obese individuals based on the socio-ecological model: a cross-sectional national survey in China Frontiers in Psychology body mass index depression depressive subtypes multilevel factors mental health |
| title | Latent depressive profiles and associated factors among overweight/obese individuals based on the socio-ecological model: a cross-sectional national survey in China |
| title_full | Latent depressive profiles and associated factors among overweight/obese individuals based on the socio-ecological model: a cross-sectional national survey in China |
| title_fullStr | Latent depressive profiles and associated factors among overweight/obese individuals based on the socio-ecological model: a cross-sectional national survey in China |
| title_full_unstemmed | Latent depressive profiles and associated factors among overweight/obese individuals based on the socio-ecological model: a cross-sectional national survey in China |
| title_short | Latent depressive profiles and associated factors among overweight/obese individuals based on the socio-ecological model: a cross-sectional national survey in China |
| title_sort | latent depressive profiles and associated factors among overweight obese individuals based on the socio ecological model a cross sectional national survey in china |
| topic | body mass index depression depressive subtypes multilevel factors mental health |
| url | https://www.frontiersin.org/articles/10.3389/fpsyg.2025.1644701/full |
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