Variety ACEs and risk of developing anxiety, depression, or anxiety-depression co-morbidity: the 2006–2022 UK Biobank data
ObjectivesAdverse childhood experiences (ACEs) and anxiety-depression co-morbidity are attracting widespread attention. Previous studies have shown the relationship between individual psychiatric disorders and ACEs. This study will analyze the correlation between anxiety-depression co-morbidity and...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-12-01
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| Series: | Frontiers in Psychiatry |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1233981/full |
| _version_ | 1797367268151132160 |
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| author | Peilin Yu Zhou Jiang Chu Zheng Chu Zheng Chu Zheng Chu Zheng Chu Zheng Ping Zeng Ping Zeng Ping Zeng Ping Zeng Ping Zeng Lihong Huang Yingliang Jin Yingliang Jin Yingliang Jin Yingliang Jin Yingliang Jin Ke Wang Ke Wang Ke Wang Ke Wang Ke Wang |
| author_facet | Peilin Yu Zhou Jiang Chu Zheng Chu Zheng Chu Zheng Chu Zheng Chu Zheng Ping Zeng Ping Zeng Ping Zeng Ping Zeng Ping Zeng Lihong Huang Yingliang Jin Yingliang Jin Yingliang Jin Yingliang Jin Yingliang Jin Ke Wang Ke Wang Ke Wang Ke Wang Ke Wang |
| author_sort | Peilin Yu |
| collection | DOAJ |
| description | ObjectivesAdverse childhood experiences (ACEs) and anxiety-depression co-morbidity are attracting widespread attention. Previous studies have shown the relationship between individual psychiatric disorders and ACEs. This study will analyze the correlation between anxiety-depression co-morbidity and different levels of ACEs.MethodsSeven categories of ACE and four classifications of psychiatric disorders were defined in a sample of 126,064 participants identified by the UK Biobank from 2006–2022, and correlations were investigated using logistic regression models. Then, to explore nonlinear relationships, restricted spline models were developed to examine differences in sex and age across cohorts (n = 126,064 for the full cohort and n = 121,934 for the European cohort). Finally, the impact of the category of ACEs on psychiatric disorders was examined.ResultsAfter controlling for confounders, ACEs scores showed dose-dependent relationships with depression, anxiety, anxiety-depression co-morbidity, and at least one (any of the first three outcomes) in all models. ACEs with different scores were significantly positively correlated with the four psychiatric disorders classifications, with the highest odds of anxiety-depression co-morbidity (odds ratio [OR] = 4.87, 95% confidence intervals [CI]: 4.37 ~ 5.43), p = 6.08 × 10−178. In the restricted cubic spline models, the risk was relatively flat for females at ACEs = 0–1 and males at ACEs = 0–2/3 (except in males, where ACEs were associated with a lower risk of anxiety, all other psychiatric disorders had an increased risk of morbidity after risk smoothing). In addition, the risk of having anxiety, depression, anxiety-depression co-morbidity, and at least one of these disorders varies with each category of ACEs.ConclusionThe prevalence of anxiety-depression comorbidity was highest across ACE scores after controlling for confounding factors and had a significant effect on each category of ACEs. |
| first_indexed | 2024-03-08T17:14:56Z |
| format | Article |
| id | doaj.art-8393cc1f8e7441038f1e6f4ffbd264ad |
| institution | Directory Open Access Journal |
| issn | 1664-0640 |
| language | English |
| last_indexed | 2024-03-08T17:14:56Z |
| publishDate | 2023-12-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Psychiatry |
| spelling | doaj.art-8393cc1f8e7441038f1e6f4ffbd264ad2024-01-03T13:47:52ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402023-12-011410.3389/fpsyt.2023.12339811233981Variety ACEs and risk of developing anxiety, depression, or anxiety-depression co-morbidity: the 2006–2022 UK Biobank dataPeilin Yu0Zhou Jiang1Chu Zheng2Chu Zheng3Chu Zheng4Chu Zheng5Chu Zheng6Ping Zeng7Ping Zeng8Ping Zeng9Ping Zeng10Ping Zeng11Lihong Huang12Yingliang Jin13Yingliang Jin14Yingliang Jin15Yingliang Jin16Yingliang Jin17Ke Wang18Ke Wang19Ke Wang20Ke Wang21Ke Wang22Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaDepartment of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaDepartment of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaKey Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaKey Lab of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaCenter for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaJiangsu Engineering Research Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaDepartment of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaKey Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaKey Lab of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaCenter for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaJiangsu Engineering Research Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaDepartment of Biostatistics, Zhongshan Hospital, Fudan University, Shanghai, ChinaDepartment of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaKey Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaKey Lab of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaCenter for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaJiangsu Engineering Research Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaDepartment of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaKey Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaKey Lab of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaCenter for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaJiangsu Engineering Research Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaObjectivesAdverse childhood experiences (ACEs) and anxiety-depression co-morbidity are attracting widespread attention. Previous studies have shown the relationship between individual psychiatric disorders and ACEs. This study will analyze the correlation between anxiety-depression co-morbidity and different levels of ACEs.MethodsSeven categories of ACE and four classifications of psychiatric disorders were defined in a sample of 126,064 participants identified by the UK Biobank from 2006–2022, and correlations were investigated using logistic regression models. Then, to explore nonlinear relationships, restricted spline models were developed to examine differences in sex and age across cohorts (n = 126,064 for the full cohort and n = 121,934 for the European cohort). Finally, the impact of the category of ACEs on psychiatric disorders was examined.ResultsAfter controlling for confounders, ACEs scores showed dose-dependent relationships with depression, anxiety, anxiety-depression co-morbidity, and at least one (any of the first three outcomes) in all models. ACEs with different scores were significantly positively correlated with the four psychiatric disorders classifications, with the highest odds of anxiety-depression co-morbidity (odds ratio [OR] = 4.87, 95% confidence intervals [CI]: 4.37 ~ 5.43), p = 6.08 × 10−178. In the restricted cubic spline models, the risk was relatively flat for females at ACEs = 0–1 and males at ACEs = 0–2/3 (except in males, where ACEs were associated with a lower risk of anxiety, all other psychiatric disorders had an increased risk of morbidity after risk smoothing). In addition, the risk of having anxiety, depression, anxiety-depression co-morbidity, and at least one of these disorders varies with each category of ACEs.ConclusionThe prevalence of anxiety-depression comorbidity was highest across ACE scores after controlling for confounding factors and had a significant effect on each category of ACEs.https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1233981/fullACEsanxiety-depression co-morbidityUK Biobankrestricted cubic splinesex |
| spellingShingle | Peilin Yu Zhou Jiang Chu Zheng Chu Zheng Chu Zheng Chu Zheng Chu Zheng Ping Zeng Ping Zeng Ping Zeng Ping Zeng Ping Zeng Lihong Huang Yingliang Jin Yingliang Jin Yingliang Jin Yingliang Jin Yingliang Jin Ke Wang Ke Wang Ke Wang Ke Wang Ke Wang Variety ACEs and risk of developing anxiety, depression, or anxiety-depression co-morbidity: the 2006–2022 UK Biobank data Frontiers in Psychiatry ACEs anxiety-depression co-morbidity UK Biobank restricted cubic spline sex |
| title | Variety ACEs and risk of developing anxiety, depression, or anxiety-depression co-morbidity: the 2006–2022 UK Biobank data |
| title_full | Variety ACEs and risk of developing anxiety, depression, or anxiety-depression co-morbidity: the 2006–2022 UK Biobank data |
| title_fullStr | Variety ACEs and risk of developing anxiety, depression, or anxiety-depression co-morbidity: the 2006–2022 UK Biobank data |
| title_full_unstemmed | Variety ACEs and risk of developing anxiety, depression, or anxiety-depression co-morbidity: the 2006–2022 UK Biobank data |
| title_short | Variety ACEs and risk of developing anxiety, depression, or anxiety-depression co-morbidity: the 2006–2022 UK Biobank data |
| title_sort | variety aces and risk of developing anxiety depression or anxiety depression co morbidity the 2006 2022 uk biobank data |
| topic | ACEs anxiety-depression co-morbidity UK Biobank restricted cubic spline sex |
| url | https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1233981/full |
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