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Schoenweger P, Kirschneck M, Biersack K, Di Meo AF, Reindl-Spanner P, Prommegger B, Ditzen-Janotta C, Henningsen P, Krcmar H, Gensichen J, Jung-Sievers C. Community indicators for mental health in Europe: a scoping review. Front Public Health 2023; 11:1188494. [PMID: 37538274 PMCID: PMC10396773 DOI: 10.3389/fpubh.2023.1188494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 06/19/2023] [Indexed: 08/05/2023] Open
Abstract
Background Community indicators may predict and influence individuals` mental health, and support or impede mental health management. However, there is no consensus on which indicators should be included in predictions, prognostic algorithms, or management strategies for community-based mental health promotion and prevention approaches. Therefore, this scoping review provides an overview of relevant community-level indicators for mental health in the general as well as risk populations in a European context. Methods We conducted a scoping review in the following electronic databases: PubMed, Embase, and PsycInfo. Eligible studies focused on context factors such as either the physical or social environment, reporting at least one mental health outcome and referring to a European population. Publications between 2012 and March 8, 2022 are considered. Results In total, the search yielded 12,200 identified records. After the removal of duplicates, 10,059 records were screened against the eligibility criteria. In total, 169 studies were included in the final analysis. Out of these included studies, 6% focused on pan-European datasets and 94% on a specific European country. Populations were either general or high-risk populations (56 vs. 44%, respectively) with depressive disorder as the main reported outcome (49%), followed by general mental health (33%) and anxiety (23%). Study designs were cross-sectional studies (59%), longitudinal (27%), and others (14%). The final set of indicators consisted of 53 indicators, which were grouped conceptually into 13 superordinate categories of community indicators. These were divided into the domains of the physical and social environment. The most commonly measured and reported categories of community indicators associated with mental health outcomes were social networks (n = 87), attitudinal factors toward vulnerable groups (n = 76), and the characteristics of the built environment (n = 56). Conclusion This review provides an evidence base of existing and novel community-level indicators that are associated with mental health. Community factors related to the physical and social environment should be routinely recorded and considered as influencing factors or potentially underestimated confounders. The relevance should be analyzed and included in clinical outcomes, data, monitoring and surveillance as they may reveal new trends and targets for public mental health interventions.
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Affiliation(s)
- Petra Schoenweger
- Institute of Medical Data Processing, Biometrics and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Munich, Germany
- Pettenkofer School of Public Health, Munich, Germany
| | - Michaela Kirschneck
- Institute of Medical Data Processing, Biometrics and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Munich, Germany
- Pettenkofer School of Public Health, Munich, Germany
| | - Katharina Biersack
- Department of Psychosomatic Medicine and Psychotherapy, University Hospital, Technical University of Munich, Munich, Germany
| | - Anna-Francesca Di Meo
- Institute of Medical Data Processing, Biometrics and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Munich, Germany
- Pettenkofer School of Public Health, Munich, Germany
| | - Philipp Reindl-Spanner
- TUM School of Computation, Information and Technology, Technical University of Munich, Munich, Germany
| | - Barbara Prommegger
- TUM School of Computation, Information and Technology, Technical University of Munich, Munich, Germany
| | - Claudia Ditzen-Janotta
- Institute of Medical Data Processing, Biometrics and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Munich, Germany
- Pettenkofer School of Public Health, Munich, Germany
| | - Peter Henningsen
- Department of Psychosomatic Medicine and Psychotherapy, University Hospital, Technical University of Munich, Munich, Germany
| | - Helmut Krcmar
- TUM School of Computation, Information and Technology, Technical University of Munich, Munich, Germany
| | - Jochen Gensichen
- Institute of General Practice and Family Medicine, University Hospital of Ludwig-Maximilians-University Munich, Munich, Germany
| | - Caroline Jung-Sievers
- Institute of Medical Data Processing, Biometrics and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Munich, Germany
- Pettenkofer School of Public Health, Munich, Germany
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Filiatreau LM, Ebasone PV, Dzudie A, Ajeh R, Pence BW, Wainberg M, Nash D, Yotebieng M, Anastos K, Pefura-Yone E, Nsame D, Parcesepe AM. Prevalence of stressful life events and associations with symptoms of depression, anxiety, and post-traumatic stress disorder among people entering care for HIV in Cameroon. J Affect Disord 2022; 308:421-431. [PMID: 35452755 PMCID: PMC9520993 DOI: 10.1016/j.jad.2022.04.061] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 01/19/2022] [Accepted: 04/10/2022] [Indexed: 01/04/2023]
Abstract
BACKGROUND Exposure to stressors increases the risk of mental health disorders. People living with HIV (PLWH) are particularly affected by poor mental health which can contribute to adverse HIV treatment outcomes. METHODS We estimated the prevalence of recent stressful life events (modified Life Events Survey) among a cohort of PLWH entering HIV care at three public health care facilities in Cameroon and quantified the association of seven types of stressful life events with symptoms of depression (Patient Health Questionnaire-9 scores>9), anxiety (General Anxiety Disorder-7 scores>9), and PTSD (PTSD Checklist for DSM-5 scores>30) using separate log-binomial regression models. RESULTS Of 426 PLWH enrolling in care, a majority were women (59%), in relationships (58%), and aged 21 to 39 years (58%). Recent death of a family member (39%) and severe illness of a family member (34%) were the most commonly reported stressful life events. In multivariable analyses, more stressful life event types, a negative relationship change, death or illness of a friend/family member, experience of violence, work-related difficulties, and feeling unsafe in one's neighborhood were independently associated with at least one of the mental health outcomes assessed. The greatest magnitude of association was observed between work-related difficulties and PTSD (adjusted prevalence ratio: 3.1; 95% confidence interval: 2.0-4.8). LIMITATIONS Given the design of our study, findings are subject to recall and social desirability bias. CONCLUSIONS Stressful life events were common among this population of PLWH entering care in Cameroon. Evidence-based interventions that improve coping, stress management, and mental health are needed.
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Affiliation(s)
- Lindsey M Filiatreau
- Washington University in St. Louis, School of Medicine, Department of Psychiatry, St. Louis, MO, United States of America; Washington University in St. Louis, Brown School, International Center for Child Health and Development, St. Louis, MO, United States of America; University of North Carolina at Chapel Hill, Carolina Population Center, Chapel Hill, NC, United States of America.
| | | | - Anastase Dzudie
- Clinical Research Education Networking and Consultancy, Yaounde, Cameroon
| | - Rogers Ajeh
- Clinical Research Education Networking and Consultancy, Yaounde, Cameroon
| | - Brian W Pence
- University of North Carolina at Chapel Hill, Gillings School of Global Public Health, Department of Epidemiology, Chapel Hill, NC, United States of America
| | - Milton Wainberg
- Columbia University, Department of Psychiatry, New York, NY, United States of America
| | - Denis Nash
- City University of New York, Institute of Implementation Science in Population Health, New York, NY, United States of America
| | - Marcel Yotebieng
- Albert Einstein College of Medicine, Department of Medicine, Bronx, NY, United States of America
| | - Kathryn Anastos
- Albert Einstein College of Medicine, Department of Medicine, Bronx, NY, United States of America; Albert Einstein College of Medicine, Department of Epidemiology & Population Health, Bronx, NY, United States of America
| | | | - Denis Nsame
- Bamenda Regional Hospital, Bamenda, Cameroon
| | - Angela M Parcesepe
- University of North Carolina at Chapel Hill, Carolina Population Center, Chapel Hill, NC, United States of America; University of North Carolina at Chapel Hill, Gillings School of Global Public Health, Department of Maternal and Child Health, Chapel Hill, NC, United States of America
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