Darío Moreno-Agostino1, Yu-Tzu Wu2, Christina Daskalopoulou2, M Tasdik Hasan3, Martijn Huisman4, Matthew Prina2. 1. Department of Health Service and Population Research, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK. Electronic address: dario.moreno@kcl.ac.uk. 2. Department of Health Service and Population Research, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK. 3. Department of Health Service and Population Research, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK; Department of Psychological Sciences, University of Liverpool, UK. 4. Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands; Department of Sociology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Abstract
BACKGROUND: There is mixed evidence regarding the change in the prevalence of depression in the general population over time. This study aimed to synthesise the evidence on studies that use equivalent approaches in equivalent populations across different time points. METHODS: A systematic review was conducted to identify studies focused on the change over time in depression incidence and prevalence in the general population. A random-effects meta-analysis was performed to obtain a pooled effect for the change in the prevalence estimates between the first and last time points considered. Subgroup and meta-regression analyses were used to ascertain differences in the effect sizes by gender, age group, prevalence type, elapsed time between cross-sections, and depression operationalisation. RESULTS: 19 studies provided information on the change in depression prevalence over time, whereas none provided such information regarding incidence. The pooled odds ratio (OR) and confidence interval (CI) were estimated by using 17 studies: OR=1.35 (95% CI: 1.14, 1.61). Similar pooled effects were obtained for females and males, separately. The high heterogeneity across studies was not explained by any of the design variables considered. No evidence for publication bias was found. LIMITATIONS: The review included published articles up to August 2018, and the information of studies with more than two time points was summarised in a single estimate of change. CONCLUSIONS: There is a predominant increasing trend in the likelihood of experiencing depression over time that seems not to be explainable by study design differences or publication bias alone.
BACKGROUND: There is mixed evidence regarding the change in the prevalence of depression in the general population over time. This study aimed to synthesise the evidence on studies that use equivalent approaches in equivalent populations across different time points. METHODS: A systematic review was conducted to identify studies focused on the change over time in depression incidence and prevalence in the general population. A random-effects meta-analysis was performed to obtain a pooled effect for the change in the prevalence estimates between the first and last time points considered. Subgroup and meta-regression analyses were used to ascertain differences in the effect sizes by gender, age group, prevalence type, elapsed time between cross-sections, and depression operationalisation. RESULTS: 19 studies provided information on the change in depression prevalence over time, whereas none provided such information regarding incidence. The pooled odds ratio (OR) and confidence interval (CI) were estimated by using 17 studies: OR=1.35 (95% CI: 1.14, 1.61). Similar pooled effects were obtained for females and males, separately. The high heterogeneity across studies was not explained by any of the design variables considered. No evidence for publication bias was found. LIMITATIONS: The review included published articles up to August 2018, and the information of studies with more than two time points was summarised in a single estimate of change. CONCLUSIONS: There is a predominant increasing trend in the likelihood of experiencing depression over time that seems not to be explainable by study design differences or publication bias alone.
Authors: Mathias V Schmidt; Jan M Deussing; Iven-Alex von Mücke-Heim; Lidia Urbina-Treviño; Joeri Bordes; Clemens Ries Journal: Mol Psychiatry Date: 2022-09-14 Impact factor: 13.437
Authors: Roosje Walrave; Simon Gabriël Beerten; Pavlos Mamouris; Kristien Coteur; Marc Van Nuland; Gijs Van Pottelbergh; Lidia Casas; Bert Vaes Journal: BMC Prim Care Date: 2022-06-28
Authors: Tran B Huynh; Vanessa M Oddo; Bricia Trejo; Kari Moore; D Alex Quistberg; Jannie J Kim; Francisco Diez-Canseco; Alejandra Vives Journal: SSM Popul Health Date: 2022-04-20