Neighbourhood characteristics and prevalence and severity of depression: pooled analysis of eight Dutch cohort studies

Abstract

BackgroundStudies on neighbourhood characteristics and depression show equivocal results. AimsThis large-scale pooled analysis examines whether urbanisation, socioeconomic, physical and social neighbourhood characteristics are associated with the prevalence and severity of depression. MethodCross-sectional design including data are from eight Dutch cohort studies (n = 32 487). Prevalence of depression, either DSM-IV diagnosis of depressive disorder or scoring for moderately severe depression on symptom scales, and continuous depression severity scores were analysed. Neighbourhood characteristics were linked using postal codes and included (a) urbanisation grade, (b) socioeconomic characteristics: socioeconomic status, home value, social security beneficiaries and non-Dutch ancestry, (c) physical characteristics: air pollution, traffic noise and availability of green space and water, and (d) social characteristics: social cohesion and safety. Multilevel regression analyses were adjusted for the individual's age, gender, educational level and income. Cohort-specific estimates were pooled using random-effects analysis. ResultsThe pooled analysis showed that higher urbanisation grade (odds ratio (OR) = 1.05, 95% CI 1.01-1.10), lower socioeconomic status (OR = 0.90, 95% CI 0.87-0.95), higher number of social security beneficiaries (OR = 1.12, 95% CI 1.06-1.19), higher percentage of non-Dutch residents (OR = 1.08, 95% CI 1.02-1.14), higher levels of air pollution (OR = 1.07, 95% CI 1.01-1.12), less green space (OR = 0.94, 95% CI 0.88-0.99) and less social safety (OR = 0.92, 95% CI 0.88-0.97) were associated with higher prevalence of depression. All four socioeconomic neighbourhood characteristics and social safety were also consistently associated with continuous depression severity scores. ConclusionsThis large-scale pooled analysis across eight Dutch cohort studies shows that urbanisation and various socioeconomic, physical and social neighbourhood characteristics are associated with depression, indicating that a wide range of environmental aspects may relate to poor mental health. Declaration of interestNone.

Auswirkungen von Umweltrisikofaktoren wie Lärm und Luftverschmutzung auf die psychische Gesundheit: Was wissen wir?

“…In 3 aktuellen niederländischen Studien wurde der Zusammenhang zwischen Verkehrslärm und dem Vorhandensein von Depressionen und Angststörungen untersucht [28][29][30]. Leijssen et al zeigten, dass Straßenverkehrslärmexposition mit erhöhter Wahrscheinlichkeit einer bestehenden depressiven Verstimmung einhergeht (n = 23 293; OR 1,65; 95 %-KI 1,10-2,48 beim Vergleich von ≥ 70 vs. 45-54 dB(A) L den ), die unabhängig von ethnischen und sozioökonomischen Ungleichheiten zwischen den Expositionsgruppen war [28].…”

“…mit einer OR von 1,29 (95 %-KI 1,11-1,50) für eine bestehende Angststörung pro Zunahme um 3,21 dB(A) L den assoziiert [29]. Die gepoolte Analyse von 8 niederländischen Kohortenstudien (n = 32 487) ergab eine OR von 1,05 (95 %-KI 0,96-1,15) für den Zusammenhang zwischen Verkehrslärm und einer prävalenten Depression, wobei hier kritisch angemerkt werden muss, dass in der Hälfte der eingeschlossenen Studien die Bestimmung der Verkehrslärmpegel 1-2 Jahre später erfolgte als die Erfassung der Depression [30]. Zudem war in derselben Studie das Ausmaß der Luftverschmutzung mit dem Auftreten von Depressionen assoziiert (OR 1,07; 95 %-KI 1,01-1,12).…”

The Longitudinal Aging Study Amsterdam: cohort update 2019 and additional data collections

“…The main environmental data that are currently available in LASA are shown in Table 6 and include: urbanization grade (i.e., number of residents/km 2 ), population demographics (e.g., age-and sex-distribution, marital status and proportions of immigrants and ethnic minority groups), household characteristics (e.g., average household size), educational level (e.g., proportions of individuals who attained high, intermediate or low education), income (e.g., average income and proportion of income recipients), socioeconomic status (e.g., socioeconomic status score), social security (e.g., proportion of social security beneficiaries), air pollution (e.g., concentrations of air pollutants), noise (e.g., road-traffic, rail-traffic and air-traffic noise), crime rates (e.g., number of criminal offenses per 1000 residents), availability of facilities (e.g., in terms of density of/proximity to specific health care facilities and socio-cultural facilities), physical environmental characteristics (e.g., green space and water) and daily average weather parameters (e.g., daily average temperature and humidity). Several of these variables have been used in recent LASA studies [35,[37][38][39][40][41].…”

Overview of “Systematic Reviews” of the Built Environment’s Effects on Mental Health

“…Studies about the relationship between built environments and mental health have reported that a state of wellbeing, response to stressors, the ability to work productively, and to make contributions to the community all can be affected by factors such as the quality of public utilities, walking distance to public spaces, access to transport, and level of infrastructure [8,[12][13][14][15][16][17]. Generaal et al reported through analysis across eight Dutch cohort studies that urbanization is associated with depression, indicating that a wide range of environmental aspects may relate to poor mental health [18].…”