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Studies on neighbourhood characteristics and depression show equivocal results.
This large-scale pooled analysis examines whether urbanisation, socioeconomic, physical and social neighbourhood characteristics are associated with the prevalence and severity of depression.
Cross-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.
The 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.
This 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.
To identify a high-sugar (HS) dietary pattern, a high-saturated-fat (HF) dietary pattern and a combined high-sugar and high-saturated-fat (HSHF) dietary pattern and to explore if these dietary patterns are associated with depressive symptoms.
We used data from the HELIUS (Healthy Life in an Urban Setting) study and included 4969 individuals aged 18–70 years. Diet was assessed using four ethnic-specific FFQ. Dietary patterns were derived using reduced rank regression with mono- and disaccharides, saturated fat and total fat as response variables. The nine-item Patient Health Questionnaire (PHQ-9) was used to assess depressive symptoms by using continuous scores and depressed mood (identified using the cut-off point: PHQ-9 sum score ≥10).
Three dietary patterns were identified; an HSHF dietary pattern (including chocolates, red meat, added sugars, high-fat dairy products, fried foods, creamy sauces), an HS dietary pattern (including sugar-sweetened beverages, added sugars, fruit (juices)) and an HF dietary pattern (including high-fat dairy products, butter). When comparing extreme quartiles, consumption of an HSHF dietary pattern was associated with more depressive symptoms (Q1 v. Q4: β=0·18, 95 % CI 0·07, 0·30, P=0·001) and with higher odds of depressed mood (Q1 v. Q4: OR=2·36, 95 % CI 1·19, 4·66, P=0·014). No associations were found between consumption of the remaining dietary patterns and depressive symptoms.
Higher consumption of an HSHF dietary pattern is associated with more depressive symptoms and with depressed mood. Our findings reinforce the idea that the focus should be on dietary patterns that are high in both sugar and saturated fat.
To test Koctürk’s model of dietary change among South-Asian Surinamese in the Netherlands. The model categorizes foods into staple, complementary and accessory foods and postulates that dietary change after migration begins with accessory foods while foods associated with ethnic identity (staple foods) change at a slower rate.
Cross-sectional data from the HELIUS study. Dietary intake was assessed with an FFQ. Acculturation was based on social contacts and sense of belonging and was translated into four strategies of acculturation: assimilation, integration, separation and marginalization. Other indicators of acculturation included residence duration, age at migration and migration generation status.
Amsterdam, the Netherlands.
Participants of Dutch (n 1456) and South-Asian Surinamese origin (n 968).
Across all acculturation strategies, South-Asian Surinamese participants reported significantly higher intakes of rice (staple food) and chicken (complementary food) and significantly lower intakes of red meat and vegetables (complementary foods) and cookies and sweets (accessory food) than Dutch participants. Men, second-generation and assimilated South-Asian Surinamese were inclined towards Dutch foods such as potato, pasta and red meat. Accessory foods like fruits showed variation across acculturation strategies.
Consistent with the Koctürk model, the intake of staple foods was stable among South-Asian Surinamese irrespective of acculturation strategy while the intake of accessory foods like fruit varied. Contrary to expectations, South-Asian Surinamese showed consistently high intakes of complementary foods like chicken and fish irrespective of acculturation strategy. Public health practitioners should take into consideration the complex and dynamic nature of dietary acculturation.
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