There are indications that dietary patterns may have influence on the onset of depression, but no firm conclusion can be drawn at this point. Further research is needed to clarify the diet-depression relationship, preferably in the form of methodological strong prospective studies using more homogeneous methods.

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BackgroundDepression is supposed to be associated with an unhealthy lifestyle including poor diet. The objective of this study was to investigate differences in diet quality between patients with a clinical diagnosis of depression and population-based controls. Additionally, we aimed to examine effects of specific depression characteristics on diet by analyzing if diet quality varies between patients with distinct depression subtypes, and if depression severity is associated with diet quality.MethodsThe study included 1660 participants from the BiDirect Study (n = 840 patients with depression, n = 820 population-based controls). The psychiatric assessment was based on clinical interviews and a combination of depression scales in order to provide the classification of depression subtypes and severity. Diet quality scores, reflecting the adherence to a healthy dietary pattern, were calculated on the basis of an 18-item food frequency questionnaire. Using analysis of covariance, we calculated adjusted means of diet quality scores and tested differences between groups (adjusted for socio-demographic, lifestyle-, and health-related factors).ResultsWe found no differences in diet quality between controls and patients with depression if depression was considered as one entity. However, we did find differences between patients with distinct subtypes of depression. Patients with melancholic depression reported the highest diet quality scores, whereas patients with atypical depression reported the lowest scores. Depression severity was not associated with diet quality.ConclusionsPrevious literature has commonly treated depression as a homogeneous entity. However, subtypes of depression may be associated with diet quality in different ways. Further studies are needed to enlighten the diet-depression relationship and the role of distinct depression subtypes.Electronic supplementary materialThe online version of this article (doi:10.1186/s12888-015-0426-9) contains supplementary material, which is available to authorized users.

ObjectiveThe accessibility of green space is an important aspect of the urban residential environment and has been found to be beneficial for health and well-being. This study investigates the association between different indicators of green space and the outcomes body mass index (BMI) and prevalent type 2 diabetes in an urban population.DesignPopulation-based cross-sectional study.SettingDortmund, a city located in the industrial Ruhr area in Western Germany.Participants1312 participants aged 25–74 years from the Dortmund Health Study.MethodsThe participants’ addresses were geocoded and shapefiles of statistical districts, road network and land use, as well as data on neighbourhood characteristics were obtained at baseline. Three indicators of green space were constructed using geographical information systems: proportion of green space, recreation location quotient (RLQ) weighted by population and distance to the next park or forest. Multilevel linear and logistic regression analyses on the association of green space with BMI and type 2 diabetes were performed, adjusted by individual-level characteristics and neighbourhood unemployment rate.ResultsThe multilevel regression analyses showed no association between green space and BMI. In contrast, the three indicators of green space were significantly associated with type 2 diabetes. Residents of neighbourhoods with a low RLQ had a 2.44 (95% CI 1.01 to 5.93) times higher odds to have type 2 diabetes compared with residents of high RLQ neighbourhoods. Likewise, residing more than 0.8 km away from the nearest park or forest increased the odds of type 2 diabetes (OR 1.71, 95% CI 1.05 to 2.77).ConclusionsThis study indicates that green space and its spatial accessibility might play a role in the development of type 2 diabetes. Further research is needed to clarify this association.

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