Inner-city green space and its association with body mass index and prevalent type 2 diabetes: a cross-sectional study in an urban German city.

OBJECTIVE: The 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. DESIGN: Population-based cross-sectional study. SETTING: Dortmund, a city located in the industrial Ruhr area in Western Germany. PARTICIPANTS: 1312 participants aged 25-74 years from the Dortmund Health Study. METHODS: The 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. RESULTS: The 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). CONCLUSIONS: This 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.

Impact of major depressive disorder, distinct subtypes, and symptom severity on lifestyle in the BiDirect Study.

The aim of this study was to examine associations of major depressive disorder (MDD), its distinct subtypes, and symptom severity with the individual lifestyle factors smoking, diet quality, physical activity, and body mass index as well as with a combined lifestyle index measuring the co-occurrence of these lifestyle factors. A sample of 823 patients with MDD and 597 non-depressed controls was examined. The psychiatric assessment was based on a clinical interview including the Mini International Neuropsychiatric Interview and the Hamilton Depression Rating Scale. Each lifestyle factor was scored as either healthy or unhealthy, and the number of unhealthy lifestyle factors was added up in a combined lifestyle index. Cross-sectional analyses were performed using alternating logistic regression and ordinal logistic regression, adjusted for socio-demographic characteristics. After adjustment, MDD was significantly associated with smoking, low physical activity, and overweight. Likewise, MDD was significantly related to the overall lifestyle index. When stratifying for subtypes, all subtypes showed higher odds for an overall unhealthier lifestyle than controls, but the associations with the individual lifestyle factors were partly different. Symptom severity was associated with the lifestyle index in a dose-response manner. In conclusion, patients with MDD represent an important target group for lifestyle interventions.

Association between major depressive disorder and odor identification impairment.

BACKGROUND: There is evidence of olfactory deficits in patients with major depressive disorder (MDD) but causes and mechanisms are largely unknown. METHODS: We compared 728 patients with current MDD and 555 non-depressed controls regarding odor identification impairment taking into account the severity of acute symptoms and of the disease course. We assessed current symptom severity with the Hamilton Depression Rating Scale, and disease course severity based on admission diagnosis (ICD-10, F32/F33) and self-reported hospitalization frequency, defined as infrequent (<2) and frequent (≥2) depression-related hospitalizations under constant disease duration. A score of <10 on the Sniffin' Sticks-Screen-12 test determined the presence of odor identification impairment. RESULTS: Compared to non-depressed controls patients with frequent (rapidly recurring) hospitalizations had an elevated chance of odor identification impairment, even after adjustment for smell-influencing factors, such as age and smoking, (OR=1.7; 95% CI 1.0-2.9). Patients with recurrent MDD (F33) also had an elevated odds of odor identification impairment compared to those with a first-time episode (F32, OR=1.5; 95% CI 1.0-2.4). In patients with a first-time episode the chance of odor identification impairment increased by 7% with each point increase in the Hamilton Score. LIMITATIONS: Cross-sectional study. Variation in the use of psychotropic medication is a potential bias. CONCLUSION: Odor identification impairment was evident in MDD patients with first-time high symptom severity and in patients with a severe disease course. Whether odor identification impairment is a marker or mediator of structural and functional brain changes associated with acute or active MDD requires further investigations in longitudinal studies.

Associations between poor sleep quality and different measures of obesity.

OBJECTIVE: Poor sleep may be a risk factor for obesity. Previous studies have mainly investigated the effects of sleep duration on body mass index, but research considering overall sleep quality and other anthropometric measures is scarce. The aim of this study was to examine the association between sleep quality and different measures of obesity (general obesity, abdominal obesity, body composition) in a population-based sample of adults. METHODS: The study included 753 participants aged 35-65 years from the BiDirect Study, conducted in Münster, Germany. Participants completed the Pittsburgh Sleep Quality Index (PSQI) on sleep characteristics. Weight, height, and waist circumference were measured by trained study nurses. Body composition (fat mass and fat-free mass) was assessed using bioelectrical impedance analysis. The cross-sectional relationship between sleep quality and measures of obesity was investigated using logistic regression analysis. RESULTS: Among the participants, 65.3% reported good (PSQI ≤ 5) and 34.7% poor (PSQI > 5) sleep quality. We observed a significant association of poorer sleep quality assessed by the continuous PSQI score with general obesity and high body fat (for both, odds ratio = 1.07, 95% confidence interval = 1.01-1.13), adjusted for socio-demographic and lifestyle factors. Further adjustment for depressive symptoms and somatic comorbidities attenuated the relationship. The observed association was mainly driven by the PSQI components sleep latency, sleep disturbances, and daytime dysfunction. CONCLUSIONS: The present study suggests that poor sleep quality may predict obesity and high body fat mass among adults. However, a causal relationship still has to be confirmed by prospective studies with objective measurements of sleep and obesity.

Associations between depression subtypes, depression severity and diet quality: cross-sectional findings from the BiDirect Study.

BACKGROUND: Depression 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. METHODS: The 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). RESULTS: We 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. CONCLUSIONS: Previous 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.

Dietary patterns and the risk of depression in adults: a systematic review of observational studies.

PURPOSE: Diet, a modifiable lifestyle factor, may influence the development of depression. We performed a systematic review of observational studies examining the relationship between dietary patterns and depression in healthy adults. METHODS: A literature research was conducted searching various electronic databases up to May 2013. Study selection was based on predefined inclusion and exclusion criteria. Included studies were reviewed, and relevant data were extracted by two independent researchers. Due to a high level of heterogeneity, no meta-analysis was conducted. Therefore, main results are presented in a descriptive way. RESULTS: In total, 16 studies met the inclusion criteria and are part of this review. Dietary patterns most commonly found were traditional/healthy patterns, Western/unhealthy patterns and Mediterranean patterns. The available literature suggests a protective effect of healthy and Mediterranean patterns, as well as a potential positive association of Western patterns and depression. However, comparison of the included studies was difficult, due to differences in relevant study characteristics and methodological limitations. CONCLUSIONS: 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.