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      Is Neighborhood Green Space Associated With a Lower Risk of Type 2 Diabetes? Evidence From 267,072 Australians

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      Diabetes Care
      American Diabetes Association

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          Abstract

          OBJECTIVE Lifestyle interventions for type 2 diabetes mellitus (T2DM) are best positioned for success if participants live in supportive neighborhood environments. Deprived neighborhoods increase T2DM risk. Parks and other "green spaces" promote active lifestyles and therefore may reduce T2DM risk. We investigated association between neighborhood green space and the risk of T2DM in a large group of adult Australians. RESEARCH DESIGN AND METHODS Multilevel logit regression was used to fit associations between medically diagnosed T2DM and green space exposure among 267,072 participants in the 45 and Up Study. Green space data were obtained from the Australian Bureau of Statistics, and exposure was calculated using a 1-km buffer from a participant's place of residence. Odds ratios (ORs) were controlled for measures of demographic, cultural, health, diet, active lifestyles, socioeconomic status, and neighborhood circumstances. RESULTS The rate of T2DM was 9.1% among participants in neighborhoods with 0-20% green space, but this rate dropped to approximately 8% for participants with over 40% green space within their residential neighborhoods. The risk of T2DM was significantly lower in greener neighborhoods, controlling for demographic and cultural factors, especially among participants residing in neighborhoods with 41-60% green space land use (OR 0.87; 95% CI 0.83-0.92). This association was consistent after controlling for other explanatory variables and did not vary according to neighborhood circumstances. CONCLUSIONS People in greener surroundings have a lower risk of T2DM. Planning, promoting, and maintaining local green spaces is important in multisector initiatives for addressing the T2DM epidemic.

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          Effect of exposure to natural environment on health inequalities: an observational population study.

          Studies have shown that exposure to the natural environment, or so-called green space, has an independent effect on health and health-related behaviours. We postulated that income-related inequality in health would be less pronounced in populations with greater exposure to green space, since access to such areas can modify pathways through which low socioeconomic position can lead to disease. We classified the population of England at younger than retirement age (n=40 813 236) into groups on the basis of income deprivation and exposure to green space. We obtained individual mortality records (n=366 348) to establish whether the association between income deprivation, all-cause mortality, and cause-specific mortality (circulatory disease, lung cancer, and intentional self-harm) in 2001-05, varied by exposure to green space measured in 2001, with control for potential confounding factors. We used stratified models to identify the nature of this variation. The association between income deprivation and mortality differed significantly across the groups of exposure to green space for mortality from all causes (p<0.0001) and circulatory disease (p=0.0212), but not from lung cancer or intentional self-harm. Health inequalities related to income deprivation in all-cause mortality and mortality from circulatory diseases were lower in populations living in the greenest areas. The incidence rate ratio (IRR) for all-cause mortality for the most income deprived quartile compared with the least deprived was 1.93 (95% CI 1.86-2.01) in the least green areas, whereas it was 1.43 (1.34-1.53) in the most green. For circulatory diseases, the IRR was 2.19 (2.04-2.34) in the least green areas and 1.54 (1.38-1.73) in the most green. There was no effect for causes of death unlikely to be affected by green space, such as lung cancer and intentional self-harm. Populations that are exposed to the greenest environments also have lowest levels of health inequality related to income deprivation. Physical environments that promote good health might be important to reduce socioeconomic health inequalities.
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            Investigation of relative risk estimates from studies of the same population with contrasting response rates and designs

            Background There is little empirical evidence regarding the generalisability of relative risk estimates from studies which have relatively low response rates or are of limited representativeness. The aim of this study was to investigate variation in exposure-outcome relationships in studies of the same population with different response rates and designs by comparing estimates from the 45 and Up Study, a population-based cohort study (self-administered postal questionnaire, response rate 18%), and the New South Wales Population Health Survey (PHS) (computer-assisted telephone interview, response rate ~60%). Methods Logistic regression analysis of questionnaire data from 45 and Up Study participants (n = 101,812) and 2006/2007 PHS participants (n = 14,796) was used to calculate prevalence estimates and odds ratios (ORs) for comparable variables, adjusting for age, sex and remoteness. ORs were compared using Wald tests modelling each study separately, with and without sampling weights. Results Prevalence of some outcomes (smoking, private health insurance, diabetes, hypertension, asthma) varied between the two studies. For highly comparable questionnaire items, exposure-outcome relationship patterns were almost identical between the studies and ORs for eight of the ten relationships examined did not differ significantly. For questionnaire items that were only moderately comparable, the nature of the observed relationships did not differ materially between the two studies, although many ORs differed significantly. Conclusions These findings show that for a broad range of risk factors, two studies of the same population with varying response rate, sampling frame and mode of questionnaire administration yielded consistent estimates of exposure-outcome relationships. However, ORs varied between the studies where they did not use identical questionnaire items.
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              Morbidity is related to a green living environment.

              As a result of increasing urbanisation, people face the prospect of living in environments with few green spaces. There is increasing evidence for a positive relation between green space in people's living environment and self-reported indicators of physical and mental health. This study investigates whether physician-assessed morbidity is also related to green space in people's living environment. Morbidity data were derived from electronic medical records of 195 general practitioners in 96 Dutch practices, serving a population of 345,143 people. Morbidity was classified by the general practitioners according to the International Classification of Primary Care. The percentage of green space within a 1 km and 3 km radius around the postal code coordinates was derived from an existing database and was calculated for each household. Multilevel logistic regression analyses were performed, controlling for demographic and socioeconomic characteristics. The annual prevalence rate of 15 of the 24 disease clusters was lower in living environments with more green space in a 1 km radius. The relation was strongest for anxiety disorder and depression. The relation was stronger for children and people with a lower socioeconomic status. Furthermore, the relation was strongest in slightly urban areas and not apparent in very strongly urban areas. This study indicates that the previously established relation between green space and a number of self-reported general indicators of physical and mental health can also be found for clusters of specific physician-assessed morbidity. The study stresses the importance of green space close to home for children and lower socioeconomic groups.
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                Author and article information

                Journal
                Diabetes Care
                Dia Care
                American Diabetes Association
                0149-5992
                1935-5548
                December 19 2013
                January 2014
                January 2014
                September 11 2013
                : 37
                : 1
                : 197-201
                Article
                10.2337/dc13-1325
                24026544
                501d8e01-08af-43d3-b7be-1e6863c9e6f2
                © 2013
                History

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