Dataset Information

Spatial pattern of body mass index among adults in the diabetes study of Northern California (DISTANCE).

ABSTRACT:

Background

The role that environmental factors, such as neighborhood socioeconomics, food, and physical environment, play in the risk of obesity and chronic diseases is not well quantified. Understanding how spatial distribution of disease risk factors overlap with that of environmental (contextual) characteristics may inform health interventions and policies aimed at reducing the environment risk factors. We evaluated the extent to which spatial clustering of extreme body mass index (BMI) values among a large sample of adults with diabetes was explained by individual characteristics and contextual factors.

Methods

We quantified spatial clustering of BMI among 15,854 adults with diabetes from the Diabetes Study of Northern California (DISTANCE) cohort using the Global and Local Moran's I spatial statistic. As a null model, we assessed the amount of clustering when BMI values were randomly assigned. To evaluate predictors of spatial clustering, we estimated two linear models to estimate BMI residuals. First we included individual factors (demographic and socioeconomic characteristics). Then we added contextual factors (neighborhood deprivation, food environment) that may be associated with BMI. We assessed the amount of clustering that remained using BMI residuals.

Results

Global Moran's I indicated significant clustering of extreme BMI values; however, after accounting for individual socioeconomic and demographic characteristics, there was no longer significant clustering. Twelve percent of the sample clustered in extreme high or low BMI clusters, whereas, only 2.67% of the sample was clustered when BMI values were randomly assigned. After accounting for individual characteristics, we found clustering of 3.8% while accounting for neighborhood characteristics resulted in 6.0% clustering of BMI. After additional adjustment of neighborhood characteristics, clustering was reduced to 3.4%, effectively accounting for spatial clustering of BMI.

Conclusions

We found substantial clustering of extreme high and low BMI values in Northern California among adults with diabetes. Individual characteristics explained somewhat more of clustering of the BMI values than did neighborhood characteristics. These findings, although cross-sectional, may suggest that selection into neighborhoods as the primary explanation of why individuals with extreme BMI values live close to one another. Further studies are needed to assess causes of extreme BMI clustering, and to identify any community level role to influence behavior change.

SUBMITTER: Laraia BA

PROVIDER: S-EPMC4320620 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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Publications

Spatial pattern of body mass index among adults in the diabetes study of Northern California (DISTANCE).

Laraia Barbara A BA Blanchard Samuel D SD Karter Andrew J AJ Jones-Smith Jessica C JC Warton Margaret M Kersten Ellen E Jerrett Michael M Moffet Howard H HH Adler Nancy N Schillinger Dean D Kelly Maggi M

International journal of health geographics 20141204

<h4>Background</h4>The role that environmental factors, such as neighborhood socioeconomics, food, and physical environment, play in the risk of obesity and chronic diseases is not well quantified. Understanding how spatial distribution of disease risk factors overlap with that of environmental (contextual) characteristics may inform health interventions and policies aimed at reducing the environment risk factors. We evaluated the extent to which spatial clustering of extreme body mass index (BM ...[more]

PMID: 25471753

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Project description:BackgroundPrevious studies have reported that health literacy limitations are associated with poorer disease control for chronic conditions, but have not evaluated potential associations with medication adherence.ObjectiveTo determine whether health literacy limitations are associated with poorer antidepressant medication adherence.DesignObservational new prescription cohort follow-up study.ParticipantsAdults with type 2 diabetes who completed a survey in 2006 and received a new antidepressant prescription during 2006-2010 (N?=?1,366) at Kaiser Permanente Northern California.Main measuresValidated three-item self-report scale measured health literacy. Discrete indices of adherence based on pharmacy dispensing data according to validated methods: primary non-adherence (medication never dispensed); early non-persistence (dispensed once, never refilled); non-persistence at 180 and 365 days; and new prescription medication gap (NPMG; proportion of time that the person is without medication during 12 months after the prescription date).Key resultsSeventy-two percent of patients were classified as having health literacy limitations. After adjusting for sociodemographic and clinical covariates, patients with health literacy limitations had significantly poorer adherence compared to patients with no limitations, whether measured as early non-persistence (46 % versus 38 %, p?<?0.05), non-persistence at 180 days (55 % versus 46 %, p?<?0.05), or NPMG (41 % versus 36%, p?<?0.01). There were no significant associations with primary adherence or non-persistence at 365 days.ConclusionsPoorer antidepressant adherence among adults with diabetes and health literacy limitations may jeopardize the continuation and maintenance phases of depression pharmacotherapy. Findings underscore the importance of national efforts to address health literacy, simplify health communications regarding treatment options, improve public understanding of depression treatment, and monitor antidepressant adherence.

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Project description:BackgroundThe effect of urban sprawl on body weight in Finland is not well known. To provide more information, we examined whether body mass index (BMI) and the prevalence of overweight are associated with an individual's distance to the local community centre and population density in his/her resident area.MethodsThe sample consisted of 5363 men and women, members of the Northern Finland Birth Cohort 1966 (NFBC), who filled in a postal questionnaire and attended a medical checkup in 1997, at the age of 31 years. Body mass index (BMI; kg/m(2)) and the prevalence of overweight (BMI ? 25.0 kg/m(2)) were regressed on each subject's road distance to the resident commune's centre and on population density in the 1 km(2) geographical grid in which he/she resided, using a generalized additive model. Adjustments were made for sex, marital status, occupational class, education, leisure-time and occupational physical activity, alcohol consumption and smoking.ResultsThe mean BMI among the subjects was 24.7 kg/m(2), but it increased by increasing road distance (by 1.3 kg/m(2) from 5-10 to 20-184 km) and by decreasing population density (by 1.7 kg/m(2) from 1000-19,192 to 1-5 inhabitants/km(2)). The respective increases in overweight (overall prevalence 41%) were 13 per cent units for distance and 14 per cent units for population density. Adjusted regressions based on continuous explanatory variables showed an inverse L-shaped pattern with a mean BMI of 24.6 kg/m(2) at distances shorter than 5 km and a rise of 2.6 kg/m(2) at longer distances, and an increase of 2.5 kg/m(2) from highest to lowest population density. The associations with road distance were stronger for women than men, while the sex difference in association with population density remained indeterminate.ConclusionsWe conclude that young adults in Northern Finland who live far away from local centres or in the most sparsely populated areas are fatter than those who live close to local centres or in densely populated areas. The likely explanations include variations in everyday physical activity in different residential environments, although causality of the associations remains to be confirmed.

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Dataset Information

Spatial pattern of body mass index among adults in the diabetes study of Northern California (DISTANCE).

Background

Methods

Results

Conclusions

Publications

Spatial pattern of body mass index among adults in the diabetes study of Northern California (DISTANCE).

Similar Datasets

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