Obesity and the food environment: income and ethnicity differences among people with diabetes: the Diabetes Study of Northern California (DISTANCE).

ObjectiveIt is unknown whether any association between neighborhood food environment and obesity varies according to individual income and/or race/ethnicity. The objectives of this study were to test whether there was an association between food environments and obesity among adults with diabetes and whether this relationship differed according to individual income or race/ethnicity.Research design and methodsSubjects (n = 16,057) were participants in the Diabetes Study of Northern California survey. Kernel density estimation was used to create a food environment score for each individual's residence address that reflected the mix of healthful and unhealthful food vendors nearby. Logistic regression models estimated the association between the modeled food environment and obesity, controlling for confounders, and testing for interactions between food environment and race/ethnicity and income.ResultsThe authors found that more healthful food environments were associated with lower obesity in the highest income groups (incomes 301-600% and >600% of U.S. poverty line) among whites, Latinos, and Asians. The association was negative, but smaller and not statistically significant, among high-income blacks. On the contrary, a more healthful food environment was associated with higher obesity among participants in the lowest-income group (<100% poverty threshold), which was statistically significant for black participants in this income category.ConclusionsThese findings suggest that the availability of healthful food environments may have different health implications when financial resources are severely constrained

Language Barriers, Physician-Patient Language Concordance, and Glycemic Control Among Insured Latinos with Diabetes: The Diabetes Study of Northern California (DISTANCE)

BackgroundA significant proportion of US Latinos with diabetes have limited English proficiency (LEP). Whether language barriers in health care contribute to poor glycemic control is unknown.ObjectiveTo assess the association between limited English proficiency (LEP) and glycemic control and whether this association is modified by having a language-concordant physician.DesignCross-sectional, observational study using data from the 2005-2006 Diabetes Study of Northern California (DISTANCE). Patients received care in a managed care setting with interpreter services and self-reported their English language ability and the Spanish language ability of their physician. Outcome was poor glycemic control (glycosylated hemoglobin A1c > 9%).Key resultsThe unadjusted percentage of patients with poor glycemic control was similar among Latino patients with LEP (n = 510) and Latino English-speakers (n = 2,683), and higher in both groups than in whites (n = 3,545) (21% vs 18% vs. 10%, p < 0.005). This relationship differed significantly by patient-provider language concordance (p < 0.01 for interaction). LEP patients with language-discordant physicians (n = 115) were more likely than LEP patients with language-concordant physicians (n = 137) to have poor glycemic control (27.8% vs 16.1% p = 0.02). After controlling for potential demographic and clinical confounders, LEP Latinos with language-concordant physicians had similar odds of poor glycemic control as Latino English speakers (OR 0.89; CI 0.53-1.49), whereas LEP Latinos with language-discordant physicians had greater odds of poor control than Latino English speakers (OR 1.76; CI 1.04-2.97). Among LEP Latinos, having a language discordant physician was associated with significantly poorer glycemic control (OR 1.98; CI 1.03-3.80).ConclusionsLanguage barriers contribute to health disparities among Latinos with diabetes. Limited English proficiency is an independent predictor for poor glycemic control among insured US Latinos with diabetes, an association not observed when care is provided by language-concordant physicians. Future research should determine if strategies to increase language-concordant care improve glycemic control among US Latinos with LEP

Potential Risk Factors for Cutaneous Squamous Cell Carcinoma include Oral Contraceptives: Results of a Nested Case-Control Study

Recently, a population-based case-control study observed a 60% increased odds ratio (OR) for cutaneous squamous cell carcinoma (SCC) among women who had ever used oral contraceptives (OCs) compared with non users (95% confidence interval (CI) = 1.0–2.5). To further characterize the putative association between OC use and SCC risk, we conducted a nested case-control study using a large retrospective cohort of 111,521 Kaiser Permanente Northern California members. Multivariable conditional logistic regression was used to estimate ORs and CIs adjusting for known and hypothesized SCC risk factors. Pre-diagnostic OC use was associated with a statistically significant increased OR for SCC in univariate analysis (OR = 2.4, CI = 1.2–4.8), with borderline statistical significance in multivariable analysis (CI = 2.0, CI = 0.91–4.5). Given the high incidence of SCC in the general population and the prevalent use of OCs among women in the United States, there is a need for more large, carefully designed epidemiologic studies to determine whether the observed association between OC use and SCC can be replicated and to better understand the etiologic basis of an association if one exists

Neighborhood deprivation and change in BMI among adults with type 2 diabetes: the Diabetes Study of Northern California (DISTANCE).

ObjectiveTo compare associations between neighborhood deprivation and measures of BMI change among adults with type 2 diabetes.Research design and methodsUsing data from the Kaiser Permanente Diabetes Study of Northern California (DISTANCE) survey, we estimated the association between neighborhood deprivation and two measures of BMI change over 3 years: 1) a continuous measure and 2) a categorical measure of clinically substantive BMI loss or gain (≥7% of baseline BMI) versus stable BMI. The sample included 13,609 adults.ResultsOn average, there was little change in BMI (-0.12, SD 3.07); 17.0 and 16.1% had clinically substantive BMI loss or gain, respectively, at follow-up. There was a positive association between neighborhood deprivation and BMI change for adults in the most versus least-deprived quartile of neighborhood deprivation (β = 0.22, P = 0.02) in adjusted models. In addition, relative to the least-deprived quartile (Q1), adults in more-deprived quartiles of neighborhood deprivation were more likely to experience either substantive BMI loss (Q2 relative risk ratio 1.19, 95% CI 1.00-1.41; Q3 1.20, 1.02-1.42; Q4 1.30, 1.08-1.55) or gain (Q2 1.25, 1.04-1.49; Q3 1.24, 1.04-1.49; Q4 1.45, 1.20-1.75).ConclusionsGreater neighborhood deprivation was positively associated with BMI change among adults with diabetes as well as with clinically substantive BMI loss or gain. Findings stress the importance of allowing for simultaneous associations with both gain and loss in future longitudinal studies of neighborhood deprivation and weight change, which may be particularly true for studies of patients with diabetes for whom both weight loss and gain have health implications

The DISTANCE model for collaborative research: distributing analytic effort using scrambled data sets.

BackgroundData-sharing is encouraged to fulfill the ethical responsibility to transform research data into public health knowledge, but data sharing carries risks of improper disclosure and potential harm from release of individually identifiable data.MethodsThe study objective was to develop and implement a novel method for scientific collaboration and data sharing which distributes the analytic burden while protecting patient privacy. A procedure was developed where in an investigator who is external to an analytic coordinating center (ACC) can conduct original research following a protocol governed by a Publications and Presentations (P&P) Committee. The collaborating investigator submits a study proposal and, if approved, develops the analytic specifications using existing data dictionaries and templates. An original data set is prepared according to the specifications and the external investigator is provided with a complete but de-identified and shuffled data set which retains all key data fields but which obfuscates individually identifiable data and patterns; this" scrambled data set" provides a "sandbox" for the external investigator to develop and test analytic code for analyses. The analytic code is then run against the original data at the ACC to generate output which is used by the external investigator in preparing a manuscript for journal submission.ResultsThe method has been successfully used with collaborators to produce many published papers and conference reports.ConclusionBy distributing the analytic burden, this method can facilitate collaboration and expand analytic capacity, resulting in more science for less money