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We investigated the association between serum 25-hydroxyvitamin D (25(OH)D) levels and basal cell carcinoma (BCC) risk in a nested case-control study at Kaiser Permanente Northern California (KPNC). 220 case patients with BCC diagnosed after serum collection were matched to 220 control subjects. We estimated odds ratios (ORs) and 95% confidence intervals (CIs) using conditional logistic regression. Fully adjusted models included body mass index (BMI), smoking, education, sun-exposure variables, x-ray exposure, and personal history of cancer. For each measure of serum 25(OH)D (continuous, clinically relevant tertiles, quintiles), we found an increased risk of BCC in unadjusted models (OR=1.03, 95% CI 1.00–1.05, p<0.05; OR= 3.98, 95% CI: 1.31–12.31, deficient vs. sufficient, test for trend p value <0.01; OR=2.32, 95% CI: 1.20–4.50, 1st vs. 5th quintile, test for trend p value 0.03). In fully adjusted models, the values attenuated slightly (OR=1.02, 95% CI 1.00–1.05, p<0.05; OR= 3.61, 95% CI: 1.00–13.10, deficient vs. sufficient, t-trend p=0.03; OR=2.09 1st vs. 5th quintile, 95% CI: 0.95–4.58, t-trend p=0.11). Our findings suggest that higher pre-diagnostic serum 25(OH)D levels may be associated with increased risk of subsequent BCC. Further studies to evaluate the effect of sun exposure on BCC and serum 25(OH)D levels may be warranted.

BackgroundThe 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.MethodsWe 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.ResultsGlobal 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.ConclusionsWe 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.Electronic supplementary materialThe online version of this article (doi:10.1186/1476-072X-13-48) contains supplementary material, which is available to authorized users.

Datasets from large health maintenance organizations (HMOs), particularly those with established cancer registries that report to the Surveillance, Epidemiology, and End Results program, are potentially excellent resources for studying melanoma epidemiology and outcomes. However, generalizability of the findings beyond HMO-based populations has not been well studied. We compared melanoma patient, tumor, and treatment characteristics at Kaiser Permanente Northern California and Henry Ford Healthcare Systems with those of corresponding regional, state, and national registry-reported melanoma databases. We identified all melanoma cases diagnosed at Kaiser Permanente Northern California (1996-2009) and Henry Ford Healthcare Systems (1996-2007) and ascertained patient (age, sex, race, and ethnicity), tumor (site, size, laterality, invasiveness, depth, ulceration, subtype, and stage), and treatment (surgery and radiation) variables from health system cancer registries. Registry data were obtained from Surveillance, Epidemiology, and End Results databases for the reporting period ending in November 2011. We found that melanoma cases arising in HMO settings generally have comparable patient, tumor, and treatment characteristics to regional, state, and national cases. An important difference included improved reporting of race information at HMO sites. Melanoma studies using data derived from select HMOs are potentially generalizable to local, state, and national populations, and may be better situated for studying racial-ethnic disparities.

The emerging body of research suggests the unprecedented increase in housing foreclosures and unemployment between 2007 and 2009 had detrimental effects on health. Using data from electronic health records of 105,919 patients with diabetes in Northern California, this study examined how increases in foreclosure rates from 2006 to 2010 affected weight change. We anticipated that two of the pathways that explain how the spike in foreclosure rates affects weight gain—increasing stress and declining salutary health behaviors- would be acute in a population with diabetes because of metabolic sensitivity to stressors and health behaviors. Controlling for unemployment, housing prices, temporal trends, and time-invariant confounders with individual fixed effects, we found no evidence of an association between the foreclosure rate in each patient's census block of residence and body mass index. Our results suggest, although more than half of the population was exposed to at least one foreclosure within their census block, the foreclosure crisis did not independently impact weight change.