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Obesity in the USA has been linked to individual income and education. Less is known about its geographic distribution. The goal of this study was to determine whether obesity rates in King County, Seattle, Washington state, at the ZIP code scale were associated with area-based measures of socioeconomic status and wealth. Data from the Behavioral Risk Factor Surveillance System were analyzed. At the ZIP code scale, crude obesity rates varied six-fold. In a model adjusting for covariates and spatial dependence, property values were the strongest predictor of the area-based smoothed obesity prevalence. Geocoding of health data provides new insights into the nature of social determinants of health. Disparities in obesity rates by ZIP code area were greater than disparities associated with individual income or race/ethnicity.

To compare asthma and bronchiolitis hospitalization rates in American Indian and Alaskan native (AI/AN) children and all children in Washington State. Methods: A retrospective data analysis using Washington State hospitalization data for 1987 through 1996. Patients were included if asthma or bronchiolitis was the first-listed diagnosis. American Indian and Alaskan native children were identified by linking state hospitalization data with Indian Health Service enrollment data. Results: Similar rates of asthma hospitalization were found for AI/AN children older than 1 year compared with all children. In AI/AN children younger than 1 year, hospitalization rates for asthma (528 per 100 000 population; 95% confidence interval [CI], 346-761) and bronchiolitis (2954 per 100000 population; 95% CI, 2501-3456) were 2 to 3 times higher than the rates in all children (232 per 100000 population [95% CI, 215-251] and 1190 per 100 000 population [95% CI, 1149-1232], respectively). Hospitalization rates for asthma and bronchiolitis increased 50% between 1987 and 1996 for all children younger than 1 year and almost doubled for AI/AN children younger than 1 year. Conclusions: American Indian and Alaskan native children have significantly higher rates of hospitalization for wheezing illnesses during the first year of life compared with children of other age groups and races. Furthermore, the disparities in rates have increased significantly over time. Future public health measures directed at managing asthma and bronchiolitis should target AI/AN infants.

IntroductionKing County, Washington, fares well overall in many health indicators. However, county-level data mask disparities among subcounty areas. For disparity-focused assessment, a demand exists for examining health data at subcounty levels such as census tracts and King County health reporting areas (HRAs).MethodsWe added a “nearest intersection” question to the Behavioral Risk Factor Surveillance System (BRFSS) and geocoded the data for subcounty geographic areas, including census tracts. To overcome small sample size at the census tract level, we used hierarchical Bayesian models to obtain smoothed estimates in cigarette smoking rates at the census tract and HRA levels. We also used multiple imputation to adjust for missing values in census tracts.ResultsDirect estimation of adult smoking rates at the census tract level ranged from 0% to 56% with a median of 10%. The 90% confidence interval (CI) half-width for census tract with nonzero rates ranged from 1 percentage point to 37 percentage points with a median of 13 percentage points. The smoothed-multiple–imputation rates ranged from 5% to 28% with a median of 12%. The 90% CI half-width ranged from 4 percentage points to 13 percentage points with a median of 8 percentage points.ConclusionThe nearest intersection question in the BRFSS provided geocoded data at subcounty levels. The Bayesian model provided estimation with improved precision at the census tract and HRA levels. Multiple imputation can be used to account for missing geographic data. Small-area estimation, which has been used for King County public health programs, has increasingly become a useful tool to meet the demand of presenting data at more granular levels.

Perchloroethylene (PCE) is a widely used dry cleaning and degreasing solvent. Although there is evidence in animals and humans for renal effects at extremely high doses, there are few studies of its potential renal toxicity at typical occupational concentrations. This study reports on the relationship of PCE in breath and estimates of chronic exposure with the urinary ratios of total urinary protein, albumin, and n-acetyl-glucosaminidase (NAG) to creatinine in dry cleaning workers exposed to PCE. Regression models including one or more exposure variables, demographic variables, mean arterial blood pressure (MAP), and the presence of diseases affecting kidney function were examined.Urine samples, breath samples, exposure histories, and medical histories were obtained from 192 dry cleaning workers. The results failed to demonstrate any consistent relationship between exposure and renal outcome variables. However, proteinlcreatinine and albumidcreatinine were significantly, although weakly and positively, associated with MAP; NAGJcreatinine was weakly but significantly positively associated with age; mean NAGkreatinine was also higher in non-whites. The reasons why an association between exposure and renal outcome was not found are discussed.