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State-Issued Identification Cards Reveal Patterns in Adult Weight Status.

Morris DS, Main EC, Harris JK, Moland A, Cude C - Int J Environ Res Public Health (2015)

Bottom Line: Together, home values, education, race, ethnicity, car commuting, and rural-urban commuting area (RUCA) explained 86% of the variation in BMI among tracts.BMI was lower in areas with higher home values and greater educational attainment, and higher in areas with more workers commuting by car.This demonstrates state-issued identification cards are a promising data source for BMI surveillance and may offer new insight into the association between weight status and economic and environmental factors.

View Article: PubMed Central - PubMed

Affiliation: School of Community Health, Portland State University, Portland, OR 97201, USA. dmorris@pdx.edu.

ABSTRACT

Background: State-issued identification cards are a promising data source for neighborhood-level obesity estimates.

Methods: We used information from three million Oregon state-issued identification cards to compute age-adjusted estimates of average adult body mass index (BMI) for each census tract in the state. We used multivariate linear regression to identify associations between weight status and population characteristics, food access, commuting behavior, and geography.

Results: Together, home values, education, race, ethnicity, car commuting, and rural-urban commuting area (RUCA) explained 86% of the variation in BMI among tracts. BMI was lower in areas with higher home values and greater educational attainment, and higher in areas with more workers commuting by car.

Discussion: Our findings are consistent with other research on socioeconomic disparities in obesity. This demonstrates state-issued identification cards are a promising data source for BMI surveillance and may offer new insight into the association between weight status and economic and environmental factors. Public health agencies should explore options for developing their own obesity estimates from identification card data.

No MeSH data available.


Related in: MedlinePlus

(a) Average BMI by Census tract, Portland metropolitan area; (b) Median home value; (c) Percent of adults 25 years and older without a college diploma.
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ijerph-12-06388-f002: (a) Average BMI by Census tract, Portland metropolitan area; (b) Median home value; (c) Percent of adults 25 years and older without a college diploma.

Mentions: The statewide regression models explained most of the observed variation in BMI (R2 = 0.85 for women, R2 = 0.81 for men) (Table 2). Median home value was the single strongest predictor of BMI, with the effect about three times as strong among women as men. As expected, BMI estimates were higher in less affluent areas. For every $100,000 median home value increased, women’s average BMI was 0.45 kg/m2 lower. These results are consistent with Drewnoski, Rehm, and Solet’s study on obesity in the Seattle, Washington area [11]. We found home value explained more of the variance in BMI than did measures of income and poverty, which were not retained in the final models. BMI was also higher in areas where educational attainment was lower; this effect was more pronounced among women. The relationship between BMI and socioeconomic status was striking. In the Portland area, average BMI, median home value, and educational attainment show very similar patterns. (Figure 2).


State-Issued Identification Cards Reveal Patterns in Adult Weight Status.

Morris DS, Main EC, Harris JK, Moland A, Cude C - Int J Environ Res Public Health (2015)

(a) Average BMI by Census tract, Portland metropolitan area; (b) Median home value; (c) Percent of adults 25 years and older without a college diploma.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4483708&req=5

ijerph-12-06388-f002: (a) Average BMI by Census tract, Portland metropolitan area; (b) Median home value; (c) Percent of adults 25 years and older without a college diploma.
Mentions: The statewide regression models explained most of the observed variation in BMI (R2 = 0.85 for women, R2 = 0.81 for men) (Table 2). Median home value was the single strongest predictor of BMI, with the effect about three times as strong among women as men. As expected, BMI estimates were higher in less affluent areas. For every $100,000 median home value increased, women’s average BMI was 0.45 kg/m2 lower. These results are consistent with Drewnoski, Rehm, and Solet’s study on obesity in the Seattle, Washington area [11]. We found home value explained more of the variance in BMI than did measures of income and poverty, which were not retained in the final models. BMI was also higher in areas where educational attainment was lower; this effect was more pronounced among women. The relationship between BMI and socioeconomic status was striking. In the Portland area, average BMI, median home value, and educational attainment show very similar patterns. (Figure 2).

Bottom Line: Together, home values, education, race, ethnicity, car commuting, and rural-urban commuting area (RUCA) explained 86% of the variation in BMI among tracts.BMI was lower in areas with higher home values and greater educational attainment, and higher in areas with more workers commuting by car.This demonstrates state-issued identification cards are a promising data source for BMI surveillance and may offer new insight into the association between weight status and economic and environmental factors.

View Article: PubMed Central - PubMed

Affiliation: School of Community Health, Portland State University, Portland, OR 97201, USA. dmorris@pdx.edu.

ABSTRACT

Background: State-issued identification cards are a promising data source for neighborhood-level obesity estimates.

Methods: We used information from three million Oregon state-issued identification cards to compute age-adjusted estimates of average adult body mass index (BMI) for each census tract in the state. We used multivariate linear regression to identify associations between weight status and population characteristics, food access, commuting behavior, and geography.

Results: Together, home values, education, race, ethnicity, car commuting, and rural-urban commuting area (RUCA) explained 86% of the variation in BMI among tracts. BMI was lower in areas with higher home values and greater educational attainment, and higher in areas with more workers commuting by car.

Discussion: Our findings are consistent with other research on socioeconomic disparities in obesity. This demonstrates state-issued identification cards are a promising data source for BMI surveillance and may offer new insight into the association between weight status and economic and environmental factors. Public health agencies should explore options for developing their own obesity estimates from identification card data.

No MeSH data available.


Related in: MedlinePlus