Faculty Bibliography

We conducted a cross-sectional study to evaluate the interrelationships between past arsenic exposure, biomarkers specific for susceptibility to arsenic exposure, and carotid intima-media thickness (cIMT) in 959 subjects from the Health Effects of Arsenic Longitudinal Study in Bangladesh. We measured cIMT levels on average 7.2 years after baseline during 2010-2011. Arsenic exposure was measured in well water at baseline and in urine samples collected at baseline and during follow-up. Every 1-standard-deviation increase in urinary arsenic (357.9 microg/g creatinine) and well-water arsenic (102.0 microg/L) concentration was related to a 11.7-microm (95% confidence interval (CI): 1.8, 21.6) and 5.1-microm (95% CI: -0.2, 10.3) increase in cIMT, respectively. For every 10% increase in monomethylarsonic acid (MMA) percentage, there was an increase of 12.1 microm (95% CI: 0.4, 23.8) in cIMT. Among participants with a higher urinary MMA percentage, a higher ratio of urinary MMA to inorganic arsenic, and a lower ratio of dimethylarsinic acid to MMA, the association between well-water arsenic and cIMT was stronger. The findings indicate an effect of past long-term arsenic exposure on cIMT, which may be potentiated by suboptimal or incomplete arsenic methylation capacity. Future prospective studies are needed to confirm the association between arsenic methylation capacity and atherosclerosis-related outcomes.

BACKGROUND: To induce consumers to purchase healthier foods and beverages, some policymakers have suggested special taxes or labels on unhealthy products. The potential of such policies is unknown. PURPOSE: In a controlled field experiment, researchers tested whether consumers were more likely to purchase healthy products under such policies. METHODS: From October to December 2011, researchers opened a store at a large hospital that sold a variety of healthier and less-healthy foods and beverages. Purchases (N=3680) were analyzed under five conditions: a baseline with no special labeling or taxation, a 30% tax, highlighting the phrase "less healthy" on the price tag, and combinations of taxation and labeling. Purchases were analyzed in January-July 2012, at the single-item and transaction levels. RESULTS: There was no significant difference between the various taxation conditions. Consumers were 11 percentage points more likely to purchase a healthier item under a 30% tax (95% CI=7%, 16%, p<0.001) and 6 percentage points more likely under labeling (95% CI=0%, 12%, p=0.04). By product type, consumers switched away from the purchase of less-healthy food under taxation (9 percentage point decrease, p<0.001) and into healthier beverages (6 percentage point increase, p=0.001); there were no effects for labeling. Conditions were associated with the purchase of 11-14 fewer calories (9%-11% in relative terms) and 2 fewer grams of sugar. Results remained significant controlling for all items purchased in a single transaction. CONCLUSIONS: Taxation may induce consumers to purchase healthier foods and beverages. However, it is unclear whether the 15%-20% tax rates proposed in public policy discussions would be more effective than labeling products as less healthy.

This study evaluated spatial relationships between features of the built environment and youth depressive symptoms. Data used in this study came from the 2008 Boston Youth Survey Geospatial Dataset, which includes Boston high school students with complete residential information (n=1170). Features of the built environment (such as access to walking destinations and community design features) were created for 400- and 800-m street network buffers of the youths' residences. We computed standard Ordinary Least Squares (OLS) regression and spatial simultaneous autoregressive models. We found significant positive spatial autocorrelation in all of the built environment features at both spatial scales (all p=0.001), depressive symptoms (p=0.034) as well as in the OLS regression residuals (all p<0.001), and, therefore, fit spatial regression models. Findings from the spatial regression models indicate that the built environment can have depressogenic effects, which can vary by spatial scale, gender and race/ethnicity (though sometimes in unexpected directions, i.e. associations opposite to our expectations). While our results overall suggest that the built environment minimally influences youth depressive symptoms, additional research is needed, including to understand our results in the unexpected direction.

OBJECTIVE: The objective of this study is to examine associations of proximity to food establishments with body mass index (BMI) among preschool-age children. METHODS: We used baseline data from 438 children ages 2-6.9 years with a BMI >/= 85th percentile participating in a RCT in Massachusetts from 2006 to 2009. We used a geographic information system to determine proximity to six types of food establishments: 1) convenience stores, 2) bakeries, coffee shops, candy stores, 3) full service restaurants, 4) large supermarkets, 5) small supermarkets, and 6) fast-food restaurants. The main outcome was child's BMI. RESULTS: Children's mean (SD) BMI was 19.2 (2.4)kg/m(2); 35% lived 1 to 2 miles, and 22% lived >2 miles. Compared to children living >2 miles from a large supermarket, those who lived within 1 mile had a BMI 1.06 kg/m(2) higher. Adjustment for socioeconomic characteristics and distance to fast-food restaurants attenuated this estimate to 0.77 kg/m(2). Living in any other distance category from a large supermarket and proximity to other food establishments were not associated with child BMI. CONCLUSIONS: Living closer to a large supermarket was associated with higher BMI among preschool-age children who were overweight or obese.

The geography of recreational open space might be inequitable in terms of minority neighborhood racial/ethnic composition and neighborhood poverty, perhaps due in part to residential segregation. This study evaluated the association between minority neighborhood racial/ethnic composition, neighborhood poverty, and recreational open space in Boston, Massachusetts (US). Across Boston census tracts, we computed percent non-Hispanic Black, percent Hispanic, and percent families in poverty as well as recreational open space density. We evaluated spatial autocorrelation in study variables and in the ordinary least squares (OLS) regression residuals via the Global Moran's I. We then computed Spearman correlations between the census tract socio-demographic characteristics and recreational open space density, including correlations adjusted for spatial autocorrelation. After this, we computed OLS regressions or spatial regressions as appropriate. Significant positive spatial autocorrelation was found for neighborhood socio-demographic characteristics (all p value = 0.001). We found marginally significant positive spatial autocorrelation in recreational open space (Global Moran's I = 0.082; p value = 0.053). However, we found no spatial autocorrelation in the OLS regression residuals, which indicated that spatial models were not appropriate. There was a negative correlation between census tract percent non-Hispanic Black and recreational open space density (r (S) = -0.22; conventional p value = 0.005; spatially adjusted p value = 0.019) as well as a negative correlation between predominantly non-Hispanic Black census tracts (>60 % non-Hispanic Black in a census tract) and recreational open space density (r (S) = -0.23; conventional p value = 0.003; spatially adjusted p value = 0.007). In bivariate and multivariate OLS models, percent non-Hispanic Black in a census tract and predominantly Black census tracts were associated with decreased density of recreational open space (p value < 0.001). Consistent with several previous studies in other geographic locales, we found that Black neighborhoods in Boston were less likely to have recreational open spaces, indicating the need for policy interventions promoting equitable access. Such interventions may contribute to reductions and disparities in obesity.