Dataset Information

Impact of multiple food environments on body mass index.

ABSTRACT:

Background

Although the relationship between residential food environments and health outcomes have been extensively studied, the relationship between body mass index (BMI) and multiple food environments have not been fully explored. We examined the relationship between characteristics of three distinct food environments and BMI among elementary school employees in the metropolitan area of New Orleans, LA. We assessed the food environments around the residential and worksite neighborhoods and the commuting corridors.

Research methodology/principal findings

This study combined data from three different sources: individual and worksite data (ACTION), food retailer database (Dunn and Bradstreet), and the U.S. Census TIGER/Line Files. Spatial and hierarchical analyses were performed to explore the impact of predictors at the individual and environmental levels on BMI. When the three food environments were combined, the number of supermarkets and the number of grocery stores at residential food environment had a significant association with BMI (? = 0.56 and ? = 0.24, p < 0.01), whereas the number of full-service restaurants showed an inverse relationship with BMI (? = -0.15, p < 0.001). For the commute corridor food environment, it was found that each additional fast-food restaurant in a vicinity of one kilometer traveled contributed to a higher BMI (? = 0.80, p <0.05), while adjusting for other factors. No statistical associations were found between BMI and worksite food environment.

Conclusions

The current study was the first to examine the relationship between BMI and food environments around residential neighborhoods, work neighborhoods, and the commuting corridor. Significant results were found between BMI and the availability of food stores around residential neighborhoods and the commuting corridor, adjusted for individual-level factors. This study expands the analysis beyond residential neighborhoods, illustrating the importance of multiple environmental factors in relation to BMI.

SUBMITTER: Dornelles A

PROVIDER: S-EPMC6685601 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Publications

Impact of multiple food environments on body mass index.

Dornelles Adriana A

PloS one 20190807 8

<h4>Background</h4>Although the relationship between residential food environments and health outcomes have been extensively studied, the relationship between body mass index (BMI) and multiple food environments have not been fully explored. We examined the relationship between characteristics of three distinct food environments and BMI among elementary school employees in the metropolitan area of New Orleans, LA. We assessed the food environments around the residential and worksite neighborhood ...[more]

PMID: 31390365

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Project description:Background/objectiveMexico has one of the highest rates of obesity and overweight worldwide, affecting 75% of the population. The country has experienced a dietary and food retail transition involving increased availability of high-calorie-dense foods and beverages. This study aimed to assess the relationship between the retail food environment and body mass index (BMI) in Mexico.Subjects/methodsGeographical and food outlet data were obtained from official statistics; anthropometric measurements and socioeconomic characteristics of adult participants (N = 22,219) came from the nationally representative 2012 National Health and Nutrition Survey (ENSANUT). Densities (store count/census tract area (CTA)) of convenience stores, restaurants, fast-food restaurants, supermarkets and fruit and vegetable stores were calculated. The association of retail food environment variables, sociodemographic data and BMI was tested using multilevel linear regression models.ResultsConvenience store density was high (mean (SD) = 50.0 (36.9)/CTA) compared with other food outlets in Mexico. A unit increase in density of convenience stores was associated with a 0.003 kg/m2 (95% CI: 0.0006, 0.005, p = 0.011) increase in BMI, equivalent to 0.34 kg extra weight for an adult 1.60 m tall for every additional 10% store density increase (number of convenience stores per CTA (km2)). Metropolitan areas showed the highest density of food outlet concentration and the highest associations with BMI (β = 0.01, 95% CI: 0.004-0.01, p < 0.001). A 10% store density increase in these areas would represent a 1 kg increase in weight for an adult 1.60 m tall.ConclusionsConvenience store density was associated with higher mean BMI in Mexican adults. An excessive convenience store availability, that offers unhealthy food options, coupled with low access to healthy food resources or stores retailing healthy food, including fruits and vegetables, may increase the risk of higher BMI. This is the first study to assess the association of the retail food environment and BMI at a national level in Mexico.

Project description:ImportanceBody mass index (BMI) is used to diagnose obesity in adolescents worldwide, despite evidence that weight does not scale with height squared in adolescents. To account for this, health care providers diagnose obesity using BMI percentiles for each age (BMI z scores), but this does not ensure that BMI is accurate in adolescents.ObjectiveTo compare the accuracy of BMI vs other body fat indices of the form body mass divided by heightn in estimating body fat levels in adolescents.Design, setting, and participantsCross-sectional data from the 1999 to 2006 US National Health and Nutrition Examination Survey were analyzed between September 2015 and December 2016.Main outcomes and measuresDual-energy x-ray absorptiometry and anthropometric data were used to determine changes in body fat levels, body proportions, and the scaling relationships among body mass, height, and percent body fat. To assess the merits of each adiposity index, 3 criteria were used: stability with age, accuracy in estimating percent body fat, and accuracy in classifying adolescents as overweight vs normal weight.ResultsParticipants included 2285 non-Hispanic white participants aged 8 to 29 years. Percent body fat varied with both age and height during adolescence, invalidating the standard weight-to-height regression as the way of finding the optimal body fat index. Because the correct regression model (percent body fat is proportional to mass divided by heightn) suggested that percent body fat scales to height with an exponent closer to 3, we therefore focused on the tri-ponderal mass index (TMI; mass divided by height cubed) as an alternative to BMI z scores. For ages 8 to 17 years, TMI yielded greater stability with age and estimated percent body fat better than BMI (R2?=?0.64 vs 0.38 in boys and R2?=?0.72 vs 0.66 in girls). Moreover, TMI misclassified adolescents as overweight vs normal weight less often than BMI z scores (TMI, 8.4%; 95% CI, 7.3%-9.5% vs BMI, 19.4%; 95% CI, 17.8%-20.0%; P?<?.001) and performed equally as well as updated BMI percentiles derived from the same data set (TMI, 8.4%; 95% CI, 7.3%-9.5% vs BMI, 8.0%; 95% CI, 6.9%-9.1%; P?=?.62).Conclusions and relevanceThe tri-ponderal mass index estimates body fat levels more accurately than BMI in non-Hispanic white adolescents aged 8 to 17 years. Moreover, TMI diagnoses adolescents as overweight more accurately than BMI z scores and equally as well as updated BMI percentiles but is much simpler to use than either because it does not involve complicated percentiles. Taken together, it is worth considering replacing BMI z scores with TMI to estimate body fat levels in adolescents.

Dataset Information

Impact of multiple food environments on body mass index.

Background

Research methodology/principal findings

Conclusions

Publications

Impact of multiple food environments on body mass index.

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