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spaceLeung CW, Gregorich SE, Laraia BA, Kushi LH and Yen IH. (2010) Measuring the neighborhood environment: Associations with young girls’ energy intake and expenditure in a cross-sectional study. International Journal of Behavioral Nutrition and Physical Activity 2010, 7:52

Article summary

Background: Neighborhood characteristics affect health conditions such as asthma and obesity, but what isn’t so clear is how they affect children’s diet and exercise.  Previous studies have found that neighborhood safety, access to sports equipment, and presence of sidewalks are associated with increased exercise in children while areas with high crime rates, graffiti and high rates of unemployment are associated with decreased exercise. In this study, the researchers looked at the associations between neighborhood characteristics and young girls diet and exercise habits.

Study Design: Two hundred and fifteen (215) girls participated in the study.  The girls who participated in this study represent a subset of participants from the Cohort Study of Young Girls’ Nutrition, Environment and Transitions (CYGNET) Study.  To determine neighborhood characteristics in the current study, direct observations of the neighborhood were made via in-person street audits and census data was also used.  To determine diet habits, phone calls were made to girls and their parents asking about what the girls ate in the past 24 hours.   Based on this information, the researchers calculated the calories consumed per day. Exercise data was based on a questionnaire that collected information about the number of hours per week over a one-year period that a girl participated in activities such as dance, soccer, basketball and swimming.  The researchers examined on how many calories the girls ate per day (energy intake) and how many hours of exercise they got (energy expenditure) in association with neighborhood characteristics including: presence of residential and commercial entities, food and retail establishments, recreation spaces, walkability, and physical disorder.

Results: The average age of the girls in the study was 7.4 years old.  The girls were mostly non-Hispanic Whites (40.5%), followed by Hispanic/Latinas (23.3%) and African-Americans (19.1%).  According to Body Mass Index (BMI), 29.8% of the girls were overweight or obese.  The researchers found an inverse association between number of food and retail shops and amount of calories consumed by the girls.  This means that the more food and retail shops in a girl’s neighborhood, the fewer the calories the she consumed.   They also found an inverse association between exercise and neighborhoods with more residents living in poverty.  This indicates that the more poverty in a girl’s neighborhood, the less exercise the she got.

Overall, there were no differences among girls of different races and ethnicities between neighborhood characteristics and caloric consumption; however, there were differences by race and ethnicity between neighborhood characteristics and exercise. Asian girls exercised the most and Hispanic/Latina girls exercised the least. Certain neighborhood characteristics were strongly associated with exercise by girls of different racial/ethnic groups.  For example, Hispanic/Latina girls who live in areas that are highly walkable and neighborhoods that contain parks, trails, and sports fields were more likely to exercise. African-American girls who live in neighborhoods with garbage and broken glass on the street and sidewalk and graffiti on buildings, signs and walls were less likely to exercise. 

Conclusions: Girls who live in areas with many food and retail shops consume fewer calories per day compared to girls who live near few or no food and retail shops.  Furthermore, girls who live in neighborhoods with more residents living in poverty were less likely to exercise.   This study is the first to link girls’ eating habits to directly observed neighborhood characteristics.  Understanding the mechanisms that underlie children’s exercise and eating habits will help to inform evidenced-based policy and behavioral changes.

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