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1.
JAMA Netw Open ; 6(12): e2346851, 2023 Dec 01.
Article En | MEDLINE | ID: mdl-38100109

Importance: Menu labeling has been implemented in restaurants in some US jurisdictions as early as 2008, but the extent to which menu labeling is associated with calories purchased is unclear. Objective: To estimate the association of menu labeling with calories and nutrients purchased and assess geographic variation in results. Design, Setting, and Participants: A cohort study was conducted with a quasi-experimental design using actual transaction data from Taco Bell restaurants from calendar years 2007 to 2014 US restaurants with menu labeling matched to comparison restaurants using synthetic control methods. Data were analyzed from May to October 2023. Exposure: Menu labeling policies in 6 US jurisdictions. Main Outcomes and Measures: The primary outcome was calories per transaction. Secondary outcomes included total and saturated fat, carbohydrates, protein, sugar, fiber, and sodium. Results: The final sample included 2329 restaurants, with menu labeling in 474 (31 468 restaurant-month observations). Most restaurants (94.3%) were located in California. Difference-in-differences model results indicated that customers purchased 24.7 (95% CI, 23.6-25.7) fewer calories per transaction from restaurants in the menu labeling group in the 3- to 24-month follow-up period vs the comparison group, including 21.9 (95% CI, 20.9-22.9) fewer calories in the 3- to 12-month follow-up period and 25.0 (95% CI, 24.0-26.1) fewer calories in the 13- to 24-month follow-up period. Changes in the nutrient content of transactions were consistent with calorie estimates. Findings in California were similar to overall estimates in magnitude and direction; yet, among restaurants outside of California, no association was observed in the 3- to 24-month period. The outcome of menu labeling also differed by item category and time of day, with a larger decrease in the number of tacos vs other items purchased and a larger decrease in calories purchased during breakfast vs other times of the day in the 3- to 24-month period. Conclusions and Relevance: In this quasi-experimental cohort study, fewer calories were purchased in restaurants with calorie labels compared with those with no labels, suggesting that consumers are sensitive to calorie information on menu boards, although associations differed by location.


Fast Foods , Restaurants , Humans , Cohort Studies , Energy Intake , Policy
2.
Health Place ; 65: 102408, 2020 09.
Article En | MEDLINE | ID: mdl-32861053

Using objectively-measured height and weight data from academic years 2009-2013 (n = 1,114,010 student-year observations), we estimated the association between the food outlet in closest proximity to schools and the likelihood of obesity among New York City public high school students. Obesity risk was higher for students with a corner store as the nearest option to schools, regardless of whether other food outlet types were located within a quarter mile or a half mile of schools (i.e., benchmarks for zoning policies). Policymakers may want to consider introducing healthier food options near schools, in conjunction with programs to support changes within corner stores.


Fast Foods/supply & distribution , Pediatric Obesity/epidemiology , Restaurants/statistics & numerical data , Schools , Students/statistics & numerical data , Adolescent , Female , Humans , Male , Marketing , New York City/epidemiology , Students/psychology
3.
Obesity (Silver Spring) ; 28(1): 65-72, 2020 01.
Article En | MEDLINE | ID: mdl-31675159

OBJECTIVE: This study aimed to examine the relationship between proximity to healthy and unhealthy food outlets around children's homes and their weight outcomes. METHODS: A total of 3,507,542 student-year observations of height and weight data from the 2009-2013 annual FitnessGram assessment of New York City public school students were used. BMI z scores were calculated, student obesity or obesity/overweight was determined using Centers for Disease Control and Prevention growth charts, and these data were combined with the locations of four food outlet types (fast-food restaurants, wait-service restaurants, corner stores, and supermarkets) to calculate distance to the nearest outlet. Associations between weight status outcomes and distance to these food outlet types were examined using neighborhood (census tract) fixed effects. RESULTS: Living farther than 0.025 mile (about half of a city block) from the nearest fast-food restaurant was associated with lower obesity and obesity/overweight risk and lower BMI z scores. Results ranged from 2.5% to 4.4% decreased obesity. Beyond this distance, there were generally no impacts of the food environment and little to no impact of other food outlet types. CONCLUSIONS: Proximity to fast-food restaurants was inversely related to childhood obesity, but no relationships beyond that were seen. These findings can help better inform policies focused on food access, which could, in turn, reduce childhood obesity.


Environment Design/statistics & numerical data , Pediatric Obesity/epidemiology , Pediatric Obesity/etiology , Schools/statistics & numerical data , Social Environment , Students/statistics & numerical data , Adolescent , Body Weight/physiology , Child , Child, Preschool , Fast Foods/statistics & numerical data , Fast Foods/supply & distribution , Female , Humans , Male , New York City/epidemiology , Overweight/epidemiology , Overweight/etiology , Residence Characteristics/statistics & numerical data , Restaurants , Risk Factors , Socioeconomic Factors , Young Adult
4.
PLoS One ; 14(6): e0217341, 2019.
Article En | MEDLINE | ID: mdl-31188866

Demographic and income disparities may impact food accessibility. Research has not yet well documented the precise location of healthy and unhealthy food resources around children's homes and schools. The objective of this study was to examine the food environment around homes and schools for all public school children, stratified by race/ethnicity and poverty status. This cross-sectional study linked data on the exact home and school addresses of a population-based sample of public school children in New York City from 2013 to all corner stores, supermarkets, fast-food restaurants, and wait-service restaurants. Two measures were created around these addresses for all children: 1) distance to the nearest outlet, and 2) count of outlets within 0.25 miles. The total analytic sample included 789,520 K-12 graders. The average age was 11.78 years (SD ± 4.0 years). Black, Hispanic, and Asian students live and attend schools closer to nearly all food outlet types than White students, regardless of poverty status. Among not low-income students, Black, Hispanic, and Asian students were closer from home and school to corner stores and supermarkets, and had more supermarkets around school than White students. The context in which children live matters, and more nuanced data is important for development of appropriate solutions for childhood obesity. Future research should examine disparities in the food environment in other geographies and by other demographic characteristics, and then link these differences to health outcomes like body mass index. These findings can be used to better understand disparities in food access and to help design policies intended to promote healthy eating among children.


Food Supply/statistics & numerical data , Residence Characteristics/statistics & numerical data , Schools/statistics & numerical data , Black or African American/statistics & numerical data , Body Mass Index , Child , Cross-Sectional Studies , Diet, Healthy/statistics & numerical data , Ethnicity/statistics & numerical data , Fast Foods/statistics & numerical data , Female , Hispanic or Latino/statistics & numerical data , Humans , Male , New York City , Pediatric Obesity/physiopathology , Poverty/statistics & numerical data , Restaurants/statistics & numerical data , Socioeconomic Factors , Students/statistics & numerical data
5.
BMC Public Health ; 18(1): 300, 2018 03 01.
Article En | MEDLINE | ID: mdl-29490651

BACKGROUND: Publicly funded healthcare forms an intricate part of government spending in most Organisation for Economic Co-operation and Development (OECD) countries, because of its reliance on entitlements and dedicated revenue streams. The impact of budgetary rules and procedures on publicly funded health care might thus be different from other spending categories. In this study we focus on the potential of fiscal rules to contain these costs and their design features. METHODS: We assess the relationship between fiscal rules and the level of public health care expenditure of 32 (OECD) countries between 1985 and 2014. Our dataset consists of health care expenditure data of the OECD and data on fiscal rules of the International Monetary Fund (IMF) for that same period. Through a multivariate regression analysis, we estimate the association between fiscal rules and its subcategories and inflation adjusted public health care expenditure. We control for population, Gross Domestic Product (GDP), debt and whether countries received an IMF bailout for the specific period. In all our regressions we include country and year fixed effects. RESULTS: The presence of a fiscal rule on average is associated with a 3 % reduction of public health care expenditure. Supranational balanced budget rules are associated with some 8 % lower expenditure. Health service provision-oriented countries with more passive purchasing structures seem less capable of containing costs through fiscal rules. Fiscal rules demonstrate lagged effectiveness; the potential for expenditure reduction increases after one and two years of fiscal rule implementation. Finally, we find evidence that fiscal frameworks that incorporate multi-year expenditure ceilings show additional potential for cost control. CONCLUSIONS: Our study shows that there seems a clear relationship between the potential of fiscal rules and budgeting health expenses. Using fiscal rules to contain the level of health care expenditure can thus be a necessary precondition for successful strategies for cost control.


Budgets/legislation & jurisprudence , Developed Countries/economics , Health Expenditures/legislation & jurisprudence , Organisation for Economic Co-Operation and Development , Health Expenditures/statistics & numerical data , Humans
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