Dataset Information

Association of Chain Restaurant Advertising Spending With Obesity in US Adults.

ABSTRACT: Importance:Restaurants spend billions of dollars on marketing. However, little is known about the association between restaurant marketing and obesity risk in adults. Objective:To examine associations between changes in per capita county-level restaurant advertising spending over time and changes in objectively measured body mass index (BMI) for adult patients. Design, Setting, and Participants:This cohort study used regression models with county fixed effects to examine associations between changes in per capita county-level (370 counties across 44 states) restaurant advertising spending over time with changes in objectively measured body mass index (BMI) for US adult patients from 2013 to 2016. Different media types and restaurant types were analyzed together and separately. The cohort was derived from deidentified patient data obtained from athenahealth. The final analytic sample included 5?987?213 patients, and the analysis was conducted from March 2018 to November 2019. Exposure:Per capita county-level chain restaurant advertising spending. Main Outcomes and Measures:Individual-level mean BMI during the quarter. Results:The included individuals were generally older (37.1% older than 60 years), female (56.8%), and commercially insured (53.5%). For the full population of 29?285?920 person-quarters, there was no association between changes in all restaurant advertising per capita (all media types, all restaurants) and changes in BMI. However, restaurant advertising spending was positively associated with weight gain for patients in low-income counties but not in high-income counties. A $1 increase in quarterly advertising per capita across all media and restaurant types was associated with a 0.053-unit increase in BMI (95% CI, 0.001-0.102) for patients in low-income counties, corresponding to a 0.12% decrease in BMI at the 10th percentile of changes in county advertising spending vs a 0.12% increase in BMI at the 90th percentile. Conclusions and Relevance:The results of this study suggest that restaurant advertising is associated with modest weight gain among adult patients in low-income counties. To date, there has been no public policy action or private sector action to limit adult exposure to unhealthy restaurant advertising. Efforts to decrease restaurant advertising in low-income communities should be intensified and rigorously evaluated to understand their potential for increasing health equity.

SUBMITTER: Bleich SN

PROVIDER: S-EPMC7542328 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Association of Chain Restaurant Advertising Spending With Obesity in US Adults.

Bleich Sara N SN Soto Mark J MJ Jones-Smith Jesse C JC Wolfson Julia A JA Jarlenski Marian P MP Dunn Caroline G CG Frelier Johannah M JM Herring Bradley J BJ

JAMA network open 20201001 10

<h4>Importance</h4>Restaurants spend billions of dollars on marketing. However, little is known about the association between restaurant marketing and obesity risk in adults.<h4>Objective</h4>To examine associations between changes in per capita county-level restaurant advertising spending over time and changes in objectively measured body mass index (BMI) for adult patients.<h4>Design, setting, and participants</h4>This cohort study used regression models with county fixed effects to examine as ...[more]

PMID: 33026451

Similar Datasets

Project description:ImportanceSome drugs are heavily marketed through direct-to-consumer advertising.ObjectiveTo identify drug characteristics associated with a greater share of promotional spending on advertising directly to consumers.Design, setting, and participantsExploratory cross-sectional analysis of drug characteristics and promotional spending for the 150 top-selling branded prescription drugs in the US in 2020 as identified from IQVIA National Sales Perspectives data. Promotional spending data were provided by IQVIA ChannelDynamics.ExposuresDrug characteristics (total 2020 sales; total 2020 promotional spending; clinical benefit ratings; number of indications, off-label use; molecule type; nature of condition treated; administration type; generic availability; US Food and Drug Administration [FDA] approval year, World Health Organization anatomical therapeutic chemical classification; Medicare annual mean spending per beneficiary; percent sales attributable to the drug; market size; market competitiveness) assessed from health technology assessment agencies (France's Haute Autorité de Santé and Canada's Patented Medicine Prices Review Board) and drug data sources (Drugs@FDA, the FDA Purple Book, Lexicomp, Merative Marketscan Research Databases, and Medicare Spending by Drug data).Main outcomes and measuresProportion of total promotional spending allocated to direct-to-consumer-advertising for each drug.ResultsThe 2020 median proportion of promotional spending allocated to direct-to-consumer advertising was 13.5% (IQR, 1.96%-36.6%); median promotional spending, $20.9 million (IQR, $2.72-$131 million); and median total sales, $1.51 billion (IQR, $0.97-$2.26 billion). Of the 150 best-selling drugs, 16 were missing data and key covariates; therefore, the primary study sample comprised 134 drugs. After adjustment for multiple drug characteristics, the mean proportion of total promotional spending allocated to direct-to-consumer advertising for the remaining 134 drugs was an absolute 14.3% (95% CI, 1.43%-27.2%; P = .03) higher for those with low added clinical benefit than for those with high added clinical benefit and an absolute 1.5% (95% CI, 0.44%-2.56%; P = .005) higher for each 10% increase in total sales.Conclusions and relevanceAmong top-selling US drugs in 2020, a rating of lower added benefit and higher total drug sales were associated with a higher proportion of manufacturer total promotional spending allocated to direct-to-consumer advertising. Further research is needed to understand the implications of these findings.

Project description:The food environment has been implicated as an underlying contributor to the global obesity epidemic. However, few studies have evaluated the relationship between the food environment, dietary intake, and overweight/obesity in low- and middle-income countries (LMICs). The aim of this study was to assess the association of full service and fast food restaurant density with dietary intake and overweight/obesity in Delhi, India.Data are from a cross-sectional, population-based study conducted in Delhi. Using multilevel cluster random sampling, 5364 participants were selected from 134 census enumeration blocks (CEBs). Geographic information system data were available for 131 CEBs (n = 5264) from a field survey conducted using hand-held global positioning system devices. The number of full service and fast food restaurants within a 1-km buffer of CEBs was recorded by trained staff using ArcGIS software, and participants were assigned to tertiles of full service and fast food restaurant density based on their resident CEB. Height and weight were measured using standardized procedures and overweight/obesity was defined as a BMI ≥25 kg/m2.The most common full service and fast food restaurants were Indian savory restaurants (57.2%) and Indian sweet shops (25.8%). Only 14.1% of full service and fast food restaurants were Western style. After adjustment for age, household income, education, and tobacco and alcohol use, participants in the highest tertile of full service and fast food restaurant density were less likely to consume fruit and more likely to consume refined grains compared to participants in the lowest tertile (both p < 0.05). In unadjusted logistic regression models, participants in the highest versus lowest tertile of full service and fast food restaurant density were significantly more likely to be overweight/obese: odds ratio (95% confidence interval), 1.44 (1.24, 1.67). After adjustment for age, household income, and education, the effect was attenuated: 1.08 (0.92, 1.26). Results were consistent with further adjustment for tobacco and alcohol use, moderate physical activity, and owning a bicycle or motorized vehicle.Most full service and fast food restaurants were Indian, suggesting that the nutrition transition in this megacity may be better characterized by the large number of unhealthy Indian food outlets rather than the Western food outlets. Full service and fast food restaurant density in the residence area of adults in Delhi, India, was associated with poor dietary intake. It was also positively associated with overweight/obesity, but this was largely explained by socioeconomic status. Further research is needed exploring these associations prospectively and in other LMICs.

Project description:ImportanceHigh use of subspecialty care is an important source of health care spending. Medical subspecialty care in particular may duplicate the scope of practice of the primary attending physicians for patients hospitalized for medical conditions. Under value-based payments, which aim to control overall spending during an episode of hospitalization (including Part B physician fees), subspecialty consultations may be a target for hospitals working to reduce costs.ObjectivesTo measure the use of subspecialty consultation for Medicare beneficiaries hospitalized for nonsurgical conditions; to compare payments for consultative and nonconsultative care, adjusted for case mix and demographics; and to measure variation in payments across hospital referral regions (HRRs).Design, setting, and participantsThis retrospective cross-sectional study included a 15% random sample of Medicare fee-for-service beneficiaries enrolled in Parts A and B and identified all discharges after acute care hospital stays for nonsurgical conditions from January 1 through December 31, 2014. A total of 735 627 discharges were included. The analyses were conducted from December 1, 2017, through February 12, 2019. Total Part B payments were extrapolated to the population of Medicare fee-for-service beneficiaries.Main outcomes and measuresProbability of any consultation during a hospitalization was estimated using logistic regression. The number of consultations per stay and the number of consultative visits per hospital day were estimated using Poisson regression. Part B payments for consultative and nonconsultative care were estimated using generalized linear regression with gamma-log link. All models were adjusted for patient demographics and case mix. Payment models also included HRR fixed effects.ResultsA total of 735 627 discharges from 4534 hospitals in 2014 were included in the analysis (41.2% men and 58.8% women; mean [SD] age, 79.6 [8.9] years; 84.7% white, 10.1% black, and 5.2% other race). After adjusting for patient case mix and demographics, a 6-fold variation between the top and bottom quintiles of hospitals (relative difference, $401 [95% CI, $368-$434]) and HRRs (relative difference, $363 [95% CI, $337-$389]) was found in payments per stay for consultative care. Part B payments for consultative care by medical subspecialists accounted for 41.3% of payments for physician visits during hospitalization and totaled $1.3 billion in 2014.Conclusions and relevanceThe substantial variation in the use of subspecialty consultative care suggests potential opportunities for cost savings.

Dataset Information

Association of Chain Restaurant Advertising Spending With Obesity in US Adults.

Publications

Association of Chain Restaurant Advertising Spending With Obesity in US Adults.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets