Dataset Information

Census Tract Food Tweets and Chronic Disease Outcomes in the U.S., 2015?2018.

ABSTRACT: There is a growing recognition of social media data as being useful for understanding local area patterns. In this study, we sought to utilize geotagged tweets-specifically, the frequency and type of food mentions-to understand the neighborhood food environment and the social modeling of food behavior. Additionally, we examined associations between aggregated food-related tweet characteristics and prevalent chronic health outcomes at the census tract level. We used a Twitter streaming application programming interface (API) to continuously collect ~1% random sample of public tweets in the United States. A total of 4,785,104 geotagged food tweets from 71,844 census tracts were collected from April 2015 to May 2018. We obtained census tract chronic disease outcomes from the CDC 500 Cities Project. We investigated associations between Twitter-derived food variables and chronic outcomes (obesity, diabetes and high blood pressure) using the median regression. Census tracts with higher average calories per tweet, less frequent healthy food mentions, and a higher percentage of food tweets about fast food had higher obesity and hypertension prevalence. Twitter-derived food variables were not predictive of diabetes prevalence. Food-related tweets can be leveraged to help characterize the neighborhood social and food environment, which in turn are linked with community levels of obesity and hypertension.

SUBMITTER: Huang Y

PROVIDER: S-EPMC6466014 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Publications

Census Tract Food Tweets and Chronic Disease Outcomes in the U.S., 2015⁻2018.

Huang Yuru Y Huang Dina D Nguyen Quynh C QC

International journal of environmental research and public health 20190318 6

There is a growing recognition of social media data as being useful for understanding local area patterns. In this study, we sought to utilize geotagged tweets-specifically, the frequency and type of food mentions-to understand the neighborhood food environment and the social modeling of food behavior. Additionally, we examined associations between aggregated food-related tweet characteristics and prevalent chronic health outcomes at the census tract level. We used a Twitter streaming applicatio ...[more]

PMID: 30889911

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Project description:BackgroundRace is an important predictor of TKA outcomes in the United States; however, analyses of race can be confounded by socioeconomic factors, which can result in difficulty determining the root cause of disparate outcomes after TKA.Questions/purposesWe asked: (1) Are race and socioeconomic factors at the individual level associated with patient-reported pain and function 2 years after TKA? (2) What is the interaction between race and community poverty and patient-reported pain and function 2 years after TKA?MethodsWe identified all patients undergoing TKA enrolled in a hospital-based registry between 2007 and 2011 who provided 2-year outcomes and lived in New York, Connecticut, or New Jersey. Of patients approached to participate in the registry, more than 82% consented and provided baseline data, and of these patients, 72% provided 2-year data. Proportions of patients with complete followup at 2 years were lower among blacks (57%) than whites (74%), among patients with Medicaid insurance (51%) compared with patients without Medicaid insurance (72%), and among patients without a college education (67%) compared with those with a college education (71%). Our final study cohort consisted of 4035 patients, 3841 (95%) of whom were white and 194 (5%) of whom were black. Using geocoding, we linked individual-level registry data to US census tracts data through patient addresses. We constructed a multivariate linear mixed-effect model in multilevel frameworks to assess the interaction between race and census tract poverty on WOMAC pain and function scores 2 years after TKA. We defined a clinically important effect as 10 points on the WOMAC (which is scaled from 1 to 100 points, with higher scores being better).ResultsRace, education, patient expectations, and baseline WOMAC scores are all associated with 2-year WOMAC pain and function; however, the effect sizes were small, and below the threshold of clinical importance. Whites and blacks from census tracts with less than 10% poverty have similar levels of pain and function 2 years after TKA (WOMAC pain, 1.01 ± 1.59 points lower for blacks than for whites, p = 0.53; WOMAC function, 2.32 ± 1.56 lower for blacks than for whites, p = 0.14). WOMAC pain and function scores 2 years after TKA worsen with increasing levels of community poverty, but do so to a greater extent among blacks than whites. Disparities in pain and function between blacks and whites are evident only in the poorest communities; decreasing in a linear fashion as poverty increases. In census tracts with greater than 40% poverty, blacks score 6 ± 3 points lower (worse) than whites for WOMAC pain (p = 0.03) and 7 ± 3 points lower than whites for WOMAC function (p = 0.01).ConclusionsBlacks and whites living in communities with little poverty have similar patient-reported TKA outcomes, whereas in communities with high levels of poverty, there are important racial disparities. Efforts to improve TKA outcomes among blacks will need to address individual- and community-level socioeconomic factors.Level of evidenceLevel III, therapeutic study.

Project description:Previous analysis of U.S. physician office visits (1993-2007) indicated that the medicalization of sleeplessness was on the rise and had potentially negative implications for population health. Our study asks if the medicalization of sleeplessness at the level of patient-physician interaction has persisted over time. Using the most recent years available (2008-2015) of the National Ambulatory Medical Care Survey we calculated nationally representative estimates for four sleeplessness-related outcomes of physician office visits: sleeplessness complaint, insomnia diagnosis, and prescription of benzodiazepine and non-benzodiazepine sedative-hypnotics (NBSH). To test for the significance of the linear trajectory, we ran a series of bivariate linear models. We tested three hypotheses grounded in the medicalization framework: if the medicalization of sleeplessness at the interactional level is continuing at a rate comparable to previous analyses, sleeplessness-related outcomes will continue to increase significantly over time (Hypothesis 1); NBSH prescriptions and insomnia diagnoses will continue to outpace sleeplessness complaints (Hypothesis 2); and insomnia diagnoses and use of sedative-hypnotics will increase or remain concentrated among age groups who lack the changing sleep patterns and commonly occurring comorbidities associated with older age (Hypothesis 3). Support for these hypotheses was mixed. Unlike previous analyses wherein all sleeplessness-related outcome trends were positive and statistically significant over time, regression analyses revealed a significant negative NBSH prescription trend 2008-2015 (slope, b?=?-699,628, P?<?0.05). No other associations were significant. Younger age groups were most likely to receive an insomnia diagnosis and NBSH prescription. These trends imply that the medicalization of sleeplessness at the level of patient-physician interaction may be on the decline. We suggest that increasingly negative portrayals of sedative-hypnotics, conservative practice recommendations, and decreased direct-to-consumer advertising for NBSH may decrease consumerism and physician compliance related to the medicalization of sleeplessness. We conclude with a discussion on non-pharmaceutical methods of reducing sleeplessness relevant to population health.

Dataset Information

Census Tract Food Tweets and Chronic Disease Outcomes in the U.S., 2015?2018.

Publications

Census Tract Food Tweets and Chronic Disease Outcomes in the U.S., 2015⁻2018.

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