scholarly journals Use of social media, search queries, and demographic data to assess obesity prevalence in the United States

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Nina Cesare ◽  
Pallavi Dwivedi ◽  
Quynh C. Nguyen ◽  
Elaine O. Nsoesie
Keyword(s):  
Physical Activity ◽  
Social Media ◽  
Built Environment ◽  
Demographic Data ◽  
The United States ◽  
Obesity Prevalence ◽  
Male And Female ◽  
Search Queries ◽  
Environment Variables ◽  
Google Search

Abstract Obesity is a global epidemic affecting millions. Implementation of interventions to curb obesity rates requires timely surveillance. In this study, we estimated sex-specific obesity prevalence using social media, search queries, demographics and built environment variables. We collected 3,817,125 and 1,382,284 geolocated tweets on food and exercise respectively, from Twitter’s streaming API from April 2015 to March 2016. We also obtained searches related to physical activity and diet from Google Search Trends for the same time period. Next, we inferred the gender of Twitter users using machine learning methods and applied mixed-effects state-level linear regression models to estimate obesity prevalence. We observed differences in discussions of physical activity and foods, with males reporting higher intensity physical activities and lower caloric foods across 40 and 48 states, respectively. In addition, counties with the highest percentage of exercise and food tweets had lower male and female obesity prevalence. Lastly, our models separately captured overall male and female spatial trends in obesity prevalence. The average correlation between actual and estimated obesity prevalence was 0.797(95% CI, 0.796, 0.798) and 0.830 (95% CI, 0.830, 0.831) for males and females, respectively. Social media can provide timely community-level data on health information seeking and changes in behaviors, sentiments and norms. Social media data can also be combined with other data types such as, demographics, built environment variables, diet and physical activity indicators from other digital sources (e.g., mobile applications and wearables) to monitor health behaviors at different geographic scales, and to supplement delayed estimates from traditional surveillance systems.

The Built Environment, Physical Activity, and Aging in the United States: A State of the Science Review

2015 ◽  
Vol 23 (2) ◽  
pp. 323-329 ◽  
Author(s):  
Elizabeth M. Haselwandter ◽  
Michael P. Corcoran ◽  
Sara C. Folta ◽  
Raymond Hyatt ◽  
Mark Fenton ◽  
...  
Keyword(s):  
Physical Activity ◽  
United States ◽  
Built Environment ◽  
The United States ◽  
Science Review ◽  
State Of The Science

Built Environment Associations With Health Behaviors Among Hispanics

2013 ◽  
Vol 10 (3) ◽  
pp. 335-342 ◽  
Author(s):  
Robert Fields ◽  
Andrew T. Kaczynski ◽  
Melissa Bopp ◽  
Elizabeth Fallon
Keyword(s):  
Physical Activity ◽  
Built Environment ◽  
Health Behaviors ◽  
Neighborhood Change ◽  
Active Commuting ◽  
Environment Variables ◽  
Hispanic Adults ◽  
Physical Activity Recommendations ◽  
Multiple Health ◽  
Activity Recommendations

Background:Few studies of the built environment and physical activity or other health behaviors have examined minority populations specifically. The purpose of this study was to examine associations between the built environment and multiple health behaviors and outcomes among Hispanic adults.Methods:Community partners distributed surveys (n = 189) in 3 communities in southwest Kansas. Logistic regression was used to examine relationships between neighborhood perceptions and 4 outcomes.Results:Meeting physical activity recommendations was associated with the presence of sidewalks and a safe park, and inversely related to higher crime. Residential density and shops nearby were related to active commuting. Sedentary behavior was inversely related to having a bus stop, bike facilities, safe park, interesting things to look at, and seeing people active. Finally, seeing people active was positively associated with being overweight.Conclusions:This study suggests that among Hispanics, many built environment variables are related to health behaviors and should be targets for future neighborhood change efforts and research.

scholarly journals Walking toward Metro Stations: the Contribution of Distance, Attitudes, and Perceived Built Environment

2020 ◽  
Vol 12 (24) ◽  
pp. 10291
Author(s):  
Mohammad Paydar ◽  
Asal Kamani Fard ◽  
Mohammad Mehdi Khaghani
Keyword(s):  
Physical Activity ◽  
United States ◽  
Built Environment ◽  
Developed Countries ◽  
The United States ◽  
Walking Distance ◽  
Policy Makers ◽  
Walking Behavior ◽  
Mode Of Transport ◽  
Surrounding Areas

Walking as an active means of travel is important as a sustainable mode of transport. Moreover, the level of walking in the surrounding areas of metro stations would contribute to maintaining the minimum rate of physical activity and, therefore, inhabitants’ general health. This study examined the impacts of walking attitude, walking distance, and perceived built environment on walking behavior for reaching the metro stations in Shiraz, Iran. Three metro stations were selected and a quantitative approach was used to examine the objectives. It was found that the average walking distance is less than the average in developed countries, such as the United States. People walked more when there was a shorter distance between their starting points and the metro stations. The contribution of walking attitudes and several built environment attributes to walking behavior was demonstrated. Finding the contribution of aesthetic attributes, such as accessibility to parks and housing types of the starting points of the walking trips, to walking for transport are taken into account as the novelties of this study. Policy makers of this city may apply the findings of this study—especially around the metro stations—to improve the average walking distance as well as walking behavior.

scholarly journals Google Street View Derived Built Environment Indicators and Associations with State-Level Obesity, Physical Activity, and Chronic Disease Mortality in the United States

2020 ◽  
Vol 17 (10) ◽  
pp. 3659
Author(s):  
Lynn Phan ◽  
Weijun Yu ◽  
Jessica M. Keralis ◽  
Krishay Mukhija ◽  
Pallavi Dwivedi ◽  
...  
Keyword(s):  
Physical Activity ◽  
Built Environment ◽  
Health Outcomes ◽  
State Level ◽  
Premature Mortality ◽  
The United States ◽  
Single Family ◽  
Google Street View ◽  
Street View ◽  
Neighborhood Built Environment

Previous studies have demonstrated that there is a high possibility that the presence of certain built environment characteristics can influence health outcomes, especially those related to obesity and physical activity. We examined the associations between select neighborhood built environment indicators (crosswalks, non-single family home buildings, single-lane roads, and visible wires), and health outcomes, including obesity, diabetes, cardiovascular disease, and premature mortality, at the state level. We utilized 31,247,167 images collected from Google Street View to create indicators for neighborhood built environment characteristics using deep learning techniques. Adjusted linear regression models were used to estimate the associations between aggregated built environment indicators and state-level health outcomes. Our results indicated that the presence of a crosswalk was associated with reductions in obesity and premature mortality. Visible wires were associated with increased obesity, decreased physical activity, and increases in premature mortality, diabetes mortality, and cardiovascular mortality (however, these results were not significant). Non-single family homes were associated with decreased diabetes and premature mortality, as well as increased physical activity and park and recreational access. Single-lane roads were associated with increased obesity and decreased park access. The findings of our study demonstrated that built environment features may be associated with a variety of adverse health outcomes.

Online Search Behaviour of Seeking Support for Obsessive Compulsive Disorder and Its Impact on Unemployment Level of the United States: Evidence from Google Search Queries (Preprint)

2019 ◽  
Author(s):  
Chamil W Senarathne ◽  
Wei Jianguo
Keyword(s):  
United States ◽  
The United States ◽  
Aggregate Data ◽  
Online Search ◽  
Search Behaviour ◽  
Search Queries ◽  
Compulsive Disorder ◽  
Google Search ◽  
The Impact ◽  
Age Category

BACKGROUND People have access to a massive volume of up-to-date health information processed by various search engines. Before seeing a doctor, people are used to seek information about identification and support available (e.g. doctors, support centers. forum discussions etc.) for their disorder/s online. Researchers have shown that Internet search queries contain much valuable information about the disequilibrium dynamics of various economics activities (e.g. employment, consumption). OCD as a disorder steals much of the valuable time, energy and effort in day-to-day work life and scholars argues that patients diagnosed with OCD may have higher unemployment rates and lower average income. Except for a handful of work examining the relationship between various disorders (e.g. cancer) and online search volume data, the direct linkage between online search behaviour of seeking support for OCD and unemployment in the United States has been completely ignored in the literature. OBJECTIVE The objective of this paper is to examine the impact of online search behaviour of identifying and seeking support for OCD on unemployment level of the United States at aggregate data and age category level. METHODS This paper analyzes 50 closely related online search terms on identifying and seeking support for OCD from March 2006 to June 2019. Ordinary least squares technique is used to identify the significance of the impact of search behaviour on the unemployment levels of the United States. After screening for instrumentality, a reduced version of regression is derived after treating for multicollinearity among regression variables. In order to eliminate the effect of searches made by people other than employed people who have subsequently been unemployed, a diagnostic regression is run. RESULTS The findings show that online search behaviour of identifying and seeking support for OCD significantly impacts unemployment level of the United States at overall regression level (p<0.01, R^2=73%) and age category level regressions (p<0.01, average R^2=66%). Moreover, the diagnostic test confirms that the regression on aggregate data and age category level data properly explains the underlying relationship as hypothesized because the coefficient of Google search queries driven (the effect) by employed population is positive and highly significant in explaining the unemployment level of the United States (p<0.01, average R^2=90%). CONCLUSIONS The findings of this study are helpful for policymakers and regulators in providing useful inputs for designing and administering programms on prevention and counseling OCD diagnosed working population of the United States. In particular, this paper is helpful in identifying the age categories of male and female employed population who are searching and seeking support on OCD. The government institutions in the USA must utilize online search queries for effective analysis and identification of different age category of people who are in need of support. Since search query data are available at country-level and regional level, this could easily be done by IT rather than population surveys that are costly and time consuming.

Associations Between Social Media Use, Physical Activity, and Emotional Well-Being From the Midlife in the United States Refresher Daily Diary Study

2021 ◽  
pp. 1-10
Author(s):  
Xin Yao Lin ◽  
Margie E. Lachman
Keyword(s):  
Physical Activity ◽  
United States ◽  
Social Media ◽  
Media Use ◽  
Daily Diary ◽  
Well Being ◽  
The United States ◽  
Diary Study ◽  
Social Media Use ◽  
Daily Diary Study

Only a small percentage of adults engage in regular physical activity, even though it is widely recommended as beneficial for well-being. Thus, it is essential to identify factors that can promote increased physical activity among adults of all ages. The current study examined the relationship of social media use to physical activity and emotional well-being. The sample is from the Midlife in the United States Refresher daily diary study, which includes 782 adults ages 25–75 years. Results showed that those who used social media less often engaged in more frequent physical activity, which, in turn, led to more positive affect. This relationship was found for midlife and older adults but not younger adults. The findings show the benefits of physical activity for well-being and suggest that social media use may dampen efforts to increase physical activity, especially among middle-aged and older adults.

scholarly journals Data Collection Instruments for Obesogenic Environments in Adults: A Scoping Review

2019 ◽  
Vol 16 (8) ◽  
pp. 1414 ◽  
Author(s):  
Martínez-García ◽  
Trescastro-López ◽  
Galiana-Sánchez ◽  
Pereyra-Zamora
Keyword(s):  
Data Collection ◽  
Built Environment ◽  
Scoping Review ◽  
Food Environment ◽  
Interdisciplinary Approach ◽  
The United States ◽  
Obesity Prevalence ◽  
Obesogenic Environment ◽  
Comparison Of The Results ◽  
Obesogenic Environments

The rise in obesity prevalence has increased research interest in the obesogenic environment and its influence on excess weight. The aim of the present study was to review and map data collection instruments for obesogenic environments in adults in order to provide an overview of the existing evidence and enable comparisons. Through the scoping review method, different databases and webpages were searched between January 1997 and May 2018. Instruments were included if they targeted adults. The documents were categorised as food environment or built environment. In terms of results, 92 instruments were found: 46 instruments measuring the food environment, 42 measuring the built environment, and 4 that characterised both environments. Numerous diverse instruments have been developed to characterise the obesogenic environment, and some of them have been developed based on existing ones; however, most of them have not been validated and there is very little similarity between them, hindering comparison of the results obtained. In addition, most of them were developed and used in the United States and were written in English. In conclusion, there is a need for a robust instrument, improving or combining existing ones, for use within and across countries, and more sophisticated study designs where the environment is contemplated in an interdisciplinary approach.

scholarly journals Ethnic Differences in Risk Factors for Obesity among Adults in California, the United States

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Liang Wang ◽  
Jodi Southerland ◽  
Kesheng Wang ◽  
Beth A. Bailey ◽  
Arsham Alamian ◽  
...  
Keyword(s):  
Physical Activity ◽  
Risk Factors ◽  
African Americans ◽  
Binge Drinking ◽  
Ethnic Disparities ◽  
The United States ◽  
California Health Interview Survey ◽  
Obesity Prevalence ◽  
Obesity Risk Factors ◽  
Using Data

Little attention has been given to differences in obesity risk factors by racial/ethnic groups. Using data from the 2011-2012 California Health Interview Survey, we examined differences in risk factors for obesity among Whites, Latinos, Asians, and African Americans among 42,935 adults (24.8% obese). Estimates were weighted to ensure an unbiased representation of the Californian population. Multiple logistic and linear regression analyses were used to examine the differences in risk factors for obesity. Large ethnic disparities were found in obesity prevalence: Whites (22.0%), Latinos (33.6%), African Americans (36.1%), and Asians (9.8%). Differences in risk factors for obesity were also observed: Whites (gender, age, physical activity, smoking, arthritis, and diabetes medicine intake), Latinos (age, arthritis, and diabetes medicine intake), Asians (age, binge drinking, arthritis, and diabetes medicine intake), and African Americans (gender, physical activity, smoking, binge drinking, and diabetes medicine intake). Females were more likely to be obese among African Americans (odds ratio (OR) = 1.43, 95% confidence interval (CI) = 1.05–1.94), but less likely among Whites (OR = 0.80, 95% CI = 0.74–0.87). Race/ethnicity should be considered in developing obesity prevention strategies.

scholarly journals The Causality Inference of Public Interest in Restaurants and Bars on Daily COVID-19 Cases in the United States: Google Trends Analysis

10.2196/22880 ◽  
2021 ◽  
Vol 7 (4) ◽  
pp. e22880
Author(s):  
Milad Asgari Mehrabadi ◽  
Nikil Dutt ◽  
Amir M Rahmani
Keyword(s):  
United States ◽  
Granger Causality ◽  
Public Interest ◽  
Granger Causality Test ◽  
The United States ◽  
Google Trends ◽  
Causality Test ◽  
Us States ◽  
Search Queries ◽  
Google Search

Background The COVID-19 pandemic has affected virtually every region in the world. At the time of this study, the number of daily new cases in the United States was greater than that in any other country, and the trend was increasing in most states. Google Trends provides data regarding public interest in various topics during different periods. Analyzing these trends using data mining methods may provide useful insights and observations regarding the COVID-19 outbreak. Objective The objective of this study is to consider the predictive ability of different search terms not directly related to COVID-19 with regard to the increase of daily cases in the United States. In particular, we are concerned with searches related to dine-in restaurants and bars. Data were obtained from the Google Trends application programming interface and the COVID-19 Tracking Project. Methods To test the causation of one time series on another, we used the Granger causality test. We considered the causation of two different search query trends related to dine-in restaurants and bars on daily positive cases in the US states and territories with the 10 highest and 10 lowest numbers of daily new cases of COVID-19. In addition, we used Pearson correlations to measure the linear relationships between different trends. Results Our results showed that for states and territories with higher numbers of daily cases, the historical trends in search queries related to bars and restaurants, which mainly occurred after reopening, significantly affected the number of daily new cases on average. California, for example, showed the most searches for restaurants on June 7, 2020; this affected the number of new cases within two weeks after the peak, with a P value of .004 for the Granger causality test. Conclusions Although a limited number of search queries were considered, Google search trends for restaurants and bars showed a significant effect on daily new cases in US states and territories with higher numbers of daily new cases. We showed that these influential search trends can be used to provide additional information for prediction tasks regarding new cases in each region. These predictions can help health care leaders manage and control the impact of the COVID-19 outbreak on society and prepare for its outcomes.

scholarly journals Social Media as an Early Proxy for Social Distancing Indicated by the COVID-19 Reproduction Number: Observational Study (Preprint)

2020 ◽  
Author(s):  
Joseph Younis ◽  
Harvy Freitag ◽  
Jeremy S Ruthberg ◽  
Jonathan P Romanes ◽  
Craig Nielsen ◽  
...  
Keyword(s):  
United States ◽  
Social Media ◽  
Observational Study ◽  
Social Mobility ◽  
Reproduction Number ◽  
The United States ◽  
Google Trends ◽  
Basic Reproductive Number ◽  
Social Distancing ◽  
Google Search

BACKGROUND  The magnitude and time course of the COVID-19 epidemic in the United States depends on early interventions to reduce the basic reproductive number to below 1. It is imperative, then, to develop methods to actively assess where quarantine measures such as social distancing may be deficient and suppress those potential resurgence nodes as early as possible. OBJECTIVE We ask if social media is an early indicator of public social distancing measures in the United States by investigating its correlation with the time-varying reproduction number (R<sub>t</sub>) as compared to social mobility estimates reported from Google and Apple Maps. METHODS  In this observational study, the estimated R<sub>t</sub> was obtained for the period between March 5 and April 5, 2020, using the EpiEstim package. Social media activity was assessed using queries of “social distancing” or “#socialdistancing” on Google Trends, Instagram, and Twitter, with social mobility assessed using Apple and Google Maps data. Cross-correlations were performed between R<sub>t</sub> and social media activity or mobility for the United States. We used Pearson correlations and the coefficient of determination (ρ) with significance set to <i>P</i>&lt;.05. RESULTS Negative correlations were found between Google search interest for “social distancing” and R<sub>t</sub> in the United States (<i>P</i>&lt;.001), and between search interest and state-specific R<sub>t</sub> for 9 states with the highest COVID-19 cases (<i>P</i>&lt;.001); most states experienced a delay varying between 3-8 days before reaching significance. A negative correlation was seen at a 4-day delay from the start of the Instagram hashtag “#socialdistancing” and at 6 days for Twitter (<i>P</i>&lt;.001). Significant correlations between R<sub>t</sub> and social media manifest earlier in time compared to social mobility measures from Google and Apple Maps, with peaks at –6 and –4 days. Meanwhile, changes in social mobility correlated best with R<sub>t</sub> at –2 days and +1 day for workplace and grocery/pharmacy, respectively. CONCLUSIONS Our study demonstrates the potential use of Google Trends, Instagram, and Twitter as epidemiological tools in the assessment of social distancing measures in the United States during the early course of the COVID-19 pandemic. Their correlation and earlier rise and peak in correlative strength with R<sub>t</sub> when compared to social mobility may provide proactive insight into whether social distancing efforts are sufficiently enacted. Whether this proves valuable in the creation of more accurate assessments of the early epidemic course is uncertain due to limitations. These limitations include the use of a biased sample that is internet literate with internet access, which may covary with socioeconomic status, education, geography, and age, and the use of subtotal social media mentions of social distancing. Future studies should focus on investigating how social media reactions change during the course of the epidemic, as well as the conversion of social media behavior to actual physical behavior.

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