Trends in linoleic acid intake in the United States adult population: NHANES 1999–2014

2018 ◽  
Vol 133 ◽  
pp. 23-28 ◽  
Author(s):  
Susan K Raatz ◽  
Zach Conrad ◽  
Lisa Jahns
2020 ◽  
Author(s):  
Ruoyan Sun ◽  
Henna Budhwani

BACKGROUND Though public health systems are responding rapidly to the COVID-19 pandemic, outcomes from publicly available, crowd-sourced big data may assist in helping to identify hot spots, prioritize equipment allocation and staffing, while also informing health policy related to “shelter in place” and social distancing recommendations. OBJECTIVE To assess if the rising state-level prevalence of COVID-19 related posts on Twitter (tweets) is predictive of state-level cumulative COVID-19 incidence after controlling for socio-economic characteristics. METHODS We identified extracted COVID-19 related tweets from January 21st to March 7th (2020) across all 50 states (N = 7,427,057). Tweets were combined with state-level characteristics and confirmed COVID-19 cases to determine the association between public commentary and cumulative incidence. RESULTS The cumulative incidence of COVID-19 cases varied significantly across states. Ratio of tweet increase (p=0.03), number of physicians per 1,000 population (p=0.01), education attainment (p=0.006), income per capita (p = 0.002), and percentage of adult population (p=0.003) were positively associated with cumulative incidence. Ratio of tweet increase was significantly associated with the logarithmic of cumulative incidence (p=0.06) with a coefficient of 0.26. CONCLUSIONS An increase in the prevalence of state-level tweets was predictive of an increase in COVID-19 diagnoses, providing evidence that Twitter can be a valuable surveillance tool for public health.


2020 ◽  
pp. 1-10
Author(s):  
Jeremy S. Ruthberg ◽  
Chandruganesh Rasendran ◽  
Armine Kocharyan ◽  
Sarah E. Mowry ◽  
Todd D. Otteson

BACKGROUND: Vertigo and dizziness are extremely common conditions in the adult population and therefore place a significant social and economic burden on both patients and the healthcare system. However, limited information is available for the economic burden of vertigo and dizziness across various health care settings. OBJECTIVE: Estimate the economic burden of vertigo and dizziness, controlling for demographic, socioeconomic, and clinical comorbidities. METHODS: A retrospective analysis of data from the Medical Expenditures Panel Survey (2007–2015) was performed to analyze individuals with vertigo or dizziness from a nationally representative sample of the United States. Participants were included via self-reported data and International Classification of Diseases, 9th Revision Clinical Modification codes. A cross-validated 2-component generalized linear model was utilized to assess vertigo and dizziness expenditures across demographic, socioeconomic and clinical characteristics while controlling for covariates. Costs and utilization across various health care service sectors, including inpatient, outpatient, emergency department, home health, and prescription medications were evaluated. RESULTS: Of 221,273 patients over 18 years, 5,275 (66% female, 34% male) reported either vertigo or dizziness during 2007–2015. More patients with vertigo or dizziness were female, older, non-Hispanic Caucasian, publicly insured, and had significant clinical comorbidities compared to patients without either condition. Furthermore, each of these demographic, socioeconomic, and clinical characteristics lead to significantly elevated costs due to having these conditions for patients. Significantly higher medical expenditures and utilization across various healthcare sectors were associated with vertigo or dizziness (p <  0.001). The mean incremental annual healthcare expenditure directly associated with vertigo or dizziness was $2,658.73 (95% CI: 1868.79, 3385.66) after controlling for socioeconomic and demographic characteristics. Total annual medical expenditures for patients with dizziness or vertigo was $48.1 billion. CONCLUSION: Vertigo and dizziness lead to substantial expenses for patients across various healthcare settings. Determining how to limit costs and improve the delivery of care for these patients is of the utmost importance given the severe morbidity, disruption to daily living, and major socioeconomic burden associated with these conditions.


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