County-Level Life Expectancy Change: A Novel Metric for Monitoring Public Health.

Life expectancy (LE) is a core measure of population health. Studies have confirmed the predictive importance of modifiable determinants on LE, but less is known about their association with LE change over time at the US county level. In addition, we explore the predictive association of LE change with COVID-19 mortality. We used a linear regression model to calculate county-level annual LE change from 2011 to 2016, and categorized LE change (≤-0.1 years change per year as decreasing, ≥0.1 years as increasing, otherwise no change). A multinomial regression model was used to determine the association between modifiable determinants of health indicators from the County Health Rankings and LE change. A Poisson regression model was used to evaluate the relationship between change in life expectancy and COVID-19 mortality through September 2021. Among 2943 counties, several modifiable determinants of health were significantly associated with odds of being in increasing LE or decreasing LE counties, including adult smoking, obesity, unemployment, and proportion of children in poverty. The presence of an increasing LE in 2011-2016, as compared to no change, was significantly associated with a 5% decrease in COVID-19 mortality between 2019 and 2021 (ß = 0.953, 95% CI: 0.943, 0.963). We demonstrated that change in LE at the county level is a useful metric for tracking public health progress, measuring the impact of public health initiatives, and gauging preparedness and vulnerability for future public health emergencies.

Infographics Are More Effective at Increasing Social Media Attention in Comparison With Original Research Articles: An Altmetrics-Based Analysis.

PURPOSE: To compare social media attention and citation rates between infographics (visual abstracts) and original research articles. METHODS: All infographics in 2019 from electronic versions of Arthroscopy were matched by topic to articles in the "Original Research" section of the journal in a 4:1 ratio within the same year. The primary outcome was the Altmetric Attention Score (AAS), a cumulative measure of social media attention from various platforms such as Twitter and Facebook. Secondary outcomes included citation rates, article characteristics, and number of shares on social media platforms. Independent t tests and χ2 analyses were used to compare primary and secondary outcomes between infographics and control articles. Multivariate linear regression analysis was performed to determine the association between article type and social media attention while controlling for bibliometric characteristics. RESULTS: A total of 60 matched research articles (n = 48, 80.0%) and infographics (n = 12, 20.0%) published in 2019 in Arthroscopy were included. The mean AAS among all infographics was 29.75 ± 32.84 (range, 3-118), whereas the mean AAS among all control research articles was 5.75 ± 8.90 (range, 0-41), representing a statistically significant difference (P < .001). Infographics had significantly more Twitter mentions (100% vs 70.8%, P < .001) and Facebook mentions (75% vs. 6.2%, P < .001) compared with original articles. Multivariate linear regression analysis demonstrated a statistically significant and positive association between AAS and article type, with an additional mean increase in the AAS of 33.7 (95% confidence interval 11.6-50.6; P = .003) for every infographic article compared with an original research article. The mean citation rate among all infographics was 2.4 ± 2.4 (range, 0-7), whereas the mean citation rate among all control research articles was 2.2 ± 4.0 (range, 0-27), which was not a significant difference (P = .69). CONCLUSIONS: Infographics resulted in significantly greater AAS and social media attention in comparison with original research articles of similar topics. We recommend the routine creation of infographics by journals to increase the social media attention that their research and chosen topics of interest receive. However, viewers of infographics should read them out of interest but turn their attention toward the original article or a source of more detailed information before making changes in clinical decision-making or practice, as they can be oversimplified. CLINICAL RELEVANCE: Infographics are an increasingly used by journals as a form of depicting research findings from select studies. By producing infographics, journals may increase the amount of social media attention received for a particular study or topic of interest.