ImportanceSome individuals experience persistent symptoms after initial symptomatic SARS-CoV-2 infection (often referred to as Long COVID).ObjectiveTo estimate the proportion of males and females with COVID-19, younger or older than 20 years of age, who had Long COVID symptoms in 2020 and 2021 and their Long COVID symptom duration.Design, Setting, and ParticipantsBayesian meta-regression and pooling of 54 studies and 2 medical record databases with data for 1.2 million individuals (from 22 countries) who had symptomatic SARS-CoV-2 infection. Of the 54 studies, 44 were published and 10 were collaborating cohorts (conducted in Austria, the Faroe Islands, Germany, Iran, Italy, the Netherlands, Russia, Sweden, Switzerland, and the US). The participant data were derived from the 44 published studies (10 501 hospitalized individuals and 42 891 nonhospitalized individuals), the 10 collaborating cohort studies (10 526 and 1906), and the 2 US electronic medical record databases (250 928 and 846 046). Data collection spanned March 2020 to January 2022.ExposuresSymptomatic SARS-CoV-2 infection.Main Outcomes and MeasuresProportion of individuals with at least 1 of the 3 self-reported Long COVID symptom clusters (persistent fatigue with bodily pain or mood swings; cognitive problems; or ongoing respiratory problems) 3 months after SARS-CoV-2 infection in 2020 and 2021, estimated separately for hospitalized and nonhospitalized individuals aged 20 years or older by sex and for both sexes of nonhospitalized individuals younger than 20 years of age.ResultsA total of 1.2 million individuals who had symptomatic SARS-CoV-2 infection were included (mean age, 4-66 years; males, 26%-88%). In the modeled estimates, 6.2% (95% uncertainty interval [UI], 2.4%-13.3%) of individuals who had symptomatic SARS-CoV-2 infection experienced at least 1 of the 3 Long COVID symptom clusters in 2020 and 2021, including 3.2% (95% UI, 0.6%-10.0%) for persistent fatigue with bodily pain or mood swings, 3.7% (95% UI, 0.9%-9.6%) for ongoing respiratory problems, and 2.2% (95% UI, 0.3%-7.6%) for cognitive problems after adjusting for health status before COVID-19, comprising an estimated 51.0% (95% UI, 16.9%-92.4%), 60.4% (95% UI, 18.9%-89.1%), and 35.4% (95% UI, 9.4%-75.1%), respectively, of Long COVID cases. The Long COVID symptom clusters were more common in women aged 20 years or older (10.6% [95% UI, 4.3%-22.2%]) 3 months after symptomatic SARS-CoV-2 infection than in men aged 20 years or older (5.4% [95% UI, 2.2%-11.7%]). Both sexes younger than 20 years of age were estimated to be affected in 2.8% (95% UI, 0.9%-7.0%) of symptomatic SARS-CoV-2 infections. The estimated mean Long COVID symptom cluster duration was 9.0 months (95% UI, 7.0-12.0 months) among hospitalized individuals and 4.0 months (95% UI, 3.6-4.6 months) among nonhospitalized individuals. Among individuals with Long COVID symptoms 3 months after symptomatic SARS-CoV-2 infection, an estimated 15.1% (95% UI, 10.3%-21.1%) continued to experience symptoms at 12 months.Conclusions and RelevanceThis study presents modeled estimates of the proportion of individuals with at least 1 of 3 self-reported Long COVID symptom clusters (persistent fatigue with bodily pain or mood swings; cognitive problems; or ongoing respiratory problems) 3 months after symptomatic SARS-CoV-2 infection.

ObjectivesTo examine the association between the number of teeth remaining and cognitive decline among Chinese older adults over a 13-year period.DesignA large national longitudinal survey of Chinese older adultsSettingThe Chinese Longitudinal Healthy Longevity Survey (CLHLS) (1998–2011).ParticipantsA total of 8,153 eligible participants aged 60+ interviewed in up to six waves.MeasurementsCognitive function and teeth number were measured at each interview. Cognitive function was measured by the Mini-Mental Status Examination (MMSE). Number of natural teeth was self-reported. Individuals with severe cognitive impairment were excluded. Covariates included demographic characteristics, adult socioeconomic status characteristics, childhood socioeconomic status, health conditions, and health behaviors. Linear mixed models were applied in the analysis.ResultsThe mean teeth number at baseline was 17.5(SD = 0.1), and the mean of baseline cognitive function was 27.3(SD = 0.0). Cognitive function declined over time (β = -0.19, P < .001) after controlling covariates. But, regardless of time, more teeth were associated with better cognitive function (β = 0.01, P < .001). The interaction of teeth number and time was significant (β = 0.01, P < .001), suggesting that the participants who had more teeth showed a slower pace of cognitive decline over time than those with fewer teeth after controlling for other covariates.ConclusionThis study showed that tooth loss was associated with cognitive decline among Chinese older adults. Further studies are needed to examine the linkages between cognitive decline and oral health status using clinical examination data.

Background: Quality of life (QoL) is an important component of individuals' general well-being, particularly in older adults. However, factors influencing QoL among older adults in low-and middle-income countries (LMICs) have not been fully examined. Furthermore, the role of gender differences in relation to QoL in multiple LMICs has also not been examined in detail. Methods: This study used data from the World Health Organization's Study on global AGEing and adult health (SAGE), Wave-1. Based on a literature review of existing works, a set of variables-an independent variable and covariates-were selected. The study sample consisted of 33,019 participants aged 50 years and above from China, Ghana, India, Russia, and South Africa. Multivariate linear regression models were estimated with the World Health Organization QoL scores as the dependent variable. To preserve the analytical sample size, multiple imputation was used to account for missing data. Results: The results showed that generally, male older adults reported a better QoL than female older adults across all of the countries. The associations between QoL and sociodemographic factors, health-related factors, and social support factors among older adults differed according to country. Conclusions: This study provides a better understanding of QoL among older adults in LMICs, which can help prepare LMICs to better address the QoL of older adults. The results of this study can be used to develop programs to promote better living standards and services to reduce gender disparities and ultimately, to improve the QoL among older adults in LMICs.

Aims The objectives of this study were to (a) identify nursing journal articles that provoked the most online activity and discussion and (b) assess the association between these articles’ altmetric scores and publication characteristics, citation counts; and publishing journals metrics. Background Altmetrics, or alternative metrics, have recently emerged as a complementary way of measuring the societal impact of research by assessing the public engagement with research output. To date, no studies have yet investigated the online attention about scientific papers published in the nursing field. Design Integration of quantitative and qualitative synthesized evidence. Data sources and review methods InCites Journal Citation Report was used to identify a list of nursing journals indexed in the Web of Science Core Collection. Altmetric Explorer was selected as an altmetrics harvesting tool. The search in Altmetric Explorer yielded 66,608 research outputs from 118 nursing journals. The articles with the top 100 altmetric attention score (AAS) were identified and a new search, limited to only those 100 articles, was run to produce aggregate metrics specific to those articles. The articles were also exported for thematic analysis. Results The median AAS for the 100 articles was 248, ranging from 138 – 649. The articles were mostly discussed on Twitter, followed by news outlets and Mendeley. Articles indexed in the nursing journals category attracted low online attention compared with articles published in other health journal categories. Twitter remained the dominant source of attention over the years 2012–2018, followed distantly by news outlets. Most online attention came from the USA and the UK. Of the top 100 articles included in the study, the Journal of Advanced Nursing published the highest number of articles (N = 26; Median AAS = 179). The AAS was not significantly different between articles published in Q1 journals and those published in Q2 and Q3 journals. There was a significant relationship between articles’ AASs and their citation counts on Scopus and Web of Science. Publication date was significantly related to citation counts on Scopus and Web of Science but not with AASs. Conclusion Altmetrics will likely continue to evolve alongside the rapidly expanding use of social media and online platforms. As nursing continues to strive to have our research and scholarship inform policy, translated into practice and recognized for its scientific merit, we have to remain vigilant about the best ways to disseminate the important work we are doing. Research, such as this study, will allow nursing scholars to benchmark our progress as we adapt to the changing environment for measuring impact and quality in the digital age.