Tracking Self-reported Symptoms and Medical Conditions on Social Media During the COVID-19 Pandemic: Infodemiological Study.

BACKGROUND: Harnessing health-related data posted on social media in real time can offer insights into how the pandemic impacts the mental health and general well-being of individuals and populations over time. OBJECTIVE: This study aimed to obtain information on symptoms and medical conditions self-reported by non-Twitter social media users during the COVID-19 pandemic, to determine how discussion of these symptoms and medical conditions changed over time, and to identify correlations between frequency of the top 5 commonly mentioned symptoms post and daily COVID-19 statistics (new cases, new deaths, new active cases, and new recovered cases) in the United States. METHODS: We used natural language processing (NLP) algorithms to identify symptom- and medical condition-related topics being discussed on social media between June 14 and December 13, 2020. The sample posts were geotagged by NetBase, a third-party data provider. We calculated the positive predictive value and sensitivity to validate the classification of posts. We also assessed the frequency of health-related discussions on social media over time during the study period, and used Pearson correlation coefficients to identify statistically significant correlations between the frequency of the 5 most commonly mentioned symptoms and fluctuation of daily US COVID-19 statistics. RESULTS: Within a total of 9,807,813 posts (nearly 70% were sourced from the United States), we identified a discussion of 120 symptom-related topics and 1542 medical condition-related topics. Our classification of the health-related posts had a positive predictive value of over 80% and an average classification rate of 92% sensitivity. The 5 most commonly mentioned symptoms on social media during the study period were anxiety (in 201,303 posts or 12.2% of the total posts mentioning symptoms), generalized pain (189,673, 11.5%), weight loss (95,793, 5.8%), fatigue (91,252, 5.5%), and coughing (86,235, 5.2%). The 5 most discussed medical conditions were COVID-19 (in 5,420,276 posts or 66.4% of the total posts mentioning medical conditions), unspecified infectious disease (469,356, 5.8%), influenza (270,166, 3.3%), unspecified disorders of the central nervous system (253,407, 3.1%), and depression (151,752, 1.9%). Changes in posts in the frequency of anxiety, generalized pain, and weight loss were significant but negatively correlated with daily new COVID-19 cases in the United States (r=-0.49, r=-0.46, and r=-0.39, respectively; P<.05). Posts on the frequency of anxiety, generalized pain, weight loss, fatigue, and the changes in fatigue positively and significantly correlated with daily changes in both new deaths and new active cases in the United States (r ranged=0.39-0.48; P<.05). CONCLUSIONS: COVID-19 and symptoms of anxiety were the 2 most commonly discussed health-related topics on social media from June 14 to December 13, 2020. Real-time monitoring of social media posts on symptoms and medical conditions may help assess the population's mental health status and enhance public health surveillance for infectious disease.

Engagement With COVID-19 Public Health Measures in the United States: A Cross-sectional Social Media Analysis from June to November 2020.

BACKGROUND: COVID-19 has continued to spread in the United States and globally. Closely monitoring public engagement and perceptions of COVID-19 and preventive measures using social media data could provide important information for understanding the progress of current interventions and planning future programs. OBJECTIVE: The aim of this study is to measure the public's behaviors and perceptions regarding COVID-19 and its effects on daily life during 5 months of the pandemic. METHODS: Natural language processing (NLP) algorithms were used to identify COVID-19-related and unrelated topics in over 300 million online data sources from June 15 to November 15, 2020. Posts in the sample were geotagged by NetBase, a third-party data provider, and sensitivity and positive predictive value were both calculated to validate the classification of posts. Each post may have included discussion of multiple topics. The prevalence of discussion regarding these topics was measured over this time period and compared to daily case rates in the United States. RESULTS: The final sample size included 9,065,733 posts, 70% of which were sourced from the United States. In October and November, discussion including mentions of COVID-19 and related health behaviors did not increase as it had from June to September, despite an increase in COVID-19 daily cases in the United States beginning in October. Additionally, discussion was more focused on daily life topics (n=6,210,255, 69%), compared with COVID-19 in general (n=3,390,139, 37%) and COVID-19 public health measures (n=1,836,200, 20%). CONCLUSIONS: There was a decline in COVID-19-related social media discussion sourced mainly from the United States, even as COVID-19 cases in the United States increased to the highest rate since the beginning of the pandemic. Targeted public health messaging may be needed to ensure engagement in public health prevention measures as global vaccination efforts continue.

Physical activity mediates the relationship between fruit and vegetable consumption and cognitive functioning: a cross-sectional analysis.

Background: Excess adiposity is associated with impairments in cognitive functioning, whereas physical activity (PA) and fruit and vegetable consumption (FVC) may be protective against cognitive decline. Therefore, this study investigated the interrelationships between FVC, body mass index (BMI), PA and cognitive functioning in younger and older adults. Methods: Cross-sectional data of 45 522 participants (≥30 years) were examined from the 2012 annual component of the Canadian Community Health Survey. Cognitive function was assessed using a single six-level question of the Health Utilities Index. PA was classified according to the Physical Activity Index kilocalories per kilogram per day  as active, moderately active and inactive; BMI was measured in kg/m2 and FVC (servings/day) was classified as low, moderate or high. To assess the interrelationship between FVC, BMI, PA, age and cognitive functioning, general linear models and mediation analyses were used. Results: Higher BMIs, lower PA and FVC were associated with poorer cognitive functioning. Additionally, PA statistically mediated the relationship between FVC and cognitive function (Sobel test: t = -3.15; P < 0.002); and higher education levels and daily FVC were associated with better cognitive function (P < 0.001). Conclusion: Higher PA levels were associated with better cognitive functioning in younger and older adults. Also, higher daily FVC and education levels were associated with better cognitive scores.

Association Between Body Mass Index, Physical Activity, and Health-Related Quality of Life in Canadian Adults.

BACKGROUND: Obesity is associated with impairments in health-related quality of life (HRQL), whereas physical activity (PA) is a promoter of HRQL. PURPOSE: The aim of this study was to investigate the interaction between BMI and PA with HRQL in younger and older Canadian adults. METHODS: Data from the 2012 annual component of the Canadian Community Health Survey (N = 48,041; ≥ 30 years) were used to capture self-reported body mass index (BMI- kg/m2), PA (kcal/kg/day, KKD), and HRQL. Interactions between PA and age on the BMI and HRQL relationship were assessed using general linear models and logistic regression. RESULTS: Those younger (younger: µ = 0.79 ± 0.02; older: µ = 0.70 ± 0.02) and more active (active: µ = 0.82 ± 0.02; moderately active: µ = 0.77 ± 0.03; inactive: µ = 0.73 ± 0.01) reported higher HRQL. Older inactive underweight, normal weight, and overweight adults have lower odds of high HRQL. CONCLUSION: PA was associated with higher HRQL in younger adults. In older adults, BMI and PA influenced HRQL.

Attention-deficit/hyperactivity disorder in relation to addictive behaviors: a moderated-mediation analysis of personality-risk factors and sex.

INTRODUCTION: Research has shown that those with attention-deficit/hyperactivity disorder (ADHD) have an increased risk for addiction disorders like alcoholism and substance abuse. What is less clear is the mechanism(s) whereby ADHD gives rise to increased engagement in addictive behaviors, and whether there are sex differences in the ADHD-addiction propensity. Both ADHD and addictions have also been associated with personality traits such as impulsivity, reward seeking, anxiousness, and negative affect. In this study, we tested a moderator-mediation model, which predicted that both sex and ADHD-symptom status would make independent contributions to the variance in personality risk and in addictive behaviors, with males, and those with diagnosed ADHD, scoring higher on both dependent variables. Our model also predicted that the effect of sex and ADHD-symptom status on addictive behaviors would be via the mediating or intervening influence of personality-risk factors. METHODS: A community-based sample of young men and women took part in the study. Among these individuals, 46 had received a lifetime diagnosis of ADHD. The non-diagnosed participants were dichotomized into a high-ADHD-symptom group (n = 83) and a low-symptom group (n = 84). RESULTS: We found that a high-risk personality profile may, in part, account for the relationship between ADHD symptomatology and the use/abuse of a broad range of addictive behaviors. However, we found no sex differences in personality risk for addiction or in the use of addictive behaviors; nor did sex moderate the relationships we assessed. CONCLUSION: While ADHD status showed a strong relationship with both dependent variables in the model, we found no difference between those who had been diagnosed with ADHD and treated with stimulants, and their high-symptom non-diagnosed/non-treated counterparts. These results add support to claims that the treatment of ADHD with stimulant medication neither protects nor fosters the risk for substance abuse disorders.