We examined the hemodynamic factors associated with the lower maximal O2 consumption (VO2max) in older formerly elite distance runners. Heart rate and VO2 were measured during submaximal and maximal treadmill exercise in 11 master [66 +/- 8 (SD) yr] and 11 young (32 +/- 5 yr) male runners. Cardiac output was determined using acetylene rebreathing at 30, 50, 70, and 85% VO2max. Maximal cardiac output was estimated using submaximal stroke volume and maximal heart rate. VO2max was 36% lower in master runners (45.0 +/- 6.9 vs. 70.4 +/- 8.0 ml.kg-1.min-1, P less than or equal to 0.05), because of both a lower maximal cardiac output (18.2 +/- 3.5 vs. 25.4 +/- 1.7 l.min-1) and arteriovenous O2 difference (16.6 +/- 1.6 vs. 18.7 +/- 1.4 ml O2.100 ml blood-1, P less than or equal to 0.05). Reduced maximal heart rate (154.4 +/- 17.4 vs. 185 +/- 5.8 beats.min-1) and stroke volume (117.1 +/- 16.1 vs. 137.2 +/- 8.7 ml.beat-1) contributed to the lower cardiac output in the older athletes (P less than or equal 0.05). These data indicate that VO2max is lower in master runners because of a diminished capacity to deliver and extract O2 during exercise.
National surveys of U.S. adults have observed significant increases in health-related internet use (HRIU), but there are documented disparities. The study aims to identify social and demographic patterns of health-related internet use among U.S. adults. Using data from the Health Information National Trends Survey (HINTS) 4 cycle 3 and HINTS 5 cycle 1, we examined HRIU across healthcare, health information seeking, and participation on social media. Primary predictors were gender, race/ethnicity, age, education, income, and nativity with adjustments for smoking and survey year. We used multivariable logistic regression with survey weights to identify independent predictors of HRIU. Of the 4817 respondents, 43% had used the internet to find a doctor; 80% had looked online for health information. Only 20% had used social media for a health issue; 7% participated in an online health support group. In multivariable models, older and low SES participants were significantly less likely to use the internet to look for a provider, use the internet to look for health information for themselves or someone else, and less likely to use social media for health issues. Use of the internet for health-related purposes is vast but varies significantly by demographics and intended use.
Background Adults with chronic conditions are disproportionately burdened by COVID-19 morbidity and mortality. Although COVID-19 mobile health (mHealth) apps have emerged, research on attitudes toward using COVID-19 mHealth tools among those with chronic conditions is scarce. Objective This study aimed to examine attitudes toward COVID-19, identify determinants of COVID-19 mHealth tool use across demographic and health-related characteristics, and evaluate associations between chronic health conditions and attitudes toward using COVID-19 mHealth tools (eg, mHealth or web-based methods for tracking COVID-19 exposures, symptoms, and recommendations). Methods We used nationally representative data from the COVID-19 Impact Survey collected from April to June 2020 (n=10,760). Primary exposure was a history of chronic conditions, which were defined as self-reported diagnoses of cardiometabolic, respiratory, immune-related, and mental health conditions and overweight/obesity. Primary outcomes were attitudes toward COVID-19 mHealth tools, including the likelihood of using (1) a mobile phone app to track COVID-19 symptoms and receive recommendations; (2) a website to track COVID-19 symptoms, track location, and receive recommendations; and (3) an app using location data to track potential COVID-19 exposure. Outcome response options for COVID-19 mHealth tool use were extremely/very likely, moderately likely, or not too likely/not likely at all. Multinomial logistic regression was used to compare the likelihood of COVID-19 mHealth tool use between people with different chronic health conditions, with not too likely/not likely at all responses used as the reference category for each outcome. We evaluated the determinants of each COVID-19 mHealth intervention using Poisson regression. Results Of the 10,760 respondents, 21.8% of respondents were extremely/very likely to use a mobile phone app or a website to track their COVID-19 symptoms and receive recommendations. Additionally, 24.1% of respondents were extremely/very likely to use a mobile phone app to track their location and receive push notifications about whether they have been exposed to COVID-19. After adjusting for age, race/ethnicity, sex, socioeconomic status, and residence, adults with mental health conditions were the most likely to report being extremely/very or moderately likely to use each mHealth intervention compared to those without such conditions. Adults with respiratory-related chronic diseases were extremely/very (conditional odds ratio 1.16, 95% CI 1.00-1.35) and moderately likely (conditional odds ratio 1.23, 95% CI 1.04-1.45) to use a mobile phone app to track their location and receive push notifications about whether they have been exposed to COVID-19. Conclusions Our study demonstrates that attitudes toward using COVID-19 mHealth tools vary widely across modalities (eg, web-based method vs app) and chronic health conditions. These findings may inform the adoption of long-term engagement with COVID-19 apps, which is crucial for determining their potential in reducing disparities in COVID-19 morbidity and mortality among individuals with chronic health conditions.
Adults living with chronic respiratory diseases are at higher risk of death due to COVID-19. Our objective was to evaluate the physical and mental health symptoms among US adults living with chronic respiratory conditions. We used data of 10,760 US adults from the nationally representative COVID-19 Impact Survey. Chronic respiratory conditions were self-reported and included asthma (14.7%), chronic obstructive pulmonary disease or COPD (4.7%), and bronchitis/emphysema (11.6%). We used multivariable Poisson regression to evaluate physical health symptoms. We estimated associations of mental health symptoms using multinomial logistic regression. In multivariable models, adults with asthma were more likely to report physical symptoms including runny or stuffy nose, chest congestion, fever, and chills. In addition, adults with COPD were more likely to report several physical symptoms including fever (adjusted prevalence ratio [aPR]: 1.37, 95% confidence interval [CI]: 1.09–1.72), chills (aPR: 2.10, 95% CI: 1.67–2.64), runny or stuffy nose (aPR: 1.78, 95% CI: 1.39–2.27), chest congestion (aPR: 2.14, 95% CI: 1.74–2.61), sneezing (aPR: 1.59, 95% CI: 1.23–2.05), and muscle or body aches (aPR: 1.38, 95% CI: 1.06–1.81). Adults with chronic respiratory conditions are more likely to report physical and mental health symptoms during the COVID-19 pandemic compared to others. Providers should prioritize discussing mental health symptom management as the pandemic continues to be a public health concern in the US.
Effective patient–provider communication is a cornerstone of patient-centered care. Patient portals provide an effective method for secure communication between patients or their proxies and their health care providers. With greater acceptability of patient portals in private practices, patients have a unique opportunity to manage their health care needs. However, studies have shown that less than 50% of patients reported accessing the electronic health record (EHR) in a 12-month period. We used HINTS 5 cycle 1 and cycle 2 to assess disparities among US residents 18 and older with any chronic condition regarding the use of EHR for secure direct messaging with providers, to request refills, to make clinical decisions, or to share medical records with another provider. The results indicate that respondents with multimorbidity are more likely to share their medical records with other providers. However, respondents who are 75 and older are less likely to share their medical records with another provider. Additionally, respondents who are 65 and older are less likely to use the EHR for secure direct messaging with their provider. Additional health care strategies and provider communication should be developed to encourage older patients with chronic conditions to leverage the use of patient portals for effective disease management.
There are documented disparities in smoking behaviors among Hispanic adults in the U.S., but little is known about patterns of e-cigarette use. Using data from the HINTS 5 cycle 1–3, we examined cigarette and e-cigarette history and current use, as well as perceptions of the dangers of e-cigarette use relative to cigarette use. Primary predictors were Hispanic ethnic group, gender, age, education, income, and English language proficiency. Binary outcomes were modeled using the logit link, and multinomial outcome variables were modeled using generalized logit model. Fifty-three percent of participants were Mexican, 8% Puerto Rican, 4% were Cuban, and 35% identified as other Hispanics. Of the 1618 respondents, 23% were former cigarette smokers and 10% were current cigarette smokers. Twenty percent reported history of electronic cigarettes and 4% reported current use. In multivariable models, Hispanic women were significantly less likely to report ever being smokers compared to Hispanic men (aOR = 0.61, 95% CI = 0.42, 0.88). Puerto Ricans were 2.4 times as likely to report being current smokers (95% CI = 1.11, 5.11) compared to Mexicans. Among Hispanics, significant differences in e-cigarette and cigarette use behaviors emerged by gender, age, ethnicity, and cancer history, with implications for tailoring smoking prevention and cessation messages.
BACKGROUND Adults with chronic conditions are disproportionately burdened by COVID-19 morbidity and mortality. Although COVID-19 mobile health (mHealth) apps have emerged, research on attitudes toward using COVID-19 mHealth tools among those with chronic conditions is scarce. OBJECTIVE This study aimed to examine attitudes toward COVID-19, identify determinants of COVID-19 mHealth tool use across demographic and health-related characteristics, and evaluate associations between chronic health conditions and attitudes toward using COVID-19 mHealth tools (eg, mHealth or web-based methods for tracking COVID-19 exposures, symptoms, and recommendations). METHODS We used nationally representative data from the COVID-19 Impact Survey collected from April to June 2020 (n=10,760). Primary exposure was a history of chronic conditions, which were defined as self-reported diagnoses of cardiometabolic, respiratory, immune-related, and mental health conditions and overweight/obesity. Primary outcomes were attitudes toward COVID-19 mHealth tools, including the likelihood of using (1) a mobile phone app to track COVID-19 symptoms and receive recommendations; (2) a website to track COVID-19 symptoms, track location, and receive recommendations; and (3) an app using location data to track potential COVID-19 exposure. Outcome response options for COVID-19 mHealth tool use were extremely/very likely, moderately likely, or not too likely/not likely at all. Multinomial logistic regression was used to compare the likelihood of COVID-19 mHealth tool use between people with different chronic health conditions, with not too likely/not likely at all responses used as the reference category for each outcome. We evaluated the determinants of each COVID-19 mHealth intervention using Poisson regression. RESULTS Of the 10,760 respondents, 21.8% of respondents were extremely/very likely to use a mobile phone app or a website to track their COVID-19 symptoms and receive recommendations. Additionally, 24.1% of respondents were extremely/very likely to use a mobile phone app to track their location and receive push notifications about whether they have been exposed to COVID-19. After adjusting for age, race/ethnicity, sex, socioeconomic status, and residence, adults with mental health conditions were the most likely to report being extremely/very or moderately likely to use each mHealth intervention compared to those without such conditions. Adults with respiratory-related chronic diseases were extremely/very (conditional odds ratio 1.16, 95% CI 1.00-1.35) and moderately likely (conditional odds ratio 1.23, 95% CI 1.04-1.45) to use a mobile phone app to track their location and receive push notifications about whether they have been exposed to COVID-19. CONCLUSIONS Our study demonstrates that attitudes toward using COVID-19 mHealth tools vary widely across modalities (eg, web-based method vs app) and chronic health conditions. These findings may inform the adoption of long-term engagement with COVID-19 apps, which is crucial for determining their potential in reducing disparities in COVID-19 morbidity and mortality among individuals with chronic health conditions.
e18573 Background: Despite the use of clinical trials to provide gold-standard evidence of treatment and intervention effectiveness, racial/ethnic minorities are frequently underrepresented participants. Our objective was to evaluate racial/ethnic differences in knowledge and attitudes towards clinical trials among adults in the U.S. Methods: We leveraged Health Informational National Trends Survey (HINTS) data, which is a weighted, nationally representative survey of 3865 adults (≥18 years). Data were collected between February-June 2020, and included age, race/ethnicity, sex, cancer history, and comorbidities. Participants were asked questions focused on clinical trials, including their knowledge, influential factors to participate, trusted sources of information, and if they were ever invited or participated in a clinical trial. Among adults who self-reported to have heard of clinical trials (n = 2366), we used multivariable logistic regression to evaluate racial/ethnic differences in self-reported invitation and participation in clinical trials after adjustment for cancer history, age, sex, comorbidities, and insurance status. Results: Overall, the sample included 64% non-Hispanic (NH) White, 11% NH-Black, 17% Hispanic, and 5% NH-Asian respondents. Nine percent were cancer survivors. Almost 60% self-reported to at least have some knowledge about clinical trials. When asked about factors that would influence their decision to participate in clinical trials “A lot”, participants across racial groups most frequently chose “I would want to get better” and “If the standard care was not covered by my insurance.” Cancer survivors also frequently reported their decision would be influenced “A lot” or “Somewhat” if “My doctor encouraged me to participate.” NH-White (76%), NH-Black (78%), and Hispanic (77%) cancer survivors reported their trusted source of information about clinical trials was their health care provider; NH-Asian cancer survivors reported their health care provider (51%) as well as government health agencies (30%). Compared to NH-White adults, NH-Black adults were more likely to be invited to participate in a clinical trial (OR: 2.60, 95% CI: 1.53-4.43). However, compared to NH-White adults, our data suggest NH-Black adults were less likely to participate in the clinical trial (OR: 0.76, 95% CI: 0.39-1.49) although not statistically significant. Compared to NH-White adults, NH-Asian adults were less likely to participate in clinical trials (OR: 0.10, 95% CI: 0.06-0.18). Conclusions: Health care providers are a trusted source of clinical trial information. Although NH-Black adults are more likely to be invited, they are less likely to participate in a clinical trial; as well as Asian adults. Efforts to leverage insights gained on factors of influence and sources of trusted information on clinical trials should be prioritized.
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