METHODS: The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2021 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease.
RESULTS: Each of the 27 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.
CONCLUSIONS: The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
METHODS: Five graph models were fit using data from 1574 people who inject drugs in Hartford, CT, USA. We used a degree-corrected stochastic block model, based on goodness-of-fit, to model networks of injection drug users. We simulated transmission of HCV and HIV through this network with varying levels of HCV treatment coverage (0%, 3%, 6%, 12%, or 24%) and varying baseline HCV prevalence in people who inject drugs (30%, 60%, 75%, or 85%). We compared the effectiveness of seven treatment-as-prevention strategies on reducing HCV prevalence over 10 years and 20 years versus no treatment. The strategies consisted of treatment assigned to either a randomly chosen individual who injects drugs or to an individual with the highest number of injection partners. Additional strategies explored the effects of treating either none, half, or all of the injection partners of the selected individual, as well as a strategy based on respondent-driven recruitment into treatment.
FINDINGS: Our model estimates show that at the highest baseline HCV prevalence in people who inject drugs (85%), expansion of treatment coverage does not substantially reduce HCV prevalence for any treatment-as-prevention strategy. However, when baseline HCV prevalence is 60% or lower, treating more than 120 (12%) individuals per 1000 people who inject drugs per year would probably eliminate HCV within 10 years. On average, assigning treatment randomly to individuals who inject drugs is better than targeting individuals with the most injection partners. Treatment-as-prevention strategies that treat additional network members are among the best performing strategies and can enhance less effective strategies that target the degree (ie, the highest number of injection partners) within the network.
INTERPRETATION: Successful HCV treatment as prevention should incorporate the baseline HCV prevalence and will achieve the greatest benefit when coverage is sufficiently expanded.
FUNDING: National Institute on Drug Abuse.
METHODS: Behavioural Risk Factors Surveillance System data were used to estimate the weight the US population needed to lose to achieve a BMI
METHODS: The HIV-CAUSAL Collaboration consisted of 12 cohorts from the United States and Europe of HIV-positive, ART-naive, AIDS-free individuals aged ≥18 years with baseline CD4 cell count and HIV RNA levels followed up from 1996 through 2007. We estimated hazard ratios (HRs) for cART versus no cART, adjusted for time-varying CD4 cell count and HIV RNA level via inverse probability weighting.
RESULTS: Of 65 121 individuals, 712 developed tuberculosis over 28 months of median follow-up (incidence, 3.0 cases per 1000 person-years). The HR for tuberculosis for cART versus no cART was 0.56 (95% confidence interval [CI], 0.44-0.72) overall, 1.04 (95% CI, 0.64-1.68) for individuals aged >50 years, and 1.46 (95% CI, 0.70-3.04) for people with a CD4 cell count of <50 cells/μL. Compared with people who had not started cART, HRs differed by time since cART initiation: 1.36 (95% CI, 0.98-1.89) for initiation <3 months ago and 0.44 (95% CI, 0.34-0.58) for initiation ≥3 months ago. Compared with people who had not initiated cART, HRs <3 months after cART initiation were 0.67 (95% CI, 0.38-1.18), 1.51 (95% CI, 0.98-2.31), and 3.20 (95% CI, 1.34-7.60) for people <35, 35-50, and >50 years old, respectively, and 2.30 (95% CI, 1.03-5.14) for people with a CD4 cell count of <50 cells/μL.
CONCLUSIONS: Tuberculosis incidence decreased after cART initiation but not among people >50 years old or with CD4 cell counts of <50 cells/μL. Despite an overall decrease in tuberculosis incidence, the increased rate during 3 months of ART suggests unmasking IRIS.
METHODS: We conducted a cross-sectional study consisting of 1551 participants from the National Heart, Lung and Blood Institute Family Heart Study to assess the relation of Apo E polymorphism with the prevalence of MetS. MetS was defined according to the American Heart Association-National Heart, Lung and Blood Institute-International Diabetes Federation-World Health Organization harmonized criteria. We used generalized estimating equations to estimate adjusted odds ratios (ORs) for prevalent MetS and the Bonferroni correction to account for multiple testing in the secondary analysis.
RESULTS: Our study population had a mean age (standard deviation) of 56.5 (11.0) years, and 49.7% had MetS. There was no association between the Apo E genotypes and the MetS. The multivariable adjusted ORs (95% confidence interval) were 1.00 (reference), 1.26 (0.31-5.21), 0.89 (0.62-1.29), 1.13 (0.61-2.10), 1.13 (0.88-1.47) and 1.87 (0.91-3.85) for the Ɛ3/Ɛ3, Ɛ2/Ɛ2, Ɛ2/Ɛ3, Ɛ2/Ɛ4, Ɛ3/Ɛ4 and Ɛ4/Ɛ4 genotypes, respectively. In a secondary analysis, Ɛ2/Ɛ3 genotype was associated with 41% lower prevalence odds of low high-density lipoprotein [multivariable adjusted ORs (95% confidence interval) = 0.59 (0.36-0.95)] compared with Ɛ3/Ɛ3 genotype.
CONCLUSIONS: Our findings do not support an association between Apo E polymorphism and MetS in a multicentre population-based study of predominantly White US men and women.
METHODS: Data were from population-based studies of aging and their Harmonized Cognitive Assessment Protocols (HCAPs) in the US, South Africa, India, and Mexico (N = 10,037; Age range: 50 to 105 years; 2016 to 2020). Main lifetime occupational skill was classified according to the International Standard Classification of Occupations. Weighted, adjusted regression models estimated pooled and country-specific associations between main lifetime occupational skill and later-life general cognitive function in men and women.
RESULTS: We observed positive gradients between occupational skill and later-life cognitive function for men and women in the US and Mexico, a positive gradient for women but not men in India, and no association for men or women in South Africa.
DISCUSSION: Main lifetime occupations may be a source of later-life cognitive reserve, with cross-national heterogeneity in this association.
HIGHLIGHTS: No studies have examined cross-national differences in the association of occupational skill with cognition. We used data from Harmonized Cognitive Assessment Protocols in the US, Mexico, India, and South Africa. The association of occupational skill with cognitive function varies by country and gender.
OBJECTIVE: This study aims to analyze and evaluate the contents as well as features of COVID-19 mobile apps. The findings are instrumental in helping health care professionals to identify suitable mobile apps for COVID-19 self-monitoring and education. The results of the mobile apps' assessment could potentially help mobile app developers improve or modify their existing mobile app designs to achieve optimal outcomes.
METHODS: The search for the mHealth apps available in the android-based Play Store and the iOS-based App Store was conducted between April 18 and May 5, 2020. The region of the App Store where we performed the search was the United States, and a virtual private network app was used to locate and access COVID-19 mobile apps from all countries on the Google Play Store. The inclusion criteria were apps that are related to COVID-19 with no restriction in language type. The basic features assessment criteria used for comparison were the requirement for free subscription, internet connection, education or advisory content, size of the app, ability to export data, and automated data entry. The functionality of the apps was assessed according to knowledge (information on COVID-19), tracing or mapping of COVID-19 cases, home monitoring surveillance, online consultation with a health authority, and official apps run by health authorities.
RESULTS: Of the 223 COVID-19-related mobile apps, only 30 (19.9%) found in the App Store and 28 (44.4%) in the Play Store matched the inclusion criteria. In the basic features assessment, most App Store (10/30, 33.3%) and Play Store (10/28, 35.7%) apps scored 4 out of 7 points. Meanwhile, the outcome of the functionality assessment for most App Store apps (13/30, 43.3%) was a score of 3 compared to android-based apps (10/28, 35.7%), which scored 2 (out of the maximum 5 points). Evaluation of the basic functions showed that 75.0% (n=36) of the 48 included mobile apps do not require a subscription, 56.3% (n=27) provide symptom advice, and 41.7% (n=20) have educational content. In terms of the specific functions, more than half of the included mobile apps are official mobile apps maintained by a health authority for COVID-19 information provision. Around 37.5% (n=18) and 31.3% (n=15) of the mobile apps have tracing or mapping and home monitoring surveillance functions, respectively, with only 17% (n=8) of the mobile apps equipped with an online consultation function.
CONCLUSIONS: Most iOS-based apps incorporate infographic mapping of COVID-19 cases, while most android-based apps incorporate home monitoring surveillance features instead of providing focused educational content on COVID-19. It is important to evaluate the contents and features of COVID-19 mobile apps to guide users in choosing a suitable mobile app based on their requirements.
METHODS: Using empirical data from Hartford, Connecticut, we deployed a stochastic block model to simulate an injection network of 1574 PWID. We used a susceptible-infected model for HCV and human immunodeficiency virus to evaluate the effectiveness of several HCV TasP strategies, including in combination with OAT and SSP scale-up, over 20 years.
RESULTS: At the highest HCV prevalence (75%), when OAT coverage is increased from 10% to 40%, combined with HCV treatment of 10% per year and SSP scale up to 40%, the time to achieve microelimination is reduced from 18.4 to 11.6 years. At the current HCV prevalence (60%), HCV TasP strategies as low as 10% coverage per year may achieve HCV microelimination within 10 years, with minimal impact from additional OAT scale-up. Strategies based on mass initial HCV treatment (50 per 100 PWID the first year followed by 5 per 100 PWID thereafter) were most effective in settings with HCV prevalence of 60% or lower.
CONCLUSIONS: Scale-up of HCV TasP is the most effective strategy for microelimination of HCV. OAT scale-up, however, scale-up may be synergistic toward achieving microelimination goals when HCV prevalence exceeds 60% and when HCV treatment coverage is 10 per 100 PWID per year or lower.