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.
Objective: To determine whether rates of gestational diabetes among individuals at first live birth changed from 2011 to 2019 and how these rates differ by race and ethnicity in the US.
Design, Setting, and Participants: Serial cross-sectional analysis using National Center for Health Statistics data for 12 610 235 individuals aged 15 to 44 years with singleton first live births from 2011 to 2019 in the US.
Exposures: Gestational diabetes data stratified by the following race and ethnicity groups: Hispanic/Latina (including Central and South American, Cuban, Mexican, and Puerto Rican); non-Hispanic Asian/Pacific Islander (including Asian Indian, Chinese, Filipina, Japanese, Korean, and Vietnamese); non-Hispanic Black; and non-Hispanic White.
Main Outcomes and Measures: The primary outcomes were age-standardized rates of gestational diabetes (per 1000 live births) and respective mean annual percent change and rate ratios (RRs) of gestational diabetes in non-Hispanic Asian/Pacific Islander (overall and in subgroups), non-Hispanic Black, and Hispanic/Latina (overall and in subgroups) individuals relative to non-Hispanic White individuals (referent group).
Results: Among the 12 610 235 included individuals (mean [SD] age, 26.3 [5.8] years), the overall age-standardized gestational diabetes rate significantly increased from 47.6 (95% CI, 47.1-48.0) to 63.5 (95% CI, 63.1-64.0) per 1000 live births from 2011 to 2019, a mean annual percent change of 3.7% (95% CI, 2.8%-4.6%) per year. Of the 12 610 235 participants, 21% were Hispanic/Latina (2019 gestational diabetes rate, 66.6 [95% CI, 65.6-67.7]; RR, 1.15 [95% CI, 1.13-1.18]), 8% were non-Hispanic Asian/Pacific Islander (2019 gestational diabetes rate, 102.7 [95% CI, 100.7-104.7]; RR, 1.78 [95% CI, 1.74-1.82]), 14% were non-Hispanic Black (2019 gestational diabetes rate, 55.7 [95% CI, 54.5-57.0]; RR, 0.97 [95% CI, 0.94-0.99]), and 56% were non-Hispanic White (2019 gestational diabetes rate, 57.7 [95% CI, 57.2-58.3]; referent group). Gestational diabetes rates were highest in Asian Indian participants (2019 gestational diabetes rate, 129.1 [95% CI, 100.7-104.7]; RR, 2.24 [95% CI, 2.15-2.33]). Among Hispanic/Latina participants, gestational diabetes rates were highest among Puerto Rican individuals (2019 gestational diabetes rate, 75.8 [95% CI, 71.8-79.9]; RR, 1.31 [95% CI, 1.24-1.39]). Gestational diabetes rates increased among all race and ethnicity subgroups and across all age groups.
Conclusions and Relevance: Among individuals with a singleton first live birth in the US from 2011 to 2019, rates of gestational diabetes increased across all racial and ethnic subgroups. Differences in absolute gestational diabetes rates were observed across race and ethnicity subgroups.
OBJECTIVE: To analyze trends in levels of lipids and apolipoprotein B in US youths during 18 years from 1999 through 2016.
DESIGN, SETTING, AND PARTICIPANTS: Serial cross-sectional analysis of US population-weighted data for youths aged 6 to 19 years from the National Health and Nutrition Examination Surveys for 1999 through 2016. Linear temporal trends were analyzed using multivariable regression models with regression coefficients (β) reported as change per 1 year.
EXPOSURES: Survey year; examined periods spanned 10 to 18 years based on data availability.
MAIN OUTCOMES AND MEASURES: Age- and race/ethnicity-adjusted mean levels of high-density lipoprotein (HDL), non-HDL, and total cholesterol. Among fasting adolescents (aged 12-19 years), mean levels of low-density lipoprotein cholesterol, geometric mean levels of triglycerides, and mean levels of apolipoprotein B. Prevalence of ideal and adverse (vs borderline) levels of lipids and apolipoprotein B per pediatric lipid guidelines.
RESULTS: In total, 26 047 youths were included (weighted mean age, 12.4 years; female, 51%). Among all youths, the adjusted mean total cholesterol level declined from 164 mg/dL (95% CI, 161 to 167 mg/dL) in 1999-2000 to 155 mg/dL (95% CI, 154 to 157 mg/dL) in 2015-2016 (β for linear trend, -0.6 mg/dL [95% CI, -0.7 to -0.4 mg/dL] per year). Adjusted mean HDL cholesterol level increased from 52.5 mg/dL (95% CI, 51.7 to 53.3 mg/dL) in 2007-2008 to 55.0 mg/dL (95% CI, 53.8 to 56.3 mg/dL) in 2015-2016 (β, 0.2 mg/dL [95% CI, 0.1 to 0.4 mg/dL] per year) and non-HDL cholesterol decreased from 108 mg/dL (95% CI, 106 to 110 mg/dL) to 100 mg/dL (95% CI, 99 to 102 mg/dL) during the same years (β, -0.9 mg/dL [95% CI, -1.2 to -0.6 mg/dL] per year). Among fasting adolescents, geometric mean levels of triglycerides declined from 78 mg/dL (95% CI, 74 to 82 mg/dL) in 1999-2000 to 63 mg/dL (95% CI, 58 to 68 mg/dL) in 2013-2014 (log-transformed β, -0.015 [95% CI, -0.020 to -0.010] per year), mean levels of low-density lipoprotein cholesterol declined from 92 mg/dL (95% CI, 89 to 95 mg/dL) to 86 mg/dL (95% CI, 83 to 90 mg/dL) during the same years (β, -0.4 mg/dL [95% CI, -0.7 to -0.2 mg/dL] per year), and mean levels of apolipoprotein B declined from 70 mg/dL (95% CI, 68 to 72 mg/dL) in 2005-2006 to 67 mg/dL (95% CI, 65 to 70 mg/dL) in 2013-2014 (β, -0.4 mg/dL [95% CI, -0.7 to -0.04 mg/dL] per year). Favorable trends were generally also observed in the prevalence of ideal and adverse levels. By the end of the study period, 51.4% (95% CI, 48.5% to 54.2%) of all youths had ideal levels for HDL, non-HDL, and total cholesterol; among adolescents, 46.8% (95% CI, 40.9% to 52.6%) had ideal levels for all lipids and apolipoprotein B, whereas 15.2% (95% CI, 13.1% to 17.3%) of children aged 6 to 11 years and 25.2% (95% CI, 22.2% to 28.2%) of adolescents aged 12 to 19 years had at least 1 adverse level.
CONCLUSIONS AND RELEVANCE: Between 1999 and 2016, favorable trends were observed in levels of lipids and apolipoprotein B in US youths aged 6 to 19 years.
METHODS: Behavioural Risk Factors Surveillance System data were used to estimate the weight the US population needed to lose to achieve a BMI
METHODS: In this umbrella review, we searched four databases (Pubmed, Embase, the Cochrane Database of Systematic Reviews, and Epistemonikos) from database inception to April 2022. The methodological quality of each meta-analysis was assessed using the Assessment of Multiple Systematic Reviews, version 2 (AMSTAR-2). The strength of evidence of the associations between race and ethnicity with outcomes was ranked according to established criteria as convincing, highly suggestive, suggestive, weak, or non-significant. The study protocol was registered with PROSPERO, CRD42022336805.
RESULTS: Of 880 records screened, we selected seven meta-analyses for evidence synthesis, with 42 associations examined. Overall, 10 of 42 associations were statistically significant (p ≤ 0.05). Two associations were highly suggestive, two were suggestive, and two were weak, whereas the remaining 32 associations were non-significant. The risk of COVID-19 infection was higher in Black individuals compared to White individuals (risk ratio, 2.08, 95% Confidence Interval (CI), 1.60-2.71), which was supported by highly suggestive evidence; with the conservative estimates from the sensitivity analyses, this association remained suggestive. Among those infected with COVID-19, Hispanic individuals had a higher risk of COVID-19 hospitalization than non-Hispanic White individuals (odds ratio, 2.08, 95% CI, 1.60-2.70) with highly suggestive evidence which remained after sensitivity analyses.
CONCLUSION: Individuals of Black and Hispanic groups had a higher risk of COVID-19 infection and hospitalization compared to their White counterparts. These associations of race and ethnicity and COVID-19 outcomes existed more obviously in the pre-hospitalization stage. More consideration should be given in this stage for addressing health inequity.
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: 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: A total of 13 805 non-US-born persons at high risk of TB infection or progression to TB disease were screened for LTBI at 16 clinical sites located across the United States with a tuberculin skin test, QuantiFERON Gold In-Tube test, and T-SPOT.TB test. Bayesian latent class analysis was applied to test results to estimate LTBI prevalence and associated credible intervals (CrIs) for each country or world region of birth.
RESULTS: Among the study population, the estimated LTBI prevalence was 31% (95% CrI, 26%-35%). Country-of-birth-level LTBI prevalence estimates were highest for persons born in Haiti, Peru, Somalia, Ethiopia, Vietnam, and Bhutan, ranging from 42% to 55%. LTBI prevalence estimates were lowest for persons born in Colombia, Malaysia, and Thailand, ranging from 8% to 13%.
CONCLUSIONS: LTBI prevalence in persons born outside the US varies widely by country. These estimates can help target community outreach efforts to the highest-risk groups.
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.
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.