OBJECTIVES: The purpose of this study was to describe trends in maternal pre-pregnancy hypertension among women in rural and urban areas in 2007 to 2018 in order to inform community-engaged prevention and policy strategies.
METHODS: We performed a nationwide, serial cross-sectional study using maternal data from all live births in women age 15 to 44 years between 2007 and 2018 (CDC Natality Database). Rates of pre-pregnancy hypertension were calculated per 1,000 live births overall and by urbanization status. Subgroup analysis in standard 5-year age categories was performed. We quantified average annual percentage change using Joinpoint Regression and rate ratios (95% confidence intervals [CIs]) to compare yearly rates between rural and urban areas.
RESULTS: Among 47,949,381 live births to women between 2007 and 2018, rates of pre-pregnancy hypertension per 1,000 live births increased among both rural (13.7 to 23.7) and urban women (10.5 to 20.0). Two significant inflection points were identified in 2010 and 2016, with highest annual percentage changes between 2016 and 2018 in rural and urban areas. Although absolute rates were lower in younger compared with older women in both rural and urban areas, all age groups experienced similar increases. The rate ratios of pre-pregnancy hypertension in rural compared with urban women ranged from 1.18 (95% CI: 1.04 to 1.35) for ages 15 to 19 years to 1.51 (95% CI: 1.39 to 1.64) for ages 40 to 44 years in 2018.
CONCLUSIONS: Maternal burden of pre-pregnancy hypertension has nearly doubled in the past decade and the rural-urban gap has persisted.
DESIGN: A collaboration of 12 prospective cohort studies from Europe and the United States (the HIV-CAUSAL Collaboration) that includes 62 760 HIV-infected, therapy-naive individuals followed for an average of 3.3 years. Inverse probability weighting of marginal structural models was used to adjust for measured confounding by indication.
RESULTS: Two thousand and thirty-nine individuals died during the follow-up. The mortality hazard ratio was 0.48 (95% confidence interval 0.41-0.57) for cART initiation versus no initiation. In analyses stratified by CD4 cell count at baseline, the corresponding hazard ratios were 0.29 (0.22-0.37) for less than 100 cells/microl, 0.33 (0.25-0.44) for 100 to less than 200 cells/microl, 0.38 (0.28-0.52) for 200 to less than 350 cells/microl, 0.55 (0.41-0.74) for 350 to less than 500 cells/microl, and 0.77 (0.58-1.01) for 500 cells/microl or more. The estimated hazard ratio varied with years since initiation of cART from 0.57 (0.49-0.67) for less than 1 year since initiation to 0.21 (0.14-0.31) for 5 years or more (P value for trend <0.001).
CONCLUSION: We estimated that cART halved the average mortality rate in HIV-infected individuals. The mortality reduction was greater in those with worse prognosis at the start of follow-up.
METHODS AND RESULTS: We compared 5697 chronic HF patients of Indian (26%), white (23%), Chinese (17%), Japanese/Koreans (12%), black (12%), and Malay (10%) ethnicities from the HF-ACTION and ASIAN-HF multinational studies using the Kansas City Cardiomyopathy Questionnaire (KCCQ; range 0-100; higher scores reflect better health status). KCCQ scores were lowest in Malay (58±22) and Chinese (60±23), intermediate in black (64±21) and Indian (65±23), and highest in white (67±20) and Japanese or Korean patients (67±22) after adjusting for age, sex, educational status, HF severity, and risk factors. Self-efficacy, which measures confidence in the ability to manage symptoms, was lower in all Asian ethnicities (especially Japanese/Koreans [60±26], Malay [66±23], and Chinese [64±28]) compared to black (80±21) and white (82±19) patients, even after multivariable adjustment (P
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: 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 AND FINDINGS: Our approach is based on a parsimonious mathematical model of disease transmission and only requires data collected through routine surveillance and standard case investigations. We apply it to assess the transmissibility of swine-origin influenza A H3N2v-M virus in the US, Nipah virus in Malaysia and Bangladesh, and also present a non-zoonotic example (cholera in the Dominican Republic). Estimation is based on two simple summary statistics, the proportion infected by the natural reservoir among detected cases (G) and among the subset of the first detected cases in each cluster (F). If detection of a case does not affect detection of other cases from the same cluster, we find that R can be estimated by 1-G; otherwise R can be estimated by 1-F when the case detection rate is low. In more general cases, bounds on R can still be derived.
CONCLUSIONS: We have developed a simple approach with limited data requirements that enables robust assessment of the risks posed by emerging zoonoses. We illustrate this by deriving transmissibility estimates for the H3N2v-M virus, an important step in evaluating the possible pandemic threat posed by this virus. Please see later in the article for the Editors' Summary.
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.