METHODS: Behavioural Risk Factors Surveillance System data were used to estimate the weight the US population needed to lose to achieve a BMI
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: 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.
METHODS: Data were obtained from large samples of students enrolled at universities in Malaysia and the US, including self-reported information on handedness, sexual orientation, and five somatic markers of prenatal androgen exposure (2D:4D, height, strength, muscularity, and athletic ability). Factor analysis of these somatic markers yielded two factors: a muscular coordination and a bone growth factor.
RESULTS: In women, but not in men, ambidextrousness was more prevalent among those with homosexual tendencies. Modest and often complex associations were found between the androgen factors and handedness. Clear links between the androgen factors and sexual orientation were found, especially for muscular coordination. For males and females, intermediate sex-typical androgen exposure was associated with heterosexual preferences.
CONCLUSIONS: Ambidextrousness appears to be somewhat more common among females with homosexual tendencies, but left-handedness is nearly as strongly associated with heterosexual preferences, particularly in males, as is right-handedness. Factors indicative of prenatal androgen exposure are associated with sexual orientation in theoretically predictable ways, especially for muscular coordination, but associations between prenatal androgens and handedness are complex.
OBJECTIVE: This study examined the COVID-19 pandemic-related topics online users discussed with a commercially available social chatbot and compared the sentiment expressed by users from 5 culturally different countries.
METHODS: We analyzed 19,782 conversation utterances related to COVID-19 covering 5 countries (the United States, the United Kingdom, Canada, Malaysia, and the Philippines) between 2020 and 2021, from SimSimi, one of the world's largest open-domain social chatbots. We identified chat topics using natural language processing methods and analyzed their emotional sentiments. Additionally, we compared the topic and sentiment variations in the COVID-19-related chats across countries.
RESULTS: Our analysis identified 18 emerging topics, which could be categorized into the following 5 overarching themes: "Questions on COVID-19 asked to the chatbot" (30.6%), "Preventive behaviors" (25.3%), "Outbreak of COVID-19" (16.4%), "Physical and psychological impact of COVID-19" (16.0%), and "People and life in the pandemic" (11.7%). Our data indicated that people considered chatbots as a source of information about the pandemic, for example, by asking health-related questions. Users turned to SimSimi for conversation and emotional messages when offline social interactions became limited during the lockdown period. Users were more likely to express negative sentiments when conversing about topics related to masks, lockdowns, case counts, and their worries about the pandemic. In contrast, small talk with the chatbot was largely accompanied by positive sentiment. We also found cultural differences, with negative words being used more often by users in the United States than by those in Asia when talking about COVID-19.
CONCLUSIONS: Based on the analysis of user-chatbot interactions on a live platform, this work provides insights into people's informational and emotional needs during a global health crisis. Users sought health-related information and shared emotional messages with the chatbot, indicating the potential use of chatbots to provide accurate health information and emotional support. Future research can look into different support strategies that align with the direction of public health policy.
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: Individual participant data meta-analysis included 362,114 participants (43% women), from seven prospective cohort studies, free from cancer at enrollment. The WCRF/AICR diet score was based on: (i) energy-dense foods and sugary drinks, (ii) plant foods, (iii) red and processed meat, and (iv) alcoholic drinks. Cox proportional hazards regression was used to examine the association between the diet score and cancer risks. Adjusted, cohort-specific HRs were pooled using random-effects meta-analysis. Risk advancement periods (RAP) were calculated to quantify the time period by which the risk of cancer was postponed among those adhering to the recommendations.
RESULTS: After a median follow-up of 11 to 15 years across cohorts, 70,877 cancer cases were identified. Each one-point increase in the WCRF/AICR diet score [range, 0 (no) to 4 (complete adherence)] was significantly associated with a lower risk of total cancer [HR, 0.94; 95% confidence interval (CI), 0.92-0.97], cancers of the colorectum (HR, 0.84; 95% CI, 0.80-0.89) and prostate (HR, 0.94; 95% CI, 0.92-0.97), but not breast or lung. Adherence to an additional component of the WCRF/AICR diet score significantly postponed the incidence of cancer at any site by 1.6 years (RAP, -1.6; 95% CI, -4.09 to -2.16).
CONCLUSIONS: Adherence to WCRF/AICR dietary recommendations is associated with lower risk of cancer among older adults.
IMPACT: Dietary recommendations for cancer prevention are applicable to the elderly. Cancer Epidemiol Biomarkers Prev; 26(1); 136-44. ©2016 AACR.
METHODS: We retrieved the records of 25,323 women diagnosed with primary stage IV breast cancer in the surveillance, epidemiology, and end results 18 registries database from 1990 to 2012. For each case, we extracted information on age at diagnosis, tumour size, nodal status, oestrogen receptor status, progesterone receptor status, ethnicity, cause of death and date of death. The Cox proportional hazards model was used to estimate the unadjusted and adjusted hazard ratio (HR) of death due to stage IV breast cancer, according to age group.
RESULTS: Among 25,323 women with stage IV breast cancer, 2542 (10.0 %) were diagnosed at age 40 or below, 5562 (22.0 %) were diagnosed between ages 41 and 50 and 17,219 (68.0 %) were diagnosed between ages 51 and 70. After a mean follow-up of 2.2 years, 16,387 (64.7 %) women died of breast cancer (median survival 2.3 years). The ten-year actuarial breast cancer-specific survival rate was 15.7 % for women ages 40 and below, 14.9 % for women ages 41-50 and 11.7 % for women ages 51 to 70 (p