Purpose: We examined the relationship between family factors and HIV-related sexual risk behaviors among adolescent sexual minority males (ASMM) who are affected disproportionately by HIV. Methods: We analyzed results from the National HIV Behavioral Surveillance among Young Men Who Have Sex with Men. Adolescent males ages 13–18 who identified as gay or bisexual, or who reported attraction to or sex with males were interviewed in 2015 in Chicago, New York City, and Philadelphia. Separate log-linked Poisson regression models were used to estimate associations between family factors and sexual risk behaviors. Results: Of the 569 ASMM, 41% had condomless anal intercourse in the past 12 months, 38% had ≥4 male sex partners in the past 12 months, and 23% had vaginal or anal sex before age 13. ASMM who had ever been kicked out of their house or run away, those who were out to their mother, and those who were out to their father, were more likely to engage in sexual risk behaviors. ASMM who were currently living with parents or guardians and those who received a positive reaction to their outness by their mother were less likely to engage in sexual risk behaviors. Conclusion: Our findings highlight the important role of family factors in HIV risk reduction among ASMM. A better understanding of the complex dynamics of these families will help in developing family-based interventions.
INTRODUCTION:
Diabetes is rapidly emerging as a major public health problem in India, especially in
Urban areas. The prevalence of type 2 diabetes has been steadily increasing in urban areas from
A low of 2.1% reported in early 19701 to a whopping 11.6%2 in 1996, in the adult population.
Moreover, there is an equally large pool of persons with IGT (impaired glucose tolerance),
Many of whom will go on to develop type 2 diabetes in the future. There is evidence to suggest
That prevalence of type 2 diabetes is increasing even in rural areas3. The national data on
Prevalence of diabetes in urban area was 6.7%and 3.1% in rural area as per 2003-04 data.
The prevailing poverty, ignorance, illiteracy and poor health consciousness further adds to the
Problem. Patients can access any level of care (primary, secondary or tertiary) based on close location,
Knowledge of its existence and resources. Thus many sociological factors determine long-term outcome
of illness. A study of these factors and their influence on the prognosis and outcome are necessary to
Tackle diabetes in the community. Previous studies by Kapur A et al6,7 have looked at perceptions and
Attitudes of persons with diabetes and of the diabetes care providers and their significance to proper
Diabetes care delivery. Diabetes education and awareness programmes are an integral and essential part of diabetes care.
There is now irrefutable evidence that diabetes education, awareness and improving motivation for self
Care, improves care, reduce complications and thus overall reduces economic costs of diabetes .
Despite the high prevalence, serious long term complications, and established evidence based
Guidelines for management, translation of practice recommendations to care is still deficient in
Developed and developing countries.
OBJECTIVES :
1. To assess the quality of care in type 2 diabetic patients of age 35 years and above in an
Urban slum of North Chennai.
2. To identify the possible factors associated with quality of care in the above said age group.
3. JUSTIFICATION
It is projected that more than half of the Indian population will live in urban areas by
2020 and nearly one third of this urban population will be of urban slum dwellers. With the rise
in the urban/rural population ratio in all regions, and growing prevalence of obesity among
urban dwellers, diabetes will increasingly concentrate in urban areas. It is also known that the
prevalence of diabetes is high among urban slum dwellers than rural community. Previously a
disease of the middle aged and elderly, type 2 diabetes has recently escalated in all age groups
and is now being seen in younger age groups10.. This will have major implications with respect
to health care needs and costs. It is also evident that annual economic burden of diabetes at
individual, family and societal level is huge11.
Addressing health problems of urban poor is must for overall development of the
country. Since they are underserved and unreached by the health personnel, vulnerability for
worsening of Diabetes and its complications cannot be overlooked. It is also evident from some
prospective studies that good glycemic control, lipid control, blood pressure control by
providing good quality of care, protects against complications of type 2 diabetes12. Age limit
was chosen at 35 years as lower limit because type 1 diabetes was sometimes difficult to
differentiate from type 2 diabetes in 20 to 35 years age group in this population (poor
educational background and lack of medical records).
Even though there are many studies done on quality of care in developed countries,
few studies exist in our country. The factors associated with quality of care like race,
socioeconomic status, ethnicity differs between areas and people13. Assessment of quality of care in the community can help draw attention to the need for improving diabetes management
and provide a benchmark for monitoring changes over time.
In view of above reasons, this study on quality of care was conducted in 35 years
and above age group in Bakthavatchalam Colony in division 36, under zone III of Chennai
Corporation.
HIV infection is monitored through the National HIV Surveillance System (NHSS) to help improve the health of people with HIV and reduce transmission. NHSS data are routinely used at federal, state, and local levels to monitor the distribution and transmission of HIV, plan and evaluate prevention and care programs, allocate resources, inform policy development, and identify and respond to rapid transmission in the United States. We describe the expanded use of HIV surveillance data since the 2013 NHSS status update, during which time the Centers for Disease Control and Prevention (CDC) coordinated to revise the HIV surveillance case definition to support the detection of early infection and reporting of laboratory data, expanded data collection to include information on sexual orientation and gender identity, enhanced data deduplication processes to improve quality, and expanded reporting to include social determinants of health and health equity measures. CDC maximized the effects of federal funding by integrating funding for HIV prevention and surveillance into a single program; the integration of program funding has expanded the use of HIV surveillance data and strengthened surveillance, resulting in enhanced cluster response capacity and intensified data-to-care activities to ensure sustained viral suppression. NHSS data serve as the primary source for monitoring HIV trends and progress toward achieving national initiatives, including the US Department of Health and Human Services' Ending the HIV Epidemic in the United States initiative, the White House's National HIV/AIDS Strategy (2022-2025), and Healthy People 2030. The NHSS will continue to modernize, adapt, and broaden its scope as the need for high-quality HIV surveillance data remains.
To identify whether school health policies and programs vary by demographic characteristics of schools, using data from the School Health Policies and Programs Study (SHPPS) 2006. This study updates a similar study conducted with SHPPS 2000 data and assesses several additional policies and programs measured for the first time in SHPPS 2006.SHPPS 2006 assessed the status of 8 components of the coordinated school health model using a nationally representative sample of public, Catholic, and private schools at the elementary, middle, and high school levels. Data were collected from school faculty and staff using computer-assisted personal interviews and then linked with extant data on school characteristics.Results from a series of regression analyses indicated that a number of school policies and programs varied by school type (public, Catholic, or private), urbanicity, school size, discretionary dollars per pupil, percentage of white students, percentage of students qualifying for free lunch funds, and, among high schools, percentage of college-bound students. Catholic and private schools, smaller schools, and those with low discretionary dollars per pupil did not have as many key school health policies and programs as did schools that were public, larger, and had higher discretionary dollars per pupil. However, no single type of school had all key components of a coordinated school health program in place.Although some categories of schools had fewer policies and programs in place, all had both strengths and weaknesses. Regardless of school characteristics, all schools have the potential to implement a quality school health program.
To monitor priority health risk behaviors and school health policies and practices, respectively, the Centers for Disease Control and Prevention (CDC) developed the Youth Risk Behavior Surveillance System (YRBSS) and the School Health Profiles (Profiles). CDC is often asked about the use and application of these survey data to improve adolescent and school health. The purpose of this article is to describe the importance and potential impact of Youth Risk Behavior Survey (YRBS) and Profiles data based on examples from participating sites.The authors spoke with representatives from 25 state and 8 local agencies funded by CDC to learn how data from the YRBS, Profiles, and other data sources are used. The authors identified common themes in the responses and categorized the responses accordingly.Representatives indicated survey data are used to describe risk behaviors and school health policies and practices, inform professional development, plan and monitor programs, support health-related policies and legislation, seek funding, and garner support for future surveys. Examples presented highlight the range of possible uses of survey data.State and local agencies use YRBS and Profiles data in many ways to monitor and address issues related to adolescent and school health. Innovative uses of survey data are encouraged, although it is also crucial to continue the more fundamental uses of survey data. If the data are not disseminated, the current health needs of students may not be adequately addressed.
ABSTRACT: Sexual violence continues to be a major public health problem affecting millions of adults and children in the United States. Medical consequences of sexual assault include sexually transmitted infections; mental health conditions, including posttraumatic stress disorder; and risk of unintended pregnancy in reproductive-aged survivors of sexual assault. Obstetrician–gynecologists and other women’s health care providers play a key role in the evaluation and management of sexual assault survivors and should screen routinely for a history of sexual assault. When sexual violence is identified, individuals should receive appropriate and timely care. A clinician who examines sexual assault survivors in the acute-care setting has a responsibility to comply with state and local statutory or policy requirements for the use of evidence-gathering kits. This document has been updated to include model screening protocols and questions, relevant guidelines from other medical associations, trauma-informed care, and additional guidance regarding acute evaluation of survivors and evidence-gathering kits.
Abstract Background On average, persons with diagnosed HIV (PWH) are living longer, and PWH who are engaged in effective care can expect lifespans comparable to persons without HIV. Understanding changes in the age structure of PWH can help plan where to direct healthcare resources to match need, especially medical needs related to aging and to preventive care for AIDS- and non-AIDS-related comorbidities. Methods Using data from CDC’s National HIV Surveillance System (NHSS) for PWH aged ≥ 13 years in the United States, we compared changes in the number of PWH alive at each year-end over the period 2010-2021, examined changes in their age structure, and for 2021 calculated duration of HIV infection since diagnosis for all PWH aged ≥ 18 years. Results During 2010-2021, the overall number of PWH increased 29.9%, from 835,004 in 2010 to 1,084,351 in 2021 (Fig 1). The number of PWH aged ≥ 50 years increased 96.3%, from 295,464 to 580,011, and the number aged ≥ 65 years increased 335%, from 33,646 to 146,485 (Fig 2). At year-end 2021, overall median age was 51 years, 53.5% of all PWH were aged ≥ 50 years, and 13.5% were aged ≥ 65 years. Of all adult PWH, 45.8% (497,005) had lived with HIV over 15 years since diagnosis. Among the subset of 12,563 PWH living with perinatally acquired HIV, the median age at year-end 2021 was 26 years; 31.4% were infected at least 30 years, and 76.6% at least 20 years. Conclusion From 2010-2021, the number of PWH aged ≥ 50 years increased markedly and overall median age of PWH aged ≥ 13 years increased to exceed 50 years; 1 in 7 were aged ≥ 65 years. By year-end 2021, PWH aged ≥ 50 years totaled over one half million, among whom 1 in 4 was aged ≥ 65 years. Almost half of adult PWH had lived with diagnosed HIV for at least 15 years and three-quarters of young adults with perinatally acquired HIV had lived with HIV for 20 years or more. Our findings highlight the large and rapidly growing need not only for expertise treating older PWH but also integration of prevention strategies to minimize the impact of AIDS- and non-AIDS-related comorbidities of aging in PWH with long-standing HIV. Disclosures All Authors: No reported disclosures
Abstract Background and aims Maintenance of abstinence in alcohol-related liver disease (ARLD) is a major unmet therapeutic need. Digital therapeutics can deliver ongoing behavioural therapy, in real-time, for chronic conditions. The aim of this project was to develop and clinically test AlcoChange, a novel digital therapeutic for ARLD. Methods AlcoChange was developed using validated behaviour change techniques (BCTs) and a digital alcohol breathalyser. This was an open-label, single-centre study. Patients with ARLD, ongoing alcohol use (within 1 month) and possession of a suitable smartphone were eligible. Patients were recruited from inpatient and outpatient settings, and received AlcoChange therapy for 3-months. The primary outcome was reduction in alcohol use from baseline to 3-months, measured by timeline follow-back (TLFB). Secondary outcomes included: (i) compliance with the AlcoChange app, (ii) alcohol-related and all-cause hospital re-admissions up to 1-year, (iii) qualitative analysis to determine factors associated with compliance. Results Sixty-five patients were recruited, of whom forty-one completed the study per-protocol. Patients compliant with the intervention (>60 logins over 3-months) had a significant reduction in alcohol use from baseline compared to non-compliant patients [median (IQR): −100% (100% to −55.1%) vs −57.1% (−95.3% to +32.13%), p=0.029]. The proportion attaining abstinence at 3-months was higher in the compliant group (57.1% vs 22.2%, p=0.025). The compliant group had a significantly decreased risk of subsequent alcohol-related re-admission up to 12-months (p=0.008). Qualitative analysis demonstrated receiving in-app feedback and presence of health-related ‘sentinel event’ were predictors of compliance with the intervention. Conclusions Use of the novel digital therapeutic, AlcoChange, was associated with a significant reduction in alcohol use and increase in proportion attaining abstinence in ARLD patients. Definitive, randomized trials are warranted for this intervention.
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