6 research outputs found
Bushehr Elderly Health (BEH) Programme, phase I (cardiovascular system)
Purpose: The main objective of the Bushehr Elderly
Health Programme, in its first phase, is to investigate
the prevalence of cardiovascular risk factors and their
association with major adverse cardiovascular events.
Participants: Between March 2013 and October
2014, a total of 3000 men and women aged
≥60 years, residing in Bushehr, Iran, participated in
this prospective cohort study ( participation
rate=90.2%).
Findings to date: Baseline data on risk factors,
including demographic and socioeconomic status,
smoking and medical history, were collected through a
modified WHO MONICA questionnaire. Vital signs and
anthropometric measures, including systolic and
diastolic blood pressure, weight, height, and waist and
hip circumference, were also measured. 12-lead
electrocardiography and echocardiography were
conducted on all participants, and total of 10 cc
venous blood was taken, and sera was separated and
stored at –80°C for possible future use. Preliminary
data analyses showed a noticeably higher prevalence of
risk factors among older women compared to that in
men.
Future plans: Risk factor assessments will be
repeated every 5 years, and the participantswill be
followed during the study to measure the occurrence
of major adverse cardiac events. Moreover, the second
phase, which includes investigation of bone health and
cognition in the elderly, was started in September
2015. Data are available at the Persian Gulf Biomedical
Research Institute, Bushehr University of Medical
Sciences, Bushehr, Iran, for any collaboratio
Enhancing Clinical Translation of Cancer Using Nanoinformatics
Application of drugs in high doses has been required due to the limitations of no specificity, short circulation half-lives, as well as low bioavailability and solubility. Higher toxicity is the result of high dosage administration of drug molecules that increase the side effects of the drugs. Recently, nanomedicine, that is the utilization of nanotechnology in healthcare with clinical applications, has made many advancements in the areas of cancer diagnosis and therapy. To overcome the challenge of patient-specificity as well as time- and dose-dependency of drug administration, artificial intelligence (AI) can be significantly beneficial for optimization of nanomedicine and combinatorial nanotherapy. AI has become a tool for researchers to manage complicated and big data, ranging from achieving complementary results to routine statistical analyses. AI enhances the prediction precision of treatment impact in cancer patients and specify estimation outcomes. Application of AI in nanotechnology leads to a new field of study, i.e., nanoinformatics. Besides, AI can be coupled with nanorobots, as an emerging technology, to develop targeted drug delivery systems. Furthermore, by the advancements in the nanomedicine field, AI-based combination therapy can facilitate the understanding of diagnosis and therapy of the cancer patients. The main objectives of this review are to discuss the current developments, possibilities, and future visions in naoinformatics, for providing more effective treatment for cancer patients
Response-oriented measuring inequalities in Tehran: Second round of Urban health equity assessment and response tool (Urban HEART-2), concepts and framework
Background: Current evidence consistently confirm inequalities in health status among socioeconomic groups, gender, ethnicity, geographical area and other social determinants of health (SDH), which adversely influence health of the population. SDH refer to a wide range of factors not limited to social component, but also involve economic, cultural, educational, political or environmental problems. Measuring inequalities, improving daily living conditions, and tackling inequitable distribution of resources are highly recommended by international SDH commissioners in recent years to 'close the gaps within a generation'. To measure inequalities in socio-economic determinants and core health indicators in Tehran, the second round of Urban Health Equity Assessment and Response Tool (Urban HEART-2) was conducted in November 2011, within the main framework of WHO Centre for Health Development (Kobe Centre). Method: For 'assessment' part of the project, 65 indicators in six policy domains namely 'physical and infrastructure', 'human and social', 'economic', 'governance', 'health and nutrition', and also 'cultural' domain were targeted either through a population based survey or using routine system. Survey was conducted in a multistage random sampling, disaggregated to 22 districts and 368 neighborhoods of Tehran, where data of almost 35000 households (118000 individuals) were collected. For 'response' part of the project, widespread community based development (CBD) projects were organized in all 368 neighborhoods, which are being undertaken throughout 2013. Conclusion: Following the first round of Urban HEART project in 2008, the second round was conducted to track changes over time, to institutionalize inequality assessment within the local government, to build up community participation in 'assessment' and 'response' parts of the project, and to implement appropriate and evidence-based actions to reduce health inequalities within all neighborhoods of Tehran
Global Burden of Cardiovascular Diseases and Risks, 1990-2022
The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) is a multinational collaborative research study with >10,000 collaborators around the world. GBD generates a time series of summary measures of health, including prevalence, cause-specific mortality (CSMR), years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life years (DALYs) to provide a comprehensive view of health burden for a wide range of stakeholders including clinicians, public and private health systems, ministries of health, and other policymakers. These estimates are produced for 371 causes of death and 88 risk factors according to mutually exclusive, collectively exhaustive hierarchies of health conditions and risks. The study is led by a principal investigator and governed by a study protocol, with oversight from a Scientific Council, and an Independent Advisory Committee.1 GBD is performed in compliance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER).2 GBD uses de-identified data, and the waiver of informed consent was reviewed and approved by the University of Washington Institutional Review Board (study number 9060).
This almanac presents results for 18 cardiovascular diseases (CVD) and the CVD burden attributed to 15 risk factors (including an aggregate grouping of dietary risks) by GBD region. A summary of methods follows. Additional information can be found online at https://ghdx.healthdata.org/record/ihme-data/cvd-1990-2022, including:Funding was provided by the Bill and Melinda Gates Foundation, and the American College of Cardiology Foundation. The authors have reported that they have no relationships relevant to the contents of this paper to disclose. The contents and views expressed in this report are those of the authors and do not necessarily reflect the official views of the National Institutes of Health, the Department of Health and Human Services, the U.S. Government, or the affiliated institutions