Smoke-Free Policy in Vermont Public Housing Authorities

Introduction. Millions of adults and children living in public housing face exposure to second hand smoke from adjacent apartments. These tenants are less able to escape smoke exposure by moving, and Housing Authorities are beginning to implement smoke-free policies. We assessed the status of smoke-free policy in Vermont public housing, and explored the experience of tenants and managers in Burlington who recently implemented such a policy.https://scholarworks.uvm.edu/comphp_gallery/1080/thumbnail.jp

Analysis of drug resistance among difficult-to-treat tuberculosis patients in Ghana identifies several pre-XDR TB cases

BACKGROUND: Resistance to tuberculosis (TB) drugs has become a major threat to global control efforts. Early case detection and drug susceptibility profiling of the infecting bacteria are essential for appropriate case management. The objective of this study was to determine the drug susceptibility profiles of difficult-to-treat (DTT) TB patients in Ghana. METHODS: Sputum samples obtained from DTT-TB cases from health facilities across Ghana were processed for rapid diagnosis and detection of drug resistance using the Genotype MTBDRplus and Genotype MTBDRsl.v2 from Hain Life science. RESULTS: A total of 298 (90%) out of 331 sputum samples processed gave interpretable bands out of which 175 (58.7%) were resistant to at least one drug (ANY(r)); 16.8% (50/298) were isoniazid-mono-resistant (INH(r)), 16.8% (50/298) were rifampicin-mono-resistant (RIF(r)), and 25.2% (75/298) were MDR. 24 (13.7%) of the ANY(r) were additionally resistant to at least one second line drug: 7.4% (2 RIF(r), 1 INH(r), and 10 MDR samples) resistant to only FQs and 2.3% (2 RIF(r), 1 INH(r), and 1 MDR samples) resistant to AMG drugs kanamycin (KAN), amikacin (AMK), capreomycin (CAP), and viomycin (VIO). Additionally, there were 4.0% (5 RIF(r) and 2 MDR samples) resistant to both FQs and AMGs. 81 (65.6%) out of 125 INH-resistant samples including INH(r) and MDR had katG-mutations (MT) whereas 15 (12%) had inhApro-MT. The remaining 28 (22.4%) had both katG and inhA MT. All the 19 FQ-resistant samples were gyrA mutants whereas the 10 AMGs were rrs (3), eis (3) as well as rrs, and eis co-mutants (4). Except for the seven pre-XDR samples, no sample had eis MT. CONCLUSION: The detection of several pre-XDR TB cases in Ghana calls for intensified drug resistance surveillance and monitoring of TB patients to, respectively, ensure early diagnosis and treatment compliance

The health-related quality of life in a Swedish sample of HIV-infected persons

The purposes of the present study are (1) to assess the health-related quality of life (HRQOL) and the subjective health status in a sample of human immunodeficiency virus (HIV)-infected persons (2) to relate the results to different population groups and (3) to investigate the relationship of medical and demographic variables with HRQOL. A total of 72 HIV-infected men were included. They answered the Swedish health-related quality of life questionnaire and the health index. Demographic and medical data were obtained from the medical records. The data collection took place before entering a therapeutic HIV vaccine trial. The results showed a more negative impact on the HRQOL and subjective health status in the HIV-positive subjects, compared with male population groups. The dimensions of emotional well-being were most affected. When comparisons were made according to the medical and demographic variables for different subgroups within the HIV sample, differences in the physical-dimension scales were most prominent. Symptomatic HIV infection or acquired immunodeficiency syndrome (AIDS), anti-retroviral treatment, sick leave or disability pension, low income and basic education were associated with worse HRQOL and health status. In conclusion, it is of utmost importance to take into account, aspects of the patients' emotional well-being in nursing, as well as in medical care and interventions. Moreover, individualized caring programs are needed because the disruptions in HRQOL fluctuated within the HIV sample

Reference values of whole-blood fatty acids by age and sex from European children aged 3-8 years

OBJECTIVES: To establish reference values for fatty acids (FA) especially for n-3 and n-6 long-chain polyunsaturated FAs (LC PUFA) in whole-blood samples from apparently healthy 3-8-year-old European children. The whole-blood FA composition was analysed and the age-and sex-specific distribution of FA was determined. DESIGN AND SUBJECTS: Blood samples for FA analysis were taken from 2661 children of the IDEFICS (identification and prevention of dietary-and lifestyle-induced health effects in children and infants) study cohort. Children with obesity (n = 454) and other diseases that are known to alter the FA composition (n = 450) were excluded leaving 1653 participants in the reference population. MEASUREMENTS: The FA composition of whole blood was analysed from blood drops by a rapid, validated gas chromatographic method. RESULTS: Pearson correlation coefficients showed an age-dependent increase of C18:2n-6 and a decrease of C18:1n-9 in a subsample of normal weight boys and girls. Other significant correlations with age were weak and only seen either in boys or in girls, whereas most of the FA did not show any age dependence. For age-dependent n-3 and n-6 PUFA as well as for other FA that are correlated with age (16:0, C18:0 and C18:1n-9) percentiles analysed with the general additive model for location scale and shape are presented. A higher median in boys than in girls was observed for C20:3n-6, C20:4n-6 and C22:4n-6. CONCLUSIONS: Given the reported associations between FA status and health-related outcome, the provision of FA reference ranges may be useful for the interpretation of the FA status of children in epidemiological and clinical studies

The role of lifestyle changes in the management of chronic liver disease

The prevalence of obesity worldwide has dramatically increased during the last three decades. With obesity comes a variety of adverse health outcomes which are grouped under the umbrella of metabolic syndrome. The liver in particular seems to be significantly impacted by fat deposition in the presence of obesity. In this article we discuss several liver conditions which are directly affected by overweight and obese status, including non-alcoholic fatty liver disease, chronic infection with hepatitis C virus and post-liver transplant status. The deleterious effects of obesity on liver disease and overall health can be significantly impacted by a culture that fosters sustained nutritional improvement and regular physical activity. Here we summarize the current evidence supporting non-pharmacological, lifestyle interventions that lead to weight reduction, improved physical activity and better nutrition as part of the management and treatment of these liver conditions

Novel functional insights into ischemic stroke biology provided by the first genome-wide association study of stroke in indigenous Africans

\ua9 The Author(s) 2024. Background: African ancestry populations have the highest burden of stroke worldwide, yet the genetic basis of stroke in these populations is obscure. The Stroke Investigative Research and Educational Network (SIREN) is a multicenter study involving 16 sites in West Africa. We conducted the first-ever genome-wide association study (GWAS) of stroke in indigenous Africans. Methods: Cases were consecutively recruited consenting adults (aged > 18 years) with neuroimaging-confirmed ischemic stroke. Stroke-free controls were ascertained using a locally validated Questionnaire for Verifying Stroke-Free Status. DNA genotyping with the H3Africa array was performed, and following initial quality control, GWAS datasets were imputed into the NIH Trans-Omics for Precision Medicine (TOPMed) release2 from BioData Catalyst. Furthermore, we performed fine-mapping, trans-ethnic meta-analysis, and in silico functional characterization to identify likely causal variants with a functional interpretation. Results: We observed genome-wide significant (P-value < 5.0E−8) SNPs associations near AADACL2 and miRNA (MIR5186) genes in chromosome 3 after adjusting for hypertension, diabetes, dyslipidemia, and cardiac status in the base model as covariates. SNPs near the miRNA (MIR4458) gene in chromosome 5 were also associated with stroke (P-value < 1.0E−6). The putative genes near AADACL2, MIR5186, and MIR4458 genes were protective and novel. SNPs associations with stroke in chromosome 2 were more than 77 kb from the closest gene LINC01854 and SNPs in chromosome 7 were more than 116 kb to the closest gene LINC01446 (P-value < 1.0E−6). In addition, we observed SNPs in genes STXBP5-AS1 (chromosome 6), GALTN9 (chromosome 12), FANCA (chromosome 16), and DLGAP1 (chromosome 18) (P-value < 1.0E−6). Both genomic regions near genes AADACL2 and MIR4458 remained significant following fine mapping. Conclusions: Our findings identify potential roles of regulatory miRNA, intergenic non-coding DNA, and intronic non-coding RNA in the biology of ischemic stroke. These findings reveal new molecular targets that promise to help close the current gaps in accurate African ancestry-based genetic stroke’s risk prediction and development of new targeted interventions to prevent or treat stroke

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990-2013: A systematic analysis for the Global Burden of Disease Study 2013

Background: The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the first of a series of annual updates of the GBD. Risk factor quantification, particularly of modifiable risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution. Methods: Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk-outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990-2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the first level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular filtration rate. For most risks, data for exposure were synthesised with a Bayesian metaregression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol. Findings: All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8-58·5) of deaths and 41·6% (40·1-43·0) of DALYs. Risks quantified account for 87·9% (86·5-89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa. Interpretation: Behavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks

Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015

Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography–year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61·7 years (95% uncertainty interval 61·4–61·9) in 1980 to 71·8 years (71·5–72·2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11·3 years (3·7–17·4), to 62·6 years (56·5–70·2). Total deaths increased by 4·1% (2·6–5·6) from 2005 to 2015, rising to 55·8 million (54·9 million to 56·6 million) in 2015, but age-standardised death rates fell by 17·0% (15·8–18·1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14·1% (12·6–16·0) to 39·8 million (39·2 million to 40·5 million) in 2015, whereas age-standardised rates decreased by 13·1% (11·9–14·3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42·1%, 39·1–44·6), malaria (43·1%, 34·7–51·8), neonatal preterm birth complications (29·8%, 24·8–34·9), and maternal disorders (29·1%, 19·3–37·1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000–183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000–532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Funding Bill & Melinda Gates Foundation