The association of anthropometric indices and cardiac function in healthy adults

BACKGROUND: Obesity is a major risk factor for many diseases including cardiovascular diseases (CVDs). Recently, it has been shown that upper body obesity can predict CVDs per se. In this study, we aimed to determine the association between indicators of upper body obesity and echocardiographic indices. METHODS: In this cross-sectional study conducted in Hajar Hospital in Shahrekord, Iran, from March to August 2014, 80 healthy adults were included. Participants' neck circumference (NC), waist circumference (WC), body mass index (BMI), and blood pressure were measured. Echocardiography was performed for all participants, and echocardiographic indices such as early (E') and late (A') diastolic tissue velocity, early (E) and late (A) transmitral flow velocity, E/E' ratio, pulmonary arterial pressure (PAP), and left atrial volume (LAV) were recorded. The association between these indices were investigated using bivariate Pearson correlation coefficient. RESULTS: For men, NC had a significant correlation with LAV, systolic blood pressure (SBP), diastolic blood pressure (DBP), PAP, and A', and a negative correlation with E'. WC had a significant correlation with LAV, SBP, and PAP, and a negative correlation with E', while BMI had a significant correlation with LAV, PAP, SBP, A, and A'. For women, NC had a significant positive correlation with LAV, A, ejection fraction (EF), SBP, PAP, and A', and a negative correlation with E' and E/E'. WC had a significant positive correlation with LAV, DBP, PAP, A, A', and a negative correlation with E', while BMI had a significant correlation with LAV, EF, SBP, PAP, E', A, and A'. CONCLUSION: The positive correlation of NC with SBP, A, and A', as well as NC, WC, and BMI with LAV and PAP in both sexes, and the negative correlation of NC with E' show the importance of these measures in estimation of metabolic and cardiovascular risk factors. KEYWORDS: Cardiovascular Diseases; Obesity; Risk Factor

The association of anthropometric indices and cardiac function in healthy adults

BACKGROUND: Obesity is a major risk factor for many diseases including cardiovascular diseases (CVDs). Recently, it has been shown that upper body obesity can predict CVDs per se. In this study, we aimed to determine the association between indicators of upper body obesity and echocardiographic indices. METHODS: In this cross-sectional study conducted in Hajar Hospital in Shahrekord, Iran, from March to August 2014, 80 healthy adults were included. Participants' neck circumference (NC), waist circumference (WC), body mass index (BMI), and blood pressure were measured. Echocardiography was performed for all participants, and echocardiographic indices such as early (E') and late (A') diastolic tissue velocity, early (E) and late (A) transmitral flow velocity, E/E' ratio, pulmonary arterial pressure (PAP), and left atrial volume (LAV) were recorded. The association between these indices were investigated using bivariate Pearson correlation coefficient. RESULTS: For men, NC had a significant correlation with LAV, systolic blood pressure (SBP), diastolic blood pressure (DBP), PAP, and A', and a negative correlation with E'. WC had a significant correlation with LAV, SBP, and PAP, and a negative correlation with E', while BMI had a significant correlation with LAV, PAP, SBP, A, and A'. For women, NC had a significant positive correlation with LAV, A, ejection fraction (EF), SBP, PAP, and A', and a negative correlation with E' and E/E'. WC had a significant positive correlation with LAV, DBP, PAP, A, A', and a negative correlation with E', while BMI had a significant correlation with LAV, EF, SBP, PAP, E', A, and A'. CONCLUSION: The positive correlation of NC with SBP, A, and A', as well as NC, WC, and BMI with LAV and PAP in both sexes, and the negative correlation of NC with E' show the importance of these measures in estimation of metabolic and cardiovascular risk factors

Molecular Characterization of Antibiotic Resistance Genes in Staphylococcus Isolated from Cell Phone Users’ and Non- Users’ Ears

Introduction: Resistance to macrolide can be created by erm genes in Staphylococcus. The aim of the current study was to determine whether or not cell phone use can result in the antibiotic resistance of 16S rDNA, Coa, ermA, ermB and ermC genes in Staphylococci isolated from cell phone users’ and non- users’ ears. Methods: A total of 150 isolates of Staphylococci were tested by the disk diffusion method. The isolates were examined by PCR for 16S rDNA, Coa, ermA, ermB and ermC genes. Results: According to PCR results, in two statistical societies, 65.33% cell phone users with positive Coa had only one erm, 33.33% cell phone non-users with negative Coa had only one erm and %1.34 had genes, whereas 24% cell phone non-users with positive Coa had one erm, %44 cell phone non-users with negative Coa had one erm and 32% had a minority of genes. Results showed that 16S rDNA, Coa, ermA, ermB, and ermC genes in the cell phone users group were more prevalent than the other group in Staphylococci isolated from ears. Conclusion: It is revealed that the presence of 16S rDNA, Coa, and erms genes had a significant relation to erythromycin and methicillin. Detection of ermA, ermB and ermC plays crucial roles in the molecular mechanisms, epidemiology of the efflux pump and methylase erythromycin ribosome. Since antibiotic resistant Staphylococci isolates may mutate and prompt constitutive resistances it is suggested that inducible resistance test should be implemented on erythromycin resistant sensitive isolates to prevent treatment failures

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Evaluation of the effect of adherence to treatment regimen program on quality of life in atrial fibrillation patients hospitalized in Shahid Chamran Hospital in Isfahan in 2017

Background and objective: Atrial fibrillation is the mostcommon cardiac arrhythmia, which is associated with reducedquality of life due to prolonged treatment and itsrecurrence. One of the key goals in the care of patientswith atrial fibrillation is increasing adherence to treatmentregimen program and the recommendations providedby the treatment group. Thus, the present study was designedand carried out with the aim of determining theeffect of treatment regimen program on quality of life inatrial fibrillation patients hospitalized in Shahid ChamranHospital in Isfahan in 2017.Methodology: This clinical trial study was conducted onpatients with atrial fibrillation arrhythmia in the CardiacCare Unit (CCU) and Post CCU Unit and Internal HeartSurgery Unit of Shahid Chamran Hospital in Isfahan. Atotal of 50 people were randomly selected as sample ofstudy and assigned to two groups of test and control. Thetest group received two 45-minute sessions of adherenceand educational booklet and they were followed-up forone month through phone call. The control group also receivedone session of usual care training individually withregard to the illness. Demographic data and quality of lifedata were collected through Atrial Fibrillation Effects onQuality of Life (AFEQT) before intervention, and one andthree month after the intervention. Data were analyzed bydescriptive and inferential statistics.Results: There was no significant difference between twogroups in terms of quality of life and demographic informationbefore the intervention. However, significant differencewas seen between the two groups in terms of qualityof life one month and three months after the intervention.Conclusion: The results suggest the positive effects ofadherence to treatment regimen program and follow-upof the patients by experienced nurses on quality of life inthese patients one and three months after discharge

Evaluation of the effect of adherence to treatment regimen program on quality of life in atrial fibrillation patients hospitalized in Shahid Chamran Hospital in Isfahan in 2017

Background and objective: Atrial fibrillation is the mostcommon cardiac arrhythmia, which is associated with reducedquality of life due to prolonged treatment and itsrecurrence. One of the key goals in the care of patientswith atrial fibrillation is increasing adherence to treatmentregimen program and the recommendations providedby the treatment group. Thus, the present study was designedand carried out with the aim of determining theeffect of treatment regimen program on quality of life inatrial fibrillation patients hospitalized in Shahid ChamranHospital in Isfahan in 2017.Methodology: This clinical trial study was conducted onpatients with atrial fibrillation arrhythmia in the CardiacCare Unit (CCU) and Post CCU Unit and Internal HeartSurgery Unit of Shahid Chamran Hospital in Isfahan. Atotal of 50 people were randomly selected as sample ofstudy and assigned to two groups of test and control. Thetest group received two 45-minute sessions of adherenceand educational booklet and they were followed-up forone month through phone call. The control group also receivedone session of usual care training individually withregard to the illness. Demographic data and quality of lifedata were collected through Atrial Fibrillation Effects onQuality of Life (AFEQT) before intervention, and one andthree month after the intervention. Data were analyzed bydescriptive and inferential statistics.Results: There was no significant difference between twogroups in terms of quality of life and demographic informationbefore the intervention. However, significant differencewas seen between the two groups in terms of qualityof life one month and three months after the intervention.Conclusion: The results suggest the positive effects ofadherence to treatment regimen program and follow-upof the patients by experienced nurses on quality of life inthese patients one and three months after discharge

Pulmonary vascular capacitance as a predictor of vasoreactivity in idiopathic pulmonary arterial hypertension tested by adenosine

Background: Acute pulmonary vasoreactivity testing has been recommended in the diagnostic work-up of patients with idiopathic pulmonary arterial hypertension (IPAH). Pulmonary arteriolar capacitance (Cp) approximated by stroke volume divided by pulmonary pulse pressure (SV/PP) is considered as an independent predictor of mortality in patients with IPAH. Objectives: We sought to evaluate any differences in baseline and adenosine Cp between vasoreactive and non-vasoreactive IPAH patients tested with adenosine. Patients and Methods: Fourteen patients with IPAH and a vasoreactive adenosine vasoreactivity testing according to the ESC guidelines were compared with 24 IPAH patients with nonreactive adenosine test results. Results: There were no statistical significant differences between the two groups regarding NYHA class, body surface area, heart rate, and systemic blood pressure during right heart catheterization. Hemodynamic study showed no statistical significant differences in cardiac output/Index, mean pulmonary artery pressure, pulmonary vascular resistance, and baseline Cp between the two groups. There was a statistical significant but weak increase in adenosine Cp in vasoreactive group compared to non-reactive group (P = 0.04). Multivariable analysis showed an association between Cp and vasoreactivity (Beta = 2, P = 0.04, OR = 0.05 (95%CI = 0.003 - 0.9). Conclusions: Cp could be considered as an index for the prediction of vasoreactivity in patients with IPAH. Prediction of long-term response to calcium channel blockers in patients with IPAH and a positive vasoreactive test by this index should be addressed in further studies

Assessing Metabolic Syndrome Through Increased Heart Rate During Exercise

The present study aimed to assess changes in resting and maximum heart rates as primary indicators of cardiac autonomic function in metabolic syndrome (MetS) patients and to determine their value for discriminating MetS from non-MetS. 468 participants were enrolled in this cross-sectional study and assessed according to the updated adult treatment panel III (ATP-III) definition of MetS. Resting and maximum heart rates were recorded following the Bruce protocol during an exercise. A receiver operating characteristic (ROC) curve was used to identify the best cutoff point for discriminating MetS from the non-MetS state. 194 participants (41.5%) were diagnosed as MetS. The mean resting heart rate (RHR) was not statistically different between the two groups (P=0.078). However, the mean maximum heart (MHR) rate was considerably higher in participants with MetS (142.37±14.84 beats per min) compared to the non-MetS group (134.62±21.63 beats per min) (P<0.001). In the MetS group, the MHR was positively correlated with the serum triglyceride level (β=0.185, P=0.033) and was inversely associated with age (β=-0.469, P<0.001). The MHR had a moderate value for discriminating MetS from the non-MetS state (c=0.580, P=0.004) with the optimal cutoff point of 140 beats per min. In MetS patients, the MHR was significantly greater compared to non-MetS subjects and was directly correlated with serum triglyceride levels and inversely with advanced age. Moreover, MHR can be used as a suspicious indicator for identifying MetS