Effectiveness of Acupressure on Reducing Blood Sugar and Glycosylated Hemoglobin Levels in Patients with Type 2 Diabetes: A Rapid Systematic Review and Meta-analysis

Background: Acupressure as one of the complementary and alternative medicine (CAM) has become very popular in the management of various diseases such as diabetes. Although the increasing use of acupuncture, there are limited systematic reviews and meta-analyses in this field.Aim: The present study was performed with aim to investigate the effectiveness of acupressure on the blood sugar parameters of patients with type 2 diabetes.Method: In this rapid systematic review and meta-analysis, the studies published globally between 2010 and 2022 were searched in the PubMed, Google Scholar, and Science Direct databases with the keywords of acupressure, diabetes, complementary medicine, blood sugar and glycosylated hemoglobin as separately and in combination. To analyze data, STATA software version 11 was used to analyze data, and the random effect model method was applied for meta-analysis of the studies.Results: Among the 411 articles found in the initial search, finally 8 articles were selected for this study. The results of the meta-analysis of studies showed that acupressure had a positive effect on blood sugar (95% CI = 0.816-1.553, P < 0.001, OR = 1.18) and fasting blood sugar (95% CI = 0.260 - 0.857, P˂0.001, OR = 0.559) in diabetic patients, while it had no effect on the level of glycosylated hemoglobin (95% CI = -0.139 - 0.389, P = 0.355, OR = 0.559).Implications for Practice: This study showed the positive effect of acupressure in reducing blood sugar and fasting blood sugar in patients with diabetes, however more studies are required to confirm the effect of acupressure on glycosylated hemoglobin

Risk factors related to COVID-19 survival and mortality: a cross-sectional-descriptive study in regional COVID-19 registry in Fasa, Iran

INTRODUCTION: The COVID-19 pandemic, as the most important health challenge in the world today, has made numerous irretrievable damages to the social, economic, and health dimensions of societies, especially in developing countries. An essential measure that can be taken to prevent and control the disease is to identify risk factors related to its prognosis and mortality rate. Therefore, this study aimed at investigating COVID-19 survival and mortality risk factors and their relationship with the demographic characteristics of the subjects diagnosed with the disease. MATERIAL AND METHODS: The present study is cross-sectional and descriptive. The samples consist of 1395 patients diagnosed with COVID-19 admitted to medical centers affiliated with Fasa University of Medical Sciences. The subjects were selected by census sampling. Data were collected using demographic information forms, paraclinical and radiological tests, and clinical examinations. Data were analyzed using SPSS version 18 via descriptive tests, paired t-tests, one-way ANOVA, and post hoc tests. RESULTS: According to the data, the participants’ average age was 57.72 ± 4.63 years, and most of them (56.41%) were male. The mortality rate among the participants was estimated to be 13.19%. The results of the study showed a significant relationship between the survival status of patients with COVID-19 and underlying chronic diseases such as diabetes and cardiovascular and renal diseases (p &lt; 0.05). CONCLUSIONS: Identifying high-risk groups is an important measure that health professionals should consider in controlling epidemics. The findings of this study showed that the presence of underlying chronic diseases such as diabetes and cardiac and renal conditions, which are associated with immune system defects, are among the most important factors related to the COVID-19 mortality

Investigating Glenohumeral Joint Contact Forces and Kinematics in Different Keyboard and Monitor Setups using Opensim

Background: The musculoskeletal complaints of the shoulder are prevalent in people who work with computers for a long time. Objective: This study aimed to investigate the glenohumeral joint contact forces and kinematics in different keyboards and monitor setups using OpenSim. Material and Methods: Twelve randomly selected healthy males participated in an experimental study. A 3×3 factorial design was used in which three angles were considered for the monitor and three horizontal distances for the keyboard while performing standard tasks. The workstation was adjusted based on ANSI/HFES-100-2007 standard to maintain a comfortable ergonomic posture for controlling confounding variables. Qualisys motion capture system and OpenSim were used. Results: The maximum mean range of motion (ROM) of both shoulders’ flexion and adduction was observed when the keyboard was 15 cm from the edge of the desk, and the monitor angle was 30°. The maximum mean ROM of both shoulders’ internal rotation was recorded for the keyboard at the edge of the desk. Peak forces for most right shoulder complex muscles were obtained in two setups. 3D shoulder joint moments were significantly different among nine setups (P-value<0.05). The peak anteroposterior and mediolateral joint contact forces were recorded for the keyboard at 15 cm and the monitor at zero angles (0.751 and 0.780 N/BW, respectively). The peak vertical joint contact force was observed for the keyboard at 15 cm and the monitor at 15° (0.310 N/BW).  Conclusion: The glenohumeral joint contact forces are minimum for the keyboard at 8 cm and the monitor at zero angles

A Complementary Therapy with Whey Protein in Diabetes: A Double-Blind Randomized Controlled Clinical Trial

Type 2 diabetes (T2DM) and its complications can cause severe morbidity and mortality. The researchers and clinicians’ attention has been toward finding the efficient treatment for T2DM to decrease its heavy burden on the people and countries. Whey protein (WP) is a known glucose-lowering treatment of traditional Persian medicine. This randomized controlled clinical trial aimed to evaluate the efficacy of the WP on the improvement of the glycemic index of the patients with T2DM in Fars, Fasa, Iran. A total of 58 people with T2DM met the inclusion criteria and were randomly assigned to one of two groups: intervention or placebo. For 12 weeks, they were given 1 sachet of WP or 1 sachet of placebo. Before and after the trial, fasting blood sugar, lipid profile, and liver enzymes were tested. Finally, 35 patients completed the study (18 in the whey group and 17 in the placebo group). The mean ± standard deviation of age, BMI, and the disease duration in placebo group were: 52.1±9.2 years, 26.8±3.9 kg/m2 and 102.9±67.7 months and in WP group were 51.2±8.2 years, 25.7±3.7 kg/m2 and 74.2±51.1 months. There were no significant differences among the study groups at the beginning (P>0.05). Meanwhile, the WP and placebo groups were the same by means of the amount of anti-diabetic drugs that participants consumed (P=0.242). After 12 weeks: the fasting blood sugar (FBS) and hemoglobin A1C amounts showed important decreases in the WP group compared to its starting point (P=0.011 and P=0.001 respectively), while in the placebo group, there was no significant difference in this matter (P>0.05).  No severe complications were reported in both groups. In conclusion, we found that whey protein would be a promising complementary therapy to control hyperglycemia in the patients with T2DM

Correlation of resting heart rate with anthropometric factors and serum biomarkers in a population-based study: Fasa PERSIAN cohort study

BACKGROUND: There is a positive association between raised resting heart rate (RHR), and all causes of mortality and shorter life expectancy. Several serum biomarkers and some anthropometric factors can affect the resting heart rate. This study aimed to investigate the determinants of resting heart rate in a large random sample of the Iranian population. MATERIAL AND METHODS: It is a standardized, retrospective study and the subjects were chosen from the baseline survey of the Prospective Epidemiological Research Study in IrAN (PERSIAN) Fasa non-communicable disease cohort study. It was conducted from winter 2014 to summer 2019 and after obtaining informed consent from a random sample, all the eligible subjects were enrolled. All anthropometric factors and biologic laboratory factors were collected and analyzed by implement smoothly clipped absolute deviation (SCAD) linear regression and SCAD quantile regression. The comparisons between males and females were done via independent T-test. RESULTS & CONCLUSION: A total number of 9975 persons from 35 to 90 years old were included. The overall median resting heart rate was 74 (interquartile range:66-80). Mean age has no important difference between males and females (P = 0.79) but, resting heart rate was significantly higher in females (76.6 versus 71.4, P < 0.001). All anthropometric factors except wrist circumference were higher in females (P < 0.05). Age has an adverse effect on resting heart rate and also, there was a direct association between resting heart rate and systolic blood pressure and blood glucose. Alpha-blockers (coefficient = 5.2) and Beta1-blockers (coefficient = - 2.2) were the most effective drugs with positive and negative effects on resting heart rate respectively. Lower hemoglobin, obesity, and more body mass index, and more low-density lipoprotein were associated with more resting heart rate. Continuing the monitoring of this sample via our cohort study and put to action multinational prospective researches with large sample sizes and long follow-ups can lead to more precise results and better scientific judgments

Association between inter-arm blood pressure difference and cardiovascular disease: result from baseline Fasa Adults Cohort Study

The inter-arm blood pressure difference has been advocated to be associated with cardiovascular mortality and morbidity. Our study aimed to investigate the association between Inter-arm systolic and diastolic blood pressure differences and Cardio Vascular Disease (CVD). A total of 10,126 participants aged 35–70 years old were enrolled in a prospective Fasa Persian Adult Cohort. In this cross-sectional study, the cutoff values for inter-arm blood pressure difference were less than 5, greater than 5, greater than 10, and greater than 15 mm Hg. Descriptive statistics and logistic regression were used to analyze the data. Based on the results the prevalence of ≥ 15 mmHg inter-arm systolic and diastole blood pressure difference (inter-arm SBPD and inter-arm DBPD) were 8.08% and 2.61%. The results of logistic regression analysis showed that inter-arm SBPD ≥ 15 and (OR<5/≥15 = 1.412; 95%CI = 1.099–1.814) and inter-arm DBPD ≥ 10 (OR<5/≥10 = 1.518; 95%CI = 1.238–1.862) affected the risk of CVD. The results showed that the differences in BP between the arms had a strong positive relationship with CVD. Therefore, inter-arm blood pressure could be considered a marker for the prevention and diagnosis of CVD for physicians

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

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

A comparative assessment between Globorisk and WHO cardiovascular disease risk scores: a population-based study

Abstract The Globorisk and WHO cardiovascular risk prediction models are country-specific and region-specific, respectively. The goal of this study was to assess the agreement and correlation between the WHO and Globorisk 10-year cardiovascular disease risk prediction models. The baseline data of 6796 individuals aged 40–74 years who participated in the Fasa cohort study without a history of cardiovascular disease or stroke at baseline were included. In the WHO and Globorisk models scores were calculated using age, sex, systolic blood pressure (SBP), current smoking, diabetes, and total cholesterol for laboratory-based risk and age, sex, SBP, current smoking, and body mass index (BMI) for non-laboratory-based risk (office-based or BMI-based). In Globorisk and WHO risk agreement across risk categories (low, moderate, and high) was examined using the kappa statistic. Also, Pearson correlation coefficients and scatter plots were used to assess the correlation between Globorisk and WHO models. Bland–Altman plots were presented for determination agreement between Globorisk and WHO risk scores in individual’s level. In laboratory-based models, agreement across categories was substantial in the overall population (kappa values: 0.75) and also for females (kappa values: 0.74) and males (kappa values: 0.76), when evaluated separately. In non-laboratory-based models, agreement across categories was substantial for the whole population (kappa values: 0.78), and almost perfect for among males (kappa values: 0.82) and substantial for females (kappa values: 0.73). The results showed a very strong positive correlation (r ≥ 0.95) between WHO and Globorisk laboratory-based scores for the whole population, males, and females and also a very strong positive correlation (r > 0.95) between WHO and Globorisk non-laboratory-based scores for the whole population, males, and females. In the laboratory-based models, the limit of agreements was better in males (95%CI 2.1 to − 4.2%) than females (95%CI 4.3 to − 7.3%). Also, in the non-laboratory-based models, the limit of agreements was better in males (95%CI 2.9 to − 4.0%) than females (95%CI 3.2 to − 6.1%). There was a good agreement between both the laboratory-based and the non-laboratory-based WHO models and the Globorisk models. The correlation between two models was very strongly positive. However, in the Globorisk models, more people were in high-risk group than in the WHO models. The scatter plots and Bland–Altman plots showed systematic differences between the two scores that vary according to the level of risk. So, for these models may be necessary to modify the cut points of risk groups. The validity of these models must be determined for this population