Adherence to Mediterranean Diet Is Associated With Lung Function in Older Adults: Data From the Health and Retirement Study.

Objective: The aim of this work was to examine the association between adherence to a Mediterranean diet (MD) and lung function in older adults.Design: This was an observational and cross-sectional study.Setting: This research was conducted among community-dwelling older adults from the 2014 Health and Retirement Study (HRS).Subjects: Subjects were 2108 adults aged 50 years or older, 1234 (58.5%) of whom were female.Measures: Dietary intakes from respondents of the Health and Retirement Study (HRS) were used for the current analysis. Adherence to MD was evaluated using the MedDietScore, while lung function was evaluated through peak expiratory flow rate (PEF; l/min). Multiple linear regression and logistic regression were performed, adjusted for potential confounders, to examine the relation between adherence to MD and lung function.Results: Mean MedDietScore was 28.0 (± 5.0), indicating a moderate adherence to MD. Multiple linear regression showed a significant association between the MedDietScore and lung function (ß = 0.072, 95% confidence interval [CI]: 0.039-0.104) after adjusting for age, gender, body mass index, race, comorbidities, education, height, grip strength, smoking history, physical activity, and daily caloric intake. Specific food groups such as grains, dairy products, and fish consumption were also associated with PEF rate (p < 0.05). Logistic regression confirmed these findings, and high adherence to MD was associated with reduced risk of having PEF rate < 80% of its peak predictive value (odds ratio: 0.65, 95% CI: 0.48-0.89).Conclusions: The results of this study indicate that adherence to MD is an independent predictor of lung function in older adults, and dietary interventions could be a possible preventive measure in adults with a high risk of developing lung function decline.

Short-term effectiveness of a theory-based intervention to promote diabetes management behaviours among adults with type 2 diabetes in Iran: A randomised control trial.

BACKGROUND: Diet and physical activity are recommended for diabetes management. Evidence suggests theory-based interventions are more efficacious than non-theory approaches. This study aimed to test the short-term effectiveness of an integrated theoretical model-based intervention to encourage compliance for low-fat food consumption, carbohydrate counting and physical activity in adults with type 2 diabetes. METHODS: A 4-week parallel randomised control trial was conducted in Iran. Data were collected using a self-report questionnaire at baseline and 8-weeks post-intervention. This survey assessed the theory of planned behaviour (TPB) constructs of attitude, subjective norm (others' approval) and perceived behavioural control (PBC). We also assessed risk perceptions (motivational) and planning (volitional) from the health action process approach (HAPA). Furthermore, weight, body mass index, triglyceride (TG) and LDL-cholesterol were measured, with a sub-sample of participants providing haemoglobin A1c (HbA1c) assessments. RESULTS: For both low-fat food consumption and physical activity, only planning revealed a significant improvement over time for intervention rather than control participants (F = 8.78, P ≤ .001 for low-fat vs F = 11.26, P ≤ .001 for physical activity). For carbohydrate counting, significant effects were found for behaviour (F = 4.37, P = .03), intention (F = 8.14, P ≤ .001), PBC (F = 7.52, P ≤ .001) and planning (F = 4.54, P = .03), reflecting improvements over time in the intervention participants compared to controls. Furthermore, the effects of the intervention on behaviour were partially mediated via participants' degree of planning (B = 0.10, SE = 0.06, CI = 0.01 to 0.26). The serum TG level was significantly reduced from pre to post-intervention for intervention rather than for control participants (F = 18.69, P ≤ .001) as did Hb1Ac in a sub-sample of study participants. CONCLUSIONS: This intervention showed promising short-term effects for carbohydrate counting but did not show improvements for low-fat diet nor physical activity. Given the improvement in psychological measures and self-reported behaviour for carbohydrate counting, coupled with the findings for TG, future research is needed to demonstrate longer-term improvements.

Smartphone-Based Interventions to Reduce Sedentary Behavior and Promote Physical Activity Using Integrated Dynamic Models: Systematic Review.

BACKGROUND: Traditional psychological theories are inadequate to fully leverage the potential of smartphones and improve the effectiveness of physical activity (PA) and sedentary behavior (SB) change interventions. Future interventions need to consider dynamic models taken from other disciplines, such as engineering (eg, control systems). The extent to which such dynamic models have been incorporated in the development of interventions for PA and SB remains unclear. OBJECTIVE: This review aims to quantify the number of studies that have used dynamic models to develop smartphone-based interventions to promote PA and reduce SB, describe their features, and evaluate their effectiveness where possible. METHODS: Databases including PubMed, PsycINFO, IEEE Xplore, Cochrane, and Scopus were searched from inception to May 15, 2019, using terms related to mobile health, dynamic models, SB, and PA. The included studies involved the following: PA or SB interventions involving human adults; either developed or evaluated integrated psychological theory with dynamic theories; used smartphones for the intervention delivery; the interventions were adaptive or just-in-time adaptive; included randomized controlled trials (RCTs), pilot RCTs, quasi-experimental, and pre-post study designs; and were published from 2000 onward. Outcomes included general characteristics, dynamic models, theory or construct integration, and measured SB and PA behaviors. Data were synthesized narratively. There was limited scope for meta-analysis because of the variability in the study results. RESULTS: A total of 1087 publications were screened, with 11 publications describing 8 studies included in the review. All studies targeted PA; 4 also included SB. Social cognitive theory was the major psychological theory upon which the studies were based. Behavioral intervention technology, control systems, computational agent model, exploit-explore strategy, behavioral analytic algorithm, and dynamic decision network were the dynamic models used in the included studies. The effectiveness of quasi-experimental studies involved reduced SB (1 study; P=.08), increased light PA (1 study; P=.002), walking steps (2 studies; P=.06 and P<.001), walking time (1 study; P=.02), moderate-to-vigorous PA (2 studies; P=.08 and P=.81), and nonwalking exercise time (1 study; P=.31). RCT studies showed increased walking steps (1 study; P=.003) and walking time (1 study; P=.06). To measure activity, 5 studies used built-in smartphone sensors (ie, accelerometers), 3 of which used the phone's GPS, and 3 studies used wearable activity trackers. CONCLUSIONS: To our knowledge, this is the first systematic review to report on smartphone-based studies to reduce SB and promote PA with a focus on integrated dynamic models. These findings highlight the scarcity of dynamic model-based smartphone studies to reduce SB or promote PA. The limited number of studies that incorporate these models shows promising findings. Future research is required to assess the effectiveness of dynamic models in promoting PA and reducing SB. TRIAL REGISTRATION: International Prospective Register of Systematic Reviews (PROSPERO) CRD42020139350; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=139350.

Precision Surgery for Obesity.

Precision medicine is targeted towards improving the effectiveness of treatment, reducing the side effects of drugs and reducing medical costs. The application of precision surgery for obesity is a new concept that involves 2 stages: the first stage is to attain a precise obesity surgery, and the second stage is to achieve individualized obese gene therapy. In this article, we discuss the value of precision surgery for obesity, its stages and its future application to improve obesity surgery. Due to recent advancements in medical technologies, genetics, surgical and clinical research; precision surgery for obesity will lead the future of obesity surgery.

Effects of pycnogenol on cardiometabolic health: A systematic review and meta-analysis of randomized controlled trials.

AIM: Clinical trials on the effect of pycnogenol supplementation on cardiometabolic health have been controversial. We conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) to evaluate the potential effect of pycnogenol supplementation on cardiometabolic profile. METHODS: PubMed, Scopus, and ISI Web of Science databases were searched until October 2018. RCTs that evaluated the effects of pycnogenol on cardiometabolic parameters were included. DerSimonian and Laird random-effect models were used to compute the weighted mean differences (WMDs) and 95% confidence intervals (CIs). RESULTS: Twenty-four RCTs including 1594 participants were included in the meta-analysis. Pycnogenol significantly reduced fasting blood glucose (WMD: -5.86 mg/dl; 95% CI: -9.56, -2.15), glycated hemoglobin (WMD = -0.29%, 95%CI: -0.56, -0.01), systolic blood pressure (WMD: -2.54 mmhg; 95% CI: -4.08, -0.99), diastolic blood pressure (WMD: -1.76 mmhg; 95% CI: -3.12, -0.41), body mass index (WMD: -0.47 kg/m2; 95% CI: -0.90, -0.03), LDL cholesterol (WMD: -7.12 mg/dl; 95% CI: -13.66, -0.58) and increased HDL cholesterol (WMD: 3.27 mg/dl; 95% CI: 0.87, 5.66). CONCLUSION: This meta-analysis suggests that pycnogenol may have a role in preventing cardiometabolic disease. However, further well-designed RCTs are recommended to evaluate its long-term effects and explore the optimal duration of use and dosage.

mHealth Interventions for Exercise and Risk Factor Modification in Cardiovascular Disease.

Exercise and lifestyle risk factor management are critical for the secondary prevention of cardiovascular disease but are poorly adhered to. Mobile health interventions could enhance engagement; however, a one-size intervention approach cannot meet the needs of all people. We hypothesize a unifying digital platform that enables choice from a suite of evidence-based programs will enhance access, delivery, and engagement.

Mobile phone use and willingness to pay for SMS for diabetes in Bangladesh.

BACKGROUND: Mobile phone SMS is increasingly used as a means of communication between patients and their healthcare providers in many countries of the world. We investigated mobile phone use and factors associated with willingness-to-pay (WTP) for diabetes SMS among patients with type 2 diabetes in Bangladesh. METHODS: As part of a randomized controlled study, in 515 patients with type 2 diabetes, socioeconomic status, mobile phone use, WTP for diabetes SMS, anthropometry and HbA1c were measured. Multivariate regression was used to identify factors associated with WTP. RESULTS: The median (interquartile range [IQR]) of WTP for diabetes SMS was 20 (45) Bangladesh Taka (BDT) (1 BDT = 0.013 US$). WTP was significantly higher for males [OR 2.4, 95% CI (1.0-5.7)], patients with household income >50 000 BDT [4.6 (1.1-20.4)] and those with primary education [5.6 (1.2-26.6)] and secondary and higher education [5.2 (1.4-19.6)]. CONCLUSIONS: The high proportion of mobile phone use and WTP for diabetes SMS are encouraging as possible strategy to use such technologies and deserve further evaluation.

Relationship between income generating activities of rural women and their reproductive health behavior in Bangladesh.

INTRODUCTION: The objective of the study was to find out the effects of income generating activities of rural women and their reproductive health behavior (contraceptive use) in Bangladesh. METHODS: A cross-sectional study using a multi-stage sampling technique was carried out among 200 married rural women in Cox's Bazar, Bangladesh. Data were collected using a structured questionnaire on socioeconomic factors, income generating activities, women's empowerment in mobility, decision making and reproductive health behavior in terms of contraceptive use, number of children and desire for more children. Logistic regression analysis was used to determine the relationship between income generating activities and contraceptive use. RESULTS: Almost half (45.5%) of the participants were involved in income generating activities. A great majority (63.9%) worked year-round, two-thirds (75.0%) earned cash for their family and 21.3% were engaged in poultry farms. Women aged 26-35 years, members of any non-governmental organization and from a poor family were more likely to be engaged in income generating activities (≤0.001). Highly educated women worked more than their less educated counterparts and the opposite was true for their husbands (≤0.001). Almost half of the women (45.0%) did not use any contraceptive. Contraceptive use was significantly higher among working women (73.4%) than with non-working women (33.0%). Women engaged in income generating activities were more likely to use contraceptives compared to non-working women (odds ratio 5.6, 95% confidence interval 3.1-7.0, ≤0.001). RESULTS: Income generating activities seem to empower women, increase their likelihood of using contraception and are one of the key issues for changing the life of rural women in Bangladesh.

NeuroNet19: an explainable deep neural network model for the classification of brain tumors using magnetic resonance imaging data.

Brain tumors (BTs) are one of the deadliest diseases that can significantly shorten a person's life. In recent years, deep learning has become increasingly popular for detecting and classifying BTs. In this paper, we propose a deep neural network architecture called NeuroNet19. It utilizes VGG19 as its backbone and incorporates a novel module named the Inverted Pyramid Pooling Module (iPPM). The iPPM captures multi-scale feature maps, ensuring the extraction of both local and global image contexts. This enhances the feature maps produced by the backbone, regardless of the spatial positioning or size of the tumors. To ensure the model's transparency and accountability, we employ Explainable AI. Specifically, we use Local Interpretable Model-Agnostic Explanations (LIME), which highlights the features or areas focused on while predicting individual images. NeuroNet19 is trained on four classes of BTs: glioma, meningioma, no tumor, and pituitary tumors. It is tested on a public dataset containing 7023 images. Our research demonstrates that NeuroNet19 achieves the highest accuracy at 99.3%, with precision, recall, and F1 scores at 99.2% and a Cohen Kappa coefficient (CKC) of 99%.

The Effect of Adding Mirtazapine to Quetiapine on Reducing Agitation in Patients with Alzheimer's Disease.

Background: Alzheimer's disease (AD) is one of the most debilitating diseases in old age, associated with cognitive decline and behavioral symptoms. Objective: This study aimed to investigate the effect of adding mirtazapine to quetiapine in reducing agitation among patients with AD. Methods: Thirty-seven elderly patients (18 cases and 19 controls) with AD, diagnosed according to National Institute on Aging and Alzheimer's Association (NIA-AA) criteria, were enrolled at Nezam-Mafi Clinic. Inclusion criteria comprised a minimum of two years post-diagnosis, a Cohen-Mansfield Agitation and Aggression Questionnaire (CMAI) score above 45, and treatment with 100-150 mg of quetiapine. Patients were randomly assigned to receive mirtazapine (15 mg at night, increased to 30 mg at night after two weeks) or a placebo. Cognitive changes were assessed at weeks 0 and 6 using the Mini-Mental State Examination instrument. Furthermore, symptoms of agitation and aggression were evaluated using the CMAI questionnaire at weeks 4 and 6. Results: In this study, the mean duration of AD in the control group was 4.68 years, and in the case group, it was 5.05 years. Although the total agitation score showed no significant change at the end of the study compared to the control group, the rate of physical non-aggressive behavior showed a significant decrease (p <  0.05). Conclusions: According to this study, adding mirtazapine to the antipsychotic drug regimen may not be an effective treatment for agitation in AD patients.

A control system model of capability-opportunity-motivation and behaviour (COM-B) framework for sedentary and physical activity behaviours.

Objective: Theoretical frameworks are essential for understanding behaviour change, yet their current use is inadequate to capture the complexity of human behaviour such as physical activity. Real-time and big data analytics can assist in the development of more testable and dynamic models of current theories. To transform current behavioural theories into more dynamic models, it is recommended that researchers adopt principles such as control systems engineering. In this article, we aim to describe a control system model of capability-opportunity-motivation and behaviour (COM-B) framework for reducing sedentary behaviour (SB) and increasing physical activity (PA) in adults. Methods: The COM-B model is explained in terms of control systems. Examples of effective behaviour change techniques (BCTs) (e.g. goal setting, problem-solving and social support) for reducing SB and increasing PA were mapped to the COM-B model for illustration. Result: A fluid analogy of the COM-B system is presented. Conclusions: The proposed integrated model will enable empirical testing of individual behaviour change components (i.e. BCTs) and contribute to the optimisation of digital behaviour change interventions.

A Bluetooth-Enabled Device for Real-Time Detection of Sitting, Standing, and Walking: Cross-Sectional Validation Study.

BACKGROUND: This study assesses the accuracy of a Bluetooth-enabled prototype activity tracker called the Sedentary behaviOR Detector (SORD) device in identifying sedentary, standing, and walking behaviors in a group of adult participants. OBJECTIVE: The primary objective of this study was to determine the criterion and convergent validity of SORD against direct observation and activPAL. METHODS: A total of 15 healthy adults wore SORD and activPAL devices on their thighs while engaging in activities (lying, reclining, sitting, standing, and walking). Direct observation was facilitated with cameras. Algorithms were developed using the Python programming language. The Bland-Altman method was used to assess the level of agreement. RESULTS: Overall, 1 model generated a low level of bias and high precision for SORD. In this model, accuracy, sensitivity, and specificity were all above 0.95 for detecting sitting, reclining, standing, and walking. Bland-Altman results showed that mean biases between SORD and direct observation were 0.3% for sitting and reclining (limits of agreement [LoA]=-0.3% to 0.9%), 1.19% for standing (LoA=-1.5% to 3.42%), and -4.71% for walking (LoA=-9.26% to -0.16%). The mean biases between SORD and activPAL were -3.45% for sitting and reclining (LoA=-11.59% to 4.68%), 7.45% for standing (LoA=-5.04% to 19.95%), and -5.40% for walking (LoA=-11.44% to 0.64%). CONCLUSIONS: Results suggest that SORD is a valid device for detecting sitting, standing, and walking, which was demonstrated by excellent accuracy compared to direct observation. SORD offers promise for future inclusion in theory-based, real-time, and adaptive interventions to encourage physical activity and reduce sedentary behavior.

Social and economic impact of diabetics in Bangladesh: protocol for a case-control study.

BACKGROUND: Diabetes affects both individuals and their families and has an impact on economic and social development of a country. Information on the availability, cost, and quality of medical care for diabetes is mostly not available for many low- and middle-income countries including Bangladesh. Complications from diabetes, which can be devastating, could largely be prevented by wider use of several inexpensive generic medicines, simple tests and monitoring and can be a cost saving intervention. This study will provide an in-depth and comprehensive picture of social and economic impacts of diabetes in Bangladesh and propose clear recommendations for improving prevention and management of diabetes. The objectives of the study are: 1) To study the association between diabetes and other health problems and its social impacts. 2) To estimate the economic impact of diabetes including total direct and indirect costs. 3) To measure the impact of diabetes on quality of life among diabetes patients in Bangladesh. 4) To study the impact of diabetes on the health care system METHODS: This is a case-control study comparing cases with type 2 diabetes to controls without diabetes matched on age, sex and place of residence. 564 cases and 564 controls will be selected from the outpatient department of a tertiary hospital in Dhaka, Bangladesh. Data on socioeconomic status, health utility index, direct and indirect costs for diabetes, medication adherence, quality of life, treatment satisfaction, diet, physical activity, mental state examination, weight, height, hip and waist circumference, blood pressure, pulse, medication history, laboratory data and physical examination will be conducted. OUTCOME MEASURES: The primary outcome measures will be association between diabetes and other health problems, cost of diabetes, impact of diabetes on quality of life and secondary outcome measures are impact of diabetes on healthcare systems in Bangladesh. DISCUSSION: This study will provide an in-depth and comprehensive picture of social and economic impacts of diabetics in Bangladesh and propose clear recommendations for improving prevention and management of diabetics. It will help to develop programs and policies for better management of Diabetics and cost effective strategies in Bangladesh context.

The effectiveness of psychoeducation in improving attitudes towards psychological disorders and internalized stigma in the family members of bipolar patients: A quasi-experimental study.

Family members of bipolar patients experience stigma following being labeled by others, which can disrupt their routine lives and result in social isolation. This study aims to evaluate the effectiveness of psychoeducation in improving the attitudes of bipolar patients' family members towards psychological disorders and internalized stigma. The present study is a quasi-experimental study with a pre- and post-test follow-up design, in which 74 individuals were selected by convenience sampling among families who had a member with a bipolar disorder who was referred to the largest psychiatric hospital in Iran in 2021. The participants were randomly divided into the experimental and control groups (n = 37 per group). The members of the experimental group then underwent eight 90-min sessions of psychoeducation. The control group also received psychoeducation at the end of the study. The results of analysis of covariance showed that psychoeducation reduced internalized stigma in the family members of bipolar patients and increased their positive attitudes towards psychological disorders compared with the control group (p < .01). On this basis, psychoeducation can be useful to reduce the internalized stigma of family members of bipolar patients and to increase their positive attitudes towards psychological disorders.

Ambient carbon monoxide and cardiovascular-related hospital admissions: A time-series analysis.

Background and aims: Although several studies have investigated the association between air pollutants and cardiovascular diseases (CVDs) in recent years, a lack of evidence exists regarding carbon monoxide (CO) exposure, especially in the Eastern Mediterranean's polluted regions. In this study, we aimed to evaluate the short-term effect of CO exposure on daily CVD hospital admissions in Isfahan, a major city in Iran. Methods: Data were extracted from the CAPACITY study on daily CVD hospital admissions in Isfahan from March 2010 to March 2012. The 24-h mean CO concentrations were obtained from four local monitoring stations. In a time-series framework, the association between CO and daily hospitalizations for total and cause-specific CVDs in adults (ischemic heart disease (IHD), heart failure (HF), and cerebrovascular disease) was conducted using Poisson's (or negative binomial) regression, after adjusting for holidays, temperature, dew point, and wind speed, considering different lags and mean lags of CO. The robustness of the results was examined via two- and multiple-pollutant models. Stratified analysis was also conducted for age groups (18-64 and ≥65 years), sex, and seasons (cold and warm). Results: The current study incorporated a total of 24,335 hospitalized patients, (51.6%) male with a mean age of 61.9 ± 16.4 years. The mean CO concentration was 4.5 ± 2.3 mg/m³. For a 1 mg/m3 increase in CO, we found a significant association with the number of CVD hospitalizations. The largest adjusted percent change in HF cases was seen in lag0, 4.61% (2.23, 7.05), while that for total CVDs, IHD, and cerebrovascular diseases occurred in mean lag2-5, 2.31% (1.42, 3.22), 2.23% (1.04, 3.43), and 5.70% (3.59, 7.85), respectively. Results were found to be robust in two- and multiple-pollutant models. Although the associations changed for sex, age groups, and seasons, they remained significant for IHD and total CVD, except for the warm season, and for HF, except for the younger age group and cold seasons. Additionally, the exposure-response relationship curve of the CO concentrations with total and cause-specific CVD admissions showed non-linear relationships for IHD and total CVDs. Conclusions: Our results showed that exposure to CO contributed to an increase in the number of CVD hospitalizations. The associations were not independent of age groups, season, and sex.

Effects of sulfur dioxide and particulate matter pollution on hospital admissions for hypertensive cardiovascular disease: A time series analysis.

Background and aims: Air pollution is a major environmental risk factor and the leading cause of disease burden with detrimental effects on cardiovascular systems. Cardiovascular diseases are predisposed by various risk factors, including hypertension, as the most important modifiable risk factor. However, there is a lack of sufficient data concerning the impact of air pollution on hypertension. We sought to study the associations of short-term exposure to Sulfur dioxide (SO2) and particulate matter (PM10) with the number of daily hospital admissions of hypertensive cardiovascular diseases (HCD). Methods: All hospitalized patients between March 2010 to March 2012 were recruited with the final diagnosis of HCD based on the International Classification of Diseases 10 (codes: I10-I15) from 15 hospitals in Isfahan, one of the most polluted cities in Iran. The 24-hour average concentrations of pollutants were obtained from 4 monitoring stations. In addition to single- and two-pollutant models, we used Negative Binomial and Poisson models with covariates of holidays, dew point, temperature, wind speed, and extracted latent factors of other pollutants controlling for multi-collinearity to examine the risk for hospital admissions for HCD affected by SO2 and PM10 exposures in the multi-pollutant model. Results: A total of 3132 hospitalized patients (63% female) with a mean (standard deviation) age of 64.96 (13.81) were incorporated in the study. The mean concentrations of SO2 and PM10 were 37.64 µg/m3 and 139.08 µg/m3, respectively. Our findings showed that a significantly increased risk of HCD-induced hospital admission was detected for a 10 µg/m3 increase in the 6-day and 3-day moving average of SO2 and PM10 concentrations in the multi-pollutant model with a percent change of 2.11% (95% confidence interval: 0.61 to 3.63%) and 1.19% (0.33 to 2.05%), respectively. This finding was robust in all models and did not vary by gender (for SO2 and PM10) and season (for SO2). However, people aged 35-64 and 18-34 years were vulnerable to SO2 and PM10 exposure-triggered HCD risk, respectively. Conclusions: This study supports the hypothesis of the association between short-term exposure to ambient SO2 and PM10 and the number of hospital admissions due to HCD.

Body composition predicts hypertension using machine learning methods: a cohort study.

We used machine learning methods to investigate if body composition indices predict hypertension. Data from a cohort study was used, and 4663 records were included (2156 were male, 1099 with hypertension, with the age range of 35-70 years old). Body composition analysis was done using bioelectrical impedance analysis (BIA); weight, basal metabolic rate, total and regional fat percentage (FATP), and total and regional fat-free mass (FFM) were measured. We used machine learning methods such as Support Vector Classifier, Decision Tree, Stochastic Gradient Descend Classifier, Logistic Regression, Gaussian Naïve Bayes, K-Nearest Neighbor, Multi-Layer Perceptron, Random Forest, Gradient Boosting, Histogram-based Gradient Boosting, Bagging, Extra Tree, Ada Boost, Voting, and Stacking to classify the investigated cases and find the most relevant features to hypertension. FATP, AFFM, BMR, FFM, TRFFM, AFATP, LFATP, and older age were the top features in hypertension prediction. Arm FFM, basal metabolic rate, total FFM, Trunk FFM, leg FFM, and male gender were inversely associated with hypertension, but total FATP, arm FATP, leg FATP, older age, trunk FATP, and female gender were directly associated with hypertension. AutoMLP, stacking and voting methods had the best performance for hypertension prediction achieving an accuracy rate of 90%, 84% and 83%, respectively. By using machine learning methods, we found that BIA-derived body composition indices predict hypertension with acceptable accuracy.

Changes in the burden and underlying causes of heart failure in the Eastern Mediterranean Region, 1990-2019: An analysis of the Global Burden of Disease Study 2019.

Background: The burden of heart failure (HF) is high globally, but information on its burden in the Eastern Mediterranean Region (EMR) is limited. This study provides a systematic analysis of the burden and underlying causes of HF in the EMR, including at the country level, between 1990 and 2019. Methods: We used the 2019 Global Burden of Disease (GBD) data for estimates of prevalence, years lived with disability (YLDs), and underlying causes of HF in the EMR. Age-standardised prevalence, YLDs, and underlying causes of HF were compared by 5-year age groups (considering 15 years old and more), sex (male and female), and countries. Findings: In contrast with the decreasing trend of HF burden globally, EMR showed an increasing trend. Globally, the HF age-standardised prevalence and YLDs decreased by 7.06% (95% UI: -7.22%, -6.9%) and 6.82% (95% UI: -6.98%, -6.66%) respectively, from 1990 to 2019. The HF age-standardised prevalence and YLDs in the EMR in 2019 were 706.43 (95% UI: 558.22-887.87) and 63.46 (95% UI: 39.82-92.59) per 100,000 persons, representing an increase of 8.07% (95% UI: 7.9%, 8.24%) and 8.79% (95% UI: 8.61%, 8.97%) from 1990, respectively. Amongst EMR countries, the age-standardised prevalence and YLDs were highest in Kuwait, while Pakistan consistently had the lowest HF burden. The dramatic increase of the age-standardised prevalence and YLDs were seen in Oman (28.79%; 95% UI: 28.51%, 29.07% and 29.56%; 95% UI: 29.28%, 29.84%), while Bahrain witnessed a reduction over the period shown (-9.66%; 95% UI: -9.84%, -9.48% and-9.14%; 95% UI: -9.32%, -8.96%). There were significant country-specific differences in trends of HF burden from 1990 to 2019. Males had relatively higher rates than females in all age groups. Among all causes of HF in 2019, ischemic heart disease accounted for the highest age-standardised prevalence and YLDs, followed by hypertensive heart disease. Interpretation: The burden of HF in the EMR was higher than the global, with increasing age-standardised prevalence and YLDs in countries of the region. A more comprehensive approach is needed to prevent underlying causes and improve medical care to control the burden of HF in the region. Funding: None.

Trends in the burden and determinants of hypertensive heart disease in the Eastern Mediterranean region, 1990-2019: an analysis of the Global Burden of Disease Study 2019.

Background: Hypertensive heart disease (HHD), one of the end-organ damage consequences of hypertension, is an important public health issue worldwide. Data on the HHD burden in the Eastern Mediterranean region (EMR) are scarce. We aimed to investigate the burden of HHD in the EMR, its member countries, and globally from 1990 to 2019. Methods: We used 2019 Global Burden of Disease (GBD) data to report the HHD age-standardised prevalence, disability adjusted life years (DALYs), years of life lost (YLLs), and mortality, as well as HHD risk factors attribution percent with their 95% uncertainty interval (UI). Global data are reported alongside EMR data, and its 22 respective countries. We compared the burden of HHD by socio-demographic index (SDI), sex, age groups, and countries. Findings: The age-standardised prevalence rate (per 100,000 population) of HHD was higher in the EMR (281.7; 95% UI: 204.5-383.4) in 2019, compared with the global prevalence (233.8; 95% UI: 170.5-312.9). The EMR age-standardised DALYs (per 100,000 population) for HHD in 2019 was 561.9 (361.0-704.1), compared with 268.2 (204.6-298.1) at the global level. There was an increase in HHD prevalence, reduction in mortality, and DALYs between 1990 and 2019 (4.01%, -7.6%, and -6.5%, respectively) in EMR. Among EMR countries, the highest versus lowest rates of age-standardised prevalence, mortality, and DALYs in 2019 [estimate (95% UI)] were in Jordan [561.62 (417.9-747.6)] versus Saudi Arabia [94.9 (69.5-129.0)]; Afghanistan [74.5 (23.7-112.3)] versus Saudi Arabia [4.3 (3.3-5.9)]; and Afghanistan [1374.1 (467.2-2020.7)] versus Qatar [87.11 (64.40-114.29)], respectively. Interpretation: HHD remains a significant problem in the EMR, with a higher burden than global levels. Serious efforts toward high-quality management and prevention are strongly recommended. Based on this study, our recommendation for the EMR is to adopt effective preventive strategies. For example, promoting healthy dietary patterns and prompt screening for undiagnosed HTN in public places, promoting regular blood pressure measurements at home, and creating community awareness about early detection of HTN. Funding: None.