Performance of body mass index in predicting diabetes and hypertension in the Eastern Province of Saudi Arabia

A Review of Anthropometric Measurements for Saudi Adults and Elderly, Directions for Future Work and Recommendations to Establish Saudi Guidelines in Line with the Saudi 2030 Vision

Body weight is a significant risk factor for the disease burden of noncommunicable diseases (NCDs). Anthropometric measurements are the first step in determining NCDs risk, and clinicians must have access to valid cutoffs. This study aims to review the literature of Saudi national guidelines and studies previously conducted in Saudi Arabia (SA) and to provide insights and recommendations to establish national guidelines in anthropometric measurements for Saudi adults/elderly in line with the Saudi 2030 Vision. In total, 163 studies were included, and 12 of them contributed to the development of specific anthropometric cutoffs. Cutoffs for metabolic syndrome, waist circumference, and body mass index were established in Saudi adults. However, limited studies were conducted in the elderly. This review warrants establishing standard cutoffs of Saudi adult anthropometrics to avoid over/underreporting of malnutrition and adiposity. This review will help policymakers and the Ministry of Health to establish national guidelines and standard cutoffs to be used in SA for anthropometric measurements that may assist in detecting malnutrition and NCDs.

The future health and economic burden of obesity-attributable type 2 diabetes and liver disease among the working-age population in Saudi Arabia

Background

Obesity and type 2 diabetes (T2DM) are increasing in Saudi Arabia (SA). Among other conditions, these risk factors increase the likelihood of non-alcoholic fatty liver disease (NAFLD), which in turn increases risks for advanced liver diseases, such as non-alcoholic steatohepatitis (NASH), cirrhosis and cancer. The goal of this study was to quantify the health and economic burden of obesity-attributable T2DM and liver disease in SA.

Methods

We developed a microsimulation of the SA population to quantify the future incidence and direct health care costs of obesity-attributable T2DM and liver disease, including liver cancer. Model inputs included population demographics, body mass index, incidence, mortality and direct health care costs of T2DM and liver disease and relative risks of each condition as a function of BMI category. Model outputs included age- and sex-disaggregated incidence of obesity-attributable T2DM and liver disease and their direct health care costs for SA’s working-age population (20–59 years) between 2020 and 2040.

Results

Between 2020 and 2040, the available data predicts 1,976,593 [± 1834] new cases of T2DM, 285,346 [±874] new cases of chronic liver diseases, and 2,101 [± 150] new cases of liver cancer attributable to obesity, amongst working-age people. By 2040, the direct health care costs of these obesity-attributable diseases are predicted to be 127,956,508,540 [± 51,882,446] USD.

Conclusions

The increase in obesity-associated T2DM and liver disease emphasises the urgent need for obesity interventions and strategies to meaningfully reduce the future health and economic burden of T2DM, chronic liver diseases and liver cancer in SA.

The Association between Obesity and Chronic Conditions: Results from a Large Electronic Health Records System in Saudi Arabia

This cross-sectional study aimed to estimate the prevalence of obesity and its association with diabetes and hypertension among beneficiaries in the National Guard Health Affairs system of Saudi Arabia. We included individuals aged 17 years and older, and patients were classified as diabetic or hypertensive if they had any visit during the 4 years where the primary diagnosis was one of those conditions or they were taking diabetes or hypertension medications. The association between obesity (body mass index ≥30) and diabetes and hypertension were evaluated using a multiple logistic regression model, adjusting for age, gender, nationality, and region. A total of 616,092 individuals were included. The majority were Saudi nationals (93.1%). Approximately 68% of the population were either obese (38.9%) or overweight (29.30%). Obesity was more prevalent among Saudi nationals (39.8% vs. 26.7%, p < 0.01) and females (45.3% vs. 31.2%, p < 0.01). Obesity was independently associated with diabetes mellitus (OR = 2.24, p < 0.01) and hypertension (OR = 2.15, p < 0.01). The prevalence of obesity in the study population was alarming and more pronounced among women. Our findings call for efforts to intensify preventive measures to reduce obesity and associated conditions. Using electronic records to examine the impact of interventions to reduce obesity and chronic conditions may help monitor and improve population health.

Body-mass index and diabetes risk in 57 low-income and middle-income countries: a cross-sectional study of nationally representative, individual-level data in 685 616 adults

BACKGROUND

The prevalence of overweight, obesity, and diabetes is rising rapidly in low-income and middle-income countries (LMICs), but there are scant empirical data on the association between body-mass index (BMI) and diabetes in these settings.

METHODS

In this cross-sectional study, we pooled individual-level data from nationally representative surveys across 57 LMICs. We identified all countries in which a WHO Stepwise Approach to Surveillance (STEPS) survey had been done during a year in which the country fell into an eligible World Bank income group category. For LMICs that did not have a STEPS survey, did not have valid contact information, or declined our request for data, we did a systematic search for survey datasets. Eligible surveys were done during or after 2008; had individual-level data; were done in a low-income, lower-middle-income, or upper-middle-income country; were nationally representative; had a response rate of 50% or higher; contained a diabetes biomarker (either a blood glucose measurement or glycated haemoglobin [HbA1c]); and contained data on height and weight. Diabetes was defined biologically as a fasting plasma glucose concentration of 7·0 mmol/L (126·0 mg/dL) or higher; a random plasma glucose concentration of 11·1 mmol/L (200·0 mg/dL) or higher; or a HbA1c of 6·5% (48·0 mmol/mol) or higher, or by self-reported use of diabetes medication. We included individuals aged 25 years or older with complete data on diabetes status, BMI (defined as normal [18·5-22·9 kg/m2], upper-normal [23·0-24·9 kg/m2], overweight [25·0-29·9 kg/m2], or obese [≥30·0 kg/m2]), sex, and age. Countries were categorised into six geographical regions: Latin America and the Caribbean, Europe and central Asia, east, south, and southeast Asia, sub-Saharan Africa, Middle East and north Africa, and Oceania. We estimated the association between BMI and diabetes risk by multivariable Poisson regression and receiver operating curve analyses, stratified by sex and geographical region.

FINDINGS

Our pooled dataset from 58 nationally representative surveys in 57 LMICs included 685 616 individuals. The overall prevalence of overweight was 27·2% (95% CI 26·6-27·8), of obesity was 21·0% (19·6-22·5), and of diabetes was 9·3% (8·4-10·2). In the pooled analysis, a higher risk of diabetes was observed at a BMI of 23 kg/m2 or higher, with a 43% greater risk of diabetes for men and a 41% greater risk for women compared with a BMI of 18·5-22·9 kg/m2. Diabetes risk also increased steeply in individuals aged 35-44 years and in men aged 25-34 years in sub-Saharan Africa. In the stratified analyses, there was considerable regional variability in this association. Optimal BMI thresholds for diabetes screening ranged from 23·8 kg/m2 among men in east, south, and southeast Asia to 28·3 kg/m2 among women in the Middle East and north Africa and in Latin America and the Caribbean.

INTERPRETATION

The association between BMI and diabetes risk in LMICs is subject to substantial regional variability. Diabetes risk is greater at lower BMI thresholds and at younger ages than reflected in currently used BMI cutoffs for assessing diabetes risk. These findings offer an important insight to inform context-specific diabetes screening guidelines.

FUNDING

Harvard T H Chan School of Public Health McLennan Fund: Dean's Challenge Grant Program.

Revising BMI Cut-Off Points for Obesity in a Weight Management Setting in Lebanon

Obesity is defined by the World Health Organization (WHO) as a body mass index (BMI) ≥ 30 Kg/m2. This study aimed to test the validity of this BMI cut-off point for adiposity in a weight management clinical setting in Lebanon. This cross-sectional study of 442 adults of mixed gender, categorized by the WHO BMI classification, included: 66 individuals of normal weight, 110 who were overweight and 266 with obesity. The clinical sample was referred to the Outpatient Clinic in the Department of Nutrition and Dietetics at Beirut Arab University (BAU) in Lebanon. All participants underwent anthropometric evaluation. The gold standard for defining obesity was based on the National Institutes of Health (NIH)/WHO guidelines for total body fat percentage (BF%). The best sensitivity and specificity were attained to predict obesity, according to the receiver operating characteristic curve (ROC) analysis. The BMI cut-off point for predicting obesity in the clinical sample was nearly 31.5 Kg/m2, and more than 90% of individuals with obesity and cardiometabolic disease were above this cut-off point. In conclusion, this new BMI cut-off point, an obesity definition higher than suggested in Western populations, was demonstrated to have clinical usefulness. Obesity guidelines in Lebanon, therefore, need revising.

Machine-learning to stratify diabetic patients using novel cardiac biomarkers and integrative genomics

BACKGROUND

Diabetes mellitus is a chronic disease that impacts an increasing percentage of people each year. Among its comorbidities, diabetics are two to four times more likely to develop cardiovascular diseases. While HbA1c remains the primary diagnostic for diabetics, its ability to predict long-term, health outcomes across diverse demographics, ethnic groups, and at a personalized level are limited. The purpose of this study was to provide a model for precision medicine through the implementation of machine-learning algorithms using multiple cardiac biomarkers as a means for predicting diabetes mellitus development.

METHODS

Right atrial appendages from 50 patients, 30 non-diabetic and 20 type 2 diabetic, were procured from the WVU Ruby Memorial Hospital. Machine-learning was applied to physiological, biochemical, and sequencing data for each patient. Supervised learning implementing SHapley Additive exPlanations (SHAP) allowed binary (no diabetes or type 2 diabetes) and multiple classification (no diabetes, prediabetes, and type 2 diabetes) of the patient cohort with and without the inclusion of HbA1c levels. Findings were validated through Logistic Regression (LR), Linear Discriminant Analysis (LDA), Gaussian Naïve Bayes (NB), Support Vector Machine (SVM), and Classification and Regression Tree (CART) models with tenfold cross validation.

RESULTS

Total nuclear methylation and hydroxymethylation were highly correlated to diabetic status, with nuclear methylation and mitochondrial electron transport chain (ETC) activities achieving superior testing accuracies in the predictive model (~ 84% testing, binary). Mitochondrial DNA SNPs found in the D-Loop region (SNP-73G, -16126C, and -16362C) were highly associated with diabetes mellitus. The CpG island of transcription factor A, mitochondrial (TFAM) revealed CpG24 (chr10:58385262, P = 0.003) and CpG29 (chr10:58385324, P = 0.001) as markers correlating with diabetic progression. When combining the most predictive factors from each set, total nuclear methylation and CpG24 methylation were the best diagnostic measures in both binary and multiple classification sets.

CONCLUSIONS

Using machine-learning, we were able to identify novel as well as the most relevant biomarkers associated with type 2 diabetes mellitus by integrating physiological, biochemical, and sequencing datasets. Ultimately, this approach may be used as a guideline for future investigations into disease pathogenesis and novel biomarker discovery.

Hypomethylation of the Angiotensin II Type I Receptor (AGTR1) Gene Along with Environmental Factors Increases the Risk for Essential Hypertension

OBJECTIVES

The present study aimed to evaluate the hypertension status of community residents, analyze environmental and epigenetic factors, and propose prevention measures for hypertension.

METHODS

In our study, different methylation levels were distinguished utilizing melting temperature (Tm) values in both the case and the control group. Multiple logistic regression analysis was used to estimate the risk of having essential hypertension (EH) between hypertensive and nonhypertensive participants. A receiver-operating characteristic curve was used to analyze Tm cutoff levels of methylation.

RESULTS

The average DNA Tm was 71.784 with a standard deviation of 0.210. The Tm value of community residents (Fujian, China) was inversely correlated with systolic and diastolic blood pressure. Student t test analysis showed a clear separation in Tm expression levels between the hypertensive and the control group (p < 0.05). The Tm value was lower in the hypertension group than in the normotensive group. Multivariate regression analysis showed that high levels of DNA methylation were a protective factor in hypertension with adjustment of demographic and environmental factors, whereas when the Tm value increased by 0.1 units, the risk of hypertension was reduced by 0.652 times. Patients that smoked and consumed an irregular diet demonstrated a lower degree of methylation in the presence of hypertension.

CONCLUSIONS

DNA methylation affects the risk for the development of hypertension; therefore, epigenetic markers could be used to measure hypertension levels to help elucidate the pathogenesis of EH.

Evaluation of health care services provided for older adults in primary health care centers and its internal environment. A step towards age-friendly health centers

Objectives:

To evaluate the health care services provided for older adults by primary health care centers (PHCCs) in Riyadh, Kingdom of Saudi Arabia (KSA), and the ease of use of these centers by older adults.

Methods:

Between October 2013 and January 2014, we conducted a descriptive cross-sectional study of 15 randomly selected PHCCs in Riyadh City, KSA. The evaluation focused on basic indicators of clinical services offered and factors indicative of the ease of use of the centers by older adults. Evaluations were based upon the age-friendly PHCCs toolkit of the World Health Organization.

Results:

Coverage of basic health assessments (such as blood pressure, diabetes, and blood cholesterol) was generally good. However, fewer than half of the PHCCs offered annual comprehensive screening for the common age-related conditions. There was no screening for cancer. Counseling on improving lifestyle was provided by most centers. However, there was no standard protocol for counseling. Coverage of common vaccinations was poor. The layout of most PHCCs and their signage were good, except for lack of Braille signage. There may be issues of access of older adults to PHCCs through lack of public transport, limited parking opportunities, the presence of steps, ramps, and internal stairs, and the lack of handrails.

Conclusions:

Clinical services and the internal environment of PHCCs can be improved. The data will be useful for health-policy makers to improve PHCCs to be more age-friendly.

Defining a BMI Cut-Off Point for the Iranian Population: The Shiraz Heart Study

In this study we evaluated and redefined the optimum body mass index (BMI) cut-off point for the Iranian population based on metabolic syndrome (MeS) risk factors. We further evaluated BMI cut-off points with and without waist circumference (WC) as a cofactor of risk and compared the differences. This study is part of the largest surveillance programs conducted in Shiraz, Iran, termed the Shiraz Heart study. Our study sample included subjects between the ages of 20 to 65 years old. After excluding pregnant women, those with missing data and those with comorbid disease, a total of 12283 made up the study population. The participants underwent a series of tests and evaluations by trained professionals in accordance with WHO recommendations. Hypertension, abnormal fasting blood sugar (FBS), triglyceride (TG) and high density lipoprotein cholesterol (HDL) (in the context of the definition of metabolic syndrome) were prevalent among 32.4%, 27.6%, 42.1 and 44.2% of our participants, respectively. Women displayed higher rates of overall obesity compared to men (based on the definition by the WHO as higher than 30 kg/m²). Regarding MeS, 38.9% of our population had the all symptoms of MeS which was more prevalent among women (41.5% vs. 36%). When excluding WC in the definition of MeS, results showed that males tend to show a higher rate of metabolic risk factors (19.2% vs. 15.6%). Results of multivariate analysis showed that parallel to an increase in BMI, the odds ratio (OR) for acquiring each component of the metabolic syndrome increased (OR = 1.178; CI: 1.166–1.190). By excluding WC, the previous OR decreased (OR = 1.105; CI: 1.093–1.118). Receiver Operating Characteristic (ROC) curve analysis showed that the optimum BMI cut-off point for predicting metabolic syndrome was 26.1 kg/m² and 26.2 kg/m² [Accuracy (Acc) = 69% and 61%, respectively)] for males and females, respectively. The overall BMI cut-off for both sexes was 26.2 kg/m² (Acc = 65%) with sensitivity and specificity of 69% and 62%, respectively. This cut-off had a positive predictive value of 54% and a negative predictive value of 76%. When we excluded waist circumference, the optimum BMI cut-off for acquiring metabolic risk factors in males decreased to 25.7 kg/m² (Acc = 67%) and increased for women to 27.05 kg/m² (Acc = 66%). Iranians are at higher risks of morbidity related to metabolic factors at a lower BMI cut-off and prompt action and preventive health policy are required to prevent and educate Iranians regarding diseases associated with obesity.

Diabetes epidemic sweeping the Arab world

The prevalence of type-2 diabetes mellitus (T2DM) has increased dramatically during the last 2 decades, a fact driven by the increased prevalence of obesity, the primary risk factor for T2DM. The figures for diabetes in the Arab world are particularly startling as the number of people with diabetes is projected to increase by 96.2% by 2035. Genetic risk factors may play a crucial role in this uncontrolled raise in the prevalence of T2DM in the Middle Eastern region. However, factors such as obesity, rapid urbanization and lack of exercise are other key determinants of this rapid increase in the rate of T2DM in the Arab world. The unavailability of an effective program to defeat T2DM has serious consequences on the increasing rise of this disease, where available data indicates an unusually high prevalence of T2DM in Arabian children less than 18 years old. Living with T2DM is problematic as well, since T2DM has become the 5^th leading cause of disability, which was ranked 10^th as recently as 1990. Giving the current status of T2DM in the Arab world, a collaborative international effort is needed for fighting further spread of this disease.

Evaluation of malnutrition in patients with nervous system disease

Nutritional deficiencies are independent risk factors for adverse outcomes in patients with nervous system disease. Patients with nervous system disease can often become malnourished due to swallowing difficulties or unconsciousness. This malnourishment increases hospitalization duration; average total hospital cost; occurrence of infection, pressure ulcers, and other complications. These problems need to be addressed in the clinic. In this paper, we review the relevant literature, including studies on influencing factors, evaluations, indexes, and methods: Our aim is to understand the current status of malnutrition in patients with nervous system disease and reasons associated with nutritional deficiencies by using malnutrition evaluation methods to assess the risk of nutritional deficiencies in the early stages.

Diabetes in the Middle East and North Africa

AIMS

Even though the Middle East and North Africa (MENA) region had the highest comparative prevalence of diabetes in 2012, little is known about the nuances of diabetes risk and capacity to address the burdens. To provide a comprehensive overview, we reviewed the literature on diabetes in the MENA region.

METHODS

We conducted a systematic search in PubMed between January 1990 and January 2012 for studies on diabetes in the MENA region without language restriction.

RESULTS

There was a paucity of country-specific epidemiology data in the region. Diabetes prevalence varied widely across studies, from 2.5% in 1982 to 31.6% in 2011. Older age and higher body mass index were the most strongly associated risk factors for diabetes. Among people with diabetes, over half did not meet recommended care targets. In addition, macrovascular and microvascular complications were observed in 9-12% and 15-54% of diabetes population, respectively.

CONCLUSIONS

This review suggests a need for more representative surveillance data in this noteworthy focal point of the global diabetes epidemic. Such actions will not only help to understand the actual burden of diabetes but also motivate actions on design and implementation of diabetes prevention and control programs.