Adapting a Prediction Rule for Metabolic Syndrome Risk Assessment Suitable for Developing Countries

Association between urbanization and metabolic syndrome in low- and middle-income countries: A systematic review and meta-analysis

AIMS

The prevalence of metabolic syndrome (MetS) is on the rise in an increasingly urbanized world. The study aimed to review the association between urbanization and MetS in low- and middle-income countries (LMICs).

DATA SYNTHESIS

A comprehensive search of five databases (MEDLINE, Web of Science, Scopus, EMBASE, and CENTRAL) was performed in January 2022 and updated in October 2022. Peer-reviewed studies that met the eligibility selection criteria were included. Search terms were used for the main concepts which are MetS, dietary patterns, and urbanization in LMICs. Study selection was done in two stages and in duplicate. Random effects models were used to calculate the overall pooled prevalence and main study-level characteristics. Out of 9,773 identified studies, nineteen were included in the systematic review and meta-analysis. The studies were done on 313,644 participants (149,616 urban and 164,028 rural). The pooled risk ratio (RR, 95% confidence interval) of MetS between urban and rural dwellers was RR = 1.24; 95%CI [1.15, 1.34] (I2 = 96.0%, P < 0.0001). A relatively higher prevalence of MetS among urban than rural residents has been observed, especially with the International Diabetes Federation criteria (RR = 1.54; 95%CI [1.21, 1.96]; I2 = 65.0%), and in the population in India (RR = 2.19; 95%CI = 1.24, 3.88, I2 = 85%). Overall, the role of dietary patterns in the development of MetS was inconsistent, and few studies showed a lower risk of MetS with adherence to recommended healthy dietary patterns.

CONCLUSIONS

There was an association between urbanization and the high prevalence of MetS. Interventions and policies to reduce the risk of MetS are needed.

Prevalence and predictors of undiagnosed type 2 diabetes and pre-diabetes among adult Egyptians: a community-based survey

BACKGROUND

The global prevalence of abnormal glycemic level comprising diabetes mellitus (DM) and pre-diabetes (PDM) is rapidly increasing with special concern for the entity silent or undiagnosed diabetes; those unaware of their condition. Identification of people at risk became much easier with the use of risk charts than the traditional methods. The current study aimed to conduct a community-based screening for T2DM to estimate the prevalence of undiagnosed DM and to assess the AUSDRISK Arabic version as a predictive tool in an Egyptian context.

METHODS

A cross-sectional study was conducted among 719 Adults aging 18 years or more and not known to be diabetics through a population-based household survey. Each participant was interviewed to fill demographic and medical data as well as the AUSDRISK Arabic version risk score and undergo testing for fasting plasma glucose (FPG) and oral glucose tolerance test (OGTT).

RESULTS

The prevalence of DM and PDM were 5% and 21.7% respectively. The multivariate analysis revealed that age, being physically inactive, history of previous abnormal glycemic level and waist circumference were the predictors for having abnormal glycemic level among the studied participants. At cut off points ≥ 13 and ≥ 9, the AUSDRISK respectively discriminated DM [sensitivity (86.11%), specificity (73.35%), and area under the curve (AUC): 0.887, 95% CI: 0.824-0.950] and abnormal glycemic level [sensitivity (80.73%), specificity (58.06%), and AUC: 0.767, 95% CI: 0.727-0.807], p < 0.001.

CONCLUSIONS

Overt DM just occupies the top of an iceberg, its unseen big population have undiagnosed DM, PDM or been at risk of T2DM because of sustained exposure to the influential risk factors. The AUSDRISK Arabic version was proved to be sensitive and specific tool to be used among Egyptians as a screening tool for the detection of DM or abnormal glycemic level. A prominent association has been demonstrated between AUSDRISK Arabic version score and the diabetic status.

Arabic version of the Australian type 2 diabetes risk assessment tool (AUSDRISK): translation and validation

Objective

The current study aimed to translate the Australian Type 2 Diabetes Risk Assessment tool (AUSDRISK) into the Arabic language and evaluate the reliability and validity of the resultant Arabic version among Egyptians. The AUSDRISK was translated into Arabic language using the World Health Organization (WHO) forward and backward translation protocol. Using the WHO cluster sampling, a sample of 18+ years 719 Egyptians was randomly selected through a population-based household survey. Each participant was interviewed to fill the AUSDRISK Arabic version risk score and undergo confirmatory testing for fasting plasma glucose (FPG) and oral glucose tolerance test (OGTT). Test-retest reliability and convergent validity were computed.

Results

Most of the study participants were physically active (60.5%) and females (69.3%). The Arabic version of the AUSDRISK reflected statistically significant perfect positive correlation (r = 1 and p < 0.01) for test re-test reliability as well as a significant moderate positive correlation with each of FPG (r = 0.48, p < 0.01) and OGTT (r = 0.52, p < 0.01) for the criterion-related (convergent) validity. The recalibrated noninvasive AUSDRISK Arabic version proved to be a simple, reliable, and valid predictive tool, and thereof, its employment for opportunistic mass public screening is strongly recommended. This can reduce diabetes mellitus Type 2disease burden and health expenditure.

Cardiometabolic Health Status, Ethnicity and Health-Related Quality of Life (HRQoL) Disparities in an Adult Population: NutrIMDEA Observational Web-Based Study

Precision public health supported on online tools is increasingly emerging as a potential strategy to achieve health promotion and disease prevention. Our aim was to assess the relationships of sociodemographic variables, anthropometric data, dietary habits and lifestyle factors with health-related quality of life (HRQoL), cardiometabolic health status and ethnicity in an online recruited adult population (NutrIMDEA Study). NutrIMDEA Study is a web-based cross-sectional survey that included 17,333 adults. Self-reported sociodemographic characteristics, anthropometric data, clinical and family history of cardiometabolic illnesses, dietary habits, lifestyle factors and HRQoL features were collected. Diseased individuals showed significative poorer MedDiet and worse HRQoL than those in the healthy cardiometabolic status group (p < 0.05). In comparison, European/Caucasian individuals reported a significantly better HRQoL, higher MedDiet and HRQoL values compared with those of other ethnicities (p < 0.05). We obtained a total of 16.8% who reported poor/fair, 56.5% good and 26.6% very good/excellent HRQoL. Respondents with very good/excellent HRQoL showed lower BMI, greater adherence to a Mediterranean diet (MedDiet) and higher physical activity. The results suggest the presence of interactions between the mental and physical components of HRQoL with obesity, sedentarism and dietary intake, which were dependent on disease status and ethnicity. Online HRQoL assessment could contribute to wider implementation of precision public health strategies to promote health targeted interventions with policy implications to community health promotion.

Construction of Xinjiang metabolic syndrome risk prediction model based on interpretable models

Background

We aimed to construct simple and practical metabolic syndrome (MetS) risk prediction models based on the data of inhabitants of Urumqi and to provide a methodological reference for the prevention and control of MetS.

Methods

This is a cross-sectional study conducted in the Xinjiang Uygur Autonomous Region of China. We collected data from inhabitants of Urumqi from 2018 to 2019, including demographic characteristics, anthropometric indicators, living habits and family history. Resampling technology was used to preprocess the data imbalance problems, and then MetS risk prediction models were constructed based on logistic regression (LR) and decision tree (DT). In addition, nomograms and tree diagrams of DT were used to explain and visualize the model.

Results

Of the 25,542 participants included in the study, 3,267 (12.8%) were diagnosed with MetS, and 22,275 (87.2%) were diagnosed with non-MetS. Both the LR and DT models based on the random undersampling dataset had good AUROC values (0.846 and 0.913, respectively). The accuracy, sensitivity, specificity, and AUROC values of the DT model were higher than those of the LR model. Based on a random undersampling dataset, the LR model showed that exercises such as walking (OR=0.769) and running (OR= 0.736) were protective factors against MetS. Age 60 ~ 74 years (OR=1.388), previous diabetes (OR=8.902), previous hypertension (OR=2.830), fatty liver (OR=3.306), smoking (OR=1.541), high systolic blood pressure (OR=1.044), and high diastolic blood pressure (OR=1.072) were risk factors for MetS; the DT model had 7 depth layers and 18 leaves, with BMI as the root node of the DT being the most important factor affecting MetS, and the other variables in descending order of importance: SBP, previous diabetes, previous hypertension, DBP, fatty liver, smoking, and exercise.

Conclusions

Both DT and LR MetS risk prediction models have good prediction performance and their respective characteristics. Combining these two methods to construct an interpretable risk prediction model of MetS can provide methodological references for the prevention and control of MetS.

Molecular pathways dysregulated by Pb2+ exposure prompts pancreatic beta-cell dysfunction

Type 2 diabetes mellitus (T2DM) is a metabolic disease characterized by reduced insulin sensitivity and dysfunction of β-cells. Although the increasing prevalence of diabetes worldwide is largely attributed to genetic predisposition or lifestyle factors (insufficient physical activity), and caloric intake. Environmental factors, exposure to xenobiotics and heavy metals have also been reported to be causative factors of T2DM. At this juncture, we, through our work unveil a plausible link between Pb²⁺ exposure and diabetes mellitus, and delineated a comprehensive understanding of the potential mechanisms of Pb²⁺-induced β-cells dysfunction. In our in vivo observations, we found that Pb²⁺ exposure strongly reduced glucose-stimulated insulin secretion and diminished functional pancreatic β-cell mass. Mechanistically, we found that Pb²⁺ downregulates intracellular cAMP level via hyper-activating Ca²⁺/calmodulin-dependent 3',5'-cyclic nucleotide phosphodiesterase 1C and thereby reduces glucose-stimulated insulin secretion. Further, we report that Pb²⁺ inhibited mitochondrial adenosine triphosphate production and also identified Pb²⁺ as a negative regulator of β-cell proliferation via Ca²⁺/calmodulin-dependent protein kinase kinases-pAMPK-pRaptor axis. Together, our findings strongly reinforce Pb²⁺ to hijack the physiological role of calcium ions, by mimicking Ca²⁺ within pancreatic β-cell and thereby stands as a diabetogenic xenobiotic.

Study of DYRK1B gene expression and its association with metabolic syndrome in a small cohort of Egyptians

BACKGROUND

A cluster of many risk factors for type 2 diabetes and cardiovascular disease is used to describe the metabolic syndrome (MetS). Moreover, genetic differences associated with metabolic syndrome play a key role in its prevalence and side effects. This study aims to investigate the expression of DYRK1B and its association with metabolic syndrome in a small cohort of Egyptian.

MATERIALS AND METHODS

A total of 100 adult Egyptians (50 with MetS and 50 healthy control subjects) were included to this study. Clinical, biochemical and anthropometric analysis were assessed. Relative gene expressions of DYRK1B were compared between two groups of subjects using real time PCR.

RESULTS

We observed marked overexpression in DYRK1B (p < 0.05) in MetS subjects when compared with the healthy control subjects.

CONCLUSION

This is the first study to provide evidence that DYRK1B is highly expressed among the MetS subjects.

Cardiometabolic risk prediction algorithms for young people with psychosis: a systematic review and exploratory analysis

OBJECTIVE

Cardiometabolic risk prediction algorithms are common in clinical practice. Young people with psychosis are at high risk for developing cardiometabolic disorders. We aimed to examine whether existing cardiometabolic risk prediction algorithms are suitable for young people with psychosis.

METHODS

We conducted a systematic review and narrative synthesis of studies reporting the development and validation of cardiometabolic risk prediction algorithms for general or psychiatric populations. Furthermore, we used data from 505 participants with or at risk of psychosis at age 18 years in the ALSPAC birth cohort, to explore the performance of three algorithms (QDiabetes, QRISK3 and PRIMROSE) highlighted as potentially suitable. We repeated analyses after artificially increasing participant age to the mean age of the original algorithm studies to examine the impact of age on predictive performance.

RESULTS

We screened 7820 results, including 110 studies. All algorithms were developed in relatively older participants, and most were at high risk of bias. Three studies (QDiabetes, QRISK3 and PRIMROSE) featured psychiatric predictors. Age was more strongly weighted than other risk factors in each algorithm. In our exploratory analysis, calibration plots for all three algorithms implied a consistent systematic underprediction of cardiometabolic risk in the younger sample. After increasing participant age, calibration plots were markedly improved.

CONCLUSION

Existing cardiometabolic risk prediction algorithms cannot be recommended for young people with or at risk of psychosis. Existing algorithms may underpredict risk in young people, even in the face of other high-risk features. Recalibration of existing algorithms or a new tailored algorithm for the population is required.

Validation of a Non-Laboratory Based Screening Tool for Predicting Non-Alcoholic Fatty Liver Disease in an Egyptian Setting

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver disorder in more than 20% of the general population worldwide.  Several combinations of non-invasive factors and scoring models were investigated as indicators of NAFLD. This study aimed to validate and adapt an established fatty liver score, which allows the identification of NAFLD based on routinely available clinical and laboratory data.

MATERIALS AND METHODS

The study cohort comprised 190 adults seeking health check-up at the out-patient clinic of a tertiary care hospital in Alexandria, Egypt. Anthropometric, clinical, and laboratory data were recorded and the status of fatty liver was diagnosed by abdominal ultrasound. A logistic regression model was built to determine the predictors of NAFLD. The performance of the derived risk scores was compared to other existing models.

RESULTS

Obesity (60.0%), metabolic syndrome (42.6%), and NAFLD (56.8%) were predominant features among the study population. Smoking [OR (95% CI) = 4.4 (0.9-21.4)], obesity [OR (95% CI) = 4.0 (1.7-9.7)], hypertension [OR (95% CI) = 2.4 (1.03-5.5)], elevated serum total cholesterol [OR (95% CI) = 4.8 (1.8-13.1)], triglycerides [OR (95% CI) = 11.8 (2.3-661.02)], and ALT [OR (95% CI) = 4.8 (1.8-13.1)] were multivariate predictors of NAFLD. A NAFLD screening questionnaire with values applicable for Egyptians was adapted from an existing model after validation. A total score ≥7 was suggestive of NAFLD [AUC = 0.810 (0.749-0.871); sensitivity = 87.0%; specificity = 62.2%; PPV = 75.2%; NPV = 78.5%].

CONCLUSIONS

NAFLD can be sufficiently predicted among apparently healthy Egyptians by a tempted simple and non-invasive scoring index although external validation is warranted.