Gender differences in the modifiable risk factors associated with the presence of prediabetes: A systematic review

Undetected and undiagnosed comorbidity in patients with obesity undergoing bariatric surgery-Results from the Berlin Bariatric Cohort study

The quality of general obesity management before bariatric surgery (BS) is rarely investigated. Inadequate information regarding undetected and undiagnosed comorbidities (UUCs) in individuals with obesity may influence the penetration, risks, and outcomes of BS. We conducted a cohort study involving a pre-specified medical check-up in a cooperation between a BS department and an outpatient medical centre. A total of 1068 patients (74.4% women) were enrolled in the study. The mean age was 42.1 years (standard deviation [SD] 11.9) and the mean body mass index (BMI) was 46.1 (SD 6.91). The onset of obesity occurred in 11.4% of patients during childhood, 47.2% during schooltime/adolescence, 41.4% in adulthood. Gender differences were observed: men had higher BMI, systolic blood pressure, and impaired metabolic state (including diabetes, dyslipidemia, and liver disease with p-values <.001 for all). Women had lower haemoglobin levels, impaired iron status, lower albumin levels (p < .001), and increased C-reactive protein levels (p < .05). The prevalence of UUC conditions (percentage of cases) was as follows: arterial hypertension, 53%; decreased cystatin C clearance, 57%; dyslipidemia, 41%; fatty liver, 40%; iron deficiency, 37%; diabetes mellitus, 34%; vitamin D deficiency, 32%; chronic pain syndrome, 23%; liver fibrosis, 12%; obstructive sleep apnea, 10%; and vitamin deficiencies (vitamin B12, folic acid, vitamin K1) <10%. Undiagnosed hypertension was more prevalent in younger women, and nutritional deficits were associated with high BMI in both genders. Older age and high BMI were associated with undiagnosed diabetes and decreased glomerular filtration rate in both genders, and with liver fibrosis in men. UUC are highly prevalent in individuals undergoing BS. A refined assessment is recommended to improve health conditions and outcome in these candidates.

Cardiometabolic risk assessment: A school-based study in Brazilian adolescent

BACKGROUND AND AIMS

Recently, new indices combining routine and low-cost anthropometric and biochemical measurements have emerged. Among them, the visceral adiposity index (VAI) and lipid accumulation product (LAP) are being investigated for the prediction of altered blood pressure (BP) and insulin resistance (IR). Therefore, this study aimed to evaluate whether visceral adiposity index (VAI) and height-corrected lipid accumulation product (HLAP) are predictors of cardiometabolic risk in Brazilian adolescents.

METHODS AND RESULTS

Data were obtained from the Cardiovascular Risk in Adolescents (ERICA) study, a cross-sectional, national, multicenter, school-based survey conducted between 2013 and 2014 in Brazil. The sample consisted of 37,815 adolescents aged 12-17 years of both genders attending the last 3 years of elementary or secondary school from public and private schools located in 273 municipalities with more than 100,000 inhabitants. A Poisson regression was performed to verify associations between VAI and HLAP indices and the presence of altered BP and IR according to sex. In addition, receiver operating characteristic curve (ROC) analysis was applied to compare the predictive ability and determine the cut-off points of the VAI and HLAP indices in identifying cardiometabolic risk obtained by altered BP and IR. The prevalences of altered BP and IR were 24.49 % (95 % confidence interval [CI]: 23.14-25.87) and 24.22 % (95 % CI: 22.70-25.80), respectively.

CONCLUSIONS

The VAI and HLAP indices are good predictors of cardiometabolic risk in Brazilian adolescents. HLAP showed better performance in identifying insulin resistance in males.

Patterns of dyslipidemia and its associated factors among prediabetic subjects. A cross-sectional study at a primary care clinic

Introduction

Diabetes is closely linked to cardiovascular diseases, with diabetic dyslipidaemia serving as an established marker of the acceleration of complications, contributing to an increased cardiovascular risk among patients. Timely detection and early characterization of lipid abnormalities can help clinicians in implementing effective preventive measures. This study aimed to determine the patterns and associated factors of dyslipidaemia among Malaysian subjects with borderline diabetes.

Methods

A retrospective study was conducted among subjects with borderline diabetes aged ≥18 years who visited a primary healthcare centre at Universiti Sains Malaysia from January 2017 to December 2018. Sociodemographic, clinical and laboratory data were obtained from electronic medical records. Data were analysed using SPSS version 25.

Results

A total of 250 participants with borderline diabetes were included in the analysis. Of them, 93.6% (n=234) had lipid abnormalities. Isolated dyslipidaemia characterised by a high low-density lipoprotein cholesterol (LDL-C) level (38.8%, n=97) was the most common pattern found, followed by combined dyslipidaemia of high LDL-C and triglyceride (TG) levels (22.8%, n=57). The male sex was found to be significantly associated with hypertriglyceridemia (adjusted odds ratio [AOR] = 1.86, 95% confidence interval [CI] =1.09-3.1)(P=0.02). Diastolic blood pressure ≥90mmHg was significantly associated with a low HDL-C level (A0R=2.09, 95% CI=1.0-4.1) (P=0.03).

Conclusion

The majority of subjects with borderline diabetes have lipid abnormalities. Specifically, isolated dyslipidaemia characterised by a high LDL-C level is alarmingly prevalent. Further large-scale robust studies are needed to confirm the present findings.

Baseline prevalence of hyperglycemia and its predictors among community clinic users of a selected rural area of Bangladesh: A cross-sectional study using the WHO PEN Protocol 1

AIMS/INTRODUCTION

Our objective was to estimate the prevalence of hyperglycemia at baseline, and identify its predictors among community clinic (CC) users from a selected rural area of Bangladesh.

MATERIALS AND METHODS

This cross-sectional study partly used the baseline data of implementation research in which a total of 11,244 adults visited the CC, and their blood glucose, blood pressure and anthropometry were evaluated according to 'Action 2' of the World Health Organization (WHO) Package of Essential Noncommunicable Disease Interventions (PEN) protocol 1. Of these, 11,144 had complete information on demography, chronic diseases and their risk factors, which were collected during the implementation of 'Action 1' of WHO PEN protocol 1 at the household level. Hyperglycemia, prediabetes (PreD) and type 2 diabetes were diagnosed using the WHO criteria.

RESULTS

Using WHO PEN protocol 1, the estimated baseline prevalence was 12.5% for hyperglycemia, 3.4% for PreD and 9.2% for type 2 diabetes, and was more prevalent among men compared with women. PreD and type 2 diabetes had significantly higher odds ratio (OR >1) of having common risk factors as follows: age ≥40 years (PreD, P < 0.001; type 2 diabetes, P < 0.001), generalized obesity (PreD, P < 0.001; type 2 diabetes, P = 0.005) and hypertension (PreD, P < 0.000; type 2 diabetes, P < 0.001). Furthermore, participants with a family history of diabetes appeared to be a significant predictor of type 2 diabetes (P < 0.001), but not for PreD (P = 0.303).

CONCLUSIONS

Hyperglycemia, preD and type 2 diabetes showed a comparatively high prevalence among the CC users of the selected rural area. Obesity and hypertension are the key modifiable risk factors that should be reduced using a CC-centered risk reduction strategy.

Establishment of hypertension risk nomograms based on physical fitness parameters for men and women: a cross-sectional study

Objective

This study aims to establish hypertension risk nomograms for Chinese male and female adults, respectively.

Method

A series of questionnaire surveys, physical assessments, and biochemical indicator tests were performed on 18,367 adult participants in China. The optimization of variable selection was conducted by running cyclic coordinate descent with 10-fold cross-validation through the least absolute shrinkage and selection operator (LASSO) regression. The nomograms were built by including the predictors selected through multivariable logistic regression. Calibration plots, receiver operating characteristic curves (ROC), decision curve analysis (DCA), clinical impact curves (CIC), and net reduction curve plots (NRC) were used to validate the models.

Results

Out of a total of 18 variables, 5 predictors-namely age, body mass index, waistline, hipline, and resting heart rate-were identified for the hypertension risk predictive model for men with an area under the ROC of 0.693 in the training set and 0.707 in the validation set. Seven predictors-namely age, body mass index, body weight, cardiovascular disease history, waistline, resting heart rate, and daily activity level-were identified for the hypertension risk predictive model for women with an area under the ROC of 0.720 in the training set and 0.748 in the validation set. The nomograms for both men and women were externally well-validated.

Conclusion

Gender differences may induce heterogeneity in hypertension risk prediction between men and women. Besides basic demographic and anthropometric parameters, information related to the functional status of the cardiovascular system and physical activity appears to be necessary.

Sex-specific differences in the effect of the atherogenic index of plasma on prediabetes and diabetes in the NHANES 2011-2018 population

BACKGROUND

Although a great deal of scientific evidence on the epidemiological risk factors for diabetes and prediabetes has been accumulated, there is still insufficient evidence to explore sex-related differences. The aim of this study was to examine sex-specific differences in the effect of the atherogenic index of plasma (AIP) on prediabetes and diabetes.

METHODS

This cross-sectional study included data from 10099 American adults. The exposure variable was the AIP, which was defined as log10 (triglycerides/high-density lipoprotein cholesterol). The outcome variables included prediabetes and diabetes defined by the 2013 American Diabetes Association guidelines.

RESULTS

The median age (mean ± SD) was 48.51 ± 18.42 years, and the average value (SD) of the AIP was - 0.09 (0.34). The prevalence of prediabetes was 40.24%, and that of diabetes was 21.32%. Overall, there was a significant positive association between the AIP and prediabetes and diabetes (per 1-unit increment in the AIP: OR, 2.49; 95% CI 1.75, 3.54). The multivariate logistic regression model demonstrated that for each unit increment in the AIP, the prediabetes and diabetes prevalence increased 4.96-fold among female participants (OR 4.96, 95% CI 2.68, 9.18) but not among male participants. We found that the AIP was not related to the prevalence of prediabetes or diabetes (OR 1.41; 95% CI 0.87, 2.29) among males. There was an interaction between sex and the AIP (P for interaction < 0.0001).

CONCLUSIONS

This study showed that a higher AIP was significantly associated with an increased prevalence of prediabetes and diabetes, and the above relationships occurred only among women and not men.

Hyperglycemia screening based on survey data: an international instrument based on WHO STEPs dataset

BACKGROUND

Hyperglycemia is rising globally and its associated complications impose heavy health and economic burden on the countries. Developing effective survey-based screening tools for hyperglycemia using reliable surveillance data, such as the WHO STEPs surveys, would be of great importance in early detection and/or prevention of hyperglycemia, especially in low or middle-income regions.

METHODS

In this study, data from the nationwide 2016 STEPs study in Iran were used to identify socioeconomic, lifestyle, and metabolic factors associated with hyperglycemia. Furthermore, the ability of five commonly used machine learning algorithms (random forest; gradient boosting; support vector machine; logistic regression; artificial neural network) in the prediction of hyperglycemia on STEPs dataset were compared via tenfold cross validation in terms of specificity, sensitivity, and the area under the receiver operating characteristic curve.

RESULTS

A total of 17,705 individuals were included in this study, of those 29.624% (n = 5245) had (undiagnosed) hyperglycemia. Multivariate logistic regression analysis showed that older age (for the elderly group: OR = 5.096; for the middle-aged group: OR = 2.784), high BMI status (morbidly obese: OR = 3.465; obese: OR = 1.992), having hypertension (OR = 1.647), consuming fish more than twice per week (OR = 1.496), and abdominal obesity (OR = 1.464) were the five most important risk factors for hyperglycemia. Furthermore, all the five hyperglycemia prediction models achieved AUC around 0.70, and logistic regression (specificity = 70.22%; sensitivity = 70.2%) and random forest (specificity = 70.75%; sensitivity = 69.78%) had the optimal performance.

CONCLUSIONS

This study shows that it is possible to develop survey-based screening tools for early detection of hyperglycemia using data from nationwide surveys, such as WHO STEPs surveys, and machine learning techniques, such as random forest and logistic regression, without using blood tests. Such screening tools can potentially improve hyperglycemia control, especially in low or middle-income countries.

Development and validation of a risk assessment model for prediabetes in China national diabetes survey

BACKGROUND

Prediabetes risk assessment models derived from large sample sizes are scarce.

AIM

To establish a robust assessment model for prediabetes and to validate the model in different populations.

METHODS

The China National Diabetes and Metabolic Disorders Study (CNDMDS) collected information from 47325 participants aged at least 20 years across China from 2007 to 2008. The Thyroid Disorders, Iodine Status and Diabetes Epidemiological Survey (TIDE) study collected data from 66108 participants aged at least 18 years across China from 2015 to 2017. A logistic model with stepwise selection was performed to identify significant risk factors for prediabetes and was internally validated by bootstrapping in the CNDMDS. External validations were performed in diverse populations, including populations of Hispanic (Mexican American, other Hispanic) and non-Hispanic (White, Black and Asian) participants in the National Health and Nutrition Examination Survey (NHANES) in the United States and 66108 participants in the TIDE study in China. C statistics and calibration plots were adopted to evaluate the model’s discrimination and calibration performance.

RESULTS

A set of easily measured indicators (age, education, family history of diabetes, waist circumference, body mass index, and systolic blood pressure) were selected as significant risk factors. A risk assessment model was established for prediabetes with a C statistic of 0.6998 (95%CI: 0.6933 to 0.7063) and a calibration slope of 1.0002. When externally validated in the NHANES and TIDE studies, the model showed increased C statistics in Mexican American, other Hispanic, Non-Hispanic Black, Asian and Chinese populations but a slightly decreased C statistic in non-Hispanic White individuals. Applying the risk assessment model to the TIDE population, we obtained a C statistic of 0.7308 (95%CI: 0.7260 to 0.7357) and a calibration slope of 1.1137. A risk score was derived to assess prediabetes. Individuals with scores ≥ 7 points were at high risk of prediabetes, with a sensitivity of 60.19% and specificity of 67.59%.

CONCLUSION

An easy-to-use assessment model for prediabetes was established and was internally and externally validated in different populations. The model had a satisfactory performance and could screen individuals with a high risk of prediabetes.

Sociodemographic, anthropometric, and lifestyle correlates of prediabetes and type 2 diabetes in europe: The Feel4Diabetes study

BACKGROUND AND AIMS

The current work aimed to identify the predominant correlates of prediabetes and T2DM among a variety of socio-demographic, anthropometric and lifestyle indices, in a large sample of adults from families at high risk for T2DM.

METHODS AND RESULTS

In this cross-sectional study, 2816 adults were recruited from low-socioeconomic areas in high-income countries (HICs) (Belgium-Finland), HICs under austerity measures (Greece-Spain), and low/middle-income countries (LMICs) (Bulgaria-Hungary). A positive association between the male sex (OR, 95% C.I.2.77 (1.69-4.54)) and prediabetes was revealed compared to females, while there was a negative association between younger age (<45 years) (OR, 95% C.I. 0.58 (0.37-0.92)), and low/medium levels of waist circumference (OR, 95% C.I. 0.44 (0.22-0.89)) with prediabetes compared to older age and high levels of waist circumference, respectively. Concerning T2DM, 0-0.5 cups/day of fruits and berries (OR, 95% C.I.2. 13 (1.16-3.91)) and 150-300 g fish/week (OR, 95% C.I. 2.55 (1.01-6.41)) have a positive association compared to higher consumptions, respectively. Conversely, <1 cup/week legumes (OR, 95% C.I. 0.55 (0.31-0.99) as well as 0-0.5 servings (OR, 95% C.I. 0.34 (0.12-0.95) and 0.5-1 servings (OR, 95% C.I. 0.37 (0.19-0.71) of full-fat dairy/day have a negative association compared to higher consumptions, respectively.

CONCLUSION

These findings indicate the need for diabetes prevention measures targeting young adults and especially men, above 45 years of age, with central obesity and poor dietary habits and prioritize vulnerable groups and populations living in LMICs.

NATIONAL CLINICAL TRIAL NUMBER

NCT02393872.

Exploring the association between habitual food intake and the urine and blood metabolome in adolescents and young adults: a cohort study

SCOPE

Habitual diet may be reflected in metabolite profiles that can improve accurate assessment of dietary exposure and further enhance our understanding of their link to health conditions. We aimed to explore the relationship of habitual food intake with blood and urine metabolites in adolescents and young adults.

METHODS

The study population comprised 228 participants (94 male and 134 female) of the DONALD study. Dietary intake was assessed by yearly repeated 3d-food records. Habitual diet was estimated as the average consumption of 23 food groups in adolescence. Using an untargeted metabolomics approach, we quantified 2638 metabolites in plasma and 1407 metabolites in urine. In each sex, we determined unique diet-metabolite associations using orthogonal projection to latent structures (oPLS) and random forests (RF).

RESULTS

We observed 6 metabolites in agreement between oPLS and RF in urine, 1 in females (vanillylmandelate to processed/ other meat) and 5 in males (indole-3-acetamide, and N6-methyladenosine to eggs; hippurate, citraconate/glutaconate, and X - 12111 to vegetables). We observed no association in blood in agreement.

CONCLUSION

We observed a limited reflection of habitual food group intake by single metabolites in urine and not in blood. The explored biomarkers should be confirmed in additional studies. This article is protected by copyright. All rights reserved.

Association of Mixed Use of Electronic and Conventional Cigarettes and Exposure to Secondhand Smoke With Prediabetes

CONTEXT

Despite previous studies regarding the association between smoking and diabetes, the effects of electronic cigarettes and secondhand smoke (SHS) on glucose metabolism and insulin sensitivity have not been fully elucidated.

OBJECTIVE

To examine the association of mixed electronic and conventional cigarette use and exposure to SHS with prediabetes.

DESIGN

Data from the 2014-2018 Korean National Health and Nutrition Examination Survey were analyzed.

SETTING

Nationwide population-based.

PARTICIPANTS

Of 39 199 participants, 22 385 participants (9490 men, 12 895 women) without diabetes were included. The main independent variables were smoking behaviors, including exposure to SHS.

INTERVENTIONS

None.

MAIN OUTCOME MEASURES

Prediabetes (hemoglobin A1C of 5.7-6.4%).

RESULTS

Of 22 385 participants without diabetes, 6735 had prediabetes. Mixed cigarette use was associated with a 1.57-fold increase in the odds of prediabetes when compared with never-smoking [odds ratio (OR) = 1.57, 95% CI = 1.29-1.92] and a 1.27-fold increase when compared with conventional cigarette use only (OR = 1.27, 95% CI = 1.07-1.52). Participants who were current nonsmokers, but mixed users in the past had an increased risk of prediabetes (OR = 1.54, 95% CI = 1.04-2.13). There was no significant association between prediabetes and current nonsmoking in individuals with previous conventional cigarette use only. Among never-smokers, exposure to SHS significantly increased the risk of prediabetes (OR = 1.16, 95% CI = 1.04-1.30).

CONCLUSIONS

Mixed use of electronic and conventional cigarettes and exposure to SHS increased the risk of prediabetes. Further studies are required to comprehensively investigate the molecular biology underlying the effects of previous and current mixed use of electronic cigarettes and SHS on glucose metabolism.

Related Factors for Impaired Fasting Glucose in Korean Adults: A Population Based Study

Background

Individuals with impaired fasting glucose (IFG) who have poor health behaviors are at a greater risk for various health outcomes. This study compared the health behaviors and health literacy between individuals with non-IFG and IFG; factors that were associated with IFG were identified by sex.

Methods

This study was an observational study with a cross-sectional design based on data from the Korea National Health and Nutrition Examination Survey (KNHANES) that used a stratified, multi-stage, cluster-sampling design to obtain a nationally representative sample. This study analyzed the KNHANES Health Examination Survey and Health Behavior Survey from 2016 to 2018 (N=9919). Multiple logistic regression analysis was employed to compute the odds ratios of health behaviors and health literacy to identify the risk factors for IFG.

Results

The prevalence of IFG among the total was 29.0% (weighted n=2826, 95% CI 27.8–30.2). In the IFG group, 63.6% were male and 36.4% were female (X²=320.57, p<.001). In multiple logistic regression by sex, the factors associated with IFG in male were as follows: age (50s; OR=2.36, 95% CI 1.79–3.13), high BMI (OR=2.27, 95% CI 1.78–2.90), frequent drinking (OR=1.83, 95% CI 1.23–2.72), and using nutrition fact labels (OR=1.35, 95% CI 1.05–1.75). Low economic status (OR=4.18, 95% CI 1.57–11.15) and high BMI (OR=2.35, 95% CI 1.29–4.28) were the affecting factors in female. On the other hand, employment status, perceived stress, and job type were not related to IFG in both male and female.

Conclusions

Strategies should be targeted to improve health behaviors and health literacy for those in their 40s and 60s, male in shift work, those who frequently dine out, overweight male, female with low economic statuses, and frequent drinkers. Moreover, healthcare providers should understand the barriers to health behaviors and literacy to effectively deliver healthcare service.

Diagnostic and Predictive Values of LAP in Hypertension: A Cross-Sectional Study in Chinese Population Older Than 65 Years

This study aimed to investigate the predictive value of lipid accumulation product (LAP) in hypertension in Chinese population older than 65 years. A total of 2092 adults from the communities in Pudong New Area of Shanghai were included in this cross-sectional study. The participants filled in questionnaire and received anthropometric and laboratory examinations. The receiver operating characteristics curve (ROC) was used to analyze the predictive value of different risk factors in hypertension. Results showed that LAP was closely related to hypertension (adjusted OR: 1.011, 95% CI: 1.007-1.015). In females, LAP, fasting blood glucose (FPG), and body mass index (BMI) were associated with hypertension; in males, triglycerides (TG) and waist circumference (WC) were related to hypertension. LAP (AUC = 0.655, 95% CI: 0.632-0.679) was better than neck circumference (NC) and BMI in predicting hypertension. When the cutoff value was 33.5, LAP had the best predictive performance. In males, LAP at 36.72 and 56.76 had the best predictive performance in males (AUC = 0.663, 95% CI: 0.629-0.697) and females (AUC = 0.650, 95% CI: 0.618-0.682), respectively. In conclusion, LAP is a risk factor of hypertension in the elderly. For hypertension, BMI, FPG, and LAP have favorable predictive performance in females, and WC and TG have better predictive performance in males.

Impact of alcohol use disorder on stroke risk in geriatric patients with prediabetes: A nationwide analysis

BACKGROUND

With rising trends of prediabetes in the geriatric population, we aim to assess the impact of alcohol use disorder (AUD) on the outcomes of patients with prediabetes.

METHODS

Hospitalisations amongst the patients (≥65 years) with prediabetes were identified with a diagnosis of AUD and in-hospital stroke using the National Inpatient Sample database (2007-2014). We compared demographics, comorbidities, all-cause mortality, stroke rate and resource utilisation in the elderly prediabetes patients with vs without AUD. Primary outcomes of interest were all-cause mortality and stroke rate, whereas secondary outcomes were the length of stay (days), disposition and resource utilisation in the AUD cohort as compared to the non-AUD cohort.

RESULTS

We had a total of 1.7 million hospitalisations amongst elderly patients with prediabetes, 2.8% (n = 47 962) had AUD. The AUD cohort was more often younger (71 vs 77 years), male (74.1% vs 43.5%) and nonelectively (84.5% vs 78.3%) admitted than non-AUD cohort. The AUD cohort more often consisted of African Americans (9.0% vs 6.6%) and Hispanics (5.3% vs 5.1%) than non-AUD cohort. The AUD cohort showed higher rates of smoking, drug abuse, chronic obstructive pulmonary disease, coagulopathy, peripheral vascular disease and fluid-electrolyte disorders whereas a lower rate of cardiovascular risk factors than non-AUD cohort. All-cause mortality (4.4% vs 3.9%) and stroke (5.5% vs 4.8%, aOR 1.33, 95% CI 1.28-1.39) were significantly higher in the AUD cohort with prolonged stay, higher charges and frequent transfers than non-AUD cohort.

CONCLUSION

AUD in the elderly prediabetes patients increases the stroke risk by up to 33% which can adversely influence the survival rate and healthcare infrastructure.

Precision nutrition based on phenotypical traits and the (epi)genotype: nutrigenetic and nutrigenomic approaches for obesity care

PURPOSE OF REVIEW

The purpose of this article is to rationally review and critically appraise the current knowledge in the most relevant nongenetic and genetic factors influencing obesity predisposition. This information may be translated into the implementation of personalized nutrition approaches involving precision nutrigenetic and nutrigenomic strategies for obesity monitoring and weight management.

RECENT FINDINGS

The importance and influence of several nongenetic contributors to obesity onset and individual responses to weight-loss interventions have been highlighted including the role of age, sex or perinatal feeding and others related to an individual's lifestyle and modifiable. Nutrigenetic studies have analysed potential interactions between polymorphisms influencing energy homeostasis/body composition and dietary factors in relation to adiposity phenotypes and therapy responsiveness. A second approach comprises the Nutrigenomic analysis of gene expression modifications in response to the consumption of specific nutrients or dietary bioactive compounds, which may involve epigenetic mechanisms including deoxyribonucleic acid methylation and micro-ribonucleic acid expression profiles.

SUMMARY

Taken together, these findings encompass the importance of taking into account up-to-date advances in Nutrigenetic and Nutrigenomic hallmarks, globally analysing the risk of weight gain and related outcomes after following nutrition counselling, this contributing to improve obesity care considering phenotypical traits and the genetic make-up for precision obesity care.

Prevalence and determinants of diabetes and prediabetes in southwestern Iran: the Khuzestan comprehensive health study (KCHS)

BACKGROUND

The Middle East and North Africa (MENA) is postulated to have the highest increase in the prevalence of diabetes by 2030; however, studies on the epidemiology of diabetes are rather limited across the region, including in Iran.

METHODS

This study was conducted between 2016 and 2018 among Iranian adults aged 20 to 65 years residing in Khuzestan province, southwestern Iran. Diabetes was defined as the fasting blood glucose (FBG) level of 126 mg/dl or higher, and/or taking antidiabetic medications, and/or self-declared diabetes. Prediabetes was defined as FBG 100 to 125 mg/dl. Multinomial logistic regression models were used to examine the association of multiple risk factors that attained significance on the outcome.

RESULTS

Overall, 30,498 participants were recruited; the mean (±SD) age was 41.6 (±11.9) years. The prevalence of prediabetes and diabetes were 30.8 and 15.3%, respectively. We found a similar prevalence of diabetes in both sexes, although it was higher among illiterates, urban residents, married people, and smokers. Participants aged 50-65 and those with Body Mass Index (BMI) 30 kg/m² or higher were more likely to be affected by diabetes [RR: 20.5 (18.1,23.3) and 3.2 (3.0,3.6)]. Hypertension [RR: 5.1 (4.7,5.5)], waist circumference (WC) equal or more than 90 cm [RR: 3.6 (3.3,3.9)], and family history [RR: 2.3 (2.2,2.5)] were also significantly associated with diabetes. For prediabetes, the main risk factors were age 50 to 65 years [RR: 2.6 (2.4,2.8)], BMI 30 kg/m² or higher [RR: 1.9 (1.8,2.0)], hypertension and WC of 90 cm or higher [RR: 1.7 (1.6,1.8)]. The adjusted relative risks for all variables were higher in females than males, with the exception of family history for both conditions and waist circumference for prediabetes.

CONCLUSIONS

Prediabetes and diabetes are prevalent in southwestern Iran. The major determinants are older age, obesity, and the presence of hypertension. Further interventions are required to escalate diabetes prevention and diagnosis in high-risk areas across Iran.

Phenotyping the Prediabetic Population-A Closer Look at Intermediate Glucose Status and Cardiovascular Disease

Even though the new thresholds for defining prediabetes have been around for more than ten years, there is still controversy surrounding the precise characterization of this intermediate glucose metabolism status. The risk of developing diabetes and macro and microvascular disease linked to prediabetes is well known. Still, the prediabetic population is far from being homogenous, and phenotyping it into less heterogeneous groups might prove useful for long-term risk assessment, follow-up, and primary prevention. Unfortunately, the current definition of prediabetes is quite rigid and disregards the underlying pathophysiologic mechanisms and their potential metabolic progression towards overt disease. In addition, prediabetes is commonly associated with a cluster of risk factors that worsen the prognosis. These risk factors all revolve around a common denominator: inflammation. This review focuses on identifying the population that needs to be screened for prediabetes and the already declared prediabetic patients who are at a higher risk of cardiovascular disease and require closer monitoring.

Different Curve Shapes of Fasting Glucose and Various Obesity-Related Indices by Diabetes and Sex

Fasting plasma glucose (FPG) and obesity-related indices are prognostic factors for adverse outcomes in both subjects with and without diabetes. A few studies have investigated sex differences in obesity indices related to the risk of diabetes, however no studies have compared the relationship between FPG and obesity-related indices by diabetes and sex. Therefore, in this study, we compared the curve shapes of FPG and various obesity-related indices by diabetes, and further explored sex differences in these associations. Data were derived from the Taiwan Biobank database, which included 5000 registered individuals. We used an adjusted generalized linear regression model and calculated the difference of least square means (Lsmean; standard error, SE) for males and females with and without diabetes. Associations between obesity-related indices and fasting glucose level by diabetes and sex groups were estimated, and the ORTHOREG procedure was used to construct B-splines. The post-fitting for linear models procedure was used to determine the range at which the trends separated significantly. The diabetes/sex/FPG interaction term was significant for all obesity-related indices, including body mass index, waist circumference, hip circumference, waist-to-hip ratio, waist-to-height ratio, lipid accumulation product, body roundness index, conicity index, body adiposity index and abdominal volume index. B-spline comparisons between males and females did not reach significance. However, FPG affected the trend towards obesity-related indices. As the fasting glucose level increased, the values of obesity-related indices varied more obviously in the participants without diabetes than in those with diabetes mellitus. The current study revealed that there was a different relationship between FPG and obesity-related indices by diabetes and sex. FPG affected the trend towards obesity-related indices more obviously in participants without diabetes than in those with diabetes. Further studies with a longitudinal design would provide a better understanding of the underlying mechanisms for the relationships.

Effect of nicotine exposure on the rate of orthodontic tooth movement: A meta-analysis based on animal studies

Background

Nicotine exposure has been reported to modify bone cell function and the osseous metabolism with potential effects on the rate of orthodontic tooth movement.

Objectives

To systematically investigate and quantitively synthesize the most recent available evidence from animal studies regarding the effect of nicotine exposure on the rate of orthodontic tooth movement.

Search methods

Unrestricted searches in 7 databases and hand searching were performed until July 2020 (PubMed, Central, Cochrane Database of Systematic Reviews, SCOPUS, Web of Science, Arab World Research Source, ProQuest Dissertations and Theses Global).

Selection criteria

We searched for controlled studies on healthy animals investigating the effect of nicotine on the rate of orthodontic tooth movement.

Data collection and analysis

Following study retrieval and selection, relevant data was extracted and the risk of bias was assessed using the SYRCLE’s Risk of Bias Tool. Exploratory synthesis and meta-regression were carried out using the random effects model.

Results

From the initially identified records, 5 articles meeting the inclusion criteria were selected and no specific concerns regarding bias were identified. Quantitative data synthesis showed that the rate of orthodontic tooth movement in the nicotine exposed rats was higher than in the control group animals (2 weeks of force application; 0.317 mm more movement in nicotine exposed rats; 95% Confidence Interval: 0.179–0.454; p = 0.000). No effect of the concentration or the duration force application was demonstrated following exploratory meta-regression.

Conclusion

Rats administered with nicotine showed accelerated rates of orthodontic tooth movement. Although, information from animal studies cannot be fully translated to human clinical scenarios, safe practice would suggest that the orthodontist should be able to identify patients exposed to nicotine and consider the possible implications for everyday clinical practice.

Impact of Work and Recreational Physical Activity on Prediabetes Condition among U.S. Adults: NHANES 2015-2016

More minutes of physical activity (PA) accumulated during a day are associated with a lower risk of diabetes mellitus type 2. However, it is less known if distinct dimensions of PA can produce a different protective effect in the prevention of prediabetes. The aim of this study was to analyze the impact of work and recreational PA on prediabetes among U.S. adults during the period 2015–2016 using the National Health and Nutrition Examination Survey (NHANES) database. Individuals (n = 4481) with hemoglobin A1c (HbA1c) test values of 5.7% to 6.4% were included. A logistic regression multivariate-adjusted analysis was conducted to estimate the association between the odds ratios (ORs) and 95% confidence intervals (CIs) of prediabetes, with work and recreational PA. The prevalence of prediabetes among U.S. adults was lower in physically active individuals both at work (~24%) and recreational (~21%) physical activities compared to individuals who were not physically active (27 to 30%). Individuals lacking practice of recreational PA had a high risk of prediabetes (OR = 1.26, 95% CI: 1.080 to 1.466). PA may be a protective factor for prediabetes conditions depending on gender, age, ethnic group, waist circumference, and thyroid disease.