Diabetes & Metabolic Syndrome: Clinical Research & Reviews

Clinical characteristics, types and complications of diabetes with young age at the onset (14 to 25 years). Age at the onset of diabetes, type of diabetes, family history, presence of osmotic symptoms and ketosis, BMI and complications like hypertension, nephropathy and neuropathy were noted.

The results of the study of the morphology of platelets in MS patients and control subjects were shown in Table 1: the composition of the main morphological forms of platelets in the blood plasma of patients with MS and control group, (M ± m).

Subjects Baseline and follow-up data were collected through comprehensive health examination from January 2002 to December 2009 at one comprehensive examination center of the hospital. Study subjects were male workers in semiconductor and electric appliance manufacturing company. They took follow-up examinations every year or every other year. Study subjects were limited to those who had no metabolic abnormalities in 2002 out of 15,347 male workers who received health examinations in 2002. Subjects who had any one of five components of metabolic syndrome (total 10,251, metabolic syndrome: 2,182) were excluded. hs-CRP and HOMA-IR are indicators reflecting inflammatory response and insulin resistance, respectively. Both of them are known as main mechanisms involved in the development of metabolic syndrome.[9] Thus, those who had blood hs-CRP concentration over 1.0 mg/L (n = 4,132) and those who had homeostasis model assessment-insulin resistance (HOMA-IR) over 2.5 (n = 2,181) [17] were also excluded. Based on self-reported questionnaire, subjects who reported a history of high blood pressure (n = 106), diabetes (n = 33), dyslipidemia (n = 125), cardiac disorder (n = 5), thyroid disease (n = 10), cancer (n = 27), asthma (n = 5), and immune disease (n = 2), or taking antibiotics, tetracycline, and steroidal drugs (n = 48) were also excluded. Subjects with missing crucial variables such as hs-CRP and HOMA-IR (n = 825) were also excluded. Hence, 3,748 subjects were designated as the study population for 2002. Out of these subjects, final analysis was conducted on 3,386 subjects after excluding 362 who were unable to be followed up before December 31, 2009 (Fig. 1). The study protocol was reviewed and approved by the Institutional Review Board of Kangbuk Samsung Hospital (KBC12052) where permitted an exemption for informed consent in this study.

Supplementary materials

Data for this study were originally collected as part of the Study of Urban Residents Eating-out Behavior (SUREB) (13), a cross-sectional community-based survey that has evaluated the dining-out behaviors and nutritional status of urban residents in Shanghai, China. Data were collected using cluster sampling from various districts of Shanghai between 2012 and 2014. A total of 1,032 participants, aged 18 to 74 years, were recruited to answer questionnaires that included self-reported demographic information, dining-out behaviors, and other lifestyle issues. Half of the participants were randomly selected to participate in further examinations, which included the collection of anthropometric measures and a fasting venous blood draw. In the present study, we only included those participants who had blood test results, and further excluded those with missing data for anthropometric measurements, for a final sample size of 508. Each participant answered a self-reported questionnaire, including age, gender, education level, total annual income, and lifestyle factors (i.e., cigarette smoking, alcohol use, sleep duration, appetite, and outdoor physical activity (PA)). Current smokers were defined as those who consume at least one cigarette per day. Alcohol use was classified as either “Yes” or “No” when asked if it was consumed on a daily basis. Sleep duration was calculated as the average self-reported sleep time for the previous three nights. The time spent performing outdoor PA (hours/week) were calculated as the product of mins/day of daily PA and weekly frequency (days/week) and then converted to hours/week. Participants arrived for their examination between 8:00 and 10:00 a.m. after an overnight fast. The participants were asked to wear light clothing and to void their bladders before measurements. Body height was measured barefoot using a stadiometer to the nearest 0.1 cm, and body mass was obtained to the nearest 0.1 kg using a digital scale. Waist circumference (WC) was measured using a plastic tape measure to the nearest 0.1 cm, and body mass index (BMI, kg/m2) was calculated as body mass (kg) divided by body height (m) squared. After sitting quietly for a minimum of 5 minutes, systolic and diastolic blood pressure (SBP and DBP, respectively) were measured on the left arm at heart level in a seated position using a standard mercurial sphygmomanometer. Venous blood samples were collected into vacuum test tubes and were sent to the clinical laboratory of Changhai Hospital within 30 minutes of blood draw. Blood glucose was determined enzymatically. Total cholesterol (TC), triglyceride (TG), and high- and low-density lipoprotein cholesterol (HDL-C and LDL-C) concentrations were determined using an automated enzymatic analyzer (Automatic Analyzer 7080, Hitachi, Tokyo, Japan). Finally, serum 25(OH)D concentrations were determined using enzyme immunoassays (human ELISA assay kit, Cayman chemical Co., USA).

Aims: The goal of this study was to determine insulin sensitivity in a fasted state and during an oral glucose tolerance test (OGTT), in normoglycemic (NGT), lean (L) (n=35) and, for comparison, overweight/obese (OW/O) (n=9) college-aged subjects. Material and Methods: Insulin sensitivity for 44 NGT, normotensive subject, age 18-26 yrs., was determined by homeostasis model assessment (HOMA-IR) and from Matsuda index (ISI Matsuda). Results: Subjects were normoglycemic fasted (4.59 + 0.35 mmol/L) and at two hours post OGTT 4.52+1.35 mmol/L).Besides anthropometric measures, there were significant differences between OW/O and L for fasting insulin (P<0.001) and both measures of insulin sensitivity (P<0.05). All subjects exhibited a 9-fold range in HOMA-IR (0.88 +0.51, range 0.3-2.7) and an 8-fold range in ISI Matsuda (11.9+4.7, range 3.0-24.2). The latter was inversely correlated with systolic blood pressure (r= 0.35, P=0.04) even though subjects were normotensive. In lean subjects, 2.3% were IR by HOMA-IR >2.1, 5.7% by ISI Matsuda<5.9, and 22.9% had >one criteria for metabolic syndrome (MetS); 28.6% had some negative metabolic biomarker. Conclusions: Insulin resistance is present in lean, NGT college-age subjects even without MetS criteria and is discernable with an easily applicable OGTT-derived index

This file contain the raw data upon collection. Further files can be provided, and files with spss format can be provided upon request.

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Participants A total of 203 patients with type 2 diabetes mellitus who attended nine primary care areas in four Cuban provinces belonging to different regions of the country (Pinar del Río, La Habana, Ciego de Ávila and Santiago de Cuba) participated in the study. Participants were selected by non-probabilistic sampling based on the following inclusion criteria: 1. have a diagnosis of type 2 DM according to the World Health Organization criteria, 2. be older than 18 years old, 3. be patients of the health care areas mentioned above, and 4. be willing to participate in the study and to sign the informed consent form. Patients with mental illness, cognitive deficit (dementia, psychosis or mental disability) or other apparent condition that prevents understanding and completion of the questionnaire were excluded. Although retrospective data on infection rates in diabetic patients suggest that people with type 1 DM are at higher risk for infectious diseases in general, and death rates are similar to those of people with type 2 DM,this study focused on the latterfortwo main reasons. First, patients with type 1 DM are mostly children and young people and the prevalence of this type of diabetes is lower compared to type 2 DM, which leads to a lower number of patients seen in consultation and primary health care. Second, the study was conducted in the context of the COVID-19 pandemic and patients with type 2 DM were the most accessible population to be surveyed by the research team in primary care areas. The minimum sample size was calculated with the Soper software package for a multiple regression study, according to the desired probability level (α=0.05), the number of predictors in the model (18 predictors), the anticipated effect size (f2=0.15) and the desired statistical power level (1- β=0.80). The software suggested a minimum number of 118 participants; however, the final number was higher than the minimum required. Instruments Socio-demographic and health information A questionnaire was developed specifically for this study, where participants were asked to provide information about their sex, age, educational level, type of work, cohabitation, marital status, presence of chronic complications, presence of comorbidities, family or friends infected with COVID-19, and time since diagnosis with DM. Concern about COVID-19 contagion We used the COVID-19 contagion concern scale (PRECOVID-19) originally developed for the general population, which assesses worry about becoming infected with COVID-19 and its impact on people’s mood and ability to perform daily activities. In this study we used the version validated for Cuban patients with diabetes, which consists of 5 items. All items have 4 Likert-type response options, ranging from 1=never or rarely to 4=almost all the time. The PRE-COVID-19 has a unidimensional structure, where the total score is calculated by adding the scores of each of the 5 items. Higher scores indicate greater concern about becoming infected with COVID19. The reliability of the PRE-COVID-19 for this study was very good (ω=0.91). Blood glucose level Fasting blood glucose values were obtained from the patients’ clinical histories and from blood tests performed in the last three months in laboratories equipped for this purpose. Based on this, poor glycemic control was determined as fasting blood glucose greaterthan or equal to 7 mmol/L (126 mg/dl) in the last three months and good control as figures below this value. The criterion based on glycosylated hemoglobin (HbA1c) could not be used because it is not a test regularly available in the primary health care system where the survey was applied. Other control criteria using continuous glucose monitoring systems were not possible either, as they are not generally available for patients with DM living in Cuba. Procedure The questionnaire was applied by properly trained researchers, who complied with strict COVID-19 prevention health protocols, between the months of January and April 2021. The questionnaire was administered during patients’ visits to primary care centers or in their homes. During this period of time, the fight against COVID-19 in Cuba suffered some setbacks, characterized by an increase in the number of infected people, even higherthan that observed during the first stage of the disease, in 2020. Thus, during those dates, more than 64,414 positive diagnoses and 384 deaths were reported in the country. Participation was voluntary and without any financial compensation. Participants signed the informed consent form and were informed that they could withdraw from the study at any time. Similarly, the reliability of the data was guaranteed. The study protocol was approved by the Ethics Committee of theUniversidad Privada delNorte in Peru (registration number: 20213002). Data Analysis The frequencies and percentages of the categorical variables included in the model were examined. In the case of the outcome variable (concern about COVID-19 contagion), the mean±standard deviation (SD) was calculated for the total sample. These values were then also calculated for each category of each variable. For inferential purposes, bivariate associations were examined with a series of analyses of variance (ANOVA). The assumption of homoscedasticity was reasonably well met in most cases; however, a possible noncompliance with the assumption of normality of the residuals was observed. Therefore, we repeated the analyses after a power transformation of the outcome variable. Since the results were practically identical with both procedures, only those obtained with the variable in its original form are reported. Variables that reached statistical significance (p<.05) in the ANOVAs were selected as potential predictors in a linear regression. Crude (simple) regressions were run, which replicated the ANOVAs but also allowed for a more detailed examination of between-group differences. Finally, a fitted (multiple) regression was run with all predictors simultaneously. Statistical significance was judged from the 95% CIs, which provide a set of possible values of the coefficient in the population. A CI that does not include zero is equivalent to a p<.05.

This capsule contains the code for reproducing the result of the paper entitled "Joint analysis of fasting and postprandial plasma glucose and insulin concentrations in Venezuelan women." published in Diabetes & Metabolic Syndrome: Clinical Research & Reviews.