Risk Factors For Diabetes Mellitus Research Articles

Advanced maternal age is a risk factor for both early and late gestational diabetes mellitus: The Japan Environment and Children's Study.

This study investigated the association between maternal age and early and late gestational diabetes mellitus (GDM). In total, 72,270 pregnant women were included in this prospective birth cohort study. Associations between maternal age and early GDM (diagnosed at <24 gestational weeks) and late GDM (diagnosed at ≥24 gestational weeks) were evaluated using a multinomial logistic regression model with possible confounding factors. The reference category was maternal age of 30-34.9 years. Higher maternal age was associated with higher odds of early and late GDM (P-value for trend <0.0001 and <0.0001, respectively). The adjusted odds ratios (aORs) for early GDM with maternal age of 35-39.9 years and ≥40 were 1.399 (95% confidence interval [CI]: 1.134-1.725) and 2.494 (95% CI: 1.828-3.402), respectively. The aORs for late GDM with maternal age of 35-39 years and ≥40 were 1.603 (95% CI: 1.384-1.857) and 2.276 (95% CI: 1.798-2.881), respectively. Higher maternal age was associated with an increased risk of GDM regardless of when GDM was diagnosed. The association between maternal age and early GDM was similar to that between maternal age and late GDM.

Correlation between microRNA-21 expression and overweight/obesity.

Obesity and overweight are chronic conditions characterized by excessive adiposity that negatively impact health. They are among the most significant risk factors for respiratory failure, diabetes mellitus, cardiovascular disease, and hypertension. Genetic factors may contribute to some of these conditions, but they are mainly associated with the lifestyle in the majority. However, neither genetics nor lifestyle can fully explain all cases. Recent studies have proven that microRNA-21 causes the systemic hypertension, many cardiac pathologies, and some cancers. MicroRNA-21 is viewed as an important future biomarker for many critical conditions. We explored the role of microRNA-21 in the causation of overweight and obesity. There is conflicting data about this association in the literature. Determining if there is an association may help us in better understanding and managing this condition.

Gestational Diabetes Mellitus Prevalence and Risk Factors - A Study from a Tertiary Care Centre in North India

Introduction: Type 2 diabetes mellitus (T2DM) and gestational diabetes mellitus (GDM) pose significant global health challenges. The increasing global prevalence of GDM and its associated complications underscores the need for proactive screening and management. The study aimed to evaluate the prevalence of GDM and its associated risk factors in a tertiary care hospital in North India Methodology: A prospective cross-sectional study conducted at Max Super Speciality Hospital, New Delhi, during 2016-2017, enrolled 900 pregnant women (aged 18-50 years) from the antenatal outpatient department (OPD). Primary objective: To assess impaired oral glucose tolerance prevalence (IADPSG criteria) at 24th-28th weeks. The data covered demographic, socioeconomic, obstetric, and medical details. Descriptive statistics were used to summarize the variables. Chi-square or Fisher's tests were applied to categorical data, while continuous data were analysed using independent t-tests. Multiple regression analysis was conducted to identify risk factors. Results: GDM was diagnosed in 7.4% of participants. Prevalence was highest in the age group &gt;35 years (36.2%, p=0.000), and a significant association was found between increasing body mass index (BMI) and GDM (p=0.04). Adverse obstetric history, including previous abortions and GDM in prior pregnancies, increased the risk of GDM. Complications during pregnancy, such as macrosomia (present in 1 patient with GDM and none in non-GDM), foetal distress (9.09% in GDM), and preeclampsia (4.7% in GDM), were higher in women with GDM. Vaginal delivery prevalence was higher in non-GDM, while GDM had a higher rate of caesarean section delivery (p&lt;0.005). Conclusion: The study discloses a 7.4% GDM prevalence in North Indian tertiary care, accentuating rising diabetes trends. Identified risk factors inform antenatal screening, highlighting the need for early GDM management to mitigate complications and prevent future diabetes. Single-centre limitations emphasise the necessity for broader population studies for accurate prevalence rates.

Impact of Gestational Diabetes Mellitus on Neonatal Birth Outcomes.

Aims/Background The purpose of this study is to investigate the risk factors for gestational diabetes mellitus (GDM) during pregnancy and its impact on neonatal birth outcomes. Methods A total of 2010 cases of mothers with GDM who underwent routine prenatal examinations and delivered at The Fourth Hospital of Shijiazhuang from June 2021 to April 2022, and their newborns were selected as the GDM group. For comparison, 2087 cases of mothers with normal glucose tolerance (NGT) and their newborns during the same period were selected as the NGT group. Birth outcomes of both groups were compared. Results Pregnant women in the GDM group exhibited significantly higher proportions of advanced age, higher body mass index (BMI), and irregular dietary habits compared to the NGT group (p < 0.05). Conversely, the GDM group had significantly lower proportions of nutrient supplementation and prenatal exercise compared to the NGT group (p < 0.05). The incidences of macrosomia, neonatal hypoglycemia, hyperbilirubinemia, and acute respiratory distress syndrome (ARDS) were significantly higher in the GDM group compared to the NGT group (p < 0.05 for all). Among GDM women with adverse outcomes, significant differences were observed in pre-pregnancy BMI, insufficient or excessive weight gain during pregnancy, and poor glycemic control during pregnancy compared to those without adverse outcomes (p < 0.05 for all). Poor glycemic control during pregnancy, pre-pregnancy BMI, and inadequate or excessive weight gain were significant factors influencing adverse pregnancy outcomes in GDM patients (p < 0.05). Conclusion The risk factors for GDM include advanced maternal age, being underweight, overweight, or obese prior to pregnancy, irregular eating habits, dietary nutritional deficiencies, and lack of prenatal exercise. The incidence of adverse pregnancy outcomes is higher in GDM patients compared to those without GDM. Poor glycemic control during pregnancy and higher pre-pregnancy BMI are significant factors that contribute to negative outcomes for both GDM patients and their newborns.

Risk Factors Analysis of Diabetes Prevalence in Wetland Area: A Study from Borneo Wetland Study on Diabetes

Background: National Basic Health Survey held by the Ministry of Health Republic of Indonesia shows the prevalence of Diabetes Mellitus increased from 6.9% to 8.5% in 2018. Wetland is an area covered by shallow water on the surface, which represents a unique ecosystem. Aim: This study investigated the association between various risk factors and DM prevalence in South Kalimantan Wetlands, Indonesia. Early identification and management of risk factors may prevent progression into diabetes mellitus. Methods: We conducted the Borneo Wetland Study on Diabetes (Best-Diab 1) with a cross-sectional study approach using the latest health survey data conducted by the South Kalimantan Provincial Health Office from the primary health center visit from January 2020 to March 2022. Using Proportionate Random Sampling, we divided samples into two groups; 6.010 in the DM group, and 6.010 non DM group. Results: Gender, age, BMI, blood pressure, and blood glucose level were significantly correlated with diabetes mellitus prevalence (p&lt;0.001). Family history of DM surprisingly has a significant impact on DM prevalence (PR, 3.16; 95% CI, 2.80-3.57, p&lt;0.001). The prevalence of DM in the smoking group was 0.78 times less than in non-smoking individuals (PR, 0.78; 95% CI, 0.74-0.82; p&lt;0.001). Excess sugar was the greatest risk factor for diabetes mellitus, with the prevalence of DM 4.72 times greater than normal sugar intake (PR, 4.72; 95% CI, 4.29-5.2; p&lt;0.001). Excess salt intake also seemed to be a significant risk factor among DM patients (PR, 1.24; 95% CI, 1.17-1.30, p&lt;0.001. Conclusion: Females, older age, higher BMI, and family history of DM were significant risk factors for diabetes mellitus prevalence in this study. Further studies are needed to determine how those factors impacted diabetes mellitus. Keywords: risk factors, prevalence, diabetes mellitus, wetland, South Kalimantan

Evaluation of laboratory findings indicating pancreatitis in healthy lean, obese, and diabetic cats.

Obesity is a risk factor for diabetes mellitus, which commonly coexists with pancreatitis in cats. However, obesity has not previously been associated with pancreatitis in cats. To evaluate factors affecting serum concentrations of pancreatic lipase immunoreactivity (fPLI), trypsin-like immunoreactivity (fTLI), cobalamin and folate in clinically healthy lean, overweight and obese, or diabetic cats. Seventy-nine client-owned cats (27 healthy lean [LN, BCS 4-5/9], 30 healthy overweight and obese [OW, BCS 7-9/9], and 22 diabetic [DM]) were included. Cross-sectional study. The cats underwent physical examination, and blood tests. Linear regression models compared differences in fPLI, fTLI, cobalamin, and folate concentrations. Fisher's exact test assessed the proportions of cats with fPLI and fTLI indicative of pancreatitis, and hypocobalaminemia. A random forest algorithm identified explanatory variables for cats having fPLI levels indicative of pancreatitis. No LN cats, while 6/30 (20%) of OW and 10/22 (45%) of DM cats had fPLI concentrations indicative of pancreatitis. Body condition score (P = .02) and body weight (P = .002) were positively associated with fPLI levels in LN and OW cats. Higher fPLI, and lower cobalamin concentrations were associated with higher age across groups. Body condition score and body weight were associated with higher fPLI levels in nondiabetic cats. A larger proportion of OW and DM cats had fPLI concentrations indicative of pancreatitis compared to LN cats. Whether this indicates subclinical pancreatitis remains to be determined. Hypocobalaminemia was less frequent in OW compared to DM cats.

Examining childhood and adulthood stressors as risk factors for gestational diabetes mellitus in working pregnant individuals: A prospective cohort study

AimsThis study aimed to examine the individual and joint associations of adverse childhood experiences (ACEs) and maternal work and non-work related stressors with the risk of gestational diabetes mellitus (GDM). MethodsWorking pregnant individuals (n = 1163) from a United States (U.S.) prospective cohort conducted in South Carolina between 2016 and 2021 were included in the study. ACEs were assessed at study enrollment before 20 gestational weeks (GW), while maternal stressors were assessed in late pregnancy and GDM diagnosis occurred between 24 and 30 GW. Multivariable logistic regressions were performed to assess associations of ACEs and maternal stressors with GDM. ResultsChildhood abuse, an ACE subdomain, was associated with an elevated but statistically insignificant risk of GDM (adjusted OR = 1.47; 95 % CI: 0.85–2.53). Only maternal work stressors were associated with an increased risk of GDM (adjusted OR = 2.11; 95 % CI: 1.17–3.79) and the association became much stronger among those with childhood abuse experiences (adjusted OR = 3.80; 95 % CI:1.68–8.60). ConclusionAmong U.S. working pregnant individuals, having work stressors during pregnancy was associated with an elevated risk of developing GDM, particularly among those who had childhood experience of abuse.

Analysis of Risk Factors and Development and Validation of a Dynamic Nomogram for Postherpetic Neuralgia: A Retrospective Study.

Postherpetic Neuralgia (PHN), recognized as the most common complication of Herpes Zoster, is experiencing an increasing trend in its occurrence. The goal of this study was to identify the independent risk factors for PHN and create a dynamic nomogram using routine clinical characteristics to predict PHN in patients with herpes zoster, for early identification and prevention of PHN. A total of 2420 patients were retrospectively reviewed and divided into training (n=1696) and validation (n=724) cohort using a 7:3 random allocation. Univariable, LASSO and multivariable logistic regression analysis was performed to identified independent risk factors for PHN. A dynamic nomogram was assessed through the area under the receiver operating characteristic curve (AUC), calibration curves and Hosmer-Lemeshow test. The decision curve analysis (DCA) was used to evaluate its clinical validity. Multivariable logistic regression identified several independent risk factors for PHN, including age, female, diabetes mellitus, malignant tumors, and connective tissue diseases. The area under the curve was 0.698 (95% CI, 0.666-0.730) for training cohort and 0.713 (95% CI, 0.663-0.763) for the validation cohort. Calibration curve revealed a moderate consistency between actual observation and prediction. Decision curve analysis showed a risk threshold of 16% and demonstrated a clinically effective predictive model. We have developed a user-friendly dynamic nomogram to predict PHN in patients with herpes zoster, which can assist in early identification and prevention of PHN.

The incidence and risk factors of post-transplant diabetes mellitus in living donor kidney transplantation patients: a retrospective study

BackgroundPost-transplant diabetes mellitus (PTDM) is a well-known complication of kidney transplantation that significantly impacts recipient morbidity and mortality. Over the recent years, the incidence of PTDM has increased considerably worldwide. Therefore, the primary purpose of this study was to evaluate the incidence and risk factors for PTDM in living donor kidney transplantation patients in Riyadh, Saudi Arabia.MethodsA retrospective cohort study was conducted at a tertiary transplant center in Riyadh, Saudi Arabia, and data were extracted between February 2016 and March 2022. Patients aged ≥ 18 years who underwent renal transplant with at least one year of post-transplant follow-up were included in the analysis, and their medical records were comprehensively reviewed. Patients < 18 years of age, history of diabetes mellitus, other organ transplants, or those who underwent transplantation outside the Kingdom of Saudi Arabia were excluded from the study.ResultsThe study included 247 living donor kidney transplant patients, with a mean age of 39.5 ± 14.6 years. 17.0% of the patients were diagnosed with PTDM. Patient age and fasting glucose levels at 6-months and 12-months after transplantation were found to be significant risk factors for the development of PTDM.ConclusionAn increased occurrence of PTDM emphasizes the importance of identifying high-risk patients prior to transplantation and implementing early interventions to prevent potential complications that could affect graft and patient survival.

Development of a Diabetes Dietary Quality Index: Reproducibility and Associations with Measures of Insulin Resistance, Beta Cell Function, and Hyperglycemia.

Various dietary risk factors for type 2 diabetes have been identified. A short assessment of dietary patterns related to the risk for type 2 diabetes mellitus may be relevant in clinical practice given the largely preventable nature of the disease. The aim of this study was to investigate the reproducibility of a short food frequency questionnaire based on available knowledge of diabetes-related healthy diets. In addition, we aimed to investigate whether a Diabetes Dietary Quality Index based on this questionnaire was related to metabolic risk factors, including measures of beta cell function and insulin sensitivity. A short food frequency questionnaire was composed by selecting fourteen questions (representing eight dietary factors) from existing food frequency questionnaires on the basis of their reported relationship with diabetes risk. Healthy participants (N = 176) from a Dutch family study completed the questionnaire and a subgroup (N = 123) completed the questionnaire twice. Reproducible items from the short questionnaire were combined into an index. The association between the Diabetes Dietary Quality index and metabolic risk factors was investigated using multiple linear regression analysis. Measures of beta cell function and insulin sensitivity were derived from a mixed meal test and an euglycemic-hyperinsulinemic and modified hyperglycemic clamp test. Our results show that this new short food frequency questionnaire is reliable (Intraclass Correlations ranged between 0.5 and 0.9). A higher Diabetes Dietary Quality index score was associated with lower 2 h post-meal glucose (β -0.02, SE 0.006, p < 0.05), HbA1c (β -0.07, SE 0.02, p < 0.05), total cholesterol, (β -0.02, SE 0.07, p < 0.05), LDL cholesterol, (β -0.19, SE 0.07, p < 0.05), fasting (β -0.4, SE 0.16, p < 0.05) and post-load insulin, (β -3.9, SE 1.40, p < 0.05) concentrations and the incremental AUC of glucose during MMT (β -1.9, SE 0.97, p < 0.05). The scores obtained for the oral glucose insulin sensitivity-derived mixed meal test were higher in subjects who scored higher on the Diabetes Dietary Quality index (β 0.89, 0.39, p < 0.05). In contrast, we found no significant associations between the Diabetes Dietary Quality index and clamp measures of beta cell function. We identified a questionnaire-derived Diabetes Dietary Quality index that was reproducible and inversely associated with a number of type 2 diabetes mellitus and metabolic risk factors, like 2 h post-meal glucose, Hba1c and LDL, and total cholesterol. Once relative validity has been established, the Diabetes Dietary Quality index could be used by health care professionals to identify individuals with diets adversely related to development of type 2 diabetes.

The Influence of Physical Activity and Diet Mobile Apps on Cardiovascular Disease Risk Factors: Meta-Review.

The literature on whether physical activity (PA) and PA and diet (PA+Diet) mobile apps improve cardiovascular disease (CVD) risk factors is promising. The aim of this meta-review is to provide an evidence synthesis of systematic reviews and meta-analyses examining the influence of PA and PA+Diet apps on the major CVD risk factors. We systematically searched 5 databases until January 12, 2022. Included systematic reviews and meta-analyses (1) reported the CVD risk factor outcomes of BMI, waist circumference, body weight, blood pressure (BP), hemoglobin A1c (HbA1c), fasting blood glucose, blood lipids, or PA; (2) enrolled healthy participants ≥18 years who may or may not have the metabolic syndrome, diabetes mellitus, or preexisting CVD risk factors; (3) reviewed PA or PA+Diet app interventions integrating behavioral change techniques (BCT) to deliver their information; and (4) had a nonapp control. In total, 17 reviews (9 systematic reviews and 8 meta-analyses) published between 2012 and 2021 qualified. Participants were middle-aged, mostly women ranging in number from 10 to 62,219. Interventions lasted from 1 to 24 months, with the most common behavioral strategies being personalized feedback (n=8), self-monitoring (n=7), and goal setting (n=5). Of the PA app systematic reviews (N=4), the following CVD risk factors improved: body weight and BMI (n=2, 50%), BP (n=1, 25%), HbA1c (n=1, 25%), and blood lipids (n=1, 25%) decreased, while PA (n=4, 100%) increased. Of the PA+Diet app systematic reviews (N=5), the following CVD risk factors improved: body weight and BMI (n=3, 60%), BP (n=1, 20%), and HbA1c (n=3, 60%) decreased, while PA (n=3, 60%) increased. Of the PA app meta-analyses (N=1), the following CVD risk factors improved: body weight decreased (-0.73 kg, 95% CI -1.45 to -0.01; P=.05) and PA increased by 25 minutes/week (95% CI 0.58-1.68; P<.001), while BMI (-0.09 kg/m2, 95% CI -0.29 to 0.10; P=.35) and waist circumference (-1.92 cm, 95% CI -3.94 to 0.09; P=.06) tended to decrease. Of the PA+Diet app meta-analyses (n=4), the following CVD risk factors improved: body weight (n=4, 100%; from -1.79 kg 95% CI -3.17 to -0.41; P=.01 to -2.80 kg 95% CI -4.54 to -1.06, P=.002), BMI (n=1, 25%; -0.64 kg/m2, 95% CI -1.09 to -0.18; P=.01), waist circumference (n=1, 25%; -2.46 cm, 95% CI -4.56 to -0.36; P=.02), systolic/diastolic BP (n=1, 25%; -4.22/-2.87 mm Hg, 95% CI -6.54 to -1.91/ -4.44 to -1.29; P<.01), and HbA1c (n=1, 25%; -0.43%, 95% CI -0.68 to -0.19; P<.001) decreased. PA and PA+Diet apps appear to be most consistent in improving PA and anthropometric measures with favorable but less consistent effects on other CVD risk factors. Future studies are needed that directly compare and better quantify the effects of PA and PA+Diet apps on CVD risk factors. PROSPERO CRD42023392359; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=392359.

Diabetes Risk Factors in People With HIV Receiving Pitavastatin Versus Placebo for Cardiovascular Disease Prevention : A Randomized Trial.

REPRIEVE (Randomized Trial to Prevent Vascular Events in HIV) led to new guidelines for statin use among people with HIV (PWH) with low to moderate risk for atherosclerotic cardiovascular disease (ASCVD). Little is known about the natural history of diabetes mellitus (DM) or mechanisms contributing to statin effects on DM among this population. To determine the contribution of known DM risk factors to excess risk for DM with pitavastatin in REPRIEVE. Phase 3, primary ASCVD prevention trial over a median of 5.6 years of follow-up. (ClinicalTrials.gov: NCT02344290). Global, multicenter trial. 7731 PWH aged 40 to 75 years with low to moderate ASCVD risk (by the pooled cohort equations from the American College of Cardiology and American Heart Association) without DM at study entry. Random 1:1 assignment to pitavastatin, 4 mg daily, or placebo. New-onset DM was determined at each visit by clinical diagnosis requiring initiation of medication treatment for DM. The incidence of new-onset DM was assessed in relation to predefined demographic and metabolic risk factors, stratified by treatment group. Treatment effects of pitavastatin on progression to new DM in key subgroups were determined. Participants with at least 3 DM risk factors (vs. no risk factors) had increased risk for DM in each treatment group (incidence rate, 3.24 per 100 person-years [PY] vs. 0.34 per 100 PY [pitavastatin] and 2.66 per 100 PY vs. 0.27 per 100 PY [placebo]). The incidence of DM was highest in South Asia. In adjusted analyses, high body mass index, prediabetes, and metabolic syndrome components were strongly associated with new-onset DM (all P < 0.005). Pitavastatin was the only statin assessed; DM was assessed clinically. Metabolic risk factors, including prediabetes and obesity, contributed to new-onset DM in statin- and placebo-treated participants. A clinically significant effect of pitavastatin on DM was seen primarily among those with multiple risk factors for DM at entry. Strategies targeting key metabolic risk factors, like obesity and prediabetes, may help protect against DM among PWH. National Heart, Lung, and Blood Institute of the National Institutes of Health.

National burden and risk factors of diabetes mellitus in China from 1990 to 2021: Results from the Global Burden of Disease study 2021.

In recent years, the prevalence and mortality rates of diabetes have been rising continuously, posing a significant threat to public health and placing a heavy burden on the population. This study was conducted to describe and analyze the burden of diabetes in China from 1990 to 2021 and its attributable risk factors. Utilizing data from the Global Burden of Disease Study 2021, we analyzed the incidence, prevalence, and disability-adjusted life years (DALYs) of type 1 diabetes (T1DM) and type 2 diabetes (T2DM) in China from 1990 to 2021. We extracted sex- and age-specific data on diabetes, focusing on DALYs, years lived with disability, and years of life lost. Bayesian meta-regression and spatiotemporal Gaussian process regression were used to estimate disease parameters. Age-standardized rates (ASRs) and estimated annual percentage changes (EAPC) were calculated using direct standardization and log-linear regression. The population-attributable fractions were also determined for each risk factor. In 2021, the absolute number of incident diabetes mellitus (DM) cases was estimated at 4003543.82, including 32 000 T1DM and 3971486.24 T2DM cases. The ASRs were 244.57 for DM, 2.67 for T1DM, and 241.9 for T2DM (per 100 000 population). The absolute number of prevalent DM cases was 117288553.93, including 1442775.09 T1DM and 115845778.84 T2DM cases. The ASRs were 6142.29 for DM, 86.78 for T1DM, and 6055.51 for T2DM (per 100 000 population). In 2021, there were 178475.73 deaths caused by DM, with an ASR of mortality of 8.98 per 100 000 population. The DALYs due to DM in 2021 were 11713613.86, with an ASR of 585.43 per 100 000 population and an EAPC of 0.57. This increase can be attributed to several factors, including high body mass index, air pollution, and dietary habits. The burden of diabetes is considerable, with high prevalence and incidence rates, highlighting the urgent need for public health interventions. Addressing factors like high fasting plasma glucose, body mass index, air pollution, and dietary risks through effective interventions is critical.

Impact of lead and nickel contamination on metabolic health: Associations with diabetes mellitus in a pakistani cohort

Environmental exposure to heavy metals, particularly lead (Pb) and nickel (Ni), is implicated in chronic metabolic diseases, including diabetes mellitus (DM). This cross-sectional study assessed the Pb and Ni levels in groundwater using ICP-OES and urine samples collected from 2688 participants using ICP-MS. We aimed to establish the associations between Pb and Ni exposure and risk factors for DM and metabolic disorders. Groundwater analysis revealed the elevated levels of total dissolved solids, electrical conductivity, hardness, turbidity, Ni, and Pb, exceeding the WHO guidelines. The mean concentration of Pb in groundwater samples of study area was 0.025 mg/L which was higher than the WHO permissible limit of 0.01 mg/L. Similarly the mean concentration of Ni in groundwater samples of study area was 0.038 mg/L which was also higher than the WHO permissible limit of 0.02 mg/L. In human study, participants, categorized into Pb-detected and Ni-detected groups, exhibited significantly higher Pb and Ni levels and non-exposed non-diabetic groups. Ni-detected diabetics showed elevated Ni levels compared to non-exposed non-diabetics. Similarly, Pb-detected diabetics showed elevated Pb levels compared to non-exposed non-diabetics. These findings suggest a potential contribution of Pb and Ni exposure to DM development. The study also identified associations between heavy metal exposure and disruptions in various biomarkers related to DM, lipid profile, inflammation, oxidative stress, liver function, and kidney function. Pb-detected diabetics demonstrated elevated levels of glycemic index biomarkers, including fasting blood glucose (P < 0.0001) and HbA1c (P < 0.0001). Ni-detected diabetics exhibited increased inflammatory markers, such as CRP (P < 0.0001) and IL-6 (P < 0.0001). Both Pb and Ni exposure were associated with dyslipidemia, as indicated by elevated levels of total cholesterol (P < 0.0001) and LDL (P < 0.0001). Additionally, heavy metal exposure was linked to impaired liver and kidney function, supported by elevated levels of AST (P < 0.0001), ALT (P < 0.0001), creatinine (P < 0.0001), and blood urea nitrogen (P < 0.0001), with Pb exposure also associated with higher levels of MDA (P < 0.0001). Correlation analyses demonstrated significant associations between urinary Pb and Ni concentrations and various biomarkers related to DM and metabolic disorders. In conclusion, this study provides substantial evidence linking Pb and Ni exposure to the development of DM and metabolic disorders in a Pakistani population, emphasizing the need for strict regulations and preventive measures to reduce heavy metal contamination and safeguard public health. Future longitudinal studies and interventions are warranted to elucidate mechanistic links between heavy metal exposure and metabolic diseases.

Risk factors for post-acute pancreatitis diabetes mellitus: A systematic review and meta-analysis

Risk factors for post-acute pancreatitis diabetes mellitus: A systematic review and meta-analysis

Elevated risk of pre-diabetes and diabetes in people with past history of COVID-19 in northeastern Nigeria

BackgroundAn increased risk of diabetes mellitus (DM) after COVID-19 has been reported in the United States, Europe, and Asia. The burden of COVID-related DM has yet to be described in Africa, where the overall risk of DM has been increasing rapidly. Our objective was to compare the prevalence of pre-DM and DM in Nigerian individuals with a history of COVID-19 to individuals without known COVID-19 infection.MethodsWe undertook a retrospective cohort study with 256 individuals with a past medical history of COVID-19 with no history of pre-DM or DM and 256 individuals without a history of COVID-19 or pre-DM/DM. Participants were categorized as pre-DM (fasting capillary glucose 100–125 mg/dL) or DM (fasting capillary glucose ≥ 126 mg/dL). We employed univariate and multivariable logistic regression to identify key predictors and adjust for confounders related to hyperglycaemia risk factors. Additionally, we used multinomial logistic regression to analyze the relationship between COVID-19 history and diabetes status, distinguishing between normal, pre-diabetic, and diabetic glucose levels. All models were adjusted for age, gender, hypertension, physical activity, central adiposity, and family history of DM.ResultsCompared to the control group, those with a history of COVID-19 had a similar median age (38 vs. 40 years, p = 0.84), had a higher proportion of men (63% vs. 49%), and had a lower prevalence of central adiposity (waist: hip ratio ≥ 0.90 for males and WHR ≥ 0.85 for females) (48% vs. 56.3%, p = 0.06). Of the 256 with a history of COVID-19, 44 (17%) required in-patient care. The median (interquartile range) time interval between COVID-19 diagnosis and the glycaemic assessment was 19 (IQR: 14, 24) months. Pre-DM prevalence was 27% in the post-COVID-19 group and 4% in the control group, whereas the prevalence of DM was 7% in the post-COVID-19 group and 2% in the control group. After multivariable adjustment, the odds of pre-DM were 8.12 (95% confidence interval (CI): 3.98, 16.58; p < 0.001) higher, and the odds of DM were 3.97 (95% CI: 1.16, 13.63) higher in those with a history of COVID-19 compared to controls. In the adjusted multinomial logistic regression analysis, individuals with a history of COVID-19 exhibited significantly elevated risks for pre-diabetes (RRR = 7.55, 95% CI: 3.76–15.17) and diabetes (RRR = 3.44, 95% CI: 1.01–11.71) compared to those without COVID-19.ConclusionPrevious COVID-19 was found to be a risk factor for prevalent pre-diabetes and diabetes mellitus in Nigeria. More intensive screening for DM in those with a history of COVID-19 should be considered.

Perioperative glucose monitoring with continuous glucose monitors identifies risk factors for post-transplant diabetes mellitus in kidney transplant recipients

Post-transplantation diabetes mellitus (PTDM) negatively affects graft and patient survival after kidney transplantation (KT). This prospective study used continuous glucose monitoring (CGM) to evaluate perioperative blood glucose dynamics, identify PTDM risk factors, and compare predictive accuracy with capillary blood glucose monitoring (CBGM) in 60 non-diabetic living-donor KT recipients. Patients underwent 2-week pre- and postoperative CGM, including routine CBGM during their in-hospital stays. PTDM-related risk factors and glucose profiles were analyzed with postoperative CGM and CBG. PTDM developed in 14 (23.3%) patients and was associated with older age, male sex, higher baseline HbA1c, high-density lipoprotein cholesterol, and 3-month cumulative tacrolimus exposure levels. Male sex and postoperative time above the range (TAR) of 180 mg/dL by CGM were PTDM-related risk factors in the multivariate analysis. For predictive power, the CGM model with postoperative glucose profiles exhibited higher accuracy compared with the CBGM model (areas under the curves of 0.916, and 0.865, respectively). Therefore, we found that male patients with a higher postoperative TAR of 180 mg/dL have an increased risk of PTDM. Postoperative CGM provides detailed glucose dynamics and demonstrates superior predictive potential for PTDM than CBGM.

Investigating the effects of percutaneous endovascular aneurysm repair for abdominal aortic aneurysm on the lumen size of the common femoral artery

BackgroundPercutaneous endovascular aneurysm repair (PEVAR) is the definitive therapy of choice for abdominal aortic aneurysms worldwide. However, current literature regarding the anatomic changes in the common femoral artery (CFA) post-PEVAR is sparse and contradictory, and a significant proportion of these studies did not control for the potential confounding effects of ethnicity. Thus, this study aims to investigate the anatomical effects of PEVAR on the CFA using an Asian study cohort.MethodsBetween January 2019 and September 2023, the records of 113 patients who received PEVAR were reviewed. Groins with previous surgical interventions were excluded. The most proximate pre- and postoperative CT angiography of patients receiving PEVAR via the Perclose ProGlide™ Suture-Mediated Closure System were retrospectively analysed for changes in both the CFA inner luminal diameter (ID) and outer diameter (OD), the latter also encompassing the arterial walls. Access site complications within 3 months post-PEVAR were also recorded per patient.ResultsOne hundred seventeen groins from 60 patients were included in this study, with 1 report of pseudoaneurysm. The CFA ID exhibited a 0.167 mm decrease (p-value = 0.0403), while the OD decreased by 0.247 mm (p-value = 0.0107). This trend persisted when the data was separately analysed with the common cardiovascular risk factors of diabetes mellitus, hypertension and hyperlipidaemia.ConclusionOur analysis demonstrated a statistically significant decrease in the CFA diameters post-PEVAR. However, the percentage changes were below established flow-limiting values, as reflected by the single access site complication reported. Hence, our findings give confidence in the safety profile of this procedure, even with the reported smaller baseline CFA lumen size in Asians. Moving forward, similar longer-term studies should be considered to characterise any late postoperative effects.Graphical

Exploring the link between leptin levels and metabolic syndrome in elderly Indian patients: Implications for family medicine and primary care practices.

The metabolic syndrome (MetS), according to the Adult Treatment Panel III of the National Cholesterol Education Programme, is a collection of metabolic abnormalities that includes one, two, or all three of the following traits: obesity in the abdomen, dyslipidemia, hypertension, fasting blood sugar, or insulin resistance. This study's aim was to assess the relationship between fasting serum leptin and MetS in elderly adults with T2DM in the Northern Indian population. The following information was collected from all the participants: (1) anthropometric data, (2) biochemical data, and (3) a lifestyle questionnaire on sociodemographic data, dietary practices, smoking, and alcohol intake to identify their risk factors for diabetes mellitus, CVD, and hypertension. A total of 36 older participants (56.30%) had a history of hypertension, while 29 elderly participants (44.61%) had diabetes mellitus. A total of 32 elderly participants (49.2%) had MetS, and this group had higher serum leptin (P 0.003), body weight (P = 0.019), BMI (P 0.001), waist circumference (P 0.001), CRP (P = 0.021), insulin (P = 0.001), and HOMA-IR (P = 0.003) values as well as higher percentages of females (P = 0.001), and those with type 2 diabetes mellitus (P = 0.002) and hypertension (P = 0.039) than those in the non-MetS group. In older persons with T2DM, our study discovered a favorable correlation between serum leptin and MetS. It can act as a standalone indicator of MetS, offering a way to spot populations at risk for associated consequences and enabling early intervention.

Weight Change After Cancer Diagnosis and Risk of Diabetes Mellitus: A Population-Based Nationwide Study.

Cancer survivors are at increased risk of diabetes mellitus (DM). Additionally, the prevalence of obesity, which is also a risk factor for DM, is increasing in cancer survivors. We investigated the associations between weight change after cancer diagnosis and DM risk. This retrospective cohort study used data from the Korean National Health Insurance Service. Participants who were newly diagnosed with cancer from 2010 to 2016 and received national health screening before and after diagnosis were included and followed until 2019. Weight change status after cancer diagnosis was categorized into four groups: sustained normal weight, obese to normal weight, normal weight to obese, or sustained obese. Cox proportional hazard analyses were performed to examine associations between weight change and DM. The study population comprised 264,250 cancer survivors. DM risk was highest in sustained obese (adjusted hazard ratios, 95% confidence interval: 2.17, 2.08-2.26), followed by normal weight to obese (1.66, 1.54-1.79), obese to normal weight (1.29, 1.21-1.39), and then sustained normal weight group (reference). In subgroup analyses according to cancer type, most cancers showed the highest risks in sustained obese group. Obesity at any time point was related to increased DM risk, presenting the highest risk in cancer survivors with sustained obesity. Survivors who changed from obese to normal weight had lower risk than survivors with sustained obesity. Survivors who changed from normal weight to obese showed increased risk compared to those who sustained normal weight. Our finding supports the significance of weight management among cancer survivors.