Comparison of food intake pattern of diabetic patients and healthy individuals in a sample of Saudi population: a case-control study.

BACKGROUND: There has been a significant rise in the number of individuals diagnosed with type 2 diabetes mellitus (T2DM), with the condition reaching epidemic proportions globally. This study examined the dietary pattern of a sample of Saudi Arabian adults with T2DM compared to control non-diabetics. METHODS: Data from 414 participants, 207 control and 207 T2DM was analyzed. Anthropometric measurements, foods intake such as vegetables, fruits, whole grains, fried foods, sweetened juice, sweets, and pastries consumption as well as physical activity were obtained by an interview-survey. RESULTS: The consumption of vegetables, green and leafy vegetables, starchy vegetables, fruits, proteins, and milk was significantly higher in the diabetics (p< 0.0001 for all and p<0.01 for starchy vegetables). Of the case group, 79.7% of them consumed whole-wheat bread while 54.6% of them consumed low fat milk (p<0.0001). There was a significant decrease in the percentage of cases who consumed discretionary foods and sweetened juices and soft drinks (24.1%), avoided sweets (75.8%) and pastries (37.1%), (p<0.0001). There were also significant increases in the percentages of participants who use healthy fat (as olive oil) in the case group (78.7%) (p<0.001). There was a significant increase in the percentage of diabetics who followed a diet to lose weight (15%) (p<0.05). The majority of the two study groups were physically inactive (control 95.2% & case 94.2%). CONCLUSIONS: The results of this study provide insight on that diabetics generally follow a healthy diet, yet their engagement in physical activity may not be optimal.

Association of ADIPOQ Gene Polymorphisms with Type 2 Diabetes and Obesity Risk in the Kazakh Population: A Case-Control and Population-Based Study.

Type 2 diabetes mellitus (T2DM) is a socially significant disease with increasing prevalence worldwide. It is characterized by heterogeneous metabolic disorders and is associated with various risk factors, including BMI, abnormal lipid levels, hypertension, smoking, dietary preferences, physical inactivity, sedentary lifestyle, family history of diabetes, prediabetes or gestational diabetes, inflammation, intrauterine environment, age, sex, ethnicity, and socioeconomic status. Assessing the genetic risk of developing T2DM in specific populations remains relevant. The ADIPOQ gene, encoding adiponectin, is directly related to the risk of developing T2DM, obesity, and cardiovascular diseases. Our study demonstrated significant associations of ADIPOQ gene polymorphisms with the risk of developing T2DM and obesity, as well as with fasting glucose levels and BMI, in the Kazakh population. Specifically, rs266729 was significantly associated with T2DM and obesity in the Kazakh population, while other studied polymorphisms (rs1501299, rs2241766, and rs17846866) did not show a significant association. These findings suggest that ADIPOQ gene polymorphisms may influence T2DM risk factors and highlight the importance of genetic factors in T2DM development. However, further research in larger cohorts is needed to confirm these associations.

MicroRNAs Associated with Metformin Treatment in the Diabetes Prevention Program.

The Diabetes Prevention Program (DPP) randomized controlled trial demonstrated that metformin treatment reduced progression to type 2 diabetes (T2D) by 31% compared to placebo in adults with prediabetes. Circulating micro-ribonucleic acids (miRs) are promising biomarkers of T2D risk, but little is known about their associations with metformin regimens for T2D risk reduction. We compared the change in 24 circulating miRs from baseline to 2 years in a subset from DPP metformin intervention (n = 50) and placebo (n = 50) groups using Wilcoxon signed rank tests. Spearman correlations were used to evaluate associations between miR change and baseline clinical characteristics. Multiple linear regression was used to adjust for covariates. The sample was 73% female, 17% Black, 13% Hispanic, and 50 ± 11 years. Participants were obese, normotensive, prediabetic, and dyslipidemic. Change in 12 miR levels from baseline to 2 years was significantly different in the metformin group compared with placebo after adjusting for multiple comparisons: six (let-7c-5p, miR-151a-3p, miR-17-5p, miR-20b-5p, miR-29b-3p, and miR-93-5p) were significantly upregulated and six (miR-130b-3p, miR-22-3p, miR-222-3p, miR-320a-3p, miR-320c, miR-92a-3p) were significantly downregulated in the metformin group. These miRs help to explain how metformin is linked to T2D risk reduction, which may lead to novel biomarkers, therapeutics, and precision health strategies.

Risk assessment of diabetes using the Indian Diabetes Risk Score among older adults: Secondary analysis from the Longitudinal Ageing Study in India.

BACKGROUND: The Indian Diabetes Risk Score (IDRS) is a simple tool to assess the probability of an individual having type 2 diabetes (T2DM) but its applicability in community-dwelling older adults is lacking. This study aimed to estimate the risk of T2DM and its determinants among older adults without prior diabetes (DM) using the IDRS, while also assessing its sensitivity and specificity in individuals with a history of diabetes. METHODS: We analyzed cross-sectional data from the Longitudinal Ageing Study in India (LASI) wave-1 (2017-18). IDRS was calculated amongst individuals aged ≥45 years considering waist circumference, physical activity, age and family history of DM. Risk was categorized as high (≥60), moderate (30-50), and low (<30). RESULTS: Among 64541 individuals, 7.27 % (95 % CI: 6.78, 7.80) were at low risk, 61.80 % (95 % CI: 60.99, 62.61) at moderate risk, and 30.93 % (95 % CI: 30.19, 31.67) at high risk for T2DM. Adjusted analysis showed higher risk of T2DM among men, widowed/divorced, urban residents, minority religions, overweight, obese, and individuals with hypertension. ROC curve yielded an AUC of 0.67 (95 % CI: 0.66, 0.67, P < 0.001). The IDRS cutoff ≥50 had 73.69 % sensitivity and 51.40 % specificity for T2DM detection. CONCLUSION: More than 9 in 10 older adults in India without history of DM have high-moderate risk of T2DM when assessed with the IDRS risk-prediction tool. However, the low specificity and moderate sensitivity of IDRS in existing DM cases constraints its practical utility as a decision tool for screening.

Predictive value of Systematic Coronary Risk Evaluation 2-Diabetes risk model and arterial stiffness for cardiovascular events in the Asian population with type 2 diabetes mellitus.

AIMS/INTRODUCTION: Individuals with diabetes are at high risk of developing cardiovascular events. The present study investigated the predictive value of the cardio-ankle vascular index (CAVI) when added to the Systematic Coronary Risk Evaluation 2-Diabetes (SCORE2-Diabetes) risk algorithm to predict cardiovascular events in the Asian population. MATERIALS AND METHODS: The SCORE2-Diabetes risk was assessed in 1,502 patients with diabetes, aged 40-69 years. Then, we further stratified each 10-year risk category with a CAVI value of 9.0. The primary outcomes (composite of all causes of death, myocardial infarction, stroke and hospitalization for heart failure) were assessed over 5 years. RESULTS: The mean age of the population was 59.8 ± 6.4 years. The proportion of 10-year risk according to the SCORE2-Diabetes risk of low, moderate, high and very high risk identified at 7.2, 30.0, 27.2 and 35.6%, respectively. The mean CAVI value was 8.4 ± 1.4, and approximately 35.4% of the patients had CAVI ≥9.0. The SCORE2-Diabetes risk algorithm independently predicted the primary outcomes in patients with diabetes (hazard ratio 1.18, 95% confidence interval [CI] 1.13-1.22), whereas CAVI did not (hazard ratio 1.03, 95% CI 0.89-1.18). The C-index for the primary outcomes of the SCORE2-Diabetes risk algorithm alone was 0.72 (95% CI 0.67-0.77). The combination of SCORE2-Diabetes and CAVI, both in the continuous value and risk groups, did not improve discrimination (C-index 0.72, 95% CI 0.67-0.77 and 0.68, 95% CI 0.64-0.74, respectively). CONCLUSIONS: Adding the CAVI to the SCORE2-Diabetes risk algorithm did not improve individual risk stratification in patients with diabetes.

Beyond the assembly line: An assessment of diabetes risks among Indian male industrial workers.

Background: Diabetes mellitus is a chronic non-communicable disease that imposes a significant burden on affected individuals and the community. Considerable attention has been given to industrial accidents and ergonomics, however, lifestyle-related diseases among industrial workers have often been neglected. Therefore, the present study was conducted with the aim to assess the prevalence of obesity/overweight and ascertain the risk of diabetes mellitus among male employees of an industrial unit in South Mumbai. Methods: The cross-sectional study was conducted among male employees of an industrial unit in South Mumbai. Family history, exercise patterns, anthropometric measurements and physical vital parameters were recorded. Body composition was assessed using bioelectrical impedance analysis (BIA). The Indian Diabetes Risk Score (IDRS) was employed to evaluate the risk of diabetes mellitus. Results: In total, 3791 industrial workers participated in the study and 44.5% of participants were above 40 years. Mean height, weight, body mass index (BMI), Waist Circumference (WC) and waist to hip ratio (WHR) were 1.67 m, 71.33 kg, 25.99, 90.81 cm and 0.91 respectively. 56.1% individuals had WC more than 90 cm and 79.1% had WHR more than 0.90. 1846 (53%) and 927 (26.6%) participants had moderate and high diabetes risk respectively. The relationship between age, weight, BMI, WC, WHR, body fat mass and fat percentage, and IDRS was statistically significant. Conclusion: A substantial proportion of industrial workers were identified as overweight and at high risk of diabetes mellitus. Consequently, it becomes imperative to offer health education and implement interventions to encourage regular exercise, adopt an active lifestyle, and promote healthy dietary habits among industrial workers.

Adverse Childhood Experiences and Diabetes Risk in Mississippi Adults.

Despite Mississippi's high diabetes prevalence and the growing literature finding significant associations between adverse childhood experiences (ACEs) and diabetes, no research has examined the relationship between ACEs and diabetes risk in Mississippi adults. This study utilized data from the 2020 Behavioral Risk Factor Surveillance System (BRFSS) to determine if such a relationship existed. Data for Mississippi respondents were weighted to account for nonresponse bias and non-coverage errors. Each respondent's total ACE exposure score was calculated based on the number of ACE categories experienced. Multivariate logistic regression was utilized to model the relationship between diabetes and ACE categories and diabetes and total ACE exposure scores. Variables that were significant at p<0.05 were retained in the final (best-fitting) models. All models were adjusted for sex, age, race, level of education, income, and body mass index (BMI). After adjusting for covariates, those experiencing physical abuse (adjusted odds ratio (AOR) 1.72, 95% CI 1.69; 1.75) or sexual abuse (AOR 1.56, 95% CI 1.53; 1.58) had the highest odds of ever being diagnosed with diabetes. Experiencing one ACE (AOR 1.02, 95% CI 1.01; 1.03) was associated with slightly higher odds of having diabetes, while experiencing seven ACE categories (AOR 2.20, 95% CI 2.10; 2.31) had the highest odds. Overall, this study shows a strong association between ACEs and a diagnosis of diabetes in the state of Mississippi. This relationship represents an important focus area for prevention efforts in legislation, public health campaigns, and universal screening procedures in primary care that may decrease the prevalence and burden of diabetes in Mississippi.

Serum concentration of polychlorinated biphenyls and the risk of type 2 diabetes: a 10-year follow-up historical cohort study.

This study investigated the association between serum concentrations of Polychlorinated Biphenyls (PCBs) and the risk of type 2 diabetes within the general population. A ten-year follow-up historical cohort study was conducted during 2009-2019 as part of the Bushehr MONICA cohort study in Iran. Of 893 non-diabetes participants at base line, 181 individuals were included in the study. The concentration of nine PCB congeners was measured in individuals' serum samples at baseline, and the risk of type 2 diabetes was determined based on fasting blood sugar at the end of follow-up. Multiple logistic regression models were used to assess the study outcomes after adjusting for covariates. This study included 59 diabetes individuals (32.6%; mean [SD] age: 58.64 [8.05]) and 122 non-diabetes individuals (67.4%; mean [SD] age: 52.75 [8.68]). Multivariable analysis revealed that a one-tertile increase (increasing from 33rd centile to 67th centile) in Σ non-dioxin-like-PCBs (OR 2.749, 95% CI 1.066-7.089), Σ dioxin-like-PCBs (OR 4.842, 95% CI 1.911-12.269), and Σ PCBs (OR 2.887, 95% CI 1.120-7.441) significantly associated with an increased risk of type 2 diabetes. The strongest association was obtained for dioxin-like PCBs. The results highlight a significant correlation between PCB exposure and an increased risk of type 2 diabetes. The evidence suggests that additional epidemiological studies are necessary to clarify the link between PCBs and diabetes.

Estimating the effect of lipid-lowering agents on novel subtypes of adult-onset diabetes.

AIMS: The aims of the present study were to assess the effects of lipid-lowering drugs [HMG-CoA reductase inhibitors, proprotein convertase subtilisin/kexin type 9 inhibitors, and Niemann-Pick C1-Like 1 (NPC1L1) inhibitors] on novel subtypes of adult-onset diabetes through a Mendelian randomisation study. MATERIALS AND METHODS: We first inferred causal associations between lipid-related traits [including high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), apolipoproteins A-I, and apolipoproteins B] and novel subtypes of adult-onset diabetes. The expression quantitative trait loci of drug target genes for three classes of lipid-lowering drugs, as well as genetic variants within or nearby drug target genes associated with LDL-C, were then utilised as proxies for the exposure of lipid-lowering drugs. Mendelian randomisation analysis was performed using summary data from genome-wide association studies of LDL-C, severe autoimmune diabetes, severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD), and mild age-related diabetes. RESULTS: There was an association between HMGCR-mediated LDL-C and the risk of SIRD [odds ratio (OR) = 0.305, 95% confidence interval (CI) = 0.129-0.723; p = 0.007], and there was an association of PCSK9-mediated LDL-C with the risk of SIDD (OR = 0.253, 95% CI = 0.120-0.532; p < 0.001) and MOD (OR = 0.345, 95% CI = 0.171-0.696; p = 0.003). Moreover, NPC1L1-mediated LDL-C (OR = 0.109, 95% CI = 0.019-0.613; p = 0.012) and the increased expression of NPC1L1 gene in blood (OR = 0.727, 95% CI = 0.541-0.977; p = 0.034) both showed a significant association with SIRD. These results were further confirmed by sensitivity analyses. CONCLUSIONS: In summary, the different lipid-lowering medications have a specific effect on the increased risk of different novel subtypes of adult-onset diabetes.

Gestational diabetes and risk of future diabetes in a multi-ethnic population.

AIM: To investigate ethnic disparities in risk of gestational diabetes-mellitus (GDM) and future diabetes. METHODS: A population-based retrospective cohort study of women who underwent a 100-g oral glucose-tolerance-test (oGTT) during pregnancy between 2007 and 2017 in Clalit-Health-Services of the Jerusalem district. Univariate and multivariate logistic regression analyses were used to compare the risk of GDM in Arab versus Jewish women. Further, Cox-regression analysis was used to establish the risk of future diabetes. RESULTS: A total of 9875 women, 71 % of Jewish ethnicity and 29 % of Arab ethnicity were included. Arab women had a higher incidence of GDM compared to Jewish women (17.3 % vs. 10.6 %, p < 0.001), which persisted after adjusting for age, BMI, and metabolic profile (aOR 1.7; CI 1.48-2.0, P < 0.001). Additionally, Arab ethnicity was associated with an increased risk of future diabetes, even after adjusting for GDM status (aHR 5.9; 95 % CI 3.7-9.4, P < 0.001). CONCLUSIONS: Women of Arab ethnicity have a higher risk for both GDM and future diabetes, a risk that is beyond the initial increased risk associated with GDM. These findings highlight the need for increased focus on preventing diabetes in women of Arab ethnicity, especially those with a history of GDM.

A feature optimization study based on a diabetes risk questionnaire.

Introduction: The prevalence of diabetes, a common chronic disease, has shown a gradual increase, posing substantial burdens on both society and individuals. In order to enhance the effectiveness of diabetes risk prediction questionnaires, optimize the selection of characteristic variables, and raise awareness of diabetes risk among residents, this study utilizes survey data obtained from the risk factor monitoring system of the Centers for Disease Control and Prevention in the United States. Methods: Following univariate analysis and meticulous screening, a more refined dataset was constructed. This dataset underwent preprocessing steps, including data distribution standardization, the application of the Synthetic Minority Oversampling Technique (SMOTE) in combination with the Round function for equilibration, and data standardization. Subsequently, machine learning (ML) techniques were employed, utilizing enumerated feature variables to evaluate the strength of the correlation among diabetes risk factors. Results: The research findings effectively delineated the ranking of characteristic variables that significantly influence the risk of diabetes. Obesity emerges as the most impactful factor, overshadowing other risk factors. Additionally, psychological factors, advanced age, high cholesterol, high blood pressure, alcohol abuse, coronary heart disease or myocardial infarction, mobility difficulties, and low family income exhibit correlations with diabetes risk to varying degrees. Discussion: The experimental data in this study illustrate that, while maintaining comparable accuracy, optimization of questionnaire variables and the number of questions can significantly enhance efficiency for subsequent follow-up and precise diabetes prevention. Moreover, the research methods employed in this study offer valuable insights into studying the risk correlation of other diseases, while the research results contribute to heightened societal awareness of populations at elevated risk of diabetes.

Diabetes prediction model for unbalanced community follow-up data set based on optimal feature selection and scorecard.

Objectives: Diabetes is a metabolic disease and early detection is crucial to ensuring a healthy life for people with prediabetes. Community care plays an important role in public health, but the association between community follow-up of key life characteristics and diabetes risk remains unclear. Based on the method of optimal feature selection and risk scorecard, follow-up data of diabetes patients are modeled to assess diabetes risk. Methods: We conducted a study on the diabetes risk assessment model and risk scorecard using follow-up data from diabetes patients in Haizhu District, Guangzhou, from 2016 to 2023. The raw data underwent preprocessing and imbalance handling. Subsequently, features relevant to diabetes were selected and optimized to determine the optimal subset of features associated with community follow-up and diabetes risk. We established the diabetes risk assessment model. Furthermore, for a comprehensible and interpretable risk expression, the Weight of Evidence transformation method was applied to features. The transformed features were discretized using the quantile binning method to design the risk scorecard, mapping the model's output to five risk levels. Results: In constructing the diabetes risk assessment model, the Random Forest classifier achieved the highest accuracy. The risk scorecard obtained an accuracy of 85.16%, precision of 87.30%, recall of 80.26%, and an F1 score of 83.27% on the unbalanced research dataset. The performance loss compared to the diabetes risk assessment model was minimal, suggesting that the binning method used for constructing the diabetes risk scorecard is reasonable, with very low feature information loss. Conclusion: The methods provided in this article demonstrate effectiveness and reliability in the assessment of diabetes risk. The assessment model and scorecard can be directly applied to community doctors for large-scale risk identification and early warning and can also be used for individual self-examination to reduce risk factor levels.

Intersectional analysis of social disparities in type 2 diabetes risk among adults in Germany: results from a nationwide population-based survey.

BACKGROUND: Differences in type 2 diabetes risk have been reported for several sociodemographic determinants including sex/gender or socioeconomic status. From an intersectional perspective, it is important to not only consider the role of social dimensions individually, but also their intersections. This allows for a deeper understanding of diabetes risk and preventive needs among diverse population groups. METHODS: As an intersectionality-informed approach, multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) was used in a population-based sample of adults without known diabetes in Germany from the cross-sectional survey "Disease knowledge and information needs- Diabetes mellitus (2017)". Diabetes risk was assessed by the German Diabetes Risk Score (GDRS, range 0-122 points), estimating the individual risk of developing type 2 diabetes within the next 5 years based on established self-reported risk factors. Nesting individuals in 12 intersectional strata defined by combining sex/gender, educational level, and history of migration, we calculated measures to quantify the extent to which individual differences in diabetes risk were explained at strata level, and how much this was due to additive or multiplicative intersectional effects of social determinants. RESULTS: Drawing on data of 2,253 participants, we found good discriminatory accuracy of intersectional strata (variance partition coefficient = 14.00% in the simple intersectional model). Model-predicted GDRS means varied between 29.97 (corresponding to a "low risk" of < 2%) in women with high educational level and a history of migration, and 52.73 ("still low risk" of 2-5%) in men with low educational level without a history of migration. Variance in GDRS between strata was mainly explained by additive effects of social determinants (proportional change in variance to intersectional interaction model = 77.95%) with being male and having low educational level being associated with higher GDRS. There was no evidence of multiplicative effects in individual strata. CONCLUSIONS: Type 2 diabetes risk differed between intersectional strata and can to some extent be explained at strata level. The role of intersectional effects was minor and needs to be further investigated. Findings suggest a need for specific preventive measures targeted at large groups with increased diabetes risk, such as men and persons with low educational level.

Fasting plasma lactate as a possible early clinical marker for metabolic disease risk.

BACKGROUND AND AIM: Elevated fasting plasma lactate concentrations are evident in individuals with metabolic diseases. However, it has yet to be determined if these associations exist in a young, healthy population as a possible early marker for metabolic disease risk. The purpose of this study was to determine if indices of the metabolic syndrome are related to plasma lactate concentrations in this population. METHODS: Fifty (29 ± 7 yr) men (n = 19) and women (n = 31) classified as overweight (26.4 ± 1.8 kg/m2) participated in this observational study. Blood pressure and blood metabolites were measured after an overnight fast. Lactate was also measured before and after a three-day eucaloric high-fat (70 %) diet. The homeostatic model assessment for insulin resistance (HOMA-IR) was calculated as a measure of insulin resistance. Visceral adipose tissue mass was determined via dual X-ray absorptiometry. RESULTS: Triglycerides (r = 0.55, p=<0.0001), HOMA-IR (r = 0.53, p=<0.0001), and systolic and diastolic (both, r = 0.36, p = 0.01) blood pressures associated with fasting plasma lactate. No differences in visceral adipose tissue existed between the sexes (p = 0.41); however, the relationship between visceral adipose tissue and lactate existed only in females (r = 0.59, p = 0.02) but not in males (p = 0.53). Fasting lactate and HOMA-IR increased in males (p = 0.01 and p = 0.02, respectively), but not females, following a three-day high-fat diet. CONCLUSION: Indices of the metabolic syndrome associated with fasting plasma lactates in young relatively healthy individuals. Fasting lactate also increased in a sex-specific manner after a three-day high fat diet. Thus, lactate could become a clinical marker for metabolic disease risk.

Risk of Type 2 Diabetes in University Students at the University of Extremadura: A Cross-Sectional Study.

The prevalence of type 2 diabetes is increasing worldwide. The aim of our study was to detect people susceptible to DM among a university population aged 18 to 45 years and analyze the existence of modifiable risk factors in order to implement prevention programs, in addition to analyzing BMI data related to the variables under study. We proposed a descriptive, cross-sectional study following the recommendations of cross-sectional studies (STROBE), with a sample of 341 subjects, students enrolled at the University of Extremadura, carried out by two researchers. The research protocol was approved by the Bioethics Committee of the University of Extremadura (165/2021). The study considered the Findrisk questionnaire in Spanish, validated by the Blackboard Study, a stadiometer to measure height, a bioimpedance meter to evaluate weight and body composition parameters, and a blood pressure monitor to measure blood pressure. The results indicated that the participants had a low risk of suffering T2DM. The highest Findrisk test scores were found in those with a BMI value above 25, lower physical activity, poor dietary intake of fruits and vegetables, and increased fat mass. Our future research will be the implementation of T2DM prevention programs, acting on modifiable factors.

HDL levels modulate the impact of type 2 diabetes susceptibility alleles in older adults.

BACKGROUND: Type 2 Diabetes (T2D) is influenced by genetic, environmental, and ageing factors. Ageing pathways exacerbate metabolic diseases. This study aimed to examine both clinical and genetic factors of T2D in older adults. METHODS: A total of 2,909 genotyped patients were enrolled in this study. Genome Wide Association Study was conducted, comparing T2D patients to non-diabetic older adults aged ≥ 60, ≥ 65, or ≥ 70 years, respectively. Binomial logistic regressions were applied to examine the association between T2D and various risk factors. Stepwise logistic regression was conducted to explore the impact of low HDL (HDL < 40 mg/dl) on the relationship between the genetic variants and T2D. A further validation step using data from the UK Biobank with 53,779 subjects was performed. RESULTS: The association of T2D with both low HDL and family history of T2D increased with the age of control groups. T2D susceptibility variants (rs7756992, rs4712523 and rs10946403) were associated with T2D, more significantly with increased age of the control group. These variants had stronger effects on T2D risk when combined with low HDL cholesterol levels, especially in older control groups. CONCLUSIONS: The findings highlight a critical role of age, genetic predisposition, and HDL levels in T2D risk. The findings suggest that individuals over 70 years who have high HDL levels without the T2D susceptibility alleles may be at the lowest risk of developing T2D. These insights can inform tailored preventive strategies for older adults, enhancing personalized T2D risk assessments and interventions.

Impact of migration on diabetes burden: audit in the metropolitan area of Bologna, Italy.

PURPOSE: To investigate the impact of diabetes in immigrants on the Italian healthcare system, as well as their compliance with standard protocols of control and treatment. METHODS: The prevalence of immigrants with diabetes living in the metropolitan area of Bologna (about 1 million inhabitants) in 2019 was investigated using a database containing all subjects in active follow-up for diabetes, based on antidiabetic drug use, disease-specific copayment exemption, ICD-9 codes, continuous care in diabetes units. Country of origin was derived from fiscal code. RESULTS: The overall prevalence of diabetes (n = 53,941; 51.8% males, median age 64) was 6.1% in both Italy-born and immigrant cohorts. Immigrant prevalence was 12.4%, moderately higher than that observed in the total population (12.2%). Diabetes risk was increased in the whole immigrant cohort (odds ratio (OR) 1.74; 95% Confidence Interval (CI) 1.69-1.79). Among cases with incident diabetes, the proportion of immigrants (median age, 49 vs. 65 in Italy-born individuals) increased progressively from 11.7% to 26.5% from 2011 to 2019 (males, 8.9-21.0%; females, 14.9-32.8%) in all age groups, particularly in young adults, but also in older subjects. Metabolic control was lower in immigrants, as was adherence to shared diagnostic and therapeutic protocols, without systematic differences in antidiabetic drug use, but much lower use of drugs for comorbid conditions. CONCLUSIONS: The population with diabetes in the metropolitan area of Bologna is rapidly changing. Quality improvement initiatives are needed to reduce the burden for the universalistic Italian health care system generated by the rapidly-growing high-risk immigrant population.

Frequency and determinants of phytotherapy use in patients with type 2 diabetes in the Dschang Health District, Cameroon: a cross-sectional study

Introduction: phytotherapy is widely used in Africa for the management of many diseases. Data on the use of phytotherapy in people with type 2 diabetes are scarce. We aimed to determine the frequency and factors associated with the consumption/use of phytotherapy products among patients with type 2 diabetes in the Dschang Health District. Methods: we conducted a cross-sectional study from January to May 2022, including community-dwelling or hospitalized patients with type 2 diabetes who had lived in the Dschang Health District for at least one year. Informed consent was obtained from all patients. Data were collected using a pre-designed questionnaire. Variables collected included socio-demographic characteristics, diabetes knowledge and practices, and perceptions of care. Results: we included 403 (249 women) patients with type 2 diabetes with a mean (SD) age of 63 (± 14.86) years). Among them, 240 (59.55%) used phytotherapy, either in combination with conventional treatment (168 (41.69%) participants) or not (72 (17.86%) participants), to treat diabetes. The most common reasons for using phytotherapy were easy accessibility and belief in its efficacy. Most patients used both treatments because they thought the combination was more effective. In univariable analysis, we observed a statistically significant association between level of education (p=0.003), socioeconomic level (p<0.001), place of residence (p=0.003), duration of diabetes (p=0.007), and use of phytotherapy. In multivariable analysis, only age between 51 and 60 years (OR: 0.50, 95% CI 0.298 - 0.8521; p=0.01) was associated with the use of phytotherapy. Conclusion: people living with T2D in the Dschang Health District frequently use phytotherapy as an antidiabetic remedy, especially those aged between 51 and 60 years, those with low education level, low socioeconomic level and medium duration of diabetes. There is a need to evaluate its effectiveness in treating diabetes and its adverse effects.

Prácticas de crianza en alimentación, conducta alimentaria y riesgo de diabetes: Una revisión sistemática / Parenting practices in feeding, eating behavior and risk of diabetes: A systematic review

INTRODUCCIÓN: Las prácticas de crianza en alimentación y la conducta alimentaria han sido ampliamente estudiadas en niños, sin embargo, es necesario proporcionar información sobre su impacto en adultos. La evidencia sugiere que las prácticas de crianza en alimentación pueden tener un impacto en la conducta alimentarias emocional, descontrolada, restrictiva y desordenada, las cuales están asociadas con el incremento del Índice de masa corporal (IMC), el sobrepeso y la obesidad, mismos que se encuentran como principal factor de riesgo para el desarrollo de DT2. OBJETIVO: analizar través de una revisión sistemática la evidencia existente acerca de la relación entre las prácticas de crianza en alimentación, la conducta alimentaria y el riesgo de diabetes en adultos. METODOLOGÍA: Se realizó una búsqueda de literatura publicada de 2013 a 2023 en las bases de datos Pubmed, Scopus, EBSCOhost, Clarivate Science Citation Index Expanded y SpringerLink. Se identificaron 459 estudios, luego de aplicar los criterios de exclusión, se revisaron 15 estudios en total. RESULTADOS: Las subescalas de las prácticas de crianza en alimentación más empleadas fueron: preocupación, control, presión para comer y restricción. Se encontró asociación entre las prácticas de crianza en alimentación, la conducta alimentaria y el incremento del IMC. CONCLUSIÓN: Se consideran insuficientes las investigaciones que muestran el impacto de las prácticas de crianza en alimentación sobre la conducta alimentaria y si estas a su vez tienen efectos en el riesgo de diabetes en la etapa adulta.

INTRODUCTION: Parenting practices in feeding and eating behavior have been widely studied in children, however, it is necessary to provide information on their impact on adults. The evidence suggests that parenting practices in feeding can have an impact on emotional, uncontrolled, restrictive and disordered eating behavior, which are associated with an increase in BMI, overweight and obesity, which are found as the main factor of risk for the development of T2D. OBJECTIVE: To analyze, through a systematic review, the existing evidence about the relationship between parenting feeding practices, eating behavior and the risk of diabetes in adults. METHODOLOGY: A search of literature published from 2013 to 2023 was carried out in the Pubmed, Scopus, EBSCOhost, Clarivate Science Citation Index Expanded and SpringerLink databases. 459 studies were identified, after applying the exclusion criteria, 15 studies in total were reviewed. RESULTS: The subscales of the most frequently used parenting practices in feeding were: concern, control, pressure to eat and restriction. An association was found between parenting feeding practices, eating behavior and increased BMI. CONCLUSION: Research showing the impact of parenting feeding practices on eating behavior and whether these in turn have effects on the risk of diabetes in adulthood are considered insufficient.