Pub Date : 2024-08-01DOI: 10.1016/j.dsx.2024.103125
{"title":"Highlights of the Current Issue","authors":"","doi":"10.1016/j.dsx.2024.103125","DOIUrl":"10.1016/j.dsx.2024.103125","url":null,"abstract":"","PeriodicalId":48252,"journal":{"name":"Diabetes & Metabolic Syndrome-Clinical Research & Reviews","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142318616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1016/j.dsx.2024.103115
Aims
The clinical manifestation of type 2 diabetes (T2D) varies across populations. We compared the phenotypic characteristics of Black Africans and White Europeans with recently diagnosed T2D to understand the ethnic differences in the manifestation of T2D.
Methods
We searched Medline, EMBASE, CINAHL, Google Scholar, African Index Medicus, and Global Health for studies reporting information on phenotypic characteristics in Black Africans and White Europeans with recently diagnosed T2D.
Results
A total of 28 studies were included in this systematic review (14 studies conducted on 2586 Black Africans in eight countries and 14 studies conducted on 279,621 White Europeans in nine countries). Compared with White Europeans, Black Africans had a lower pooled mean (95 % confidence interval) age (51.5 [48.5–54.4] years vs. 60.2 [57.9–62.6] years), body mass index (27.0 [24.2–29.8] kg/m2 vs. 31.3 [30.5–32.1] kg/m2), and a higher pooled median glycated haemoglobin (9.0 [8.0–10.3]% vs. 7.1 [6.7–7.7]%). Ugandan and Tanzanian participants had lower markers of beta-cell function and insulin resistance when compared with four White European populations.
Conclusion
These findings provide evidence of the ethnic differences in the manifestation of T2D, underscoring the importance of understanding the underlying factors influencing these differences and formulating ethnic-specific approaches for managing and preventing T2D.
目的 不同人群 2 型糖尿病（T2D）的临床表现各不相同。方法 我们检索了 Medline、EMBASE、CINAHL、Google Scholar、African Index Medicus 和 Global Health 中有关非洲黑人和欧洲白人新近确诊的 T2D 表型特征的研究。结果 本系统综述共纳入 28 项研究（14 项研究针对 8 个国家的 2586 名非洲黑人，14 项研究针对 9 个国家的 279621 名欧洲白人）。与欧洲白人相比，非洲黑人的总平均年龄（95 % 置信区间）较低（51.5 [48.5-54.4] 岁 vs. 60.2 [57.9-62.6]岁）、体重指数（27.0 [24.2-29.8] kg/m2 vs. 31.3 [30.5-32.1] kg/m2）和汇总糖化血红蛋白中位数（9.0 [8.0-10.3]% vs. 7.1 [6.7-7.7]%）较高。与四个欧洲白人群体相比，乌干达和坦桑尼亚参与者的β细胞功能和胰岛素抵抗指标较低。 结论：这些研究结果证明了T2D表现形式的种族差异，强调了了解影响这些差异的潜在因素并制定针对不同种族的T2D管理和预防方法的重要性。
{"title":"Differential manifestation of type 2 diabetes in Black Africans and White Europeans with recently diagnosed type 2 diabetes: A systematic review","authors":"","doi":"10.1016/j.dsx.2024.103115","DOIUrl":"10.1016/j.dsx.2024.103115","url":null,"abstract":"<div><h3>Aims</h3><p>The clinical manifestation of type 2 diabetes (T2D) varies across populations. We compared the phenotypic characteristics of Black Africans and White Europeans with recently diagnosed T2D to understand the ethnic differences in the manifestation of T2D.</p></div><div><h3>Methods</h3><p>We searched Medline, EMBASE, CINAHL, Google Scholar, African Index Medicus, and Global Health for studies reporting information on phenotypic characteristics in Black Africans and White Europeans with recently diagnosed T2D.</p></div><div><h3>Results</h3><p>A total of 28 studies were included in this systematic review (14 studies conducted on 2586 Black Africans in eight countries and 14 studies conducted on 279,621 White Europeans in nine countries). Compared with White Europeans, Black Africans had a lower pooled mean (95 % confidence interval) age (51.5 [48.5–54.4] years vs. 60.2 [57.9–62.6] years), body mass index (27.0 [24.2–29.8] kg/m<sup>2</sup> vs. 31.3 [30.5–32.1] kg/m<sup>2</sup>), and a higher pooled median glycated haemoglobin (9.0 [8.0–10.3]% vs. 7.1 [6.7–7.7]%). Ugandan and Tanzanian participants had lower markers of beta-cell function and insulin resistance when compared with four White European populations.</p></div><div><h3>Conclusion</h3><p>These findings provide evidence of the ethnic differences in the manifestation of T2D, underscoring the importance of understanding the underlying factors influencing these differences and formulating ethnic-specific approaches for managing and preventing T2D.</p></div>","PeriodicalId":48252,"journal":{"name":"Diabetes & Metabolic Syndrome-Clinical Research & Reviews","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142147789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1016/j.dsx.2024.103087
Background
Patients afflicted by type 1 diabetes (T1D) exhibit polyautoimmunity (PolyA). However, the frequency and distribution of PolyA in T1D is still unknown.
Objective
We conducted a systematic review and meta-analysis to define the prevalence of latent and overt PolyA in individuals with T1D.
Methods
Following PRISMA guidelines, a comprehensive search across medical databases identified studies on latent and overt PolyA in T1D. Two researchers independently screened, extracted data, and assessed study quality. A random effects model was utilized to calculate the pooled prevalence, along with its corresponding 95 % confidence interval (CI), for latent PolyA and overt PolyA. Meta-regression analysis was conducted to study the effect of study designs, age, sex, and duration of disease on pooled prevalence.
Results
A total of 158 articles, encompassing a diverse composition of study designs were scrutinized. The analysis included 270,890 individuals with a confirmed diagnosis of T1D. The gender was evenly distributed (50.30 % male). Notably, our analysis unveiled an overt PolyA prevalence rate of 8.50 % (95 % CI, 6.77 to 10.62), with North America having the highest rates (14.50 %, 95 % CI, 7.58 to 24.89). This PolyA profile was further characterized by a substantial incidence of concurrent autoimmune thyroid disease (7.44 %, 95 % CI, 5.65 to 9.74). Moreover, we identified a notable prevalence of latent PolyA in the T1D population, quantified at 14.45 % (95 % CI, 11.17 to 18.49) being most frequent in Asia (23.29 %, 95 % CI, 16.29 to 32.15) and Oceania (21.53 %, 95 % CI, 16.48 to 27.62). Remarkably, this latent PolyA phenomenon primarily featured an array of autoantibodies, including rheumatoid factor, followed by Ro52, thyroid peroxidase antibodies, and thyroglobulin antibodies. Duration of the disease was associated with a highest frequency of latent (β: 0.0456, P-value: 0.0140) and overt PolyA (β: 0.0373, P-value: 0.0152). No difference in the pooled prevalence by study design was observed.
Conclusion
This meta-analysis constitutes a substantial advancement in the realm of early detection of PolyA in the context of T1D. Individuals with T1D should regularly undergo assessments to identify potential concurrent autoimmune diseases, especially as they age.
{"title":"Prevalence of latent and overt polyautoimmunity in type 1 diabetes: A systematic review and meta-analysis","authors":"","doi":"10.1016/j.dsx.2024.103087","DOIUrl":"10.1016/j.dsx.2024.103087","url":null,"abstract":"<div><h3>Background</h3><p>Patients afflicted by type 1 diabetes (T1D) exhibit polyautoimmunity (PolyA). However, the frequency and distribution of PolyA in T1D is still unknown.</p></div><div><h3>Objective</h3><p>We conducted a systematic review and meta-analysis to define the prevalence of latent and overt PolyA in individuals with T1D.</p></div><div><h3>Methods</h3><p>Following PRISMA guidelines, a comprehensive search across medical databases identified studies on latent and overt PolyA in T1D. Two researchers independently screened, extracted data, and assessed study quality. A random effects model was utilized to calculate the pooled prevalence, along with its corresponding 95 % confidence interval (CI), for latent PolyA and overt PolyA. Meta-regression analysis was conducted to study the effect of study designs, age, sex, and duration of disease on pooled prevalence.</p></div><div><h3>Results</h3><p>A total of 158 articles, encompassing a diverse composition of study designs were scrutinized. The analysis included 270,890 individuals with a confirmed diagnosis of T1D. The gender was evenly distributed (50.30 % male). Notably, our analysis unveiled an overt PolyA prevalence rate of 8.50 % (95 % CI, 6.77 to 10.62), with North America having the highest rates (14.50 %, 95 % CI, 7.58 to 24.89). This PolyA profile was further characterized by a substantial incidence of concurrent autoimmune thyroid disease (7.44 %, 95 % CI, 5.65 to 9.74). Moreover, we identified a notable prevalence of latent PolyA in the T1D population, quantified at 14.45 % (95 % CI, 11.17 to 18.49) being most frequent in Asia (23.29 %, 95 % CI, 16.29 to 32.15) and Oceania (21.53 %, 95 % CI, 16.48 to 27.62). Remarkably, this latent PolyA phenomenon primarily featured an array of autoantibodies, including rheumatoid factor, followed by Ro52, thyroid peroxidase antibodies, and thyroglobulin antibodies. Duration of the disease was associated with a highest frequency of latent (β: 0.0456, P-value: 0.0140) and overt PolyA (β: 0.0373, P-value: 0.0152). No difference in the pooled prevalence by study design was observed.</p></div><div><h3>Conclusion</h3><p>This meta-analysis constitutes a substantial advancement in the realm of early detection of PolyA in the context of T1D. Individuals with T1D should regularly undergo assessments to identify potential concurrent autoimmune diseases, especially as they age.</p></div>","PeriodicalId":48252,"journal":{"name":"Diabetes & Metabolic Syndrome-Clinical Research & Reviews","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141793806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1016/j.dsx.2024.103117
{"title":"Highlights of the current issue","authors":"","doi":"10.1016/j.dsx.2024.103117","DOIUrl":"10.1016/j.dsx.2024.103117","url":null,"abstract":"","PeriodicalId":48252,"journal":{"name":"Diabetes & Metabolic Syndrome-Clinical Research & Reviews","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142326670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1016/j.dsx.2024.103086
Introduction
In 2021, the International Diabetes Federation reported that 537 million people worldwide are living with diabetes. While glucagon-like peptide-1 agonists provide significant benefits in diabetes management, approximately 40 % of patients do not respond well to this therapy. This study aims to enhance treatment outcomes by using machine learning to predict individual response status to glucagon-like peptide-1 therapy.
Methods
We analysed a type-2 diabetes mellitus dataset from the Diastrat cohort, recruited at the Northern Ireland Centre for Stratified Medicine. The dataset included individuals prescribed glucagon-like peptide-1 therapy, with response status determined by glycated haemoglobin levels of ≤53 mmol/mol. We identified genomic and proteomic markers and developed machine learning models to predict therapy response.
Results
The study found 5 genomic variants and 45 proteomic markers that help differentiate glucagon-like peptide-1 therapy responders from non-responders, achieving 95 % prediction accuracy with a machine learning model.
Conclusion
This study demonstrates the potential of machine learning in predicting the response to glucagon-like peptide-1 therapy in individuals with type-2 diabetes mellitus. These findings suggest that integrating genomic and proteomic data can significantly enhance personalized treatment approaches, potentially improving outcomes for patients who might otherwise not respond well to glucagon-like peptide-1 therapy. Further research and validation in larger cohorts are necessary to confirm these results and translate them into clinical practice.
{"title":"Computational approaches for clinical, genomic and proteomic markers of response to glucagon-like peptide-1 therapy in type-2 diabetes mellitus: An exploratory analysis with machine learning algorithms","authors":"","doi":"10.1016/j.dsx.2024.103086","DOIUrl":"10.1016/j.dsx.2024.103086","url":null,"abstract":"<div><h3>Introduction</h3><p>In 2021, the International Diabetes Federation reported that 537 million people worldwide are living with diabetes. While glucagon-like peptide-1 agonists provide significant benefits in diabetes management, approximately 40 % of patients do not respond well to this therapy. This study aims to enhance treatment outcomes by using machine learning to predict individual response status to glucagon-like peptide-1 therapy.</p></div><div><h3>Methods</h3><p>We analysed a type-2 diabetes mellitus dataset from the Diastrat cohort, recruited at the Northern Ireland Centre for Stratified Medicine. The dataset included individuals prescribed glucagon-like peptide-1 therapy, with response status determined by glycated haemoglobin levels of ≤53 mmol/mol. We identified genomic and proteomic markers and developed machine learning models to predict therapy response.</p></div><div><h3>Results</h3><p>The study found 5 genomic variants and 45 proteomic markers that help differentiate glucagon-like peptide-1 therapy responders from non-responders, achieving 95 % prediction accuracy with a machine learning model.</p></div><div><h3>Conclusion</h3><p>This study demonstrates the potential of machine learning in predicting the response to glucagon-like peptide-1 therapy in individuals with type-2 diabetes mellitus. These findings suggest that integrating genomic and proteomic data can significantly enhance personalized treatment approaches, potentially improving outcomes for patients who might otherwise not respond well to glucagon-like peptide-1 therapy. Further research and validation in larger cohorts are necessary to confirm these results and translate them into clinical practice.</p></div>","PeriodicalId":48252,"journal":{"name":"Diabetes & Metabolic Syndrome-Clinical Research & Reviews","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141789467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1016/j.dsx.2024.103089
Background & aim
Much of the cost data from India is restricted to patients recruited purely from healthcare institutions and do not explore determinants. Therefore, the out of pocket expenditure for ambulatory diabetes care was evaluated in Delhi.
Methods
The DEDICOM-II survey used a two-stage probability-proportionate-to-size(systematic) cluster design. Thirty clusters were chosen to recruit 25 to 30 subjects per area. We used questionnaires to estimate the direct out-of-pocket expenditure (OOPE) on drugs, investigations, consultation and travel, excluding hospitalization, and then analysed its determinants and impact on quality of care.
Results
We enrolled 843 subjects with a mean age of 53.1 years. The annual direct OOPE on ambulatory care of diabetes was US$ 116.3 (95 % CI 93.8–138.9) or INR 8074.8 (95 % CI 6512.9–9636.7), corresponding to 3.6 %(95 % CI 2.9–4.3) of the yearly family income. The burden of expenses was disproportionately higher for those visiting private providers from lower-income groups(19.1 %). Duration of disease and treatment with insulin predicted higher annual OOPE while care at public facilities was less expensive. Cost was higher for those adhering to the recommended processes of care. Quality of care was better for institutional care and worse for alternative medicine or self-care.
Conclusions
The study provides representative estimates of the high cost of diabetes management in Delhi across the socio-economic and care provider spectra. Poorer patients suffer a high financial burden from diabetes, highlighting the need for enhancing equity in diabetes care.
背景& 目的印度的大部分费用数据仅限于纯粹从医疗机构招募的患者，并没有探究决定因素。因此，我们对德里非住院糖尿病护理的自费支出进行了评估。方法DEDICOM-II调查采用了两阶段概率-比例-规模（系统）群组设计。我们选择了 30 个群组，每个地区招募 25 至 30 名调查对象。我们使用调查问卷估算了药物、检查、咨询和旅行（不包括住院）的直接自付支出（OOPE），然后分析了其决定因素和对医疗质量的影响。每年用于糖尿病非住院治疗的直接OOPE为116.3美元（95 % CI 93.8-138.9）或8074.8印度卢比（95 % CI 6512.9-9636.7），相当于家庭年收入的3.6 %（95 % CI 2.9-4.3）。低收入群体中去私人医疗机构就诊者的费用负担更高（19.1%）。病程长和使用胰岛素治疗预示着每年的门诊费用较高，而在公立医疗机构就诊的费用较低。遵守推荐护理流程的患者费用更高。机构护理的质量较好，而替代药物或自我护理的质量较差。贫困患者承受着糖尿病带来的沉重经济负担，这凸显了加强糖尿病护理公平性的必要性。
{"title":"Out-of-pocket direct cost of ambulatory care of type 2 diabetes in Delhi: Estimates from the Delhi diabetes community-II (DEDICOM-II) survey","authors":"","doi":"10.1016/j.dsx.2024.103089","DOIUrl":"10.1016/j.dsx.2024.103089","url":null,"abstract":"<div><h3>Background & aim</h3><p>Much of the cost data from India is restricted to patients recruited purely from healthcare institutions and do not explore determinants. Therefore, the out of pocket expenditure for ambulatory diabetes care was evaluated in Delhi.</p></div><div><h3>Methods</h3><p>The DEDICOM-II survey used a two-stage probability-proportionate-to-size(systematic) cluster design. Thirty clusters were chosen to recruit 25 to 30 subjects per area. We used questionnaires to estimate the direct out-of-pocket expenditure (OOPE) on drugs, investigations, consultation and travel, excluding hospitalization, and then analysed its determinants and impact on quality of care.</p></div><div><h3>Results</h3><p>We enrolled 843 subjects with a mean age of 53.1 years. The annual direct OOPE on ambulatory care of diabetes was US$ 116.3 (95 % CI 93.8–138.9) or INR 8074.8 (95 % CI 6512.9–9636.7), corresponding to 3.6 %(95 % CI 2.9–4.3) of the yearly family income. The burden of expenses was disproportionately higher for those visiting private providers from lower-income groups(19.1 %). Duration of disease and treatment with insulin predicted higher annual OOPE while care at public facilities was less expensive. Cost was higher for those adhering to the recommended processes of care. Quality of care was better for institutional care and worse for alternative medicine or self-care.</p></div><div><h3>Conclusions</h3><p>The study provides representative estimates of the high cost of diabetes management in Delhi across the socio-economic and care provider spectra. Poorer patients suffer a high financial burden from diabetes, highlighting the need for enhancing equity in diabetes care.</p></div>","PeriodicalId":48252,"journal":{"name":"Diabetes & Metabolic Syndrome-Clinical Research & Reviews","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141849583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1016/j.dsx.2024.103093
Background
Gestational diabetes mellitus (GDM) is glucose intolerance first detected during pregnancy. Twin pregnancies have a higher risk of GDM, likely due to increased placental mass and elevated placental lactogen levels.
Objective
The aims of this study were 1) to assess the impact of chorionicity on the development of GDM in twin pregnancies and 2) to assess a possible association between placenta weight and the development of GDM.
Methods
We conducted a prospective cohort study of all women with twin pregnancies (N = 819) at the department of Obstetrics and Gynecology, Lillebaelt University Hospital, Kolding, Denmark, between January 1, 2007 and April 30, 2019. Information on chronicity was determined at the first visit with ultrasonic imaging, during weeks’ gestation 11–13. Oral glucose-tolerance test was performed to diagnose gestational diabetes mellitus.
Results
Among 819 twins, 17.8 % were monochorionic twins and 82.2 % were dichorionic twins. There were no statistically significant difference of GDM prevalence between monochorionic twins group 7.4 % and dichorionic twins group 9.8 % (P = 0.42). Placenta's weight in dichorionic twins was larger compared with monochorionic twins. No association was found between the weight of placenta and the prevalence of GDM (P = 0.21), even after adjustment for body mass index, gestational age, and fertility treatment (P = 0.87).
Conclusions
Our study could not find an association between chorionicity, placental weight, and GDM. It is, therefore, possible that twin pregnancies, regardless of chorionicity and placental weight, have the same risk for GDM.
{"title":"Chorionicity and gestational diabetes mellitus in twin pregnancies in relation to placental weight","authors":"","doi":"10.1016/j.dsx.2024.103093","DOIUrl":"10.1016/j.dsx.2024.103093","url":null,"abstract":"<div><h3>Background</h3><p>Gestational diabetes mellitus (GDM) is glucose intolerance first detected during pregnancy. Twin pregnancies have a higher risk of GDM, likely due to increased placental mass and elevated placental lactogen levels.</p></div><div><h3>Objective</h3><p>The aims of this study were 1) to assess the impact of chorionicity on the development of GDM in twin pregnancies and 2) to assess a possible association between placenta weight and the development of GDM.</p></div><div><h3>Methods</h3><p>We conducted a prospective cohort study of all women with twin pregnancies (N = 819) at the department of Obstetrics and Gynecology, Lillebaelt University Hospital, Kolding, Denmark, between January 1, 2007 and April 30, 2019. Information on chronicity was determined at the first visit with ultrasonic imaging, during weeks’ gestation 11–13. Oral glucose-tolerance test was performed to diagnose gestational diabetes mellitus.</p></div><div><h3>Results</h3><p>Among 819 twins, 17.8 % were monochorionic twins and 82.2 % were dichorionic twins. There were no statistically significant difference of GDM prevalence between monochorionic twins group 7.4 % and dichorionic twins group 9.8 % (P = 0.42). Placenta's weight in dichorionic twins was larger compared with monochorionic twins. No association was found between the weight of placenta and the prevalence of GDM (P = 0.21), even after adjustment for body mass index, gestational age, and fertility treatment (P = 0.87).</p></div><div><h3>Conclusions</h3><p>Our study could not find an association between chorionicity, placental weight, and GDM. It is, therefore, possible that twin pregnancies, regardless of chorionicity and placental weight, have the same risk for GDM.</p></div>","PeriodicalId":48252,"journal":{"name":"Diabetes & Metabolic Syndrome-Clinical Research & Reviews","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141876367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1016/j.dsx.2024.103092
Background
The study investigates substituting non-nutritive sweeteners (NNS) for sugar to address health concerns related to excess sugar intake. It specifically examines how stevia affects insulin and blood glucose levels. The systematic review and meta-analysis aim to evaluate stevia's impact on glycemic indices.
Methods
We conducted a systematic review and meta-analysis following PRISMA guidelines, including 26 studies with 1439 participants. The PROSPERO registration number for this research is CRD42023414411. We systematically searched PubMed (MEDLINE), Scopus, Web of Science, and Google Scholar. Additionally, we thoroughly reviewed the reference lists of the articles we extracted and relevant reviews. Two evaluators independently carried out screening, quality assessment, and data extraction. The GRADE (grading of recommendations, assessment, development, and evaluation) approach was utilized to evaluate the certainty of the evidence.
Results
Stevia consumption was associated with significantly reducing blood glucose levels (WMD: −3.84; 95 % CI: −7.15, −0.53; P = 0.02, low certainty), especially in individuals with higher BMI, diabetes, and hypertension. Dose-response analysis revealed a decrease in blood glucose for ≥3342 mg/day of stevia consumption. Stevia consumption has been shown to reduce blood glucose levels within 1–4 months, as evidenced by dose-response analysis (less than 120 days) and subgroup analysis (more than four weeks). However, stevia did not significantly affect insulin concentration or HbA1C levels (very low and low certainty, respectively).
Conclusions
Low certainty evidence showed that stevia improved blood glucose control, especially when consumed for less than 120 days. However, more randomized trials with higher stevia dosages are required.
{"title":"Effect of stevia on blood glucose and HbA1C: A meta-analysis","authors":"","doi":"10.1016/j.dsx.2024.103092","DOIUrl":"10.1016/j.dsx.2024.103092","url":null,"abstract":"<div><h3>Background</h3><p>The study investigates substituting non-nutritive sweeteners (NNS) for sugar to address health concerns related to excess sugar intake. It specifically examines how stevia affects insulin and blood glucose levels. The systematic review and meta-analysis aim to evaluate stevia's impact on glycemic indices.</p></div><div><h3>Methods</h3><p>We conducted a systematic review and meta-analysis following PRISMA guidelines, including 26 studies with 1439 participants. The PROSPERO registration number for this research is CRD42023414411. We systematically searched PubMed (MEDLINE), Scopus, Web of Science, and Google Scholar. Additionally, we thoroughly reviewed the reference lists of the articles we extracted and relevant reviews. Two evaluators independently carried out screening, quality assessment, and data extraction. The GRADE (grading of recommendations, assessment, development, and evaluation) approach was utilized to evaluate the certainty of the evidence.</p></div><div><h3>Results</h3><p>Stevia consumption was associated with significantly reducing blood glucose levels (WMD: −3.84; 95 % CI: −7.15, −0.53; P = 0.02, low certainty), especially in individuals with higher BMI, diabetes, and hypertension. Dose-response analysis revealed a decrease in blood glucose for ≥3342 mg/day of stevia consumption. Stevia consumption has been shown to reduce blood glucose levels within 1–4 months, as evidenced by dose-response analysis (less than 120 days) and subgroup analysis (more than four weeks). However, stevia did not significantly affect insulin concentration or HbA1C levels (very low and low certainty, respectively).</p></div><div><h3>Conclusions</h3><p>Low certainty evidence showed that stevia improved blood glucose control, especially when consumed for less than 120 days. However, more randomized trials with higher stevia dosages are required.</p></div>","PeriodicalId":48252,"journal":{"name":"Diabetes & Metabolic Syndrome-Clinical Research & Reviews","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141890500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1016/j.dsx.2024.103085
Background
Noncommunicable diseases (NCDs) are the leading cause of adult mortality in India. However, the data regarding the prevalence of NCD risk factors at district level is scarce. This study aims to analyse and map NCD risk factors at the state and district levels, exploring sociodemographic influences on these risks in Indian males and females.
Methods
We analyzed National Family Health Survey-5 database and used the prevalence estimates to create choropleth maps, enabling us to examine the geographical variations in NCD risk factors at the district level in India.
Results
Districts in the Satluj-Yamuna plains, western Rajasthan, and the northeastern regions exhibited clusters with a prevalence of high blood pressure exceeding 30.1 %. Northeastern districts showed over 40 % prevalence of current tobacco use, while high alcohol consumption clusters were observed in the northeastern and Telangana districts. Southern districts showed clusters of both obesity (as measured by BMI) and highest rates of oral, breast, and cervical cancer screening, moreover districts in Tamil Nadu exhibited notable clusters of raised blood glucose prevalence.
Conclusion
Our analysis revealed variations in the prevalence of NCD risk factors at both the state and district levels. Accordingly, this study ranks districts based on the NCD burden, offering valuable insights to state and district teams to devise targeted measures for the prevention and control of NCDs, particularly in the most heavily affected districts.
{"title":"District-level epidemiology and sociodemographic determinants of noncommunicable diseases - results the National Family Health Survey −5 (2019–21)","authors":"","doi":"10.1016/j.dsx.2024.103085","DOIUrl":"10.1016/j.dsx.2024.103085","url":null,"abstract":"<div><h3>Background</h3><p>Noncommunicable diseases (NCDs) are the leading cause of adult mortality in India. However, the data regarding the prevalence of NCD risk factors at district level is scarce. This study aims to analyse and map NCD risk factors at the state and district levels, exploring sociodemographic influences on these risks in Indian males and females.</p></div><div><h3>Methods</h3><p>We analyzed National Family Health Survey-5 database and used the prevalence estimates to create choropleth maps, enabling us to examine the geographical variations in NCD risk factors at the district level in India.</p></div><div><h3>Results</h3><p>Districts in the Satluj-Yamuna plains, western Rajasthan, and the northeastern regions exhibited clusters with a prevalence of high blood pressure exceeding 30.1 %. Northeastern districts showed over 40 % prevalence of current tobacco use, while high alcohol consumption clusters were observed in the northeastern and Telangana districts. Southern districts showed clusters of both obesity (as measured by BMI) and highest rates of oral, breast, and cervical cancer screening, moreover districts in Tamil Nadu exhibited notable clusters of raised blood glucose prevalence.</p></div><div><h3>Conclusion</h3><p>Our analysis revealed variations in the prevalence of NCD risk factors at both the state and district levels. Accordingly, this study ranks districts based on the NCD burden, offering valuable insights to state and district teams to devise targeted measures for the prevention and control of NCDs, particularly in the most heavily affected districts.</p></div>","PeriodicalId":48252,"journal":{"name":"Diabetes & Metabolic Syndrome-Clinical Research & Reviews","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141849474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-01DOI: 10.1016/j.dsx.2024.103090
Background
To investigate whether and what lifestyle factors in later life modify the associations of early-life smoking behaviors and genetic susceptibility with type 2 diabetes (T2D).
Methods
In the UK Biobank, in utero tobacco exposure (n = 354,493) and age of smoking initiation (n = 353,557) were self-reported. A composite lifestyle score was calculated based on diet, physical activity, nicotine exposure, sleep duration, and BMI. Hazard ratio (HR) and absolute risk difference (ARD) were used to estimate the associations of early-life smoking behaviors and genetic risk with incident T2D, as well as the effect modification of the lifestyle score.
Results
During a median follow-up of 14.6 years, the HRs (95 % CIs) of T2D for in utero tobacco exposure, and smoking initiation in adulthood, adolescence, and childhood, compared with no smoking behavior, were 1.19 (1.16–1.23), 1.34 (1.29–1.39), 1.58 (1.53–1.64), 2.22 (2.11–2.32), respectively (P for trend<0.001). Early-life smoking behaviors and high genetic risk (vs no smoking behavior and low genetic risk) were associated with a 302%–593 % higher T2D risk (P for additive interaction<0.05). Compared to participants with early-life smoking behaviors, high genetic risk, and an unfavorable lifestyle, those who adhered to a favorable lifestyle had a lower T2D risk in all subgroups (HRs from 0.05 to 0.36 and ARD from −14.97 % to −9.51 %), with the highest ARD attributable to lifestyle in participants with early-life smoking behaviors and high genetic risk.
Conclusions
The T2D risk associated with early-life smoking behaviors and genetic risk was modified by a favorable lifestyle.
{"title":"Lifestyle modifies the associations of early-life smoking behaviors and genetic susceptibility with type 2 diabetes: A prospective cohort study involving 433,872 individuals from UK Biobank","authors":"","doi":"10.1016/j.dsx.2024.103090","DOIUrl":"10.1016/j.dsx.2024.103090","url":null,"abstract":"<div><h3>Background</h3><p>To investigate whether and what lifestyle factors in later life modify the associations of early-life smoking behaviors and genetic susceptibility with type 2 diabetes (T2D).</p></div><div><h3>Methods</h3><p>In the UK Biobank, in utero tobacco exposure (n = 354,493) and age of smoking initiation (n = 353,557) were self-reported. A composite lifestyle score was calculated based on diet, physical activity, nicotine exposure, sleep duration, and BMI. Hazard ratio (HR) and absolute risk difference (ARD) were used to estimate the associations of early-life smoking behaviors and genetic risk with incident T2D, as well as the effect modification of the lifestyle score.</p></div><div><h3>Results</h3><p>During a median follow-up of 14.6 years, the HRs (95 % CIs) of T2D for in utero tobacco exposure, and smoking initiation in adulthood, adolescence, and childhood, compared with no smoking behavior, were 1.19 (1.16–1.23), 1.34 (1.29–1.39), 1.58 (1.53–1.64), 2.22 (2.11–2.32), respectively (<em>P</em> for trend<0.001). Early-life smoking behaviors and high genetic risk (vs no smoking behavior and low genetic risk) were associated with a 302%–593 % higher T2D risk (<em>P</em> for additive interaction<0.05). Compared to participants with early-life smoking behaviors, high genetic risk, and an unfavorable lifestyle, those who adhered to a favorable lifestyle had a lower T2D risk in all subgroups (HRs from 0.05 to 0.36 and ARD from −14.97 % to −9.51 %), with the highest ARD attributable to lifestyle in participants with early-life smoking behaviors and high genetic risk.</p></div><div><h3>Conclusions</h3><p>The T2D risk associated with early-life smoking behaviors and genetic risk was modified by a favorable lifestyle.</p></div>","PeriodicalId":48252,"journal":{"name":"Diabetes & Metabolic Syndrome-Clinical Research & Reviews","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141842421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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