Journal of Diabetes最新文献

{"title":"Interactive correlations between artificial light at night, health risk behaviors, and cardiovascular health among patients with diabetes: A cross-sectional study","authors":"Yi Zhang,&nbsp;Keyan Hu,&nbsp;Ying Tang,&nbsp;Qing Feng,&nbsp;Tian Jiang,&nbsp;Liwen Chen,&nbsp;Xin Chen,&nbsp;Chunhan Shan,&nbsp;Chen Han,&nbsp;Wenhui Chu,&nbsp;Nanzhen Ma,&nbsp;Honglin Hu,&nbsp;Hui Gao,&nbsp;Qiu Zhang","doi":"10.1111/1753-0407.70008","DOIUrl":"https://doi.org/10.1111/1753-0407.70008","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Artificial light at night (ALAN) is a common phenomenon and contributes to the severe light pollution suffered by more than 80% of the world's population. This study aimed to evaluate the relationship between outdoor ALAN exposure and cardiovascular health (CVH) in patients with diabetes and the influence of various modifiable factors.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A survey method based on the China Diabetes and Risk Factor Monitoring System was adopted. Study data were extracted for 1765 individuals with diabetes in Anhui Province. Outdoor ALAN exposure (nW/cm²/sr) within 1000 m of each participant's residential address was obtained from satellite imagery data, with a resolution of ~1000 m. Health risk behaviors (HRBs) were measured via a standardized questionnaire. A linear regression model was employed to estimate the relationship between outdoor ALAN, HRBs, and CVH.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Participants' mean age was 59.10 ± 10.0 years. An association was observed between ALAN and CVH in patients with diabetes (<i>β</i> = 0.205) and exercise (<i>β</i> = −1.557), moderated by HRBs, or metabolic metrics. There was an association between ALAN, ALAN, vegetable intake, and CVH.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Exploring the relationship between ALAN exposure and cardiovascular and metabolic health provides policy data for improving light pollution strategies and reducing the risk of cardiovascular and metabolic disease in patients with diabetes.</p>\u0000 \u0000 <div>\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure>\u0000 </div>\u0000 </section>\u0000 </div>","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"16 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142435417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physical activity modifies the association between atherogenic index of plasma and prediabetes and diabetes: A cross-sectional analysis","authors":"Shenglan Yang,&nbsp;Xinyu Gou,&nbsp;Hui Dong,&nbsp;Limei Chen,&nbsp;Yiyan Wang,&nbsp;Jing Wu","doi":"10.1111/1753-0407.70006","DOIUrl":"https://doi.org/10.1111/1753-0407.70006","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Although research has explored the association between atherogenic index of plasma (AIP) and prediabetes and diabetes, there is still not sufficient available evidence the role of physical activity (PA) in this relationship. Our purpose is to examine the complex connections between AIP, PA, and prediabetes and diabetes in a young and middle-aged population.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This study included 2220 individuals from the general population, aged 20–60 years. AIP was calculated from the logarithm of the triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C) ratio. PA was assessed depending to the American Heart Association (AHA) criteria and categorized into medium-high and low PA levels. We used binary logistic regression to explore associations and subsequently performed sensitivity and subgroup analyses.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The 2220 participants had a mean age of 38 years, with a mean AIP of −0.1185, and a prediabetes and diabetes prevalence of 7.2%. After adjusting for auxiliary variables, AIP was positively correlated with prediabetes and diabetes (odds ratio [OR]: 3.447, 95% confidence interval [CI]: 1.829–6.497). In the low PA population, the prevalence of prediabetes and diabetes raised significantly with higher AIP (OR: 3.678, 95% CI: 1.819–7.434). This association was not meaningful in the medium to high PA population (OR: 1.925, 95% CI: 0.411–9.007). Joint and sensitivity analyze results also showed agreement. Restricted cubic spline identified a linear relationship between AIP and the prevalence of prediabetes and diabetes. Notably, the prevalence significantly increases when AIP values exceed −0.16 (<i>p</i> for linearity &lt;0.05). The findings revealed heterogeneity across subgroups stratified by sex and age.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>PA may modify the link as regards AIP with prediabetes and diabetes in young and middle-aged populations. Adherence to PA prevents the adverse effects of abnormal glucose metabolism caused by dyslipidemia, particularly in women.</p>\u0000 \u0000 <div>\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure>\u0000 </div>\u0000 </section>\u0000 </div>","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"16 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142435416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association between coffee consumption and metabolic syndrome: A cross-sectional and Mendelian randomization study","authors":"Tommy Hon Ting Wong,&nbsp;Shan Luo,&nbsp;Shiu Lun Au Yeung,&nbsp;Jimmy Chun Yu Louie","doi":"10.1111/1753-0407.70004","DOIUrl":"10.1111/1753-0407.70004","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>This study investigates the associations between coffee consumption and metabolic syndrome and its components, as well as the effect of milk, sugar, and artificial sweeteners on these associations.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A cross-sectional analysis was conducted with 351805 UK Biobank participants. Coffee consumption data were collected via food frequency questionnaires and 24-h recall. Metabolic syndrome was identified through blood biochemistry and self-reported medication use. Odds ratios were calculated using multivariable logistic regression, and results were verified with two-sample Mendelian randomization.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Consuming up to two cups of coffee per day was inversely associated with metabolic syndrome (1 cup/day: odds ratio [OR]: 0.88, 95% confidence interval [CI]: 0.85–0.92; 2 cups/day: OR: 0.90, 95% CI: 0.86–0.93). Higher intakes showed near-null associations. Mendelian randomization did not support a causal link between coffee intake and metabolic syndrome. Both self-reported and genetically predicted high coffee consumption (four cups per day or more) were associated with central obesity. The inverse association between coffee consumption and metabolic syndrome was more profound among drinkers of ground coffee than those of instant coffee. Results were similar when stratified by the use of milk and sugar, yet the use of artificial sweetener with coffee was positively associated with metabolic syndrome and all component conditions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Coffee consumption may increase the risk of central obesity but is unlikely to impact the risk of metabolic syndrome. The potential health effects of artificial sweeteners in coffee need further investigation.</p>\u0000 \u0000 <div>\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure>\u0000 </div>\u0000 </section>\u0000 </div>","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"16 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142398844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The association of ideal cardiovascular health and its change with subclinical atherosclerosis according to glucose status: A prospective cohort study","authors":"Xiaojing Jia,&nbsp;Yilan Ding,&nbsp;Chunyan Hu,&nbsp;Hong Lin,&nbsp;Lin Lin,&nbsp;Xueyan Wu,&nbsp;Hongyan Qi,&nbsp;Shuangyuan Wang,&nbsp;Ruizhi Zheng,&nbsp;Jie Zheng,&nbsp;Min Xu,&nbsp;Yu Xu,&nbsp;Tiange Wang,&nbsp;Zhiyun Zhao,&nbsp;Yuhong Chen,&nbsp;Mian Li,&nbsp;Guang Ning,&nbsp;Weiqing Wang,&nbsp;Weiguo Hu,&nbsp;Yufang Bi,&nbsp;Jieli Lu","doi":"10.1111/1753-0407.70007","DOIUrl":"https://doi.org/10.1111/1753-0407.70007","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>An updated definition was developed to better evaluate cardiovascular health (CVH). We aimed to investigate whether optimal or improvement of six CVH metrics defined by new Life's Essential 8 (LE8) may counteract the risk of subclinical atherosclerosis among patients with hyperglycemia.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We conducted a prospective analysis of 5225 participants without prior cardiovascular diseases, of whom 4768 had complete data on CVH change. Subjects with CVH scores of 0–49, 50–79, and 80–100 points were categorized as having low, moderate, or high CVH, respectively. Subclinical atherosclerosis was evaluated by brachial-ankle pulse wave velocity, pulse pressure and albuminuria, both separately and in combination.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Of the 5225 participants, 1937 (37.1%) had normal glucose regulation, while 3288 (62.9%) had hyperglycemia. The multivariable-adjusted odds ratio (OR) for composite subclinical atherosclerosis was 2.34 (95% confidence interval [CI], 1.88–2.91), 1.43 (95% CI, 1.21–1.70), and 0.74 (95% CI, 0.46–1.18), for participants with hyperglycemia who had low, moderate, or high overall CVH scores, respectively, compared with participants with normal glucose regulation. In addition, compared with those with stable CVH and normal glucose regulation, participants who exhibited greater improvements in overall CVH from 2010 to 2014 had a reduced risk of composite subclinical atherosclerosis with an OR of 0.72 (95% CI, 0.53–0.98) for those with normal glucose regulation, and 1.13 (95% CI, 0.87–1.48) for those with hyperglycemia.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The novel defined CVH using six metrics was inversely associated with subsequent risk of subclinical atherosclerosis. Both the status of CVH and its changes modified the relationship between hyperglycemia and subclinical atherosclerosis.</p>\u0000 \u0000 <div>\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure>\u0000 </div>\u0000 </section>\u0000 </div>","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"16 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142429820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"National burden and risk factors of diabetes mellitus in China from 1990 to 2021: Results from the Global Burden of Disease study 2021","authors":"Wenzhen Deng,&nbsp;Li Zhao,&nbsp;Cheng Chen,&nbsp;Ziyu Ren,&nbsp;Yuanyuan Jing,&nbsp;Jingwen Qiu,&nbsp;Dongfang Liu","doi":"10.1111/1753-0407.70012","DOIUrl":"10.1111/1753-0407.70012","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>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.</p>\u0000 \u0000 <div>\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure>\u0000 </div>\u0000 </section>\u0000 </div>","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"16 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11457207/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142379584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Increased prevalence of diabetes mellitus and its metabolic risk factors from 2002 to 2017 in Shanghai, China","authors":"Qinping Yang,&nbsp;Jingyan Tian,&nbsp;Yanyun Li,&nbsp;Qinghua Yan,&nbsp;Wenli Xu,&nbsp;Chaowei Fu,&nbsp;Minna Cheng,&nbsp;Yan Shi","doi":"10.1111/1753-0407.70003","DOIUrl":"10.1111/1753-0407.70003","url":null,"abstract":"&lt;p&gt;The prevalence of diabetes in China continues to climb at an alarmingly rapid rate relative to other Asian countries.&lt;span&gt;&lt;sup&gt;1-3&lt;/sup&gt;&lt;/span&gt; And the prevalence in Shanghai was much higher than other areas in China.&lt;span&gt;&lt;sup&gt;4-6&lt;/sup&gt;&lt;/span&gt; Diabetes has therefore gradually developed into a significant public health concern affecting the health of Shanghai residents. Interventions on high-risk population of diabetes were very cost-effective for diabetes prevention supported by strong evidence.&lt;span&gt;&lt;sup&gt;7&lt;/sup&gt;&lt;/span&gt; It was shown that metabolic factors such as obesity, hypertension, and dyslipidemia may be risk factors for diabetes.&lt;span&gt;&lt;sup&gt;8-10&lt;/sup&gt;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&gt;Data sourced from the 2002, 2009, and 2017 Shanghai Diabetes Mellitus Epidemiological Investigation and the 2013 Shanghai Non-communicable Disease and Risk Factors Surveillance databases were integrated. In these investigations, information on demographic characteristics, lifestyle, personal histories, and family histories of diabetes and other diseases was collected by questionnaires. Heights, weights, waist circumferences, and blood pressures were obtained using a standardized protocol. A venous blood sample was collected from each participant after an overnight fast of at least 10 h in all investigations; for each subject without a history of diabetes, a blood sample was drawn 120 min after an oral glucose tolerance test after imbibing a standard 75-g glucose solution. Compound Annual Growth Rate (CAGR) = (Ending Value/Beginning Value) ^ (1/n) -1, where “n” represents the number of years of observation. Cochran–Armitage trend test was used to analyze the temporal trends. Logistic regression was utilized to estimate the odds ratio (OR). The population attributable risk percentage (PAR%), which can be used to evaluate the possible reduction in the prevalence of diabetes after elimination of risk factors,&lt;span&gt;&lt;sup&gt;11&lt;/sup&gt;&lt;/span&gt; was calculated with OR.&lt;/p&gt;&lt;p&gt;From 2002 to 2017, the standardized prevalence rates of diabetes among Shanghai residents aged 35–74 years old rose from 10.14% to 18.47%. The CAGR was 4.08%, which was higher than that for rural southwest China (3.05%),&lt;span&gt;&lt;sup&gt;12&lt;/sup&gt;&lt;/span&gt; New York (1.79%),&lt;span&gt;&lt;sup&gt;13&lt;/sup&gt;&lt;/span&gt; Thailand (3.54%),&lt;span&gt;&lt;sup&gt;14&lt;/sup&gt;&lt;/span&gt; or India (1.65%–3.83%).&lt;span&gt;&lt;sup&gt;15&lt;/sup&gt;&lt;/span&gt; The prevalence of diabetes rose over time for all groups but was higher in men, elderly, and urban residents, a phenomenon also observed in other areas in China.&lt;span&gt;&lt;sup&gt;12, 16&lt;/sup&gt;&lt;/span&gt; The gap of prevalence between men and women gradually widened (CAGR: 4.55% vs. 3.37%), which was similar in Shenzhen (a first-tier city in China)&lt;span&gt;&lt;sup&gt;16&lt;/sup&gt;&lt;/span&gt; (Figure 1). The prevalence of all metabolic risk factors included in this study increased across years (&lt;i&gt;p&lt;/i&gt;&lt;sub&gt;trend&lt;/sub&gt; &lt;0.05). All four risk factors were positively correlated with diabetes mellitus (&lt;i&gt;p&lt;/i&gt; &lt; 0.05), but the ORs did not changed significantly (&lt;i&gt;p&lt;/","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"16 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11457206/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142379583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prevalence and influencing factors of malnutrition in diabetic patients: A systematic review and meta-analysis","authors":"Tong Zhang,&nbsp;Jiangxia Qin,&nbsp;Jiali Guo,&nbsp;Jianhui Dong,&nbsp;Junbo Chen,&nbsp;Yuxia Ma,&nbsp;Lin Han","doi":"10.1111/1753-0407.13610","DOIUrl":"10.1111/1753-0407.13610","url":null,"abstract":"<p>The prevalence of malnutrition in diabetic patients and its influencing factors remain poorly described. We aim to investigate the prevalence of malnutrition and the influencing factors in diabetic patients through meta-analysis. Utilizing search terms, such as diabetes, malnutrition, and prevalence, we systematically searched eight databases, including Embase, PubMed, Web of Science, The Cochrane Library, China Knowledge Resource Integrated Database (CNKI), Wanfang Database, Chinese Biomedical Database (CBM), and VIP Database, from inception to May 4, 2023. The search aimed to identify studies related to the prevalence of malnutrition and its influencing factors in adult patients with diabetes. Cohort studies, case–control studies, and cross-sectional studies that met the inclusion criteria were included in the analysis. Stata 16.0 software was used for meta-analysis. Quality of the evidence was assessed using Grading of Recommendations, Assessment, Development and Evaluation (GRADE). The study protocol is registered with Prospective Register of Systematic Reviews (PROSPERO), CRD42023443649. A total of 46 studies were included, involving 18 062 patients with ages ranging from 18 to 95 years. The overall malnutrition prevalence was 33% (95% confidence interval [CI]: 0.25–0.40), compared with an at-risk prevalence of 44% (95% CI: 0.34–0.54). Sixteen factors associated with malnutrition in diabetic patients were identified. This meta-analysis provides insights into the prevalence of malnutrition and its risk factors in diabetic patients. Regular nutritional screening for patients with risk factors is essential for early detection and intervention.</p><p>\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"16 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11450603/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142370424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparing Glucagon-like peptide-1 receptor agonists versus metformin in drug-naive patients: A nationwide cohort study","authors":"Kathrine Kold Sørensen,&nbsp;Thomas Alexander Gerds,&nbsp;Lars Køber,&nbsp;Emil Loldrup Fosbøl,&nbsp;Henrik Enghusen Poulsen,&nbsp;Amalie Lykkemark Møller,&nbsp;Mikkel Porsborg Andersen,&nbsp;Ulrik Pedersen-Bjergaard,&nbsp;Christian Torp-Pedersen,&nbsp;Bochra Zareini","doi":"10.1111/1753-0407.70000","DOIUrl":"10.1111/1753-0407.70000","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Glucagon-like peptide-1 receptor agonists (GLP-1 RA) are increasingly being prescribed in drug-naive patients. We aimed to contrast add-on therapy, adherence, and changes in biomarkers, 1 year after treatment initiation with GLP-1 RA or metformin.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Using Danish nationwide registers, we included incident GLP-1 RA or metformin users from 2018 to 2021 with glycated hemoglobin (HbA1c) ≥ 42 mmol/mol. GLP-1 RA initiators were matched to metformin initiators in a ratio of 1:1 to assess outcomes in prediabetes and diabetes. Main outcomes analyzed were 1-year risk of add-on glucose-lowering medication and 1-year risk of nonadherence. One-year risks were estimated with multiple logistic regression and standardized. Multiple linear regression was used to estimate the average differences in biomarker changes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In total, 1778 individuals initiating GLP-1 RA and metformin were included. After standardizing for various factors, GLP-1 RA compared with metformin was associated with reduced 1-year risk of add-on glucose-lowering treatment in patients with prediabetes (1-year risk ratio [RR]: 0.27, 95% confidence interval [CI]: 0.10–0.44) and diabetes (RR: 0.67, 95% CI: 0.37–0.98). GLP-1 RA was associated with higher 1-year risk of nonadherence among patients with prediabetes (RR: 1.60, 95% CI: 1.45–1.75), but no difference in patients with diabetes (RR: 0.88, 95% CI: 0.70–1.06). Compared to metformin, GLP-1 RA was associated with greater HbA1c reduction (prediabetes: −2.59 mmol/mol 95% CI: −3.10 to −2.09, diabetes: −3.79 mmol/mol, 95% CI: −5.28 to −2.30).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>GLP-1 RA was associated with a reduced risk of additional glucose-lowering medication, achieving better glycated hemoglobin control overall. However, among patients with prediabetes, metformin was associated with better adherence.</p>\u0000 \u0000 <div>\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure>\u0000 </div>\u0000 </section>\u0000 </div>","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"16 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11450598/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142370421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effectiveness of wearable technology-based physical activity interventions for adults with type 2 diabetes mellitus: A systematic review and meta-regression","authors":"Rachael Ern Ching Chua,&nbsp;Ying Lau,&nbsp;Wen Wei Ang,&nbsp;Allison Ann Ying Faustina Boey,&nbsp;Siew Tiang Lau","doi":"10.1111/1753-0407.70002","DOIUrl":"10.1111/1753-0407.70002","url":null,"abstract":"<p>Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder with the increasing prevalence of a modern sedentary lifestyle. Wearable technology-based physical activity interventions (WT-BPAI) might provide a channel to improve diabetic self-management. The study aimed to (1) evaluate the effectiveness of WT-BPAI on PA levels, glycemic levels, and other outcomes (blood pressure [BP], body mass index [BMI], and serum lipid profile) in adults with T2DM, and (2) investigate the potential covariates affecting aforementioned outcomes. Eight databases were searched thoroughly using three steps from inception until January 16, 2024. The quality of the studies and overall evidence were evaluated. The package <i>meta</i> of the <i>R</i> software program version 4.3.1. was utilized for meta-analyses, subgroup analyses, and meta-regression analyses. A total of 19 randomized controlled trials (RCTs) were found. Meta-analyses revealed that WT-BPAI significantly increased 1583 steps per day and decreased systolic BP (SBP) by 2.46 mmHg. Subgroup and meta-regression analyses found that function, duration of intervention, and age were significant covariates. According to the risk of bias version 2, more than half of the trials raised some concerns about the randomization process, deviations from the intended intervention, and missing outcome data. The certainty of the evidence was very low for all outcomes based on the Grading of Recommendations Assessment, Development and Evaluation (GRADE) criteria. WT-BPAI can be considered a supplementary intervention to increase the steps per day and decrease SBP, especially when used for short periods in young adults with T2DM. However, we need more well-designed research with long-term outcomes.</p><p>\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"16 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11450597/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142370422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing and predicting type 2 diabetes risk with triglyceride glucose-body mass index in the Chinese nondiabetic population—Data from long-term follow-up of Da Qing IGT and Diabetes Study","authors":"Haixu Wang,&nbsp;Siyao He,&nbsp;Jinping Wang,&nbsp;Xin Qian,&nbsp;Bo Zhang,&nbsp;Zhiwei Yang,&nbsp;Bo Chen,&nbsp;Guangwei Li,&nbsp;Qiuhong Gong,&nbsp;for the Da Qing Diabetes Prevention Outcome Study Group","doi":"10.1111/1753-0407.70001","DOIUrl":"10.1111/1753-0407.70001","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aims</h3>\u0000 \u0000 <p>We intended to characterize the superiority of triglyceride glucose-body mass index (TyG-BMI) in predicting type 2 diabetes mellitus (T2DM) compared with triglyceride glucose (TyG) and homeostatic model assessment for insulin resistance (HOMA-IR).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A total of 699 nondiabetic participants in the Da Qing IGT and Diabetes Study were involved in the present analysis and classified according to the median of baseline TyG-BMI, namely the G1 (low TyG-BMI) and G2 (high TyG-BMI) groups. Information on developing diabetes was assessed from 1986 to 2020.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>During the 34-year follow-up, after adjustment for confounders, the G2 group had a higher risk of developing type 2 diabetes than the G1 group (hazard ratio [HR]: 1.92, 95% confidence interval [CI]: 1.51–2.45, <i>p</i> &lt; 0.0001). Restricted cubic spline analyses showed that increased TyG-BMI was linearly related to higher risks of type 2 diabetes (<i>p</i> for non-linearity&gt;0.05). Time-dependent receiver operator characteristics curves suggested that TyG-BMI exhibited higher predictive ability than TyG (6-year: area under the curve [AUC]_TyG-BMI vs. AUC_TyG, 0.78 vs. 0.70, <i>p</i> = 0.03; 34-year: AUC_TyG-BMI vs. AUC_TyG, 0.79 vs. 0.73, <i>p</i> = 0.04) and HOMA-IR (6-year: AUC_TyG-BMI vs. AUC_HOMA-IR, 0.78 vs. 0.70, <i>p</i> = 0.07; 34-year: AUC_TyG-BMI vs. AUC_HOMA-IR, 0.79 vs. 0.71, <i>p</i> = 0.04) in both short and long terms, and the thresholds of TyG-BMI to predict type 2 diabetes were relatively stable (195.24–208.41) over the 34-year follow-up.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>In this post hoc study, higher TyG-BMI was associated with an increased risk of type 2 diabetes and demonstrated better predictability than TyG and HOMA-IR, favoring the application of TyG-BMI as a potential tool for evaluating the risk of type 2 diabetes in clinical practice.</p>\u0000 \u0000 <div>\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure>\u0000 </div>\u0000 </section>\u0000 </div>","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"16 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11450669/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142370420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}