Primary Care Diabetes最新文献

{"title":"Continuous glucose monitoring patterns among pregnant individuals with varying levels of glucose intolerance","authors":"Rachel D. Gordon ,&nbsp;Jiqiang Wu ,&nbsp;Jennifer Grasch ,&nbsp;Neeharika Nandam ,&nbsp;Patrick Schneider ,&nbsp;Steven Gabbe ,&nbsp;Mark B. Landon ,&nbsp;Maged M. Costantine ,&nbsp;Kartik K. Venkatesh ,&nbsp;Elizabeth O. Buschur","doi":"10.1016/j.pcd.2025.11.006","DOIUrl":"10.1016/j.pcd.2025.11.006","url":null,"abstract":"<div><div>We conducted a prospective observational cohort of pregnant individuals to compare continuous glucose monitoring trends between pregnant individuals with varying levels of glucose intolerance. We found that individuals who had an abnormal value on an oral glucose tolerance test had similar glucose trends to those with gestational diabetes mellitus</div></div>","PeriodicalId":48997,"journal":{"name":"Primary Care Diabetes","volume":"20 1","pages":"Pages 133-136"},"PeriodicalIF":2.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145673000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Achieving pregnancy glycemic targets and postpartum depressive symptoms among individuals with pregestational diabetes","authors":"Jenna Meiman ,&nbsp;Abigail Steinbrunner ,&nbsp;Naleef Fareed ,&nbsp;Joshua J. Joseph ,&nbsp;Mark B. Landon ,&nbsp;William A. Grobman ,&nbsp;Kartik K. Venkatesh","doi":"10.1016/j.pcd.2025.12.006","DOIUrl":"10.1016/j.pcd.2025.12.006","url":null,"abstract":"<div><div>We determined whether achieving glycemic control during pregnancy was associated with fewer postpartum depressive symptoms among individuals with pregestational diabetes. We found achievement of pregnancy glycemic targets was not associated with a lower risk of postpartum depressive symptoms in a population with a high frequency of pre-existing psychiatric morbidity.</div></div>","PeriodicalId":48997,"journal":{"name":"Primary Care Diabetes","volume":"20 1","pages":"Pages 137-139"},"PeriodicalIF":2.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145795508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Routine HbA1c monitoring and cardiovascular outcomes in diabetes: Evidence from a large Spanish cohort","authors":"Domingo Orozco-Beltran ,&nbsp;Samuel Seidu ,&nbsp;Jose Antonio Quesada","doi":"10.1016/j.pcd.2025.11.012","DOIUrl":"10.1016/j.pcd.2025.11.012","url":null,"abstract":"<div><h3>AIM</h3><div>Glycated hemoglobin (HbA_1c) is a key indicator of diabetes control. However, the risk of missing HbA_1c values in clinical records is unknown. We aimed to analyze the relationship between missing HbA_1c values and the occurrence of major cardiovascular events or death from all causes.</div></div><div><h3>Methods</h3><div>Retrospective cohort study based on a national database of primary care electronic medical records in Spain (BIFAP). We included people aged 30 years and older with an incident diagnosis of diabetes mellitus. Follow-up started on the date of diabetes diagnosis between 2005 and 2019, and ended on occurrence of composite endpoint (major cardiovascular events and/or death from all causes), or <em>December 31st</em>, 2019. The baseline exposure variable was HbA_1c (&lt; 7 %, 7 %–8 %, &gt; 8 %, missing). Cox models were fitted.</div></div><div><h3>Results</h3><div>Our analysis included 303,199 people with diabetes, with an average age of 62.2 years and 44.7 % were women. The mean follow-up was 5.7 years, and 10.2 % of patients had missing HbA_1c values. The cardiovascular risk was 1.18 (95 %CI: 1.14–1.22) in the HbA_1c 7 %-8 % group, 1.41 (95 %CI: 1.36–1.46) in HbA_1c &gt; 8 %, and 2.95 (95 %CI: 2.89–3.05) in HbA_1c missing, compared with HbA_1c &lt; 7 %.</div></div><div><h3>Conclusions</h3><div>In this large cohort of people with newly diagnosed diabetes, missing HbA1c values was associated with a significantly higher risk of major cardiovascular events or death, more than double the risk observed in people with the worst glycemic control. These findings underscore the clinical importance of routinely recording and monitoring HbA1c at diagnosis, not only as a marker of metabolic control but also as a potential prognostic indicator. The lack of HbA1c may act as an indicator of suboptimal clinical follow-up.</div></div>","PeriodicalId":48997,"journal":{"name":"Primary Care Diabetes","volume":"20 1","pages":"Pages 13-20"},"PeriodicalIF":2.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145776969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of an online self-management programme for type 2 diabetes. The BEATdiabetes prospective service evaluation","authors":"S. Carrod ,&nbsp;M.B. Whyte ,&nbsp;K. Bennett-Eastley ,&nbsp;P. Grob ,&nbsp;C. Steacy ,&nbsp;M. Shabbir ,&nbsp;M. Glover ,&nbsp;J. Harris ,&nbsp;K. Hart ,&nbsp;H. Gage ,&nbsp;M. Stedman ,&nbsp;A. Heald ,&nbsp;D. Cooke","doi":"10.1016/j.pcd.2025.10.005","DOIUrl":"10.1016/j.pcd.2025.10.005","url":null,"abstract":"<div><h3>Aims</h3><div>To deliver and evaluate online, supported self-management interventions (BEATdiabetes) designed to promote lifestyle change and reduce psychological distress in type 2 diabetes (T2D).</div></div><div><h3>Design &amp; methods</h3><div>A prospective service evaluation of BEATdiabetes, delivered within primary care in the National Health Service (NHS), 2019–2021. Primary outcome was absolute change in HbA1c and secondary outcomes were BMI, blood pressure (BP) and total cholesterol (TC) analysed using adjusted regression models. Pre- and post-analysis of the Diabetes Distress Scale (DDS) in the BEATdiabetes group only. The comparator population was The Salford Integrated Record (SIR, Salford, UK) diabetes cohort (no access to BEATdiabetes); matched by age, sex, ethnicity and BMI. Odds ratios (OR) evaluated achievement of clinical targets according to national guidelines.</div></div><div><h3>Results</h3><div>BEATdiabetes (n = 574) followed for median 217 days (interquartile range [IQR] 158–328); comparator group 241 days (IQR 187–328). BEATdiabetes had greater change in mean HbA1c (0.3 % DCCT; −3.3 mmol/mol; 95 % confidence interval [CI] −4.7 to −1.9 mmol/mol), BMI (-0.81 kg/m²; 95 % CI −1.07 to −0.54), systolic BP (-2.8 mmHg; 95 % CI −4.3 to −1.3; all P &lt; 0.001), and diastolic BP (-1.3 mmHg; 95 % CI −2.3 to −0.3; P &lt; 0.01). At baseline, n = 58 had DDS of ≥ 2 and n = 39 at follow-up (P = 0.023). BEATdiabetes had greater achievement target BP (OR 1.69 [95 % CI 1.28–2.24]), HbA1c (OR 1.79 [95 % CI 1.33–2.42]) and TC (OR 0.71 [95 % CI 0.50–0.99]). Estimated average cost per intervention was £ 149; 2021/2).</div></div><div><h3>Conclusions</h3><div>Combined online nutritional, psychological and behavioural intervention was more effective for weight and glycaemic reduction among adults with T2D, compared with usual care, with associated reduction in DDS.</div></div>","PeriodicalId":48997,"journal":{"name":"Primary Care Diabetes","volume":"20 1","pages":"Pages 21-29"},"PeriodicalIF":2.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145395170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mortality in offspring of women with type 1 diabetes during pregnancy","authors":"Erik Somersalo ,&nbsp;Cedric Korpijaakko ,&nbsp;Mia D. Eriksson ,&nbsp;Miira M. Klemetti ,&nbsp;Hannu Kautiainen ,&nbsp;Johan G. Eriksson ,&nbsp;Merja K. Laine","doi":"10.1016/j.pcd.2025.12.004","DOIUrl":"10.1016/j.pcd.2025.12.004","url":null,"abstract":"<div><h3>Aims</h3><div>Fetal and neonatal complications are common in pregnancies affected by maternal type 1 diabetes. The aim of this study is to investigate whether type 1 diabetes during pregnancy is reflected in offspring long-term mortality during a follow-up of up to 30 years.</div></div><div><h3>Methods</h3><div>This register-based follow-up study included 1762 offspring of women with type 1 diabetes (cases) and 8810 offspring of women without diabetes (controls). Time and causes of death between 1988 and 2018 were obtained from Statistics Finland. Clinical characteristics at birth of study participants and their mothers were obtained from the Finnish Medical Birth Register.</div></div><div><h3>Results</h3><div>Cases had an 1,67 times higher mortality than controls during the 30-year follow-up period (crude HR 1.67 [95 % CI: 1.01–2.77]), with a median follow-up of 21 years (IQR 15–28). Cases possessed an adverse risk-profile at the neonatal stage. Endocrine, nutritional and metabolic diseases (IRR 5.02/100 000 person years [95 % CI 1.01–24.88]), and diseases of the nervous system (IRR 5.03/100 000 person years [95 % CI 1.16–21.82]) were overrepresented as the cause of death in this group.</div></div><div><h3>Conclusions</h3><div>These findings suggest that maternal type 1 diabetes during pregnancy is associated with higher mortality during a 30-year follow-up.</div></div>","PeriodicalId":48997,"journal":{"name":"Primary Care Diabetes","volume":"20 1","pages":"Pages 127-132"},"PeriodicalIF":2.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145795552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of smart watch mobile application on the risk treatment of type 2 diabetes mellitus (iSMART-DM)","authors":"Min Kyoung Jang,&nbsp;Yun Kyung Cho,&nbsp;Jung Yoon Moon,&nbsp;Se Hee Min,&nbsp;Ju Hee Hwang,&nbsp;Chang Hee Jung","doi":"10.1016/j.pcd.2025.10.008","DOIUrl":"10.1016/j.pcd.2025.10.008","url":null,"abstract":"<div><div>Mobile health (mHealth) interventions incorporating smartwatches and personalized coaching show promise in improving diabetes self-management. Although studies report modest glycemic benefits and behavioral improvements from app-based interventions, real-world data from East Asian populations remain limited.</div></div><div><h3>Aims</h3><div>To evaluate the effectiveness of a smartwatch-based, app-linked lifestyle intervention (iSMART-DM) in improving glycemic control and self-care behavior in patients with non-insulin-treated type 2 diabetes mellitus (T2DM).</div></div><div><h3>Methods</h3><div>In a 12-week, open-label randomized controlled trial, 80 adults with T2DM were randomized in a 2:1 ratio to an intervention group (n = 54; smartwatch + mobile app + structured education) or a control group (n = 26; structured education alone). The primary endpoint was the change in glycated hemoglobin (HbA1c). Secondary endpoints included fasting plasma glucose (FPG), HbA1c target attainment (&lt;6.5 %), and changes in self-care behavior scores using the Summary of Diabetes Self-Care Activities Questionnaire (SDSCA-K). Satisfaction and adherence to the digital health intervention were also assessed.</div></div><div><h3>Results</h3><div>After 12 weeks, the mean HbA1c change was −0.14 % and −0.13 % in the intervention and control groups, respectively (p = 0.837). No significant differences were observed in FPG change or HbA1c target attainment. However, the intervention group showed significantly greater improvement in SDSCA-K scores (+9.7 points; 95 % CI 4.0–15.6; p = 0.001), particularly in diet and physical activity. User satisfaction with the mobile platform was high, with &gt; 85 % reporting a positive effect on daily health management.</div></div><div><h3>Conclusions</h3><div>Although short-term glycemic control showed no significant difference, the smartwatch-based mobile intervention significantly enhanced self-care behaviors in patients with T2DM. These findings highlight the behavioral benefits of wearable-integrated mHealth platforms and support their broader application in lifestyle modification strategies</div></div>","PeriodicalId":48997,"journal":{"name":"Primary Care Diabetes","volume":"20 1","pages":"Pages 47-52"},"PeriodicalIF":2.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145380553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of pay-for-performance programs on hospitalization risks in subjects with type 1 diabetes mellitus: A nationwide cohort study","authors":"Yun-Kai Yeh ,&nbsp;Fu-Shun Yen ,&nbsp;James Cheng-Chung Wei ,&nbsp;Yi-Ting Tsai ,&nbsp;Heng-Jun Lin ,&nbsp;Ying-Hsiu Shih ,&nbsp;Chih-Cheng Hsu ,&nbsp;Chii-Min Hwu","doi":"10.1016/j.pcd.2025.11.011","DOIUrl":"10.1016/j.pcd.2025.11.011","url":null,"abstract":"<div><h3>Aims</h3><div>This retrospective cohort study aimed to investigate the impact of pay-for-performance programs (P4P) on hospitalization rates in individuals with type 1 diabetes mellitus (T1D).</div></div><div><h3>Methods</h3><div>Using propensity score matching, we recruited 625 pairs of individuals with T1D with and without P4P care from the National Health Insurance Research Database of Taiwan between January 1, 2006, and December 31, 2018. The study used a multivariable Cox regression model to compare the risks of hospitalization for various reasons in individuals with T1D with and without P4P care.</div></div><div><h3>Results</h3><div>Individuals with T1D receiving pay-for-performance (P4P) care demonstrated a significantly lower risk of all-cause hospitalization (adjusted hazard ratio [aHR] 0.63, 95 % confidence interval [CI] 0.54–0.73). This reduction was particularly notable for hospitalizations related to glucose management or metabolic disorders, infectious diseases, pneumonia, circulatory and respiratory system diseases, and mental health, compared with those not receiving P4P care. However, no significant differences were observed in hospitalization risks for hyperglycemic crisis, severe hypoglycemia, or injury between individuals with and without P4P care.</div></div><div><h3>Conclusions</h3><div>This nationwide cohort study found that P4P participation was associated with a lower risk of hospitalization in individuals with type 1 diabetes.</div></div>","PeriodicalId":48997,"journal":{"name":"Primary Care Diabetes","volume":"20 1","pages":"Pages 68-73"},"PeriodicalIF":2.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145644130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Time-restricted eating and circadian rhythms: A new frontier in diabetes and obesity management","authors":"Sammra Maqsood ,&nbsp;Saiqa Amjad ,&nbsp;Faiyaz Ahmed ,&nbsp;Md Faruque Ahmad","doi":"10.1016/j.pcd.2025.11.004","DOIUrl":"10.1016/j.pcd.2025.11.004","url":null,"abstract":"<div><h3>Background</h3><div>A new feeding strategy called time-restricted eating (TRE) is being developed with the goal to remedy obesity and type 2 diabetes by aligning food consumption with the body's endogenous circadian rhythms. These rhythms regulate metabolic function on a daily 24-hour basis by exerting a significant impact on energy balance, lipid metabolism, and glucose homeostasis.</div></div><div><h3>Methods</h3><div>These databases were searched in an exhaustive manner: Scopus, Web of Science, Google Scholar, PubMed, Saudi Digital Library, and the Cochrane Library; the search was widened until January 2025. Essential search terms were: dieting on time constraint, metabolic health, the circadian rhythm, obesity, and diabetes.</div></div><div><h3>Results</h3><div>To optimize metabolic health, TRE takes advantage of circadian rhythms by restricting daily calorie consumption to a specified time window. TRE has been shown in clinical trials to enhance weight loss, insulin sensitivity, and glucose metabolism. Clinical evidence indicates that TRE can alter the disease trajectory of obese patients as well as patients with type 2 diabetes. The psychological and behavioral determinants of compliance with this intervention are also addressed in this review.</div></div><div><h3>Conclusion</h3><div>For the control of metabolic disease, TRE holds promise. For more insight into the therapeutic benefit of TRE, future studies should investigate its possible combination with individualized nutritional regimens and its long-term impact on metabolic and psychological health.</div></div>","PeriodicalId":48997,"journal":{"name":"Primary Care Diabetes","volume":"20 1","pages":"Pages 1-12"},"PeriodicalIF":2.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145590610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The U.S. diabetes belt and factors explaining the excess risk: Multifactorial modeling and machine learning analysis","authors":"Longjian Liu ,&nbsp;Nathalie S. May ,&nbsp;Yuwei Hou ,&nbsp;Jingyi Shi ,&nbsp;Edward J. Gracely ,&nbsp;Arthur L. Frank ,&nbsp;Howard J. Eisen","doi":"10.1016/j.pcd.2025.12.001","DOIUrl":"10.1016/j.pcd.2025.12.001","url":null,"abstract":"<div><h3>Aim</h3><div>Research on the epidemiology of diabetes mellitus (DM) has identified a geographically distinct region in the United States (U.S.) known as the diabetes belt (DM Belt), which represents a significant public health concern. This study aimed to examine the factors contributing to the increased risk of DM in the DM Belt compared to the non-DM Belt.</div></div><div><h3>Methods</h3><div>Data were analyzed from 398,243 adults aged ≥ 18 years who participated in the 2019 Behavior Risk Factor Surveillance System. DM status was based on participants’ self-reported physician-diagnosed DM. The DM Belt was defined at the state level according to the U.S. Center for Disease Control and Prevention’s classification. Logistic regression (LR) was used to estimate odds ratios for DM and assess the excess DM risk in the DM Belt versus the non-DM Belt. Random Forest (RF) and stepwise LR were employed to identify and rank key contributors to the excess DM risk.</div></div><div><h3>Results</h3><div>Residents of the DM Belt had a significantly higher prevalence of DM than those in the non-DM Belt (age-sex-adjusted rate: 12.5 % versus 10.5 %, p &lt; 0.001). Low socioeconomic status (SES), physical inactivity, and hypertension were identified as the top three factors explaining the excess DM risk in the DM Belt.</div></div><div><h3>Conclusions</h3><div>These findings underscore the importance of an integrated approach to improving SES, promoting healthy behaviors, managing chronic conditions for reducing DM risk. Addressing these factors can help mitigate health disparities in DM risk across the U.S.</div></div>","PeriodicalId":48997,"journal":{"name":"Primary Care Diabetes","volume":"20 1","pages":"Pages 99-105"},"PeriodicalIF":2.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145746569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantitative analysis of obesity predictors: Evidence from the Ravansar non-communicable disease (RaNCD) cohort study","authors":"Sharareh Rostam Niakan Kalhori ,&nbsp;Farid Najafi ,&nbsp;Seyed Mohammad Ayyoubzadeh ,&nbsp;Fatemeh Sadat Mirebrahimzadeh ,&nbsp;Soroush Heydari","doi":"10.1016/j.pcd.2025.10.007","DOIUrl":"10.1016/j.pcd.2025.10.007","url":null,"abstract":"<div><h3>Background</h3><div>Obesity is a significant public health issue, influenced by dietary, environmental, socioeconomic, and behavioral factors. Identifying these predictors is crucial for effective prevention strategies and policies. Cohort datasets provide a valuable resource for understanding long-term health trends and risk factors, offering robust insights into obesity determinants. This study aims to identify obesity predictors using cohort data from western Iran.</div></div><div><h3>Methods</h3><div>This study used the main phase and first follow-up data from the RaNCD cohort study, including 2064 participants with an obesity incidence of 18 %. We used a hybrid feature selection approach combining filter and wrapper methods using Linear Regression (LR) and Decision Tree (DT) algorithms. Training, testing, and evaluation were performed in Jupyter Notebook using Python 3.12.</div></div><div><h3>Results</h3><div>Fifty-seven variables were identified as significant predictors of BMI. Among them, anthropometric measures such as weight (r = 0.688) and waist circumference (r = 0.686) showed the strongest positive associations, while physical activity (MET, r = –0.151) had the strongest negative correlation. Anthropometric, demographic, and laboratory measures yielded the most accurate BMI predictions, whereas dietary and lifestyle factors contributed less, likely due to limited variability in self-reported data.</div></div><div><h3>Conclusion</h3><div>According to the results, anthropometric, demographic, and lab tests variables were three common predictors for obesity. Integrating these with basic clinical and laboratory data could improve early detection of metabolic risk in primary care screening programs. Public health programs should emphasize culturally tailored approaches to physical activity and dietary behavior to address obesity at the community level.</div></div>","PeriodicalId":48997,"journal":{"name":"Primary Care Diabetes","volume":"20 1","pages":"Pages 74-79"},"PeriodicalIF":2.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145369423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}