BMC Public Health最新文献

{"title":"How many children have parents with gambling disorder - a Germany-based estimate.","authors":"Nina Stefan, Larissa Schwarzkopf, Sven Buth, Gerhard Meyer, Andreas M Bickl","doi":"10.1186/s12889-025-23520-7","DOIUrl":"10.1186/s12889-025-23520-7","url":null,"abstract":"<p><strong>Background: </strong>Parental gambling disorder has detrimental financial, psychological, physiological, familial, and behavioral implications for the offspring, making these children highly vulnerable. In Germany, population-based estimates on how many minor children have parents with gambling disorder are lacking; thus, the immediacy of need for corresponding (public) health care policies remains unknown.</p><p><strong>Methods: </strong>Based on the population-representative German Gambling Survey 2023, we estimated the number of children having parents with gambling disorder, including estimates for rates at each parental gambling disorder severity level (mild, moderate, severe). Both cohabiting children and separate living children were considered. To extrapolate lower and upper bounds of estimates, data on number of parents in the household and average number of children was combined with official population statistics.</p><p><strong>Results: </strong>Of 282 participants with gambling disorder, 46.8% (n = 132) cohabit with 1.55 children on average; 16.7% (n = 47) are parents of 1.51 separate living children on average. Therefore, in Germany 574,079 to 604,966 children have a parent with gambling disorder, with about 84.0% of them (482,076 to 508,712) cohabiting with the gambling parent. The likelihood of cohabiting decreases with increasing gambling disorder severity (mild: 97.7%; moderate: 85.0%; severe: 72.2%).</p><p><strong>Discussion: </strong>In Germany about 1 in 25 children has a parent with gambling disorder. Given that parental gambling disorder is an established risk factor for developing own gambling problems, more comprehensive addiction care and health policy are needed to address this issue. Integrated care and counselling offers targeting both gambling parents and their children may be a promising starting point. Special attention should be paid to separate living children in these approaches.</p>","PeriodicalId":9039,"journal":{"name":"BMC Public Health","volume":"25 1","pages":"2166"},"PeriodicalIF":3.5,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12180145/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144332432","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":"Exposure to gender-based violence and the risk of hypertension, obesity, and anemia: a multilevel analysis of the 2017 Tajikistan demographic and health survey.","authors":"Shiva Raj Acharya","doi":"10.1186/s12889-025-23414-8","DOIUrl":"10.1186/s12889-025-23414-8","url":null,"abstract":"<p><strong>Background: </strong>Gender-based violence (GBV), including physical violence (PV), sexual violence (SV), and emotional violence (EV) in women, may influence both their physical and psychological health. Prior studies suggest a potential link between these forms of GBV and chronic health conditions, yet evidence remains inconsistent, particularly in low-resource settings. This study investigates the associations between PV, SV, and EV and the risk of hypertension, obesity, and anemia in Tajik women.</p><p><strong>Methods: </strong>Using data from the 2017 Tajikistan Demographic and Health Survey (TjDHS), 3,620 women aged 15-49 were analyzed. Outcome variables included hypertension (systolic pressure ≥ 140 mmHg or diastolic pressure ≥ 90 mmHg), obesity (BMI ≥ 27.5 kg/m²), and anemia (blood hemoglobin < 12 g/dl), classified based on WHO guidelines. Exposure variables included PV, SV, and EV, assessed using the Conflict Tactics Scale and categorized by severity scores and intensity levels. Multilevel-adjusted linear and logistic regression models were performed.</p><p><strong>Results: </strong>The mean age of the participants was 32.64 ± 8.52 years. The prevalence of lifetime exposure to overall GBV, PV, SV, and EV was 32.1%, 26.9%, 1.7%, and 15.3%, respectively. The prevalence of hypertension, obesity, and anemia was 10.2%, 27.2%, and 44.0%, respectively. Lifetime exposure to EV was significantly associated with increased odds of obesity (OR, 95% CI: 1.27, 1.04-1.54), whereas moderate-intensity EV exposure was inversely associated with anemia (OR, 95% CI: 0.75, 0.56-0.98). Higher PV severity scores were linked to lower systolic (β, 95% CI: -0.53, -0.72 to -0.34) and diastolic blood pressure (β, 95% CI: -0.17, -0.31 to -0.04). Women in the poorest wealth quintiles, with no education, those who smoke, the unemployed, and those with husbands/partners who consume alcohol were significantly at an increased risk of GBV.</p><p><strong>Conclusion: </strong>Of the three types of GBV, EV demonstrated a substantial association with obesity and anemia, with differential impacts based on the intensity level. PV severity scores showed an inverse relationship with blood pressure. The findings suggest that EV might be a significant independent risk factor for obesity. Therefore, prioritizing EV in integrated interventions addressing both GBV prevention and chronic conditions is crucial for improving women's health outcomes.</p><p><strong>Clinical trial number: </strong>Not applicable.</p>","PeriodicalId":9039,"journal":{"name":"BMC Public Health","volume":"25 1","pages":"2165"},"PeriodicalIF":3.5,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12164065/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144293278","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":"Correction to: Methods and participant characteristics in the Cancer risk in vegetarians consortium: a cross-sectional analysis across 11 prospective studies.","authors":"Yashvee Dunneram, Jia Yi Lee, Cody Z Watling, Gary E Fraser, Fayth Miles, Dorairaj Prabhakaran, Krithiga Shridhar, Dimple Kondal, Viswanathan Mohan, Mohammed K Ali, Kabayam M Venkat Narayan, Nikhil Tandon, Tammy Y N Tong, Tina H T Chiu, Ming-Nan Lin, Chin-Lon Lin, Hsin-Chou Yang, Yu-Jen Liang, Darren C Greenwood, Huaidong Du, Zhengming Chen, Canqing Yu, Maria G Kakkoura, Gillian K Reeves, Keren Papier, Sarah Floud, Rashmi Sinha, Linda M Liao, Erikka Loftfield, Janet E Cade, Timothy J Key, Aurora Perez-Cornago","doi":"10.1186/s12889-025-22844-8","DOIUrl":"10.1186/s12889-025-22844-8","url":null,"abstract":"","PeriodicalId":9039,"journal":{"name":"BMC Public Health","volume":"25 1","pages":"2164"},"PeriodicalIF":3.5,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12153113/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144274153","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 training needs and influencing factors among personnel at centers for disease control and prevention in northeast China: a cross-sectional study framed by SDT and TPB using machine learning techniques.","authors":"Kexin Wang, Peng Wang, Min Wei, Yanping Wang, Huan Liu, Ruiqian Zhuge, Qunkai Wang, Nan Meng, Yiran Gao, Yuxuan Wang, Lijun Gao, Jingjing Liu, Xin Zhang, Mingli Jiao, Qunhong Wu","doi":"10.1186/s12889-025-23393-w","DOIUrl":"10.1186/s12889-025-23393-w","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Objectives: &lt;/strong&gt;Training public health personnel is crucial for enhancing the capacity of public health systems. However, existing research often falls short in providing a comprehensive theoretical framework and fails to account for the intricate interplay of multi-dimensional factors in public health. This study aims to identify knowledge and skill gaps at both individual and organizational levels, and to explore multi-dimensional factors influencing training needs within the theoretical frameworks of the Theory of Planned Behavior and Self-Determination Theory.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This cross-sectional study used stratified cluster sampling to conduct an online survey among personnel at the Centers for Disease Control and Prevention from Heilongjiang Province, Jilin Province, Liaoning Province, and Inner Mongolia Autonomous Regions during May 2023. A total of 11,912 valid questionnaires were collected. Latent Class Analysis was used to analyze competency subgroups covering professional abilities, general abilities, and management abilities. Boruta algorithm was used to select feature and improve the performance of the following predictive models. Logistic regression, random forest, least absolute shrinkage and selection operator (LASSO), and extreme gradient boosting (XGBoost) were used to predict training needs and explore the impact of various multi-dimensional factors. SHapley Additive exPlanations (SHAP) were used to explain the output of the optimal machine learning model.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;This study identified the four subgroups of competency patterns, including novice (25.3%), public health experts (15.1%), potential expansion talents (24.7%), and versatile talents (34.9%). Boruta algorithm identified 9 confirmed variables, 3 tentative variables, and 30 rejected variables. Compared with other models, XGBoost model demonstrated the best performance. The value of AUC was 0.702, and the value of accuracy, precision, recall, and F1 score was 0.6485, 0.6564, 0.6301, and 0.6430, respectively. The SHAP based on XGBoost model indicated on-job training satisfaction had a strong association with training needs among public health personnel. Self-improvement needs, college education satisfaction, workload, competency patterns, and team cohesion were also important factors.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Intrinsic motivation is the key factor influencing the training needs of public health personnel. When formulating training plans, priority should be given to how to improve on-job training satisfaction and design a more targeted competency patterns tailored training curriculum. Moreover, organizational incentives aimed at motivating trainees and integrating career development goals into training program design are important. Therefore, setting training priorities becomes key to help ensure that training programs are targeted and effective, thereby promoting individual and organizational career develop","PeriodicalId":9039,"journal":{"name":"BMC Public Health","volume":"25 1","pages":"2157"},"PeriodicalIF":3.5,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12150469/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144265153","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":"Impact of meteorological conditions and air pollution on the incidence of carbon monoxide poisoning: a retrospective analysis in northern China.","authors":"Rui Ma, Xiaoshuang Xia, Juanjuan Xue, Yongyuan Yao, Aihua Xin, Shuli Song, Lin Wang, Xin Li","doi":"10.1186/s12889-025-23403-x","DOIUrl":"10.1186/s12889-025-23403-x","url":null,"abstract":"<p><strong>Background: </strong>Carbon monoxide (CO) poisoning remains a critical public health issue, particularly in residential settings during colder months when heating practices can lead to indoor CO accumulation. The relationship between meteorological conditions, air pollutants, and CO poisoning remains poorly understood. This study aims to investigate the impact of weather factors and air pollution on the incidence of CO poisoning, with a focus on identifying risk factors associated with severe outcomes such as coma.</p><p><strong>Methods: </strong>We conducted a retrospective study of CO poisoning cases in a northern Chinese urban area, categorizing patients into coma and non-coma groups. We analyzed clinical characteristics, including age, gender, comorbidities, time of hospital admission, and severity of poisoning. Meteorological data, including temperature, relative humidity, wind speed, and 24-hour temperature changes, as well as air quality indices (AQI), concentrations of CO, NO₂, SO₂, O₃, PM2.5, and PM10, were collected and analyzed for their correlation with CO poisoning incidence.</p><p><strong>Results: </strong>The investigation revealed significant correlations between CO poisoning and patient characteristics and environmental factors. Notably, patients in the coma group were significantly older (P = 0.003) and predominantly presented at the hospital between 6:00 AM and 11:59 AM. Atmospheric CO concentration emerged as a critical risk factor, demonstrating nearly a twofold increase in poisoning risk per 1 mg/m³ increment (OR = 2.001, 95% CI: 1.105-3.622). Meteorological parameters exhibited complex interactions with poisoning susceptibility: mean temperature showed a pronounced protective effect (OR = 0.893, 95% CI: 0.873-0.914, P < 0.001), with each unit decrease corresponding to a 10.7% increase in risk. Temperature dynamics further amplified this risk, with 24-hour temperature fluctuations significantly increasing poisoning susceptibility by 25.7% per unit change (OR = 1.257, 95% CI: 1.174-1.344, P < 0.001), underscoring the multifaceted nature of environmental influences on CO poisoning occurrence.</p><p><strong>Conclusions: </strong>Older age and faster hospital admission are associated with more severe CO poisoning outcomes. Meteorological and environmental pollutant factors, including low temperatures, 24-hour temperature fluctuations and elevated CO concentrations, increase the risk of CO poisoning.Public health interventions, such as safety education, improved ventilation, install CO concentration alarm and early warnings during extreme weather, could significantly reduce the incidence of CO poisoning, particularly in colder months with adverse meteorological conditions.</p>","PeriodicalId":9039,"journal":{"name":"BMC Public Health","volume":"25 1","pages":"2155"},"PeriodicalIF":3.5,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12150491/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144265219","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":"Mental health and energy drink consumption among Norwegian adolescents; a cross-sectional study.","authors":"Siri Kaldenbach, Marja Leonhardt, Tor A Strand, Mads Holten-Andersen","doi":"10.1186/s12889-025-23432-6","DOIUrl":"10.1186/s12889-025-23432-6","url":null,"abstract":"<p><strong>Background: </strong>Energy drinks (ED) are marketed as boosters of mental and physical health, but few studies have looked at the mental health of adolescents who consume large amounts of ED. The current study aims to investigate the association between symptoms of depression and ED consumption among Norwegian adolescents between 2017 and 2022.</p><p><strong>Methods: </strong>Data from the Norwegian nationwide youth survey (Ungdata) with participants from lower and upper secondary schools was used. A total of 133,401 adolescents who participated between 2017 and 2022 were included. Multivariable Poisson regression models were used to calculate the relative risks and the corresponding 95% confidence intervals with symptoms of depression as the main outcome variable. The models have been controlled for the exposure variable (ED consumption) and the covariates; perceived everyday pressure, school-related stress, general self-efficacy next to other background variables.</p><p><strong>Results: </strong>The sample comprised 63,233 (47.5%) boys and 66,621 (52.5%) girls. In total, 2.9% consumed ED daily, 52.3% had consumed any ED while 44.7% had never consumed ED. 18.3% of the total sample had a high level of symptoms of depression. Moreover, when adjusted for all variables, any (RR: 1.23, CI: 1.20-1.26) and daily ED consumption (RR: 1.94, CI: 1.85-2.03) were associated with increased symptoms of depression.</p><p><strong>Conclusion: </strong>ED continues to be a popular beverage among Norwegian adolescents and regular consumption of ED is related to key elements of adolescents' symptoms of depression when adjusted by perceived everyday pressure, school-related stress and general self-efficacy. This study adds to the body of evidence linking regular ED consumption to mental health which is increasingly common among adolescents. Public health initiatives such as increasing public information or restricting ED sales to adolescents should be considered to reduce ED consumption among adolescents. Yet, further research is needed to understand the specific mechanisms of how ED and symptoms of depression are associated.</p>","PeriodicalId":9039,"journal":{"name":"BMC Public Health","volume":"25 1","pages":"2158"},"PeriodicalIF":3.5,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12150526/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144265222","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":"Seasonal variations in public perceptions of diphtheria in Northern Nigeria.","authors":"Abara Erim, Habibat Ohunene Lawal, Chizaram Anselm Onyeaghala, Chinenye Claire Chukwu-Mba, Olufunke Olayemi Ajibade, Ukamaka Gladys Okafor, Okechi Eberechukwu Nzedibe","doi":"10.1186/s12889-025-23427-3","DOIUrl":"10.1186/s12889-025-23427-3","url":null,"abstract":"<p><strong>Background: </strong>Diphtheria remains a significant public health concern in Nigeria, with over 20,000 suspected cases and more than 500 deaths reported during the 2022-2023 outbreak period, particularly concentrated in the northern regions. Understanding public perceptions and behavior regarding diphtheria, including symptoms, transmission, and vaccination across different seasons, is vital for developing effective interventions. This study aimed to evaluate seasonal variations in public awareness of diphtheria, including knowledge of its symptoms and information sources. Additionally, it sought to assess the perceived at-risk groups and attitudes toward diphtheria vaccination in the country.</p><p><strong>Methods: </strong>A cross-sectional survey was conducted among residents aged 18 years and older in Kano, Katsina, Bauchi, Yobe, Borno, Kaduna, Jigawa, Kebbi, and the Federal Capital Territory (FCT). Data were collected by trained fieldworkers over 12 months via structured questionnaires divided into four sections: demographics, public awareness, perceived risk, and vaccination attitudes. Ethical approval was obtained, and verbal informed consent was secured from all participants. Data analysis involved descriptive statistics and statistical tests to examine associations between variables.</p><p><strong>Results: </strong>A total of 3,070 respondents participated in the study. Public awareness of common diphtheria symptoms such as fever (68.0%) and sore throat (60.5%) was high, whereas awareness of conjunctivitis (23.9%) was lower. Children under 5 years of age were consistently perceived as the most at-risk group (80.5%). The willingness to vaccinate against diphtheria remained high at 94.4%, with no significant seasonal variation (p-value 0.894; Chi-square test). Radio (53.1%) was identified as the primary information source, especially during the rainy season (54.6%). Seasonal variations in preventive and vaccination practices were minimal, indicating consistent public health behaviors throughout the year.</p><p><strong>Conclusion: </strong>This study highlights the importance of maintaining robust public health education campaigns, leveraging both traditional and digital media to sustain high awareness and vaccination rates for public health interventions. Based on our findings, we recommend implementing targeted school-based health education programs and strengthening partnerships with community health workers to enhance diphtheria awareness, especially among caregivers of young children. Understanding sociodemographic and seasonal contexts is crucial for effective public health interventions, ensuring that at-risk groups are adequately protected.</p>","PeriodicalId":9039,"journal":{"name":"BMC Public Health","volume":"25 1","pages":"2146"},"PeriodicalIF":3.5,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12150561/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144265227","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":"Socioeconomic factors predictive of access delays in oncology.","authors":"Allen M Chen","doi":"10.1186/s12889-025-23398-5","DOIUrl":"10.1186/s12889-025-23398-5","url":null,"abstract":"<p><strong>Purpose: </strong>To identify demographic and socioeconomic factors predictive of access delays in patients referred for radiation oncology services.</p><p><strong>Methods and materials: </strong>A prospective data registry of consecutive patients referred for initial consultation from October 2018 to April 2022 was reviewed. To evaluate access, the number of business days from referral to consultation was calculated. Demographic characteristics recorded included age, gender, race, language preference, and insurance status. Zip code data linked to a patient's residential address was used to classify socioeconomic status (SES) based on publicly available data on median household income. Descriptive statistics were presented to identify factors predictive of delays in the time from referral to consultation.</p><p><strong>Results: </strong>A total of 9,241 consecutive patients were referred and logged into the database during the 4-year period, of which 5,321 were scheduled, registered, and seen in the outpatient setting. Delays in access were associated with low SES and Black race (p < 0.05, for both). Three hundred and seventeen of the 1,203 patients (26%) in the lowest SES quartile had their appointments scheduled greater than 21 days from the time of referral compared to 482 of the 4,118 patients (12%) in the non-lowest quartile SES group (p < 0.001). Black patients were significantly less likely to have their appointments within 5 days compared to non-Black patients (17% versus 24%, p = 0.01). On multivariate analysis, the only variable independently associated with higher odds of appointment delays was SES (low-SES quartile versus non-low-SES quartile (OR = 3.98, 95% CI [2.01-7.92], p < 0.001).</p><p><strong>Conclusions: </strong>SES factors related to geographical zip code predict for access delays in radiation oncology care. Targeted interventions are urgently warranted for low SES groups residing in underserved communities.</p>","PeriodicalId":9039,"journal":{"name":"BMC Public Health","volume":"25 1","pages":"2153"},"PeriodicalIF":3.5,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12150564/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144265228","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":"Hybrid time series and machine learning models for forecasting cardiovascular mortality in India: an age specific analysis.","authors":"M Darshan Teja, G Mokesh Rayalu","doi":"10.1186/s12889-025-23318-7","DOIUrl":"10.1186/s12889-025-23318-7","url":null,"abstract":"<p><p>Cardiovascular disease (CVD) is a primary cause of death in India, accounting for a significant portion of the global CVD burden. This study looks at statistics on heart disease mortality from the Institute for Health Metrics and Evaluation (IHME) from 1990 to 2021, divided into five age groups: 0-5, 6-15, 16-49, 50-69, and 70 + . We used both classic ARIMA and hybrid models that combined ARIMA with machine learning techniques such as Random Forest, Support Vector Machine (SVM), XGBoost, and GARCH to anticipate mortality trends. Model performance was assessed using the Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). Across several age groups, the ARIMA + SVM model outperformed standalone ARIMA in terms of accuracy, with RMSE improvements of up to 15.6%. The 70 + population has the greatest mortality rates, highlighting the urgent need for focused healthcare treatments. These hybrid models are valuable tools for healthcare legislators in developing preventative programs, allocating resources effectively, and prioritizing treatment for high-risk age groups, especially the elderly, since they improve forecasting accuracy and offer interpretive insights. Given India's growing cardiovascular disease load, our results highlight how predictive analytics may support data-driven public health planning.</p>","PeriodicalId":9039,"journal":{"name":"BMC Public Health","volume":"25 1","pages":"2150"},"PeriodicalIF":3.5,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12150534/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144265218","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":"Associations of circadian syndrome with gout and hyperuricemia: a cross‑sectional analysis of NHANES 2007-2018.","authors":"Jun-Wei Ren, Jia-Hao Wang, Yun-Fei Xiao, Yun-Jin Bai, Ping Han","doi":"10.1186/s12889-025-23319-6","DOIUrl":"10.1186/s12889-025-23319-6","url":null,"abstract":"","PeriodicalId":9039,"journal":{"name":"BMC Public Health","volume":"25 1","pages":"2152"},"PeriodicalIF":3.5,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12150540/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144265154","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}