Background/Aims: Obesity is associated with several gastrointestinal (GI) disorders and has been identified as a potential risk factor for various GI symptoms. Bowel frequency is an important indicator of bowel function. However, the causal link between obesity and gastrointestinal motility remains uncertain. This study aims to determine the causal effect of overall and central obesity on stool frequency. Methods: Four obesity-related anthropometric indicators–body mass index, body fat percentage, waist circumference (WC), and waist-tohip ratio (WHR)–were investigated. Individual-level baseline information from the UK Biobank was used to explore observational associations between obesity and stool frequency. Additionally, summary-level data from published genome-wide association studies were subjected to two-sample Mendelian randomization (MR) analyses to examine causal associations. Results: For all 4 indicators of obesity, higher levels of obesity were associated with more frequent bowel movements after adjusting for demographic characteristics, lifestyle, and dietary factors. After rigorous screening, 482 body mass index single nucleotide polymorphisms (SNPs), 7 body fat percentage SNPs, 48 WC SNPs, and 287 WHR SNPs were identified as instrument variables for MR analysis. The MR results were generally consistent with observational findings, proving that the associations observed in the overall obesity indicators were causal. For central obesity, the association between WHR and stool frequency remained consistent in both analysis phases, whereas WC showed a multidirectional association. Conclusions Obesity-related anthropometric indicators were causally associated with increased stool frequency in the overall and central obesity groups. Weight loss could be a potential approach to improve gastrointestinal regularity in individuals with obesity.

Background/Aims: Obesity is associated with several gastrointestinal (GI) disorders and has been identified as a potential risk factor for various GI symptoms. Bowel frequency is an important indicator of bowel function. However, the causal link between obesity and gastrointestinal motility remains uncertain. This study aims to determine the causal effect of overall and central obesity on stool frequency. Methods: Four obesity-related anthropometric indicators–body mass index, body fat percentage, waist circumference (WC), and waist-tohip ratio (WHR)–were investigated. Individual-level baseline information from the UK Biobank was used to explore observational associations between obesity and stool frequency. Additionally, summary-level data from published genome-wide association studies were subjected to two-sample Mendelian randomization (MR) analyses to examine causal associations. Results: For all 4 indicators of obesity, higher levels of obesity were associated with more frequent bowel movements after adjusting for demographic characteristics, lifestyle, and dietary factors. After rigorous screening, 482 body mass index single nucleotide polymorphisms (SNPs), 7 body fat percentage SNPs, 48 WC SNPs, and 287 WHR SNPs were identified as instrument variables for MR analysis. The MR results were generally consistent with observational findings, proving that the associations observed in the overall obesity indicators were causal. For central obesity, the association between WHR and stool frequency remained consistent in both analysis phases, whereas WC showed a multidirectional association. Conclusions Obesity-related anthropometric indicators were causally associated with increased stool frequency in the overall and central obesity groups. Weight loss could be a potential approach to improve gastrointestinal regularity in individuals with obesity.

Background/Aims: Obesity is associated with several gastrointestinal (GI) disorders and has been identified as a potential risk factor for various GI symptoms. Bowel frequency is an important indicator of bowel function. However, the causal link between obesity and gastrointestinal motility remains uncertain. This study aims to determine the causal effect of overall and central obesity on stool frequency. Methods: Four obesity-related anthropometric indicators–body mass index, body fat percentage, waist circumference (WC), and waist-tohip ratio (WHR)–were investigated. Individual-level baseline information from the UK Biobank was used to explore observational associations between obesity and stool frequency. Additionally, summary-level data from published genome-wide association studies were subjected to two-sample Mendelian randomization (MR) analyses to examine causal associations. Results: For all 4 indicators of obesity, higher levels of obesity were associated with more frequent bowel movements after adjusting for demographic characteristics, lifestyle, and dietary factors. After rigorous screening, 482 body mass index single nucleotide polymorphisms (SNPs), 7 body fat percentage SNPs, 48 WC SNPs, and 287 WHR SNPs were identified as instrument variables for MR analysis. The MR results were generally consistent with observational findings, proving that the associations observed in the overall obesity indicators were causal. For central obesity, the association between WHR and stool frequency remained consistent in both analysis phases, whereas WC showed a multidirectional association. Conclusions Obesity-related anthropometric indicators were causally associated with increased stool frequency in the overall and central obesity groups. Weight loss could be a potential approach to improve gastrointestinal regularity in individuals with obesity.

In recent years, cardiovascular disease has become a common disease. With the development of machine learning and big data technologies, the processing ability of electrocardiogram (ECG) signals has been greatly enhanced through new computer technologies, enabling the auxiliary diagnosis technology for cardiovascular disease (CVD) to achieve new improvements. This article discusses the application of machine learning in ECG processing, especially in the auxiliary diagnosis of diseases. Firstly, the conventional signal preprocessing methods are introduced, and then the EEG signal processing methods based on feature extraction and fuzzy classification are explored. Secondly, the application of auxiliary diagnosis in CVD is further summarized. Finally, the advantages and disadvantages of the two methods are analyzed, and based on this, a design of an auxiliary diagnostic system compatible with the two methods is proposed, providing a new perspective for similar applied researches in the future.
Machine Learning ; Cardiovascular Diseases/diagnosis* ; Humans ; Electrocardiography ; Signal Processing, Computer-Assisted ; Diagnosis, Computer-Assisted ; Fuzzy Logic ; Electroencephalography

Objective:Based on"the System of Health Account 2011",it aimed to analyze the differences and causes of the medical economic burden between domestic and foreign population,and provide reference for the medical economic risk protection policies in China.Methods:Data of recurrent health expenditure of China and OECD member states were collected and descriptive statistical analysis was used to explore the relationship between the population's economic burden of medical treatment and medical security system and health service system.Results:In 2020,the average proportion of personal health expenditure in household con-sumption expenditure in OECD member countries was 3%,and the proportion in China was 5.24%.In China,public financing ac-counted for 54.81%of recurrent health expenses,which was lower than the average of OECD member states.Personal health expendi-ture of OECD member states was mainly spent on medical supplies and outpatient services,and China's personal health expenditure was mainly spent on outpatient services and inpatient services.Conclusion:Difference of medical security system is the important factor of the uneven medical burden.An appropriate health service delivery system is the basis to reduce the medical economic bur-den,a perfect hierarchical medical service system can guide the demand for medical service,and the collaborative chain of"pre-vention-diagnosis-control-care-rehabilitation"is fundamental to alleviate the medical economic burden.

Objective:Clarifying the comorbidity patterns of chronic disease and its distribution of catastrophic health expenditure in the elderly,in order to provide scientific data support for the development of chronic disease management strategies in various regions.Methods:Data were selected from China Health and Retirement Survey.Latent class model and Geoda were used to analyze the mode of chronic disease comorbidities in the elderly and the spatial distribution of catastrophic health expenditures.Results:The comorbidity pattems of chronic diseases in the elderly included circulatory and metabolic diseases,digestive disease,skeletal diseases,respiratory diseases,tumors,digestive and psychiatric diseases,and multisystem diseases.The incidence of catastrophic health expenditure with chronic disease comorbidities was 30.12％,and Moran's I value was 0.854(P＜0.05),indicating spatial autocorrelation.Qinghai,Inner Mongolia and Tianjin etc.were high-high areas,while Liaoning,Jilin and Zhejiang etc.were low-low areas.Conclusion:The occurrence of catastrophic health expenditures was characterized by sociodemographic differences and regional and comorbidity pattems of inequality.It is suggested that we should pay more attention to the management of chronic diseases,dynamically adjust the old-age chronic disease insurance policy and explore medical security system with a comorbidity model.

Objective:Based on"the System of Health Account 2011",it aimed to analyze the differences and causes of the medical economic burden between domestic and foreign population,and provide reference for the medical economic risk protection policies in China.Methods:Data of recurrent health expenditure of China and OECD member states were collected and descriptive statistical analysis was used to explore the relationship between the population's economic burden of medical treatment and medical security system and health service system.Results:In 2020,the average proportion of personal health expenditure in household con-sumption expenditure in OECD member countries was 3%,and the proportion in China was 5.24%.In China,public financing ac-counted for 54.81%of recurrent health expenses,which was lower than the average of OECD member states.Personal health expendi-ture of OECD member states was mainly spent on medical supplies and outpatient services,and China's personal health expenditure was mainly spent on outpatient services and inpatient services.Conclusion:Difference of medical security system is the important factor of the uneven medical burden.An appropriate health service delivery system is the basis to reduce the medical economic bur-den,a perfect hierarchical medical service system can guide the demand for medical service,and the collaborative chain of"pre-vention-diagnosis-control-care-rehabilitation"is fundamental to alleviate the medical economic burden.

Objective:Clarifying the comorbidity patterns of chronic disease and its distribution of catastrophic health expenditure in the elderly,in order to provide scientific data support for the development of chronic disease management strategies in various regions.Methods:Data were selected from China Health and Retirement Survey.Latent class model and Geoda were used to analyze the mode of chronic disease comorbidities in the elderly and the spatial distribution of catastrophic health expenditures.Results:The comorbidity pattems of chronic diseases in the elderly included circulatory and metabolic diseases,digestive disease,skeletal diseases,respiratory diseases,tumors,digestive and psychiatric diseases,and multisystem diseases.The incidence of catastrophic health expenditure with chronic disease comorbidities was 30.12％,and Moran's I value was 0.854(P＜0.05),indicating spatial autocorrelation.Qinghai,Inner Mongolia and Tianjin etc.were high-high areas,while Liaoning,Jilin and Zhejiang etc.were low-low areas.Conclusion:The occurrence of catastrophic health expenditures was characterized by sociodemographic differences and regional and comorbidity pattems of inequality.It is suggested that we should pay more attention to the management of chronic diseases,dynamically adjust the old-age chronic disease insurance policy and explore medical security system with a comorbidity model.

Objective:Based on"the System of Health Account 2011",it aimed to analyze the differences and causes of the medical economic burden between domestic and foreign population,and provide reference for the medical economic risk protection policies in China.Methods:Data of recurrent health expenditure of China and OECD member states were collected and descriptive statistical analysis was used to explore the relationship between the population's economic burden of medical treatment and medical security system and health service system.Results:In 2020,the average proportion of personal health expenditure in household con-sumption expenditure in OECD member countries was 3%,and the proportion in China was 5.24%.In China,public financing ac-counted for 54.81%of recurrent health expenses,which was lower than the average of OECD member states.Personal health expendi-ture of OECD member states was mainly spent on medical supplies and outpatient services,and China's personal health expenditure was mainly spent on outpatient services and inpatient services.Conclusion:Difference of medical security system is the important factor of the uneven medical burden.An appropriate health service delivery system is the basis to reduce the medical economic bur-den,a perfect hierarchical medical service system can guide the demand for medical service,and the collaborative chain of"pre-vention-diagnosis-control-care-rehabilitation"is fundamental to alleviate the medical economic burden.

Objective:Clarifying the comorbidity patterns of chronic disease and its distribution of catastrophic health expenditure in the elderly,in order to provide scientific data support for the development of chronic disease management strategies in various regions.Methods:Data were selected from China Health and Retirement Survey.Latent class model and Geoda were used to analyze the mode of chronic disease comorbidities in the elderly and the spatial distribution of catastrophic health expenditures.Results:The comorbidity pattems of chronic diseases in the elderly included circulatory and metabolic diseases,digestive disease,skeletal diseases,respiratory diseases,tumors,digestive and psychiatric diseases,and multisystem diseases.The incidence of catastrophic health expenditure with chronic disease comorbidities was 30.12％,and Moran's I value was 0.854(P＜0.05),indicating spatial autocorrelation.Qinghai,Inner Mongolia and Tianjin etc.were high-high areas,while Liaoning,Jilin and Zhejiang etc.were low-low areas.Conclusion:The occurrence of catastrophic health expenditures was characterized by sociodemographic differences and regional and comorbidity pattems of inequality.It is suggested that we should pay more attention to the management of chronic diseases,dynamically adjust the old-age chronic disease insurance policy and explore medical security system with a comorbidity model.