Clinical Value Of Sarcopenic Obesity And Physical Activity Patterns In Predicting The Risk Of Diabetes And Metabolic Syndrome

Background:With the rapid development of countries' economies and the improvement of living standards,bad lifestyles and accelerated aging,diabetes mellitus(DM)has become the third chronic non-communicable disease after cardiovascular disease and cancer.Spread across the globe,a serious threat to human health.The International Diabetes Federation(IDF)indicated that in 2017,among people aged 20-79,the number of diabetic patients is 425 million;and if the current rate of diabetes growth cannot be contained,this number will increase by 48%to 629 million by 2045.Metabolic syndrome is a group of clinical syndromes characterized by central obesity,elevated blood pressure,elevated fasting plasma glucose,and dyslipidemia.The five components of the metabolic syndrome are risk factors for most chronic non-communicable diseases(NCD),which are closely related to diabetes and cardiovascular disease(CVD).In recent years,with the economic development,metabolic syndrome,like other non-chronic diseases,has a tendency to increase hastily.Although the criteria used to diagnose metabolic syndrome vary in different countries,the prevalence of metabolic syndrome showed to increase worldwide.Diabetes and metabolic syndrome not only cause patients to suffer physical and mental pain,but also shorten the life span,and bring a heavy economic burden to the countries and the regions.Type 2 diabetes(T2DM)is a long-term metabolic disorder characterized by hyperglycemia,insulin resistance,and relative lack of insulin with many complications.However,in front of such a huge social and economic burden brought by T2DM and metabolic syndrome,the prevention of diabetes and metabolic syndrome and controlling the increase in the prevalence of diseases have become more cost-effective strategies.With the emphasis on exercise therapy and the prevention of type 2 diabetes and metabolic syndrome,more and more people are aware of the importance of skeletal muscle and abdominal obesity for metabolism.The reduction in skeletal muscle mass has become a global problem with accompanying aging problem,and the reduction in bone mass is considered to be a risk factor for metabolic syndrome and cardiovascular disease.Considering skeletal muscle one of the main sites of glucose uptake and utilization,a decrease in muscle mass were proved to increase insulin resistance,thereby increasing the risk of T2DM and metabolic syndrome.According to reports,abdominal obesity is a high-risk factor not only for T2DM and metabolic syndrome,but also for CVD and fatty liver disease.Although widely used,the Body Mass Index(BMI)and the waist circumference(WC)are not precise parameters for abdominal obesity.Recent studies have shown that visceral fat area(VFA)can measure abdominal obesity more accurately and is a riskier factor for metabolic syndrome than WC or BMI.And increased VFA is associated with the elevated prevalence of metabolic syndrome and is the only best predictor of female metabolic syndromeAging is one of the more important risk factors for T2DM and metabolic syndrome.Aging is usually accompanied by a decrease in muscle mass and/or strength,also known as sarcopenia,with a consequent increase in visceral fat.Even without significant changes in BMI,an imbalance between skeletal muscle mass and visceral fat mass in the elderly can occur and may have synergistic effects on health outcomes including metabolic disorders,cardiovascular disease,and mortality.These metabolic imbalances are extreme in some people,and the resulting condition is a combination of obesity and sarcopenia,a condition known recently as"sarcopenic obesity." In the case of obesity,sarcopenia tends to increase the difficulty of physical function.Since skeletal muscle mass is closely related to systemic fat,an increase in skeletal muscle mass is usually accompanied by an increase in fat.Therefore,assessing the effects of sarcopenia on T2DM and metabolic syndrome may require consideration of visceral obesity.Considering the interaction between skeletal muscle mass loss and visceral fat elevation,we used the skeletal muscle mass to visceral fat area ratio(SVR)to study chronic diseases such as T2DM and metabolic syndrome,relationshipThere are still many unsolved problems in the current research on the relationship between SVR and T2DM and metabolic syndrome.First,the inconsistency of the population included in the studies.Although SVR is associated with metabolic syndrome in non-diabetic participants,their potential relationship between SVR and metabolic syndrome or T2DM in the general population remains unknown.Secondly,using the risk of T2DM and metabolic syndrome as an indicator to find the appropriate cut-off value of SVR can be used to prevent the onset of T2DM and metabolic syndrome and the progress of the disease earlier.Therefore,it is necessary to obtain SVR through research.Appropriate cut-point values are used to control blood glucose and blood lipid levels by early changes in poor lifestyle interventions,and only a small number of studies have been conducted on SVR.A lot of uncertainties about the relationship between SVR and chronic diseases still exist.To provide a scientific basis for preventing the occurrence of T2DM.more research is still needed in the future.In summary,in order to explore the relationship between SVR and T2DM or metabolic syndrome,we designed and implemented a cross-sectional study in the epidemiological survey population to verify the relationship between SVR and the risk of T2DM and metabolic syndrome,thus identifying the risk factors of T2DM and metabolic syndrome.Factors provide a new perspective view and more scientific evidence for further prevention of T2DM and metabolic syndrome by improving poor lifestyle habits to control abnormal blood glucose.blood lipids and blood pressure levels.Objective:1.Verify the relationship between SVR and the risk of T2DM and metabolic syndrome2.To explore the correlation between SVR and metabolic indicators related to T2DM and metabolic syndrome3.Estimate the cut-offs of SVR for discriminating incident T2DM and metabolic syndromeMethods:1.Study Design and ParticipantsThe present article reports on the data from a cross sectional study,which was obtained from residents in N ingyang County,Shandong Province.After exclusion,798 individuals were eligible for this study.The exclusion criteria are as follows:(1)suffering from severe systemic diseases,including malignant tumors or severe liver and kidney dysfunction;(2)pregnant women;(3)type 1 diabetes;(4)data incomplete.After excluding those who did not meet the criteria,a total of 798 individuals were included in the study.2.Data CollectionBlood samples were drawn after an overnight fast for at least 10 hours.Fasting total cholesterol,LDL,HDL and triglyceride were measured using an auto-analyzer(ARCHITECT c16000 System,Abbott Laboratories,IL,USA).Participants without a known history of diabetes underwent the oral glucose tolerance test(OGTT),and plasma glucose was measured at 0 hours(FPG)and 2 hours(2hPG)by the glucose oxidase method.3.Definition of glycemic status(1)diabetesGlycemic status was evaluated by standardized OGTT and was defined based on the World Health Organization(WHO)1999 criteria:NGT,FPG<6.1 mmol/L and 2hPG<7.8 mmol/L;diabetes,FPG>7.0 mmol/L and/or 2hPG?11.1 mmol/L;pre-diabetes was defined as meeting either of the following two criteria:a)6.1 mmol/L?FPG<7.0 mmol/L and 2hPG<11.1mmol/L;b)FPG<7.0 mmol/L and 7.8 mmol/L?2hPG<11.1 mmol/L.(2)metabolic syndromeMetabolic syndrome is defined if three or more of the following criteria are met:(1)abdominal obesity:waist circumference male?90 cm;female?85 cm(2)hyperglycemia:fasting blood glucose level 6.1 mmol/L or higher;OGTT 2-hour blood glucose level is 7.8 mmol/L or higher;diagnosis is diabetes(3)hypertension:blood pressure is 135/80 mmHg or higher;diagnosis is hypertension(4)high triglyceride:fasting plasma triglyceride is 1.7 mmol/L or higher(5)low HDL-C:fasting plasma HDL-C is lower than 1.04 mmol/L.(3)obesity and overweightOverweight is defined as a BMI of 24.0 kg/m2 to 27.9 kg/m2,and obesity is defined as a BMI of 28.0 kg/m2 or higher.4.Statistical analysisSPSS version 22.0 for Windows(Chicago,IL,USA)was used for statistical analyses.Multivariate Logistic regression analysis was used to estimate the odds ratios and 95%confidence intervals(CIs)of incident T2DM according to different SVR levels.To compare the risk of SVR on the development of T2DM and metabolic syndrome,univariate and multivariate Logistic regression analysis were included respectively.Receiver operatingcharacteristic analysis was used to compare the ability of each cholesterol index indiscriminating incident T2DM.The optimal cut-off values were identified as the point at which the value of "sensitivity + specificity-1"(Youden index)was maximum.Results:The basic characteristics of the eligible participants according to SVR quartiles(n =798,mean 40.12±10.23 age years)were shown.Men accounts for 35.0%of the total participants.Among the total subject population,the prevalence of T2DM and MS are 25.92%and 41.19%respectively.SVR values were divided into four groups by quartile based on our population,increasing from Q1 to Q4.The mean age decreased from Q1 to Q4 and there was significant difference by sex(p=0.005).BMI,HOMA-IR,TC,TG,LDL-C,FBG,2h-PG,WC,DBP decreased from Q1 to Q4,while a positive trend was showed in HDL-C.There were significant differences of the parameters above.No trend was showed in systolic blood pressure(SBP).The prevalence of T2DM and MS were also showed decreased trends with SVR increasing from Q1 to Q4.Considering that MS were diagnosed by the number of abnormal components,we analyzed the rate of MS comprised of different numbers of components.The prevalence of MS with different numbers of components were all reduced with SVR augmenting from Q1 to Q4.Significant differences were showed in the prevalence above when grouped by quartile of SVR.Consistently,the SVR levels were significantly higher in subjects without MS or T2DM compared to those with MS or T2DM.When compared SVR level in different groups according to the diagnosis of T2DM and MS,significant difference was stated in the comparisons.Furthermore,SVR was strongly inversely correlated with SBP,DBP,LDL,TC,TG,HOMA-IR and WC,especially BMI with r>0.5(all p<0.001),although the correlation is rather weak with HDL(r= 0.100),FPG(r=-0.227)and 2h-PG(r=-0.114).Logistic regression analysis was performed to evaluate the relation between SVR quartiles and T2DM and MS.As a result,with Q4 as the reference,the relative risks for T2DM were 2.43(95%CI:0.92-6.47)in Q3,and 3.18(95%CI:1.24-8.19)in Q2,and 9.88(95%Cl:4.11-23.72)in Q1(model 1).Meanwhile,the relative risk for MS with Q4 as the reference were 4.06(95%Cl:2.11-7.81)in Q3,and 8.22(95%CI:4.37-15.47)in Q2,and 12.95(95%Cl:6.92-24.23)in Q1(model 1).Univariate logistic regression was performed in Model 1.The results of analyses adjusted for age and sex(model 2)were similar.These results indicated that a decreased SVR was a risk factor for MS and T2DM.To evaluate the predictive performance of SVR for T2DM and MS,the AUC in ROC curve was calculated,which was 0.726[95%CI(0.669-0.782),p<0.001]for T2DM,and 0.730[95%CI(0.694-0.766),p<0.001].Conclusion:1.Metabolic index related to T2DM and metabolic syndrome(except HDL-C)increase with decreasing SVR,and HDL-C decreased with decreasing SVR.2.As SVR decreases,the prevalence of T2DM and metabolic syndrome increases respectively.3.Decreased SVR is an independent risk factor for T2DM and metabolic syndrome.Background:Diabetes and metabolic syndrome have become a serious burden on the global economy.While increasing the incidence of related cardiovascular and cerebrovascular diseases,the associated morbidity and mortality are also increasing simultaneously.Type 2 diabetes(T2DM)is a long-term metabolic disorder characterized by hyperglycemia,insulin resistance,and relative lack of insulin with many complications.A number of studies have shown that both T2 DM and metabolic syndrome show a trend of increasing prevalence with age.The mortality from chronic noncommunicable diseases is close to 30 million a year,and nearly 80% occur in low-and middle-income countries.In different populations,previous studies investigated risk factors for chronic noncommunicable diseases,including unhealthy eating habits,physical inactivity,and other behavioral and environmental factors.Physical inactivity(PI)refers to the failure to achieve the recommended level of healthy physical activity,that is,at least 30 minutes of regular,moderate-intensity physical activity,which is currently one of the major independent risk factors for chronic non-communicable diseases worldwide.Increasing physical activity has become one of the more important measures in the current interventions for chronic noncommunicable diseases.The latest Healthy People 2020 and the National Institute for Health and Care Excellence(NICE)guidelines specifically mention the addition of physical activity(PA)as an important component of disease management for cardiovascular disease,T2 DM and musculoskeletal related diseases.According to previous scholars,about 9% of global deaths were attributed to insufficient physical activity.Studies have shown that one out of every four adults in the world meets the criteria for insufficient physical activity.Globally,more than 80% of the youth population is in a state of physical inactivity.It turns out that people with insufficient physical activity are 20 to 30% more likely to die from active individuals than active individuals.At present,the world is striving to reduce the proportion of people with insufficient physical activity by 10% by the end of 2025.Although multiple methods can increase the total amount of physical activity,exercise is the best method compared.Countries around the world must develop interventions for insufficient physical activity to prevent and manage the development of chronic noncommunicable diseases.However,due to the diversity of physical activity and the difficulty in calculation of time,only a few studies focused on the relationship between physical activity and disease,especially in rural China.This cross-sectional study will use the International Physical Activity Questionnaire to objectively monitor the physical activity of middle-aged and elderly people,and analyze these individuals by assessing the components of T2 DM and metabolic syndrome,analyzing physical activity and T2 DM.and metabolic syndrome and its relationship between the components.By stratifying the total amount of physical activity,the total amount of physical activity appropriate for middle-aged and elderly people is further recommended.Objectives:The study followed the principles of evidence-based medicine and used clinical epidemiological methods to observe the basic state of the group's active activities in rural areas and its impact on T2 DM and metabolic syndrome.Through the stratified analysis of the total amount of physical activity,the relationship between the total physical activity classification and T2 DM and metabolic syndrome is explored,which provides a reference for the total amount of recommended physical activity.Methods:1.Study Design and ParticipantsThe present article reports on the data from a cross sectional study,which was obtained from residents in Ningyang County,Shandong Province.After exclusion,2076 individuals were eligible for this study.The exclusion criteria are as follows:(1)suffering from severe systemic diseases,including malignant tumors or severe liver and kidney dysfunction;(2)pregnant women;(3)type 1 diabetes;(4)data incomplete.After excluding those who did not meet the criteria,a total of 2076 individuals were included in the study.2.Data CollectionBlood samples were drawn after an overnight fast for at least 10 hours.Fasting total cholesterol,LDL-C,HDL-C and triglyceride were measured using an auto-analyzer(ARCHITECT cl6000 System.Abbott Laboratories,IL,USA).Participants without a known history of diabetes underwent the oral glucose tolerance test(OGTT),and plasma glucose was measured at 0 hours(FPG)and 2 hours(2hPG)by the glucose oxidase method.3.Definition of glycemic statusCl)diabetesGlycemic status was evaluated by standardized OGTT and was defined based on the World Health Organization(WHO)1999 criteria: NGT,FPG < 6.1 mmol/L and 2hPG < 7.8mmol/L;diabetes,FPG > 7.0 mmol/L and/or 2hPG >11.1 mmol/L;pre-diabetes was defined as meeting either of the following two criteria: a)6.1 mmol/L < FPG < 7.0 mmol/L and 2hPG<11.lmmol/L;b)FPG < 7.0 mmol/L and 7.8 mmol/L < 2hPG <11.1 mmol/L.(2)metabolic syndromeMetabolic syndrome is defined if three or more of the following criteria are met:(1)abdominal obesity:waist circumference male ?90 cm;female?85 cm(2)hyperglycemia:fasting blood glucose level 6.1 mmol/L or higher;OGTT 2-hour blood glucose level is 7.8mmol/L or higher;diagnosis is diabetes(3)hypertension: blood pressure is 135/80 mmHg or higher;diagnosis is hypertension(4)high triglyceride: fasting plasma triglyceride is 1.7mmol/L or higher(5)low HDL-C: fasting plasma HDL-C is lower than 1.04 mmol / L.C3)obesity and overweightOverweight is defined as a BMI of 24.0 kg/m2 to 27.9 kg/m2,and obesity is defined as a BMI of 28.0 kg/m2 or higher.4.Statistical analysisSPSS version 22.0 for Windows(Chicago,IL,USA)was used for statistical analyses.Multivariate Logistic regression analysis was used to estimate the odds ratios and 95%confidence intervals(CIs)of incident T2 DM according to different PA levels.To compare the risk of PA on the development of T2 DM and metabolic syndrome,univariate and multivariate Logistic regression analysis were included respectively.The analysis between physical activities and other T2DM-related indicators was also analyzed using a logistics regression model.Results:1.Sociodemographic characteristicsThe basic characteristics of the total subject population(n =2076,mean 55.2±8.5 age years)are presented.Age,WC,triglyceride,HDL-C and 2-hour plasma glucose were significantly different between men and women(p<0.05).In addition,men accounted for 47.2% of the total participants,while women account for 52.8%.Among the total subject population,the prevalence of T2 DM and MS was 26.0% and 41.2% respectively.There were significant differences in the prevalence of both T2DM(p=0.035)and MS(p<0.001)when the participants were grouped by sex.2.PA status and types of PAWorking and transportation PA were the major components of the total PA.Approximately half of the total activity was contributed by working PA(49.3%)followed by transportation PA(30.2%)and leisure time physical activity(LTPA)(20.5%).Generally,with increases in age,educational level and WC,total PA tended to decrease.No trend in total PA was found when the participants were grouped by BMI.3.Prevalence of PA levels(low,moderate,and high)According to the classification criteria,the prevalence of PA levels in the overall papulation was 28.6% for low levels,47.3% for moderate levels,and 24.1% for high levels.The prevalence of low PA was higher in men(29.4%)than in women(27.8%),but the difference was not significant.No trends in prevalence were found when we classified the prevalence of the various PA levels by BMI.The prevalence of a high PA level decreased as the educational level increased(p<0.001).4.Associations between total PA and educational levels,smoking and drinking.The logistic regression model showed a significant negative association between educational level and PA levels(low and moderate levels vs high level)after adjusting for age and sex.The OR(95% Cl)across decreasing categories of educational levels was l.OO(reference),2.53(1.49-4.30),6.94(4.12-11.68),8.89(5.13-15.40),and 8.54(4.70-15.52)(p< 0.001 for trend).No significant correlation was observed between smoking or drinking and PA level.Same results were showed in the univariate logistic regression between PA and smoking/drinking status when stratified the population based on sex and age.5.Insufficient PA is a high-risk factor for T2 DM,MS and metabolic parametersFurthermore,we examined whether the level of PA has a significant association with T2 DM or MS.After adjustment for age and sex,the moderate PA level showed a significant association with T2 DM,MS and WC.In addition,the low level of PA showed a significant association with MS and WC but not with T2 DM.With respect to metabolic parameters,participants with higher PA exhibited lower levels of WC,diastolic blood pressure,triglyceride and fasting plasma glucose values but higher levels of HDL-C.When we analyzed the relationship between PA levels and some metabolic parameters,PA levels only showed significant association with HOMA-IR with and without adjusting for age and sex.We also found tiiat PA levels could be grouped according to the presence of T2 DM or MS.Conclusion:1.Among the social behavioral factors,the high level of education is a risk factor for the lack of total physical activity.2.Insufficient physical activity is a risk factor for type 2 diabetes and metabolic syndrome and its associated components.In this population,it is recommended that the amount of physical activity is higher than the minimum standard for the total amount of physical activity in the middle level.3.Insufficient physical activity is a risk factor for insulin resistance.