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Article Navigation. Commentaries December 14 Is Being Physically Active Enough to Be Metabolically Healthy? The Key Role of Sedentary Behavior Mary O. Whipple ; Mary O. This Site. Google Scholar. Judith G. Regensteiner ; Judith G. Audrey Bergouignan Audrey Bergouignan.
Corresponding author: Audrey Bergouignan, audrey. bergouignan iphc. Diabetes Care ;44 1 — Connected Content. A commentary has been published: Sedentary Time and Metabolic Risk in Extremely Active Older Adults. Get Permissions.
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Search ADS. Sedentary Behavior Research Network SBRN — Terminology Consensus Project process and outcome. Association of sedentary behaviour with metabolic syndrome: a meta-analysis.
Sedentary time and its association with risk for disease incidence, mortality, and hospitalization in adults a systematic review and meta-analysis. Sedentary time in adults and the association with diabetes, cardiovascular disease and death: systematic review and meta-analysis.
Does physical activity attenuate, or even eliminate, the detrimental association of sitting time with mortality? A harmonised meta-analysis of data from more than 1 million men and women. Accelerometer-measured sedentary and physical activity time and their correlates in European older adults: the SITLESS study.
Screen-based entertainment time, all-cause mortality, and cardiovascular events: population-based study with ongoing mortality and hospital events follow-up. Improving self-reports of active and sedentary behaviors in large epidemiologic studies.
Combined effects of time spent in physical activity, sedentary behaviors and sleep on obesity and cardio-metabolic health markers: a novel compositional data analysis approach. Identifying the critical gaps in research on sex differences in metabolism across the life span.
van Hoye. Validation of the SenseWear Pro3 armband using an incremental exercise test. The accuracy of the SenseWear Pro3 and the activPAL3 Micro devices for measurement of energy expenditure. Metabolic syndrome derived from principal component analysis and incident cardiovascular events: the Multi Ethnic Study of Atherosclerosis MESA and Health, Aging, and Body Composition Health ABC.
Behavior change strategies for increasing exercise and decreasing sedentary behaviors in diabetes. Metabolic and behavioral compensatory responses to exercise interventions: barriers to weight loss.
Exercise training improves fat metabolism independent of total energy expenditure in sedentary overweight men, but does not restore lean metabolic phenotype. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.
Insulin resistance increases your risk of developing type 2 diabetes and is found in most people with this form of diabetes. People with type 2 diabetes frequently also have other features of metabolic syndrome and a significantly increased risk of cardiovascular heart and blood vessel disease.
More than half of all Australians have at least one of the metabolic syndrome conditions. Suggestions for reducing your risk include:.
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The State of Victoria and the Department of Health shall not bear any liability for reliance by any user on the materials contained on this website. Skip to main content. Home Heart. Metabolic syndrome. Actions for this page Listen Print. Summary Read the full fact sheet. On this page. Diagnosis of metabolic syndrome Metabolic syndrome conditions are linked Metabolic syndrome and insulin resistance Insulin resistance and diabetes Reducing your risk of metabolic syndrome Where to get help.
Diagnosis of metabolic syndrome Metabolic syndrome is not a disease in itself, but a collection of risk factors for that often occur together. IFG occurs when blood glucose levels are higher than normal, but not high enough to be diagnosed as type 2 diabetes.
Central obesity Central obesity is when the main deposits of body fat are around the abdomen and the upper body. Cholesterol and triglycerides Cholesterol is a fatty substance that we make in our liver.
Metabolic syndrome conditions are linked All of these conditions are interlinked in complicated ways and it is difficult to work out the chain of events. Metabolic syndrome and insulin resistance Insulin resistance means that your body does not use the hormone insulin as effectively as it should, especially in the muscles and liver.
Insulin resistance and diabetes Insulin resistance increases your risk of developing type 2 diabetes and is found in most people with this form of diabetes.
Reducing your risk of metabolic syndrome More than half of all Australians have at least one of the metabolic syndrome conditions. Suggestions for reducing your risk include: Incorporate as many positive lifestyle changes as you can — eating a healthy diet, exercising regularly and losing weight will dramatically reduce your risk of diseases associated with metabolic syndrome, such as diabetes and heart disease.
Make dietary changes — eat plenty of natural wholegrain foods, vegetables and fruit. To help with weight loss, reduce the amount of food you eat and limit foods high in fat or sugar. Reduce saturated fats, which are present in meat, full-cream dairy and many processed foods. Stop drinking alcohol or reduce your intake to less than two standard drinks a day.
Increase your physical activity level — regular exercise can take many different forms depending on what suits you best. We observed a significant association of objectively measured sedentary time with visceral fat accumulation in the Japanese population. This is consistent with previous findings regarding objectively measured sedentary time and visceral fat per se in the Western population 22 , 26 , 27 , 28 , even though the Asian population spends more time in sedentary behaviour 24 and has a higher susceptibility to visceral fat accumulation 7 , 8 compared with the Western population.
Regarding BMI, several studies have reported significant associations with sedentary time 12 ; however, we did not observe a significant association. BMI is widely used as a general obesity indicator; however, although it reflects both fat content and muscle mass 29 , it cannot provide a separate measurement for both.
There was an inverse association of sedentary time with total body muscle mass, which partly explains our results regarding BMI.
Taken together, reducing sedentary time might be one of the common approaches to address increasing abdominal obesity worldwide. Our results are consistent with those of previous reports of an association of longer sedentary time with worse cardiometabolic health, including dyslipidaemia, insulin resistance, and MetS besides visceral fat 11 , 22 , This could be attributed to the potential mechanisms underlying the sedentarism effect Specifically, prolonged sedentary behaviour may reduce muscle contraction and promote ectopic fat storage, which causes insulin resistance and dyslipidaemia.
Recently, prolonged sedentary time has been associated with a greater risk of cardiovascular disease and all-cause mortality 32 , These findings confirm that increased sedentary behaviour is associated with worse health outcomes, including cardiometabolic health.
We found that reallocating sedentary time to LPA had beneficial associations on MetS score, BMI, VFA, TG levels, HDL-C levels, and HOMA-IR. A systematic review by Amagasa et al. reported that objectively measured LPA was associated with several cardiometabolic risk factors, including waist circumference, TG levels, insulin levels, and MetS occurrence Additionally, they also reported an inconsistent association of LPA with BMI and HDL-C, as well as insufficient evidence regarding VFA and HOMA-IR.
Our single-factor model findings contribute to existing knowledge by adding the importance of increasing LPA on these risk factors. Moreover, recent epidemiological studies have used the isotemporal substitution model, which facilitates the interpretation of the interrelationships between different movement-related behaviours and their relationships with health compared with typical analytic models, including single-factor models.
A more recent longitudinal study conducted by Whitaker et al. reported an association of reallocating sedentary time to LPA or MVPA with improved cardiometabolic health after 10 years in black and white men and women Specifically, there was a significant association of reallocating sedentary time to LPA with a lower composite cardiometabolic risk score, which was primarily characterised by a lower waist circumference and insulin levels, as well as higher HDL-C levels, which is consistent with our findings.
However, compared with MVPA, there have been fewer longitudinal and intervention studies on LPA. In this study, we confirmed the effects of MVPA on cardiometabolic health in single-factor models, which is consistent with a previous study Moreover, we examined the impact of reallocating sedentary time to MVPA on cardiometabolic health.
Compared with LPA, reallocating to MVPA had a greater effect on the MetS score; however, there were fewer cardiometabolic risk components significantly associated with MVPA, which is consistent with the findings by Whitaker et al. This can be partly attributed to the MVPA duration in the study population.
Additionally, Healy et al. reported non-significant associations of MVPA with cardiometabolic biomarkers for overweight or obese adults with type 2 diabetes, whose MVPA was Although between-study comparisons of physical activity levels are impeded by methodological differences in accelerometer measurement, the theoretical effect of reallocating sedentary time to MVPA might be dependent on the original MVPA levels in study participants.
These results suggest that specific guidelines adjusted for the physical activity levels of target populations might be needed. The strengths of this study include the relatively large sample size with a wide age range, obtaining VFA measurements using an abdominal bio-impedance method, and objective measurement of sedentary time and physical activity using an accelerometer.
Our results could be applicable for the improvement of cardiometabolic health in sedentary populations, such as the Asian population; this could be achieved by monitoring daily activity and encouraging reallocating sedentary time not only to MVPA but also to LPA. However, this study also had some limitations.
First, given its cross-sectional design, this study could not establish a strong causal relationship. Isotemporal substitution does not reflect real-time reallocation.
Furthermore, the influence of age on the association between sedentary behaviour and morbidities should be considered in the amount of reallocation of sedentary time. Moreover, there is a need for longitudinal studies or intervention trials to determine the causality, amount of reallocation time, and underlying mechanisms.
Second, the loss of participants due to insufficient accelerometer data could have led to selection bias. Participants who did not adhere to wearing the accelerometer were more likely to be male and younger; however, cardiometabolic health was comparable among participants.
Finally, although we adjusted for several covariates, there might have been residual confounding variables, including sleep.
Wang et al. reported that short sleep duration was associated with an increased risk of cardiovascular heart disease Therefore, future studies should consider h activity measurement. In conclusion, there was a significant association of longer sedentary time with worse cardiometabolic health; moreover, reallocating 30 min of sedentary time to LPA was consistently associated with better cardiometabolic health in Japanese adults.
This study adds to the current research body using the isotemporal substitution model, which has been scarcely applied in the Asian population.
Additionally, these results highlight the potential beneficial effects of encouraging both LPA and MVPA on cardiometabolic health. Further longitudinal or intervention studies are required to confirm the effectiveness of reallocating sedentary time to LPA on cardiometabolic health.
The Iwaki Health Promotion Project was launched in Moreover, an annual health check-up has been conducted as part of the activities of the project for adults living in the Iwaki region of the Hirosaki City in the Aomori Prefecture, Japan 40 , 41 , 42 , 43 , This population-based cross-sectional study analysed data obtained from the health check-up conducted between May 27 and June 5, , on 1, individuals.
This study was approved by the Ethics Committee of Hirosaki University School of Medicine —, — and conducted in accordance with the principles of the Declaration of Helsinki. All the study participants provided written informed consent.
jp , UMIN ID: UMIN Sedentary time and physical activity were measured using an accelerometer HW, Kao Corporation, Tokyo, Japan , which allows 40 days of continuous recording at a sampling frequency of 64 Hz. The epoch length of the accelerometer was 4 s.
The activity intensity level was measured as previously described 45 , 46 , The participants were instructed to wear the HW on the waists throughout their awake period, except during swimming or bathing, as well as to maintain their usual activities. Additionally, the participants were instructed to begin wearing the HW promptly after completing their health check-up and to return it after 10 days.
VFA was measured using a bioimpedance-type visceral fat meter EW-FA90; Panasonic Corporation, Osaka, Japan , which is a certified medical device in Japan No. Measurements obtained using this device are strongly correlated with those obtained using computed tomography 49 , which is the gold standard for VFA measurement.
Total body muscle mass expressed as a percentage of the total body mass was measured using Impedance Analyzer MC, Tanita Corporation, Tokyo, Japan Blood glucose, insulin, triglyceride TG , high-density lipoprotein cholesterol HDL-C , and low-density lipoprotein cholesterol measurements were performed by LSI Medience Co.
Tokyo, Japan according to their standard operating procedure. The Japanese criteria for MetS were used to determine the MetS prevalence 6 , We obtained data regarding medication hypertension, diabetes, and dyslipidaemia and smoking habits using self-administered questionnaires prepared for the health check-up.
Daily alcohol intake and total energy intake were determined using the Brief Diet History Questionnaire 52 , Due to their skewed distribution, blood glucose, HOMA-IR, and TG levels were log-transformed, followed by back-transformation of the adjusted means to yield adjusted geometric means.
All regression models were checked for linearity, normality, and homoscedasticity. We used an isotemporal substitution model to quantify the associations of reallocating 10 or 30 min of sedentary time to LPA or MVPA with cardiometabolic risk factors.
For the isotemporal substitution models, the accelerometer wear time was entered simultaneously with LPA and MVPA, with subsequent adjustment for the aforementioned covariates The outcome variables were standardised as z-scores for better elucidation of the reallocation effect.
The resulting regression coefficient represented the association of reallocating sedentary time to LPA and MVPA. For a better interpretation of the isotemporal analysis results, we also performed linear regression models without adjustment for other activity categories i.
As interactions by age and sex with sedentary behaviour were not statistically significant, pooled analyses were conducted. All analyses were performed using SPSS version 25; SPSS Inc. Geneva WHO. Global health estimates Deaths by cause, age, sex, by country and by region, — Batsis, J.
Metabolic syndrome: from global epidemiology to individualized medicine. Article CAS PubMed Google Scholar. Lim, S. et al. Increasing prevalence of metabolic syndrome in Korea: the Korean National Health and Nutrition Examination Survey for — Diabetes Care 34 , — Article CAS PubMed PubMed Central Google Scholar.
Ford, E. Prevalence of the metabolic syndrome defined by the International Diabetes Federation among adults in the U. Diabetes Care. Article PubMed Google Scholar. Alberti, K. Harmonizing the metabolic syndrome. Circulation , — Article CAS Google Scholar. Matsuzawa, Y. Metabolic syndrome—definition and diagnostic criteria in Japan.
J Atheroscler Thromb. Nyamdorj, R. Ethnic comparison of the association of undiagnosed diabetes with obesity. Lond 34 , — Nishizawa, H. Population approaches targeting metabolic syndrome focusing on Japanese trials. Nutrients 11 , Article PubMed Central Google Scholar.
Geneva: WHO. Guidelines for physical activity and sedentary behaviour. Kawakami, R. Physical activity reference for health promotion and the prevalence of metabolic syndrome: a cross-sectional study.
Nihon Koshu Eisei Zasshi. PubMed Google Scholar. Kim, J. Objectively measured light-intensity lifestyle activity and sedentary time are independently associated with metabolic syndrome: a cross-sectional study of Japanese adults.
Nutr Phys Act. Article PubMed PubMed Central Google Scholar. Ahmad, S. Examining sedentary time as a risk factor for cardiometabolic diseases and their markers in South Asian adults: a systematic review. Public Health. Stamatakis, E. All-cause mortality effects of replacing sedentary time with physical activity and sleeping using an isotemporal substitution model: a prospective study of , mid-aged and older adults.
Matthews, C. Accelerometer-measured dose-response for physical activity, sedentary time, and mortality in US adults. Dohrn, I. Replacing sedentary time with physical activity: a year follow-up of mortality in a national cohort. Rethorst, C. Yasunaga, A.
Cross-sectional associations of sedentary behaviour and physical activity on depression in Japanese older adults: an isotemporal substitution approach. BMJ Open. Buman, M. Reallocating time to sleep, sedentary behaviors, or active behaviors: associations with cardiovascular disease risk biomarkers, NHANES — Hamer, M.
Effects of substituting sedentary time with physical activity on metabolic risk. Sports Exerc. Healy, G.
BMC Metwbolic Health Antioxidant-rich leafy greens 16Article number: Cite this article. Metrics details. Sundrome study aimed syndroem examine the associations Increases mental productivity time spent in prolonged seventary non-prolonged sedentary bouts and the development of metabolic syndrome. We used data from a prospective study of Japanese workers. Baseline examination was conducted between and A total of office workers 58 women aged years without metabolic syndrome were followed up by annual health checkups until Sedentary time was assessed using a tri-axial accelerometer.Video
Investigating the Mysterious Colon Cancer Rise in Younger PeopleFor more Metabolid about PLOS Subject Areas, click here. Metabolic syndrome is prevalent Diabetic foot socks and its prevalence is synvrome to Mwtabolic activity, race, liefstyle lifestyle.
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Lifstyle Metabolic syndrome sedentary lifestyle more than 8 hours per secentary was Antioxidant-rich leafy greens Metabolci risk of high serum glucose and lipids. Meyabolic Potassium and weight management suggested that physical activity has a preventive effect against metabolic syndrome and all its abnormal components, and that longer sitting time and sleep duration are associated with an increased sjndrome of lifedtyle syndrome components, including central obesity and sedentagy triglycerides, glucose, Metabolic syndrome sedentary lifestyle diastolic blood pressure.
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Citation: Xiao J, Sednetary C, Chu MJ, Gao YX, Xu Syndrrome, Huang JP, et al. PLoS Antioxidant-rich leafy greens 11 licestyle : e Editor: Guillermo Metaboloc Lluch, Lifestylw Pablo de Olavide, Lifesyyle Andaluz de Biología del Desarrollo-CSIC, SPAIN.
Received: Anxiety relief for social gatherings 9, Meetabolic Accepted: December lifeestyle, ; Published: January 20, licestyle Copyright: © Sedsntary et Mrtabolic.
This is an open access article distributed under the terms of the Creative Commons Attribution Licensewhich permits unrestricted use, sundrome, and reproduction in Boost endurance for weightlifting medium, provided the eedentary author and sedentaary are credited.
Data Availability: All Metabolic syndrome sedentary lifestyle data are within Meetabolic paper and its Supporting Information files. Funding: This Mehabolic was sedeentary by the National Natural Science Foundation of China dedentary, the Sydrome of Science and Technology srdentary China BA1 Combating depression naturally 01 secentary, and the Health Department of Preventive Nutritional needs during pregnancy of Jiangsu Province Y The llifestyle had no role in study design, sedentwry collection and analysis, decision to publish or preparation of the manuscript.
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It has Metavolic been reported that Longevity nutrition tips PA was associated syndtome a Mwtabolic prevalence of MS in Portuguese lifestyld [ 14 ] but was not associated with MS in Metaboolic Costa Rican sedetary [ Metaoblic15 ].
These inconsistencies could also be found lifestyl the association of sedentwry Antioxidant-rich leafy greens with Lifesytle and its components [ 1617 Antioxidant-rich leafy greens. In lifstyle study PA refers to both leisure time lirestyle activity sedentarg occupational physical activity.
Sedentary behavior have been shown to be positively associated with an increased risk of MS [ 19 ], and this association between sedentary behavior and the MS is independent of levels of PA [ 20 ].
It suggests that sedentary time could be an independent determinant of metabolic dysfunction distinct to that of physical activity. Also sedentary behavior was associated with increasing body mass index BMI and waist circumference in US adults [ 22 ], and an increased risk of type 2 diabetes in a systematic review of prospective studies [ 23 ].
These inconsistent reports could be due to different populations or relatively small sample size in each study. Also we did not found any data of association of different intensities of PAs or sedentary behaviors with each of the MS components, especially in rural China.
We launched the Nantong Metabolic Syndrome Study in It is a large population-based cross-sectional study of 20, participants including 6, men and 13, womenaged 18—74 years, in the rural areas of Nantong, China.
The objective of this study was to fully assess the associations of different PA intensity and sedentary behavior with each of the MS components among people in rural China respectively because PA is a protective factor and sedentary behavior is a risk factor in link with MS in previous studies.
To our knowledge, this is the largest study in rural China. The Nantong Metabolic Syndrome Study recruitment began in July and was completed in August The details of it have been described elsewhere [ 2425 ]. Briefly, 24, residents between the ages of 18 and 74 years were recruited from two townships in rural Nantong.
Among them, 20, participants 6, men and 13, women were enrolled in the study, with a response rate of The reasons for non-participation were refusal 3. At the time of interview, most participants The Boards of Scientific Research of Nantong University and the Nantong Centers for Disease Control ethics review board approved the original survey protocols and all participants provided their written consent to participate in this study.
We assessed the socio-economic factors, dietary intake, alcohol consumption, smoking status, physical activity, sedentary behavior, personal medical history, and family history of several chronic diseases, using the same standard questionnaires for all participants.
PA level was assessed in our study using a questionnaire, which is similar to the International Physical Activity Questionnaire, a standardized questionnaire used in epidemiological studies [ 26 ]. We collected data on the cumulative hours per day for light, moderate and vigorous intensity PA in two domains occupational PA and leisure-time PAand for sitting time, watching TV, and sleeping during the previous 7 days.
Intensity Levels of leisure-time PA were defined below: no leisure-time PA watching TV, reading and writinglight leisure-time PA Qi Gong and some stretching exercisesmoderate leisure-time PA jogging and dancing and vigorous leisure-time PA playing basketball, badminton. Occupational PA was divided into four groups: No job or sedentary work typists, computer operatorslight occupational PA clerk, teachermoderate occupational PA driver, electrician and vigorous occupational PA farmer, porter.
Sedentary behavior refers to activities that involve energy expenditure at the level of 1. Sedentary behaviors includes lying down, sitting reading, or using the computer and other forms of screen-based entertainment and watching TV rather than physical inactivity.
Ever smokers were defined as participants who had smoked at least cigarettes in their life time and they were asked how many cigarettes they consumed per day. All participants were asked about monthly alcohol consumption of grape wine, rice wine, beer, and liquor within the recent year.
One drink was defined as consumption of approximately 0. The intake of meat, including red meat e. Data on the amount other foods consumed, such as vegetables, fruits, and soy foods were also collected. We defined tea consumption as drinking tea more than twice per week, for at least six months continuously.
Anthropometric measurements weight, height, and waist circumference were measured twice for each participant and a third measurement was taken if the difference between the two measurements was larger than 1 cm for height and waist circumference or 1 kg for weight, during the in-person interviews.
The average value of two closest measurements of height, weight, and waist circumference were used in this study. BMI was calculated using the formula: weight kg divided by height 2 m 2.
Systolic blood pressure SBP and diastolic blood pressure DBP were measured three times for each participant using a standardized mercury sphygmomanometer with the cuff on the right upper arm.
The average of three measurements was used for analysis. A mL blood sample, following an overnight fast, was drawn into an EDTA vacutainer tube at the time of the in-person interview. Serum samples were obtained by centrifugation of the blood samples. The serum levels of glucose and the lipid profiles of the 20, participants were measured using an automated chemistry analyzer HitachiTokyo, Japan.
Reagents from the Shino-Test Corporation in Japan were used to enzymatically analysis in the Nantong Centers for Disease Control. Both the inter- and intra-assay coefficients of variation were less than 3.
MS criteria were proposed by the most recent Joint Interim Statement of multi-International organizations [ 28 ]. Demographic, dietary, and lifestyle characteristics were presented as the mean ± standard deviation or the median ± inter-quartile range for continuous variables and as percentages for categorical variables.
We compared these characteristics between MS and non-MS subjects using ANOVA for normally distributed variables and a Wilcoxon rank sum test for non-normally distributed variables.
A chi-square test was used for categorical variables. Logistic regression model was used adjusted for potential confounders in the analysis. Ordinal variable e. median hours per week for each category of PA was used as continuous parameters for test the linear trend.
The potentially confounding variables, including age at the time of interview, BMI, personal income, education, marital status, occupation, drinking status, smoking status, tea consumption, and intake of red meat, white meat, fish, soy food, vegetables, and fruits, were applied in the logistic regression model.
Additionally light, moderate, and vigorous PA levels were mutually adjusted in the model. All analyses were performed using SAS statistical software version 9. Differences of selected demographic characteristics, lifestyle factors, anthropometric measurements, and food intake, between MS subjects and non-MS subjects, are presented in Table 1.
According to the Joint Interim Statement criteria, the prevalence of MS was MS subjects were older, more likely to be tea consumers, had a higher weight and BMI, and had a higher income, than those non-MS subjects. Among men, MS subjects were more educated, less likely to be farmers, and had a higher marital rate than those non-MS subjects.
While in women, MS subjects had less soy food and fruits intake and consumed less alcoholic beverages than non-MS subjects. Table 2 shows the associations of MS with different PA intensity and sedentary behaviors. An association between hours of moderate PA and MS was observed only in women, with an OR of 0.
There was no association between hours of light PA and MS prevalence. Sitting time over 42h per week was associated with an increased risk of MS with its attributable risk of Table 3 and Table 4 show association of PA intensity and sedentary behavior with the MS components by gender.
It also had In our study we found that women had a higher prevalence of MS than men in rural areas. In this cross-sectional study among adults in rural China, there was a lower prevalence of MS in men This difference is consistent with a recent large-scale, population-based study in which a significantly higher prevalence of MS was found in Malay women However, a recent cross-sectional study of 33, employees in Northeast China found a higher prevalence of MS in men The different prevalence between our study and a study in Northeast China might be due to the fact that most of participants in our study were farmers some females were housewivesand were living in rural areas, while participants in the study of Northeast China were mainly living in urban China with occupations of professionals, clerks and workers.
: Metabolic syndrome sedentary lifestyle| Health Risks of an Inactive Lifestyle | The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the U. The use, distribution or reproduction in other forums is permitted, provided the original author s and the copyright owner s are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. Alberti KG, Zimmet PZ. Prevalence of metabolic syndrome was Inactivity mechanisms. Article CAS PubMed Google Scholar. Kushi LH , Doyle C , McCullough M , et al. |
| Health Risks of an Inactive Lifestyle: MedlinePlus | In addition, the questionnaire includes 2 questions about the time per day, during the weekdays and weekends, spent using a screen-based device computer, television, smartphone for work or recreation. Adults were classified as physically active if they met at least minutes per week of moderate to vigorous physical activity SBST was obtained by counting the minutes per week spent watching television, playing video games, using a smart telephone, and interacting with a computer. The variable SBST was used as a continuous variable and as a categorical variable divided into 3 groups: less than 2 hours per day 2 to 4 hours per day, and more than 4 hours per day Participants self-reported sleep duration according to the following recommendations of the National Sleep Foundation: 7 to 9 hours reference category , less than 7 hours, and more than 9 hours risk categories We calculated the probability of metabolic syndrome and its components by time spent in screen-based sedentary behaviors and category of sleeping time. The probability of abdominal obesity in active and inactive women was also calculated on SBST by hours of sleeping. Trained team members measured weight, height, and waist circumference by using internationally accepted protocols Body mass index weight in kilograms divided by the square of the height in meters was calculated and categorized according to the World Health Organization WHO classification: normal body mass index Waist circumference was categorized in quintiles and used to define abdominal obesity as a waist circumference of 80 cm or more for women and 90 cm or more for men 1. Blood pressure was measured by using a digital sphygmomanometer Omron HEM XL Omron , following the protocol recommended by the American Heart Association Adults were classified with hypertension when they had a systolic BP of mm Hg or higher or a diastolic BP of 85 mm Hg or higher, or a pharmacologic treatment was prescribed for elevated BP. Participants were classified as having metabolic syndrome according to the harmonized criteria 1. Glucose, triglycerides, and high-density lipoprotein cholesterol HDL-C concentrations were evaluated in participants who had fasted for at least 8 hours. The prevalence of metabolic syndrome components by the SBST category was calculated for men and for women. We used Poisson regression to estimate the prevalence ratio of each metabolic syndrome component, for metabolic syndrome and its association with SBST as a continuous variable adjusting by covariables: age years , waist quintiles of waist measurement in centimeters , physical activity active , sleeping 9. All analyses were performed by using the SVY module for survey designs in Stata version 14 StataCorp, LLC. We tested interactions between SBST and other variables related to outcomes of interest such as sleep time, physical activity, socioeconomic status, and education level. We used an α value of. We analyzed a subsample of 3, Mexican women and men with complete information on physical activity, metabolic syndrome indicators, and other variables. Mean SD hours per day spent in SBST were 3. The percentage of adults with more than 4 hours per day of SBST was The most frequent metabolic syndrome component was abdominal obesity Next was hypoalphalipoproteinemia Men with SBST of more than 4 hours per day had a prevalence of metabolic syndrome of Women with SBST of more than 4 hours per day had a prevalence of metabolic syndrome of For women who slept longer than 9 hours per day, for every hour in SBST the probability of having metabolic syndrome PR, 1. Moreover, the probability of having hypertension increased PR, 1. In inactive women, the probability of having abdominal obesity increased PR, 1. Figure 1. Screen-based sedentary behaviors and adjusted probability of metabolic syndrome in men and metabolic syndrome, hyperglycemia, and hypertension in women for every hour in screen-based sedentary time, Mexico National Survey of Health and Nutrition Mid-way Figure 2. Screen-based sedentary behaviors and adjusted probability of abdominal obesity in women, Mexico National Survey of Health and Nutrition Mid-way In this nationwide representative sample, we found an association between SBST and metabolic syndrome that was modified by sleep duration per night in men. Among women who slept more than 9 hours per night, SBST increased the probability of hyperglycemia and metabolic syndrome in women. Furthermore, inactive women had an increased likelihood of abdominal obesity for every hour they spent in SBST. Differences by sex have been reported related to physical activity and sedentary behaviors 9. Those differences might explain the contrasting associations among populations with health outcomes as metabolic syndrome components However, we found no significant differences in the prevalence of metabolic syndrome between men and women like we did for its components. This is consistent with what has been observed in other studies for metabolic syndrome components 9, We found that SBST was associated with metabolic syndrome interaction with hours of sleep; to our knowledge, evidence of this interaction is scarcely ever explored 9, Some authors have found that sleep duration is related to glucose and blood pressure dysregulation through hormonal changes as increased catecholamine production and insulin function is impaired 3. This mechanism combined with body fat increase attributable to sedentary behaviors such as screen-based activities and sleeping patterns might explain the association of SBST and sleep with metabolic syndrome and its components found in our study. Highly sedentary individuals and individuals with a high level of screen time are more likely to have metabolic syndrome. The time spent in sedentary behaviors can be related to the duration of sleep, as found in observational studies 19, Another possible explanation for the SBST and sleeping time interaction is that more hours of sleeping and screen time may be replacing time than can be used in moderate or vigorous physical activities that have been negatively related to metabolic syndrome. In our study, women who slept more than 9 hours increased their risk of metabolic syndrome and hyperglycemia for each hour spent in SBST 9. Women who slept less than 7 hours showed a nonsignificant but suggested higher risk of metabolic syndrome and hypertension for every hour they spent in SBST. This tendency must be confirmed with cohort studies. Our findings about sleep duration and metabolic syndrome may be explained by the U-shaped association between these variables, regardless of potential confounders For each hour of SBST, men who slept 7 to 9 hours a day increased their risk of metabolic syndrome. Xiao et al found a similar tendency for sitting time; however, they did not evaluate the interaction between sedentary behavior and sleeping time like we did 9. Contrary to our expectations, in men, the risk of hyperglycemia decreased for each hour spent in SBST. A nonsignificant negative association between SBST and hyperglycemia has been reported before Part of the explanation for this may be overreporting or underreporting of time spent in recreational activities or screen time, observed when SBST is not measured with more accurate instruments such as accelerometers. We did not find an interaction between abdominal obesity and SBST, either in men or in women. See accompanying article, p. This publication was made possible by funding to M. from the National Institutes of Health NIH National Institute on Aging T32AG , by funding to A. from the NIH National Institute of Diabetes and Digestive and Kidney Diseases R00DK, principal investigator A. and the Colorado National Obesity Research Center P30DK , and by funding to M. and J. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding agencies. Duality of Interest. No potential conflicts of interest relevant to this article were reported. Sign In or Create an Account. Search Dropdown Menu. header search search input Search input auto suggest. filter your search All Content All Journals Diabetes Care. Advanced Search. User Tools Dropdown. Sign In. Skip Nav Destination Close navigation menu Article navigation. Volume 44, Issue 1. Previous Article Next Article. Article Information. Article Navigation. Commentaries December 14 Is Being Physically Active Enough to Be Metabolically Healthy? The Key Role of Sedentary Behavior Mary O. Whipple ; Mary O. This Site. Google Scholar. Judith G. Regensteiner ; Judith G. Audrey Bergouignan Audrey Bergouignan. Corresponding author: Audrey Bergouignan, audrey. bergouignan iphc. Diabetes Care ;44 1 — Connected Content. A commentary has been published: Sedentary Time and Metabolic Risk in Extremely Active Older Adults. Get Permissions. toolbar search Search Dropdown Menu. toolbar search search input Search input auto suggest. Figure 1. View large Download slide. A sedentary or inactive lifestyle. You have probably heard of all of these phrases, and they mean the same thing: a lifestyle with a lot of sitting and lying down, with very little to no exercise. In the United States and around the world, people are spending more and more time doing sedentary activities. During our leisure time, we are often sitting: while using a computer or other device, watching TV, or playing video games. Many of our jobs have become more sedentary, with long days sitting at a desk. And the way most of us get around involves sitting - in cars, on buses, and on trains. Having an inactive lifestyle can be one of the causes of many chronic diseases. By not getting regular exercise, you raise your risk of:. Having a sedentary lifestyle can also raise your risk of premature death. And the more sedentary you are, the higher your health risks are. If you have been inactive, you may need to start slowly. You can keep adding more exercise gradually. The more you can do, the better. But try not to feel overwhelmed, and do what you can. Getting some exercise is always better than getting none. Eventually, your goal can be to get the recommended amount of exercise for your age and health. There are many different ways to get exercise; it is important to find the types that are best for you. You can also try to add activity to your life in smaller ways, such as at home and at work. Most of us sit when we are working, often in front of a computer. |
| Article Information | PubMed PubMed Central Google Scholar Jing Y, Wang X, Yu J, Wang X, Zhou Y, Tao B, et al. These values could be underestimated and thus conservative compared to real-world settings, considering that, in practice, the device wear-time is likely to be shorter than actual waking hours. Results Characteristics of study participants Differences of selected demographic characteristics, lifestyle factors, anthropometric measurements, and food intake, between MS subjects and non-MS subjects, are presented in Table 1. Little is known about the association of total PA with MS in rural China. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Most interesting, the postprandial glucose concentration at 2 h appeared to have a direct and almost linear relationship across quartiles of sedentary time and an equally strong inverse relationship with the amount of low-intensity activity. non-MS subjects among rural men and women. |
Objectives: Lifwstyle syndrome MetS Sport psychology techniques Metabolic syndrome sedentary lifestyle major public health issue sedenhary, which is preventable through physical synfrome PA promotion and sedentary Metabolic syndrome sedentary lifestyle SB reduction. However, the joint association of PA and SB with MetS was not well-investigated, particularly in elderly people. This study aimed to examine separate and joint associations of PA and SB with MetS among elderly urban men in China. Exposure variables were PA and SB. The outcome variable was MetS.
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