Dose-response association between physical activity and metabolic syndrome

Bacevičienė, Miglė; Lukšienė, Dalia; Česnaitienė, Vida Janina; Raubaite, Sandra; Peasey, Anne; Tamošiūnas, Abdonas

doi:10.2478/s11536-012-0123-8

Cited by 8 publications

(8 citation statements)

References 31 publications

(30 reference statements)

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“…Dallongeville et al [41] has further suggested that MetS is a contributor to the familial aggregation of premature CVD independently of other classical cardiovascular risk factors. Furthermore, a higher frequency of MetS among sedentary subjects in the present study was found supported by Baceviciene et al [42]. Similarly, Edwardson et al [43] has observed that greater time spent sedentary increases the MetS odds with no differences for subgroups of sex, sedentary behavior measure, MetS definition, study quality or country income.…”

Section: Discussionsupporting

confidence: 87%

Assessment and Screening of the Risk Factors in Metabolic Syndrome

Kaur¹

2014

Medical Sciences

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Metabolic syndrome (MetS) is chronic inflammatory epidemic state contributing to total and cardiovascular mortality. The current study planned to assess and screen risk factors for MetS and its components. A cross-sectional study conducted to assess age, gender, social status, employment, education, family history, physical activity, dietary habits, alcohol, sleep, body mass index and stress as determinants of MetS. The results were analyzed by Chi Square test with statistical significance of p value <0.05. The frequency of MetS was 17.38% as per modified National Cholesterol Education Program-Adult Treatment Panel III criteria. Females (57.38%), age >50 years (86.90%; p < 0.05), middle socioeconomic status (70.50%), illiteracy (39.35%), and unemployment (81.97%; p < 0.05) were found contributing though to different extents. Subjects with a sedentary lifestyle (72.14%), positive family history (42.63%), omnivore diet (47.55%), stress (78.69%; p < 0.05), insomnia (29.51%) and increased BMI (83.62%; p < 0.001) had shown predisposition to MetS. However, the protective role of alcohol (38.28%), an active lifestyle (36.21%), vegetarian diet (62.07%) and adequate sleep (73.11%) was observed. A significant hypertension (98.37%; p < 0.001), dyslipidemia (77.05%; p < 0.001), dysglycemia (75.41%; p < 0.001) and obesity (59.02%; p < 0.001) was reported in MetS. Common concerns of female gender, increasing age and BMI, sedentary lifestyle, stress and positive family history should be considered for early identification and appropriate intervention to fight the growing MetS epidemic.

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Section: Discussionsupporting

confidence: 87%

Assessment and Screening of the Risk Factors in Metabolic Syndrome

Kaur¹

2014

Medical Sciences

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“…Another possible explanation for the gender difference is there may be a threshold for MVPA above which MetS risk is reduced and these Yakut women were not sufficiently active to reach the threshold. Yet a previous study in an urban Lithuanian population found a linear dose-response between physical activity and MetS rather than a threshold effect (Baceviciene et al, 2013). The state of the evidence is not sufficient to understand this relationship, particularly in transitioning populations.…”

Section: Gender Differencesmentioning

confidence: 82%

“…Physical activity leads to improvements in the cardio-metabolic profile (Ertek and Cicero, 2012) and reduces the potential of clustering of risk factors (Baceviciene et al, 2013;Das et al, 2012;Janseen and Ross, 2012). SB, which can also be considered physical inactivity or very low physical activity, leads to worsening of the cardio-metabolic profile (Healy et al, 2011;Saunders et al, 2012) and increases the chances of risk factor clustering (Edwardson et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Do physical activity and sedentary behavior relate to cardio‐metabolic risk factor clustering in indigenous Siberian adults?

Wilson

Leonard

Tarskaia

et al. 2014

American J Hum Biol

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“…In general, higher adherence levels of total or recreational PA were more strongly associated with the MHO phenotype. Indeed, an inverse association between leisure-time [ 28 ] and transportation-related PA [ 29 , 30 ] and MetS has also been shown, and obese individuals who engage in transportation PA are also more likely to be metabolically healthy [ 27 ]. In the present study, no participants were sufficiently active based on transportation PA alone to be considered for separate analysis.…”

Section: Discussionmentioning

confidence: 99%

Differences in physical activity domains, guideline adherence, and weight history between metabolically healthy and metabolically abnormal obese adults: a cross-sectional study

Kanagasabai

Thakkar

Kuk

et al. 2015

Int J Behav Nutr Phys Act

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BackgroundDespite the accepted health consequences of obesity, emerging research suggests that a significant segment of adults with obesity are metabolically healthy (MHO). To date, MHO individuals have been shown to have higher levels of physical activity (PA), but little is known about the importance of PA domains or the influence of weight history compared to their metabolically abnormal (MAO) counterpart.ObjectiveTo evaluate the relationship between PA domains, PA guideline adherence, and weight history on MHO.MethodsPooled cycles of the National Health and Nutritional Examination Survey (NHANES) 1999–2006 (≥20 y; BMI ≥ 30 kg/m2; N = 2,753) and harmonized criteria for metabolic syndrome (MetS) were used. Participants were categorized as “inactive” (no reported PA), “somewhat active” (>0 to < 500 metabolic equivalent (MET) min/week), and “active” (PA guideline adherence, ≥ 500 MET min/week) according to each domain of PA (total, recreational, transportation and household). Logistic and multinomial regressions were modelled for MHO and analyses were adjusted for age, sex, education, ethnicity, income, smoking and alcohol intake.ResultsCompared to MAO, MHO participants were younger, had lower BMI, and were more likely to be classified as active according to their total and recreational PA level. Based on total PA levels, individuals who were active had a 70 % greater likelihood of having the MHO phenotype (OR = 1.70, 95 % CI: 1.19–2.43); however, once stratified by age (20–44 y; 45–59 y; and; ≥60 y), the association remained significant only amongst those aged 45–59 y. Although moderate and vigorous PA were inconsistently related to MHO following adjustment for covariates, losing ≥30 kg in the last 10 y and not gaining ≥10 kg since age 25 y were significant predictors of MHO phenotype for all PA domains, even if adherence to the PA guidelines were not met.ConclusionAlthough PA is associated with MHO, the beneficial effects of PA may be moderated by longer-term changes in weight. Longitudinal analysis of physical activity and weight change trajectories are necessary to isolate the contribution of duration of obesity, PA behaviours, and longer-term outcomes amongst MHO individuals.

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Dose-response association between physical activity and metabolic syndrome

Abstract: Abstract

Cited by 8 publications

References 31 publications

Assessment and Screening of the Risk Factors in Metabolic Syndrome

Assessment and Screening of the Risk Factors in Metabolic Syndrome

Do physical activity and sedentary behavior relate to cardio‐metabolic risk factor clustering in indigenous Siberian adults?

Differences in physical activity domains, guideline adherence, and weight history between metabolically healthy and metabolically abnormal obese adults: a cross-sectional study

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