Metabolic Syndrome and Prevalent Any-site, Prostate, Breast and Colon Cancers in the U.S. Adult Population: NHANES 1999-2010

Kanagasabai, Thirumagal; Nie, Jason X; Mason, Caitlin; Ardern, Chris I.

doi:10.4172/2167-0943.1000135

Cited by 6 publications

(5 citation statements)

References 40 publications

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“…Age (20 to <40 y, 40 to <65 y, and ≥65 y), sex, ethnicity (Non-Hispanic White, Non-Hispanic Black, Mexican American, and Other), annual household income, education, alcohol intake, smoking history, leisure-time physical activity, and physician diagnosed sleep disorder were considered as covariates [ 10 , 23 ]. Smoking was categorized as current, past (if smoked ≥100 cigarettes in one's life but not a current smoker), or never (if smoked <100 cigarettes in one's life) [ 10 ].…”

Section: Methodsmentioning

confidence: 99%

“…Smoking was categorized as current, past (if smoked ≥100 cigarettes in one's life but not a current smoker), or never (if smoked <100 cigarettes in one's life) [ 10 ]. Educational attainment was categorized as <high school, high school, and college; income as <$20,000, $20,000–44,999, and ≥$45,000; and alcohol intake as 0, <3, and ≥3 drinks per day [ 23 ]. For leisure-time physical activity (PA), the metabolic equivalent (MET) scores provided by NHANES were used to calculate MET min/week, which were then categorized as no reported PA data, low PA (1 to 499 MET min/week), and guideline adherence (≥500 MET min/week) [ 10 , 24 ].…”

Section: Methodsmentioning

confidence: 99%

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Association between Sleep Habits and Metabolically Healthy Obesity in Adults: A Cross-Sectional Study

et al. 2017

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Higher body mass index (BMI) increases the risk of cardiometabolic diseases, but nearly a third of the people living with obesity (BMI: ≥30 kg/m2) are metabolically healthy (MHO). Extreme sleep durations and poor sleep quality are associated with higher bodyweight and cardiometabolic dysfunction, but the full extent to which sleep habits may help differentiate those with MHO versus metabolically abnormal obesity (MAO) is not yet known. Data from the U.S. National Health and Nutritional Examination Survey 2005–08 was used (BMI: ≥30 kg/m2; ≥20 y; N = 1,777). The absence of metabolic syndrome was used to define MHO. Those with MHO tended to be younger, female, Non-Hispanic Black, never smokers, more physically active, and with less physician diagnosed sleep disorders than MAO. Neither sleep duration nor overall sleep quality was related to MHO in crude or multivariable adjusted analyses; however, reporting “almost always” to having trouble falling asleep (OR (95% CI): 0.40 (0.20–0.78)), waking up during the night (0.38 (0.17–0.85)), feeling unrested during the day (0.35 (0.18–0.70)), and feeling overly sleepy during the day (0.35 (0.17–0.75)) was related to lower odds of MHO. Selected sleep quality factors, but not sleep quantity or overall sleep quality, are associated with the MHO phenotype.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Association between Sleep Habits and Metabolically Healthy Obesity in Adults: A Cross-Sectional Study

et al. 2017

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“…Alcohol intake was classified as high (≥3 drinks per day). Educational attainment was categorized as < high school, high school, and college, and income as < $20,000, $20,000-44,999, and ≥ $45,000 [ 21 ].…”

Section: Methodsmentioning

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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“…Age, sex, ethnicity, education, income, smoking, alcohol intake, and recreational physical activity level were considered as potential confounders [ 37 ]. Age was also categorized as 20 to < 40, 40 to < 65, and ≥ 65 y.…”

Section: Methodsmentioning

confidence: 99%

Obesity moderates the complex relationships between inflammation, oxidative stress, sleep quality and depressive symptoms

2018

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BackgroundThe relationship between obesity and depression is complex. This study assessed the impact of body mass index (BMI) on the link between BMI, inflammation, oxidative stress, sleep quality and self-reported depressive symptoms.MethodsWe used data from the U.S. National Health and Nutritional Examination Survey 2005–2008 cycles (n = 9133; ≥20y). Depressive symptoms and sleep quality were determined from questionnaires. C-reactive Protein (CRP) was used as a biomarker of inflammation and γ-glutamyltransferase was used to assess oxidative stress. The relationship between depressive symptoms, sleep quality, and biomarkers were assessed with regression models. The moderating effects of BMI and sex were tested.ResultsBMI was a significant moderator of the relationship between γ-glutamyltransferase and depressive symptoms (p = 0.02), but not CRP or sleep quality. Higher BMI increased odds of depressive symptoms in women (OR (95% CI): 3.92 (1.85–8.30) for BMI ≥25 to < 30 kg/m2; 3.17 (1.53–6.58) for BMI ≥30 to < 35 kg/m2; and 7.38 (2.11–25.76) for BMI ≥35 kg/m2). BMI was also a significant moderator of γ-glutamyltransferase levels in those with vs without depressive symptoms. Those with depressive symptoms had 24% poorer sleep quality compared to those without depressive symptoms after adjusting for inflammation, oxidative stress and other confounders.ConclusionsThe link between oxidative stress and depressive symptoms may be particularly relevant for females and people living with obesity. People with depressive symptoms also have a substantial reduction in sleep quality. Thus, research should examine these relationships prospectively to inform and improve the mental health of the adult population in developed countries.

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Metabolic Syndrome and Prevalent Any-site, Prostate, Breast and Colon Cancers in the U.S. Adult Population: NHANES 1999-2010

Abstract: Background: Metabolic Syndrome (MetS) is associated with elevated risk of diabetes, cardiovascular disease, and premature mortality. To date, however, the association between MetS and obesity-related cancers has not been systematically assessed within a population-based sample.

Cited by 6 publications

References 40 publications

Association between Sleep Habits and Metabolically Healthy Obesity in Adults: A Cross-Sectional Study

Association between Sleep Habits and Metabolically Healthy Obesity in Adults: A Cross-Sectional Study

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

Obesity moderates the complex relationships between inflammation, oxidative stress, sleep quality and depressive symptoms

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