scholarly journals Consequences of Change in Waist Circumference on Cardiometabolic Risk Factors Over 9 Years: Data from an Epidemiological Study on the Insulin Resistance Syndrome (DESIR)

Diabetes Care ◽  
2007 ◽  
Vol 30 (7) ◽  
pp. 1901-1903 ◽  
Author(s):  
B. Balkau ◽  
P. Picard ◽  
S. Vol ◽  
L. Fezeu ◽  
E. Eschwege ◽  
...  
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Waist Circumference ◽  
Epidemiological Study ◽  
Cardiometabolic Risk ◽  
Insulin Resistance Syndrome ◽  
Cardiometabolic Risk Factors

scholarly journals C-reactive protein and cardiometabolic risk factors in overweight or obese children and adolescents

2014 ◽  
Vol 27 (3) ◽  
pp. 279-288 ◽  
Author(s):  
Anajás da Silva Cardoso ◽  
Renata Oliveira Cardoso ◽  
Danielle Franklin de Carvalho ◽  
Neusa Collet ◽  
Carla Campos Muniz Medeiros
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Waist Circumference ◽  
Children And Adolescents ◽  
Cardiometabolic Risk ◽  
Severe Obesity ◽  
Cardiometabolic Risk Factors ◽  
C Reactive Protein ◽  
Cross Sectional ◽  
Reactive Protein

OBJECTIVE: To investigate the relationship between ultrasensitive C-reactive protein and cardiometabolic risk factors in overweight or obese childrenand adolescents. METHODS: Cross-sectional study conducted at the Center for Childhood Obesity in the period from April 2009 to April 2010, involving 185 overweight children and adolescents aged 2 to 18 years. Measures of ultrasensitive C-reactive protein according to age, nutritional status, gender, race, cardiometabolic risk factors (waist circumference, lipid profile, impaired fasting glucose, high blood pressure and presence of insulin resistance) were compared through the Chi-square test and analysis of variance. All analyses were performed using the Statistical Package for the Social Sciences software version 17.0, adopting a significance level of 5%. RESULTS: Altered high-density lipoprotein was the most frequent cardiometabolic risk factor, and there was a significant association between altered ultrasensitive C-reactive protein values and severe obesity (p=0.005), high waist circumference (p<0.001), hypertriglyceridemia (p=0.037) and insulin resistance (p=0.002), as well as significantly higher body mass index (p=0.000), waist circumference (p=0.001), insulin (p=0.005) and index of glucose homeostasis values(p=0.005). CONCLUSION: High prevalence of altered ultrasensitive C-reactive protein and significant association with severe obesity, waist circumference, hypertriglyceridemia and insulin resistance were observed.

scholarly journals HOMA-IR Levels in US Youth Ages 12–18 Years From 1999–2018

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A451-A451
Author(s):  
Vidhu V Thaker ◽  
Shuliang Deng ◽  
Chuhan Zhou ◽  
Brady West ◽  
Yajuan Si ◽  
...  
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Waist Circumference ◽  
Cardiometabolic Risk ◽  
Cell Function ◽  
Cardiometabolic Risk Factors ◽  
Quadratic Term ◽  
Model Assessment ◽  
Z Score ◽  
Race Ethnicity

Abstract Introduction: The Homeostasis Model Assessment of insulin resistance (HOMA-IR) is a validated surrogate measure of insulin sensitivity and beta-cell function for epidemiological studies. Insulin resistance is closely associated with obesity and shares dysmetabolic state with other cardiometabolic risk factors. The aim of this study was to analyze the change in HOMA-IR levels in US youth from 1999 to 2018. Methods: Serial cross-sectional data of fasting insulin and glucose levels measured in youth aged 12 to 18 years enrolled in National Health and Nutrition Examination Surveys representative of US population from 1999 to 2018 were used. Two-year survey cycles were combined to derive 4-year survey periods, and NHANES recommended adjustments were made for glucose and insulin levels for forward conversion to 2017–18 instrument levels. Median HOMA-IR was compared across the survey periods in subgroups by age, gender, race/ethnicity and levels of obesity. Association of HOMA-IR with selected cardiometabolic risk factors was assessed. Change of HOMA-IR levels were analyzed using design adjusted multivariable regression models, association of HOMA-IR with cardiometabolic risk factors was assessed and percentiles were derived. Results: In an analysis of 5,541 youth, the unadjusted median HOMA-IR increased from 1.83 (95% CI 1.77–1.89) in 1999-02 to 2.41 (95% CI 2.29–2.54) in 2007–10 and has remained in this range till 2015–18. Youth with obesity (Body mass index &gt; 95th percentile or waist circumference &gt; 90th percentile), female gender, those of Hispanic and Black origin, and those aged 12–16 years had higher levels of HOMA-IR (p &lt;.001). While adjusting for age category, sex, race/ethnicity, obesity represented by waist circumference z-score with its quadratic term and interaction with gender, HOMA-IR increased by 26% (95% CI 15–37) in 2015–18 as compared to 1999-02. For waist-circumference z-score (WCZ) &gt; 1, the HOMA-IR levels were higher in boys compared to girls. The addition of total body fat from DXA scans in the model, when available, explained the variance related to gender, but not the interaction between gender and WCZ. No change was observed in the higher levels of HOMA-IR by ethnicity when high sensitivity CRP level as a measure of inflammation was added to the model. There was a positive association of HOMA-IR with triglycerides (29 %/unit, 95% CI 25–33), non-HDL cholesterol (8 %/unit, 95% CI 6–10), systolic blood pressure (2% /unit, 95% CI 1–2) and alanine transferase (11 %/unit, 95% CI 8–14) while controlling for age, sex, race/ethnicity, obesity and survey period. In youth with BMI between 5-85th percentile, HOMA-IR decreased with increase in age from 12 to 18 years. Conclusions: HOMA-IR levels in US youth have increased since 1999-02 and may herald future cardiometabolic risks.

scholarly journals Waist-to-height ratio, waist circumference and BMI as indicators of percentage fat mass and cardiometabolic risk factors in children aged 3–7 years

2014 ◽  
Vol 33 (2) ◽  
pp. 311-315 ◽  
Author(s):  
Anna Sijtsma ◽  
Gianni Bocca ◽  
Carianne L'Abée ◽  
Eryn T. Liem ◽  
Pieter J.J. Sauer ◽  
...  
Keyword(s):  
Risk Factors ◽  
Waist Circumference ◽  
Fat Mass ◽  
Cardiometabolic Risk ◽  
Cardiometabolic Risk Factors ◽  
Height Ratio ◽  
Waist To Height Ratio

scholarly journals Body Mass Index, Waist Circumference, and the Clustering of Cardiometabolic Risk Factors in Early Childhood

2015 ◽  
Vol 30 (2) ◽  
pp. 160-170 ◽  
Author(s):  
Laura N. Anderson ◽  
Gerald Lebovic ◽  
Jill Hamilton ◽  
Anthony J. Hanley ◽  
Brian W. McCrindle ◽  
...  
Keyword(s):  
Risk Factors ◽  
Body Mass Index ◽  
Early Childhood ◽  
Waist Circumference ◽  
Body Mass ◽  
Cardiometabolic Risk ◽  
Cardiometabolic Risk Factors

scholarly journals Functional high-intensity exercise training ameliorates insulin resistance and cardiometabolic risk factors in type 2 diabetes

2018 ◽  
Vol 103 (7) ◽  
pp. 985-994 ◽  
Author(s):  
Ciarán E. Fealy ◽  
Stephan Nieuwoudt ◽  
Julie A. Foucher ◽  
Amanda R. Scelsi ◽  
Steven K. Malin ◽  
...  
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Exercise Training ◽  
High Intensity ◽  
Cardiometabolic Risk ◽  
High Intensity Exercise ◽  
Cardiometabolic Risk Factors

Abstract P148: Neck Circumference as an Independent Contributor to Cardio Metabolic Risk Factors - ELSA BRASIL

Circulation ◽  
2015 ◽  
Vol 131 (suppl_1) ◽  
Author(s):  
Cristina P Baena ◽  
Paulo A Lotufo ◽  
Maria J Fonseca ◽  
Isabela J Benseñor
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Blood Pressure ◽  
Primary Care ◽  
Cardiometabolic Risk ◽  
Neck Circumference ◽  
Cardiometabolic Risk Factors ◽  
Metabolic Risk ◽  
Men And Women ◽  
Low Hdl

Background: Neck circumference is a proxy for upper body fat and it is a simple anthropometric measure. Therefore it could be a useful tool to identify individuals with cardiometabolic risk factors in the context of primary care. Hypothesis: Neck circumference is independently associated to cardiometabolic risk factors in an apparently healthy population. Methods: This is a cross-sectional analysis of baseline data of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), a cohort of 15105 civil servants aged 35-74 years. We excluded from this analysis those who fulfilled American Diabetes Association criteria for diabetes diagnosis, were taking antihypertensive and/or lipid-lowering drugs. A sex-specific analysis was conducted. Partial correlation (age-adjusted) was used. Risk factors were set as low HDL<50mg/dL for women and <40mg/dL for men, hypertriglyceridemia ≥ 150 mg/dl , hypertension as systolic blood pressure ≥130 mg/dl or diastolic blood pressure ≥85 mm Hg and insulin resistance(HOMA-IR ≥ 75th percentile). Logistic regression models were built to analyze the association between individual and clustered risk factors as dependent variables and 1-SD increase in neck circumference as independent variable. Multiple adjustments were subsequently performed for age, smoking, alcohol, body-mass index, waist and physical activity. Receiver Operating Curves were employed to find the best NC cut-off points for clustered risk factors. Results: We analyzed 3810 men (mean age= 49.0 ±8.3 yrs) and 4916 women (49.2 ±8.0 yrs). Mean NC was 38.9 (±2.6)cm for men and 33.4(±2.6)cm for women. NC positively correlated with systolic and diastolic blood pressure (r=0.21 and r=0.27), HOMA - IR (r=0.44), triglycerides (r=0.31) and negatively correlated with HDL (r= -0.21) in men (p<0.001 for all) with similar results in women. Fully adjusted Odds Ratio (OR) (95% CI) of risk factor per SD increase in neck circumference in men and women were 1.29(1.14;1.46) and 1.42(1.28;1.57) for insulin resistance; 1.24(1.11;1.39) and 1.25(1.11;1.40) for hypertension; 1.33(1.19;1.49) and 1.42(1.29;1.63) for hypertriglyceridemia; 1.07(0.92;1.23) and 1.32 (1.19;1.43) for low HDL. Fully adjusted OR (95% CI) of 2 clustered risk factor per SD increase in neck circumference in men and women were 1.29(1.14;1.48) and 1.37(1.21;1.54 ). Fully adjusted OR (95% CI) of 3 or more clustered risk factors per SD increase in neck circumference in men and women were 1.33 (1.02;1.74) and 1.62 (1.33;1.92). Values of neck circumference of >40 cm for men and >34.1 cm for women were the best cut-off points for 3 or more clustered risk factors. Conclusion: Neck circumference is significantly and independently associated to cardiometabolic risk factors in a well-defined non-treated population. It should be considered as a marker of cardio metabolic risk factors in primary care settings.

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