scholarly journals Patterns of body mass index milestones in early life and cardiometabolic risk in early adolescence

2019 ◽  
Vol 48 (1) ◽  
pp. 157-167 ◽  
Author(s):  
Izzuddin M Aris ◽  
Sheryl L Rifas-Shiman ◽  
Ling-Jun Li ◽  
Ken P Kleinman ◽  
Brent A Coull ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Body Mass Index ◽  
Risk Score ◽  
Fat Mass ◽  
Early Adolescence ◽  
Cardiometabolic Risk ◽  
Metabolic Risk ◽  
Fat Mass Index ◽  
Cardiometabolic Profile ◽  
Metabolic Risk Score

Abstract Background Few studies have examined the independent and combined relationships of body mass index (BMI) peak and rebound with adiposity, insulin resistance and metabolic risk later in life. We used data from Project Viva, a well-characterized birth cohort from Boston with repeated measures of BMI, to help fill this gap. Methods Among 1681 children with BMI data from birth to mid childhood, we fitted individual BMI trajectories using mixed-effects models with natural cubic splines and estimated age, and magnitude of BMI, at peak (in infancy) and rebound (in early childhood). We obtained cardiometabolic measures of the children in early adolescence (median 12.9 years) and analysed their associations with the BMI parameters. Results After adjusting for potential confounders, age and magnitude at infancy BMI peak were associated with greater adolescent adiposity, and earlier adiposity rebound was strongly associated with greater adiposity, insulin resistance and metabolic risk score independently of BMI peak. Children with a normal timing of BMI peak plus early rebound had an adverse cardiometabolic profile, characterized by higher fat mass index {β 2.2 kg/m2 [95% confidence interval (CI) 1.6, 2.9]}, trunk fat mass index [1.1 kg/m2 (0.8, 1.5)], insulin resistance [0.2 units (0.04, 0.4)] and metabolic risk score [0.4 units (0.2, 0.5)] compared with children with a normal BMI peak and a normal rebound pattern. Children without a BMI peak (no decline in BMI after the rise in infancy) also had adverse adolescent metabolic profiles. Conclusions Early age at BMI rebound is a strong risk factor for cardiometabolic risk, independent of BMI peak. Children with a normal peak-early rebound pattern, or without any BMI decline following infancy, are at greatest risk of adverse cardiometabolic profile in adolescence. Routine monitoring of BMI may help to identify children who are at greatest risk of developing an adverse cardiometabolic profile in later life and who may be targeted for preventive interventions.

scholarly journals DNA methylation in blood as a mediator of the association of mid-childhood body mass index with cardio-metabolic risk score in early adolescence

Epigenetics ◽  
2018 ◽  
Vol 13 (10-11) ◽  
pp. 1072-1087 ◽  
Author(s):  
Jian V. Huang ◽  
Andres Cardenas ◽  
Elena Colicino ◽  
C. Mary Schooling ◽  
Sheryl L. Rifas-Shiman ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Dna Methylation ◽  
Body Mass ◽  
Risk Score ◽  
Early Adolescence ◽  
Metabolic Risk ◽  
Childhood Body Mass Index ◽  
Metabolic Risk Score

scholarly journals Associations of Serum Folate and Holotranscobalamin With Cardiometabolic Risk Factors in Rural and Urban Cameroon

2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 1058-1058
Author(s):  
Camille Mba ◽  
Albert Koulman ◽  
Stephen Sharp ◽  
Nita Forouhi ◽  
Fumiaki Imamura ◽  
...  
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Risk Score ◽  
Cardiometabolic Risk ◽  
B Vitamins ◽  
Cardiometabolic Risk Factors ◽  
Serum Folate ◽  
Metabolic Risk ◽  
Inverse Association ◽  
Metabolic Risk Score

Abstract Objectives Previous studies mostly in Western populations suggest that a low exposure to B-vitamins (folate and vitamin B12 in particular) are associated with increased cardiometabolic disease risk. This study aimed to examine the association of blood concentrations of folate and holotranscobalamin (holoTC) with cardiometabolic risk factors in adults in Cameroon. Methods We conducted a cross-sectional population-based study in 497 adults. We measured serum folate and holoTC by liquid chromatography tandem mass spectrometry and “sandwich” ELISA respectively. Total folate was calculated excluding the oxidation product 5-methyltetrahydrofolate. The outcomes were individual cardiometabolic risk factors and a continuous metabolic risk score. We fitted linear regression models to examine the association between B-vitamins and cardiometabolic risk factors and estimated β-coefficients and 95% confidence intervals per standard deviation (SD) difference in each B vitamin variable. Results Mean age was 38.2 (SD: 8.6) years and 63.5% of the participants were women. Mean serum folate was 15.9 (SD: 10.8) nmol/L and holoTC was 74.1 (SD: 33.7) pmol/L. Rural residents had higher concentrations of serum folate but lower holoTC than urban residents. There was a significant inverse association between serum folate and the metabolic risk score (−0.22 (−0.41 to −0.03)) in a multivariable model adjusted for age, sex, education level, smoking, alcohol intake, rural/urban site and BMI. This association was attenuated to the null after further adjustments for objectively measured physical activity (PAEE) and holoTC. HoloTC was positively associated with the metabolic risk score in unadjusted analysis (0.29 (0.08 to 0.51)) but attenuated to the null after adjusting for socio-demographic characteristics. For individual risk factors, an inverse association was observed between serum folate and diastolic blood pressure, which was unaffected by adjustment for confounders including PAEE and holoTC (−1.18 (−2.16 to − 0.20)). Conclusions In Cameroon, serum folate and holoTC were associated with the metabolic risk score in opposite directions, partly depending on potential demographic and socioeconomic characteristics. The inverse association between serum folate and the metabolic risk score was likely driven by the blood pressure component. Funding Sources None.

scholarly journals Longitudinal associations of modifiable risk factors in the first 1000 days with weight status and metabolic risk in early adolescence

2020 ◽  
Vol 113 (1) ◽  
pp. 113-122
Author(s):  
Jiajin Hu ◽  
Izzuddin M Aris ◽  
Pi-I D Lin ◽  
Sheryl L Rifas-Shiman ◽  
Wei Perng ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Fat Mass ◽  
Early Adolescence ◽  
Early Life ◽  
Cardiometabolic Risk ◽  
Cardiometabolic Health ◽  
Cumulative Number ◽  
Fat Mass Index ◽  
Modifiable Factors

ABSTRACT Background Many studies have identified early-life risk factors for childhood overweight/obesity (OwOb), but few have evaluated how they combine to influence later cardiometabolic health. Objectives We aimed to examine the association of risk factors in the first 1000 d with adiposity and cardiometabolic risk in early adolescence. Methods We studied 1038 mother–child pairs in Project Viva. We chose 6 modifiable early-life risk factors previously associated with child adiposity or metabolic health in the cohort: smoking during pregnancy (yes compared with no); gestational weight gain (excessive compared with nonexcessive); sugar-sweetened beverage consumption during pregnancy (≥0.5 compared with <0.5 servings/d); breastfeeding duration (<12 compared with ≥12 mo); timing of complementary food introduction (<4 compared with ≥4 mo); and infant sleep duration (<12 compared with ≥12 h/d). We computed risk factor scores by calculating the cumulative number of risk factors for each child. In early adolescence (median: 13.1 y) we measured indicators of adiposity [BMI, fat mass index (FMI), trunk fat mass index (TFMI)]. We also calculated OwOb prevalence and metabolic syndrome (MetS) risk z score of adolescents. Results Among 1038 adolescents, 71% had >1 early-life risk factor. In covariate-adjusted models, we observed positive monotonic increases in BMI, FMI, TFMI, and MetS z scores with increasing risk factor score. Children with 5‒6 risk factors (compared with 0–1 risk factors) had the highest risk of OwOb [risk ratio (RR): 2.53; 95% CI: 1.63, 3.91] and being in the highest MetS quartile (RR: 2.46; 95% CI: 1.43, 4.21). The predicted probability of OwOb in adolescence varied from 9.4% (favorable levels for all factors) to 63.6% (adverse levels for all factors), and for being in the highest MetS quartile from 9.6% to 56.6%. Conclusions Early-life risk factors in the first 1000 d cumulatively predicted higher adiposity and cardiometabolic risk in early adolescence. Intervention strategies to prevent later obesity and cardiometabolic risk may be more effective if they concurrently target multiple modifiable factors.

Dietary factors associated with metabolic risk score in Finnish children aged 6–8 years: the PANIC study

2013 ◽  
Vol 53 (6) ◽  
pp. 1431-1439 ◽  
Author(s):  
A. M. Eloranta ◽  
V. Lindi ◽  
U. Schwab ◽  
S. Kiiskinen ◽  
T. Venäläinen ◽  
...  
Keyword(s):  
Risk Score ◽  
Dietary Factors ◽  
Metabolic Risk ◽  
Factors Associated ◽  
Metabolic Risk Score

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.

scholarly journals Metabolite Profiles of the Relationship between Body Mass Index (BMI) Milestones and Metabolic Risk during Early Adolescence

Metabolites ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 316
Author(s):  
Wei Perng ◽  
Mohammad L. Rahman ◽  
Izzuddin M. Aris ◽  
Gregory Michelotti ◽  
Joanne E. Sordillo ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Early Adolescence ◽  
Early Growth ◽  
Metabolic Risk ◽  
Z Score ◽  
Sex Steroid Hormone ◽  
Metabolite Profiles ◽  
Relationship Of ◽  
The Relationship

Early growth is associated with future metabolic risk; however, little is known of the underlying biological pathways. In this prospective study of 249 boys and 227 girls, we sought to identify sex-specific metabolite profiles that mark the relationship between age and magnitude of the infancy body mass index (BMI) peak, and the childhood BMI rebound with a metabolic syndrome z-score (MetS z-score) during early adolescence (median age 12.8 years). Thirteen consensus metabolite networks were generated between male and female adolescents using weighted correlation network analysis. In girls, none of the networks were related to BMI milestones after false discovery rate (FDR) correction at 5%. In boys, age and/or magnitude of BMI at rebound were associated with three metabolite eigenvector (ME) networks comprising androgen hormones (ME7), lysophospholipids (ME8), and diacylglycerols (ME11) after FDR correction. These networks were also associated with MetS z-score in boys after accounting for age and race/ethnicity: ME7 (1.43 [95% CI: 0.52, 2.34] units higher MetS z-score per 1 unit of ME7), ME8 (−1.01 [95% CI: −1.96, −0.07]), and ME11 (2.88 [95% CI: 2.06, 3.70]). These findings suggest that alterations in sex steroid hormone and lipid metabolism are involved in the relationship of early growth with future metabolic risk in males.

scholarly journals Different Associations of Trunk and Lower-Body Fat Mass Distribution with Cardiometabolic Risk Factors between Healthy Middle-Aged Men and Women

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Bin Wu ◽  
Jingshan Huang ◽  
Keisuke Fukuo ◽  
Kazuhisa Suzuki ◽  
Gen Yoshino ◽  
...  
Keyword(s):  
Risk Factors ◽  
Gender Differences ◽  
Fat Mass ◽  
Cardiometabolic Risk ◽  
Cardiometabolic Risk Factors ◽  
Oxidative Stress Marker ◽  
Sensitivity Index ◽  
Lower Body ◽  
Middle Aged ◽  
Cardiometabolic Profile

The aim of this study was to assess whether the gender-specific pattern of fat mass (FM) distribution is related to gender differences in cardiometabolic risk factors. 207 healthy middle-aged Japanese were included in the study. We measured FM in the total body, trunk, and lower-body with dual-energy X-ray absorptiometry (DXA). The percentage of trunk FM (TFM) and lower-body FM (LFM) is noted as %TFM and %LFM, respectively. Other measurements included glucose and insulin during oral glucose tolerance test (OGTT), leptin, adiponectin, plasminogen activator inhibitor-1 (PAI-1), tumor necrosis factor-α(TNF-α), C-reactive protein (CRP), and systemic oxidative stress marker. Arterial properties were indicated by cardio-ankle vascular index (CAVI) and intima-media thickness (IMT) of the common carotid artery. The results showed that %TFM is higher whereas %LFM is lower in men than in women and men have a more atherogenic cardiometabolic profile. In both genders, %TFM (%LFM) is related to an unfavorable (favorable) cardiometabolic profile. In particular, the relation between %LFM and OGTT-derived insulin sensitivity index is stronger in women than in men. These findings suggested that in relatively healthy adults, android and gynoid pattern of FM distribution contributes to gender differences in cardiometabolic risk factors.

Sign in / Sign up

Export Citation Format

Share Document