75 research outputs found

    Long-Term Effects of Placental Growth on Overweight and Body Composition

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    Obesity is programmed in utero and small babies generally have small placentas. In some circumstances, an undernourished fetus can expand its placental surface to extract more nutrients. We hypothesize that this results in an imbalanced nutrient supply to the fetus leading to obesity. To determine whether placental size determines overweight and body composition, we studied 2003 subjects in adult life. Associations between placental surface area and indices of overweight were restricted to people who carried the Pro12Pro genotype of the PPARγ2 gene. For every 1 SD increase in placental surface area, the odds ratio for overweight was 1.37 (95% CI 1.10 to 1.71; P = 0.005). Expansion of the placental surface in compensation for fetal undernutrition increases the risk of overweight and a higher body fat percentage in people carrying the Pro12Pro genotype. We suggest that similar underlying multifactorial mechanisms affect the development of obesity in general

    A trans-ancestral meta-analysis of genome-wide association studies reveals loci associated with childhood obesity

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    Although hundreds of genome-wide association studies-implicated loci have been reported for adult obesity-related traits, less is known about the genetics specific for early-onset obesity and with only a few studies conducted in non-European populations to date. Searching for additional genetic variants associated with childhood obesity, we performed a trans-ancestral meta-analysis of 30 studies consisting of up to 13005 cases (>= 95th percentile of body mass index (BMI) achieved 2-18 years old) and 15599 controls (consistentlyPeer reviewe

    Physical activity and sedentary behaviour in relation to cardiometabolic risk in children: cross-sectional findings from the Physical Activity and Nutrition in Children (PANIC) Study

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    BACKGROUND: Lower levels of physical activity (PA) and sedentary behaviour (SB) have been associated with increased cardiometabolic risk among children. However, little is known about the independent and combined associations of PA and SB as well as different types of these behaviours with cardiometabolic risk in children. We therefore investigated these relationships among children. METHODS: The subjects were a population sample of 468 children 6–8 years of age. PA and SB were assessed by a questionnaire administered by parents and validated by a monitor combining heart rate and accelerometry measurements. We assessed body fat percentage, waist circumference, blood glucose, serum insulin, plasma lipids and lipoproteins and blood pressure and calculated a cardiometabolic risk score using population-specific Z-scores and a formula waist circumference + insulin + glucose + triglycerides - HDL cholesterol + mean of systolic and diastolic blood pressure. We analysed data using multivariate linear regression models. RESULTS: Total PA was inversely associated with the cardiometabolic risk score (β = -0.135, p = 0.004), body fat percentage (β = -0.155, p < 0.001), insulin (β = -0.099, p = 0.034), triglycerides (β = -0.166, p < 0.001), VLDL triglycerides (β = -0.230, p < 0.001), VLDL cholesterol (β = -0.168, p = 0.001), LDL cholesterol (β = -0.094, p = 0.046) and HDL triglycerides (β = -0.149, p = 0.004) and directly related to HDL cholesterol (β = 0.144, p = 0.002) adjusted for age and gender. Unstructured PA was inversely associated with the cardiometabolic risk score (β = -0.123, p = 0.010), body fat percentage (β = -0.099, p = 0.027), insulin (β = -0.108, p = 0.021), triglycerides (β = -0.144, p = 0.002), VLDL triglycerides (β = -0.233, p < 0.001) and VLDL cholesterol (β = -0.199, p < 0.001) and directly related to HDL cholesterol (β = 0.126, p = 0.008). Watching TV and videos was directly related to the cardiometabolic risk score (β = 0.135, p = 0.003), body fat percentage (β = 0.090, p = 0.039), waist circumference (β = 0.097, p = 0.033) and systolic blood pressure (β = 0.096, p = 0.039). Resting was directly associated with the cardiometabolic risk score (β = 0.092, p = 0.049), triglycerides (β = 0.131, p = 0.005), VLDL triglycerides (β = 0.134, p = 0.009), VLDL cholesterol (β = 0.147, p = 0.004) and LDL cholesterol (β = 0.105, p = 0.023). Other types of PA and SB had less consistent associations with cardiometabolic risk factors. CONCLUSIONS: The results of our study emphasise increasing total and unstructured PA and decreasing watching TV and videos and other sedentary behaviours to reduce cardiometabolic risk among children. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01803776

    Adiposity, physical activity and neuromuscular performance in children.

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    We investigated the associations of body fat percentage (BF%), objectively assessed moderate-to-vigorous physical activity (MVPA) and different types of physical activity assessed by a questionnaire with neuromuscular performance. The participants were 404 children aged 6-8 years. BF% was assessed using dual-energy x-ray absorptiometry and physical activity by combined heart rate and movement sensing and a questionnaire. The results of 50-m shuttle run, 15-m sprint run, hand grip strength, standing long jump, sit-up, modified flamingo balance, box-and-block and sit-and-reach tests were used as measures of neuromuscular performance. Children who had a combination of higher BF% and lower levels of physical activity had the poorest performance in 50-m shuttle run, 15-m sprint run and standing long jump tests. Higher BF% was associated with slower 50-m shuttle run and 15-m sprint times, shorter distance jumped in standing long jump test, fewer sit-ups, more errors in balance test and less cubes moved in box-and-block test. Higher levels of physical activity and particularly MVPA assessed objectively by combined accelerometer and heart rate monitor were related to shorter 50-m shuttle run and 15-m sprint times. In conclusion, higher BF% and lower levels of physical activity and particularly the combination of these two factors were associated with worse neuromuscular performance.This is the author accepted manuscript. The final version is available from Taylor & Francis via http://dx.doi.org/10.1080/02640414.2015.113480

    A 2 year physical activity and dietary intervention attenuates the increase in insulin resistance in a general population of children: the PANIC study

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    Funder: The NIHR Biomedical Research Centre in CambridgeFunder: Finnish Innovation Fund SitraFunder: Foundation for Paediatric ResearchFunder: Ministry of Social Affairs and Health of FinlandFunder: Yrjö Jahnsson FoundationFunder: Research Committee of the Kuopio University Hospital Catchment Area (State Research Funding)Funder: The city of KuopioFunder: The UK Medical Research CouncilFunder: Finnish Cultural FoundationFunder: Ministry of Education and Culture of FinlandFunder: Juho Vainio FoundationFunder: Paavo Nurmi FoundationFunder: Diabetes Research Foundation in FinlandFunder: Finnish Foundation for Cardiovascular ResearchFunder: Social Insurance Institution of FinlandAbstract: Aims/hypothesis: We studied for the first time the long-term effects of a combined physical activity and dietary intervention on insulin resistance and fasting plasma glucose in a general population of predominantly normal-weight children. Methods: We carried out a 2 year non-randomised controlled trial in a population sample of 504 children aged 6–9 years at baseline. The children were allocated to a combined physical activity and dietary intervention group (306 children at baseline, 261 children at 2-year follow-up) or a control group (198 children, 177 children) without blinding. We measured fasting insulin and fasting glucose, calculated HOMA-IR, assessed physical activity and sedentary time by combined heart rate and body movement monitoring, assessed dietary factors by a 4 day food record, used the Finnish Children Healthy Eating Index (FCHEI) as a measure of overall diet quality, and measured body fat percentage (BF%) and lean body mass by dual-energy x-ray absorptiometry. The intervention effects on insulin, glucose and HOMA-IR were analysed using the intention-to-treat principle and linear mixed-effects models after adjustment for sex, age at baseline, and pubertal status at baseline and 2 year follow-up. The measures of physical activity, sedentary time, diet and body composition at baseline and 2 year follow-up were entered one-by-one as covariates into the models to study whether changes in these variables might partly explain the observed intervention effects. Results: Compared with the control group, fasting insulin increased 4.65 pmol/l less (absolute change +8.96 vs +13.61 pmol/l) and HOMA-IR increased 0.18 units less (+0.31 vs +0.49 units) over 2 years in the combined physical activity and dietary intervention group. The intervention effects on fasting insulin (regression coefficient β for intervention effect −0.33 [95% CI −0.62, −0.04], p = 0.026) and HOMA-IR (β for intervention effect −0.084 [95% CI −0.156, −0.012], p = 0.023) were statistically significant after adjustment for sex, age at baseline, and pubertal status at baseline and 2 year follow-up. The intervention had no effect on fasting glucose, BF% or lean body mass. Changes in total physical activity energy expenditure, light physical activity, moderate-to-vigorous physical activity, total sedentary time, the reported consumption of high-fat (≥60%) vegetable oil-based spreads, and FCHEI, but not a change in BF% or lean body mass, partly explained the intervention effects on fasting insulin and HOMA-IR. Conclusions/interpretation: The combined physical activity and dietary intervention attenuated the increase in insulin resistance over 2 years in a general population of predominantly normal-weight children. This beneficial effect was partly mediated by changes in physical activity, sedentary time and diet but not changes in body composition. Trial registration: ClinicalTrials.gov NCT01803776 Graphical abstrac

    The effects of a 2-year physical activity and dietary intervention on plasma lipid concentrations in children: the PANIC Study

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    Funder: Opetus- ja Kulttuuriministeriö; doi: http://dx.doi.org/10.13039/501100003126Funder: Sosiaali- ja Terveysministeriö; doi: http://dx.doi.org/10.13039/501100008487Abstract: Purpose: We studied the effects of a physical activity and dietary intervention on plasma lipids in a general population of children. We also investigated how lifestyle changes contributed to the intervention effects. Methods: We carried out a 2-year controlled, non-randomized lifestyle intervention study among 504 mainly prepubertal children aged 6–9 years at baseline. We assigned 306 children to the intervention group and 198 children to the control group. We assessed plasma concentrations of total, LDL, HDL, and VLDL cholesterol, triglycerides, HDL triglycerides, and VLDL triglycerides. We evaluated the consumption of foods using 4-day food records and physical activity using a movement and heart rate sensor. We analyzed data using linear mixed-effect models adjusted for age at baseline, sex, and pubertal stage at both time points. Furthermore, specific lifestyle variables were entered in these models. Results: Plasma LDL cholesterol decreased in the intervention group but did not change in the control group ( − 0.05 vs. 0.00 mmol/L, regression coefficient (β) = − 0.0385, p = 0.040 for group*time interaction). This effect was mainly explained by the changes in the consumption of high-fat vegetable oil-based spreads (β = − 0.0203, + 47% change in β) and butter-based spreads (β = − 0.0294, + 30% change in β), moderate-to-vigorous physical activity (β = − 0.0268, + 30% change in β), light physical activity (β = − 0.0274, + 29% change in β) and sedentary time (β = − 0.0270, + 30% change in β). The intervention had no effect on other plasma lipids. Conclusion: Lifestyle intervention resulted a small decrease in plasma LDL cholesterol concentration in children. The effect was explained by changes in quality and quantity of dietary fat and physical activity. Clinical Trial Registry Number: NCT01803776, ClinicalTrials.go

    New loci associated with birth weight identify genetic links between intrauterine growth and adult height and metabolism

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    Birth weight within the normal range is associated with a variety of adult-onset diseases, but the mechanisms behind these associations are poorly understood1. Previous genome-wide association studies identified a variant in the ADCY5 gene associated both with birth weight and type 2 diabetes, and a second variant, near CCNL1, with no obvious link to adult traits2. In an expanded genome-wide association meta-analysis and follow-up study (up to 69,308 individuals of European descent from 43 studies), we have now extended the number of genome-wide significant loci to seven, accounting for a similar proportion of variance to maternal smoking. Five of the loci are known to be associated with other phenotypes: ADCY5 and CDKAL1 with type 2 diabetes; ADRB1 with adult blood pressure; and HMGA2 and LCORL with adult height. Our findings highlight genetic links between fetal growth and postnatal growth and metabolism

    New loci associated with birth weight identify genetic links between intrauterine growth and adult height and metabolism.

    Get PDF
    Birth weight within the normal range is associated with a variety of adult-onset diseases, but the mechanisms behind these associations are poorly understood. Previous genome-wide association studies of birth weight identified a variant in the ADCY5 gene associated both with birth weight and type 2 diabetes and a second variant, near CCNL1, with no obvious link to adult traits. In an expanded genome-wide association meta-analysis and follow-up study of birth weight (of up to 69,308 individuals of European descent from 43 studies), we have now extended the number of loci associated at genome-wide significance to 7, accounting for a similar proportion of variance as maternal smoking. Five of the loci are known to be associated with other phenotypes: ADCY5 and CDKAL1 with type 2 diabetes, ADRB1 with adult blood pressure and HMGA2 and LCORL with adult height. Our findings highlight genetic links between fetal growth and postnatal growth and metabolism

    Novel loci for childhood body mass index and shared heritability with adult cardiometabolic traits

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    The genetic background of childhood body mass index (BMI), and the extent to which the well-known associations of childhood BMI with adult diseases are explained by shared genetic factors, are largely unknown. We performed a genome-wide association study meta-analysis of BMI in 61,111 children aged between 2 and 10 years. Twenty-five independent loci reached genome-wide significance in the combined discovery and replication analyses. Two of these, located nearNEDD4LandSLC45A3, have not previously been reported in relation to either childhood or adult BMI. Positive genetic correlations of childhood BMI with birth weight and adult BMI, waist-to-hip ratio, diastolic blood pressure and type 2 diabetes were detected (R(g)ranging from 0.11 to 0.76, P-values Author summary Although twin studies have shown that body mass index (BMI) is highly heritable, many common genetic variants involved in the development of BMI have not yet been identified, especially in children. We studied associations of more than 40 million genetic variants with childhood BMI in 61,111 children aged between 2 and 10 years. We identified 25 genetic variants that were associated with childhood BMI. Two of these have not been implicated for BMI previously, located close to the genesNEDD4LandSLC45A3. We also show that the genetic background of childhood BMI overlaps with that of birth weight, adult BMI, waist-to-hip-ratio, diastolic blood pressure, type 2 diabetes, and age at menarche. Our results suggest that the biological processes underlying childhood BMI largely overlap with those underlying adult BMI. However, the overlap is not complete. Additionally, the genetic backgrounds of childhood BMI and other cardio-metabolic phenotypes are overlapping. This may mean that the associations of childhood BMI and later cardio-metabolic outcomes are partially explained by shared genetics, but it could also be explained by the strong association of childhood BMI with adult BMI.Peer reviewe
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