Area-level deprivation and adiposity in children: is the relationship linear?

OBJECTIVE: It has been suggested that childhood obesity is inversely associated with deprivation, such that the prevalence is higher in more deprived groups. However, comparatively few studies actually use an area-level measure of deprivation, limiting the scope to assess trends in the association with obesity for this indicator. Furthermore, most assume a linear relationship. Therefore, the aim of this study was to investigate associations between area-level deprivation and three measures of adiposity in children: body mass index (BMI), waist circumference (WC) and waist-to-height ratio (WHtR). DESIGN: This is a cross-sectional study in which data were collected on three occasions a year apart (2005-2007). SUBJECTS: Data were available for 13,333 children, typically aged 11-12 years, from 37 schools and 542 lower super-output areas (LSOAs). MEASURES: Stature, mass and WC. Obesity was defined as a BMI and WC exceeding the 95th centile according to British reference data. WHtR exceeding 0.5 defined obesity. The Index of Multiple Deprivation affecting children (IDACI) was used to determine area-level deprivation. RESULTS: Considerable differences in the prevalence of obesity exist between the three different measures. However, for all measures of adiposity the highest probability of being classified as obese is in the middle of the IDACI range. This relationship is more marked in girls, such that the probability of being obese for girls living in areas at the two extremes of deprivation is around half that at the peak, occurring in the middle. CONCLUSION: These data confirm the high prevalence of obesity in children and suggest that the relationship between obesity and residential area-level deprivation is not linear. This is contrary to the 'deprivation theory' and questions the current understanding and interpretation of the relationship between obesity and deprivation in children. These results could help make informed decisions at the local level

The effect of the UP4FUN pilot intervention on objectively measured sedentary time and physical activity in 10-12 year old children in Belgium: the ENERGY-project

<p>Abstract</p> <p>Bakckground</p> <p>The first aim was to examine the effect of the UP4FUN pilot intervention on children’s total sedentary time. The second aim was to investigate if the intervention had an effect on children’s physical activity (PA) level. Finally, we aimed to investigate demographic differences (i.e. age, gender, ethnicity, living status and having siblings) between children in the intervention group who improved in sedentary time and PA at post-test and children in the intervention group who worsened in sedentary time and PA at post-test.</p> <p>Methods</p> <p>The six weeks UP4FUN intervention was tested in a randomized controlled trial with pre-test post-test design with five intervention and five control schools in Belgium and included children of the 5^th and 6^th grade. The children wore accelerometers for seven days at pre- and post-test. Analyses included children with valid accelerometer data for at least two weekdays with minimum 10h-wearing time and one weekend day with 8h-wearing time.</p> <p>Result</p> <p>Final analyses included 372 children (60% girls, mean age = 10.9 ± 0.7 years). There were no significant differences in the change in sedentary time or light PA between intervention and control schools for the total sample or for the subgroup analyses by gender. However, children (specifically girls) in the intervention group had a higher decrease in moderate-to-vigorous PA than children in the control group. In the intervention group, children who lived with both parents and children with one or more siblings were less likely to reduce sedentary time after exposure to the intervention. Older children, girls and children who lived with both parents were less likely to increase light PA after the intervention.</p> <p>Conclusion</p> <p>The UP4FUN intervention did not result in an effect on children’s sedentary time. Based on the high amounts of accelerometer-derived sedentary time in this age group, more efforts are needed to develop strategies to reduce children’s sedentary time.</p

Common Variants at 10 Genomic Loci Influence Hemoglobin A(1C) Levels via Glycemic and Nonglycemic Pathways

OBJECTIVE Glycated hemoglobin (HbA1c), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA1c. We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA1c levels. RESEARCH DESIGN AND METHODS We studied associations with HbA1c in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA1c loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening. RESULTS Ten loci reached genome-wide significant association with HbA1c, including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 × 10−26), HFE (rs1800562/P = 2.6 × 10−20), TMPRSS6 (rs855791/P = 2.7 × 10−14), ANK1 (rs4737009/P = 6.1 × 10−12), SPTA1 (rs2779116/P = 2.8 × 10−9) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 × 10−9), and four known HbA1c loci: HK1 (rs16926246/P = 3.1 × 10−54), MTNR1B (rs1387153/P = 4.0 × 10−11), GCK (rs1799884/P = 1.5 × 10−20) and G6PC2/ABCB11 (rs552976/P = 8.2 × 10−18). We show that associations with HbA1c are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (% HbA1c) difference between the extreme 10% tails of the risk score, and would reclassify ∼2% of a general white population screened for diabetes with HbA1c. CONCLUSIONS GWAS identified 10 genetic loci reproducibly associated with HbA1c. Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA1c levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA1c

A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease

Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association studies (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of 185 thousand CAD cases and controls, interrogating 6.7 million common (MAF>0.05) as well as 2.7 million low frequency (0.005<MAF<0.05) variants. In addition to confirmation of most known CAD loci, we identified 10 novel loci, eight additive and two recessive, that contain candidate genes that newly implicate biological processes in vessel walls. We observed intra-locus allelic heterogeneity but little evidence of low frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect siz

Actigraph Accelerometer-Defined Boundaries for Sedentary Behaviour and Physical Activity Intensities in 7 Year Old Children

Background: Accurate objective assessment of sedentary and physical activity behaviours during childhood is integral to the understanding of their relation to later health outcomes, as well as to documenting the frequency and distribution of physical activity within a population.Purpose: To calibrate the Actigraph GT1M accelerometer, using energy expenditure (EE) as the criterion measure, to define thresholds for sedentary behaviour and physical activity categories suitable for use in a large scale epidemiological study in young children.Methods: Accelerometer-based assessments of physical activity (counts per minute) were calibrated against EE measures (kcal.kg(-1).hr(-1)) obtained over a range of exercise intensities using a COSMED K4b(2) portable metabolic unit in 53 seven-year-old children. Children performed seven activities: lying down viewing television, sitting upright playing a computer game, slow walking, brisk walking, jogging, hopscotch and basketball. Threshold count values were established to identify sedentary behaviour and light, moderate and vigorous physical activity using linear discriminant analysis (LDA) and evaluated using receiver operating characteristic (ROC) curve analysis.Results: EE was significantly associated with counts for all non-sedentary activities with the exception of jogging. Threshold values for accelerometer counts (counts. minute(-1)) were = 3841 for light, moderate and vigorous physical activity respectively. The area under the ROC curves for discrimination of sedentary behaviour and vigorous activity were 0.98. Boundaries for light and moderate physical activity were less well defined (0.61 and 0.60 respectively). Sensitivity and specificity were higher for sedentary (99% and 97%) and vigorous (95% and 91%) than for light (60% and 83%) and moderate (61% and 76%) thresholds.Conclusion: The accelerometer cut points established in this study can be used to classify sedentary behaviour and to distinguish between light, moderate and vigorous physical activity in children of this age

Performance related factors are the main determinants of the von Willebrand factor response to exhaustive physical exercise

Background: Physical stress triggers the endothelium to release von Willebrand Factor (VWF) from the Weibel Palade bodies. Since VWF is a risk factor for arterial thrombosis, it is of great interest to discover determinants of VWF response to physical stress. We aimed to determine the main mediators of the VWF increase by exhaustive physical exercise. Methods: 105 healthy individuals (18-35 years) were included in this study. Each participant performed an incremental exhaustive exercise test on a cycle ergometer. Respiratory gas exchange measurements were obtained while cardiac function was continuously monitored. Blood was collected at baseline and directly after exhaustion. VWF antigen (VWF:Ag) levels, VWF collagen binding (VWF:CB) levels, ADAMTS13 activity and common variations in Syntaxin Binding Protein-5 (STXBP5, rs1039084 and rs9399599), Syntaxin-2 (STX2, rs7978987) and VWF (promoter, rs7965413) were determined. Results: The median VWF:Ag level at baseline was 0.94 IU/mL [IQR 0.8-1.1] and increased with 47% [IQR 25-73] after exhaustive exercise to a median maximum VWF:Ag of 1.38 IU/mL [IQR 1.1-1.8] (p<0.0001). VWF:CB levels and ADAMTS13 activity both also increased after exhaustive exercise (median increase 43% and 12%, both p<0.0001). The strongest determinants of the VWF:Ag level increase are performance related (p<0.0001). We observed a gender difference in VWF:Ag response to exercise (females 1.2 IU/mL; males 1.7 IU/mL, p = 0.001), which was associated by a difference in performance. Genetic variations in STXBP5, STX2 and the VWF promoter were not associated with VWF:Ag levels at baseline nor with the VWF:Ag increase. Conclusions: VWF:Ag levels strongly increase upon exhaustive exercise and this increase is strongly determined by physical fitness level and the intensity of the exercise, while there is no clear effect of genetic variation in STXBP5, STX2 and the VWF promoter

Light-intensity physical activity and cardiometabolic biomarkers in US adolescents

BackgroundThe minimal physical activity intensity that would confer health benefits among adolescents is unknown. The purpose of this study was to examine the associations of accelerometer-derived light-intensity (split into low and high) physical activity, and moderate- to vigorous-intensity physical activity with cardiometabolic biomarkers in a large population-based sample.MethodsThe study is based on 1,731 adolescents, aged 12&ndash;19 years from the 2003/04 and 2005/06 National Health and Nutrition Examination Survey. Low light-intensity activity (100&ndash;799 counts/min), high light-intensity activity (800 counts/min to &lt;4 METs) and moderate- to vigorous-intensity activity (&ge;4 METs, Freedson age-specific equation) were accelerometer-derived. Cardiometabolic biomarkers, including waist circumference, systolic blood pressure, diastolic blood pressure, HDL-cholesterol, and C-reactive protein were measured. Triglycerides, LDL- cholesterol, insulin, glucose, and homeostatic model assessments of &beta;-cell function (HOMA-%B) and insulin sensitivity (HOMA-%S) were also measured in a fasting sub-sample (n=807).ResultsAdjusted for confounders, each additional hour/day of low light-intensity activity was associated with 0.59 (95% CI: 1.18&ndash;0.01) mmHG lower diastolic blood pressure. Each additional hour/day of high light-intensity activity was associated with 1.67 (2.94&ndash;0.39) mmHG lower diastolic blood pressure and 0.04 (0.001&ndash;0.07) mmol/L higher HDL-cholesterol. Each additional hour/day of moderate- to vigorous-intensity activity was associated with 3.54 (5.73&ndash;1.35) mmHG lower systolic blood pressure, 5.49 (1.11&ndash;9.77)% lower waist circumference, 25.87 (6.08&ndash;49.34)% lower insulin, and 16.18 (4.92&ndash;28.53)% higher HOMA-%S.ConclusionsTime spent in low light-intensity physical activity and high light-intensity physical activity had some favorable associations with biomarkers. Consistent with current physical activity recommendations for adolescents, moderate- to vigorous-intensity activity had favorable associations with many cardiometabolic biomarkers. While increasing MVPA should still be a public health priority, further studies are needed to identify dose-response relationships for light-intensity activity thresholds to inform future recommendations and interventions for adolescents.</div

Tracking of MVPA across childhood and adolescence

\ua9 2024 The AuthorsObjectives: Tracking of physical activity from childhood onwards is an important public health issue, but evidence on tracking is limited. This study quantified the tracking of Moderate-Vigorous Physical Activity (MVPA) across childhood and adolescence in a recent cohort from England. Design: Longitudinal, with a socio-economically representative sample from North-East England, over an 8-year period. Methods: Measures of time spent in MVPA, with an Actigraph GT1M accelerometer, were made at age 7–8y (n = 622, T1), age 9–10y (n = 585, T2), age 12–13y (n = 525, T3) and age 14–16y (n = 361, T4). Tracking of MVPA was assessed using rank order correlations between time spent in MVPA T1–T2, T1–T3, and T1–T4, and by using Cohen\u27s kappa to examine tracking of meeting the MVPA guideline (mean of 60 min/d). We examined whether tracking varied by sex, socio-economic status (SES), initial MVPA, or initial body fatness. Results: Rank order correlations were all statistically significant at p &lt; 0.01 and moderate: 0.58 between T1 and T2; 0.42 between T1 and T3; 0.41 between T1 and T4. Cohen\u27s kappas for meeting the global MVPA guideline were all significant, weakening from moderate to low over the 8 years. Tracking was stronger in higher SES compared to lower SES groups, and there was some evidence that it was stronger in girls than boys, but the other explanatory variables had little influence on tracking. Conclusions: Tracking of MVPA from mid-childhood to mid-adolescence in this cohort was moderate. This study suggests there is a need to establish high MVPA by mid-childhood, and to mitigate the age-related reduction in MVPA which occurs from mid-childhood

The relationship between appetite and food preferences in British and Australian children

Background: Appetitive traits and food preferences are key determinants of children’s eating patterns but it is unclear how these behaviours relate to one another. This study explores relationships between appetitive traits and preferences for fruits and vegetables, and energy dense, nutrient poor (noncore) foods in two distinct samples of Australian and British preschool children. Methods: This study reports secondary analyses of data from families participating in the British GEMINI cohort study (n = 1044) and the control arm of the Australian NOURISH RCT (n = 167). Food preferences were assessed by parent-completed questionnaire when children were aged 3–4 years and grouped into three categories; vegetables, fruits and noncore foods. Appetitive traits; enjoyment of food, food responsiveness, satiety responsiveness, slowness in eating, and food fussiness were measured using the Children’s Eating Behaviour Questionnaire when children were 16 months (GEMINI) or 3–4 years (NOURISH). Relationships between appetitive traits and food preferences were explored using adjusted linear regression analyses that controlled for demographic and anthropometric covariates. Results: Vegetable liking was positively associated with enjoyment of food (GEMINI; β = 0.20 ± 0.03, p < 0.001, NOURISH; β = 0.43 ± 0.07, p < 0.001) and negatively related to satiety responsiveness (GEMINI; β = -0.19 ± 0.03, p < 0.001, NOURISH; β = -0.34 ± 0.08, p < 0.001), slowness in eating (GEMINI; β = -0.10 ± 0.03, p = 0.002, NOURISH; β = -0.30 ± 0.08, p < 0.001) and food fussiness (GEMINI; β = −0.30 ± 0.03, p < 0.001, NOURISH; β = -0.60 ± 0.06, p < 0.001). Fruit liking was positively associated with enjoyment of food (GEMINI; β = 0.18 ± 0.03, p < 0.001, NOURISH; β = 0.36 ± 0.08, p < 0.001), and negatively associated with satiety responsiveness (GEMINI; β = −0.13 ± 0.03, p < 0.001, NOURISH; β = −0.24 ± 0.08, p = 0.003), food fussiness (GEMINI; β = -0.26 ± 0.03, p < 0.001, NOURISH; β = −0.51 ± 0.07, p < 0.001) and slowness in eating (GEMINI only; β = -0.09 ± 0.03, p = 0.005). Food responsiveness was unrelated to liking for fruits or vegetables in either sample but was positively associated with noncore food preference (GEMINI; β = 0.10 ± 0.03, p = 0.001, NOURISH; β = 0.21 ± 0.08, p = 0.010). Conclusion: Appetitive traits linked with lower obesity risk were related to lower liking for fruits and vegetables, while food responsiveness, a trait linked with greater risk of overweight, was uniquely associated with higher liking for noncore foods