Infant motor development and school grade in physical education.

<p>School physical education grade by approximate quintiles of age at standing unaided, adjusted for sex, gestational age, birth season and father's social class category in 1966. Data are Mean and 95% C.I (n = 5,191). P for trend<0.001</p

Descriptive Statistics.

<p>School sports grade (n = 6,212).</p><p>Number of different sports activities reported (n = 8,998).</p><p>Frequency of sports participation (n = 7,736).</p

Associations between infant motor development and proxy indicators of physical activity at age 14 years.

<p>* Model 1 adjusted for sex, gestational age, birth season and father's social class category in 1966.</p><p>† Model 2 adjusted for sex, gestational age, birth season, father's social class category in 1966, birth weight SD score and BMI SD score at age 14 years.</p><p>β Beta coefficients in this model show the change in outcome measure, for example school PE grade, per one unit change in exposure, for example 1 month earlier age at walking supported.</p

Correlations between infant motor development and indicators of sports participation at age 14 years.

*<p>p<0.05.</p>**<p>p<0.01 (2-tailed).</p

Summary Statistics.

<p>* Height was available for the full sample at both age 2 and age 5 in the NFBC1986. Height was measured on a subsample of the BCS1970 cohort at age 2 and the full sample at age 5. The main analyses used height at age 2 z-score for both the NFBC1986 and the CLHNS and used the average of height at ages 2 and 5 z-scores for the BCS1970. These summary statistics reflect that same specification.</p><p>Summary Statistics.</p

Cohort Data Description.

<p>*—Height was available at both age 2 and age 5 in the NFBC1986. Height was measured on a subsample of the BCS1970 cohort at age 2 and the full sample at age 5. The main analyses used height at age 2 z-score for both the NFBC1986 and the CLHNS and used the average of height at ages 2 and 5 z-scores for the BCS1970. Alternative specifications using height at age 5 z-score and the mean of the z-scores for height at ages 2 and 5 in the NFBC1986 were also assessed and the results do not differ substantially.</p><p>Cohort Data Description.</p

Height for age z-score and early life cognitive development.

<p>The shape of the relationship between height for age z-score and early life cognitive development in each of the 3 cohorts, including 95% confidence intervals.</p

Genome-wide significant results from standard GWAS approach and MultiPhen tested on combinations of the lipids using NFBC1966 data.

<p>Each bar shows the number of SNPs reaching genome-wide significance for a given phenotype-combination analysis (specified by the first letters of each trait, such that CHL refers to an analysis on the CHOL, HDL and LDL), with the SNPs discovered by both the univariate approach and MultiPhen shown by the white segment of the bar, the SNPs discovered by the univariate approach only shown by the grey segment, and the SNPs discovered by MultiPhen only illustrated by the black segment. The bars labelled ALL2 and ALL3 combine results across analyses on all combinations of two and three lipid traits, respectively, while ALL combines the results across the analyses of all 2, 3 and 4 combinations of the traits. A complete breakdown of these results is presented in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s018" target="_blank">Tables S5</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s019" target="_blank">S6</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s020" target="_blank">S7</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s021" target="_blank">S8</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s022" target="_blank">S9</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s023" target="_blank">S10</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s024" target="_blank">S11</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s025" target="_blank">S12</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s026" target="_blank">S13</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s027" target="_blank">S14</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s028" target="_blank">S15</a>.</p

The correlation structure between pairs of lipids.

<p>The left panel shows the correlation structure between total cholesterol (CHOL) and low-density lipoprotein (LDL) in 5655 individuals from the Northern Finland Birth Cohort 1966. Each circle depicts the value of CHOL (X-axis) and LDL (Y-axis) in mmol/L for each individual. The right panel shows the correlation structure between low-density lipoprotein (LDL) and high-density lipoprotein (HDL), in mmol/L, in the same individuals. The arrows in each plot show the direction of effect of a variant affecting only CHOL or only HDL, such that the genotypes of individuals underlying each plotted point are more likely to contain risk alleles for the labelled lipid moving through the points in the direction of the arrow. The diagonal arrows are based on the Friedewald Formula (Friedewald.72). The arrows indicate that effects of variants can be in very different directions in the 2-dimensional spaces shown; the aim of modelling and testing linear combinations of phenotypes is to capture effects in any direction.</p

Log of GDP per capita of countries represented by each cohort study.

<p>Log of GDP per capita of countries represented by each cohort study.</p