Articular diseases, symptoms and medication predicted by chronotype.^a

a<p> Model 1 crude (univariate); model 2 controlled for gender and age; model 3 controlled for gender, age, education level, civil status, physical activity, alcohol consumption, and current smoking. Morning-types as the reference category. ^*<i>p</i><0.05; ^**<i>p</i><0.01; ^***<i>p</i><0.001; ^****<i>p</i><0.0001.</p><p>Articular diseases, symptoms and medication predicted by chronotype.^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0114635#nt102" target="_blank">a</a>}</p

Spinal diseases and symptoms predicted by chronotype.^a

a<p> Model 1 crude (univariate); model 2 controlled for gender and age; model 3 controlled for gender, age, education level, civil status, physical activity, alcohol consumption, and current smoking. Morning-types as the reference category. ^*<i>p</i><0.05; ^**<i>p</i><0.01; ^***<i>p</i><0.001; ^****<i>p</i><0.0001.</p><p>Spinal diseases and symptoms predicted by chronotype.^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0114635#nt103" target="_blank">a</a>}</p

Sociodemographic, socioeconomic and health characteristics by chronotype.^a

a<p> Abbreviation: s.d.  =  standard deviation. Chi-square tests for non-parametric data, and t-test for parametric data, where ^*<i>p</i><0.05; ^**<i>p</i><0.01; ^***<i>p</i><0.001; ^****<i>p</i><0.0001.</p><p>Sociodemographic, socioeconomic and health characteristics by chronotype.^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0114635#nt101" target="_blank">a</a>}</p

Associations of common noncommunicable medical conditions and chronic diseases with chronotype in a population-based health examination study

<p>Chronotype is an emerging predictor of health and longevity, and understanding its influence on chronic diseases is important for constructing conceptual models of long-term pathways to health. We assessed the associations of chronotype with health status in the general Finnish adult population. Our population-based data were derived from the National FINRISK 2012 study and consisted of 4414 participants, aged 25–74 years, living in Finland. As part of their health examination, participants were asked about their circadian preference to the daily activities (morningness–eveningness) and a diagnosis or treatment for a set of common noncommunicable medical conditions and chronic diseases during the past 12 months. We found that there were 1935 (43.8%) morning types (MTs) and 595 (13.5%) evening types (ETs) and that 1884 (42.7%) were intermediates. As compared with the MTs, the ETs had significantly greater odds for depression (OR = 2.44, 95% CI = 1.52–3.90, <i>p</i> < 0.001) and other mental disorders (OR = 5.18, 95% CI = 2.32–11.52, <i>p</i> < 0.001). The odds were also increased for gallstones, and chronic obstructive pulmonary disease, but these did not remain significant after controlling for multiple testing. Responses to the single-item subjective estimation on the chronotype yielded the association of the definitely evening type of persons with the diagnosis or treatment of cardiac insufficiency (OR = 1.99, 95% CI = 1.02–3.88, <i>p</i> = 0.044) that was corroborated as the greater the eveningness score was, the more common the diagnosis or treatment of cardiac insufficiency was (<i>β</i> = 0.92, 95% CI = 0.85–0.98, <i>p</i> = 0.013). This exploratory study adds further support to the role of evening chronotype in chronic disease risk, albeit underlying mechanisms remain to be elucidated.</p

Meta-analysis assessing potential confounding of SES variables on the association between F_ROHLD and height.

<p>SES variables are educational attainment (EA) and occupational status (OS).</p

Three alternative measures of mean homozygosity, with 95% confidence intervals, by population sample.

<p>(A) shows mean F_ROH by population sample. F_ROH is defined as the percentage of the genotyped autosomal genome in ROH measuring at least 1.5 Mb. Mean values of F_ROH per population (with 95% confidence intervals) are: CROATIA-Korčula = 1.27 (1.18, 1.36); CROATIA-Split = 0.65 (0.59, 0.71); CROATIA-Vis = 0.94 (0.87,1.01); EGCUT = 0.56 (0.54, 0.58); ERF = 1.12 (1.04, 1.20); FINRISK = 0.79 (0.77, 0.82); HBCS = 0.63 (0.60, 0.65); H2000 = 0.84 (0.82, 0.86); INGI-CARL = 0.78 (0.65, 0.91); INGI-FVG = 1.49 (1.40, 1.58); INGI-VB = 0.76 (0.71, 0.81); LBC1921 = 0.30 (0.25, 0.35); LBC1936 = 0.26 (0.24, 0.28); MICROS = 0.93 (0.87, 0.99); NFBC1966 = 1.02 (1.00, 1.04); NSPHS = 2.83 (2.64, 3.02); ORCADES = 0.81 (0.75, 0.87); QIMR = 0.22 (0.21, 0.23); RS = 0.29 (0.28, 0.30); SOCCS = 0.30 (0.28, 0.32); YFS = 0.81 (0.79, 0.83). (B) shows mean F_ROHLD by population sample. F_ROHLD is defined as the percentage of the genotyped autosomal genome in ROH measuring at least 1.0 Mb, derived from a panel of independent SNPs. Mean values of F_ROHLD per population (with 95% confidence intervals) are: CROATIA-Korčula = 0.67 (0.61, 0.73); CROATIA-Split = 0.13 (0.11, 0.15); CROATIA-Vis = 0.48 (0.43, 0.53); EGCUT = 0.10 (0.09, 0.10); ERF = 0.53 (0.48, 0.58); FINRISK = 0.21 (0.20, 0.23); HBCS = 0.13 (0.11, 0.14); H2000 = 0.23 (0.22, 0.24); INGI-CARL = 0.44 (0.34, 0.54); INGI-FVG = 0.93 (0.86, 0.99); INGI-VB = 0.41 (037, 0.45); LBC1921 = 0.05 (0.02, 0.09); LBC1936 = 0.02 (0.01, 0.03); MICROS = 0.47 (0.43, 0.51); NFBC1966 = 0.32 (0.31, 0.33); NSPHS = 1.17 (1.07, 1.27); ORCADES = 0.35 (0.31, 0.39); QIMR = 0.013 (0.011, 0.015); RS = 0.04 (0.01, 0.07); SOCCS = 0.03 (0.02, 0.04); YFS = 0.20 (0.19, 0.21). (C) shows mean F_hom by population sample. F_hom is defined as the percentage of genotyped autosomal SNPs that are homozygous. Mean values of F_hom per population (with 95% confidence intervals) are: CROATIA-Korčula = 65.47 (65.43, 65.51); CROATIA-Split = 65.28 (65.25, 65.31); CROATIA-Vis = 65.61 (65.58, 65.64); EGCUT = 65.69 (65.68, 65.70); ERF = 65.32 (65.29, 65.35); FINRISK = 65.25 (65.23, 65.27); HBCS = 65.13 (65.12, 65.14); H2000 = 65.24 (65.23, 65.25); INGI-CARL = 65.20 (65.14, 65.26); INGI-FVG = 65.53 (65.49, 65.57); INGI-VB = 65.18 (65.16, 65.20); LBC1921 = 65.00 (64.97, 65.03); LBC1936 = 65.00 (64.99, 65.01); MICROS = 65.26 (65.23, 65.29); NFBC1966 = 65.27 (65.26, 65.28); NSPHS = 66.09 (66.01, 66.17); ORCADES = 65.37 (65.34, 65.40); QIMR = 64.75 (64.74, 64.76); RS = 65.00 (64.99, 65.01); SOCCS = 64.97 (64.95, 64.99); YFS = 65.26 (65.25, 65.27).</p

Sample details.

1<p>All data were analysed using Illumina SNP arrays. 300 refers to the Illumina HumanHap 300 panel, 370 to the Illumina HumanHap 370 Duo/Quad panels, 610 to the Illumina Human 610 Quad panel and 670 to the Illumina Human 670 Quad panel. In order to harmonise the data, the analysis was conducted using only those SNPs present in the HumanHap 300 panel.</p>2<p>Population-based studies.</p>3<p>Population-based studies in isolated populations.</p>4<p>Birth cohort studies.</p>5<p>Case control studies.</p

Forest plot of the effect of F_ROHLD on height.

<p>Results of a meta-analysis of the association between F_ROHLD and height are shown for twenty-one population samples. The model was adjusted for age and sex in all samples. Additionally, it was adjusted for genomic kinship in samples with pairs of related individuals (CROATIA-Korčula, CROATIA-Split, CROATIA-Vis, ERF, FINRISK, HBCS, H2000, INGI-CARL, INGI-FVG, INGI-VB, MICROS, NFBC1966, NSPHS, ORCADES and YFS). The plot shows estimated effect sizes (solid squares) for each population, with 95% confidence intervals (horizontal lines). Each sample estimate is weighted by the inverse of the squared standard error of the regression coefficient, so that the smaller the standard error of the study, the greater the contribution it makes to the pooled regression coefficient. The area of the solid squares is proportional to the weighting given to each study in the meta-analysis. Effect sizes in z-score units (with 95% confidence intervals) are: CROATIA-Korčula = −0.02 (−0.09, 0.04); CROATIA-Split = −0.06 (−0.1, −0.002); CROATIA-Vis = −0.07 (−0.1, −0.01); EGCUT = −0.09 (−0.04, 0.2); ERF = −0.08 (−0.1, −0.05); FINRISK = −0.1 (−0.2, −0.07); HBCS = −0.04 (−0.2, 0.1); H2000 = −0.2 (−0.5, 0.04); INGI-CARL = 0.02 (−0.03, 0.07); INGI-FVG = −0.0001 (−0.08, 0.08); INGI-VB = 0.005 (−0.03, 0.04); LBC1921 = −0.1 (−0.3, 0.04); LBC1936 = 0.2 (−0.1, 0.4); MICROS = −0.06 (−0.08, −0.05); NFBC1966 = −0.1 (−0.2, −0.1); NSPHS = −0.07 (−0.07, −0.06); ORCADES = −0.04 (−0.08, 0.001); QIMR = −0.07 (−0.5, 0.3); RS = −0.02 (−0.1, 0.08); SOCCS = −0.05 (−0.4, 0.3); YFS = −0.3 (−1.2, 0.7).</p

Meta-analysis of the association between height and genome-wide homozygosity, adjusted for age and sex only.

<p>Meta-analysis of the association between height and genome-wide homozygosity, adjusted for age and sex only.</p

Meta-analysis results of Mendelian randomization analyses on effect of <i>FTO</i>-derived adiposity on cardiovascular and metabolic disease: quantitative phenotypes.

a<p>Beta coefficient corresponds to one-unit increase in BMI (kg/m²).</p>b<p>Beta coefficient corresponds to per-allele change.</p>c<p>Values were transformed to natural logarithm scale prior to analysis.</p