Low gestational age at birth and difficulties in school—A matter of ‘dose’

<div><p>Objectives</p><p>Several studies suggest a relationship between gestational age at birth and risk of school difficulties. Our study aimed to investigate the association between the entire range of gestational ages and significant school difficulties measured as 1) More than nine hours per week special educational support and 2) Failing to complete compulsory school.</p><p>Methods</p><p>A population-based register study including all children attending the Danish compulsory school in 2015/2016 and all live-born infants born in Denmark from 1992 to 1997. Data were collected and linked using multiple registers held by Statistic Denmark. Multiple logistic regression analyses were used to estimate the association between gestational age and significant school difficulties, adjusted for explanatory variables.</p><p>Results</p><p>For measurement 1) “Special educational support” 615,789 children entered the analyses after exclusion of those with missing neonatal data. The risk of special educational support increased gradually across the entire range of gestation from 40 to ≤24 weeks: The adjusted odds ratio was 1.07 (95% confidence interval 1.03–1.12) at 39 weeks of gestational and 6.18 (95% confidence interval 5.17–7.39) at gestational ages < 28 weeks. For measurement 2) “Failing to complete compulsory school” the cohort consisted of 374,798 children after exclusion of those who died, had emigrated and/or had missing neonatal data. The risk of failing to complete compulsory school increased across the entire range of gestational ages: The adjusted odds ratio was 1.07 (95% confidence interval 1.04–1.10) at 39 weeks of gestation and 2.99 (95% confidence interval 2.41–3.71) at gestational ages < 28 weeks. In both sets of analyses GA = 40 weeks was used as reference.</p><p>Conclusions</p><p>We confirm a clear association between the degree of prematurity and significant school difficulties across the entire range of gestational ages from ≤ 24 to 40 weeks.</p></div

The attributable risk and population attributable risk for failing to complete compulsory school after 10 years of education.

<p>Week 40 is used as reference.</p

The two study populations of children who (A) were registered in a Danish compulsory school in the school year 2015/2016 and (B) were born in 1992–1997.

<p>GA indicates gestational age, BW, birth weight and SDS, standard deviation score for birth weight by gestation.</p

The percentage distribution of children who (A) received special educational support in compulsory school and (B) failed to complete compulsory school, by gestational age at birth.

<p>The percentage distribution of children who (A) received special educational support in compulsory school and (B) failed to complete compulsory school, by gestational age at birth.</p

Additional file 1: of Item analysis using Rasch models confirms that the Danish versions of the DISABKIDS® chronic-generic and diabetes-specific modules are valid and reliable

GLLRM's of the five subscales of DCGM Emotion, Social inclusion and exclusion, Physical limitation and treatment and the two subscales of DSM Impact and diabetes treatment. (DOCX 577 kb

Diagram of a single factor/component from a -block model examining biomarkers over time (Biomarkers) in relation to baseline characteristics (Baseline) and Genetic background (Genes).

<p>The pattern indicates that e.g. the biomarker <i>A</i> increases- and the biomarker <i>B</i> decreases over time. This pattern is e.g. related to high values of the baseline characteristics <i>B1</i> and high number of risk alleles for gene <i>G1</i> and low number of risk alleles for gene <i>G2.</i></p

The course of stimulated C-peptide (pmol/L), HbA_1c (%) and IDAA1c for each child during the 12 months follow-up colored according to age.

<p><b>A</b>. Raw values of stimulated C-peptide (pmol/L). Stimulated C-peptide was lowest in the youngest age groups. <b>B</b>. Raw values of HbA_1c (%). The HbA_1c level in the very young age group was lower at onset compared with the older age groups. <b>C</b>. Raw values of IDAA1c. The children with points below the black are in partial remission at that time point defined as IDAA1c ≤9. Very few of the very young children were in partial remission during the 12 months follow up (21.1% after 3 months).</p

Stimulated C-peptide (pmol/L), HbA_1c (%) and IDAA1c during 12 months follow up.

<p>Stimulated C-peptide (pmol/L), HbA_1c (%) and IDAA1c during 12 months follow up.</p

Complex <i>Multi</i>-<i>Block Analysis</i> Identifies New Immunologic and Genetic Disease Progression Patterns Associated with the Residual β-Cell Function 1 Year after Diagnosis of Type 1 Diabetes - Figure 3

<p><b>Multi-block analyses: A. ‘β-cell function’-component: (I)</b> Pattern of the paraclinical biomarkers forming the ‘β-cell function’-component and the progression of this biomarker pattern during the first 12 months after diagnosis. (<b>II</b>) The pattern of baseline (the time of diagnosis) characteristics predictive for the biomarker pattern of the ‘β-cell function’-component over time (p = 0.001), were long duration of symptoms, younger age and DKA and consequently high blood glucose and low level of standard bicarbonate. (<b>III</b>) The pattern of type 1- and T2D associated SNPs associated with the biomarker pattern of the ‘β-cell function’-component over time (I) (p = 0.006) and the pattern of baseline characteristics in (II). The best genetic predictors for the biomarker pattern of the ‘β-cell function’-component over time were a combination of more risk alleles of the <i>INS (</i>rs689 and rs3842753), <i>RNLS</i> (rs10509540), <i>WFS1</i> (rs10010131) and <i>CDKN2A/2B</i> (rs564398) variants; and less risk alleles of the <i>TSPAN8-LGR5</i> (rs7961581) variant. <b>B. ‘ZnT8’-component:</b> (<b>I</b>) Pattern of biomarkers forming the ‘ZnT8-component’ and the progression of this biomarker pattern during the first 12 months after diagnosis. (<b>II</b>) This component was not significantly associated with baseline characteristics. (<b>III</b>) The pattern of T1D and T2D associated SNPs associated with the biomarker pattern of the ‘ZnT8’-component over time (I) (p = 0.0005). The best genetic predictors for the biomarker pattern of the ‘ZnT8Ab’-component were a combination of more risk alleles of the <i>IFIH1</i> (rs1990760), <i>TAF5L</i> (rs3753886), <i>HNF1B</i> (TCF2, rs4430796), <i>IL2RA</i> (rs11594656), <i>PTPN2</i> (rs1893217) and <i>CDKAL1</i> (rs10946398) variants; and less risk alleles of the <i>ERBB3</i> (rs2292239) variant.</p