Multiple logistic regression analysis, any retinopathy.

<p>Multiple logistic regression analysis, any retinopathy.</p

Clinical and laboratory characteristics according to retinopathy status.

<p>Values represent mean (SE)</p><p>^a For p value comparison according to retinopathy status (four groups, non-parametric test, Wilcoxon's test, adjusted for multiple comparisons according to Holm)</p><p>^b Alone or in combination</p><p>Clinical and laboratory characteristics according to retinopathy status.</p

Multiple regression analysis, macula edema.

<p>Multiple regression analysis, macula edema.</p

Multiple regression analysis, severe retinopathy.

<p>Multiple regression analysis, severe retinopathy.</p

Kaplan-Meier analysis relating time to retinopathy (any versus severe versus DME) to duration of diabetes (individual survival curves are labeled).

<p>Kaplan-Meier analysis relating time to retinopathy (any versus severe versus DME) to duration of diabetes (individual survival curves are labeled).</p

Characteristics of participants with type 2 diabetes per geographic region (Nielsen area).

<p>Results are numbers (N), frequencies in % or means (SD). Abbreviation of Nielsen areas: 1 (N) = Hamburg, Bremen, Schleswig-Holstein, Lower Saxony (North); 2 (W) = North Rhine-Westfalia (West); 3 (SW) = Hesse, Rhineland-Palatinate, Saarland, Baden-Württemberg (Southwest); 4 (S) = Bavaria (South); 5 (B) = Berlin (Northeast); 6 (NE) = Mecklenburg-Vorpommern, Brandenburg, Saxony-Anhalt (Northeast); 7 (E) = Thuringia, Saxony (East). HbA1c levels in % (NGSP) can be converted to mmol/mol (IFCC) by application of the following formula: IFCC = (10.93*NGSP)−23.50.</p

Adjusted mean HbA_1c and difference in HbA_1c comparing quartiles of particulate matter (PM₁₀) exposure in type 2 diabetes patients^*.

<p>*Results are adjusted means for HbA_1c in % calculated from generalized linear regression models. Models were fitted adjusting for age, sex, body mass index, duration of diabetes, geographic region, year of treatment, and social indicators (low education, immigration background). Furthermore, difference in HbA_1c levels in % (95% CI) comparing quartiles of PM₁₀ exposure also derived from linear regression models are presented. Group differences are considered as significant (highlighted in bold) if corresponding 95% confidence intervals do not include 0. HbA1c levels in % (NGSP) can be converted to mmol/mol (IFCC) by application of the following formula: IFCC = (10.93*NGSP)−23.50.</p

Characteristics of participants with type 2 diabetes^*.

<p>*Results are numbers (N), frequencies in % or means (SD). HbA1c levels in % (NGSP) can be converted to mmol/mol (IFCC) by application of the following formula: IFCC = (10.93*NGSP)−23.50.</p

Self-reported QoL in patients with type 1 diabetes compared to KiGGS by proxy-reported mental health problems.

<p>* Defined as a SDQ score for proxy-reported total difficulties <17 and ≥17, respectively.</p>†<p>Two-sided t-test.</p>‡<p>Estimated average differences between the diabetes study and the KiGGS (reference group) adjusted for age group and sex (Model 2.1).</p>§<p>Estimated average differences between the diabetes study and the KiGGS (reference group) adjusted for age group, sex, socioeconomic status, immigration background, region of residence, family structure, weight status, and hospitalization during past twelve months (Model 2.2).</p

Proportion of adolescents with abnormal SDQ scores in patients with type 1 diabetes compared to KiGGS participants.

<p>* Based on self-reports/proxy reports, abnormal was defined as a score for total difficulties ≥20/≥17, for emotional symptoms ≥7/≥5, for conduct problems ≥5/≥4, for hyperactivity-inattention ≥7/≥7, for peer problems ≥6/≥4, for prosocial behavior <5/<5, and for impact ≥2/≥2 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0092473#pone.0092473-Goodman3" target="_blank">[25]</a>.</p>†<p>Chi-squared test.</p>‡<p>Diabetes study versus the reference group KiGGS adjusted for age group and sex (Model 1.1).</p>§<p>Diabetes study versus the reference group KiGGS adjusted for age group, sex, socioeconomic status, immigration background, region of residence, family structure, proxy-informant (except self-reports), weight status, and hospitalization during past 12 months (Model 1.2).</p