Cut points for biomarkers and prevalence of high-risk biomarkers with cut point and quartile method.

<p>AL, allostatic load.</p><p>Cut points for biomarkers and prevalence of high-risk biomarkers with cut point and quartile method.</p

Relationship of Serum Vitamin D Concentrations and Allostatic Load as a Measure of Cumulative Biological Risk among the US Population: A Cross-Sectional Study

<div><p>Introduction</p><p>The allostatic load (AL) index is a multi-systemic measure of physiologic dysregulation known to be associated with chronic exposure to stress and adverse health outcomes. We examined the relationship between AL and serum 25-hydroxyvitamin D (25(OH)D) concentration in non-institutionalized US adults.</p><p>Methods</p><p>Data from the Third National Health and Nutrition Examination Survey (NHANES III, 1988–94) were used to calculate two versions of AL including 9 biomarkers and another two with 14 biomarkers (systolic and diastolic blood pressure, pulse rate, serum cholesterol, serum HDL-cholesterol, glycated hemoglobin, sex-specific waist-to-hip ratio, serum albumin, and serum C-reactive protein for AL1, and, additionally body mass index, serum triglyceride, serum creatinine, and serum herpes I & II antibodies for AL2), each set defined by predefined cut-offs or by quartiles. Serum vitamin D concentration was ranked into quartiles. Logistic regression, Poisson regression and linear regression were used to examine the association of serum 25(OH)D concentrations on AL, after adjusting for biological, physiological, socioeconomic, lifestyle, and health variables.</p><p>Results</p><p>Odds Ratios (OR) for high AL of the lowest 25(OH)D serum quartile were between 1.45 (95% CI: 1.28, 1.67) and 1.79 (95% CI: 1.39, 2.32) for the fully adjusted model, depending on AL version. Inverse relationships between vitamin D serum concentrations were observed for all AL versions and every adjustment. This relationship was consistent after stratification by sex, age or ethnic background. Sensitivity to low 25(OH)D concentrations was highest among the youngest group (20–39 years) with an OR of 2.11 (95% CI: 1.63, 2.73) for the lowest vitamin D quartile Q1.</p><p>Conclusions</p><p>Vitamin D had a consistent and statistically significant inverse association with all tested models of high AL, which remained consistent after adjusting for biological, socioeconomic, lifestyle and health variables. Our study adds evidence linking low 25(OH)D concentrations with poorer health, further-reaching than bone health.</p></div

Logistic regression analysis of the allostatic load index and 25(OH)D concentrations stratified by health covariates.

<p>Results are stratified by self-reported health status, and long-term medication and are presented as ORs for high AL with 95% confidence intervals. Q, 25(OH)D concentrations in quartiles with Q1 lowest and Q4 highest quartile (reference).</p

Logistic regression analysis of the allostatic load index and 25(OH)D concentrations stratified by biological covariates.

<p>Results are stratified by sex, age, and ethnic background and are presented as ORs for high AL with 95% confidence intervals. Q, 25(OH)D concentrations in quartiles with Q1 lowest and Q4 highest quartile (reference).</p

Procedure to establish the four allostatic load versions.

<p>AL, allostatic load index, BMI, body mass index, HDL-cholesterol, high-density lipoprotein-cholesterol.</p

Baseline characteristics by AL1 cut point and 25(OH)D concentration quartiles.

<p>AL, allostatic load; 25(OH)D, 25-hydroxyvitamin D concentration in quartiles.</p><p>Baseline characteristics by AL1 cut point and 25(OH)D concentration quartiles.</p

Regression results for AL and 25(OH)D concentration.

<p>For logistic regression AL, allostatic load, was included as a binary variable (high or low). For Poisson regression AL, allostatic load, was included as count of the numbers of biomarkers at risk; 25(OH)D, serum 25-hydroxyvitamin D concentration. AL was the only variable considered for the basic, unadjusted model. As „biological”factors age, sex and race/ethnicity were included, “socioeconomic” variables comprised education, census region, urbanization, marital status, poverty-income ratio, “lifestyle” factors alcohol consumption, smoking status, physical activity, diet. Additionally, self-reported general health was added to the full model.</p><p>Regression results for AL and 25(OH)D concentration.</p

Proportion of Fabry patients with bronchial obstruction over time, divided by cigarette smoking.

<p>All values on y-axis are presented as percentage of patients with bronchial obstruction which was defined as FEV1/FVC < 70%.</p

Proportion of Fabry patients with bronchial obstruction over time.

<p>All values on y-axis are presented as percentage of patients with bronchial obstruction which was defined as FEV1/FVC < 70%.</p

Results of generalized linear mixed models for pulmonary obstruction with random intercept and slope for each patient.

<p>Results of generalized linear mixed models for pulmonary obstruction with random intercept and slope for each patient.</p