Percent difference and 95% confidence intervals from multivariate analysis of lung function and flow variables in relation to weighted road density within 75 m radius and 50 m radius of home.

<p>Percent difference expressed per unit increase in weighted road density variable, where one unit relates to 100</p

Data_Sheet_1_Associations between air pollution and multimorbidity in the UK Biobank: A cross-sectional study.pdf

BackgroundLong-term exposure to air pollution concentrations is known to be adversely associated with a broad range of single non-communicable diseases, but its role in multimorbidity has not been investigated in the UK. We aimed to assess associations between long-term air pollution exposure and multimorbidity status, severity, and patterns using the UK Biobank cohort.MethodsMultimorbidity status was calculated based on 41 physical and mental conditions. We assessed cross-sectional associations between annual modeled particulate matter (PM)2.5, PMcoarse, PM10, and nitrogen dioxide (NO2) concentrations (μg/m3–modeled to residential address) and multimorbidity status at the baseline assessment (2006–2010) in 364,144 people (mean age: 52.2 ± 8.1 years, 52.6% female). Air pollutants were categorized into quartiles to assess dose-response associations. Among those with multimorbidity (≥2 conditions; n = 156,395) we assessed associations between air pollutant exposure levels and multimorbidity severity and multimorbidity patterns, which were identified using exploratory factor analysis. Associations were explored using generalized linear models adjusted for sociodemographic, behavioral, and environmental indicators.ResultsHigher exposures to PM2.5, and NO2 were associated with multimorbidity status in a dose-dependent manner. These associations were strongest when we compared the highest air pollution quartile (quartile 4: Q4) with the lowest quartile (Q1) [PM2.5: adjusted odds ratio (adjOR) = 1.21 (95% CI = 1.18, 1.24); NO2: adjOR = 1.19 (95 % CI = 1.16, 1.23)]. We also observed dose-response associations between air pollutant exposures and multimorbidity severity scores. We identified 11 multimorbidity patterns. Air pollution was associated with several multimorbidity patterns with strongest associations (Q4 vs. Q1) observed for neurological (stroke, epilepsy, alcohol/substance dependency) [PM2.5: adjOR = 1.31 (95% CI = 1.14, 1.51); NO2: adjOR = 1.33 (95% CI = 1.11, 1.60)] and respiratory patterns (COPD, asthma) [PM2.5: adjOR = 1.24 (95% CI = 1.16, 1.33); NO2: adjOR = 1.26 (95% CI = 1.15, 1.38)].ConclusionsThis cross-sectional study provides evidence that exposure to air pollution might be associated with having multimorbid, multi-organ conditions. Longitudinal studies are needed to further explore these associations.</p

Relative risks and 95% confidence intervals from multivariate analysis of allergic sensitisation in relation to weighted road density within 75 m radius and 50 m radius of home.

<p>RRs expressed per unit increase in weighted road density variable, where one unit relates to 100's education, mother's education, environmental tobacco smoke exposure, breastfed to 6 months, any dog owned by 8 years, any cat owned by 8 years, maternal smoking in pregnancy, gas cooking at home.</p

(Overall Sample) Univariate and multivariate logistic regression analysis for allergic sensitisation in relation to weighted road density within 50 m radius of home.

<p>Relative Risks (RRs) expressed per unit increase in weighted road density variable, where one unit relates to 100 m local road or 33.3 m of motorway within given radius of the home.</p><p>RR is the Relative Risk per unit increase in weighted road density from Poisson regression with robust standard errors conducted on binary variables.</p>‡<p>Multivariate analyses are adjusted for sex, father's education, mother's education, environmental tobacco smoke exposure, breastfed to 6 months, any dog owned by 8 years, any cat owned by 8 years, maternal smoking in pregnancy, gas cooking at home.</p

Traffic intensity distribution within 75(Figure 1a) and 50 m of home (Figure 1b) for all children with available questionnaire or clinical data, n = 419.

<p>Traffic intensity distribution within 75(<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0098978#pone-0098978-g001" target="_blank">Figure 1a</a>) and 50 m of home (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0098978#pone-0098978-g001" target="_blank">Figure 1b</a>) for all children with available questionnaire or clinical data, n = 419.</p

(Overall Sample) Univariate and multivariate linear regression for spirometry and total IgE (kU/L) and Poisson regression with robust standard error analyses for AHR, eNO, questionnaire outcomes (all) in relation to weighted road density within 50 m radius of home.

<p>Relative Risks (RRs) and percent difference (B) expressed per unit increase in weighted road density variable, where one unit relates to 100 m local road or 33.3 m of motorway within given radius of the home.</p><p>Lung function variables are logged, therefore percent differences by B = 100(e^β−1) are presented for each unit increase in weighted road density, where β is the regression coefficient from linear regression analyses for continuous variables.</p><p>RR is the Relative Risk per unit increase in weighted road density from Poisson regression with robust standard errors conducted on binary variables.</p>‡<p>Multivariate analyses are adjusted for sex, father's education, mother's education, environmental tobacco smoke exposure, breastfed to 6 months, any dog owned by 8 years, any cat owned by 8 years, maternal smoking in pregnancy, gas cooking at home. Univariate and multivariate lung function analyses included adjustment for age, height and weight.</p>‡‡<p>p-value from additional analysis where an interaction term of weighted road density and atopy was included in the model.</p

Description of latent cardiometabolic classes by metabolic syndrome components contributing to the model in men (N = 1509).

(DOCX)</p

Model fit statistics for latent class solutions in men and women.

(DOCX)</p

Prevalence distribution and unadjusted associations of sociodemographic characteristics and health behaviours with latent classes in women (N = 1967).

(DOCX)</p

Cardiometabolic classes by metabolic syndrome components.

A) Waist circumference (cm), B) Triglyceride (mmol/l), C) HDL cholesterol, D) Systolic blood pressure (mm Hg), and E) Fasting plasma glucose (mmol/l), in male (N = 1509) and female (N = 1967) CoTaSS-2 participants in 2012–2015, Colombo, Sri Lanka. The dashed horizontal lines indicate risk thresholds according to the International Diabetes Federation and National Cholesterol Education Programme Adult Treatment Panel criteria. Higher values indicate poorer cardiometabolic function with the exception of HDL cholesterol where values below the line indicate poor cardiometabolic health. Diastolic blood pressure distributions were comparable to the systolic blood pressure presented in D) (not shown). BP, blood pressure; FPG, fasting plasma glucose; HDL-C, high-density lipoprotein cholesterol; TG, triglyceride, WC, Waist circumference.</p