Cross-sectional association between plasma selenium and adiponectin concentrations at baseline^*

*<p>Results were obtained from linear regression models of log-transformed adiponectin levels on selenium levels using only cross-sectional data from the</p><p>baseline visit.</p>†<p>Model 1 adjusted for age (continuous), sex, and study center (Bungay, Guisborough, Bromsgrove, or Linthorpe).</p>‡<p>Model 2 further adjusted for smoking status (never, former, or current), drinking habits (never, former, or current), body mass index (continuous), and waist circumference (continuous).</p>§<p>Model 3 further adjusted for total cholesterol level (continuous), HDL cholesterol level (continuous), use of lipid lowering medications, and use of diabetes medications.</p><p>∥<i>P</i> values for linear trend were obtained from Wald tests for the coefficient of an ordinal variable with the median baseline selenium level of each quartile in linear regression models.</p

Descriptive baseline characteristics overall and by treatment group^*

*<p>Data are means (SDs) or numbers (%) in participants with at least one adiponectin measurement available either at baseline or at six months.</p>†<p><i>P</i> values for homogeneity of means or proportions across the four treatment groups, as obtained from one-way analysis-of-variance <i>F</i> tests for continuous variables and Pearson’s chi-squared tests for categorical variables.</p><p>HDL, high-density lipoprotein.</p

Effect of selenium supplementation on changes in plasma adiponectin and selenium concentrations after six months^*

*<p>Results were obtained from linear mixed models on log-transformed adiponectin levels (and untransformed selenium levels) with fixed treatment-by-time interactions and random between-subject variations in both baseline levels (intercepts) and longitudinal changes over time (slopes).</p>†<p><i>P</i> values comparing the ratio of geometric mean adiponectin levels (and the change in arithmetic mean selenium levels) at six months to baseline in each active treatment group to placebo, as obtained from Wald tests for each treatment-by-time interaction coefficient in linear mixed models.</p>‡<p>Overall <i>P</i> value comparing the three active treatment groups to placebo, as obtained from the joint Wald test for all treatment-by-time interaction coefficients in linear mixed models.</p

Daily hospital admission rates for chronic obstructive pulmonary disease and asthma by single calendar year in selected Spanish provinces, 2003–2012.

<p>Average daily admission rates for each calendar year were obtained from overdispersed Poisson additive models with single-year indicators and adjusted for seasonality, day of the week, temperature, influenza epidemics, acute respiratory infections, and pollen counts for asthma-related admissions (only available in Asturias, Barcelona, Madrid, Murcia, and Zaragoza). Rates refer to 1,000,000 population ≥ 18 years for cardiovascular diseases, ≥ 40 years for chronic obstructive pulmonary disease, and all ages for asthma. Vertical dashed lines represent the dates at which the partial and comprehensive smoking bans entered into force on January 1^st, 2006, and January 2^nd, 2011, respectively.</p

Population-average and province-specific segmented linear trends in hospital admission rate ratios for chronic obstructive pulmonary disease and asthma in selected Spanish provinces, 2003–2012.

<p>Province-specific segmented linear trends in hospital admission rate ratios (gray lines) were obtained from overdispersed Poisson additive models with distinct linear segments within the 2003–2005 pre-ban, 2006–2010 partial ban, and 2011–2012 comprehensive ban periods, and adjusted for seasonality, day of the week, temperature, influenza epidemics, acute respiratory infections, and pollen counts for asthma-related admissions (only available in Asturias, Barcelona, Madrid, Murcia, and Zaragoza). Pooled segmented linear trends (bold black lines) were obtained from random-effects multivariate meta-analyses on province-specific estimates of segmented regression coefficients. The reference time point (rate ratio = 1) was set at the midpoint pre-ban period (July 1^st, 2004). Vertical dashed lines represent the dates at which the partial and comprehensive smoking bans entered into force on January 1^st, 2006, and January 2^nd, 2011, respectively.</p

Pooled changes in hospital admission rates for chronic obstructive pulmonary disease (COPD) immediately after and at the one-year mark of the implementation of the 2006 partial and 2011 comprehensive smoking bans by characteristics of the fourteen largest Spanish provinces, 2003–2012^*.

<p>Pooled changes in hospital admission rates for chronic obstructive pulmonary disease (COPD) immediately after and at the one-year mark of the implementation of the 2006 partial and 2011 comprehensive smoking bans by characteristics of the fourteen largest Spanish provinces, 2003–2012^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0177979#t003fn001" target="_blank">*</a>}.</p

Summary statistics for average daily hospital admissions and other population characteristics across the fourteen largest Spanish provinces, 2003–2012.

<p>Summary statistics for average daily hospital admissions and other population characteristics across the fourteen largest Spanish provinces, 2003–2012.</p

Table_1_Socio-geographical disparities of obesity and excess weight in adults in Spain: insights from the ENE-COVID study.DOCX

BackgroundIn Spain, differences in the prevalence of obesity and excess weight according to sex and sociodemographic factors have been described at the national level, although current data do not allow to delve into geographical differences for these conditions. The aim was to estimate national and regional prevalences of adult obesity and excess weight in Spain by sex and sociodemographic characteristics, and to explore difference sources of inequalities in its distribution, as well as its geographical pattern.MethodENE-COVID study was a nationwide representative seroepidemiological survey with 57,131 participants. Residents in 35,893 households were selected from municipal rolls using a two-stage random sampling stratified by province and municipality size (April–June 2020). Participants (77.0% of contacted individuals) answered a questionnaire which collected self-reported weight and height, as well as different socioeconomic variables, that allowed estimating crude and standardized prevalences of adult obesity and excess weight.ResultsCrude prevalences of obesity and excess weight were higher in men (obesity: 19.3% vs. 18.0%; excess weight: 63.7% vs. 48.4%), while severe obesity was more prevalent in women (4.5% vs. 5.3%). These prevalences increased with age and disability, and decreased with education, census tract income and municipality size. Differences by educational level, relative census income, nationality or disability were clearly higher among women. Obesity by province ranged 13.3–27.4% in men and 11.4–28.1% in women; excess weight ranged 57.2–76.0% in men and 38.9–59.5% in women. The highest prevalences were located in the southern half of the country and some north-western provinces. Sociodemographic characteristics only explained a small part of the observed geographical variability (25.2% obesity).ConclusionObesity and overweight have a high prevalence in Spain, with notable geographical and sex differences. Socioeconomic inequalities are stronger among women. The observed geographical variability suggests the need to implement regional and local interventions to effectively address this public health problem.</p

Table_5_Socio-geographical disparities of obesity and excess weight in adults in Spain: insights from the ENE-COVID study.DOCX

BackgroundIn Spain, differences in the prevalence of obesity and excess weight according to sex and sociodemographic factors have been described at the national level, although current data do not allow to delve into geographical differences for these conditions. The aim was to estimate national and regional prevalences of adult obesity and excess weight in Spain by sex and sociodemographic characteristics, and to explore difference sources of inequalities in its distribution, as well as its geographical pattern.MethodENE-COVID study was a nationwide representative seroepidemiological survey with 57,131 participants. Residents in 35,893 households were selected from municipal rolls using a two-stage random sampling stratified by province and municipality size (April–June 2020). Participants (77.0% of contacted individuals) answered a questionnaire which collected self-reported weight and height, as well as different socioeconomic variables, that allowed estimating crude and standardized prevalences of adult obesity and excess weight.ResultsCrude prevalences of obesity and excess weight were higher in men (obesity: 19.3% vs. 18.0%; excess weight: 63.7% vs. 48.4%), while severe obesity was more prevalent in women (4.5% vs. 5.3%). These prevalences increased with age and disability, and decreased with education, census tract income and municipality size. Differences by educational level, relative census income, nationality or disability were clearly higher among women. Obesity by province ranged 13.3–27.4% in men and 11.4–28.1% in women; excess weight ranged 57.2–76.0% in men and 38.9–59.5% in women. The highest prevalences were located in the southern half of the country and some north-western provinces. Sociodemographic characteristics only explained a small part of the observed geographical variability (25.2% obesity).ConclusionObesity and overweight have a high prevalence in Spain, with notable geographical and sex differences. Socioeconomic inequalities are stronger among women. The observed geographical variability suggests the need to implement regional and local interventions to effectively address this public health problem.</p

Smooth longitudinal associations between changes in adiposity markers and intraocular pressure over time.

<p>Curves represent average longitudinal changes in intraocular pressure (solid lines) and their 95% confidence intervals (dashed lines) based on restricted quadratic splines for adiposity marker changes over time with knots at the 5th, 50th, and 95th percentiles and constrained to be 0 at baseline. Results were obtained from linear mixed models with random variations in baseline intraocular pressure levels and intraocular pressure changes over time across participants and between eyes within participants, and adjusted for baseline adiposity marker levels (restricted quadratic splines), sex (male or female), study center (Seoul or Suwon), height (continuous), and baseline levels and changes over time in age (continuous), intraocular pressure measurement time (morning or afternoon), smoking status (never, former, or current), alcohol drinking (< 1, 1–3, or > 3 days/week), physical activity (none, 1–3, or > 3 times/week), heart rate (continuous), hypertension (yes or no), and diabetes (yes or no). Histograms represent the frequency distributions of adiposity marker changes.</p