Association between categories of smoking during pregnancy (SPD) and offspring's birthweight by different designs.

<p>All models were adjusted for gestational age, marital status, maternal age, birth order, sex of the newborn, complications during pregnancy (i.e., diabetes, hypertension and urinary problems), and Swedish snus use.</p

Characteristics of the children and the children's mothers in the two samples.

<p>Characteristics of the children and the children's mothers in the two samples.</p

Flow diagram showing the individuals excluded from the study population and the individuals included in the study samples analyzed to investigate the effect of maternal smoking during pregnancy on offspring birthweight.

<p>Flow diagram showing the individuals excluded from the study population and the individuals included in the study samples analyzed to investigate the effect of maternal smoking during pregnancy on offspring birthweight.</p

Characteristics of the mothers and babies (2002–2010) for the two samples studied.

*<p>Reference category in the analyses.</p

Flow diagram showing the selection of the study population for investigating the effect of maternal snus use during pregnancy on offspring birthweight.

<p>Flow diagram showing the selection of the study population for investigating the effect of maternal snus use during pregnancy on offspring birthweight.</p

Conventional and quasi-experimental sibling analysis of the effect of maternal snus use on offspring birthweight.

<p>All models were adjusted for gestational age, marital status, maternal age, birth order, sex of the newborn.</p

Maternal snus use and birthweight differences based on 144,017 mothers with two subsequent births.

<p>All models were adjusted for gestational age, marital status, maternal age, birth order, sex of the newborn.</p

Crude national mortality rates, number of heart failure patients, metrics on gender and age, and hospital departments included in the study.

<p>Crude national mortality rates, number of heart failure patients, metrics on gender and age, and hospital departments included in the study.</p

The role of the clinical departments for understanding patient heterogeneity in one-year mortality after a diagnosis of heart failure: A multilevel analysis of individual heterogeneity for profiling provider outcomes - Fig 2

<p><b>Ranking of 57 Danish departments for the three audit periods (A-C)</b> according to their one-year mortality for incident heart failure (21 June 2010–30 June 2013) using the overall average as reference. Values are logarithm odds ratios (i.e., shrunken residuals) with 95% confidence intervals (vertical lines) adjusted for age and gender (see model 2 in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0189050#pone.0189050.t003" target="_blank">Table 3</a>). The figure also indicates the values of the departments intra-class correlation coefficients (ICC) for one-year mortality and the AUC.</p

Measures of association (fixed effects) obtained by two-level (patients and hospitals departments) multilevel logistic regression modelling one-year mortality for heart failure patients treated in clinical departments.

<p>Values are odds ratios (OR) and 95% confidence intervals (CI).</p