Background: Whereas it is generally accepted that maternal environment plays a key role in child health, emerging evidence suggests that paternal environment before conception also impacts child health. We aimed to investigate the association between children's asthma risk and parental smoking and welding exposures prior to conception. Methods: In a longitudinal, multi-country study, parents of 24 168 offspring aged 2-51 years provided information on their life-course smoking habits, occupational exposure to welding and metal fumes, and offspring's asthma before/after age 10 years and hay fever. Logistic regressions investigated the relevant associations controlled for age, study centre, parental characteristics (age, asthma, education) and clustering by family. Results: Non-allergic early-onset asthma (asthma without hay fever, present in 5.8%) was more common in the offspring with fathers who smoked before conception {odds ratio [OR] ¼ 1.68 [95% confidence interval (CI) ¼ 1.18-2.41]}, whereas mothers' smoking before conception did not predict offspring asthma. The risk was highest if father started smoking before age 15 years [3.24 (1.67-6.27)], even if he stopped more than 5 years before conception [2.68 (1.17-6.13)]. Fathers' pre-conception welding was independently associated with non-allergic asthma in his offspring [1.80 (1.29-2.50)]. There was no effect if the father started welding or smoking after birth. The associations were consistent across countries. Conclusions: Environmental exposures in young men appear to influence the respiratory health of their offspring born many years later. Influences during susceptible stages of spermatocyte development might be important and needs further investigation in humans. We hypothesize that protecting young men from harmful exposures may lead to improved respiratory health in future generations.

BackgroundSelection bias is a systematic error in epidemiologic studies that may seriously distort true measures of associations between exposure and disease. Observational studies are highly susceptible to selection bias, and researchers should therefore always examine to what extent selection bias may be present in their material and what characterizes the bias in their material. In the present study we examined long-term participation and consequences of loss to follow-up in the studies Respiratory Health in Northern Europe (RHINE), Italian centers of European Community Respiratory Health Survey (I-ECRHS), and the Italian Study on Asthma in Young Adults (ISAYA).MethodsLogistic regression identified predictors for follow-up participation. Baseline prevalence of 9 respiratory symptoms (asthma attack, asthma medication, combined variable with asthma attack and/or asthma medication, wheeze, rhinitis, wheeze with dyspnea, wheeze without cold, waking with chest tightness, waking with dyspnea) and 9 exposure-outcome associations (predictors sex, age and smoking; outcomes wheeze, asthma and rhinitis) were compared between all baseline participants and long-term participants. Bias was measured as ratios of relative frequencies and ratios of odds ratios (ROR).ResultsFollow-up response rates after 10 years were 75% in RHINE, 64% in I-ECRHS and 53% in ISAYA. After 20 years of follow-up, response was 53% in RHINE and 49% in I-ECRHS. Female sex predicted long-term participation (in RHINE OR (95% CI) 1.30(1.22, 1.38); in I-ECRHS 1.29 (1.11, 1.50); and in ISAYA 1.42 (1.25, 1.61)), as did increasing age. Baseline prevalence of respiratory symptoms were lower among long-term participants (relative deviations compared to total baseline population 0-15% (RHINE), 0-48% (I-ECRHS), 3-20% (ISAYA)), except rhinitis which had a slightly higher prevalence. Most exposure-outcome associations did not differ between long-term participants and all baseline participants, except lower OR for rhinitis among ISAYA long-term participating smokers (relative deviation 17% (smokers) and 44% (10–20 pack years)).ConclusionsWe found comparable patterns of long-term participation and loss to follow-up in RHINE, I-ECRHS and ISAYA. Baseline prevalence estimates for long-term participants were slightly lower than for the total baseline population, while exposure-outcome associations were mainly unchanged by loss to follow-up.

New-onset asthma and respiratory symptoms increased in women becoming postmenopausal in a longitudinal population-based study. Clinicians should be aware that respiratory health might deteriorate in women during reproductive aging.

Introduction: Variation of blood gas levels in chronic obstructive pulmonary disease (COPD) patients has not been extensively reported and there is limited knowledge about predictors of chronic respiratory failure in COPD patients. Objectives: The aim of this study was to identify predictors of hypoxemia, hypercapnia and increased alveolar-arterial oxygen difference in COPD patients. We hypothesized that prediction of arterial blood gases will be improved in multivariate models including measurements of lung function, anthropometry and systemic inflammation. Methods: A cross-sectional sample of 382 Norwegian COPD patients, age 40-76, Global Initiative for Chronic Obstructive Lung Disease stage II-IV, with a smoking history of at least 10 pack-years, underwent extensive measurements, including medical examination, arterial blood gases, systemic inflammatory markers, spirometry, plethysmography, respiratory impedance and bioelectrical impedance. Possible predictors of arterial oxygen (PaO2), arterial carbon dioxide (PaCO2) and alveolar-arterial oxygen difference (AaO2) were analyzed with both bivariate and multiple regression methods. Results: We found that various lung function measurements were significantly associated with PaO2, PaCO2 and AaO2. In addition, heart rate and Fat Mass Index were predictors of PaO2 and AaO2, while heart failure and current smoking status were associated with PaCO2. The explained variance (R 2 ) in the final multivariate regression models was 0.14-0.20. Conclusions: With a wide assortment of possible clinical predictors, we could explain 14-20% of the variation in blood gas measurements in COPD patients.Please cite this paper as: Saure EW, Eagan TML, Jensen RL, Voll-Aanerud M, Aukrust P, Bakke PS and Hardie JA. Explained variance for blood gases in a population with COPD. Clin Respir J 2012; 6: 72-80.