Socio-economic factors, gender and smoking as determinants of COPD in a low-income country of sub-Saharan Africa: FRESH AIR Uganda.

In Uganda, biomass smoke seems to be the largest risk factor for the development of COPD, but socio-economic factors and gender may have a role. Therefore, more in-depth research is needed to understand the risk factors. The aim of this study was to investigate the impact of socio-economic factors and gender differences on the COPD prevalence in Uganda. The population comprised 588 randomly selected participants (>30 years) who previously completed the FRESH AIR Uganda study. In this post hoc analysis, the impact of several socio-economic characteristics, gender and smoking on the prevalence of COPD was assessed using a logistic regression model. The main risk factors associated with COPD were non-Bantu ethnicity (odds ratio (OR) 1.73, 95% confidence interval (CI) 1.06-2.82, P=0.030), biomass fuel use for heating (OR 1.76, 95% CI 1.03-3.00, P=0.038), former smoker (OR 1.87, 95% CI 0.97-3.60, P=0.063) and being unmarried (OR 0.087, 95% CI 0.93-2.95, P=0.087). A substantial difference in the prevalence of COPD was seen between the two ethnic groups: non-Bantu 20% and Bantu 12.9%. Additional analysis between these two groups showed significant differences in socio-economic circumstances: non-Bantu people smoked more (57.7% vs 10.7%), lived in tobacco-growing areas (72% vs 14.8%) and were less educated (28.5% vs 12.9% had no education). With regard to gender, men with COPD were unmarried (OR 3.09, 95% CI 1.25-7.61, P=0.015) and used more biomass fuel for heating (OR 2.15, 95% CI 1.02-4.54, P=0.045), and women with COPD were former smokers (OR 3.35, 95% CI 1.22-9.22, P=0.019). Only a few socio-economic factors (i.e., smoking, biomass fuel use for heating, marital status and non-Bantu ethnicity) have been found to be associated with COPD. This applied for gender differences as well (i.e., for men, marital status and biomass fuel for heating, and for women being a former smoker). More research is needed to clarify the complexity of the different risk factors

Regional differences in prediction models of lung function in Germany

<p>Abstract</p> <p>Background</p> <p>Little is known about the influencing potential of specific characteristics on lung function in different populations. The aim of this analysis was to determine whether lung function determinants differ between subpopulations within Germany and whether prediction equations developed for one subpopulation are also adequate for another subpopulation.</p> <p>Methods</p> <p>Within three studies (KORA C, SHIP-I, ECRHS-I) in different areas of Germany 4059 adults performed lung function tests. The available data consisted of forced expiratory volume in one second, forced vital capacity and peak expiratory flow rate. For each study multivariate regression models were developed to predict lung function and Bland-Altman plots were established to evaluate the agreement between predicted and measured values.</p> <p>Results</p> <p>The final regression equations for FEV₁and FVC showed adjusted r-square values between 0.65 and 0.75, and for PEF they were between 0.46 and 0.61. In all studies gender, age, height and pack-years were significant determinants, each with a similar effect size. Regarding other predictors there were some, although not statistically significant, differences between the studies. Bland-Altman plots indicated that the regression models for each individual study adequately predict medium (i.e. normal) but not extremely high or low lung function values in the whole study population.</p> <p>Conclusions</p> <p>Simple models with gender, age and height explain a substantial part of lung function variance whereas further determinants add less than 5% to the total explained r-squared, at least for FEV1 and FVC. Thus, for different adult subpopulations of Germany one simple model for each lung function measures is still sufficient.</p

Contribution of smoking and air pollution exposure in urban areas to social differences in respiratory health

<p>Abstract</p> <p>Background</p> <p>Socio-economic status, smoking, and exposure to increased levels of environmental air pollution are associated with adverse effects on respiratory health. We assessed the contribution of occupational exposures, smoking and outdoor air pollution as competing factors for the association between socio-economic status and respiratory health indicators in a cohort of women from the Ruhr area aged 55 at the time of investigation between 1985 and 1990.</p> <p>Methods</p> <p>Data of 1251 women with spirometry and complete questionnaire information about respiratory diseases, smoking and potential confounders were used in the analyses. Exposure to large-scale air pollution was assessed with data from monitoring stations. Exposure to small-scale air pollution was assessed as traffic-related exposure by distance to the nearest major road. Socio-economic status was defined by educational level. Multiple regression models were used to estimate the contribution of occupational exposures, smoking and outdoor air pollution to social differences in respiratory health.</p> <p>Results</p> <p>Women with less than 10 years of school education in comparison to more than 10 years of school education were more often occupationally exposed (16.4% vs. 10.1%), smoked more often (20.3% vs. 13.9%), and lived more often close to major roads (26.0% vs. 22.9%). Long-term exposure to increased levels of PM₁₀was significantly associated with lower school education. Women with low school education were more likely to suffer from respiratory symptoms and had reduced lung function. In the multivariate analysis the associations between education and respiratory health attenuated after adjusting for occupational exposure, smoking and outdoor air pollution. The crude odds ratio for the association between the lung function indicator FEV₁less than 80% of predicted value and educational level (<10 years vs. >10 years of school education) was 1.83 (95% CI: 1.22–2.74). This changed to 1.56 (95% CI: 1.03–2.37) after adjusting for occupational exposure, smoking and outdoor air pollution.</p> <p>Conclusion</p> <p>We found an association between socio-economic status and respiratory health. This can partly be explained by living conditions indicated by occupational exposure, smoking behaviour and ambient air pollution. A relevant part of the social differences in respiratory health, however, remained unexplained.</p

Global lung function initiative 2012 reference values for spirometry in Asian Americans

Background Spirometry reference values specifically designed for Asian Americans are currently unavailable. The performance of Global Lung Function Initiative 2012 (GLI-2012) equations on assessing spirometry in Asian Americans has not been evaluated. This study aimed to assess the fitness of relevant GLI-2012 equations for spirometry in Asian Americans. Methods Asian subjects who never smoked and had qualified spirometry data were extracted from the National Health and Nutrition Examination Survey (NHANES) 2011–2012. Z-scores of forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), and FEV1/FVC were separately constructed with GLI-2012 equations for North East (NE) Asians, South East (SE) Asians, and individuals of mixed ethnic origin (Mixed). In addition, Proportions of subjects with observed spirometry data below the lower limit of normal (LLN) were also evaluated on each GLI-2012 equation of interest. Results This study included 567 subjects (250 men and 317 women) aged 6–79 years. Spirometry z-scores (z-FEV1, z-FVC, and z-FEV1/FVC) based on GLI-2012 Mixed equations had mean values close to zero (− 0.278 to − 0.057) and standard deviations close to one (1.001 to 1.128); additionally, 6.0% (95% confidence interval (CI) 3.1–8.9%) and 6.4% (95% CI 3.7–9.1%) of subjects were with observed data below LLN for FEV1/FVC in men and women, respectively. In contrast, for NE Asian equations, all mean values of z-FEV1 and z-FVC were smaller than − 0.5; for SE Asian equations, mean values of z-FEV1/FVC were significantly smaller than zero in men (− 0.333) and women (− 0.440). Conclusions GLI-2012 equations for individuals of mixed ethnic origin adequately fitted spirometry data in this sample of Asian Americans. Future studies with larger sample sizes are needed to confirm these findings

Identification of microbial signatures linked to oilseed rape yield decline at the landscape scale

Background: The plant microbiome plays a vital role in determining host health and productivity. However, we lack real-world comparative understanding of the factors which shape assembly of its diverse biota, and crucially relationships between microbiota composition and plant health. Here we investigated landscape scale rhizosphere microbial assembly processes in oilseed rape (OSR), the UK’s third most cultivated crop by area and the world's third largest source of vegetable oil, which suffers from yield decline associated with the frequency it is grown in rotations. By including 37 conventional farmers’ fields with varying OSR rotation frequencies, we present an innovative approach to identify microbial signatures characteristic of microbiomes which are beneficial and harmful to the host. Results: We show that OSR yield decline is linked to rotation frequency in real-world agricultural systems. We demonstrate fundamental differences in the environmental and agronomic drivers of protist, bacterial and fungal communities between root, rhizosphere soil and bulk soil compartments. We further discovered that the assembly of fungi, but neither bacteria nor protists, was influenced by OSR rotation frequency. However, there were individual abundant bacterial OTUs that correlated with either yield or rotation frequency. A variety of fungal and protist pathogens were detected in roots and rhizosphere soil of OSR, and several increased relative abundance in root or rhizosphere compartments as OSR rotation frequency increased. Importantly, the relative abundance of the fungal pathogen Olpidium brassicae both increased with short rotations and was significantly associated with low yield. In contrast, the root endophyte Tetracladium spp. showed the reverse associations with both rotation frequency and yield to O. brassicae, suggesting that they are signatures of a microbiome which benefits the host. We also identified a variety of novel protist and fungal clades which are highly connected within the microbiome and could play a role in determining microbiome composition. Conclusions: We show that at the landscape scale, OSR crop yield is governed by interplay between complex communities of both pathogens and beneficial biota which is modulated by rotation frequency. Our comprehensive study has identified signatures of dysbiosis within the OSR microbiome, grown in real-world agricultural systems, which could be used in strategies to promote crop yield. [MediaObject not available: see fulltext.