Abstract:The present study investigated the relationship between socioeconomic status, using measures of occupational class and education level, and the prevalence and incidence of asthma (with and without atopy) and chronic bronchitis using data from the European Community Respiratory Health Survey (ECRHS).Asthma and chronic bronchitis were studied prospectively within the ECRHS (n59,023). Incidence analyses comprised subjects with no history of asthma or bronchitis at baseline. Asthma symptoms were also assessed as a… Show more
“…However, our study could not show any association of chronic bronchitis with male gender, despite 0% prevalence smoking in females and 17% prevalence smoking in males. Current evidence suggests that male gender is a potential risk factor for chronic bronchitis, fundamentally because of relatively high prevalence of smoking amongst males [28,32]. What was further intriguing was that, even exposure to biomass fuel smoke which has been regarded as important risk factor for respiratory morbidities [33] did not contribute to chronic bronchitis in slum women.…”
Section: Discussionmentioning
confidence: 92%
“…This is contradictory to what has been observed before. Studies have shown that prevalence of chronic bronchitis is positively related to age [28,29,32], which has been attributed to changes in immune system and negative impact of age on lung physiology. One approximate explanation to the contrary observations in our study could be, that exposures to adverse slum environmental dynamics [1,5] may trigger recurrent induction of immune processes in lungs of slum residents which could compromise lung growth during developmental stages such as childhood [34].…”
Background: Poverty is an important surrogate marker for obstructive airway diseases (OAD). Slum constitutes a habitat wherein various poverty related parameters are perpetually prevalent in the ambience. 1/6th of world population lives in slums yet there is no information regarding their health status in context to asthma and COPD. Aims: We investigated the prevalence of asthma and chronic-bronchitis symptoms and associated risk-factors in slum habitats of Pune city. Methodology: 7062 adult slum-dwellers living in 12 slums of Pune city were cross-sectionally interviewed by local healthcare workers with respiratory health questionnaire which was designed using respiratory symptoms of validated European Community Respiratory Health Survey (ECRHS II) questionnaire and International Union against Tuberculosis and Lung Disease (IUATLD) bronchial symptoms questionnaire. Results: The overall prevalence of selfreported asthma symptoms was 10% (18 -40 years: 6.5%; >40 years: 13.5%). The overall prevalence of chronic bronchitis was 8.5% [18 -40 years: 7% (males: 7%, females: 7%); >40 years: 10% (males: 10%, females: 10%)]. Increasing age (p = 0.00), female gender (p = 0.001), unemployment (0.00) current smoking (p = 0.00) and ex-smoking (p = 0.004) emerged as significant risk factor for asthma. While, ex-smoking (p = 0.004) and low-education status (p = 0.00) emerged as significant risk factors for chronic bronchitis. Conclusion: In slums reporting of asthma and chronic-bronchitis symptoms was much higher than what has been reported earlier from India. Asthma was commonly seen in females, old age, unemployed and ever-smokers. While chronic bronchitis was commonly seen in ex-smokers and illiterate subjects. Chronic bronchitis was equally distributed amongst male and females, despite 0% prevalence of smoking in females.
“…However, our study could not show any association of chronic bronchitis with male gender, despite 0% prevalence smoking in females and 17% prevalence smoking in males. Current evidence suggests that male gender is a potential risk factor for chronic bronchitis, fundamentally because of relatively high prevalence of smoking amongst males [28,32]. What was further intriguing was that, even exposure to biomass fuel smoke which has been regarded as important risk factor for respiratory morbidities [33] did not contribute to chronic bronchitis in slum women.…”
Section: Discussionmentioning
confidence: 92%
“…This is contradictory to what has been observed before. Studies have shown that prevalence of chronic bronchitis is positively related to age [28,29,32], which has been attributed to changes in immune system and negative impact of age on lung physiology. One approximate explanation to the contrary observations in our study could be, that exposures to adverse slum environmental dynamics [1,5] may trigger recurrent induction of immune processes in lungs of slum residents which could compromise lung growth during developmental stages such as childhood [34].…”
Background: Poverty is an important surrogate marker for obstructive airway diseases (OAD). Slum constitutes a habitat wherein various poverty related parameters are perpetually prevalent in the ambience. 1/6th of world population lives in slums yet there is no information regarding their health status in context to asthma and COPD. Aims: We investigated the prevalence of asthma and chronic-bronchitis symptoms and associated risk-factors in slum habitats of Pune city. Methodology: 7062 adult slum-dwellers living in 12 slums of Pune city were cross-sectionally interviewed by local healthcare workers with respiratory health questionnaire which was designed using respiratory symptoms of validated European Community Respiratory Health Survey (ECRHS II) questionnaire and International Union against Tuberculosis and Lung Disease (IUATLD) bronchial symptoms questionnaire. Results: The overall prevalence of selfreported asthma symptoms was 10% (18 -40 years: 6.5%; >40 years: 13.5%). The overall prevalence of chronic bronchitis was 8.5% [18 -40 years: 7% (males: 7%, females: 7%); >40 years: 10% (males: 10%, females: 10%)]. Increasing age (p = 0.00), female gender (p = 0.001), unemployment (0.00) current smoking (p = 0.00) and ex-smoking (p = 0.004) emerged as significant risk factor for asthma. While, ex-smoking (p = 0.004) and low-education status (p = 0.00) emerged as significant risk factors for chronic bronchitis. Conclusion: In slums reporting of asthma and chronic-bronchitis symptoms was much higher than what has been reported earlier from India. Asthma was commonly seen in females, old age, unemployed and ever-smokers. While chronic bronchitis was commonly seen in ex-smokers and illiterate subjects. Chronic bronchitis was equally distributed amongst male and females, despite 0% prevalence of smoking in females.
“…Subjects in the low occupational class (incident risk ratio (IRR) 1.4; 95%CI 1.2-1.7) and education group (IRR 1.3; 95% CI 1.1-1.6) had higher mean asthma scores than those in higher socioeconomic groups and that lower socioeconomic groups tended to have a higher prevalence and incidence of asthma, particularly higher mean asthma scores [42]. In a study by Basagana et al [41] using the same survey found similar results, that asthma prevalence was higher in lower socioeconomic groups, whether defined by educational level or social class regardless of atopic status.…”
Socioeconomic status (SES) is defined as an individual's social or economic standing, and is a measure of an individual's or family's social or economic position or rank in a social group. It is a composite of several measures including income, education, occupation, location of residence or housing. Studies have found a lower SES has been linked to disproportionate access to health care in many diseases. There is emerging data in pulmonary diseases such as COPD, asthma, cystic fibrosis, pulmonary hypertension and other chronic respiratory conditions that allude to a similar observation noted in other chronic diseases. In the setting of COPD, SES has an inverse relationship with COPD prevalence, mortality, health utilization costs and HRQoL. Asthma and cystic fibrosis show an increased severity and hospitalizations in relationship to a lower SES. Similar observations were seen in sarcoidosis, PHTN and obstructive sleep apnea. There remains a limited data on non-CF bronchiectasis and interstitial lung diseases. Population SES may be gauged by various measures such as education, occupation, marital status but no value is more indicative than income. Currently guidelines and management algorithms do not factor the effect of SES in the disease process. Despite the great amount of data available, a standardized method must be created to include SES in the prognostic calculations and management of chronic pulmonary diseases.
“…This last factor has been associated with a variety of differential health impacts, including premature mortality, asthma, and chronic bronchitis (Ellison-Loschmann et al, 2007). Traffic exposures are often higher in neighborhoods of low SES in the United States (Finkelstein et al, 2005;Ponce et al, 2005), but not necessarily in Europe (Forastiere et al, 2007).…”
Section: Problems Of Confounding Collinearity and Measurement Errormentioning
This work examines various metrics and models that have been used to estimate long-term health effects of exposure to vehicular traffic. Such health impacts may include effects of air pollution due to emissions of combustion products and from vehicle or roadway wear, of noise, stress, or from socioeconomic effects associated with preferred residential locations. Both categorical and continuous exposure metrics are considered, typically for distances between residences and roadways, or for traffic density or intensity. It appears that continuous measures of exposure tend to yield lower risk estimates that are also more precise than categorical measures based on arbitrary criteria. The selection of appropriate exposure increments to characterize relative risks is also important in comparing pollutants and other agents. Confounding and surrogate variables are also important issues, since studies of traffic proximity or density cannot identify the specific agents related to traffic exposures that might be responsible for the various health endpoints that have been implicated. Studies based on ambient air quality measurements are necessarily restricted to species for which data are available, some of which may be serving as markers for the actual agents of harm. Studies based on modeled air quality are limited by the accuracy of mobile source emission inventories, which may not include poorly maintained (high emitting) vehicles. Additional exposure modeling errors may result from precision limitations of geocoding methods. Studies of the health effects of traffic are progressing from establishing the existence of relationships to describing them in more detail, but effective remedies or control strategies have generally not yet been proposed in the context of these epidemiological studies. Resolution of these dose-response uncertainties is important for the development of effective public health strategies for the future.
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