Rationale and Objectives
Higher socioeconomic status (SES) has been associated with lower respiratory mortality and better lung function, but whether a similar gradient exists for computed tomography (CT) measures of subclinical emphysema is unknown.
Materials and Methods
The Multi-Ethnic Study of Atherosclerosis (MESA) recruited African-American, Chinese, Hispanic, and white participants, ages 45 to 84 years, without clinical cardiovascular disease, from six US sites between 2000 and 2002. The MESA Lung Study assessed percent emphysema, defined based on the proportion of pixels below an attenuation threshold of 910 HU from lung windows of cardiac CT scans. Generalized linear models were adjusted for demographic characteristics, height, body mass index, history of respiratory illness, occupational and residential exposures, tobacco use, and CT scanner type.
Results
Among 3706 participants with a mean age of 61 (±10), the median value for percent emphysema was 18 (interquartile range = 20). Compared with those who did not complete high school, participants with a graduate degree had a higher percent emphysema (difference of 4; P < .001). Income and wealth were also positively associated with percent emphysema. In contrast, higher SES was associated with better lung function. Descriptive and subgroup analyses were used to explore potential explanations for divergent results, including the possibility that suboptimal inspiration during CT scanning would decrease percent emphysema, making the lungs appear healthier when effort is relatively poor.
Conclusion
Although SES indicators were positively associated with subclinical emphysema detectable on CT scan, this unexpected association may highlight potential bias because of effort dependence of both CT measures and spirometry.
Socioeconomic disparities for respiratory mortality may be comparable to or larger than disparities for other major causes of death . A strong socioeconomic gradient has also been observed for subclinical respiratory health measures such as lung function . Suggested mechanisms for such an association include not only smoking and tobacco exposure , but also occupational and neighborhood exposures , obesity , and stress .
Socioeconomic status (SES) may also be associated with subclinical emphysema measured with computed tomography (CT), but no previous studies have assessed this relationship in a large, population-based sample. Subclinical emphysema is moderately correlated with but distinct from impaired lung function. We hypothesized that greater educational attainment, income, and wealth would be associated with less emphysema-like patterns on CT scans.
Materials and methods
Setting and Subjects
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CT Measures of Lung Density
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Spirometry Measures of Lung Function
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Socioeconomic Measures
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Demographic Characteristics, Tobacco Use, and Other Covariates
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Statistical Analysis
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Results
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Table 1
Participant Characteristics the MESA Lung Study, 2000–2006 (n = 3706)
Mean (SD) or % p25, Median, p75 Personal characteristics Male, % 49.4 Age, y 61 (10) 53, 61, 69 Adult height, cm 167 (10) 159, 166, 174 Body mass index 28 (5) 24, 27, 31 Black, % 25.3 Chinese, % 16.6 Hispanic, % 22.6 White, % 35.5 Born outside of United States, % 36.6 Health and tobacco exposure history Asthma before age 45, % 8.1 Hay fever, % 33.0 Family history of emphysema, % 4.7 Never smoked cigarettes, % 47.4 Current cigarette smoker, % 15.3 Former cigarette smoker, % 37.3 Pack-years for current/former cigarette smokers 20 (29) 3, 13, 29 Lived with a smoker, % 42.9 Second-hand tobacco exposure at work, % 39.8 Occupational dust exposure, % 36.6 Socioeconomic characteristics Education, estimated years 14 (4) 12, 14, 16 Annual household income, $1000s per person 26 (20) 11, 22, 38 Employed, % 52.4 Unemployed, % 1.9 Home maker, % 10.4 Retired, % 35.2 Car ownership, % 81.8 Home ownership, % 66.1 Financial investments, % 62.0 Real estate investments, % 26.4 Wealth index, range 0 to 4 2.4 (1.3) 1, 3, 3 Lung density and lung function Percent emphysema 20 (13) 9, 18, 29 Percent predicted FEV 1 94 (18) 83, 95, 105 Percent predicted FVC 96 (16) 85, 95, 106 Percent predicted FEV 1 /FVC ratio 98 (11) 93, 100, 105
FEV 1 , forced expiratory volume in 1 second; FVC, forced vital capacity; p25, 25th percentile; p75, 75th percentile.
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Socioeconomic Correlates of CT Lung Density
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Table 2
Adjusted Associations of Education, Income, and Wealth with Computed Tomography Measures of Emphysema in the MESA Lung Study, 2000–2006
Difference per SES Category ∗ β (95% CI)P Value Percent emphysema Education1.1 ( 0.8 to 1.5)<.001 Income0.4 ( 0.1 to 0.8).012 Wealth0.6 ( 0.3 to 1.0).001 FEV 1 (mL) Education17 ( 5 to 29).006 Income 7 (−5 to 19) .269 Wealth16 ( 3 to 29).018 FVC (mL) Education25 ( 10 to 40).001 Income 2 (−13 to 16) .819 Wealth18 ( 2 to 34).030 FEV 1 /FVC ratio (%) Education −0.1 (−0.3 to 0.2) .544 Income 0.2 (−0.0 to 0.4) .062 Wealth 0.2 (−0.1 to 0.4) .221
FEV 1 , forced expiratory volume in 1 second; FVC, forced vital capacity; SES, socioeconomic status.
Bold font indicates statistical significance.
Values shown are regression coefficients and 95% confidence intervals for an additional increment of a grouped linear variable with a range of 0 through 4 for education (less than a high school education; high school degree; some college; completed college; graduate degree), income (lowest quintile, <$9000 per person annually; highest quintile, >$40 000 per person annually) or wealth (no wealth indicators reported; only one indicator reported; two indicators reported; three indicators reported; car ownership, home ownership, financial investments, and real estate investments all reported); and the difference between extreme categories can be calculated by multiplying difference coefficient by 4.
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Potential for Bias from Effort Dependence
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Table 3
Spirometry Effort Indicator Associated with Socioeconomic Indicators, Lung Function, and Computed Tomography Measures of Subclinical Respiratory Disease in the Multi-Ethnic Study of Atherosclerosis, 2000–2006
Acceptable Expiratory Time,
≥6 seconds Insufficient Expiratory Time,
<6 seconds Adjusted ∗ Difference
(95% CI) n 3602 102 Socioeconomic characteristics Education, estimated years 14 120.8 ( 0.1 to 1.5) Annual household income, $1000s per person 26 23 2.1 (−0.9 to 5.1) Wealth index, range 0 to 4 2.4 2.0 0.2 (0.0 to 0.4) Lung function measures from spirometry Percent predicted FEV 1 94 93 2 (−2 to 6) Percent predicted FVC 96 8314 ( 11 to 17) Percent predicted FEV 1 /FVC ratio 98 111−14 ( −16 to −12) Low attenuation areas and air volume from CT Percent emphysema, median 20 183.4 ( 1.5 to 5.4) Estimated air volume in lungs 2333 2020145 ( 52 to 239)
CT, computed tomography; FEV 1 , forced expiratory volume in 1 second; FVC, forced vital capacity.
Bold font indicates statistical significance.
Values are means unless otherwise specified.
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Discussion
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Supplementary data
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Appendix
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References
1. Naess O., Claussen B., Thelle D.S., et. al.: Four indicators of socioeconomic position: relative ranking across causes of death. Scand J Public Health 2005; 33: pp. 215-221.
2. Davey Smith G., Hart C., Blane D., et. al.: Adverse socioeconomic conditions in childhood and cause specific adult mortality: prospective observational study. BMJ 1998; 316: pp. 1631-1635.
3. Phelan J.C., Link B.G., Diez-Roux A., et. al.: “Fundamental causes” of social inequalities in mortality: a test of the theory. J Health Soc Behav 2004; 45: pp. 265-285.
4. Prescott E., Vestbo J.: Socioeconomic status and chronic obstructive pulmonary disease. Thorax 1999; 54: pp. 737-741.
5. Shohaimi S., Welch A., Bingham S., et. al.: Area deprivation predicts lung function independently of education and social class. Eur Respir J 2004; 24: pp. 157-161.
6. Jackson B., Kubzansky L.D., Cohen S., et. al.: A matter of life and breath: childhood socioeconomic status is related to young adult pulmonary function in the CARDIA study. Int J Epidemiol 2004; 33: pp. 271-278.
7. Haustein K.O.: Smoking and poverty. Eur J Cardiovasc Prev Rehabil 2006; 13: pp. 312-318.
8. Hnizdo E., Sullivan P.A., Bang K.M., et. al.: Association between chronic obstructive pulmonary disease and employment by industry and occupation in the US population: a study of data from the Third National Health and Nutrition Examination Survey. Am J Epidemiol 2002; 156: pp. 738-746.
9. Thorn J., Bjorkelund C., Bengtsson C., et. al.: Low socio-economic status, smoking, mental stress and obesity predict obstructive symptoms in women, but only smoking also predicts subsequent experience of poor health. Int J Med Sci 2007; 4: pp. 7-12.
10. Pembroke T.P., Rasul F., Hart C.L., et. al.: Psychological distress and chronic obstructive pulmonary disease in the Renfrew and Paisley (MIDSPAN) study. J Epidemiol Community Health 2006; 60: pp. 789-792.
11. Bild D.E., Bluemke D.A., Burke G.L., et. al.: Multi-ethnic study of atherosclerosis: objectives and design. Am J Epidemiol 2002; 156: pp. 871-881.
12. Carr J.J., Nelson J.C., Wong N.D., et. al.: Calcified coronary artery plaque measurement with cardiac CT in population-based studies: standardized protocol of Multi-Ethnic Study of Atherosclerosis (MESA) and Coronary Artery Risk Development in Young Adults (CARDIA) study. Radiology 2005; 234: pp. 35-43.
13. Hoffman E.A., Jiang R., Baumhauer H., et. al.: Reproducibility and validity of lung density measures from cardiac CT xcans—The Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study. Acad Radiol 2009; 16: pp. 689-699.
14. Guo J., Reinhardt J.M., Kitaoka H., et. al.: Integrated system for CT-based assessment of parenchymal lung disease. In: International Symposium on Biomedical Imaging.2002.IEEEWashington, D.C. p. 871–874
15. Hu S., Hoffman E.A., Reinhardt J.M.: Automatic lung segmentation for accurate quantitation of volumetric X-ray CT images. IEEE Trans Med Imaging 2001; 20: pp. 490-498.
16. Coxson H.O., Mayo J.R., Behzad H., et. al.: Measurement of lung expansion with computed tomography and comparison with quantitative histology. J Appl Physiol 1995; 79: pp. 1525-1530.
17. Miller M.R., Hankinson J., Brusasco V., et. al.: Standardisation of spirometry. Eur Respir J 2005; 26: pp. 319-338.
18. Hankinson J.L., Kawut S.M., Shahar E., et. al.: Performance of American Thoracic Society-recommended spirometry reference values in a multiethnic sample of adults: the multi-ethnic study of atherosclerosis (MESA) lung study. Chest 2010; 137: pp. 138-145.
19. Auchincloss A.H., Diez Roux A.V., Brown D.G., et. al.: Association of insulin resistance with distance to wealthy areas: the multi-ethnic study of atherosclerosis. Am J Epidemiol 2007; 165: pp. 389-397.
20. Ferris B.G.: Epidemiology Standardization Project (American Thoracic Society). Am Rev Respir Dis 1978; 118: pp. 1-120.
21. Auchincloss A.H., Roux A.V., Dvonch J.T., et. al.: Associations between recent exposure to ambient fine particulate matter and blood pressure in the Multi-Ethnic Study of Atherosclerosis (MESA). Environ Health Perspect 2008; 116: pp. 486-491.
22. Royston P.: Multiple imputation of missing values. Stata J 2004; 4: pp. 227-241.
23. Hoffman E.A., Simon B.A., McLennan G.: State of the art. A structural and functional assessment of the lung via multidetector-row computed tomography: phenotyping chronic obstructive pulmonary disease. Proc Am Thorac Soc 2006; 3: pp. 519-532.
24. Lovasi G.S., Diez Roux A.V., Hoffman E.A., et. al.: Association of environmental tobacco smoke exposure in childhood with early emphysema in adulthood among nonsmokers: the MESA-lung study. Am J Epidemiol 2010; 171: pp. 54-62.
25. Prescott E., Lange P., Vestbo J.: Socioeconomic status, lung function and admission to hospital for COPD: results from the Copenhagen City Heart Study. Eur Respir J 1999; 13: pp. 1109-1114.
26. Prescott E., Godtfredsen N., Vestbo J., et. al.: Social position and mortality from respiratory diseases in males and females. Eur Respir J 2003; 21: pp. 821-826.
27. Barr R., Bluemke D., Ahmed F., et. al.: Percent emphysema, airflow obstruction, and impaired left ventricular filling. N Engl J Med 2010; 362: pp. 217.
28. Klein R., Knudtson M.D., Klein B.E., et. al.: Emphysema, airflow limitation, and early age-related macular degeneration. Arch Ophthalmol 2010; 128: pp. 472-477.
29. Lederer D.J., Enright P.L., Kawut S.M., et. al.: Cigarette smoking is associated with subclinical parenchymal lung disease: the Multi-Ethnic Study of Atherosclerosis (MESA)-lung study. Am J Respir Crit Care Med 2009; 180: pp. 407-414.
30. Barr RG, Carr JJ, Hoffman EA, et al. Subclinical cardiovascular disease in chronic obstructive pulmonary disease. The MESA Lung Study. In: International Conference of the American Thoracic Society. San Francisco, CA; 2007.
31. Barr RG, Diez Roux AV, Shen M, et al. Long term exposure to particulate matter and emphysema on CT scan: the MESA Lung Study. In: International Conference of the European Respiratory Society. Vienna, Austria; 2009.
32. Rothman K.J.: No adjustments are needed for multiple comparisons. Epidemiology 1990; 1: pp. 43-46.