Socioeconomic Inequality in Respiratory Health in the US From 1959 to 2018 | Asthma | JAMA Internal Medicine | JAMA Network
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Figure 1.  Prevalence of Respiratory Symptoms Among Adults Aged 40 to 74 Years by Family Income Quintile, 1959 to 2018
Prevalence of Respiratory Symptoms Among Adults Aged 40 to 74 Years by Family Income Quintile, 1959 to 2018

The dashed lines indicate a major change in the survey question. Data for each survey is presented at the middle year of the survey period (or the year following the midpoint for surveys with an even number of years). Quintile 1 = lowest quintile; quintile 5 = highest quintile. A, In the National Health Examination Survey I ([NHANES]1959-1962; presented at 1961), the question refers to shortness of breath with stairs, with 4 affirmative responses based on frequency and severity; we classified individuals as having dyspnea on exertion if they responded affirmatively regardless of frequency or severity. From NHANES I (1971-1975; presented at 1973) onward, the question refers to dyspnea with “hurrying on the level or walking up a slight hill,” and there are no frequency or severity responses (n = 48 969). B, In NHANES I (1971-1975; presented in 1973), the question refers to “trouble with recurring persistent cough attacks,” but from NHANES III (1988-1994; presented at 1991) onward it refers to “usually cough on most days for 3 consecutive months or more during the year.” Cough was not ascertained in the continuous NHANES after 2012 (n = 30 295). C, In NHANES I (1971-1975; presented in 1973), the question refers to ever having “wheezy or whistling sounds in your chest.” In NHANES II (1976-1980; presented at 1978), it asks whether “during the past 12 months, not counting colds or the flu, have you frequently had trouble with… wheezing.” From NHANES III (1988-1994; presented at 1991) and onward it refers to “wheezing or whistling” in the chest in the past 12 months. Wheezing was not ascertained in the continuous NHANES after 2012 (n = 39 537).

Figure 2.  Respiratory Disease Prevalence by Family Income Quintile, 1962 to 2018
Respiratory Disease Prevalence by Family Income Quintile, 1962 to 2018

The dashed lines indicate major changes in survey wording. Data for each survey is presented at the middle year of the survey period (or the year following the midpoint for surveys with an even number of years). Quintile 1 = lowest quintile; quintile 5 = highest quintile. A, For the National Health Examination Survey II ([NHANES] 1962-1965; presented at 1964) the question asks whether a child “ever had asthma,” and for NHANES I (1971-1975; presented at 1973), to whether a child has “ever been treated” for asthma. From NHANES II (1976-1980; presented at 1978) onward, the question refers to a physician (or other health professional for NHANES 1999-2018) ever having said the child had asthma, and if the child still had asthma. For these surveys, we only included children “still” with asthma as having asthma (n = 25 972). B, For NHES III (1966-1970; presented at 1968), the question refers to ever having asthma, but for NHANES I onward, the question asks whether a clinician ever said that the child had asthma, and if so, whether he or she still had it. For these surveys, we only included children still with asthma as having asthma (n = 24 379). C, In 1999-2000, NHANES lacked a question on whether asthma was still present among adults, and was not presented herein. Definition of asthma included only those still with asthma for all other survey years (n = 86 802). D, Defined as ever being told by a physician (or other health professional for 1999-2018) that the patient had emphysema or chronic bronchitis (n = 50 772).

Table 1.  Adjusted Effect of Income on FEV1, Adults Aged 25 to 74 Years: NHANES 1971 to 2012a
Adjusted Effect of Income on FEV1, Adults Aged 25 to 74 Years: NHANES 1971 to 2012a
Table 2.  Adjusted Effect of Education on FEV1: Adults Aged 25 to 74 Years, NHANES 1971 to 2012a
Adjusted Effect of Education on FEV1: Adults Aged 25 to 74 Years, NHANES 1971 to 2012a
Supplement.

eFigure 1. Current/Former Smoking among Adults, 1971-2018

eFigure 2. Prevalence of Respiratory Symptoms by education, 1959-2018

eFigure 3. Respiratory disease prevalence by family income, 1962-2018

eAppendix. Income Categories

eTable 1. Unweighted Response Rate

eTable 2. Education Treatment

eTable 3. Respiratory disease prevalence by education, 1962-2018

eTable 4. Details on respiratory symptom outcomes, including smoking

eTable 5. Details on disease outcomes

eTable 6. Details on spirometry

eTable 7. Age- and sex-adjusted effect on socioeconomic status on probability of reporting respiratory symptom among adults 40-74: NHANES, 1959-2018

eTable 8. Age, sex- and smoking-adjusted effect on socioeconomic status on probability of reporting respiratory symptom among adults 40-74: NHANES, 1971-2018

eTable 9. Age- and sex-adjusted effect on socioeconomic status on probability of diagnosis of asthma and COPD: NHANES, 1959-2018

eTable 10. Age, sex, and smoking-adjusted effect on socioeconomic status on probability of diagnosis of asthma and COPD: NHANES, 1971-2018

eTable 11. Smoking adjusted effect of education on FEV1: NHANES 1971-2012

eTable 12. Smoking adjusted effect of income on FEV1: NHANES 1971-2012

eTable 13. Adjusted effect of education on FVC: NHANES 1971-2012

eTable 14. Adjusted effect of income on FVC: NHANES 1971-2012

eTable 15. Smoking adjusted effect of education on FVC: NHANES 1971-2012

eTable 16. Smoking adjusted effect of income on FVC: NHANES 1971-2012

eTable 17. Age-adjusted effect of education on probability of airflow obstruction (FEV1/FVC < 70%): NHANES 1971-2012

eTable 18. Age-adjusted effect of income on probability of airflow obstruction (FEV1/FVC < 70%): NHANES 1971-2012

eTable 19. Age- and smoking-adjusted effect of education on probability of airflow obstruction (FEV1/FVC < 70%): NHANES 1971-2012

eTable 20. Age- and smoking-adjusted effect of income on probability of airflow obstruction (FEV1/FVC < 70%): NHANES 1971-2012

eReferences

1.
Sullivan  TJ, Driscoll  CT, Beier  CM,  et al  Air pollution success stories in the United States: the value of long-term observations.   Environmental Science & Policy. 2018;84:69-73. doi:10.1016/j.envsci.2018.02.016Google Scholar
2.
American Lung Association. Tobacco Trends Brief. Accessed September 9, 2020. https://www.lung.org/research/trends-in-lung-disease/tobacco-trends-brief/overall-tobacco-trends
3.
Jl  B, Jm  M.  Trends in pneumoconiosis deaths - United States, 1999-2018.   MMWR. 2020;69(23);693-698. doi:10.15585/mmwr.mm6923a1Google Scholar
4.
Akinbami  LJ, Simon  AE, Rossen  LM.  Changing trends in asthma prevalence among children.   Pediatrics. 2016;137(1). doi:10.1542/peds.2015-2354PubMedGoogle Scholar
5.
Bhan  N, Kawachi  I, Glymour  MM, Subramanian  SV.  Time trends in racial and ethnic disparities in asthma prevalence in the United States From the Behavioral Risk Factor Surveillance System (BRFSS) study (1999-2011).   Am J Public Health. 2015;105(6):1269-1275. doi:10.2105/AJPH.2014.302172PubMedGoogle Scholar
6.
Hegewald  MJ, Crapo  RO.  Socioeconomic status and lung function.   Chest. 2007;132(5):1608-1614. doi:10.1378/chest.07-1405PubMedGoogle Scholar
7.
Rocha  V, Soares  S, Stringhini  S, Fraga  S.  Socioeconomic circumstances and respiratory function from childhood to early adulthood: a systematic review and meta-analysis.   BMJ Open. 2019;9(6):e027528. doi:10.1136/bmjopen-2018-027528PubMedGoogle Scholar
8.
Gaffney  AW, Hawks  L, Bor  D,  et al.  National trends and disparities in healthcare access and coverage among adults with asthma and COPD: 1997-2018.   Chest. 2021;S0012-3692(21)00107-0. doi:10.1016/j.chest.2021.01.035PubMedGoogle Scholar
9.
Gold  DR, Wright  R.  Population disparities in asthma.   Annu Rev Public Health. 2005;26:89-113. doi:10.1146/annurev.publhealth.26.021304.144528PubMedGoogle Scholar
10.
Agaku  IT, Odani  S, Okuyemi  KS, Armour  B.  Disparities in current cigarette smoking among US adults, 2002-2016.   Tob Control. 2020;29(3):269-276. doi:10.1136/tobaccocontrol-2019-054948PubMedGoogle Scholar
11.
Dwyer-Lindgren  L, Bertozzi-Villa  A, Stubbs  RW,  et al.  Trends and patterns of differences in chronic respiratory disease mortality among US counties, 1980-2014.   JAMA. 2017;318(12):1136-1149. doi:10.1001/jama.2017.11747PubMedGoogle Scholar
12.
Crocker  D, Brown  C, Moolenaar  R,  et al.  Racial and ethnic disparities in asthma medication usage and health-care utilization: data from the National Asthma Survey.   Chest. 2009;136(4):1063-1071. doi:10.1378/chest.09-0013PubMedGoogle Scholar
13.
Keet  CA, McCormack  MC, Pollack  CE, Peng  RD, McGowan  E, Matsui  EC.  Neighborhood poverty, urban residence, race/ethnicity, and asthma: rethinking the inner-city asthma epidemic.   J Allergy Clin Immunol. 2015;135(3):655-662. doi:10.1016/j.jaci.2014.11.022PubMedGoogle Scholar
14.
Oraka  E, Iqbal  S, Flanders  WD, Brinker  K, Garbe  P.  Racial and ethnic disparities in current asthma and emergency department visits: findings from the National Health Interview Survey, 2001-2010.   J Asthma. 2013;50(5):488-496. doi:10.3109/02770903.2013.790417PubMedGoogle Scholar
15.
Pennington  E, Yaqoob  ZJ, Al-Kindi  SG, Zein  J.  Trends in asthma mortality in the United States: 1999 to 2015.   Am J Respir Crit Care Med. 2019;199(12):1575-1577. doi:10.1164/rccm.201810-1844LEPubMedGoogle Scholar
16.
Urquhart  A, Clarke  P.  US racial/ethnic disparities in childhood asthma emergent health care use: National Health Interview Survey, 2013-2015.   J Asthma. 2020;57(5):510-520. doi:10.1080/02770903.2019.1590588PubMedGoogle Scholar
17.
Vasquez  MM, Zhou  M, Hu  C, Martinez  FD, Guerra  S.  Low lung function in young adult life is associated with early mortality.   Am J Respir Crit Care Med. 2017;195(10):1399-1401. doi:10.1164/rccm.201608-1561LEPubMedGoogle Scholar
18.
Sabia  S, Shipley  M, Elbaz  A,  et al.  Why does lung function predict mortality? results from the Whitehall II cohort study.   Am J Epidemiol. 2010;172(12):1415-1423. doi:10.1093/aje/kwq294PubMedGoogle Scholar
19.
Chetty  R, Stepner  M, Abraham  S,  et al.  THe association between income and life expectancy in the United States, 2001-2014.   JAMA. 2016;315(16):1750-1766. doi:10.1001/jama.2016.4226PubMedGoogle Scholar
20.
Case  A, Deaton  A.  Rising morbidity and mortality in midlife among white non-Hispanic Americans in the 21st century.   PNAS. 2015;112(49);15078-15083. doi:10.1073/pnas.1518393112Google Scholar
21.
Krieger  N, Kosheleva  A, Waterman  PD, Chen  JT, Beckfield  J, Kiang  MV.  50-year trends in US socioeconomic inequalities in health: US-born Black and White Americans, 1959-2008.   Int J Epidemiol. 2014;43(4):1294-1313. doi:10.1093/ije/dyu047PubMedGoogle Scholar
22.
US Department of Health and Human Services. Public Use Data Tape Documentation: Spirometry-Best Trials Only Ages 25-74. National Center for Health Statistics. Published online November 1985. Accessed September 9, 2020. https://wwwn.cdc.gov/nchs/data/nhanes1/4250.pdf
23.
Third National Health and Nutrition Examination Survey (NHANES III), 1988-94 Catalog Number 76200. Published online December 1996. Accessed September 9, 2020. https://wwwn.cdc.gov/nchs/data/nhanes3/1a/exam-acc.pdf
24.
Ford  ES, Mannino  DM, Wheaton  AG, Giles  WH, Presley-Cantrell  L, Croft  JB.  Trends in the prevalence of obstructive and restrictive lung function among adults in the United States: findings from the National Health and Nutrition Examination surveys from 1988-1994 to 2007-2010.   Chest. 2013;143(5):1395-1406. doi:10.1378/chest.12-1135PubMedGoogle Scholar
25.
Gray  LA, Leyland  AH, Benzeval  M, Watt  GC.  Explaining the social patterning of lung function in adulthood at different ages: the roles of childhood precursors, health behaviours and environmental factors.   J Epidemiol Community Health. 2013;67(11):905-911. doi:10.1136/jech-2012-201704PubMedGoogle Scholar
26.
Gaffney  AW, Hang  JQ, Lee  MS, Su  L, Zhang  FY, Christiani  DC.  Socioeconomic status is associated with reduced lung function in China: an analysis from a large cross-sectional study in Shanghai.   BMC Public Health. 2016;16(1):96. doi:10.1186/s12889-016-2752-3PubMedGoogle Scholar
27.
Lipscomb  HJ, Loomis  D, McDonald  MA, Argue  RA, Wing  S.  A conceptual model of work and health disparities in the United States.   Int J Health Serv. 2006;36(1):25-50. doi:10.2190/BRED-NRJ7-3LV7-2QCGPubMedGoogle Scholar
28.
Sexton  K, Gong  H  Jr, Bailar  JC  III,  et al.  Air pollution health risks: do class and race matter?   Toxicol Ind Health. 1993;9(5):843-878. Published online May 30, 2017. doi:10.1177/074823379300900509PubMedGoogle Scholar
29.
Stanbury  M, Rosenman  KD.  Occupational health disparities: a state public health-based approach.   Am J Ind Med. 2014;57(5):596-604. doi:10.1002/ajim.22292PubMedGoogle Scholar
30.
O’Neill  MS, Jerrett  M, Kawachi  I,  et al; Workshop on Air Pollution and Socioeconomic Conditions.  Health, wealth, and air pollution: advancing theory and methods.   Environ Health Perspect. 2003;111(16):1861-1870. doi:10.1289/ehp.6334PubMedGoogle Scholar
31.
Di  Q, Wang  Y, Zanobetti  A,  et al.  Air pollution and mortality in the Medicare population.   N Engl J Med. 2017;376(26):2513-2522. doi:10.1056/NEJMoa1702747PubMedGoogle Scholar
32.
Gaffney  AW, Hawks  L, White  AC,  et al.  Health care disparities across the urban-rural divide: a national study of individuals with COPD.   J Rural Health. 2020. Published online October 11, 2020. doi:10.1111/jrh.12525PubMedGoogle Scholar
33.
Gaffney  A, White  A, Hawks  L,  et al.  High-Deductible Health Plans and Healthcare Access, Use, and Financial Strain in Those with Chronic Obstructive Pulmonary Disease.   Ann Am Thorac Soc. 2020;17(1):49-56. doi:10.1513/AnnalsATS.201905-400OCPubMedGoogle Scholar
34.
Global Initiative for Chronic Obstructive Lung. Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Pulmonary Disease (2018 Report). Accessed August 22, 2018. https://goldcopd.org/wp-content/uploads/2017/11/GOLD-2018-v6.0-FINAL-revised-20-Nov_WMS.pdf
35.
Voll-Aanerud  M, Eagan  TM, Plana  E,  et al.  Respiratory symptoms in adults are related to impaired quality of life, regardless of asthma and COPD: results from the European community respiratory health survey.   Health Qual Life Outcomes. 2010;8(1):107. doi:10.1186/1477-7525-8-107PubMedGoogle Scholar
36.
Carpenter  L, Beral  V, Strachan  D, Ebi-Kryston  KL, Inskip  H.  Respiratory symptoms as predictors of 27 year mortality in a representative sample of British adults.   BMJ. 1989;299(6695):357-361. doi:10.1136/bmj.299.6695.357PubMedGoogle Scholar
37.
Frostad  A, Soyseth  V, Haldorsen  T, Andersen  A, Gulsvik  A.  Respiratory symptoms and long-term cardiovascular mortality.   Respir Med. 2007;101(11):2289-2296. doi:10.1016/j.rmed.2007.06.023PubMedGoogle Scholar
38.
Cazzola  M, MacNee  W, Martinez  FJ,  et al; American Thoracic Society; European Respiratory Society Task Force on outcomes of COPD.  Outcomes for COPD pharmacological trials: from lung function to biomarkers.   Eur Respir J. 2008;31(2):416-469. doi:10.1183/09031936.00099306PubMedGoogle Scholar
39.
Duong  M, Islam  S, Rangarajan  S,  et al; PURE investigators.  Mortality and cardiovascular and respiratory morbidity in individuals with impaired FEV1 (PURE): an international, community-based cohort study.   Lancet Glob Health. 2019;7(5):e613-e623. doi:10.1016/S2214-109X(19)30070-1PubMedGoogle Scholar
40.
Mannino  DM, Buist  AS, Petty  TL, Enright  PL, Redd  SC.  Lung function and mortality in the United States: data from the First National Health and Nutrition Examination Survey follow up study.   Thorax. 2003;58(5):388-393. doi:10.1136/thorax.58.5.388PubMedGoogle Scholar
41.
Steptoe  A, Zaninotto  P.  Lower socioeconomic status and the acceleration of aging: an outcome-wide analysis.   Proc Natl Acad Sci U S A. 2020;117(26):14911-14917. doi:10.1073/pnas.1915741117PubMedGoogle Scholar
42.
Van Sickle  D, Magzamen  S, Mullahy  J.  Understanding socioeconomic and racial differences in adult lung function.   Am J Respir Crit Care Med. 2011;184(5):521-527. doi:10.1164/rccm.201012-2095OCPubMedGoogle Scholar
43.
Akinbami  LJ, Moorman  JE, Garbe  PL, Sondik  EJ.  Status of childhood asthma in the United States, 1980-2007.   Pediatrics. 2009;123(suppl 3):S131-S145. doi:10.1542/peds.2008-2233CPubMedGoogle Scholar
44.
Eder  W, Ege  MJ, von Mutius  E.  The asthma epidemic.   N Engl J Med. 2006;355(21):2226-2235. doi:10.1056/NEJMra054308PubMedGoogle Scholar
45.
Mannino  D, Homa  D, Pertowski  C,  et al Surveillance for Asthma–United States, 1960-1995. MMWR Morb Mortal Wkly Rep. Accessed August 5, 2020. https://www.cdc.gov/mmWr/preview/mmwrhtml/00052262.htm
46.
Halfon  N, Newacheck  PW.  Trends in the hospitalization for acute childhood asthma, 1970-84.   Am J Public Health. 1986;76(11):1308-1311. doi:10.2105/AJPH.76.11.1308PubMedGoogle Scholar
47.
Akinbami  LJ, Schoendorf  KC, Parker  J.  US childhood asthma prevalence estimates: the Impact of the 1997 National Health Interview Survey redesign.   Am J Epidemiol. 2003;158(2):99-104. doi:10.1093/aje/kwg109PubMedGoogle Scholar
48.
Gershon  AS, Hwee  J, Victor  JC, Wilton  AS, To  T.  Trends in socioeconomic status-related differences in mortality among people with chronic obstructive pulmonary disease.   Ann Am Thorac Soc. 2014;11(8):1195-1202. doi:10.1513/AnnalsATS.201403-094OCPubMedGoogle Scholar
49.
Pleasants  RA, Riley  IL, Mannino  DM.  Defining and targeting health disparities in chronic obstructive pulmonary disease.   Int J Chron Obstruct Pulmon Dis. 2016;11:2475-2496. doi:10.2147/COPD.S79077PubMedGoogle Scholar
50.
Link  BG, Phelan  J.  Social conditions as fundamental causes of disease.   J Health Soc Behav. 1995;(Spec No):80-94. Published online 1995. doi:10.2307/2626958PubMedGoogle Scholar
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    Original Investigation
    May 28, 2021

    Socioeconomic Inequality in Respiratory Health in the US From 1959 to 2018

    Author Affiliations
    • 1Cambridge Health Alliance, Cambridge, Massachusetts
    • 2Harvard Medical School, Boston, Massachusetts
    • 3City University of New York at Hunter College, New York
    • 4Harvard T.H. Chan School of Public Health, Boston, Massachusetts
    JAMA Intern Med. 2021;181(7):968-976. doi:10.1001/jamainternmed.2021.2441
    Key Points

    Question  Have socioeconomic disparities in respiratory health improved in the past 6 decades in the US?

    Findings  In this repeated cross-sectional analysis of national health examination surveys conducted from 1959 to 2018 and including 160 495participants, socioeconomic disparities in respiratory symptoms, lung disease prevalence, and pulmonary function mostly persisted, and in some instances appeared to widen.

    Meaning  Income- and education-based disparities in respiratory health have persisted, and potentially worsened, despite secular improvements in air quality and tobacco use, suggesting that the benefits of these improvements have not been equitably enjoyed; social class may function as an independent determinant of lung health.

    Abstract

    Importance  Air quality has improved and smoking rates have declined over the past half-century in the US. It is unknown whether such secular improvements, and other policies, have helped close socioeconomic gaps in respiratory health.

    Objective  To describe long-term trends in socioeconomic disparities in respiratory disease prevalence, pulmonary symptoms, and pulmonary function.

    Design, Setting, and Participants  This repeated cross-sectional analysis of the nationally representative National Health and Nutrition Examination Surveys (NHANES) and predecessor surveys, conducted from 1959 to 2018. included 160 495 participants aged 6 to 74 years.

    Exposures  Family income quintile defined using year-specific thresholds; educational attainment.

    Main Outcomes and Measures  Trends in socioeconomic disparities in prevalence of current/former smoking among adults aged 25 to 74 years; 3 respiratory symptoms (dyspnea on exertion, cough, and wheezing) among adults aged 40 to 74 years; asthma stratified by age (6-11, 12-17, and 18-74 years); chronic obstructive pulmonary disease ([COPD] adults aged 40-74 years); and 3 measures of pulmonary function (forced expiratory volume in 1 second [FEV1], forced vital capacity [FVC], and FEV1/FVC<0.70) among adults aged 24 to 74 years.

    Results  Our sample included 160 495 individuals surveyed between 1959 and 2018: 27 948 children aged 6 to 11 years; 26 956 children aged 12 to 17 years; and 105 591 adults aged 18 to 74 years. Income- and education-based disparities in smoking prevalence widened from 1971 to 2018. Socioeconomic disparities in respiratory symptoms persisted or worsened from 1959 to 2018. For instance, from 1971 to 1975, 44.5% of those in the lowest income quintile reported dyspnea on exertion vs 26.4% of those in the highest quintile, whereas from 2017 to 2018 the corresponding proportions were 48.3% and 27.9%. Disparities in cough and wheezing rose over time. Asthma prevalence rose for all children after 1980, but more sharply among poorer children. Income-based disparities in diagnosed COPD also widened over time, from 4.5 percentage points (age- and sex-adjusted) in 1971 to 11.3 percentage points from 2013 to 2018. Socioeconomic disparities in FEV1 and FVC also increased. For instance, from 1971 to 1975, the age- and height-adjusted FEV1 of men in the lowest income quintile was 203.6 mL lower than men in the highest quintile, a difference that widened to 248.5 mL from 2007 to 2012 (95% CI, −328.0 to −169.0). However, disparities in rates of FEV1/FVC lower than 0.70 changed little.

    Conclusions and Relevance  Socioeconomic disparities in pulmonary health persisted and potentially worsened over the past 6 decades, suggesting that the benefits of improved air quality and smoking reductions have not been equally distributed. Socioeconomic position may function as an independent determinant of pulmonary health.

    Introduction

    Over the past half century, air quality has improved in the US: regulations have reduced emissions of sulfur dioxide, nitrogen oxide, and ozone concentrations, and haze has cleared.1 Adult smoking rates, meanwhile, have fallen from 42.6% to 13.7%.2 In addition, although many people still face workplace hazards, safety regulations and economic change have reduced exposure to occupational pollutants such as silica and coal dust, causing deaths from pneumoconiosis to plummet.3

    However, among both children and adults, socioeconomic disparities in respiratory symptoms, disease,4,5 and function6,7 remain, probably owing to persistent disparities in exposure to unclean air, tobacco smoke, dusts and gases in the workplace, nutrition, access to health care,8 or other factors.6,9 Disparities in chronic obstructive lung disease (COPD) may have worsened in recent decades consequent to the growing socioeconomic divide in tobacco use.10 For instance, county-level geographic differences in COPD mortality widened from 1980 to 2014,11 and inequalities in asthma morbidity and mortality may have persisted,9,12-16 or even worsened in the twenty-first century.4,5

    Yet few studies of socioeconomic disparities in lung health have spanned the period that saw landmark policy changes affecting smoking (the 1964 Surgeon General’s Report), air quality (the 1970 Clean Air Act), occupational exposures (the establishment of OSHA in 1971), and health care access (Medicare, Medicaid, and the Affordable Care Act). Moreover, because reduced lung function is associated with elevated all-cause mortality (through mechanisms not fully understood),17,18 increased socioeconomic disparities in lung function may contribute to the widening gap in life expectancy between poorer and wealthier Americans in the twenty-first century.19,20

    Using national health examination surveys conducted over 6 decades, we evaluated changes in socioeconomic inequality in respiratory health in the US.

    Methods
    Data and Population

    Since 1959, the US Centers for Disease Control and Prevention has conducted health examination surveys involving questionnaires, physical examinations, and (in some years) spirometric analyses. We analyzed the National Health and Nutrition Examination Surveys (NHANES) and all predecessor surveys, including: the National Health Examination Survey (NHES) I (conducted 1959-62); NHES II (1963-65); NHES III (1966-70); NHANES I (1971-75); NHANES II (1976-80); NHANES III (1988-94), and all 2-year “continuous” NHANES (1999-2018). These surveys were designed to be representative of the civilian, non-institutionalized US population. Response rates were ≥49% for all survey years (eTable 1 in the Supplement).

    The NHES I included only adults, and NHES II and III only children (ages 6-11 years and 12-17 years, respectively). From NHANES I onward, all surveys enrolled both adults and children. Our study population included children aged 6-17 years and adults aged 18-74 years.

    Exposure

    The primary exposure was socioeconomic status (SES) defined by family income and (for adults) educational achievement.21 Each survey ascertained family income in categories, which changed over time. To produce income categories that could be compared across survey years, we assigned each individual to a family income quintile using year-specific thresholds based on US Census Bureau figures, similar to the approach of Krieger et al21 (eAppendix Note 1 in the Supplement). We categorized education as: less than high school, high school, some college, and college (eTable 2 in the Supplement). Approximately 10% or fewer individuals in our samples had missing data on income, or education (eTable 3 in the Supplement).

    Outcomes

    We examined 3 types of pulmonary outcomes (1) respiratory symptoms; (2) respiratory diagnoses; and (3) spirometry results. In addition, we assessed trends in current/former smoking prevalence, which the surveys consistently ascertained starting in 1971 with the question: “Have you smoked at least 100 cigarettes during your entire life?”

    The 3 symptoms examined were dyspnea on exertion, problem cough, and wheezing. We confined these analyses to adults aged 40 to 74 years because chronic pulmonary impairment is uncommon in younger persons. eTable 4 in the Supplement provides details on how we aligned survey questions across survey years. For instance, dyspnea on exertion was defined as shortness of breath with stairs in NHES I (1959-1962) but with “hurrying on the level or walking up a slight hill” from NHANES I (1971) onward. Problem cough was defined as “trouble with recurring persistent cough attacks” in NHANES I, but “usually cough on most days for 3 consecutive months or more during the year” in NHANES III (1988) and subsequent surveys. The wording for the question on wheezing changed twice in the 1970s to 1980s, but little from NHANES III (1988-1994) onward. Given these changes, for each symptom, we make comparisons about trends only for periods during which the relevant survey question was consistent.

    We next examined 2 disease outcomes, both defined by self-reported diagnosis from a medical professional: asthma (stratified by age: 6-11 years, 12-17 years, and 18-74 years) and COPD (aged 40-74 years). eTable 5 in the Supplement provides details of the survey questions used to classify diagnoses. Beginning with NHANES II, the definition of asthma changed to only include those still with asthma among persons aged 11 years or older (the change occurred with NHANES I among children aged 6-11 years), except among adults in the 1999 to 2000 survey, who we excluded. We again report comparisons only for periods when asthma was defined consistently. Chronic obstructive pulmonary disease was defined as ever having received a diagnosis of “chronic bronchitis or emphysema” from NHANES I onward.

    Finally, we examined disparities in 3 standard, clinically relevant measures of adult lung function: forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1), and airflow obstruction defined categorically as FEV1/FVC less than 0.70.

    Spirometry data were available from the NHANES I and III and continuous NHANES years 2007 to 2012. Because spirometry was only performed among adults aged 25 to 74 years in NHANES I, we confined our analyses to this age group across all surveys. We summarize spirometry procedures in eTable 6 in the Supplement.22,23 In brief, 3 or more spirometry trials were obtained in all surveys; the Ohio 800 spirometer was used for all NHANES I participants, whereas the Ohio 822 or 827 was used for 99% of all NHANES III participants and for all of our continuous NHANES participants. Trials were evaluated for acceptability and reproducibility criteria by NHANES technicians; we excluded individuals not meeting criteria.

    Analysis Plan

    We first examined time trends for each income and education group in the prevalence of current or former smoking, each respiratory symptom, asthma (stratified by age group), and COPD. Although we analyzed all income quintiles, we combine quintiles 2 to 4 in graphical presentations for visual clarity. Next, for each symptom or diagnosis we performed multivariable linear probability regressions adjusted for age category (except for analyses of children, which were age-stratified), sex, and either income or education category. Sensitivity analyses of binary outcomes were repeated using logistic regression and marginal effects, which, as expected for large data sets, yielded similar results and are not reported further. For multivariable analyses, we combined continuous NHANES surveys into 3 groups: 1999 to 2006, 2007 to 2012, and 2013 to 2018.

    Finally, we examined disparities in adult pulmonary function. For FEV1 and FVC, we performed sex-stratified linear regressions of the relationship between income (or education) category and each measure, controlling for height and age (we excluded the small number with missing height [n = 45]). We used a similar approach for FEV1/FVC lower than 0.70, but excluded control for height.

    In sensitivity analyses, we repeated all regressions with the addition of controls for cigarette smoking (former, current, or never).

    We used Stata statistical software (version SE 16.1, Stata corp) for all analyses, weights provided by the NHANES that generate nationally representative estimates, and Stata analysis procedures that account for the complex sampling methodology of the NHANES. Because the independent surveys prior to the continuous NHANES were not designed to allow combinations across years, we display confidence intervals for results for each period, but do not report statistical tests of time trends. The Cambridge Health Alliance institutional review board deemed this secondary analysis of deidentified, publicly available data exempt from review; informed consent was obtained from study participants by the NHANES.

    Results

    Our sample included 160 495 individuals surveyed between 1959 and 2018: 27 948 children aged 6 to 11 years; 26 956 children aged 12 to 17 years; and 105 591 adults aged 18 to 74 years (eTable 3 in the Supplement). The proportion of adults with a college education rose, from 9.8% in the 1959 to 1962 time period to 28.4% in the period between 1999 and 2018. The proportion of study populations who were female ranged from 48.7% to 52.6% across samples.

    Smoking

    Smoking rates fell among adults aged 25 to 74 years in all income and education groups between 1971 and 2018 (eFigure 1 in the Supplement). Prior to the 1980s, smoking rates varied little by income, and only modestly by education. The socioeconomic divide in smoking subsequently widened. For instance, in the period between 1971 and 1975, 62.5% of adults in the wealthiest quintile were current/former smokers, vs 56.3% in the poorest quintile; by the 2017 to 2018 time period, the corresponding figures were 34.2% and 57.9%.

    Respiratory Symptoms

    Figure 1 and eFigure 2 in the Supplement provide annual trends in symptoms by income and education for adults aged 40 to 74 years, respectively; eTables 7 and 8 in the Supplement provide adjusted estimates. Poorer and less-educated adults reported more respiratory symptoms in all surveys between 1959 and 2018; several disparities appeared to widen during that period and none narrowed.

    In the time period between 1971 and 1975, 44.5% of those in the lowest income quintile had dyspnea on exertion vs 26.4% in the highest income quintile (an 18.1 percentage point difference); in 2017 to 2018, the corresponding proportions were 48.3% and 27.9% (a 20.4 percentage point difference). The adjusted differences were slightly smaller. We found similarly persistent disparities by education.

    Income- and education-based disparities in problem cough appeared to widen. For instance, in the period between 1988 and 1994, 14.0% of those in the poorest quintile had a problem cough vs 8.6% of those in the wealthiest quintile, a 5.4 percentage point difference that doubled to 10.7 percentage points (16.5% vs 5.8%) by 2011 to 2012. Adjustment for age and sex had little effect on this disparity; further adjustment for smoking attenuated but did not eliminate it.

    Wheezing rates fell after 1988 to 1994 among those in the highest income and education groups, but remained relatively stable among those in the lowest income and education groups. As with “problem cough”, adjustment for age and sex had little effect, whereas adjustment for smoking attenuated, but did not eliminate the disparity.

    Pulmonary Diagnoses

    Figure 2; eFigure 3, and eTables 9 and 10 in the Supplement provide unadjusted and adjusted trends in disparities in asthma and COPD prevalence. Most income-based disparities increased over time, but educational disparities changed little.

    For instance, among children, asthma prevalence rose among all income groups after 1980, but more sharply among poorer children. Among children aged 6 to 11 years, asthma prevalence was 3% to 4% in all income groups in 1976 to 1980, and the difference between the poorest and wealthiest was nonsignificant. By 2017 to 2018, asthma prevalence among younger children was 14.8% in the poorest quintile vs 6.8% in the wealthiest quintile (an adjusted 4.9 percentage point difference; 95% CI, 1.6-8.2; adjusted difference vs 2013 to 2018). A similar pattern was observed in adults with asthma: the disparity between the poorest and wealthiest quintiles was small and nonsignificant before 1980, but widened to an age- and sex-adjusted difference of 4.4 percentage points by 2013 to 2018 (95% CI, 2.0-6.7). Adjustment for smoking only slightly reduced these differences. Education-based disparities in asthma among adults were small and changed little.

    Socioeconomic disparities in COPD prevalence were present throughout the 1971 to 2018 time period, and, as with asthma, income-based disparities widened over time. The prevalence of COPD among persons in the poorest quintile rose from 10.4% to 16.3%, but remained stable at 4.4% for those in the wealthiest quintile. The age- and sex-adjusted differences in COPD prevalence between the poorest and wealthiest quintiles more than doubled from 4.5 percentage points between 1971 and 1975 (95% CI, 1.7-7.3) to 11.3 percentage points in 2013 to 2018 (95% CI, 9.0-13.7). With additional adjustment for smoking, it increased from 3.9 to 8.2 percentage points. Disparities in COPD prevalence by education persisted, but did not widen over time.

    Pulmonary Function

    Table 1 and Table 2 provide sex-stratified estimates of age- and height-adjusted differences in FEV1 by income and education, respectively, among adults aged 25 to 74 years. Overall, both FVC and FEV1 showed socioeconomic differences, which widened over time. For instance, in 1971 to 1975, the mean FEV1 of men in the poorest quintile was 203.6 mL (95% CI, −299.5 mL to −107.8 mL) less than men in the wealthiest quintile. The gap increased to 248.5 mL (95% CI, −328.0 mL to −169.0 mL) in 2007-2012. Among women, the gap widened from 154.5 mL to 191.0 mL over this period. Education-based disparities followed similar patterns. Smoking adjustment only partially attenuated the disparities in FEV1 (eTables 11 and 12 in the Supplement).

    Socioeconomic differences in FVC are shown in eTables 13 to 16 in the Supplement. Disparities in FVC mostly grew after 1975, and followed a generally a similar pattern as FEV1 with smoking adjustment.

    Finally, socioeconomic disparities in airflow obstruction as measured by FEV1/FVC levels lower than 0.70 are presented in eTables 17 and 18 in the Supplement. Trends differed by sex. Among men, income-related disparities in the proportion with a ratio lower than 0.70 fell somewhat, from a 9.7 percentage point difference between the top and bottom quintiles in 1971 to 1975, to 5.5 percentage points in 2007 to 2012. In contrast, the disparity between women in the top and bottom income quintiles increased from a statistically insignificant 1.9 percentage points in 1971 to 1975 to a significant 5.8 percentage point gap in 2007 to 2012 (95% CI, 2.1- 9.5). Trends in disparities according to education were mixed among men, whereas no significant differences in airflow obstruction by education were present among women in any time period. Adjustment for smoking (eTables 19-20 in the Supplement) fully explained socioeconomic disparities in airflow obstruction in all periods.

    Discussion

    Socioeconomic inequalities in lung health that were evident in 1959 have persisted, and possibly worsened, over time. For instance, disparities in the prevalence of cough and wheezing, in diagnosed asthma and COPD, and in FEV1 and FVC, widened, trends only partly explained by differential changes in smoking. However, disparities in obstruction (defined by a ratio of FEV1:FVC <.70) changed little, and were explained by smoking. Notably, many income-based gaps in indicators of lung health persisted or potentially worsened despite secular improvements in air quality, occupational safety, tobacco control, and medical care—and in average lung function24—suggesting that the benefits of these advances have not been equitably enjoyed.

    Multiple factors likely contribute to these disparities, including unequal exposure to cigarette smoke, air pollution, workplace hazards, pulmonary infections, in utero exposures, premature birth, nutritional deficiencies, and other factors.6,25,26 Despite overall improvements in air quality and occupational exposures, individuals with lower SES and racial/ethnic minorities still encounter more unhealthy exposures in the workplace,27-29 and reside in more polluted neighborhoods.30 Destitution also increases individuals’ susceptibility to air pollution, possibly owing to interaction with other harmful exposures or chronic illness.30,31 Finally, unequal access to health care32,33 may play a role; good medical treatment of airway disease can improve symptoms and lung function.34

    The disparities we observed are likely clinically significant. Dyspnea, cough, and wheezing reduce quality of life—in persons with and without lung disease35—and are associated with cardiopulmonary mortality.36,37 The magnitude of the lung-function disparities we observed—eg, a 200 mL to 250 mL FEV1 difference between bottom and top income quintiles—exceed proposed “minimal important differences” of 100 mL to 140 mL used for drug trials.38 Also lung function is a strong predictor of all-cause, cardiovascular and pulmonary mortality,17,18,39,40 suggesting that the widening disparities we found could contribute to the growing income-based inequalities in US life-expectancy.19

    Our findings that pulmonary function is associated with SOS accord with studies in many settings and nations,6,7,41 including shorter-term analyses of NHANES data.24,42 Other studies, primarily using interview data from the National Health Interview Survey (NHIS), have found that asthma rates rose in the 1980s to the 1990s,43-46 and that disparities in asthma widened among adults between 1999 and 20115 and among children between 2001 and 2013.4 Changes in the NHIS’ asthma survey question in 1997 and 2001, however, obscure longer-term trends in that survey.4,47 In contrast, the NHANES’ asthma question has changed little since the 1970s, allowing us to construct a reliable, longer-term time series. Few studies, meanwhile, have examined long-term trends in income-based disparities in people diagnosed with COPD in the US.48,49 Previous spirometry-based analyses have examined shorter time periods, and educational but not income gaps.24

    Limitations

    This study has limitations. Although definitions of asthma and respiratory symptoms changed across surveys, we restricted our major comparisons to periods when survey questions were consistent. Our analyses of asthma and COPD prevalence relied on respondent's recall of diagnoses by a medical professional, and could reflect changes in health care access and diagnostic practices. However, this could not explain widening disparities in self-reported symptoms or spirometric measurements. Respiratory symptoms, however, could also be subject to ascertainment bias.

    Overall, SES is complex, and each measure of it has shortcomings. Interpretation of educational attainment is complicated by compositional changes: in earlier decades fewer people (and many fewer women) attended college, including many with middle-class incomes. More recently, persons lacking higher education have been a shrinking and relatively more disadvantaged share of the population. A different set of issues apply to evaluating inequality using income quintiles. Following previous practice,21 we did not adjust family income for family size. Although quintiles are considered “a scale-free [metric that] can validly be compared both over time and cross-nationally,21[pg.1298] population shifts (eg, the increasing share of Hispanics in the poorest quintiles) may change the demographic composition of particular income groups, but unfortunately Hispanic ethnicity was not documented in the earlier surveys. Moreover, the scale-free nature of a quintile-based income measure obscures the widening income inequalities that increase the distance between quintiles, and hence differences in exposures.

    In addition, correlations between income and illness can reflect reverse causality (ie, illness-causing impoverishment), although this would not easily explain widening income-based disparities over time, or disparities by educational attainment. Our repeated cross-sectional study design precluded analyzing SES and respiratory health within individuals over time. More broadly, our analysis was designed to describe—rather than explain—respiratory disparities; hence, we did not adjust the models for the innumerable factors (other than tobacco use) that may connect SES with poor respiratory health, such as occupation or health care access. Moreover, we lacked data on important potential mediators, eg, air pollution exposure.

    Conclusions

    In 1995, Link and Phelan50 called SES a fundamental determinant of disease. Privileged individuals, they contended, are best situated to evade health hazards, inhabit salubrious environments, and obtain optimal treatments, even as hazards, environments, and treatments change over time. Consequently, when 1 mediator between SES and disease fades, they argued, another may rise to takes its place.50 The persistent, and in many instances apparently growing socioeconomic disparities in respiratory health we observed over a 6-decade period suggest that inequality is a possible fundamental determinant of respiratory health and illness.

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    Article Information

    Accepted for Publication: March 31, 2012.

    Published Online: May 28, 2021. doi:10.1001/jamainternmed.2021.2441

    Corresponding Author: Adam W. Gaffney, MD, Cambridge Health Alliance/Harvard Medical School, 1493 Cambridge St, Cambridge, MA 02138 (agaffney@challiance.org).

    Correction: This article was corrected on July 1, 2021, to fix an error in the sample size presented in the Abstract, Key Points, and text.

    Author Contributions: Dr Gaffney had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

    oncept and design: All authors.

    Acquisition, analysis, or interpretation of data: Gaffney, Himmelstein, Woolhandler.

    Drafting of the manuscript: Gaffney, Christiani.

    Critical revision of the manuscript for important intellectual content: All authors.

    Statistical analysis: Gaffney, Christiani.

    Supervision: Himmelstein, Christiani, Woolhandler.

    Conflict of Interest Disclosures: Drs Gaffney, Himmelstein, and Woolhandler have served as leaders of Physicians for a National Health Program (PNHP), a nonprofit organization that favors coverage expansion through a single-payer program; however, none of them receive any compensation from that group, although some of Dr Gaffney’s travel on behalf of the organization has been reimbursed by it. No othert conflicts are reported.

    References
    1.
    Sullivan  TJ, Driscoll  CT, Beier  CM,  et al  Air pollution success stories in the United States: the value of long-term observations.   Environmental Science & Policy. 2018;84:69-73. doi:10.1016/j.envsci.2018.02.016Google Scholar
    2.
    American Lung Association. Tobacco Trends Brief. Accessed September 9, 2020. https://www.lung.org/research/trends-in-lung-disease/tobacco-trends-brief/overall-tobacco-trends
    3.
    Jl  B, Jm  M.  Trends in pneumoconiosis deaths - United States, 1999-2018.   MMWR. 2020;69(23);693-698. doi:10.15585/mmwr.mm6923a1Google Scholar
    4.
    Akinbami  LJ, Simon  AE, Rossen  LM.  Changing trends in asthma prevalence among children.   Pediatrics. 2016;137(1). doi:10.1542/peds.2015-2354PubMedGoogle Scholar
    5.
    Bhan  N, Kawachi  I, Glymour  MM, Subramanian  SV.  Time trends in racial and ethnic disparities in asthma prevalence in the United States From the Behavioral Risk Factor Surveillance System (BRFSS) study (1999-2011).   Am J Public Health. 2015;105(6):1269-1275. doi:10.2105/AJPH.2014.302172PubMedGoogle Scholar
    6.
    Hegewald  MJ, Crapo  RO.  Socioeconomic status and lung function.   Chest. 2007;132(5):1608-1614. doi:10.1378/chest.07-1405PubMedGoogle Scholar
    7.
    Rocha  V, Soares  S, Stringhini  S, Fraga  S.  Socioeconomic circumstances and respiratory function from childhood to early adulthood: a systematic review and meta-analysis.   BMJ Open. 2019;9(6):e027528. doi:10.1136/bmjopen-2018-027528PubMedGoogle Scholar
    8.
    Gaffney  AW, Hawks  L, Bor  D,  et al.  National trends and disparities in healthcare access and coverage among adults with asthma and COPD: 1997-2018.   Chest. 2021;S0012-3692(21)00107-0. doi:10.1016/j.chest.2021.01.035PubMedGoogle Scholar
    9.
    Gold  DR, Wright  R.  Population disparities in asthma.   Annu Rev Public Health. 2005;26:89-113. doi:10.1146/annurev.publhealth.26.021304.144528PubMedGoogle Scholar
    10.
    Agaku  IT, Odani  S, Okuyemi  KS, Armour  B.  Disparities in current cigarette smoking among US adults, 2002-2016.   Tob Control. 2020;29(3):269-276. doi:10.1136/tobaccocontrol-2019-054948PubMedGoogle Scholar
    11.
    Dwyer-Lindgren  L, Bertozzi-Villa  A, Stubbs  RW,  et al.  Trends and patterns of differences in chronic respiratory disease mortality among US counties, 1980-2014.   JAMA. 2017;318(12):1136-1149. doi:10.1001/jama.2017.11747PubMedGoogle Scholar
    12.
    Crocker  D, Brown  C, Moolenaar  R,  et al.  Racial and ethnic disparities in asthma medication usage and health-care utilization: data from the National Asthma Survey.   Chest. 2009;136(4):1063-1071. doi:10.1378/chest.09-0013PubMedGoogle Scholar
    13.
    Keet  CA, McCormack  MC, Pollack  CE, Peng  RD, McGowan  E, Matsui  EC.  Neighborhood poverty, urban residence, race/ethnicity, and asthma: rethinking the inner-city asthma epidemic.   J Allergy Clin Immunol. 2015;135(3):655-662. doi:10.1016/j.jaci.2014.11.022PubMedGoogle Scholar
    14.
    Oraka  E, Iqbal  S, Flanders  WD, Brinker  K, Garbe  P.  Racial and ethnic disparities in current asthma and emergency department visits: findings from the National Health Interview Survey, 2001-2010.   J Asthma. 2013;50(5):488-496. doi:10.3109/02770903.2013.790417PubMedGoogle Scholar
    15.
    Pennington  E, Yaqoob  ZJ, Al-Kindi  SG, Zein  J.  Trends in asthma mortality in the United States: 1999 to 2015.   Am J Respir Crit Care Med. 2019;199(12):1575-1577. doi:10.1164/rccm.201810-1844LEPubMedGoogle Scholar
    16.
    Urquhart  A, Clarke  P.  US racial/ethnic disparities in childhood asthma emergent health care use: National Health Interview Survey, 2013-2015.   J Asthma. 2020;57(5):510-520. doi:10.1080/02770903.2019.1590588PubMedGoogle Scholar
    17.
    Vasquez  MM, Zhou  M, Hu  C, Martinez  FD, Guerra  S.  Low lung function in young adult life is associated with early mortality.   Am J Respir Crit Care Med. 2017;195(10):1399-1401. doi:10.1164/rccm.201608-1561LEPubMedGoogle Scholar
    18.
    Sabia  S, Shipley  M, Elbaz  A,  et al.  Why does lung function predict mortality? results from the Whitehall II cohort study.   Am J Epidemiol. 2010;172(12):1415-1423. doi:10.1093/aje/kwq294PubMedGoogle Scholar
    19.
    Chetty  R, Stepner  M, Abraham  S,  et al.  THe association between income and life expectancy in the United States, 2001-2014.   JAMA. 2016;315(16):1750-1766. doi:10.1001/jama.2016.4226PubMedGoogle Scholar
    20.
    Case  A, Deaton  A.  Rising morbidity and mortality in midlife among white non-Hispanic Americans in the 21st century.   PNAS. 2015;112(49);15078-15083. doi:10.1073/pnas.1518393112Google Scholar
    21.
    Krieger  N, Kosheleva  A, Waterman  PD, Chen  JT, Beckfield  J, Kiang  MV.  50-year trends in US socioeconomic inequalities in health: US-born Black and White Americans, 1959-2008.   Int J Epidemiol. 2014;43(4):1294-1313. doi:10.1093/ije/dyu047PubMedGoogle Scholar
    22.
    US Department of Health and Human Services. Public Use Data Tape Documentation: Spirometry-Best Trials Only Ages 25-74. National Center for Health Statistics. Published online November 1985. Accessed September 9, 2020. https://wwwn.cdc.gov/nchs/data/nhanes1/4250.pdf
    23.
    Third National Health and Nutrition Examination Survey (NHANES III), 1988-94 Catalog Number 76200. Published online December 1996. Accessed September 9, 2020. https://wwwn.cdc.gov/nchs/data/nhanes3/1a/exam-acc.pdf
    24.
    Ford  ES, Mannino  DM, Wheaton  AG, Giles  WH, Presley-Cantrell  L, Croft  JB.  Trends in the prevalence of obstructive and restrictive lung function among adults in the United States: findings from the National Health and Nutrition Examination surveys from 1988-1994 to 2007-2010.   Chest. 2013;143(5):1395-1406. doi:10.1378/chest.12-1135PubMedGoogle Scholar
    25.
    Gray  LA, Leyland  AH, Benzeval  M, Watt  GC.  Explaining the social patterning of lung function in adulthood at different ages: the roles of childhood precursors, health behaviours and environmental factors.   J Epidemiol Community Health. 2013;67(11):905-911. doi:10.1136/jech-2012-201704PubMedGoogle Scholar
    26.
    Gaffney  AW, Hang  JQ, Lee  MS, Su  L, Zhang  FY, Christiani  DC.  Socioeconomic status is associated with reduced lung function in China: an analysis from a large cross-sectional study in Shanghai.   BMC Public Health. 2016;16(1):96. doi:10.1186/s12889-016-2752-3PubMedGoogle Scholar
    27.
    Lipscomb  HJ, Loomis  D, McDonald  MA, Argue  RA, Wing  S.  A conceptual model of work and health disparities in the United States.   Int J Health Serv. 2006;36(1):25-50. doi:10.2190/BRED-NRJ7-3LV7-2QCGPubMedGoogle Scholar
    28.
    Sexton  K, Gong  H  Jr, Bailar  JC  III,  et al.  Air pollution health risks: do class and race matter?   Toxicol Ind Health. 1993;9(5):843-878. Published online May 30, 2017. doi:10.1177/074823379300900509PubMedGoogle Scholar
    29.
    Stanbury  M, Rosenman  KD.  Occupational health disparities: a state public health-based approach.   Am J Ind Med. 2014;57(5):596-604. doi:10.1002/ajim.22292PubMedGoogle Scholar
    30.
    O’Neill  MS, Jerrett  M, Kawachi  I,  et al; Workshop on Air Pollution and Socioeconomic Conditions.  Health, wealth, and air pollution: advancing theory and methods.   Environ Health Perspect. 2003;111(16):1861-1870. doi:10.1289/ehp.6334PubMedGoogle Scholar
    31.
    Di  Q, Wang  Y, Zanobetti  A,  et al.  Air pollution and mortality in the Medicare population.   N Engl J Med. 2017;376(26):2513-2522. doi:10.1056/NEJMoa1702747PubMedGoogle Scholar
    32.
    Gaffney  AW, Hawks  L, White  AC,  et al.  Health care disparities across the urban-rural divide: a national study of individuals with COPD.   J Rural Health. 2020. Published online October 11, 2020. doi:10.1111/jrh.12525PubMedGoogle Scholar
    33.
    Gaffney  A, White  A, Hawks  L,  et al.  High-Deductible Health Plans and Healthcare Access, Use, and Financial Strain in Those with Chronic Obstructive Pulmonary Disease.   Ann Am Thorac Soc. 2020;17(1):49-56. doi:10.1513/AnnalsATS.201905-400OCPubMedGoogle Scholar
    34.
    Global Initiative for Chronic Obstructive Lung. Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Pulmonary Disease (2018 Report). Accessed August 22, 2018. https://goldcopd.org/wp-content/uploads/2017/11/GOLD-2018-v6.0-FINAL-revised-20-Nov_WMS.pdf
    35.
    Voll-Aanerud  M, Eagan  TM, Plana  E,  et al.  Respiratory symptoms in adults are related to impaired quality of life, regardless of asthma and COPD: results from the European community respiratory health survey.   Health Qual Life Outcomes. 2010;8(1):107. doi:10.1186/1477-7525-8-107PubMedGoogle Scholar
    36.
    Carpenter  L, Beral  V, Strachan  D, Ebi-Kryston  KL, Inskip  H.  Respiratory symptoms as predictors of 27 year mortality in a representative sample of British adults.   BMJ. 1989;299(6695):357-361. doi:10.1136/bmj.299.6695.357PubMedGoogle Scholar
    37.
    Frostad  A, Soyseth  V, Haldorsen  T, Andersen  A, Gulsvik  A.  Respiratory symptoms and long-term cardiovascular mortality.   Respir Med. 2007;101(11):2289-2296. doi:10.1016/j.rmed.2007.06.023PubMedGoogle Scholar
    38.
    Cazzola  M, MacNee  W, Martinez  FJ,  et al; American Thoracic Society; European Respiratory Society Task Force on outcomes of COPD.  Outcomes for COPD pharmacological trials: from lung function to biomarkers.   Eur Respir J. 2008;31(2):416-469. doi:10.1183/09031936.00099306PubMedGoogle Scholar
    39.
    Duong  M, Islam  S, Rangarajan  S,  et al; PURE investigators.  Mortality and cardiovascular and respiratory morbidity in individuals with impaired FEV1 (PURE): an international, community-based cohort study.   Lancet Glob Health. 2019;7(5):e613-e623. doi:10.1016/S2214-109X(19)30070-1PubMedGoogle Scholar
    40.
    Mannino  DM, Buist  AS, Petty  TL, Enright  PL, Redd  SC.  Lung function and mortality in the United States: data from the First National Health and Nutrition Examination Survey follow up study.   Thorax. 2003;58(5):388-393. doi:10.1136/thorax.58.5.388PubMedGoogle Scholar
    41.
    Steptoe  A, Zaninotto  P.  Lower socioeconomic status and the acceleration of aging: an outcome-wide analysis.   Proc Natl Acad Sci U S A. 2020;117(26):14911-14917. doi:10.1073/pnas.1915741117PubMedGoogle Scholar
    42.
    Van Sickle  D, Magzamen  S, Mullahy  J.  Understanding socioeconomic and racial differences in adult lung function.   Am J Respir Crit Care Med. 2011;184(5):521-527. doi:10.1164/rccm.201012-2095OCPubMedGoogle Scholar
    43.
    Akinbami  LJ, Moorman  JE, Garbe  PL, Sondik  EJ.  Status of childhood asthma in the United States, 1980-2007.   Pediatrics. 2009;123(suppl 3):S131-S145. doi:10.1542/peds.2008-2233CPubMedGoogle Scholar
    44.
    Eder  W, Ege  MJ, von Mutius  E.  The asthma epidemic.   N Engl J Med. 2006;355(21):2226-2235. doi:10.1056/NEJMra054308PubMedGoogle Scholar
    45.
    Mannino  D, Homa  D, Pertowski  C,  et al Surveillance for Asthma–United States, 1960-1995. MMWR Morb Mortal Wkly Rep. Accessed August 5, 2020. https://www.cdc.gov/mmWr/preview/mmwrhtml/00052262.htm
    46.
    Halfon  N, Newacheck  PW.  Trends in the hospitalization for acute childhood asthma, 1970-84.   Am J Public Health. 1986;76(11):1308-1311. doi:10.2105/AJPH.76.11.1308PubMedGoogle Scholar
    47.
    Akinbami  LJ, Schoendorf  KC, Parker  J.  US childhood asthma prevalence estimates: the Impact of the 1997 National Health Interview Survey redesign.   Am J Epidemiol. 2003;158(2):99-104. doi:10.1093/aje/kwg109PubMedGoogle Scholar
    48.
    Gershon  AS, Hwee  J, Victor  JC, Wilton  AS, To  T.  Trends in socioeconomic status-related differences in mortality among people with chronic obstructive pulmonary disease.   Ann Am Thorac Soc. 2014;11(8):1195-1202. doi:10.1513/AnnalsATS.201403-094OCPubMedGoogle Scholar
    49.
    Pleasants  RA, Riley  IL, Mannino  DM.  Defining and targeting health disparities in chronic obstructive pulmonary disease.   Int J Chron Obstruct Pulmon Dis. 2016;11:2475-2496. doi:10.2147/COPD.S79077PubMedGoogle Scholar
    50.
    Link  BG, Phelan  J.  Social conditions as fundamental causes of disease.   J Health Soc Behav. 1995;(Spec No):80-94. Published online 1995. doi:10.2307/2626958PubMedGoogle Scholar
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