Skip to main content
Top
Published in: Health and Quality of Life Outcomes 1/2013

Open Access 01-12-2013 | Research

The impact of socio-economic status on health related quality of life for children and adolescents with heart disease

Authors: Amy Cassedy, Dennis Drotar, Richard Ittenbach, Shawna Hottinger, Jo Wray, Gil Wernovsky, Jane W Newburger, Lynn Mahony, Kathleen Mussatto, Mitchell I Cohen, Bradley S Marino

Published in: Health and Quality of Life Outcomes | Issue 1/2013

Login to get access

Abstract

Background

Socioeconomic status (SES) is known to influence children’s health-related quality of life. Many SES indicators assess distinct dimensions of a family’s position rather than measuring the same underlying construct. Many researchers, however, see SES indicators as interchangeable. The primary aim of this study was to determine which measure of SES had the strongest impact on health-related quality of life.

Methods

This is a secondary analysis of the Pediatric Cardiac Quality of Life Inventory Validation Study. The SES variables were family income, Hollingshead Index (occupational prestige), and highest parent educational attainment level. Health-related quality of life was measured using the Pediatric Cardiac Quality of Life Inventory. Correlations tested the relationship among the three SES indicators. Regression-based modeling was used to calculate the strength of the association between SES measures and the Pediatric Cardiac Quality of Life Inventory.

Results

The correlations among the SES measures were moderately high, with the correlation between the Hollingshead Index and parental education being r = 0.62 (95% CI = 0.56-0.65). There were equally high correlations between family income and the Hollingshead (r = 0.61, 95% CI = 0.57-0.65) and a slightly lower correlation between family income and parental education (r = 0.55, 95% CI = 0.52-0.59). Family income had the highest explanatory value compared to the Hollingshead Index or parental educational attainment, while controlling for sex, race, current cardiac status, and original diagnosis, accounting for 4-5% of the variation in patient and parent Pediatric Cardiac Quality of Life Inventory Total score, respectively, compared to the other SES measures.

Conclusion

Family income as an SES measure demonstrated the greatest fidelity with respect to health-related quality of life as measured by the Pediatric Cardiac Quality of Life Inventory across respondent groups and explained more of the variation compared to the Hollingshead Index or highest parental educational attainment.
Literature
1.
go back to reference Drotar D: Measuring health-related quality of life in children and adolescents : implications for research and practice. Mahwah, N.J: Lawrence Erlbaum Associates, Publishers; 1998:372. Drotar D: Measuring health-related quality of life in children and adolescents : implications for research and practice. Mahwah, N.J: Lawrence Erlbaum Associates, Publishers; 1998:372.
2.
go back to reference Mansour ME, et al.: Health-related quality of life in urban elementary schoolchildren. Pediatrics 2003,111(6 Pt 1):1372–1381.PubMedCrossRef Mansour ME, et al.: Health-related quality of life in urban elementary schoolchildren. Pediatrics 2003,111(6 Pt 1):1372–1381.PubMedCrossRef
3.
go back to reference Olson LM, Lara M, Pat Frintner M: Measuring health status and quality of life for US children: relationship to race, ethnicity, and income status. Ambul Pediatr 2004,4(4):377–386. 10.1367/A03-156.1PubMedCrossRef Olson LM, Lara M, Pat Frintner M: Measuring health status and quality of life for US children: relationship to race, ethnicity, and income status. Ambul Pediatr 2004,4(4):377–386. 10.1367/A03-156.1PubMedCrossRef
4.
go back to reference Varni JW, Burwinkle TM, Seid M: The PedsQL 4.0 as a school population health measure: feasibility, reliability, and validity. Qual Life Res 2006,15(2):203–215. 10.1007/s11136-005-1388-zPubMedCrossRef Varni JW, Burwinkle TM, Seid M: The PedsQL 4.0 as a school population health measure: feasibility, reliability, and validity. Qual Life Res 2006,15(2):203–215. 10.1007/s11136-005-1388-zPubMedCrossRef
5.
go back to reference Davis SE, et al.: The PedsQL in pediatric patients with Duchenne muscular dystrophy: feasibility, reliability, and validity of the Pediatric Quality of Life Inventory Neuromuscular Module and Generic Core Scales. J Clin Neuromuscul Dis 2010,11(3):97–109. 10.1097/CND.0b013e3181c5053bPubMedCrossRef Davis SE, et al.: The PedsQL in pediatric patients with Duchenne muscular dystrophy: feasibility, reliability, and validity of the Pediatric Quality of Life Inventory Neuromuscular Module and Generic Core Scales. J Clin Neuromuscul Dis 2010,11(3):97–109. 10.1097/CND.0b013e3181c5053bPubMedCrossRef
6.
go back to reference Seid M, et al.: Reliability, validity, and responsiveness of the pediatric quality of life inventory (PedsQL) generic core scales and asthma symptoms scale in vulnerable children with asthma. J Asthma 2010,47(2):170–177. 10.3109/02770900903533966PubMedCrossRef Seid M, et al.: Reliability, validity, and responsiveness of the pediatric quality of life inventory (PedsQL) generic core scales and asthma symptoms scale in vulnerable children with asthma. J Asthma 2010,47(2):170–177. 10.3109/02770900903533966PubMedCrossRef
7.
go back to reference Marino BS, et al.: The development of the pediatric cardiac quality of life inventory: a quality of life measure for children and adolescents with heart disease. Qual Life Res 2008,17(4):613–626. 10.1007/s11136-008-9323-8PubMedCrossRef Marino BS, et al.: The development of the pediatric cardiac quality of life inventory: a quality of life measure for children and adolescents with heart disease. Qual Life Res 2008,17(4):613–626. 10.1007/s11136-008-9323-8PubMedCrossRef
9.
go back to reference Uzark K, et al.: Quality of life in children with heart disease as perceived by children and parents. Pediatrics 2008,121(5):e1060-e1067. 10.1542/peds.2006-3778PubMedCrossRef Uzark K, et al.: Quality of life in children with heart disease as perceived by children and parents. Pediatrics 2008,121(5):e1060-e1067. 10.1542/peds.2006-3778PubMedCrossRef
10.
go back to reference Duncan GJ, et al.: How much does childhood poverty affect the life chances of children? Am Sociol Rev 1998,63(3):406–423. 10.2307/2657556CrossRef Duncan GJ, et al.: How much does childhood poverty affect the life chances of children? Am Sociol Rev 1998,63(3):406–423. 10.2307/2657556CrossRef
11.
go back to reference Bornstein MH, Bradley RH: Socioeconomic status, parenting, and child development. Monographs in parenting. Mahwah, N.J: Lawrence Erlbaum Associates; 2003:287. Bornstein MH, Bradley RH: Socioeconomic status, parenting, and child development. Monographs in parenting. Mahwah, N.J: Lawrence Erlbaum Associates; 2003:287.
12.
13.
go back to reference Coleman JS: Social Capital in the Creation of Human-Capital. Am J Sociol 1988, 94: S95-S120. 10.1086/228943CrossRef Coleman JS: Social Capital in the Creation of Human-Capital. Am J Sociol 1988, 94: S95-S120. 10.1086/228943CrossRef
14.
go back to reference Entwisle DR, Astone NM: Some Practical Guidelines for Measuring Youths Race Ethnicity and Socioeconomic-Status. Child Dev 1994,65(6):1521–1540.CrossRef Entwisle DR, Astone NM: Some Practical Guidelines for Measuring Youths Race Ethnicity and Socioeconomic-Status. Child Dev 1994,65(6):1521–1540.CrossRef
15.
go back to reference Braveman PA, et al.: Socioeconomic status in health research: one size does not fit all. JAMA 2005,294(22):2879–2888. 10.1001/jama.294.22.2879PubMedCrossRef Braveman PA, et al.: Socioeconomic status in health research: one size does not fit all. JAMA 2005,294(22):2879–2888. 10.1001/jama.294.22.2879PubMedCrossRef
16.
17.
go back to reference Hollingshead ADB: Four factor index of social status1975. New Haven, Conn: Yale University, Dept. of Sociology; 1975:18–4. Hollingshead ADB: Four factor index of social status1975. New Haven, Conn: Yale University, Dept. of Sociology; 1975:18–4.
18.
go back to reference Limbers CA, et al.: A comparative analysis of health-related quality of life and family impact between children with ADHD treated in a general pediatric clinic and a psychiatric clinic utilizing the PedsQL. J Atten Disord 2011,15(5):392–402. 10.1177/1087054709356191PubMedCrossRef Limbers CA, et al.: A comparative analysis of health-related quality of life and family impact between children with ADHD treated in a general pediatric clinic and a psychiatric clinic utilizing the PedsQL. J Atten Disord 2011,15(5):392–402. 10.1177/1087054709356191PubMedCrossRef
19.
go back to reference Agha MM, et al.: Socioeconomic status and prevalence of congenital heart defects: does universal access to health care system eliminate the gap? Birth Defects Res A Clin Mol Teratol 2011,91(12):1011–1018. 10.1002/bdra.22857PubMedCrossRef Agha MM, et al.: Socioeconomic status and prevalence of congenital heart defects: does universal access to health care system eliminate the gap? Birth Defects Res A Clin Mol Teratol 2011,91(12):1011–1018. 10.1002/bdra.22857PubMedCrossRef
20.
go back to reference Cohen J: Statistical power analysis for the behavioral sciences. 2nd edition. Hillsdale, N.J: L. Erlbaum Associates; 1988:567. Cohen J: Statistical power analysis for the behavioral sciences. 2nd edition. Hillsdale, N.J: L. Erlbaum Associates; 1988:567.
21.
go back to reference Levine TR, Hullett CR: Eta squared, partial eta squared, and misreporting of effect size in communication research. Hum Commun Res 2002,28(4):612–625. 10.1111/j.1468-2958.2002.tb00828.xCrossRef Levine TR, Hullett CR: Eta squared, partial eta squared, and misreporting of effect size in communication research. Hum Commun Res 2002,28(4):612–625. 10.1111/j.1468-2958.2002.tb00828.xCrossRef
22.
go back to reference Acock AC: Working With Missing Values. J Marriage Fam 2005,67(4):1012–1028. 10.1111/j.1741-3737.2005.00191.xCrossRef Acock AC: Working With Missing Values. J Marriage Fam 2005,67(4):1012–1028. 10.1111/j.1741-3737.2005.00191.xCrossRef
23.
go back to reference De N-W, Proctor C, Bernadette D, Jessica CS: Income, Poverty, and Health Insurance Coverage in the United States. Washington, DC: Government Printing Office; 2011. De N-W, Proctor C, Bernadette D, Jessica CS: Income, Poverty, and Health Insurance Coverage in the United States. Washington, DC: Government Printing Office; 2011.
24.
go back to reference Newacheck PW, et al.: Disparities in adolescent health and health care: does socioeconomic status matter? Health Serv Res 2003,38(5):1235–1252. 10.1111/1475-6773.00174PubMedCentralPubMedCrossRef Newacheck PW, et al.: Disparities in adolescent health and health care: does socioeconomic status matter? Health Serv Res 2003,38(5):1235–1252. 10.1111/1475-6773.00174PubMedCentralPubMedCrossRef
25.
26.
go back to reference Adler NE, Newman K: Socioeconomic disparities in health: pathways and policies. Health Aff (Millwood) 2002,21(2):60–76. 10.1377/hlthaff.21.2.60CrossRef Adler NE, Newman K: Socioeconomic disparities in health: pathways and policies. Health Aff (Millwood) 2002,21(2):60–76. 10.1377/hlthaff.21.2.60CrossRef
27.
go back to reference Andersen R, Aday LA: Access to medical care in the U.S.: realized and potential. Med Care 1978,16(7):533–546. 10.1097/00005650-197807000-00001PubMedCrossRef Andersen R, Aday LA: Access to medical care in the U.S.: realized and potential. Med Care 1978,16(7):533–546. 10.1097/00005650-197807000-00001PubMedCrossRef
28.
go back to reference Cassedy A, Fairbrother G, Newacheck PW: The impact of insurance instability on children‘s access, utilization, and satisfaction with health care. Ambul Pediatr 2008,8(5):321–328. 10.1016/j.ambp.2008.04.007PubMedCrossRef Cassedy A, Fairbrother G, Newacheck PW: The impact of insurance instability on children‘s access, utilization, and satisfaction with health care. Ambul Pediatr 2008,8(5):321–328. 10.1016/j.ambp.2008.04.007PubMedCrossRef
29.
go back to reference Adler NE, et al.: Socioeconomic status and health. The challenge of the gradient. Am Psychol 1994,49(1):15–24.PubMedCrossRef Adler NE, et al.: Socioeconomic status and health. The challenge of the gradient. Am Psychol 1994,49(1):15–24.PubMedCrossRef
30.
go back to reference Adler NE, et al.: Socioeconomic inequalities in health No easy solution. JAMA 1993,269(24):3140–3145. 10.1001/jama.1993.03500240084031PubMedCrossRef Adler NE, et al.: Socioeconomic inequalities in health No easy solution. JAMA 1993,269(24):3140–3145. 10.1001/jama.1993.03500240084031PubMedCrossRef
31.
go back to reference Winkleby MA, et al.: Socioeconomic status and health: how education, income, and occupation contribute to risk factors for cardiovascular disease. Am J Public Health 1992,82(6):816–820. 10.2105/AJPH.82.6.816PubMedCentralPubMedCrossRef Winkleby MA, et al.: Socioeconomic status and health: how education, income, and occupation contribute to risk factors for cardiovascular disease. Am J Public Health 1992,82(6):816–820. 10.2105/AJPH.82.6.816PubMedCentralPubMedCrossRef
32.
go back to reference Roberts E, et al.: Early cognitive development and parental education. Infant Child Dev 1999,8(1):49–62. 10.1002/(SICI)1522-7219(199903)8:1<49::AID-ICD188>3.0.CO;2-1CrossRef Roberts E, et al.: Early cognitive development and parental education. Infant Child Dev 1999,8(1):49–62. 10.1002/(SICI)1522-7219(199903)8:1<49::AID-ICD188>3.0.CO;2-1CrossRef
33.
go back to reference Chen W, Petitti DB, Enger S: Limitations and potential uses of census-based data on ethnicity in a diverse community. Ann Epidemiol 2004,14(5):339–345. 10.1016/j.annepidem.2003.07.002PubMedCrossRef Chen W, Petitti DB, Enger S: Limitations and potential uses of census-based data on ethnicity in a diverse community. Ann Epidemiol 2004,14(5):339–345. 10.1016/j.annepidem.2003.07.002PubMedCrossRef
34.
go back to reference Geronimus AT, Bound J: Use of census-based aggregate variables to proxy for socioeconomic group: evidence from national samples. Am J Epidemiol 1998,148(5):475–486. 10.1093/oxfordjournals.aje.a009673PubMedCrossRef Geronimus AT, Bound J: Use of census-based aggregate variables to proxy for socioeconomic group: evidence from national samples. Am J Epidemiol 1998,148(5):475–486. 10.1093/oxfordjournals.aje.a009673PubMedCrossRef
35.
go back to reference Clarke CA, et al.: Interaction of area-level socioeconomic status and UV radiation on melanoma occurrence in California. Cancer Epidemiol Biomarkers Prev 2010,19(11):2727–2733. 10.1158/1055-9965.EPI-10-0692PubMedCentralPubMedCrossRef Clarke CA, et al.: Interaction of area-level socioeconomic status and UV radiation on melanoma occurrence in California. Cancer Epidemiol Biomarkers Prev 2010,19(11):2727–2733. 10.1158/1055-9965.EPI-10-0692PubMedCentralPubMedCrossRef
36.
go back to reference Geraghty EM, et al.: Using Geographic Information Systems (GIS) to assess outcome disparities in patients with type 2 diabetes and hyperlipidemia. J Am Board Fam Med 2010,23(1):88–96. 10.3122/jabfm.2010.01.090149PubMedCrossRef Geraghty EM, et al.: Using Geographic Information Systems (GIS) to assess outcome disparities in patients with type 2 diabetes and hyperlipidemia. J Am Board Fam Med 2010,23(1):88–96. 10.3122/jabfm.2010.01.090149PubMedCrossRef
Metadata
Title
The impact of socio-economic status on health related quality of life for children and adolescents with heart disease
Authors
Amy Cassedy
Dennis Drotar
Richard Ittenbach
Shawna Hottinger
Jo Wray
Gil Wernovsky
Jane W Newburger
Lynn Mahony
Kathleen Mussatto
Mitchell I Cohen
Bradley S Marino
Publication date
01-12-2013
Publisher
BioMed Central
Published in
Health and Quality of Life Outcomes / Issue 1/2013
Electronic ISSN: 1477-7525
DOI
https://doi.org/10.1186/1477-7525-11-99

Other articles of this Issue 1/2013

Health and Quality of Life Outcomes 1/2013 Go to the issue