Do self-reported data accurately measure health inequalities in risk factors for cardiovascular disease?
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This study aimed to compare the magnitude of educational inequalities in self-reported and examination-based hypertension and hypercholesterolemia and to assess the impact of self-reported measurement error on health inequality indicators.
We used the Portuguese National Health Examination Survey data (n = 4911). The slope index of inequality (SII) and the relative index of inequality (RII) were used to determine the magnitude of absolute and relative education-related inequalities.
Among the 25–49-year-old (yo) men, absolute and relative inequalities were smaller for self-reported than for examination-based hypertension (SIIeb = 0.18 vs. SIIsr = − 0.001, p < 0.001; RIIeb = 1.99 vs. RIIsr = 0.86, p = 0.031). For women, the relative inequalities were similar despite differences in self-reported and examination-based hypertension prevalence. For hypercholesterolemia, self-reported relative inequalities were larger than examination-based inequalities among the 50–74-yo men (RIIsr = 2.28 vs. RIIeb = 1.21, p = 0.004) and women (RIIsr = 1.22 vs. RIIeb= 0.87, p = 0.045), while no differences were observed among 25–49-yo.
Self-reported data underestimated educational inequalities among 25–49-yo men and overestimated them in older individuals. Inequality indicators derived from self-report should be interpreted with caution, and examination-based values should be preferred, when available.
KeywordsHealth examination survey Health inequalities Hypercholesterolemia Hypertension Self-report
The Portuguese National Health Examination Survey (INSEF) was developed as part of the pre-defined project of the Public Health Initiatives Program, “Improvement of epidemiological health information to support public health decision and management in Portugal. Towards reduced inequalities, improved health, and bilateral cooperation,” that benefits from a 1.500.000€ Grant from Iceland, Liechtenstein, and Norway through the EEA Grants and Portuguese Government. The authors are grateful to all professionals who were involved in the INSEF implementation and to all INSEF participants.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
- Cutler DM, Lleras-Muney A (2010) Understanding differences in health behaviors by education. J Health Econ 29:1–28. https://doi.org/10.1016/j.jhealeco.2009.10.003.Understanding CrossRefGoogle Scholar
- Direção Geral da Saúde (2013) Abordagem Terapêutica das Dislipidemias no Adulto. LisboaGoogle Scholar
- Durack-Bown I, Giral P, d’Ivernois J-F et al (2003) Patients’ and physicians’ perceptions and experience of hypercholesterolaemia: a qualitative study. Br J Gen Pract 53(496):851–857Google Scholar
- Ernstsen L, Strand BH, Nilsen SM et al (2012) Trends in absolute and relative educational inequalities in four modifiable ischaemic heart disease risk factors: repeated cross-sectional surveys from the Nord-Trøndelag Health Study (HUNT) 1984–2008. BMC Public Health 12:266. https://doi.org/10.1186/1471-2458-12-266 CrossRefGoogle Scholar
- Fifth Joint Task Force of the European Society of Cardiology, European Association of Echocardiography, European Association of Percutaneous Cardiovascular Interventions et al (2012) European guidelines on cardiovascular disease prevention in clinical practice (version 2012). Eur J Prev Cardiol 19:585–667. https://doi.org/10.1177/2047487312450228 CrossRefGoogle Scholar
- Official Journal of the European Union (2014) Regulation (EU) No 282/2014 of the European Parliament and of the Council of 11 March 2014 on the establishment of a third programme for the Union’s action in the field of health (2014–2020). Off J Eur Union 13Google Scholar
- Reiner Z, Catapano AL, De Backer G et al (2011) ESC/EAS guidelines for the management of dyslipidaemias: the task force for the management of dyslipidaemias of the European Society of Cardiology (ESC) and the European Atherosclerosis Society (EAS). Eur Heart J 32:1769–1818. https://doi.org/10.1093/eurheartj/ehr158 CrossRefGoogle Scholar
- StataCorp (2017) Stata Statistical Software: Release 15. StataCorp, College StationGoogle Scholar
- Tolonen H, Koponen P, Aromaa A et al (2008) Recommendations for the health examination surveys in Europe. Julkaisija-Utgivare-Publisher, HelsinkiGoogle Scholar
- Tolonen H, Koponen P, Mindell JS et al (2014b) Under-estimation of obesity, hypertension and high cholesterol by self-reported data: comparison of self-reported information and objective measures from health examination surveys. Eur J Public Health 24:941–948. https://doi.org/10.1093/eurpub/cku074 CrossRefGoogle Scholar
- United Nations Educational Scientific and Cultural Organization (2011) International standard classification of education. United Nations Educational Scientific and Cultural Organization, ParisGoogle Scholar
- Vellakkal S, Millett C, Basu S et al (2015) Are estimates of socioeconomic inequalities in chronic disease artefactually narrowed by self-reported measures of prevalence in low-income and middle-income countries? Findings from the WHO-SAGE survey. J Epidemiol Community Health 69:218–225. https://doi.org/10.1136/jech-2014-204621 CrossRefGoogle Scholar
- Wilkins E, Wilson L, Wickramasinghe K et al (2017) European cardiovascular disease statistics 2017 edition, vol 34. European Heart Network, Brussels, p 192. ISBN 978-2-9537898-1-2Google Scholar