Cília Mejía-Lancheros1, Ramón Estruch2, Miguel A Martínez-González3, Jordi Salas-Salvadó4, Dolores Corella5, Enrique Gómez-Gracia6, Miquel Fiol7, José Lapetra8, Maria I Covas9, Fernando Arós10, Lluís Serra-Majem11, Xavier Pintó12, Josep Basora13, José V Sorlí14, Miguel A Muñoz15. 1. Departamento de Pediatría, Obstetricia, Ginecología y Medicina Preventiva, Universitat Autònoma de Barcelona, Barcelona, Spain. 2. Departamento de Medicina Interna, IDIBAPS, Hospital Clínic, Universidad de Barcelona, Barcelona, Spain; CIBER Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain. 3. Departamento de Medicina Preventiva y Salud Pública, Universidad de Navarra, Pamplona, Navarra, Spain. 4. CIBER Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain; Departamento de Nutrición Humana, IISPV, Universitat Rovira i Virgili, Reus, Tarragona, Spain. 5. CIBER Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain; Departamento de Medicina Preventiva, Universidad de Valencia, Valencia, Spain. 6. Departamento de Medicina Preventiva, Universidad de Málaga, Málaga, Spain. 7. CIBER Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain; Instituto de Ciencias de la Salud (IUNICS), Universidad de las Islas Baleares, Palma de Mallorca, Baleares, Spain. 8. CIBER Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain; Departamento de Medicina de Familia, División de Atención Primaria de Sevilla, Centro de Salud Bellavista, Sevilla, Spain. 9. CIBER Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain; Unidad de Lípidos e Investigación en Epidemiología Cardiovascular, Institut Municipal d'Investigació Mèdica (IMIM), Barcelona, Spain. 10. Departamento de Cardiología, Hospital Universitario Txagorritxu, Vitoria, Álava, Spain. 11. Departamento de Ciencias Clínicas, Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain. 12. Unidad de Lípidos y Riesgo Vascular, Medicina Interna, Hospital Universitario de Bellvitge, Hospitalet de Llobregat, Barcelona, Spain. 13. CIBER Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain; Unidad de Investigación en Atención Primaria de Tarragona, Institut Català de la Salut e IDIAP-Jordi Gol, Tarragona, Spain. 14. CIBER Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain; Departamento de Medicina Preventiva, Facultad de Medicina, Universidad de Valencia, Valencia, Spain; División de Atención Primaria, Instituto de la Salud de Valencia, Valencia, Spain. 15. Departamento de Pediatría, Obstetricia, Ginecología y Medicina Preventiva, Universitat Autònoma de Barcelona, Barcelona, Spain; Unitat de Suport a la Recerca, División de Atención Primaria de Salud, Institut Català de la Salut e IDIAP-Jordi Gol, Barcelona, Spain. Electronic address: mamunoz.bcn.ics@gencat.cat.
Abstract
INTRODUCTION AND OBJECTIVES: Although it is known that social factors may introduce inequalities in cardiovascular health, data on the role of socioeconomic differences in the prescription of preventive treatment are scarce. We aimed to assess the relationship between the socioeconomic status of an elderly population at high cardiovascular risk and inequalities in receiving primary cardiovascular treatment, within the context of a universal health care system. METHODS: Cross-sectional study of 7447 individuals with high cardiovascular risk (57.5% women, mean age 67 years) who participated in the PREDIMED study, a clinical trial of nutritional interventions for cardiovascular prevention. Educational attainment was used as the indicator of socioeconomic status to evaluate differences in pharmacological treatment received for hypertension, diabetes, and dyslipidemia. RESULTS: Participants with the lowest socioeconomic status were more frequently women, older, overweight, sedentary, and less adherent to the Mediterranean dietary pattern. They were, however, less likely to smoke and drink alcohol. This socioeconomic subgroup had a higher proportion of coexisting cardiovascular risk factors. Multivariate analysis of the whole population found no differences between participants with middle and low levels of education in the drug treatment prescribed for 3 major cardiovascular risk factors (odds ratio [95% confidence interval]): hypertension (0.75 [0.56-1.00] vs 0.85 [0.65-1.10]); diabetic participants (0.86 [0.61-1.22] vs 0.90 [0.67-1.22]); and dyslipidemia (0.93 [0.75-1.15] vs 0.99 [0.82-1.19], respectively). CONCLUSIONS: In our analysis, socioeconomic differences did not affect the treatment prescribed for primary cardiovascular prevention in elderly patients in Spain. Free, universal health care based on a primary care model can be effective in reducing health inequalities related to socioeconomic status.
INTRODUCTION AND OBJECTIVES: Although it is known that social factors may introduce inequalities in cardiovascular health, data on the role of socioeconomic differences in the prescription of preventive treatment are scarce. We aimed to assess the relationship between the socioeconomic status of an elderly population at high cardiovascular risk and inequalities in receiving primary cardiovascular treatment, within the context of a universal health care system. METHODS: Cross-sectional study of 7447 individuals with high cardiovascular risk (57.5% women, mean age 67 years) who participated in the PREDIMED study, a clinical trial of nutritional interventions for cardiovascular prevention. Educational attainment was used as the indicator of socioeconomic status to evaluate differences in pharmacological treatment received for hypertension, diabetes, and dyslipidemia. RESULTS:Participants with the lowest socioeconomic status were more frequently women, older, overweight, sedentary, and less adherent to the Mediterranean dietary pattern. They were, however, less likely to smoke and drink alcohol. This socioeconomic subgroup had a higher proportion of coexisting cardiovascular risk factors. Multivariate analysis of the whole population found no differences between participants with middle and low levels of education in the drug treatment prescribed for 3 major cardiovascular risk factors (odds ratio [95% confidence interval]): hypertension (0.75 [0.56-1.00] vs 0.85 [0.65-1.10]); diabeticparticipants (0.86 [0.61-1.22] vs 0.90 [0.67-1.22]); and dyslipidemia (0.93 [0.75-1.15] vs 0.99 [0.82-1.19], respectively). CONCLUSIONS: In our analysis, socioeconomic differences did not affect the treatment prescribed for primary cardiovascular prevention in elderly patients in Spain. Free, universal health care based on a primary care model can be effective in reducing health inequalities related to socioeconomic status.
Authors: Mariana Haeberer; Inmaculada León-Gómez; Beatriz Pérez-Gómez; María Téllez-Plaza; Mónica Pérez-Ríos; Anna Schiaffino; Fernando Rodríguez-Artalejo; Iñaki Galán Journal: PLoS One Date: 2020-09-28 Impact factor: 3.240