Stelmach W, Kaczmarczyk-Chałas K, Bielecki W, Stelmach I, Drygas W. How income and education contribute to risk factors for cardiovascular disease in the elderly in a former Communist country.
Public Health 2004;
118:439-49. [PMID:
15313598 DOI:
10.1016/j.puhe.2003.12.012]
[Citation(s) in RCA: 14] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2003] [Revised: 09/20/2003] [Accepted: 12/02/2003] [Indexed: 11/24/2022]
Abstract
OBJECTIVES
Careful examination of the risk factors for cardiovascular disease (CVD) may enable clinicians to develop a reasonably preventive programme among the elderly. The main purpose of this paper was to examine the effects of income and education on CVD risk factors in an elderly population who had lived most of their lives in Communist times.
METHODS
The CINDI (Countrywide Integrated Non-communicable Diseases Intervention) Programme questionnaire was used to collect data from an elderly (65+ years) population in Lodz, a large industrial city in Poland. The study population (n = 1,461) was selected at random, and the overall response rate was 57.1%. The following risk factors were evaluated: hypertension, obesity, elevated cholesterol, elevated blood sugar and smoking.
RESULTS
Hypertension was the most frequently observed CVD risk factor (83.4% of participants) followed by hypercholesterolaemia (70.2%), obesity (30.5%), diabetes (18.4%) and smoking (8.5%). Hypertension and hypercholesterolaemia were related to age (OR=0.91, 95%CI: 0.88-0.95 and OR=0.95, 95%CI: 0.92-0.98, respectively). The younger people in the study population exhibited the highest prevalence of hypertension and hypercholesterolaemia; hypercholesterolaemia was observed more frequently among widowed respondents. Obesity and diabetes were associated with education level (OR=0.52, 95%CI: 0.34-0.79 and OR=0.60, 95%CI: 0.37-0.97, respectively). Younger single males with a lower level of education and income exhibited the highest prevalence of smoking. Multivariate analysis showed that age, education and gender were the best predictors for the cumulative risk factors of CVD.
CONCLUSIONS
Education is more strongly associated with CVD risk factors than material status in the elderly. The best predictors of risk factors were age, sex and education. As we gain knowledge about CVD risk factors, we may be able to target preventive services in the elderly population more accurately and effectively, and help older adults make health decisions to reduce risk factors and increase their quality of life.
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