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BMC Public Health 2006
Determinants of a healthy lifestyle and use of preventive screening in CanadaAbstract: Data from the Canadian National Population Health Survey (NPHS) 1998–9 were used. Independent variables were income, education, age, sex, marital status, body mass index, urban/rural residence and access to a regular physician. Dependent variables included smoking, excessive alcohol use, physical activity, blood pressure checks, mammography in past year and Pap smear in past 3 years. Logistic regression models were developed for each dependent variable.13,756 persons 20 years of age and older completed the health portion of the NPHS. In general, higher levels of income were associated with healthier behaviours, as were higher levels of education, although there were exceptions to both. The results for age and gender also varied depending on the outcome. The presence of a regular medical doctor was associated with increased rates of all preventive screening and reduced rates of smoking.These results expand upon previous data suggesting that socioeconomic disparities in healthy behaviours and health promotion continue to exist despite equal access to medical screening within the Canadian healthcare context. Knowledge, resources and the presence of a regular medical doctor are important factors associated with identified differences.A socioeconomic gradient favouring those with greater income exists for a variety of chronic conditions, including cardiovascular disease, most cancers, diabetes, hypertension, arthritis, respiratory disease, gastrointestinal disease and metabolic syndrome [1]. Many of these can be prevented, identified early, or ameliorated by screening and individual behaviour.Major behavioral factors affecting health include nutrition, physical activity, tobacco use, and excessive alcohol consumption. Low socioeconomic status has been associated with a more sedentary lifestyle and lower fruit and vegetable consumption [2]. A study based on the 1990 Canadian Health Promotion Survey found significant associations between socioeconomic class and patterns of
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