Health behaviours as explanations for educational level differences in cardiovascular and all-cause mortality: a follow-up of 60 000 men and women over 23 years

Laaksonen, Mikko; Talala, Kirsi; Martelin, Tuija; Rahkonen, Ossi; Roos, Eva; Helakorpi, Satu; Laatikainen, Tiina; Prättälä, Ritva

doi:10.1093/eurpub/ckm051

Cited by 245 publications

(237 citation statements)

References 28 publications

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“…We found lower SRH in patients with a lower education level. The level of education can be connected with unhealthy behaviour, as shown in other studies (24). Associations of lower education and economic status on the self-assessment of health and negative prediction of chronic diseases on the self-rating of health were also found in other studies (25,26).…”

Section: Interpretation Of the Study Resultssupporting

confidence: 67%

Evaluation of self-rated health – information on patients’ unmet needs?

Petek

Kersnik

2014

Slovenian Journal of Public Health

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Section: Interpretation Of the Study Resultssupporting

confidence: 67%

Evaluation of self-rated health – information on patients’ unmet needs?

Petek

Kersnik

2014

Slovenian Journal of Public Health

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“…Several prospective and cross-sectional studies in different countries have reported the inverse association of social class with cardiovascular morbidity and mortality independent of conventional risk factors or access to health care, and this association was also found in countries with universal healthcare systems, as in our country [8][9][10][11].…”

Section: Discussionsupporting

confidence: 66%

The relationship of socioeconomic status with coronary artery calcification and pericardial fat

et al. 2017

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A b s t r a c tBackground: Little data currently exist supporting the correlation of socioeconomic status (SES) to markers of subclinical coronary atherosclerosis. Aim:The main aim was to investigate the relationship of SES measured by economic status and educational level with coronary artery calcification (CAC) and pericardial fat volume (PFV) assessed by multi-detector computed tomography (MDCT).Methods: A total of 220 consecutive patients with suspected coronary artery disease, who underwent 64-slice MDCT angiography for assessment of coronary atherosclerosis, were recruited between January 2014 and March 2015. Of these, 186 patients were enrolled in this cross sectional study. Conclusions: Socioeconomic status, particularly economic status measure, reported a significant inverse relationship with PFV independent of conventional cardiac risk factors.

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“…People are likely to underestimate unhealthy health behavior, such as cigarette smoking [16], or alcohol abuse as self-estimated [17]. It has been shown that the main reasons for nonresponse in self-reported surveys are probably the predisposing sociodemographic and behavioral factors [18,19]: nonrespondents are more likely to represent the low socioeconomic status and have more unhealthy behaviors than respondents. The time between the HBS and the CRC screening invitation was more than 10 years for 84% of the study population, and health behavior-related factors may have changed in these individuals during this period.…”

Section: Discussionmentioning

confidence: 99%

Determinants of non-participation in a mass screening program for colorectal cancer in Finland

et al. 2016

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Background: For an effective colorectal cancer (CRC) screening program, high participation rate is essential. However, non-participation in CRC screening program has increased in Finland. Material and methods: The study was based on a population-based nationwide cohort of persons invited for CRC screening in [2004][2005][2006][2007][2008][2009][2010][2011]. Information on the first round of the CRC screening participation and related background factors was obtained from the Finnish Cancer Registry, and information about health behavior factors from the Health Behavior Survey (HBS) in 1978-1999. Non-participation in CRC screening was analyzed with Poisson regression as incidence rate ratios (IRR) with 95% confidence intervals (95% CI). Results: Of all persons invited for CRC screening (79 871 men and 80 891 women) 35% of men and 21% of women refused. Of those invited for screening, 2456 men (3.1%) and 2507 women (3.1%) were also invited to the HBS. Persons, who declined HBS, were also more likely to refuse CRC screening (men IRR 1.40, 95% CI 1.26-1.56, women 1.75, 1.52-2.02) compared to HBS participants. Never married persons had about a 75% higher risk for refusing than married ones. The youngest age group (60 years) was more likely to refuse screening than the older age groups (62 or >64 years). Smoking was associated with non-participation in screening (current smokers, men: IRR 1.32, 95% CI 1.05-1.67, women: 2.10, 1.61-2.73). Conclusions: Participation in CRC screening was affected by gender, age, and marital status. Persons, who refused the HBS, were also more likely to refuse CRC screening. Smoking was a risk factor for nonparticipation in CRC screening.

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Health behaviours as explanations for educational level differences in cardiovascular and all-cause mortality: a follow-up of 60 000 men and women over 23 years

Cited by 245 publications

References 28 publications

Evaluation of self-rated health – information on patients’ unmet needs?

Evaluation of self-rated health – information on patients’ unmet needs?

The relationship of socioeconomic status with coronary artery calcification and pericardial fat

Determinants of non-participation in a mass screening program for colorectal cancer in Finland

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