Cardiometabolic and Inflammatory Biomarkers as Mediators Between Educational Attainment and Functioning at the Age of 90 Years.
BACKGROUND
Low socioeconomic status is associated both with poorer functioning and elevated levels of inflammatory and cardiometabolic biomarkers; however, knowledge of such relations for the oldest old is limited. Our aim was to study whether education is associated with cardiometabolic (cholesterol levels, body mass index, and leptin) and inflammatory (C-reactive protein, interleukin-6, interleukin-1Ra) biomarkers for the 90-year-olds who participated in the Vitality 90+ study. In addition, we investigated whether these biomarkers explain educational inequalities in functioning.


METHODS
All persons in Tampere, Finland, who were born in 1909 or 1910, were invited to participate, irrespective of their health status or dwelling place. The sample consisted of 262 participants who went through the home interview and blood tests. The socioeconomic status indicator used was the highest education, and physical functioning was assessed using the Barthel index. The association of education with individual and combined biomarker scores, and with functioning, was analyzed cross-sectionally applying generalized linear models.


RESULTS
The low- and mid-level-educated participants had greater odds of belonging to the high risk group in cardiometabolic biomarkers than did the high-educated. Differences were statistically significant in three individual biomarkers (high-density lipoprotein-cholesterol, leptin, and body mass index) and in a cardiometabolic score. There were no educational differences in inflammatory biomarkers. When all biomarkers were combined, they mediated educational differences in functioning on an average of 23%. After controlling for smoking, alcohol use and diseases, biomarkers mediated part of the differences between the mid-level- and high-educated.


CONCLUSIONS
High education was associated with better cardiometabolic biomarkers and functioning among the 90-year-olds. In part, educational inequalities in functioning were explained by cardiometabolic biomarkers.
School of Health Sciences and Gerontology Research Center, University of Tampere, Finland. linda.enroth@uta.fi.
Linda
L
Enroth
School of Health Sciences and Gerontology Research Center, University of Tampere, Finland. UKK Institute for Health Promotion Research, Tampere, Finland.
Jani
J
Raitanen
School of Health Sciences and Gerontology Research Center, University of Tampere, Finland.
Antti
A
Hervonen
Department of Clinical Chemistry, School of Medicine, University of Tampere, Finland. Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland.
Terho
T
Lehtimäki
Gerontology Research Center, University of Tampere, Finland. Department of Microbiology and Immunology, School of Medicine, University of Tampere, Finland.
Juulia
J
Jylhävä
Gerontology Research Center, University of Tampere, Finland. Department of Microbiology and Immunology, School of Medicine, University of Tampere, Finland. Department of Microbiology, Fimlab Laboratories, Tampere, Finland.
Mikko
M
Hurme
School of Health Sciences and Gerontology Research Center, University of Tampere, Finland. Institute for Advanced Social Research, University of Tampere, Finland.
Marja
M
Jylhä
D000369:Aged, 80 and over; D000375:Aging; D015415:Biomarkers / Q000097:blood*; D002318:Cardiovascular Diseases / Q000097:blood* / Q000503:physiopathology / Q000523:psychology; D004797:Enzyme-Linked Immunosorbent Assay; D005260:Female; D005387:Finland; D006304:Health Status; D006801:Humans; D007249:Inflammation / Q000097:blood* / Q000503:physiopathology / Q000523:psychology; D008297:Male; D009043:Motor Activity / Q000502:physiology*; D010353:Patient Education as Topic; D012923:Social Class
D015415:Biomarkers
Biomarkers; Functioning.; Health disparities; Longevity; Socioeconomic status