Predicting Mortality From Human Faces


    loading  Checking for direct PDF access through Ovid

Abstract

ObjectiveTo investigate whether and to what extent mortality is predictable from facial photographs of older people.MethodsHigh-quality facial photographs of 292 members of the Lothian Birth Cohort 1921, taken at the age of about 83 years, were rated in terms of apparent age, health, attractiveness, facial symmetry, intelligence, and well-being by 12 young-adult raters. Cox proportional hazards regression was used to study associations between these ratings and mortality during a 7-year follow-up period.ResultsAll ratings had adequate reliability. Concurrent validity was found for facial symmetry and intelligence (as determined by correlations with actual measures of fluctuating asymmetry in the faces and Raven Standard Progressive Matrices score, respectively), but not for the other traits. Age as rated from facial photographs, adjusted for sex and chronological age, was a significant predictor of mortality (hazard ratio = 1.36, 95% confidence interval = 1.12–1.65) and remained significant even after controlling for concurrent, objectively measured health and cognitive ability, and the other ratings. Health as rated from facial photographs, adjusted for sex and chronological age, significantly predicted mortality (hazard ratio = 0.81, 95% confidence interval = 0.67–0.99) but not after adjusting for rated age or objectively measured health and cognition. Rated attractiveness, symmetry, intelligence, and well-being were not significantly associated with mortality risk.ConclusionsRated age of the face is a significant predictor of mortality risk among older people, with predictive value over and above that of objective or rated health status and cognitive ability.AbbreviationsBLSA = Baltimore Longitudinal Study of AgingBP = blood pressureFA = fluctuating asymmetryICC = intraclass correlationLBC1921 = Lothian Birth Cohort 1921MMSE = Mini Mental State ExaminationSPM = Standard Progressive Matrices

    loading  Loading Related Articles