Article ID Journal Published Year Pages File Type
337211 Psychoneuroendocrinology 2016 5 Pages PDF
Abstract

•Strong correlation between self-collected hair and hair collected at the laboratory.•Transportation of the hair samples by regular mail does not deteriorate cortisol measurements.•This adapted collection protocol has definite logistic and financial advantages.

IntroductionIn the last decades, cortisol has been extensively studied in association to early exposure to adversity as well as in the etiology of a number of physical and mental problems. While saliva and blood samples allow the measurement of acute changes in cortisol secretion, hair samples are thought to provide a valid retrospective measure of chronic cortisol secretion over an extended period of time. Nevertheless, the existing protocol for hair collection involves considerable financial and logistical challenges when performed in large epidemiological studies.ObjectiveThis study aimed to validate an adapted collection protocol asking participants to sample their hair at home and to send it back to our laboratory by regular mail.MethodsParticipants were 34 teenagers between 17 and 18 years of age. They participated in two hair collections: (a) at home, with the help of someone they know, and (b) in our laboratory, with a trained research assistant.ResultsWe noted a strong correlation between cortisol ascertained from hair collected at home and at the laboratory. No mean difference in cortisol levels could be detected between the two protocols. Moreover, we showed that a wide range of hair-related, sociodemographic, lifestyle factors that may be associated with hair cortisol levels did not affect the association between cortisol measures derived from each protocol.ConclusionOur study provides initial support that reliable measures of chronic cortisol secretion could be obtained by asking adolescents to collect a sample of their hair at home and send them to the laboratory by regular mail. This adapted protocol has considerable financial and logistical advantages in large epidemiological studies.

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