In previous posts I have discussed the use of self-report questionnaires to measure aspects of health, for example stress and depression. In this post, I will describe two methods for measuring “biomarkers” which are characteristics that are objectively measured and evaluated as an indicator of biological processes. As part of my research in the Bribri village of Yorkin, Costa Rica, I would like to measure health in the village in order to show that because of their initiation of an ecotourism project, which has allowed them to work in the village rather than in plantain and banana plantations, their overall health has improved. In order to accomplish this, I have chosen two biomarkers to examine health which are relatively easy to conduct in the field in minimally invasive. The first biomarker is blood pressure, which is one of the principal vital signs used in many healthcare settings. Blood pressure is the pressure exerted by circulating blood upon the walls of blood vessels. High blood pressure can be a warning sign for hypertension which can lead to strokes and various heart conditions. The second biomarker I intend to use is the level of the stress hormone cortisol (CORT), which provides a measure of hypothalamic-pituitary-adrenal axis (HPA) system activity or more simply, physiological stress. Prolonged periods of physiological stress have been found to have negative health effects including impaired cognitive performance, suppress thyroid function, blood sugar imbalances, higher blood pressure, immunity impairment, and increased abdominal fat.
To measure blood pressure in the field I will use an automatic blood pressure monitor, the OMRON HEM-711, one of which we have in the Human Behavioral Ecology Research Group HBERG lab run by Dr. Chris Lynn at the University of Alabama. Similar OMRON models have proved adequate for measuring blood pressure (Wan et al. 2010). To use this instrument, the cuff is placed on the left arm above the elbow at approximately heart level. It is suggested that the participant has remained seated for 10 minutes before taking the measurement and the person should not have consumed tobacco or caffeine for at least 30 minutes before the measurement is taken. Researchers suggest taking multiple measurements, for example three, and then calculating the mean of these measurements (Wan et al. 2010). Below is a video describing the use of the automatic blood pressure monitor.
To measure the stress hormone cortisol I intend to use the hair extraction method. Cortisol is slowly incorporated into the hair of humans and other mammals and allows for the measurement of physiological stress over several months. The process involves first obtaining a sample of hair from a participant. A portion of hair up to the width of a pencil is first secured with a clip or rubber band and then cut as close to the scalp as possible with sterilized scissors. The sample is taken from the posterior vertex portion of the skull. To examine the distribution of cortisol over time, the hair sample can be cut into 1 cm segments, the segments furthest from the scalp being the oldest. The samples can then be placed into a paper envelope and then secured in a container. Upon returning from the field, the samples can then be taken into the lab, I plan to use Dr. Jason DeCaro’s lab here at the University of Alabama, to be analyzed. The samples are washed in an alcohol solution, dried, ground, and then the cortisol is extracted and analyzed. The above procedures were described in an article by Meyer et al. (2014). Below is a video provided by the same authors describing the methodology.
I have chosen these two measurements of health because they will be logistically easy to perform in the field, require no more special instruments, and do not require refrigeration. By combining these two biomarkers with self-report measurement scales, I believe I will be provided with a robust survey of health in the village.
Meyer, J., Novak, M., K. Rosenberg, and A. Hamel 2014 Extraction and Analysis of Cortisol from Human and Monkey Hair. Journal of Visualized Experiments (83).
Wan, Y., C. Heneghan, R. Stevens, R. J. McManus, A. Ward, R. Perera, M. Thompson, L. Tarassenko, and D. Mant 2010 Determining which Automatic Digital Blood Pressure Device Performs Adequately: A Systematic Review. Journal of Human Hypertension 24(7):431-438.