Salivary alpha-amylase (sAA) has been reported to be a noninvasive biomarker of the sympathetic-adrenal-medullary system (Granger, Kivlighan, el-Sheikh, Gordis, & Stroud, 2007). Measurement of sAA has been found to reflect psychosocial and physical stress among various groups of adults when exposed to stress-inducing conditions (Granger et al., 2007; Petrakova et al., 2015). Inagaki, Ieda, Yamashita, Miyaoka, and Horiguchi (2011) have recommended the use of sAA as a method for evaluating stress in children who have limited ability to express their emotions because of severe motor and intellectual disabilities. Residents in assisted living memory care (ALMC) units, which is a growing population, may also benefit from the use of sAA as a measure of stress. Many individuals who reside in ALMC do not have the ability to recognize and express their pain and levels of stress as a result of their cognitive impairment. Individuals may express themselves with agitation, wandering, or aggression when their needs are not met or when they experience stress.
Point-of-care technology is allowing for the rapid analysis of saliva for determination of biomarkers. A review conducted by Miočević et al. (2017) indicates that saliva as an alternative biofluid in settings where rapid results are important is becoming a reality. With the availability of point-of-care analysis of sAA and a simple tongue swab saliva collection technique, the opportunity exists for use of this technology in the assessment of stress in difficult populations. Currently, the literature is sparse on the use of sAA among adults age ≥70 and those with dementia. Thus, it was important to evaluate the use of sAA using a saliva collection technique and point-of-care analysis as a potentially useful measure of stress for residents in an ALMC unit.
The current study had several aims. The first aim was to describe the changes in sAA levels over a 12-hour period in two groups of older adults (ALMC residents with dementia and independent/assisted living [I/AL] residents without dementia). The I/AL residents were included as a comparison group. In addition, the feasibility of collecting sAA through tongue swab techniques was addressed. This description will help establish usefulness of sAA as an approach to determine the stress levels of these groups. The ultimate goal was to determine if sAA can be used to determine the effect of various planned and unplanned events/activities (e.g., meals, music, massage) on the psychosocial and physical stress levels of this older adult population.
A descriptive comparison approach was used to address the aims of the current study. Case study analysis was used to address the sAA changes related to time of day and type of activity that each participant engaged in throughout the day.
Participant characteristics and sAA levels throughout the day were evaluated in 18 residents (10 from ALMC and eight from I/AL) of two assisted living facilities, each with separate memory care units. The study was approved by the Institutional Review Board. Ten residents from the ALMC were purposively selected to obtain representation of different genders and cognitive and physical ability. Directors of nursing and unit managers assisted in the selection to obtain this variety in participants. Informed consent was obtained from each resident's authorized representative, as all ALMC resident participants did not have the capacity to make informed decisions on their own. Eight residents from the I/AL community were purposively selected to obtain representation of different genders and physical ability. These residents did not have cognitive impairment and were able to provide informed consent for themselves.
A retrospective chart review was conducted to obtain resident characteristics (e.g., age, gender). Global Deterioration Scale (GDS) scores obtained as a measure of cognitive ability were recorded from chart review for participants from the ALMC unit. Cognitive decline was rated on a 7-point scale ranging from 1 (no cognitive decline) to 7 (severe dementia). Participants who were not receiving health care services from these facilities were asked to verbally provide the above information.
Saliva samples were collected at eight different time points throughout the day for a single day at awakening and bedtime; around planned activities; before and after the noon meal; one morning activity; and one evening activity for each participant over a 12-hour period (from 7 a.m. to 7 p.m.). During a 12-hour observation, a maximum of three participants from the ALMC unit and four participants in the I/AL unit were able to be observed.
A saliva collection process and point-of-care analysis (access http://somabioscience.com) with recently established reliability and validity among athletes were used. Saliva collection for participants in the current study was completed in approximately 20 to 50 seconds by placing a swab on top of the tongue. A color change in the stem of the swab indicated enough (0.5 mL) collected saliva. The swab was placed in a bottle of buffer until analysis was completed with the cube analyzer. This system uses detergents and buffers that negate the effect of any recent food and fluid intake, so it is not necessary to avoid eating, drinking, or washing the mouth out 10 minutes before obtaining the saliva sample, which typically are routine processes that are difficult among individuals living in ALMC.
Descriptive statistics were computed to evaluate patient characteristics and sAA levels throughout the day (i.e., mean, standard deviation, frequency). Levels of sAA and related activities were graphed for each resident. Linear mixed effects (LME) modeling was used to measure individual change in sAA over time and between groups (ALMC vs. I/AL, specifically participants with dementia [ALMC] and without [I/AL]). For Model 1, the model specification was as follows: sAA levels ∼ Time + (1|Subject) and the model specification for Model 2 was sAA levels ∼ Time + (1|Group Membership).
A total of 18 residents participated in the study. The ALMC unit group comprised 10 participants with a mean age of 88.7 years (SD = 5.74, range = 81 to 97 years), who were primarily female (60%). The GDS score for participants in the ALMC group ranged from 4 to 6, indicating moderate to severe cognitive impairment. The I/AL unit comprised eight residents with a mean age of 89.1 years (SD = 7.64; range = 78 to 103 years), with an equal number of men and women.
Salivary Alpha-Amylase Characteristics
Levels of sAA varied (range = <20 to >2,000 μg/mL) over a 12-hour period for each participant and between participants (Table 1). LME analyses revealed that, with an intraclass correlation coefficient (ICC) of 0.093, 9.3% of the variance in sAA levels can be explained by group membership such that a small amount of variation in sAA levels was dependent on the characteristics of those in the different settings (i.e., ALMC, I/AL). As the primary group difference between individuals in the ALMC and I/AL settings was the presence of dementia in participants within the ALMC setting, it is possible that the presence of dementia may not have significantly contributed to the variability within sAA among participants. In addition, analyses revealed that with an ICC of 0.563, 56.3% of the variance in sAA levels can be explained by within-subject variability. This could be due to the differences in activities and/or waking times among each participant. The case analysis allowed a graphic review of the variation in sAA levels throughout the day for different daily activities. A graphic presentation of the changes in sAA for one participant from ALMC and one from I/AL are provided in Figure 1.
Measures of Dispersion for Salivary Alpha-Amylase Levels (μg/mL) Throughout the Day for ALMC and I/AL Participant Groups
Case analysis of salivary alpha-amylase (sAA) levels (µg/mL) for eight times throughout the day for a selected assisted living memory care (ALMC) participant and a selected independent/assisted living (I/AL) participant.
In general, the sAA levels were higher among I/AL participants, who had increases related to national/world events, paying bills, competitive games, and/or having difficulty with a self-imposed brain challenge. Several I/AL residents had increases in sAA levels prior to going to the dining room. This increase did not occur among couples who went together to the dining room or for those who had a consistent person they sat with during dining. The uncertainty some residents felt on whether they would be accepted by those at a dining table may account for this increase.
sAA levels for ALMC residents generally decreased with several activities. The use of massage, whether individual or in a group, decreased sAA levels. Exercise has been shown to increase sAA levels among athletes, but among this group it decreased sAA levels when residents actively participated. Exercise served as a familiar routine activity that residents were able to engage in. Presence of family members decreased sAA for most participants. The resident's apartment serves as a safe, familiar, and comfortable area for residents, as reflected with lower sAA levels when in the apartment compared with other locations in the memory care unit. Several residents participated in activities outside of their room on a routine basis. Interestingly, these residents had higher sAA levels when leaving the unit. Levels of sAA increased when confronted with uncomfortable situations—such as being in the dining room when they lack desire to eat or being encouraged by a family member to change a typical eating routine. Several residents presented with spikes in sAA during the late afternoon and evenings, which may reflect the sundowning experience.
Results from the current study indicated that sAA levels vary throughout the day and when participating in different activities. In addition, levels were generally lower on awakening for all participants. Similar findings were reported by Birditt, Tighe, Nevitt, and Zarit (2018), which indicated that sAA levels are higher for older adults versus younger adults, with levels increasing over the course of the day. They also found that for older adults, sAA decreased more in response to positive interactions versus younger adults. Variability, as well as increased sAA levels in response to chronic and induced acute stressors, has been documented for middle-aged adults (Sahu, Upadhyay, & Panna, 2014; Vineetha, Pai, Vengal, Gopalakrishna, & Narayanakurup, 2014) and older adults (Liu et al., 2017; Wilcox, Granger, Szanton, & Clark, 2014).
Participants' levels of sAA were higher than levels reported in the literature (Birditt et al., 2018; Liu et al., 2017; Wilcox et al., 2014). These higher levels may be attributed to the use of point-of-care technology compared to laboratory analysis. Further research on the reliability and validity of the point-of-care analysis for an older adult population is warranted. The changes in sAA levels for individuals in response to various activities is important from a clinical perspective.
The saliva collection process was completed without difficulty for all participants, which is especially important to note for participants from the ALMC unit. Participants from the ALMC unit were cooperative during the collection of samples, which was done eight times during a 12-hour period. The process was quick and did not require necessary components of previous collection approaches, such as spitting into a container or waiting for a period after any ingestion. A protocol was established to assist residents that encouraged adequate saliva flow prior to sample collection. The protocol included demonstrating how to create saliva in the mouth and encouraging participants to think about sucking on a lemon or a favorite food. To ensure the safety of participants, the individual collecting the sample held the end of the swab while still being able to observe the change in color, indicating that an adequate sample had been collected.
The point-of-care analysis was obtained in 10 minutes, which allows care providers the opportunity to use it to evaluate situational stress levels in residents. Point-of-care analysis allows staff to capture reactions immediately to events/activities of those residents who are unable to communicate their feelings and/or stress levels. Use of this analysis could allow for the determination of whether an activity provides enjoyment; if not, this could provide knowledge of activities that increase stress levels and should thus be avoided. The results of the feasibility study informed the staff of activities that may be effective in decreasing stress levels as well as those activities that created increased levels of sAA.
As this was a feasibility study, the need for further research is essential. As the saliva collection process was found feasible for participants with dementia and analysis helpful to staff, the reliability and validity of the test needs to be conducted using a gold standard for this age group.
Levels of sAA varied throughout the 12-hour period for each resident with changes in response to activities for participants in ALMC and I/AL. The case analysis provided opportunity for the interprofessional team to address the responses to activities on an individual basis. The use of sAA as a point-of-care measure to determine the effect of various activities is promising. The feasibility of using this measure with individuals who are unable to express their stress levels in future research and quality improvement projects has initial support.
Application of the safe and simple tongue swab saliva collection method used in the current study to other populations that present with difficulty using other collection methods or in a home setting is encouraged. The advancement of point-of-care technology allows for the rapid analysis of saliva for numerous biomarkers besides sAA. Thus, the potential for the use of saliva as a biomarker for clinical use and research is promising.
- Birditt, K. S., Tighe, L. A., Nevitt, M. R. & Zarit, S. H. (2018). Daily social interactions and the biological stress response: Are there age differences in links between social interactions and alpha-amylase?The Gerontologist, 58(6), 1114–1125 https://doi.org/10.1093/geront/gnx168 PMID: doi:10.1093/geront/gnx168 [CrossRef]
- Granger, D. A., Kivlighan, K. T., el-Sheikh, M., Gordis, E. B. & Stroud, L. R. (2007). Salivary alpha-amylase in biobehavioral research: Recent developments and applications. Annals of the New York Academy of Sciences, 1098(1), 122–144 https://doi.org/10.1196/annals.1384.008 PMID: doi:10.1196/annals.1384.008 [CrossRef]17332070
- Inagaki, T., Ieda, M., Yamashita, S., Miyaoka, T. & Horiguchi, J. (2011). Salivary alpha-amylase reactivity under psycho-physiological stress. A nonverbal communication measurement tool?Journal of Behavioral and Brain Science, 01(01), 12–15 https://doi.org/10.4236/jbbs.2011.11003 doi:10.4236/jbbs.2011.11003 [CrossRef]
- Liu, Y., Granger, D. A., Kim, K., Klein, L. C., Almeida, D. M. & Zarit, S. H. (2017). Diurnal salivary alpha-amylase dynamics among dementia family caregivers. Health Psychology, 36(2), 160–168 https://doi.org/10.1037/hea0000430 PMID: doi:10.1037/hea0000430 [CrossRef]
- Miočević, O., Cole, C. R., Laughlin, M. J., Buck, R. L., Slowey, P. D. & Shirtcliff, E. A. (2017). Quantitative lateral flow assays for salivary biomarker assessment: A review. Frontiers in Public Health, 5, 133 https://doi.org/10.3389/fpubh.2017.00133 PMID: doi:10.3389/fpubh.2017.00133 [CrossRef]
- Petrakova, L., Doering, B. K., Vits, S., Engler, H., Rief, W., Schedlowski, M. & Grigoleit, J. S. (2015). Psychosocial stress increases salivary alpha-amylase activity independently from plasma noradrena-line levels. PLoS One, 10(8), e0134561 https://doi.org/10.1371/journal.pone.0134561 PMID: doi:10.1371/journal.pone.0134561 [CrossRef]
- Sahu, G. K., Upadhyay, S. & Panna, S. M. (2014). Salivary alpha amylase activity in human beings of different age groups subjected to psychological stress. Indian Journal of Clinical Biochemistry, 29(4), 485–490 https://doi.org/10.1007/s12291-013-0388-y PMID: doi:10.1007/s12291-013-0388-y [CrossRef]25298630
- Vineetha, R., Pai, K. M., Vengal, M., Gopalakrishna, K. & Narayanakurup, D. (2014). Usefulness of salivary alpha amylase as a biomarker of chronic stress and stress related oral mucosal changes - A pilot study. Journal of Clinical and Experimental Dentistry, 6(2), e132–e137 https://doi.org/10.4317/jced.51355 PMID: doi:10.4317/jced.51355 [CrossRef]24790712
- Wilcox, R. R., Granger, D. A., Szanton, S. & Clark, F. (2014). Diurnal patterns and associations among salivary cortisol, DHEA and alpha-amylase in older adults. Physiology & Behavior, 129, 11–16 https://doi.org/10.1016/j.physbeh.2014.02.012 PMID: doi:10.1016/j.physbeh.2014.02.012 [CrossRef]
Measures of Dispersion for Salivary Alpha-Amylase Levels (μg/mL) Throughout the Day for ALMC and I/AL Participant Groups
|Saliva Collection Time||Assisted Living Memory Care (n = 10)||Independent/Assisted Living (n = 8)|
|Mean (SD) (Range)||Mean (SD) (Range)|
|A.M. (awaking)||190.94 (201.90) (19.90 to 668.80)||335.03 (352.30) (30.20 to 1,094)|
|A.M. (before activity)||161.55 (162.19) (19.90 to 495.10)||557.74 (490.69) (35 to 1,390.90)|
|A.M. (following activity)||206.71 (209.29) (20 to 703.30)||373.61 (256.93) (35.40 to 759.20)|
|Before meal||319.84 (242.20) (41.30 to 776.70)||463.75 (600.34) (19.90 to 1,844.80)|
|After meal||213.70 (356.95) (19.90 to 1,190.70)||230.23 (209.88) (19.90 to 648.10)|
|P.M. (before activity)||381.41 (398.81) (19.90 to 1,041.90)||447.94 (383.69) (34.70 to 1,142.60)|
|P.M. (following activity)||441.06 (821.96) (19.90 to 2,000)||582.61 (625.05) (94.60 to 2,000)|
|P.M. (end of day)||802.49 (1,160.68) (30.30 to 3,634.20)||492.84 (803.13) (19.90 to 2,394.90)|