Available online at:
https://cc.arcabc.ca/islandora/object/cc%3Apsycjournal

J Camosun Psyc Res. (2021). Vol. 3(2), pp. 43-58.
Submitted Winter 2021; accepted July 2021.

What Are the Biological Effects Behind the Impact of
Social Isolation?
Authors: Giulia Johann*, Harmanpreet Bindra, Joao Sales, and Sarah Delaney
Supervising Instructor: Michael Pollock, Psyc 215 (“Biological Psychology”)
Department of Psychology, Camosun College, 3100 Foul Bay Road, Victoria, BC, Canada V8P 5J2
*Corresponding author email: giujohann@gmail.com

ABSTRACT
In this paper, we sought to understand the biological effects in the human body when a person
experiences social isolation, so that we can have a better understanding of these and recognize
the steps needed to reduce the severity of their biological impacts. Previous research has
predicted the biological effects of social isolation by variables such as the levels of blood
pressure, testosterone, food intake, and hippocampal functioning. In our correlational study, we
tested the strength of these relationships by examining naturalistic daily changes in their
variables longitudinally over a two-week period. We measured blood pressure levels using an
electronic blood pressure monitor, inferred the amount of food intake by counting the amount of
calories consumed, inferred testosterone levels based on measured leg hair growth rates,
measured hippocampal functioning by performance on a spatial memory test, and determined the
level of social isolation by using a scale. Data pooled across participants in our correlational
study showed significant correlations of social isolation with systolic blood pressure, but not
with calorie intake, testosterone levels or hippocampal functioning.
1. Introduction
1.2 Literature Review
1.1 Research Problem
Social isolation is one of the many
reasons for deteriorating mental health
among us today. It has the potential to cause
anxiety, stress, depression, sleep deprivation
and persistent thoughts about self-harm.
Those who are socially isolated may lose
important connections such as their family
members, friends, or loved ones, which can
make recovery long and painful, physically
as well as mentally. We wish to know more
about how the human body responds to
social isolation and the potential shifts in
behaviour.

A most significant physical symptom
found behind the impact of social isolation is
increased systolic blood pressure. In an
experiment by Shankar et al. (2011), social
isolation was measured by a point system
(ranging from zero to five, with higher
scores indicating greater social isolation) to
compute levels of social isolation. One point
was given to participants if they did not have
a partner, another point if they had less than
monthly contact with children, family and
friends (each scored separately), and another
point if they did not engage in any
organizations, religious associations, and
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committees. Participants selected were
individuals born on or before February 2,
1952 who contributed to the Health Survey
for England in 1998, 1999, or 2011 and were
selected by the English Longitudinal Study
of Ageing. Then in 2004, the participants
were checked regularly by nurses for
systolic blood pressure measurement and
blood sampling, except from participants
with hematologic disorders. It was shown
that increases in social isolation were
associated with increases of systolic blood
pressure. Based on these results, social
isolation appears to lead to reduced
cardiovascular health.
Another factor previously found to
be affected by social isolation islowered
intake of food. An experiment conducted by
Grippo et al. (2007) on 15 adult female
prairie voles (a species that display social
behavior similar to humans) revealed that
social isolation of prairie voles for 4 weeks
caused a lower intake of sucrose. There were
7 prairie voles in the isolated experimental
group and 8 prairie voles were paired with
siblings in the control group. Everything else
was kept the same for the groups except that
in the experimental group there was only
one member in each cage. The findings
showed that sucrose intake was reduced in
the experimental group throughout the 4
weeks period of isolation as compared to
prairie voles in the control group.
An important question that has arisen
among researchers is whether testosterone
levels have any association with social
isolation. The study by Havashi et al.(2020)
had a total of 159 adolescent boys who were
divided into 5 groups, from the lowest level
of testosterone group to the highest. Based
on measurements of their social withdrawal,
social isolation was found to be associated
with decreases in testosterone levels.
In addition to the effects of social
isolation on mental health, a study was

conducted on a particular line of rats to
assess if running exercise attenuates the
effects of social isolation. In an experiment
by Gómez-Galán & Femenía (2016), for a
total of five weeks rats were divided into
three groups: the first group were housed
with 3–4 rats per cage, the second group
were individually housed rats, and the third
group were individually housed rats given
free access to a running wheel. After the 5
weeks, the animals were then given
anesthetics, and humanely decapitated in
order to analyze the hippocampus, a part of
the brain is responsible for spatial memory
and navigation. It was found that social
isolation caused a decrease in hippocampus
size and that exercise could not attenuate
these effects. Based on these results, it can
be concluded that the effects of social
isolation leads to smaller than normal
hippocampi with the possibility of
irreversible cognitive consequences.
1.3 Hypotheses
Based on the above literature review, we
predicted the following hypothesis:
• Hypothesis #1: If social isolation
increases then systolic blood pressure will
increase.
• Hypothesis #2: If social isolation
increases then the amount of sugar
consumed will increase.
• Hypothesis #3: If social isolation
increases then the level of testosterone will
decrease.
• Hypothesis #4: If social isolation
increases then hippocampal functioning will
decrease.

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2. Methods
2.1 Participants
The four authors of this paper served as
the participants in its studies. The
participants ranged in age from 19 to 24
years old, with an average age of 21, and
included three women and one man. The
participants were all undergraduate students
at Camosun College who completed the
current studies as an assignment for Psyc
215 (“Biological Psychology”) and were
grouped together due to their mutual interest
in the biological effects of social isolation.
All of the participants were in social
isolation due to the COVID-19 pandemic.
2.2 Materials and Procedure
We performed a correlational study to
test concurrently all four of our hypotheses
by examining naturalistic daily changes in
their variables longitudinally. Each
participant kept a study journal with them at
all times over this study’s two-week period
in order to record self-observations of the
following five variables: (1) systolic blood
pressure, (2) intake of food, (3) testosterone
, (4) hippocampal functioning, and (5) social
isolation.
To measure the levels of blood
pressure, each participant recorded their
blood pressure by using an electronic blood
pressure monitor every day. At least 80% of
the upper arm was wrapped with the
inflatable cuff and placed on bare skin, not
over any clothing. The participants had the
blood pressure measured twice, with a small
pause in between; if the readings were
different by 5 points or more, then they had
it done a third time. To ensure a correct
reading, the participants made sure to have
an empty bladder 30 minutes prior taking
their blood pressureand did not consume any

caffeinated beverages or smoke. Five
minutes before the measurement the
participants sat quietly and they remained
silent during measurement.
To measure the amount of food
participants consumed in a day, they had
tracked the number of calories in their food
that they consumed using an online app
named “Cronometer”. At the end of each
day, participants reported the total number
of calories they had consumed from the
food.
In order to measure the level of
testosterone, we measured the leg hair
growth of the participants every day for two
weeks. Each leg was divided into four
circular samples of radius 4 cm, located in
the center of the thigh, behind the thigh, in
the center of the shin and in the center calf;
thus having a total number of 16 samples
each day. An average was calculated of the
leg hair growth across the four leg areas
measured. For this experiment a razor will
be used; once the hairs are shaved, the hair
growth of the chosen regions will be
measured daily with a ruler.
To measure hippocampal functioning,
each participant completed a memory-span
task called the “Corsi Block Tapping” task,
which assesses spatial memory ability. For
the task, participants created an online
profile on the BrainScale website
(https://brainscale.net/corsi) where they
were instructed to partake in an exercise—
they watched 5 blocks appear on their screen
and then were asked to remember the order
the blocks had appeared, so that they could
repeat it back to the best of their ability. The
exercise lasted 4 rounds, and then gave the
final results once completed. For these
records, participants wrote down the time it
took them to complete the task (seconds),
the percent of accuracy (%), their score
maximum (max), and lastly their score
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average (avg). Each day for this study
participants recorded their results.
To measure the social isolation levels,
every night participants used a method
similar to the one used by Shankar et al
(2011). The method involves calculating
social isolation with a numerical scale from
zero to five, with higher score suggesting
greater social isolation. Participants counted
the amount of social interaction daily, one
point was granted to participants, if they did
not have a partner; had less interaction with
children, families, and friends (each scored
as one) – and lastly if they did not
participate in any classes, groups, religious
societies, or committees (scored as one).
To assess the strength and statistical
significance of associations between
variables predicted by our four hypotheses,
we performed Pearson product moment
correlations of their predictor variables
(blood pressure, intake of food, depression ,
and spatial memory) with their outcome
variable (social isolation). For testing
Hypothesis #1, we correlated the level of
systolic blood pressure with the social
isolation rating. For testing Hypothesis #2,
we correlated the amount of calories
consumed with the social isolation rating.
For testing Hypothesis #3, we correlated the
levels of leg hair growth with the social
isolation rating. For testing Hypothesis #4,
we correlated the spatial memory score with
the social isolation rating. We performed all
of the above correlations separately for each
participant as well as using data pooled
across all of the participants. For the
correlations using pooled data, in addition to
using the raw data, we also performed
correlations after we had first transformed
the data from each participant into z-scores
in order to standardize differences in
averages and variability seen between the
participants in their data and thus make them
more comparable. A correlation coefficient

was considered statistically significant if the
probability of its random occurrence (p) was
< .05 (i.e., less than 5% of the time expected
by chance alone).
3. Results
As shows in Table 1, systolic blood
pressure level was significantly correlated
with social isolation levels. While not
statistically significant for Participant #2 (r
= .45, p = .10), it was statistically significant
for the three other participants (for
Participants #1, 3, & 4, all r ≤ .75 and all p
≤.001), and with systolic blood pressure
level being significantly correlated with
social isolation level using both pooled raw
data (r = 0.59, p = 7.73e-07; see Figure 1A)
and pooled standardized data (r = 0.71, p
=9.45e-11 ; see Figure 1B). In contrast, no
statistically significant correlations were
found between calorie intake, testosterone
levels, spatial memory, and social isolation
levels using any single participant’s data (all
r ≥ .48, all p ≥.08). Calorie intake was not
significantly correlated with social isolation
using either the pooled raw data (r =-.06, p
=.67 ; see Figure 2A) or the pooled
standardized data (r =.16 , p =.24 ; see
Figure 2B). Testosterone levels were not
significantly correlated with social isolation
using either the pooled raw data (r =.01, p
=.95; see Figure 3A) or the pooled
standardized data (r =.08, p =0.53; see
Figure 3B). Spatial memory was not
significantly correlated with social isolation
using either the pooled raw data (r =-.03, p =
.82; see Figure 4A) or the pooled
standardized data (r =-.06, p =.65; see
Figure 4B). Based on a comparison of the
correlation coefficient using either pooled
raw data or the pooled standardize data,
systolic blood pressure showed the strongest
correlation with social isolation.
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4. Discussion
4.1 Summary of Results
Based on previous research, we
hypothesized that increases in two variables
would be followed by higher levels of social
isolation; the systolic blood pressure level
(Hypothesis #1), and the calorie intake
(Hypothesis #2). We hypothesized that
decreases in two variables would be
followed by higher levels of social isolation;
testosterone levels (Hypothesis #3), and
hippocampus activity (Hypothesis #4). Data
pooled across participants in our
correlational study supported the predicted
relationship of systolic blood pressure and
social isolation level (Hypothesis #1) but not
calorie intake, testosterone levels, and
hippocampus activity (Hypotheses #2, 3, &
4).
4.2 Relation of Results to Past Research
The ability of our correlational study to
predict systolic blood pressure based on
social isolation level is in line with previous
research. Shankar et al. (2011) found that
social isolation levels reported by
participants was associated with higher
systolic blood pressure. While Shankar et al.
(2011), had middle-aged participants
retrospectively asses their social isolation
level and systolic blood pressure levels, we
longitudinally assessed these variables in
college students. The similarity of both out
conclusions despite using different research
designs suggests a generalized relationship
exists between increased systolic blood
pressure and increase social isolation levels.
Our correlation study failed to confirm
the relationship between food intake and
feeling of social isolation. Carter et al.
(2007) found that following 2 and 4 weeks
of social isolation, the consumption of

sucrose intake in the isolated group
decreased significantly than its respective
baseline. The paired group of prairies did
not differ from its respective baseline intake
across time. In contrast to these results from
previous study, our participants did not find
a correlation between food intake and social
isolation. The methodology of our
correlation study differs from that of Carter
et al. (2007) in three major ways. First, the
food was consumed in two different forms.
Our correlational study method relies on
self-reported calorie intake per day that
includes both liquid and sloid form of food
whereas the Carter et al. (2007) study
involves measurement of liquid sucrose
intake in prairies. Such difference in the
form of food intake might be one of the
reasons of different results obtained. Future
studies should test whether the form of food
(liquid or solid) in which it is consumed
predict same social isolation. Second, there
was no baseline set up in our correlational
study while Carter et. al (2007) constructed
the baseline for intake of sucrose and water.
Future studies should analyze whether no
baseline for food intake predicts the social
isolation. Third, our study was conducted on
humans while Carter et. al (2007) study was
conducted on prairie (the species that
displays social behavior very much similar
to humans), this might be another cause of
difference in results. Future studies should
test whether conducting exactly same study
on humans and prairie predicts the same
social isolation.
Our correlational study was not
successful in proving any relationship
between testosterone levels and social
isolation. Hayashi et al (2020) study found
an inverse association between social
isolation and testosterone levels in early
adolescent boys. The participants involved
in Hayashi’s study collected their salivary
samples at their home early in the morning,
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then these samples were stored in household
freezers, and delivered frozen to the
laboratory so that the testosterone levels
could be measured. Due to a lack of
resources, our methodology differed from
Hayashi's study in two different ways; First,
we had to measure the leg’s hair growth of
each participant every day during two weeks
using a ruler, instead of collecting salivary
samples. Second, our group was composed
of three female participants and one male
participant, and the study conducted by
Hayashi et al (2020) was only among
adolescent boys. In conclusion, our results
were not significant due to a lack of
laboratorial assistance to accurately measure
the testosterone levels of our participants.
Our correlational study failed to confirm
the relationship between spatial memory and
social isolation reported by previous
research. Gómez-Galán & Femenía et al.
(2016) found that several aspects of
hippocampus activity, measured through
both electrophysiology recordings as well as
enantioselective liquid chromatography,
which showed significant results of increase
in the basal synaptic transmission and
plasticity levels by looking into the
glutamatergic transmission in the brain, as
well as level of voluntary running in the lab
rats. The study of Gómez-Galán & Femenía
et al. (2016) were able to purely isolate the
independent variable, and look directly into
the hippocampus when the dissection was
performed on the brain— in contrast our
participants did not always find that social
isolation was high some days, as the study
was done on humans who are still
functioning in society where human
interaction was more common, therefore not
allowing pure isolation. The methodology of
our correlational study differed from that of
the Gómez-Galán & Femenía et al. (2016)
study in two major ways that might account
for the inconsistent results. First, differences

between the studies in how they measured
social isolation could have affected their
findings. Our correlational study relied only
upon self-reports of social isolation. Future
studies should test whether the objectively
verified aspects of social isolation outlined
by Gómez-Galán & Femenía et al. (2016),
but not subjective self-assessments, predict
the spatial memory. Secondly, differences
between the studies in how they measured
hippocampal activity could have affected
their findings. While we measured
hippocampal activity on a Corsi Block Test
daily average (%), Gómez-Galán & Femenía
et al. (2016) used electrophysiology by
measuring slices of the actual hippocampi
from the lab rats and processing them with a
Prism 5 software program, and inputting this
data to find a P value— allowing for more
accurate results. Future studies should
examine whether hippocampal activity is
able to predict the severity of only certain
self-reported symptoms of social isolation.

References
Gómez-Galán, M., Femenía, T., Åberg, E.,
Graae, L., Van Eeckhaut, A., Smolders,
I., Brené, S., Lindskog, M. (2016).
Running opposes the effects of social
isolation on synaptic plasticity and
transmission in a rat model of depression.
PLoS ONE, 11(10). https://
doi.org/10.1371/journal.pone.0165071
Grippo, A. J., Lamb, D. G., Carter, C. S., &
Porges, S. W. (2007). Social isolation
disrupts autonomic regulation of the
hearth and influences negative behaviors.
Biological Psychiatry, 62(10), 11621170.
https://doi.org/10.1016/j.biopsych.2007.0
4.011
Hayashi, N., Ando, S., Jinde, S., Fujikawa,
S., Okada, N., Toriyama, R., Masaoka,
M., Sugiyma, H., Shrirakawa, T., Yagi,
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T., Morita., Morishima, R., Kiyono, T.,
Yamasaki, S., Nishida, A., & Kasai, K.
(2020). Social withdrawal and
testosterone levels in early adolescent
boys. Psychhoneuroendocrinology, 116.
https://doiorg.libsecure.camosun.bc.ca:2443/10.101
6/j.psyneuen.2020.104596

Shankar, A., McMunn, A., Banks, J., &
Steptoe, A. (2011). Loneliness, social
isolation, and behavioural and biological
health indicators in older adults. Health
Psychology, 30(4), 377-385.
https://doi.org/10.1037/a0022826

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Table 1
Correlation coefficient (r) values, with number of daily trials (n) per correlation in brackets.

Participant Participant Participant Participant
#4
#1
#2
#3

Pooled
raw data

Pooled
standardized
data

Systolic Blood
Pressure &
Social isolation
level

.83(14)*

.45(14)

.75(14)*

0.81(14)*

.59(56)*

.71(56)*

Calorie Intake
& Social
isolation level

.37(14)

.33(14)

-.22(14)

.15(14)

-.06(56)

.16(56)

Testosterone
level & Social
isolation level

-.12(14)

.13(14)

.48(14)

-.15(14)

.01(56)

.08(56)

Spatial
Memory &
Social isolation
level

-.08(14)

-.17(14)

-.09(14)

.10(14)

-.03(56)

-.06(56)

Variables
correlated

* p < .05.

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Figure 1
Scatterplot of systolic blood pressure level and social isolation level (A) raw and (B)
standardized data across participants.
A.

Systolic Blood Pressure (mmHg)

188
150
113
75
38

0
0

1
3
4
5
Social Isolation (0-5 scale 0=not isolated at all 5=very isolated)

6

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B.

Systolic Blood Pressure (mmHg)

3.

1.5

0.
-3.

-1.5

0.

1.5

3.

-1.5

-3.
Social Isolation ( 0-5 Scale/ 0= not isolated 5= very isolated)
Marker colour indicates which participant data is from: red = participant #1, orange = participant
#2, yellow = participant #3, and light green = participant #4. Some data might not be visible in
the figure due to overlapping markers.

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Figure 2
Scatterplot of calorie intake level and social isolation level using pooled (A) raw and (B)
standardized data across participants.
A.

food intake (number of calories
consumed )

2400

1800

1200

600

0
0

1
3
4
5
Social isolation (0-5 scale, 0=not isolated at all, 5= very isolated)

6

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B.

food intake (number of calories
consumed)

2.63

1.31

0.
-3.

-1.5

0.

1.5

3.

-1.31

-2.63
Social isolation (0-5 Scale/ 0= not isolated at all, 5= very isolated)
.
Marker colour indicates which participant data is from: red = participant #1, orange = participant
#2, yellow = participant #3, and light green = participant #4. Some data might not be visible in

the figure due to overlapping markers.

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Figure 3
Scatterplot of testosterone levels and social isolation level using pooled (A) raw and (B)
standardized data across participants.
A.

Testosterone Levels (Millimeter)

1.4

1.1

0.7

0.4

0.
0

1
3
4
5
Social Isolation (0-5 Scale/ 0= not isolated 5= very isolated)

6

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B.

Testosterone Levels (Millimeter)

2.63

1.31

0.
-3.

-1.5

0.

1.5

3.

-1.31

-2.63
Social Isolation (0-5 Scale/ 0= not isolated 5= very isolated)

Marker colour indicates which participant data is from: red = participant #1, orange = participant
#2, yellow = participant #3, and light green = participant #4. Some data might not be visible in
the figure due to overlapping markers.

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Figure 4
Scatterplot of spatial memory and social isolation level using pooled (A) raw and (B)
standardized data across participants.
A.

Corsi Block Test (0-100% )

125

100

75

50

25

0
0

1
3
4
5
Social Isolation (0-5 scale 0=not islated at all 5=very isolated)

6

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B.

Corsi Block Test (0-100%)

2.625

1.3125

0.
-3.

-1.5

0.

1.5

3.

-1.3125

-2.625
Social Isolation (0-5 Scale/ 0= not isolated 5= very isolated)

Marker colour indicates which participant data is from: red = participant #1, orange = participant
#2, yellow = participant #3, and light green = participant #4. Some data might not be visible in the
figure due to overlapping markers.

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