The Relationship Between Light Exposure before Bedtime and Daytime Sleepiness Among People Living With Cognitive Impairment

Abstract

While sleep disturbances are common in people living with cognitive impairment, little is known about the influence of evening light exposure on their sleep. The purpose of this study was to examine the relationship between evening light exposure in natural living environment and daytime sleepiness in community residing people living with cognitive impairment. A secondary data analysis was conducted using the baseline data of the Healthy Patterns Clinical Trial. Actiwatch Spectrum Plus was used to collect information on the average white light intensity of 4 hours before sleep for three consecutive days. Multivariate regression analyses were used. Among 173 participants, the average light intensity during evening was 80.25 ± 123.04 lux. After controlling for covariates, greater intensity of light exposure during evening was related to excessive daytime sleepiness (β = 0.211, p = .004). The results of our study suggest exposure to light during evening may disturb sleep and subsequently influence daytime sleepiness the following day.

Keywords

cognitive impairment dementia sleep environment light actiwatch

Introduction

Sleep disturbances, including increased diurnal sleep, insomnia, circadian rhythm misalignment, and nocturnal sleep fragmentation (Peter-Derex et al., 2015; Porter et al., 2015), are common in persons living with cognitive impairment (Guarnieri et al., 2012). Persons living with cognitive impairment includes those living with any degree of cognitive impairment, ranging from mild cognitive impairment to moderate or severe dementia. More than 60% of people living with cognitive impairment have one or more sleep disturbances (Guarnieri et al., 2012). Sleep disturbances frequently occur in this population primarily due to underlying neurodegenerative changes in the brain (Weldemichael & Grossberg, 2010).

Daytime sleepiness is one of the most common symptoms related to sleep disturbances that people living with cognitive impairment report (Okuda et al., 2019). Excessive daytime sleepiness is defined as “sleepiness occurring in a situation when an individual would be expected to be awake and alert” (Arand et al., 2005). It is reported that approximately half of people living with cognitive impairment who live in the community experience excessive daytime sleepiness (Guarnieri et al., 2012). Caregivers report increased caregiver burden when their loved ones present with daytime sleepiness (Gehrman et al., 2018). Because sleep disturbances in people living with cognitive impairment can influence sleep and emotional burden of caregivers (Mather et al., 2022), and caregiver burden can eventually lead to institutionalization (Afram et al., 2014), it is essential to explore modifiable factors that affect daytime sleepiness in people living with cognitive impairment.

In addition to increasing caregiver burden, excessive daytime sleepiness also poses negative consequences for the people living with cognitive impairment. Excessive daytime sleepiness in people living with cognitive impairment is related to cognitive decline and can contribute to progression of dementia (Smagula et al., 2020; Tsapanou et al., 2015). When people living with cognitive impairment present with excessive daytime sleepiness, they are also at high risk for falls (Chen et al., 2016) and poor sleep the following night (Webster et al., 2020). Since sleep disturbances and their consequences are related to poor quality of life in people living with cognitive impairment (Petrovsky et al., 2018), it is imperative to find ways to help improve their sleep.

Circadian rhythm refers to a 24-hr cycle operated by the internal biological clock in the suprachiasmatic nucleus of the hypothalamus (Sack et al., 2007). Light is an important external cue for regulating circadian timing and is one of the most important environmental factors for maintaining consistent sleep-wake cycles. High levels of circadian rhythm stimulation during the day is helpful for circadian alignment and promoting healthy sleep patterns in people living with cognitive impairment (Figueiro, 2017). For example, bright light exposure during the daytime has been effective in improving nighttime sleep in people living with cognitive impairment (Hanford & Figueiro, 2013).

In the evening before bedtime, on the other hand, it is suggested to maintain low circadian rhythm stimulation (Figueiro, 2017), and evening time should be used for relaxation so that people living with cognitive impairment can prepare for sleep (Safi & Hodgson, 2014). However, because of technological breakthroughs, excessive artificial light exposure after sunset is common in the modern world (Czeisler, 2013). Excessive light exposure before bedtime can interrupt the sleep-wake cycle as it signals daytime to the suprachiasmatic nucleus (Czeisler, 2013). Lights from electronic devices in the evening can negatively impact sleep (Chang et al., 2015; Tähkämö et al., 2019). Even low intensity of light during evening is known to interrupt sleep at night (Burgess, 2013).

Recently, studies have been conducted in older adults to examine how the amount of light that a person is exposed to during the evening in natural living environment can impact sleep (Gooley et al., 2011; Obayashi et al., 2014). Increased light exposure during evening time was associated with longer sleep-onset latency in older adults (Obayashi et al., 2014). Another study compared melatonin duration of individuals who were exposed to ordinary indoor room light and dim light before bedtime (Gooley et al., 2011). It was found that people who were exposed to room light experienced shortened duration of melatonin production compared to people who were exposed to dim light (Gooley et al., 2011). These results suggest the importance of light exposure in the evening has on sleep.

What is unknown is how the light exposure during the evening in natural living environment affects sleep in people living with cognitive impairment, where sleep disturbances are extremely common. Although evening light exposure can be a potential environmental factor that interferes circadian rhythm, there has been lack of research examining the relationship between evening light exposure and sleep in people living with cognitive impairment, particularly in those living at home where most people living with cognitive impairment reside. Therefore, this study was conducted to examine the relationship between evening light exposure in natural living environment and daytime sleepiness in community residing people living with cognitive impairment.

Methods

We conducted a secondary data analysis using baseline data of the Healthy Patterns Clinical Trial, a phase III efficacy trial of a home-based activity intervention designed to alleviate symptoms of sleep-wake disturbances and circadian rhythm disorders and improve quality of life in people living with cognitive impairment (Hodgson et al., 2021). Detailed information about the parent study can be found in the published protocol paper (Hodgson et al., 2021). The parent study had three data collection time points: Pre-Test (T1), Post-Test (T2), and 3-month follow up (T3) (Hodgson et al., 2021). For the purpose of this study, we only used the data from T1 because the intervention could have altered the sleep patterns of the participants. The parent study recruited study participants who were (1) over 55 years old, (2) speaking English or Spanish, (3) living in the greater Philadelphia area, (4) able to tolerate wrist actigraphy, (5) diagnosed with probable dementia using standard assessments and diagnostic criteria, (6) having caregiver-reported symptoms of sleep-wake disturbances and circadian rhythm disorders, and (7) on a stable dose of psychotropic medications for 90 days if prescribed. A caregiver in this study was defined as a relative or friend who informally provides care, who was aware of and able to report the presence of symptoms of their loved ones. Participants were recruited in the greater Philadelphia area between February 2017 and February 2020 via direct mailing, referrals from cultural centers and Hispanic/Latino advocacy groups, distribution of flyers, bus ads, community events, and presentations at senior centers, senior living communities, and churches. Written informed consent was obtained from all study participants. For the cases where cognition was too impaired to sign the consent form (i.e., Clinical Dementia Rating score of 2 and 3), the study participants gave oral consent and written informed consent was provided by the legally authorized representative. Among a total number of 209 dyads who were enrolled in the parent study, the 173 dyads were included in the current study as they had complete baseline actigraphy data and survey data. This study was approved by the Institutional Review Board at the authors’ institution.

Data Collection

The baseline survey data were collected at the dyad’s initial consent visit by trained nurses and research staff. Information on light intensity that the participants were exposed to in natural living environment was collected using a wrist-based actigraphy device (the Philips Respironics Actiwatch Spectrum Plus). The device measured both natural and electronic light in environments to which the study participants were exposed. In the parent study, the people living with cognitive impairment wore the wrist-based actigraphy device 24/7 for the full 4 weeks. More information about the protocol of the parent study can be found here (Hodgson et al., 2021). For the purpose of this study, only data on the first three consecutive days/nights were used as we were comparing baseline survey data with the light data. All actigraphy data were downloaded using Philips Respironics Actiware software version 6.0.9. Light data were collected via the Actiwatch’s integrated light sensor.

Measures

Daytime Sleepiness

Epworth Sleepiness Scale was used to measure daytime sleepiness (Johns, 1991). Epworth Sleepiness Scale was developed to evaluate the respondent’s chances of dozing off or falling asleep during a variety of daytime activities. Caregivers were asked about sleepiness of people living with cognitive impairment during eight activities, and responses were scored from 0 to 3 scale (0 being would never doze, and 3 being would have a high chance of dozing). The total possible scores ranged from 0 to 24; higher scores indicate more daytime sleepiness (Johns, 1991). Epworth Sleepiness Scale has been widely used in people living with cognitive impairment (Boeve et al., 2019; Ferman et al., 2014).

Evening Light Exposure

The wrist-based actigraphy device (the Philips Respironics Actiwatch Spectrum Plus) was used to collect information on the average light intensity of 4 hours before sleep. The devices were set to collect data in 60 second intervals and minute-by-minute recordings of light data were used in this study. The average value of white light intensity for 4 hours before going to bed was used to indicate evening light exposure (Obayashi et al., 2014).

Participants who went to sleep before 7 pm were excluded from these analyses because 4 hours before the bedtime has too much daylight that can interfere with our main study objective. Participants were also excluded from data analyses if they removed the watch for more than 50% of the time during the three consecutive days of data collection. When the light value was less than one lux during the out-of-bed period, data were considered missing due to clothing covering the Actiwatch light sensor (Obayashi et al., 2014; Scheuermaier et al., 2010).

Covariates

Covariates were selected based on their known relationship with the dependent variable, daytime sleepiness, in this study and included age, cognitive function, behavioral and psychological symptoms of dementia, physical function, pain, social function, and depression (Gooneratne et al., 2003; Kulisevsky et al., 2008; Lee et al., 2013; Petrovsky et al., 2020; Smagula et al., 2020; Tsapanou et al., 2015).

Cognitive function was measured with Clinical Dementia Rating Clinical Dementia Rating (CDR) scale (Hughes et al., 1982; Morris, 1997). The possible range of CDR is from 0 to 3. The CDR level of 0 indicates normal cognition, the CDR level of 0.5 indicates questionable or very mild cognitive impairment, the CDR level of 1 indicates mild dementia, the CDR level of 2 indicates moderate dementia, and the CDR level of 3 indicates severe dementia (Hughes et al., 1982; Morris, 1997).

Behavioral and psychological symptoms of dementia were measured with Neuropsychiatric Inventory (NPI) (Cummings et al., 1994; Kaufer et al., 2000). The NPI was designed to evaluate ten behavioral domains in people living with cognitive impairment, and two more domains have been added after original development (Cummings, 1997). The 12 symptoms include delusions, hallucinations, agitation/aggression, dysphoria, anxiety, euphoria, apathy, disinhibition, irritability/lability, aberrant motor activity, nighttime behavioral disturbances, appetite, and eating abnormalities. A screening question was asked about each domain, and if the caregiver responded that the person living with cognitive impairment might exhibit behavior related to the domain, the caregiver was prompted to answer questions about the frequency of symptoms (4-point scale), severity of symptoms (3-point scale), and how distressing the symptoms were (5-point scale). In this study, the total NPI score was calculated by summing the frequency, severity, and caregiver distress score (higher values indicate higher frequency, severity and distress).

Physical function was measured with Barthel Index of Activities of Daily Living (Collin et al., 1988; Mahoney & Barthel, 1965). The questionnaire was originally developed for patients with chronic conditions and the scale measures a variety of activities of daily living including mobility, grooming, dressing, or feeding. The caregiver was asked about the care recipient’s abilities regarding 10 activities of daily living. Each activity was measured with a Likert scale: 0 (Unable), 5 (Needs help), and 10 (Independent). Possible scores ranged from 0 to 100 and a higher score indicated greater physical function of the person living with cognitive impairment.

Pain was measured with PROMIS Pain Behavior Short Form (Revicki et al., 2009). This questionnaire evaluates pain manifestations with verbal and non-verbal cues including facial expressions, limited movement, or social interaction. There are seven items in the scale, and the caregiver was asked how often the person living with cognitive impairment expressed each pain behavior and responses were rated on a 6-point Likert scale (1 indicating no pain and 6 indicating that the person always exhibited the pain behavior in question). Higher scores indicated higher frequency of pain manifestations.

Social function was measured with PROMIS Item Bank Ability to Participate in Social Roles and Activities (Hahn et al., 2014). This eight-item questionnaire assessed the caregiver-reported ability of the person living with cognitive impairment to perform one’s social roles and activities, such as being able to interact with family and friends or ability to perform daily routines. Responses were scored on a 5-point Likert scale (5 = never having any trouble with social role or activity; 1 = always having trouble with social role or activity). Higher scores reflect better ability to perform social activities (Hahn et al., 2014).

Depression was measured with Patient Health Questionnaire-9 (PHQ-9) (Kroenke & Spitzer, 2002; Kroenke et al., 2001; Spitzer et al., 1999). The PHQ-9 includes nine items with responses ranging from 0 (behavior is not at all exhibited) to 3 (behavior is exhibited every day). A higher PHQ-9 score represented higher depression severity. The use of this measure has been validated in people living with cognitive impairment (Hancock & Larner, 2009).

Data Analysis

Descriptive analyses were conducted to describe characteristics of the participants and variables used in this study. Univariate regression analyses and stepwise multiple regression analyses were used to examine the relationships between evening light exposure and daytime sleepiness. The variables that were statistically significant in univariate regression analyses were included in multiple regression analyses. The first model examined the relationships between covariates and daytime sleepiness. The second model examined the relationship between evening light exposure and daytime sleepiness controlling for covariates. Variance inflation factors were used to check multicollinearity. All statistical analyses were performed using Stata BE 17 (StataCorp, 2021). The level of statistical significance was set at p < 0.05.

Results

Table 1 describes the characteristics of the participants and descriptive statistics of the study variables. The mean age of the participants was 74.2 ± 8.5 (Range: 55–105), and the majority of them were female and African American. Most of the participants had questionable or very mild cognitive impairment (69.4%) with the average of CDR with 0.7 ± 0.5 (Range: 0.5–3). The average evening light exposure for 4 hours before sleep was 80.25 ± 123.04 lux (Range: 1.7–724.54). The median value of evening light exposure for 4 hours before sleep was 34.31 lux (Interquartile range: 14.71–90.55). Daytime sleepiness (ESS >10) was reported in only about 30% of the sample.

Table 1.

Study participant characteristics (n = 173).

Characteristics	n(%) or M ± SD	Min-Max
Age^*	74.2 ± 8.5	55–105
Sex
Female	114 (65.9)
Male	59 (34.1)
Race/Ethnicity^*
Black or African American	107 (61.9)
Hispanic/Latino	36 (20.8)
White	29 (16.8)
Education^*
No college	94 (54.3)
College and above	72 (41.6)
Clinical Dementia Rating (CDR)^*	0.7 ± 0.5	0.5–3
0.5 (Questionable or Very Mild Cognitive Impairment)	120 (69.4)
1.0 (Mild Dementia)	38 (22.0)
2.0 (Moderate Dementia)	10 (5.8)
3.0 (severe Dementia)	2 (1.2)
Behavioral and Psychological symptoms of Dementia	18.4 ± 18.6	0–90
Physical Function	88.3 ± 15.4	35–100
Pain^*	54.3 ± 9.2	34.1–67.8
Social Function^*	49.9±10.1	25.9–65.4
Depression^*	5.4 ± 4.9	0–27
Daytime Sleepiness^*	8.3 ± 5.4	0–24
Average evening light exposure during 4 hr before sleep (unit: lux)	80.25 ± 123.04	1.7–724.54

Missing data excluded

Univariate regression analyses indicated that the independent variable and all the covariates were in linear relationships with the dependent variable in this study. Increased daytime sleepiness was related to greater intensity of evening light exposure (β = 0.246, p = 0.001), younger age (β=−0.225, p = .001), severe cognitive impairment (β = 0.177, p = .011), more behavioral and psychological symptoms (β = 0.376, p < .001), poor physical function (β = −0.236, p = .003), more pain (β = 0.228, p = .003), poor social function (β = −0.276, p < .001), and more depression (β = 0.368, p < .001).

Table 2 shows the results of multiple regression analyses. First, the covariates were entered into the model that predicts daytime sleepiness of the participants in Model 1. Then, evening light exposure for 4 hours before sleep was added in Model 2 to examine whether it was related to daytime sleepiness and to evaluate whether it increased the variance. In our final model (Adjusted R² = 0.347, F = 9.71, p < .001), the average evening light exposure was significantly related to increased daytime sleepiness (β = 0.211, p = .004). The average evening light exposure significantly increased the variance of the model. No multicollinearity was detected with all the variance inflation factors less than 10.

Table 2.

Predictors of daytime sleepiness in persons living with cognitive impairment.

Variables	Model 1 (n = 145)					Model 2 (n = 132)
Variables	B	SE	β	t	p	B	SE	β	t	p
Age	−0.174	0.053	−0.256	−3.31	.001	−0.166	0.050	−0.257	−3.30	.001
Clinical Dementia Rating	2.682	1.072	0.219	2.50	.014	2.511	1.055	0.210	2.38	.019
Behavioral and Psychological symptoms of Dementia	0.095	0.026	0.327	3.66	< .001	0.116	0.026	0.404	4.55	< .001
Physical Function	0.020	0.032	0.055	09.63	.530	0.019	0.031	0.052	0.61	.543
Pain	0.050	0.050	0.080	1.01	.315	0.035	0.048	0.057	0.73	.469
Social Function	−0.043	0.051	−0.075	−0.86	.394	−0.028	0.050	−0.050	−0.56	.574
Depression	0.082	0.114	0.073	0.72	.471	−0.003	0.112	−0.003	−0.03	.978
Average evening light exposure during 4 hr before sleep						0.009	0.003	0.211	2.91	.004
Constant	14.596	6.401		2.28	.024	13.633	6.089		2.24	.027
	R² = 0.330, Adj. R² = 0.295, F = 9.62, p < .001					R² = 0.387, Adj. R² = 0.347, F = 9.71, p < .001

Discussion

In this study, we examined the relationship between evening light exposure in natural living environment and daytime sleepiness in people living with cognitive impairment. We found that increased evening light exposure was related to increased daytime sleepiness (β = 0.211, p = .004) after controlling for age, cognition level, behavioral and psychological symptoms of dementia, physical function, pain, social function, and depression (Adjusted R² = 0.347, F = 9.71, p < .001). Increased daytime sleepiness may be a consequence of previous night sleep disturbances and can also increase the risk of poor sleep quality the following night (Webster et al., 2020). One explanation for our study findings is that evening light can contribute to poor nighttime sleep, and subsequently disrupt daytime wakefulness. Furthermore, evening light exposure can alter the circadian clock, which further impacts the sleep-wake cycle. Given that people living with cognitive impairment already have less robust circadian rhythms, evening light exposure can be detrimental. Overall, the results of this study are aligned with previous research that examined associations between evening light exposure and sleep in people without dementia; high intensity of evening light exposure was related to sleep-onset latency (Obayashi et al., 2014) and suppressed melatonin secretion (Gooley et al., 2011). Difficulty falling asleep in the evening can contribute to daytime sleepiness (Johns, 1991).

In this study, the participants were exposed to more than the recommended amount of evening light. The average of the intensity of the evening light exposure was 83.3 ± 122.4 lux (Range: 1.7–641.2). Considering that low circadian stimulation during the evening is suggested with <50 lux for people living with cognitive impairment (Figueiro, 2017), the average intensity of light in this study far exceeds the suggested value. In a previous study which examined the evening light exposure in older adults living in community, the median value for evening light exposure for 4 hours before bedtime was 27.3 lux (Obayashi et al., 2014). Median intensity of evening light in our study was 34.31 lux. Considering the similarity of the participants of the two studies, the light values were similar yet slightly higher in the current study. It is possible that the participants were unaware of the importance of maintaining low intensity of light during the evening. Their sleep disturbance might also have caused them to pursue active activities before their sleep.

About one third of our sample had subjective daytime sleepiness, as reported by the caregiver. The rate of daytime sleepiness falls within the range we see in other studies of comparable populations (19% 45%) (Brewster et al., 2019; Carvalho et al., 2018; Tyagi et al., 2017). Given that caregivers are reporting daytime sleepiness, the rates might be even higher in our sample, suggesting the possibility for an even stronger relationship between daytime sleepiness and evening light exposure.

Timing of light exposure should be individualized to the needs of people living with cognitive impairment. Early morning light exposure may shift bedtime earlier, whereas evening light exposure may shift bedtime later. Careful consideration must be given when determining optimal timing of light and how it may impact sleep and quality of life among people living with cognitive impairment. In our study, we showed increased evening light exposure was related to sleep disturbances in people living with cognitive impairment; thus, an effort should be applied to reduce excessive artificial lights at home during evening and to create a relaxing atmosphere with dim light. Yet, the light intensity during evening should not be kept too dim to prevent accidental falls. Educating people living with cognitive impairment as well as caregivers to create a relaxing atmosphere would be helpful to improve excessive daytime sleepiness in people living with cognitive impairment.

A group of diverse experts synthesized the results of 27 light intervention studies in patients with Alzheimer’s disease and concluded that it is controversial whether artificial bright light exposure improves sleep. While there are studies examining the efficacy of bright light interventions, limited information is available on the impact of light in natural living environment. More research is warranted to understand how modifying light level in a daily life setting is helpful to improve nighttime sleep and subsequently daytime sleepiness.

Strengths and Limitations

There are several strengths of this study. This is one of the first studies to collect minute-by-minute light data via wrist actigraphy in a community dwelling sample of older adults living with cognitive impairment. Previous measure such as standing light meters cannot precisely capture light exposure because people are constantly moving around to different areas at home and elsewhere. Thus, as study participants in this study wore Actiwatches, it was possible to collect precise data from wherever they moved (e.g., from outdoor to indoor bathroom, kitchen, and bedroom).

In addition, this study added knowledge on the effect of evening light exposure in natural living environment on sleep in people living with cognitive impairment; the effect of environmental factors on sleep is an understudied area in this population. The outcome of this study can be used to educate dementia caregivers to minimize light exposure during the evening and to create a dim, calm, and relaxing environment for better sleep for their loved ones.

There are a few limitations in this study. The questionnaires were only measured once at baseline, not every day. If the survey measures were collected every day, the results of this study might have been more precise. The survey was also conducted in different time of the day for each participant, and the time of day might have influenced participants’ responses. It is also important to note that this study used proxy-reported tools and relied on information reported from caregivers. Another limitation is that the time of year for data collection was different from person to person; however given that participants were continually enrolled over a 3 year time period, we are confident there was an equal distribution of seasons and therefore light exposure variation among the participants. Furthermore, we did not have information on incontinence or nocturia in this study; it is possible that frequent trips to the bathroom could increase light exposure during the evening. Lastly, light exposure was measured at the wrist, not an eye level. Since humans mostly receive information about light using eyes, future studies which measure lights at the eye level will be helpful.

Conclusion

The results of our study suggest that exposure to bright light during evening in natural living environment may disturb sleep and subsequently influence daytime sleepiness the following day. Since evening light exposure can alter the circadian clock of people living with cognitive impairment who already have less robust circadian rhythms, it would be helpful to educate people living with cognitive impairment and caregivers to maintain low intensity of light during evening, and timing of dimming light should be individualized to the needs of people living with cognitive impairment.

Footnotes

Acknowledgments

We would like to express our gratitude to the study participants for providing valuable information for this study. We would like to thank Healthy Patterns Sleep Study research staffs for their efforts in data collection and Liming Huang for her help on data management. We would also like to thank Dr. Kyuhyun Choi for his help on data analyses.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Institute of Nursing Research at the National Institutes of Health [R01NR015226; K23NR018487 to MVM].

Ethical Research

This study was approved by the University of Pennsylvania’s Institutional Review Board (Protocol Number: 825000).

ORCID iDs

Yeji Hwang

Miranda V. McPhillips

Nancy A. Hodgson

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