U.S. Short Sleep Duration Trends Between 2011 and 2020 by Visual Impairment Status Using Cross-Sectional Behavioral Risk Factor Surveillance System Survey Data

Abstract

Keywords

visual impairment short sleep duration primary prevention sleep trends

According to the American Academy of Sleep Medicine (AASM) and Sleep Research Society (SRS), individuals 18 years (y) or older who are getting < 7 h of sleep each night are considered to have “short sleep duration” (Panel et al., 2015). Existing research links short sleep duration with poorer physical and mental well-being and a higher risk of metabolic and cardiovascular diseases (Chattu et al., 2018; Panel et al., 2015). Additionally, findings from research conducted in the United States using national survey data collected in 2005–2008, 2009, and 2016 suggest that people with visual impairments may be prone to short sleep duration (Okoro et al., 2020; Qiu et al., 2019; Ramos et al., 2014).

In December 2010, the U.S. government launched the Healthy People 2020 Campaign with the goal of sufficient sleep (≥7 h/night) in 72.8% of the U.S. population by 2020 (U.S. Department of Health and Human Services, 2022b). Aside from a study by Okoro et al. using 2016 Behavioral Risk Factor Surveillance System (BRFSS) data from the Centers for Disease Control and Prevention (CDC) (Okoro et al., 2020), there is little population-level research on short sleep duration for U.S. adults with visual impairments in the years following the initiative's implementation. Despite evidence of greater levels of short sleep duration in young and middle-aged U.S. adults from the CDC, information is also unavailable on age-specific trends in short sleep duration between 2011 and 2020 among people with visual impairments (CDC, 2017).

As such, we used national BRFSS surveys to conduct a study determining whether short sleep duration prevalence has changed among U.S. adults with visual impairments since Healthy People 2020 began. We ascertained overall and age-specific estimates of short sleep duration between 2011 and 2020 for U.S. adults with and without visual impairments. We also assessed age-specific trends in short sleep duration by visual impairment status.

Methods

Study Data

We used data from the 2011–2020 BRFSS surveys—except for 2015 and 2019, since these two years do not contain sleep duration information. Briefly, the BRFSS is a nationally representative survey that the CDC administers to noninstitutionalized U.S. residents aged 18 years or older every year (CDC, 2018). Individuals participating in the survey are asked to respond to questions pertaining to their sociodemographic background, existing health problems, and access to care. The CDC relies on a combination of oversampling of underrepresented individuals (e.g., individuals residing in rural locations, and individuals who are racial or ethnic minorities) and survey weights to ensure that findings from research using BRFSS data are generalizable to the entire U.S. population (CDC, 2020). Investigators using BRFSS data do not need to seek further institutional review board approval or informed consent, since these permissions have already been obtained by survey administrators (CDC, 2018). Following the deidentification of survey participants, BRFSS data can be readily accessed by the public on the CDC's website (CDC, 2018).

Outcomes, Visual Impairment Status, and Sociodemographic Factors

We ascertained sleep duration information using the BRFSS question, “On average, how many hours of sleep do you get in a 24 h period?” (CDC, 2020). In keeping with AASM and SRS guidelines, individuals whose response was fewer than 7 h per night were considered to have short sleep duration (Panel et al., 2015). In the 2011 and 2012 surveys, adults with visual impairments were identified through the BRFSS question, “Has a doctor, nurse or other health professional ever said that you have vision impairment in one or both eyes, even when wearing glasses?” with “Yes” and “Respondent is blind” responses indicating visual impairment. Following the 2012 survey, the CDC replaced this question with, “Are you blind or do you have serious difficulty seeing, even when wearing glasses?” with “Yes” responses indicating visual impairment (CDC, 2013, 2020). Individuals without visual impairment were those with “No” responses to these questions. From the BRFSS, we also obtained sociodemographic characteristics data (age, race, sex, education, income, whether an individual had health care coverage, and whether an individual had a personal doctor), consistent with prior U.S. research using national surveys, to examine sleep duration in individuals with visual impairments (Okoro et al., 2020; Qiu et al., 2019; Ramos et al., 2014).

Statistical Analyses

The distribution of sociodemographic factors was determined by visual impairment status. We assessed the overall and age-specific (18–44, 45–64, and 65+ years) short sleep duration prevalence among individuals with visual impairments and those without visual impairments for each survey year (see Supplemental Table 1 in Appendix A). Calculating estimates within these age groups allowed us to describe the burden of short sleep duration among young, middle-aged, and older adults (Chaput et al., 2018; Flaxman et al., 2021).

To perform trend analysis by visual impairment status, separate curvilinear logistic models were created for each age group, allowing us to accommodate the nonlinear trend in the data (see Supplemental Table 1a to f in Appendix A). We treated the survey year as a continuous variable (coding 2011 as 1, 2012 as 2, 2013 as 3, etc.) and the models added a quadratic term for the survey year. Models controlled for race, sex, education, income, whether an individual had health care coverage, and whether an individual had a personal doctor.

We used SAS Version 9.4 statistical analysis software (SAS Institute, Cary, NC) to carry out all analyses. To accommodate the BRFSS's survey design and weights, we used SAS survey procedures. We assessed for statistical significance using two-sided tests at α = 0.05.

Results

Our study included 2,221,249 respondents (see Table 1). Approximately 5.4% of respondents had visual impairments. Compared to people without visual impairments, people with visual impairments tended to be older, belong to a racial or ethnic minority group, have a lower income, and finished fewer years of education.

Table 1.
Survey-Weighted Distribution of Sociodemographic Characteristics of Behavioral Risk Factor Surveillance System Survey Participants by Visual Impairment Status (n = 2,221,249).^a

Covariates Has visual impairment(n = 121,047) No visual impairment(n = 2,100,202)

Weighted % Weighted %

(95% confidence interval) (95% confidence interval)

Age

18–44 years 28.6 (27.9, 29.2) 47.1 (46.9, 47.2)

45–64 years 42.9 (42.2, 43.6) 33.2 (33.1, 33.3)

65 years and up 28.5 (28.0, 29.1) 19.7 (19.6, 19.8)

Sex

Male 43.9 (43.2, 44.5) 48.7 (48.6, 48.9)

Female 56.1 (55.5, 56.8) 51.3 (51.1, 51.4)

Race

White 52.2 (51.5, 52.8) 64.7 (64.5, 64.8)

Black 15.7 (15.2, 16.2) 11.2 (11.1, 11.3)

Other 32.1 (31.4, 32.8) 24.2 (24.0, 24.3)

Income

< US$15,000 28.6 (28.0, 29.3) 10.9 (10.8, 11.0)

US$15,000 to < US$25,000 27.9 (27.3, 28.5) 16.9 (16.8, 17.0)

US$25,000 to < US$35,000 11.9 (11.5, 12.3) 10.5 (10.4, 10.6)

US$35,000 to < US$50,000 11.1 (10.7, 11.5) 13.5 (13.4, 13.6)

US$50,000 or more 20.4 (19.9, 20.9) 48.2 (48.0, 48.3)

Education

Did not complete high school 30.0 (29.3, 30.7) 12.5 (12.4, 12.6)

High school graduate 31.4 (30.8, 32.0) 27.7 (27.6, 27.9)

Some college or technical school 26.6 (26.1, 27.2) 31.4 (31.2, 31.5)

College graduate 12.0 (11.6, 12.3) 28.4 (28.3, 28.5)

Health insurance

Yes 82.3 (81.7, 82.9) 87.1 (87.0, 87.2)

No 17.7 (17.1, 18.3) 12.9 (12.8, 13.0)

Personal doctor

Yes, only one 69.7 (69.1, 70.4) 70.5 (70.4, 70.6)

More than one 9.8 (9.5, 10.2) 6.9 (6.8, 7.0)

No 20.4 (19.8, 21.0) 22.6 (22.4, 22.7)

a
Survey weights in the Behavioral Risk Factor Surveillance System surveys have been used to calculate the weighted percentages.

Between 2011 and 2020, the overall short sleep duration prevalence varied between 41.3% and 49.6% for individuals with visual impairments and 32.1% and 35.2% for those without visual impairments (see Figure 1, and Supplemental Table 2 in Appendix A). For all survey years, overall and age-specific short sleep duration prevalences were significantly higher among individuals with visual impairments (see Figures 1 to 4). Regardless of visual impairment status, short sleep duration prevalence was significantly higher among individuals 18–44 and 45–64 years compared to those 65+ years.

Figure 1.
Survey-weighted prevalence of short sleep duration by visual impairment status in behavioral risk factor surveillance system survey participants during 2011–2020 (N = 2,221,249): overall prevalence. Note: VI = visual impairment.

Figure 2.
Survey-weighted prevalence of short sleep duration by visual impairment status in behavioral risk factor surveillance system survey participants during 2011–2020 (N = 2,221,249): prevalence among people aged 18–44 years. Note: VI = visual impairment.

Figure 3.
Survey-weighted prevalence of short sleep duration by visual impairment status in behavioral risk factor surveillance system survey participants during 2011–2020 (N = 2,221,249): prevalence among people aged 45–64 years. Note: VI = visual impairment.

Figure 4.
Survey-weighted prevalence of short sleep duration by visual impairment status in behavioral risk factor surveillance system survey participants during 2011–2020 (N = 2,221,249): prevalence among people aged 65+ years. Note: VI = visual impairment.

Trend analysis results are presented in Table 2. For people with visual impairments aged 18–44 years, each succeeding year reduced the 12% (95% CI: 6%–18%) increase in odds of short sleep duration by 1%. Accordingly, among those with visual impairments aged 45–64 and 65+ years, we observed respectively that each succeeding year reduced the 17% (95% CI: 13%–21%) increase in odds of short sleep duration by 1% and each succeeding year reduced the 9% (95% CI: 5%–13%) increase in odds by 1%.

Table 2.
Trends in Short Sleep Duration Between 2011 and 2020 Among People With and Without Visual Impairments.

People Odds ratio for year (95% confidence interval) Odds ratio for year² (95% confidence interval)

18–44 years

With visual impairment 1.12 (1.06, 1.18) 0.99 (0.99, 1.00)

Without visual impairment 1.05 (1.03, 1.06) 1.00 (1.00, 1.00)

45–64 years

With visual impairment 1.17 (1.13, 1.21) 0.99 (0.98, 0.99)

Without visual impairment 1.04 (1.03, 1.05) 1.00 (1.00, 1.00)

65+ years

With visual impairment 1.09 (1.05, 1.13) 0.99 (0.99, 1.00)

Without visual impairment 1.03 (1.01, 1.04) 1.00 (1.00, 1.00)

Discussion

In a nationally representative sample of U.S. adults, short sleep duration patterns between 2011 and 2020 were examined by visual impairment status. Individuals with visual impairments had significantly higher short sleep duration prevalence than those without visual impairments throughout adulthood. Short sleep duration prevalence was especially high among individuals with visual impairments aged less than 65 years compared to other subgroups. We also found that short sleep duration prevalence has been significantly increasing over the past decade in people with visual impairments regardless of age, although this increase appears to have become smaller over time.

Prior U.S. studies reporting nationwide estimates of short sleep duration point towards higher levels of short sleep duration among people with visual impairments (Okoro et al., 2020; Qiu et al., 2019; Ramos et al., 2014). A study of National Health and Nutrition Examination Survey participants by Qiu et al. (2019) showed that, between 2005 and 2008, 40.0% of survey participants diagnosed with visual field defects and 35.5% of those without diagnosed visual field defects or disc-defined glaucoma slept fewer than 7 h per night. Surprisingly, a lower percentage of people diagnosed with disc-defined glaucoma slept fewer than 7 h per night compared to those without diagnosed visual field defects or disc-defined glaucoma (33.7% vs. 40.0%), but these findings may be specific to glaucoma and may not apply to other conditions that can cause visual impairment. Using 2009 National Health Interview Survey data, Ramos et al. (2014) observed that individuals with visual impairments were 1.6 times as likely to sleep fewer than 6 h per night than their counterparts without visual impairments. An examination of 2016 BRFSS survey data by Okoro et al. (2020) revealed that people with visual impairments were 14% more likely to have short sleep duration than those without visual impairments. Our findings were generally consistent with the results from these three studies. In addition, we further demonstrated trends in short sleep duration in the timeframe set to achieve the Healthy People 2020 sleep goals.

Further efforts to improve sufficient sleep among U.S. adults with visual impairments are warranted to help the estimated 23.0 million Americans with visual impairments aged 18–64 years reach the Healthy People 2030 sleep goals (i.e., 68.6% having sufficient sleep; American Foundation for the Blind, 2020; U.S. Department of Health and Human Services, 2022a). Such efforts should address the specific challenges relating to sleep treatment faced by people with visual impairments. One of these challenges is access to sleep treatment. Individuals with visual impairments who have limited transportation options may find it difficult to first go and see their physician to obtain a referral for sleep therapy and then travel to attend a sleep clinic and receive treatment from a sleep specialist (Spencer et al., 2009). Home sleep evaluations and telehealth could be potential solutions to these access barriers, but additional work is needed to assess their effectiveness and ease of use for people with visual impairments.

Another challenge is the limited amount of sleep treatment research that has been conducted in people with visual impairments. Existing evidence supporting the effectiveness of conventional sleep treatments (e.g., light therapy, melatonin, or hypnosedatives) for people with visual impairments mainly comes from studies conducted in children (Elsman et al., 2019; Ingram et al., 2022; Khan et al., 2011), making it difficult to ascertain how beneficial conventional sleep treatments would be for adults with visual impairments. The little available research on melatonin as a sleep treatment for adults with visual impairments suggests that its use may improve short sleep duration, but the appropriate dose for this population remains to be determined (Lockley et al., 2007). Furthermore, research that has evaluated the effectiveness of continuous positive airway pressure, an established sleep treatment, for adults with sleep apnea and visual impairments does not provide short sleep duration estimates (West et al., 2018).

An additional challenge is that short sleep duration may be a symptom of differing underlying conditions such as sleep apnea, chronic pain, and overactive bladder (CDC, 2022; Finan et al., 2013; Ge et al., 2017). Although the abovementioned sleep treatments and cognitive behavioral therapy have been shown to be successful in improving sleep for many of these conditions when delivered in-person or by telehealth (Edinger et al., 2021; Pavlova & Latreille, 2019), further studies are needed to determine if these findings extend to people with visual impairments. Future initiatives that concentrate on facilitating access to sleep therapy and evaluating sleep treatment strategies for the primary causes of sleep issues among adults with visual impairments have the potential to raise overall physical and mental quality of life and reduce the risk of disease for this population.

We consider the study's limitations. Sleep duration is self-reported and, as such, it is possible that self-report and nonresponse bias may exist. However, studies have found that self-reported sleep duration is highly correlated with actigraphy device–collected data (Kohatsu et al., 2006). In addition, the BRFSS has undergone extensive validation in studies conducted by the CDC and by non-CDC researchers (Bowlin et al., 1993; Klompas et al., 2017; Park et al., 2016; Pierannunzi et al., 2013). Findings from these validation efforts have demonstrated a good correlation between BRFSS responses and in-person-collected measurements (Bowlin et al., 1993; Klompas et al., 2017; Park et al., 2016; Pierannunzi et al., 2013). Thus, any potential bias is likely to lead to more conservative estimates.

Conclusions

Between 2011 and 2020, individuals with visual impairments were significantly more likely to have higher short sleep duration prevalence throughout adulthood compared to individuals without visual impairments. People with visual impairments aged 65 years and younger were especially likely to have high short sleep duration prevalence. Additionally, we observed a significant upward trend in short sleep duration that was slowly decreasing over time among adults with visual impairments regardless of age. Considering the influence of sleep on overall well-being and disease prevention, additional focus is needed on strategies to improve sleep duration among individuals with visual impairments.

Supplemental Material

sj-docx-1-jvb-10.1177_0145482X231201124 - Supplemental material for U.S. Short Sleep Duration Trends Between 2011 and 2020 by Visual Impairment Status Using Cross-Sectional Behavioral Risk Factor Surveillance System Survey Data

Supplemental material, sj-docx-1-jvb-10.1177_0145482X231201124 for U.S. Short Sleep Duration Trends Between 2011 and 2020 by Visual Impairment Status Using Cross-Sectional Behavioral Risk Factor Surveillance System Survey Data by Phoebe M. Tran, Lam T. Tran, Cenjing Zhu and Liem T. Tran in Journal of Visual Impairment & Blindness

Covariates	Has visual impairment(n = 121,047)	No visual impairment(n = 2,100,202)
Age
18–44 years	28.6 (27.9, 29.2)	47.1 (46.9, 47.2)
45–64 years	42.9 (42.2, 43.6)	33.2 (33.1, 33.3)
65 years and up	28.5 (28.0, 29.1)	19.7 (19.6, 19.8)
Sex
Male	43.9 (43.2, 44.5)	48.7 (48.6, 48.9)
Female	56.1 (55.5, 56.8)	51.3 (51.1, 51.4)
Race
White	52.2 (51.5, 52.8)	64.7 (64.5, 64.8)
Black	15.7 (15.2, 16.2)	11.2 (11.1, 11.3)
Other	32.1 (31.4, 32.8)	24.2 (24.0, 24.3)
Income
< US$15,000	28.6 (28.0, 29.3)	10.9 (10.8, 11.0)
US$15,000 to < US$25,000	27.9 (27.3, 28.5)	16.9 (16.8, 17.0)
US$25,000 to < US$35,000	11.9 (11.5, 12.3)	10.5 (10.4, 10.6)
US$35,000 to < US$50,000	11.1 (10.7, 11.5)	13.5 (13.4, 13.6)
US$50,000 or more	20.4 (19.9, 20.9)	48.2 (48.0, 48.3)
Education
Did not complete high school	30.0 (29.3, 30.7)	12.5 (12.4, 12.6)
High school graduate	31.4 (30.8, 32.0)	27.7 (27.6, 27.9)
Some college or technical school	26.6 (26.1, 27.2)	31.4 (31.2, 31.5)
College graduate	12.0 (11.6, 12.3)	28.4 (28.3, 28.5)
Health insurance
Yes	82.3 (81.7, 82.9)	87.1 (87.0, 87.2)
No	17.7 (17.1, 18.3)	12.9 (12.8, 13.0)
Personal doctor
Yes, only one	69.7 (69.1, 70.4)	70.5 (70.4, 70.6)
More than one	9.8 (9.5, 10.2)	6.9 (6.8, 7.0)
No	20.4 (19.8, 21.0)	22.6 (22.4, 22.7)

People	Odds ratio for year (95% confidence interval)	Odds ratio for year² (95% confidence interval)
18–44 years
With visual impairment	1.12 (1.06, 1.18)	0.99 (0.99, 1.00)
Without visual impairment	1.05 (1.03, 1.06)	1.00 (1.00, 1.00)
45–64 years
With visual impairment	1.17 (1.13, 1.21)	0.99 (0.98, 0.99)
Without visual impairment	1.04 (1.03, 1.05)	1.00 (1.00, 1.00)
65+ years
With visual impairment	1.09 (1.05, 1.13)	0.99 (0.99, 1.00)
Without visual impairment	1.03 (1.01, 1.04)	1.00 (1.00, 1.00)

Footnotes

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) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Phoebe M. Tran

Supplemental Material

Supplemental material for this article is available online.

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J. R.

(2018). Continuous positive airway pressure effect on visual acuity in patients with type 2 diabetes and obstructive sleep apnoea: A multicentre randomised controlled trial. European Respiratory Journal, 52(4). https://doi.org/10.1183/13993003.01177-2018

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Covariates	Has visual impairment(n = 121,047)	No visual impairment(n = 2,100,202)
	Weighted %	Weighted %
	(95% confidence interval)	(95% confidence interval)
Age
18–44 years	28.6 (27.9, 29.2)	47.1 (46.9, 47.2)
45–64 years	42.9 (42.2, 43.6)	33.2 (33.1, 33.3)
65 years and up	28.5 (28.0, 29.1)	19.7 (19.6, 19.8)
Sex
Male	43.9 (43.2, 44.5)	48.7 (48.6, 48.9)
Female	56.1 (55.5, 56.8)	51.3 (51.1, 51.4)
Race
White	52.2 (51.5, 52.8)	64.7 (64.5, 64.8)
Black	15.7 (15.2, 16.2)	11.2 (11.1, 11.3)
Other	32.1 (31.4, 32.8)	24.2 (24.0, 24.3)
Income
< US$15,000	28.6 (28.0, 29.3)	10.9 (10.8, 11.0)
US$15,000 to < US$25,000	27.9 (27.3, 28.5)	16.9 (16.8, 17.0)
US$25,000 to < US$35,000	11.9 (11.5, 12.3)	10.5 (10.4, 10.6)
US$35,000 to < US$50,000	11.1 (10.7, 11.5)	13.5 (13.4, 13.6)
US$50,000 or more	20.4 (19.9, 20.9)	48.2 (48.0, 48.3)
Education
Did not complete high school	30.0 (29.3, 30.7)	12.5 (12.4, 12.6)
High school graduate	31.4 (30.8, 32.0)	27.7 (27.6, 27.9)
Some college or technical school	26.6 (26.1, 27.2)	31.4 (31.2, 31.5)
College graduate	12.0 (11.6, 12.3)	28.4 (28.3, 28.5)
Health insurance
Yes	82.3 (81.7, 82.9)	87.1 (87.0, 87.2)
No	17.7 (17.1, 18.3)	12.9 (12.8, 13.0)
Personal doctor
Yes, only one	69.7 (69.1, 70.4)	70.5 (70.4, 70.6)
More than one	9.8 (9.5, 10.2)	6.9 (6.8, 7.0)
No	20.4 (19.8, 21.0)	22.6 (22.4, 22.7)