Napping Habit and Risk Factors for Cardiovascular Disease: Does It Matter If It is Sunday?

Abstract

Objective To assess the relationships involving the habit of napping and the risk factors for cardiovascular diseases.

Materials and Methods We conducted a cross-sectional study with 563 participants (mean age: 45.0 ± 8.5 years; 56.7% of female subjects). The variables assessed were sociodemographic characteristics, lifestyle and health habits, clinical variables, and napping habits (intentionality and allocation on weekdays or on weekends). The statistical tests used were the Mann-Whitney and Kruskal-Wallis tests followed by Dunn's post-hoc test and Pearson's Chi-squared. Modified multiple Poisson regression models and multiple linear regression models were adjusted.

Results In total, 56.6% of the participants napped (43.2% during the week and 51.8% on weekends). Unintentional napping predominated on weekdays (22.6%), and intentional napping on weekends (29.7%). Those who intentionally napped on weekdays presented higher serum lipid profile values; those who napped unintentionally on weekdays or on weekends presented higher glycated hemoglobin (HbA1c) values. Age, education, race, marital status, alcohol consumption, and physical activity were associated with increased body mass index (BMI), HbA1c, total cholesterol, high-density lipoprotein (HDL) and non-HDL cholesterol, and triglycerides. Intentional and unintentional napping remained independent risk factors for increased HbA1c and lipid profile.

Conclusion Naps can represent a warning sign for health professionals to start or maintain an individual's follow-up. The present study contributes to the literature by identifying that the habit of intentional napping, especially on weekdays, is associated with changes in the lipid profile.

Keywords

sleep - cardiovascular diseases - excessive daytime sleepiness

Introduction

Cardiovascular disease (CVD) can be avoided and prevented by changes in various behavioral risk factors, which can be reduced with healthy lifestyle attitudes.[1] However, the prevalence of CVD increased from 217 million in 2009 to 523 million in 2019, and the number of deaths increased from 12.1 million to ∼ 18.6 million in the same period.[2] Several studies[3] [4] [5] suggest that alterations in sleep quality, duration, and disorders are among the risk factors for CVD. Recently, due to the relevance of the topic, the American Heart Association[6] (AHA) included sleep health as one of the actions aimed at achieving ideal cardiovascular health (CVH) for the population, based on primordial prevention.

In modern society, sleep deprivation has become increasingly frequent due to various issues, including time spent on work, studies, social networks, and other forms of leisure. Individuals with sleep deprivation may experience sleepiness,[7] leading to the occurrence of naps. Napping is a behavior observed throughout life that can be performed unintentionally or involuntarily, as well as intentionally or voluntarily.[8] In addition to the intentionality of napping, the duration, frequency, and timing of naps are relevant to assess sleep health.[8] [9] Naps can provide benefits such as a reduction in sleepiness and an increase in emotional stability.[10] However, napping can also be associated with chronic health problems and worse health outcomes.[11]

Several studies[12] have shown that short naps do not seem to cause as much harm to health, and naps lasting between 30 minutes and 1 hour have not been associated with worse CVH. However, in a recent study,[13] individuals who napped for up to 30 minutes had a 41.0% increase in the risk of developing CVD compared with those who did not nap. Long naps were associated with several CVD risk factors, a higher prevalence of mortality, and the likelihood of obesity, hypertension, dyslipidemia, metabolic syndrome, and diabetes.[12] [14] [15] [16] The frequency and timing of naps were also associated with CVD risk and sleep quality. In a population-based cohort study,[17] individuals who had the habit of napping once or twice a week presented a lower risk of developing CVD compared with those who did not nap. The frequency of naps close to bedtime can lead to fragmentation of nighttime sleep and poorer sleep quality; however, naps throughout the day do not seem to influence nighttime sleep quality.[18]

Accordingly, the studies found in the literature present controversial results regarding the beneficial or deleterious nature of napping regarding its different characteristics. We found several studies in the literature on the relationships between napping and CVD, mainly concerning nap duration.[13] [17] The importance of evaluating other characteristics of naps and their possible association with CVDs or their risk factors is evident, aiming to propose preventive measures. The current study seeks to innovate by investigating other relevant aspects of naps that have been less studied so far, such as its intentionality and occurrence during the week or weekend, to evaluate the relationships between napping habits and risk factors for CVD.

Materials and Methods

The present is a cross-sectional study, derived from the research entitled “Ideal cardiovascular health and cardiometabolic factors: a population-based study of a public university”. Active public servants from a Brazilian public university aged between 20 and 59 years were included. For sample selection, a simple random sampling scheme was used in each of the strata (professional category and sex). The scheme was developed by a statistician who did not participate in the data collection. The sample calculation was made considering a proportion p = 0.50, whose value represents the maximum variability of the binomial distribution. Assuming a sampling error of 4% and a significance level of 5%, a sample size of 553 public servants was defined.

Data collection was conducted from June 2022 to February 2023 by trained professionals in 3 distinct stages: stage 1–sending an invitation to the institutional email of the randomly-selected workers, which directed them to the Research Electronic Data Capture (REDCap; Vanderbilt University, Nashville, TN, United States) software, which contained the consent form, sociodemographic and clinical characterization instrument, and the instruments to assessing various aspects of CVH; stage 2–in-person appointment for blood pressure measurement, anthropometric measurements, and blood sample collection; and stage 3–conducting the 24-hour dietary recall (24HR) by telephone.

The variables assessed in the present study were:

• Sociodemographic characteristics: age, sex (male and female), marital status (with partner, without partner), skin color/race (white and black/Asian/mixed race/indigenous), years of schooling, and professional category (workers in faculty, research, and other staff members).

• Lifestyle and health habits: smoking (smokers, non-smokers, and former smokers), alcohol consumption (yes or no), and physical activity assessed through the Global Physical Activity Questionnaire, version 2 (GPAQ v2), which categorizes the weekly level of physical activity into “does not meet recommendations (< 600 metabolic equivalents [MET]/minute)” and “meets recommendations (≥ 600 MET/minute).”[19] [20]

• Sleep variables:

  Reported mean sleep duration: calculated by the average values of sleep duration during weekdays and weekends, obtained from the participants' response to the following questions: “At what time do you sleep on an average weekday?”; “At what time do you wake up on an average weekday?”; “At what time do you sleep on an ordinary weekend?”; and “At what time do you wake up on an ordinary weekend?”.

  Mean sleep deficit: calculated by the difference between the average sleep duration and the value reported by the participant to the question: “How many hours do you think you need to sleep per night to wake up in a good mood?”.

• Clinical variables:

  Reported: arterial hypertension (yes or no), diabetes mellitus (DM; yes or no), and dyslipidemia (yes or no).

  Measured: blood pressure (BP) was measured using a digital monitor according to the current recommendations for the Brazilian population (hypertension if systolic BP ≥ 140 mmHg and/or diastolic BP ≥ 90 mmHg); the body mass index (BMI) was calculated using a digital scale and vertical anthropometer, dividing weight (kg) by height squared (meters[40]).

  Laboratory tests: fasting glucose, glycated hemoglobin (HbA1c), high-density lipoprotein (HDL), non-HDL, low-density lipoprotein (LDL), and total cholesterol (TC), as well as triglycerides (TG). Reference values were considered according to the guidelines of Sociedade Brasileira de Diabetes (the Brazilian Diabetes Society)[21] and the V Brazilian Dyslipidemia and Atherosclerosis Prevention Guideline;C-reactive protein (CRP: low or moderate risk: ≤ 3 mg/L; high risk: > 3 mg/L).

• Napping was assessed through the questions: “Do you nap?”; “Considering a normal week, Monday to Friday, do you nap intentionally (that is, because you want to nap)?”; “Considering a normal week, Monday to Friday, do you nap unintentionally?”; “Considering a normal weekend (Saturday and Sunday), do you nap intentionally?”; and “Considering a normal weekend, do you nap unintentionally?”. For all questions, the answers were yes or no.

Data from REDCap were analyzed using the Statistical Analysis System (SAS, SAS Institute Inc., Cary, NC, United States) software, version 9.4, and the IBM SPSS Statistics for Windows (IBM Corp., Armonk, NY, United States) software, version 23.0. The following statistical tests were applied: the Mann-Whitney and Kruskal-Wallis tests, followed by Dunn's post-hoc test, for the comparison of the variables, and the Pearson's Chi-squared for associations. Modified multiple Poisson regression models with robust variance were adjusted to identify factors related to the following variables: hypertension, dyslipidemia, DM, CRP, and blood pressure, one considering napping during the week and another, during the weekend. The results of the models presented the obtained prevalence ratio estimates, as well as their respective confidence intervals and p-values. Two multiple linear regression models were also adjusted, via generalized linear models, to identify factors related to the following variables: BMI, HbA1c, TC, HDL, LDL, and non-HDL cholesterol, and TG, considering weekdays and weekends. The results presented the regression coefficient estimates, as well as their respective confidence intervals and p-values. The presence of multicollinearity in the adjusted models was evaluated through correlation matrices among the independent variables. The level of statistical significance was 5%.

Results

A total of 563 individuals participated in the study. The population consisted predominantly of women (56.7%), of white skin color/race (75.7%), living with a partner (70.7%), who were staff members (81,2%), with a mean age of 45.0(± 8.5) years. Regarding habits and behaviors, 86.5% were non-smokers, 50.3% reported consuming alcohol on weekends, and 61.5% practiced physical activity. The mean sleep duration reported was of 7 hours and 36 (± 57) minutes. The mean sleep deficit was 1 minute (1 hour and 9 minutes). The participants presented mean values of fasting glucose of 88.8(± 18.5) mg/dL, HbA1c of 5.5(± 0.7) %, TC of 186.9(± 36.6) mg/dL, and TG of 109.9(± 63.3) mg/dL, which are within normal limits according to current parameters.[21] [22] The mean non-HDL cholesterol was of 135.8(± 13.0) mg/dL, and the LDL cholesterol, of 113.8(± 32.3) mg/dL, which are above the desired values, and the mean BMI was of 27.3(± 5.5) kg/m², indicating excess weight. In total, 56.6% of the participants napped, with 43.2% napping during the week and 51.8%, on the weekend. Unintentional napping was predominant during the week (22.6%), while intentional napping was predominant on the weekend (29.7%).

[Table 1] shows the comparison of sociodemographic and clinical variables among participants who did not nap, those who napped intentionally, and those who napped unintentionally, during the week and on the weekend. On weekdays, there was a significant difference in the values of the following variables: age, years of schooling, TC, LDL, and non-HDL cholesterol, and TG. Dunn's post-hoc test showed a significant difference in age, years of schooling, and TG values between those who did not nap and those who napped unintentionally. Regarding TC, LDL, and non-HDL cholesterol, there was a difference between those who did not nap and those who napped intentionally. On the weekend, a significant difference was found in terms of age and non-HDL cholesterol values. Dunn's post-hoc test showed a significant difference in age between those who did not nap and those who napped, both intentionally and unintentionally. Regarding non-HDL cholesterol, the significant difference was between those who did not nap and those who napped intentionally.

Table 1 Comparison of sociodemographic and clinical variables of the study sample.

Nap	Nap during the week				Nap on weekend
	n	Mean(± SD)	Median	p-valuea	n	Mean(± SD)	Median	p-valuea
Age				0.002b				0.002c
No	317	43.7(± 8.5)	42.0		271	43.6(± 8.7)	42.0
Yes, intentional	115	45.5(± 8.7)	45.0		167	46.1(± 8.3)	45.0
Yes, unintentional	126	47.3(± 8.8)	47.0		124	46.3(± 8.8)	47.0
Schooling				0.002c				0.062
No	311	18.5(± 4.1)	18.0		265	18.3(± 4.2)	18.0
Yes, intentional	111	17.6(± 4.1)	17.0		164	18.1(± 4.3)	17.0
Yes, unintentional	124	17.3(± 4.5)	16.0		121	17.4(± 4.1)	16.0
Body mass index				0.065				.0315
No	317	26.9(± 5.4)	25.9		271	26.8(± 5.2)	26.1
Yes, intentional	115	27.5(± 5.8)	26.2		167	27.8(± 6.1)	26.5
Yes, unintentional	126	28.0(± 5.3)	26.7		124	27.5(± 5.2)	26.2
Systolic blood pressure				0.792				0.374
No	317	119.5(± 13.6)	118.5		271	119.2(± 13.3)	118.5
Yes, intentional	115	119.7(± 13.0)	119.5		167	121.2(± 14.3)	120.0
Yes, unintentional	126	120.7(± 14.0)	119.3		124	119.9(± 13.3)	118.3
Diastolic blood pressure				0.782				0.761
No	317	74.2(± 9.4)	74.0		271	73.1(± 9.4)	73.5
Yes, intentional	115	73.3(± 9.1)	73.5		167	74.6(± 9.9)	74.5
Yes, unintentional	126	74.8(± 9.6)	73.5		124	74.0(± 8.8)	73.5
Fasting glucose				0.894				0.900
No	317	87.6(± 13.6)	85.0		271	88.0(± 14.1)	85.0
Yes, intentional	115	87.8(± 13.4)	86.0		167	88.4(± 15.1)	86.0
Yes, unintentional	126	92.5(± 29.8)	86.0		124	91.1(± 28.5)	85.0
Glycated hemoglobin				0.064				0.138
No	317	5.4(± 0.5)	5.4		271	5.4(± 0.5)	5.4
Yes, intentional	115	5.5(± 0.6)	5.4		167	5.5(± 0.6)	5.4
Yes, unintentional	126	5.7(± 1.1)	5.4		124	5.6(± 1.0)	5.4
Total cholesterol				0.033c				0.053
No	317	184.1(± 36.8)	182.0		271	183.9(± 38.0)	181.0
Yes, intentional	115	192.7(± 34.5)	191.0		167	191.3(± 34.6)	190.0
Yes, unintentional	126	189.7(± 37.4)	185.0		124	187.8(± 35.7)	183.0
High-density lipoprotein				0.222				0.383
No	317	51.7(± 13.1)	51.0		271	50.7(± 13.0)	50.0
Yes, intentional	115	49.3(± 11.3)	47.0		167	50.7(± 12.3)	49.0
Yes, unintentional	126	51.7(± 14.0)	50.0		124	52.7(± 13.7)	51.0
Low-density lipoprotein				0.026c				0.137
No	317	112.0(± 32.6)	109.0		271	112.5(± 33.4)	111.0
Yes, intentional	115	119.9(± 29.5)	117.0		167	117.6(± 30.6)	115.0
Yes, unintentional	126	113.8(± 33.6)	117.0		124	111.8(± 32.0)	108.5
Non-high-density lipoprotein cholesterol				0.004c				0.048c
No	317	132.4(± 36.4)	129.0		271	133.2(± 37.5)	130.0
Yes, intentional	115	143.4(± 32.9)	139.0		167	140.7(± 34.5)	137.0
Yes, unintentional	126	138.1(± 39.0)	131.5		124	135.1(± 36.1	128.5
Triglycerides				0.018c				0.318
No	317	102.9(± 57.8)	88.0		271	104.4(± 56.7)	88.0
Yes, intentional	115	119.2(± 74.3)	94.0		167	116.4(± 72.0)	96.0
Yes, unintentional	126	118.0(± 64.3)	107.0		124	113.0(± 63.9)	94.0

Abbreviation: SD, standard deviation.

Notes: ^a p-value obtained through the Kruskal-Wallis's test. ^bDunn's post-hoc test < 0.001. ^cDunn's post-hoc test ≤ 0.05.

[Table 2] presents the association of sociodemographic and clinical variables with the percentage of individuals who did not nap and those who nap intentionally or unintentionally, during the week and on the weekend. During the week, there was a higher prevalence of intentional naps among men and a higher prevalence of unintentional naps among subjects who reported DM. Those living with a partner had a lower prevalence of unintentional naps on the weekend. Participants who did not nap during the week had a lower prevalence of altered TG and HbA1c within normal values.

Table 2 Association of sociodemographic and clinical variables among the study sample.

Variable	Nap during the week				Nap on weekend
	No	Yes, intentional	Yes, unintentional	p-valuea	No	Yes, intentional	Yes, unintentional	p-valuea
	n (%)	n (%)	n (%)		n (%)	n (%)	n (%)
Sex				0.015				0.117
Male	126 (39.7)	63 (54.8)	50 (39.7)		120 (44.3)	79 (47.3)	44 (35.5)
Female	191 (60.2)	52 (42.2)	76 (60.3)		151 (55.7)	88 (52.7)	80 (64.5)
Marital status				0.902				0.032
Without partner	86 (27.5)	33 (29.7)	92(73.6)		68 (25.5)	41 (25.2)	46 (37.4)
With partner	227 (72.5)	78 (70.3)	33 (26.4)		199 (74.5)	122 (74.9)	77 (62.6)
Tobacco use				0.322				0.337
Non-smoker	280 (88.3)	96 (83.5)	108 (85.7)		230 (84.9)	144 (86.2)	112 (90.3)
Smoker/Former smoker	37 (11.7)	19 (16.5)	18 (14.3)		41 (15.1)	23 (13.8)	12 (9.7)
Physical activity (GPAQ v2)				0.687				0.597
< 600 MET/minute	117 (39.3)	38 (36.5)	49 (45.0)		101 (40.2)	56 (36.1)	48 (41.7)
≥ 600 MET/minute	181 (60.8)	66 (63.5)	66 (55.0)		150 (59.8)	99 (63.9)	67 (58.3)
Diabetes mellitus				0.042				0.283
No	285 (95.6)	102 (94.4)	107 (89.2)		239 (94.8)	151 (94.4)	107 (90.7)
Yes	13 (4.4)	6 (5.6)	13 (10.8)		13 (5.2)	9 (5.6)	11 (9.3)
Arterial hypertension				0.246				0.228
No	289 (91.2)	106 (92.2)	109 (86.5)		249 (91.9)	145 (86.8)	112 (90.3)
Yes	28 (8.8)	9 (7.8)	17 (13.5)		22 (8.1)	22 (13.2)	12 (9.7)
Low-density lipoprotein				0.395				0.842
< 130	231 (72.9)	77 (67.0)	86 (68.3)		195 (72.0)	116 (69.5)	87 (70.2)
≥ 130	86 (27.1)	38 (33.0)	40 (31.8)		76 (28.0)	51 (30.5)	37 (29.8)
Triglycerides				0.017				0.082
< 150	274 (86.4)	89 (77.4)	97 (77.0)		232 (85.6)	129 (77.3)	101 (81.5)
≥ 150	43 (13.6)	26 (22.6)	29 (23.0)		39 (14.4)	38 (22.7)	23 (18.5)
C-reactive protein				0.059				0.523
Low/Moderate risk	239 (75.4)	88 (76.5)	82 (65.1)		201 (74.2)	125 (74.8)	86 (69.4)
High risk	78 (24.6)	27 (23.5)	44 (34.9)		70 (25.8)	42 (25.2)	38 (30.7)
Glycated hemoglobin				0.0067				0.067
≤ 5.6	249 (78.5)	76 (66.1)	84 (66.7)		209 (77.1)	112 (67.1)	89 (71.8)
> 5.6	68 (21.5)	39 (33.9)	42 (33.3)		62 (22.9)	55 (32.9)	35 (28.2)

Abbreviations: GPAQ v2, Global Physical Activity Questionnaire, version 2; MET, metabolic equivalent.

Note: ^a p-value obtained through the Chi-squared test.

[Table 3] presents the linear regression analysis used to identify variables independently associated with the presence or with increased values of the risk factors for CVD. We found that napping during the week, both intentionally and unintentionally, was independently associated with an increase in the values of several CVD risk factors. Participants who reported unintentional napping during the week showed a mean increase of 0.18% in HbA1c values and of 12.89 mg/dL in TG values when compared with those who did not nap. Individuals who napped intentionally during the week showed increases in the mean TC, non-HDL, and TG values of 9.07 mg/dL, 9.87 mg/dL, and 13.58 mg/dL respectively, when compared with participants who did not nap. Other variables examined (age, education, race, marital status, alcohol consumption, and physical activity) also contributed to the increase in BMI, HbA1c, TC, non-HDL and HDL cholesterol, and TG. Regarding the weekend ([Table 3]), we found that participants who napped unintentionally showed an increase of 0.16% in the mean HbA1c values compared with those who did not nap.

Table 3 Linear regression analysis to identify variables associated with the presence or increase of risk factors for cardiovascular diseases.

Nap during the week	Body mass index	Glycated hemoglobin	Total cholesterol	High-density lipoprotein	Low-density lipoprotein	Non-high-density lipoprotein cholesterol	Triglycerides
	Coefficient (95%CI)	Coefficient (95%CI)	Coefficient (95%CI)	Coefficient (95%CI)	Coefficient (95%CI)	Coefficient (95%CI)	Coefficient (95%CI)
Intentional nap	0.37 (-0.86–1.61)	-0.03 (-0.18–0.13)	9.07a (0.69–17.45)	-0.79 (-3.51–1.92)	7.37 (-0.12–14.86)	9.87a (1.64–18.09)	13.58a (0.22–26.93)
Unintentional nap	1.01 (-0.15–2.18)	0.18a (0.04–0.33)	6.01 (-1.91–13.93)	-0.56 (-3.13–2.00)	3.00 (-4.08–10.07)	6.57 (-1.20–14.34)	12.89a (0.27–25.50)
Age	0.08a (0.08–0.02)	0.02a (0.01–0.03)	0.51a (0.14–0.88)	0.00 (-0.13–0.12)	0.31 (-0.02–0.65)	0.52a (0.15–0.88)	1.00a (0.40–1.60)
Schooling	-0.48 (-1.44–0.47)	-0.09 (-0.2–0.03)	3.2 (-3.29–9.68)	11.48b (9.38–13.58)	-1.98 (-7.78–3.82)	-8.28a (-14.65–-1.92)	-29.25b (-39.58–-18.91)
Education	-0.10 (-0.10–-0.21)	-0.02a (-0.03–-0.01)	0.05 (0.05–-0.73)	0.00 (-0.25–0.25)	-0.01 (-0.71–0.68)	0.04 (-0.72–0.80)	-0.34 (-1.58–0.89)
Marital status (without partner)	0.60 (-0.44–1.63)	0.09 (-0.04–0.22)	-1.94 (-8.99–5.11)	-2.28 (-4.56–0.00)	-1.74 (-8.04–4.57)	0.34 (-6.57–7.26)	12.16a (0.93–23.39)
Skin color/Race (Black/Mixed-Race/Indigenous)	0.33 (-0.85–1.51)	0.15a (0.01–0.30)	3.48 (-4.56–11.53)	0.47 (-2.14–3.07)	3.69 (-3.50–10.88)	3.01 (-4.88–10.91)	-1.44 (-14.26–11.38)
Tobacco use (smoker/former smoker)	1.35 (-0.07–2.77)	0.13 (-0.05–0.31)	8.09 (-1.58–17.77)	0.18 (-2.95–3.31)	5.89 (-2.76–14.54)	7.92 (-1.58–17.41)	11.65 (-3.76–27.06)
Alcohol consumption (yes)	-0.32 (-0.32–-1.31)	-0.04 (-0.17–0.08)	7.75a (0.99–14.50)	4.04a (1.86–6.23)	1.48 (-4.56–7.52)	3.71 (-2.92–10.33)	12.39a (1.63–23.16)
Physical activity (GPAQ v2)d	-1.56a (-1.56–-2.51)	-0.02 (-0.14–0.10)	-3.81 (-10.31–2.7)	2.40a (0.30–4.51)	-3.26 (-9.07–2.56)	-6.21 (-12.59–0.17)	-16.19a (-26.55–-5.82)

Nap on weekends	Body mass index	Glycated hemoglobin	Total cholesterol	High-density lipoprotein	Low-density lipoprotein	Non-high-density lipoprotein cholesterol	Triglycerides
	Coefficient (95%CI)	Coefficient (95%CI)	Coefficient (95%CI)	Coefficient (95%CI)	Coefficient (95%CI)	Coefficient (95%CI)	Coefficient (95%CI)
Intentional nap	0.92 (-0.15–2.00)	0.05 (-0.08–0.19)	5.13 (-2.20–12.46)	-0.27 (-2.64–2.10)	4.00 (-2.57–10.56)	5.40 (-1.81–12.61)	7.70 (-3.97–19.37)
Unintentional nap	1.03 (-0.18–2.23)	0.16a (0.01–0.31)	4.56 (-3.67–12.80)	0.05 (-2.60–2.71)	1.38 (-5.99–8.75)	4.51 (-3.59–12.61)	10.49 (-2.61–23.59)
Age	0.08a (0.02–0.13)	0.02b (0.01–0.03)	0.52a (0.15–0.90)	-0.01 (-0.13–0.11)	0.32 (-0.01–0.65)	0.53a (0.17–0.90)	1.05a (0.46–1.64)
Sex (Female)	-0.55 (-1.49–0.39)	-0.09 (-0.20–0.03)	2.58 (-3.83–9.00)	11.55b (9.48–13.62)	-2.32 (-8.07–3.42)	-8.96a (-15.28–-2.65)	-30.92b (-41.13–-20.72)
Schooling	0.10 (-0.21–0.01)	-0.02a (-0.03–-0.01)	0.04 (-0.74–0.81)	0.00 (-0.25–0.25)	-0.01 (-0.71–0.68)	0.04 (-0.72–0.80)	-0.38 (-1.62–0.85)
Marital status (without partner)	0.47 (-0.57–1.51)	0.07 (-0.06–0.20)	-2.16 (-9.25–4.92)	-2.20 (-4.48–0.09)	-1.85 (-8.19–4.49)	0.03 (-6.93–7.00)	11.78a (0.51–23.05)
Skin color/Race (Black/Mixed-Race/Indigenous)	0.30 (-0.88–1.48)	0.15a (0.01–0.30)	4.50 (-3.55–12.55)	0.39 (-2.21–2.98)	4.48 (-2.73–11.69)	4.11 (-3.81–12.03)	-0.16 (-12.97–12.66)
Tobacco use (smoker/former smoker)	1.61a (0.20–3.02)	0.15 (-0.02–0.33)	7.72 (-1.91–17.35)	0.33 (-2.78–3.43)	5.13 (-3.49–13.76)	7.39 (-2.08–16.87)	12.21 (-3.11–27.54)
Alcohol consumption (yes)	-0.47 (-1.46–0.52)	-0.05 (-0.17–0.07)	7.24a (0.48–13.99)	4.11a (1.94–6.29)	1.00 (-5.05–7.04)	3.12 (-3.52–9.77)	11.91a (1.16–22.65)
Physical activity (GPAQ v2)d	-1.56a (-2.48–-0.58)	-0.02 (-0.14–0.10)	-3.56 (-10.07–2.95)	2.27a (0.17–4.37)	-2.90 (-8.73–2.92)	-5.83 (-12.24–0.57)	-16.04a (-26.39–-5.68)

Abbreviations: 95%CI, 95% confidence interval; GPAQ v2, Global Physical Activity Questionnaire, version 2; MET, metabolic equivalent.

Notes: ^a p-value < 0.05. ^b p-value < 0.0001.

[Table 4] presents the Poisson regression analysis used to identify the variables independently associated with the presence of risk factors for CVD. No association was found regarding naps during the week and on the weekend and the risk factors studied. These, however, had a significant association with other variables, namely sex, age, skin color/race, and alcohol consumption.

Table 4 Poisson regression analysis to identify variables associated with the presence of risk factors for cardiovascular diseases.

Nap during the week	Hypertension		Dyslipidemia		Diabetes mellitus		C-reactive protein		Blood pressure
	PR	95%CI	PR	95%CI	PR	95%CI	PR	95%CI	PR	95%CI
Intentional nap	0.95	0.62–1.45	1.03	0.72–1.45	1.18	0.37–3.81	0.98	0.64–1.50	0.66	0.29–1.49
Unintentional nap	0.98	0.64–1.47	1.06	0.77–1.46	1.63	0.65–4.06	1.33	0.97–1.83	1.31	0.72–2.39
Sex (Female)	0.69a	0.48–0.99	0.96	0.73–1.27	2.00	0.59–6.79	1.80a	1.28–2.54	0.37a	0.20–0.68
Marital status (without partner)	1.19	0.81–1.74	0.84	0.60–1.17	0.95	0.36–2.46	1.09	0.79–1.49	2.02a	1.10–3.72
Skin color/Race (Black/Mixed-Race/Indigenous)	1.47a	1.02–2.12	1.05	0.73–1.51	1.62	0.70–3.76	1.17	0.83–1.65	1.59	0.86–2.94
Tobacco use (smoker/former smoker)	1.34	0.88–2.05	1.17	0.82–1.67	1.36	0.49–3.82	0.81	0.50–1.31	1.52	0.81–2.85
Alcohol consumption (yes)	0.80	0.56–1.15	1.54a	1.13–2.09	0.88	0.34–2.27	1.07	0.79–1.49	1.24	0.71–2.19
Physical activity (GPAQ v2)e	1.04	0.73–1.48	0.95	0.73–1.25	0.59	0.25–1.40	0.78	0.59–1.05	0.77	0.44–1.36
Age	1.06b	1.04–1.08	1.04b	1.02–1.06	1.11b	1.06–1.17	1.01	0.99–1.03	1.06b	1.03–1.09
Schooling	0.98	0.94–1.02	1.01	0.98–1.04	0.92	0.82–1.03	0.99	0.95–1.03	0.99	0.93–1.05

Nap on weekends	Hypertension		Dyslipidemia		Diabetes mellitus		C-reactive protein		Blood pressure
	PR	95%CI	PR	95%CI	PR	95%CI	PR	95%CI	PR	95%CI
Intentional nap	0.78	0.54–1.14	1.12	0.83–1.52	0.84	0.33–2.15	0.90	0.64–1.27	1.40	0.77–2.54
Unintentional nap	0.73	0.46–1.16	1.17	0.83–1.63	1.45	0.56–3.78	1.06	0.75–1.51	1.27	0.63–2.55
Sex (Female)	0.71	0.50–1.01	0.95	0.72–1.25	1.59	0.52–4.87	1.77c	1.26–2.48	0.40a	0.23–0.72
Marital status (without partner)	1.18	0.81–1.73	0.84	0.61–1.16	1.10	0.43–2.80	1.10	0.80–1.50	1.81	0.98–3.34
Skin color/Race (Black/Mixed-Race/Indigenous)	1.49a	1.04–2.14	1.05	0.73–1.50	1.47	0.63–3.40	1.16	0.82–1.64	1.47	0.81–2.67
Tobacco use (smoker/former smoker)	1.22	0.79–1.89	1.19	0.84–1.68	1.77	0.69–4.55	0.85	0.53–1.35	1.60	0.83–3.08
Alcohol consumption (yes)	0.83	0.58–1.18	1.56a	1.15–2.12	0.86	0.35–2.11	1.08	0.79–1.47	1.12	0.63–1.98
Physical activity (GPAQ v2)e	1.06	0.75–1.50	0.94	0.72–1.22	0.54	0.24–1.23	0.78	0.58–1.04	0.78	0.45–1.34
Age	1.06b	1.04–1.08	1.04b	1.02–1.06	1.12a	1.06–1.17	1.01	0.99–1.03	1.06a	1.03–1.09
Schooling	0.98	0.94–1.02	1.01	0.98–1.04	0.91	0.82–1.02	0.99	0.95–1.03	0.99	0.93–1.05

Abbreviations: 95%CI, 95% confidence interval; GPAQ v2, Global Physical Activity Questionnaire, version 2; PR, prevalence ratio.

Notes: Prevalence ratio: the probability of presenting the “yes” result was estimated. ^a p-value <0.05. ^b p-value < 0.0001.

Discussion

The present study demonstrated the relationship between napping habits and the risk factors for cardiovascular health (CVH). Different alterations were identified according to the intentionality of the nap and its allocation during the week or on the weekend. Notable among the findings is that participants who napped intentionally during the week presented, in laboratory results, the highest values of the lipid profile. Participants who napped unintentionally during the week and on the weekend showed higher HbA1c values.

In the current study, traditional factors such as age, schooling, skin color/race, marital status, alcohol consumption, and physical activity were associated with increased BMI, HbA1c, TC, non-HDL and HDL cholesterol, and TG. It should be emphasized, however, that intentional and unintentional napping remained an independent risk factor for increased HbA1c and lipid profile variables. We highlight that intentional napping, that is, voluntary and conscious as a habit, could be related to pleasure, not just to the need to sleep. On the other hand, unintentional napping occurs in a restorative way due to poor sleep quality, fatigue, short nighttime sleep duration, or to prevent sleep loss at night.[23] [24]

In the present study, the mean age of participants who did not nap was significantly lower than that of participants who napped intentionally during the week and intentionally or unintentionally on the weekend. A longitudinal study[25] conducted with middle-aged and older adults in China found that individuals who did not nap were younger compared with those who napped. The study[25] did not provide information regarding napping during the week and on the weekend, or about the intentionality of napping, which did not enable a more detailed comparison with the current study. It should be noted that, in the literature, several studies show that older adults nap more during the day, because they have decreased nighttime sleep duration and reduced sleep efficiency,[26] which contribute to frequent daytime sleepiness.[27]

Intentional napping during the week was more prevalent in men, corroborating the findings of another study.[17] Women, in the present study, were less likely to nap intentionally during the week than to not nap or to nap unintentionally. These results are compatible with those found in another study[28] in which women were the majority among those who presented unintentional napping. In a longitudinal study[29] conducted in China with middle-aged and older men and women, a higher proportion of women reported not having napped; the authors emphasized that Chinese women would be more involved in household chores and, therefore, would be less likely to nap. However, in another study[24] with older adults, intentional napping was equally prevalent among women and men. Among Chinese university students, women reported intentional naps more frequently than men, although they also had a higher proportion of naps due to fatigue and poor sleep quality.[23] Other authors[27] also highlight fatigue and poor sleep quality, caused by repeated awakenings during the night, as a factor for the occurrence of unintentional napping in middle-aged women. These sleep disorders may be associated with the double work shift of women who need to balance paid work with household chores and family care. Maintaining a balance among professional, domestic, intellectual, leisure, and rest activities can contribute to good sleep quality, with a reduction in daytime fatigue and sleepiness.[30]

Participants living with a partner were less likely to nap unintentionally than to not nap or to take intentional naps on weekends. In a study with public servants,[14] most participants were married and napped for a longer time, more than 90 minutes. The authors[14] considered only the mean duration of naps, not verifying the intentionality or on which days of the week the naps occurred, making it difficult to compare their data with those of the present study. An epidemiological cohort study[31] indicated that being married or cohabiting was associated with better overall sleep health, including normal sleep duration, fewer insomnia symptoms, and greater sleep efficiency. The results suggest that being in a serious relationship is associated with better sleep health.[31] Married participants had better mental health than those who were single, mainly decreased anxiety, insomnia, and severe depression,[32] which could contribute to good quality sleep and reduced sleepiness.

In the current study, individuals who did not nap presented more years of schooling compared with those who napped, which similar to a study[33] that found that men with higher education took fewer naps during the day. However, contrary to the present study, other studies[25] have found that most of the level of schooling of the participants in a population survey who did not nap was elementary education or below. One study[23] found that individuals with higher education took more unintentional naps compared with individuals with elementary education, and, in this case, naps were taken as a way to make up for a lack of sleep. In another study,[17] those who napped three to seven times a week had elementary-level education. Certain risk factors for poor sleep quality may affect mainly individuals with lower levels of schooling, such as a high number of hours worked per week, shift work, lack of physical exercise, and use of cell phones at bedtime.[34]

Considering the risk factors for CVD, several relationships involving them and naps were found in the present study. Individuals who napped intentionally during the week presented increased TC, LDL, and non-HDL cholesterol values, and those who napped intentionally on the weekend presented increased TC and non-HDL cholesterol values compared with those who did not nap. According to the 2023 Brazilian Guidelines for In-Office and Out-of-Office Blood Pressure Measurement,[35] typical dyslipidemia with reduced HDL cholesterol levels is associated with the risk of CVD. In a Chinese study[25] with 12,277 participants, those who napped were more likely to present dyslipidemia. However, a Swiss study[17] showed that individuals who napped once or twice a week presented a lower risk of dyslipidemia, with no information on whether the napping occurred during the week or on the weekend. The naps could have contributed to make up for short nighttime sleep duration,[17] an aspect that was not evaluated in the current study.

Another important factor associated with dyslipidemia is related to increased TG. In the present study, individuals who did not nap (during the week and on the weekend) presented TG levels within the reference values. It should be emphasized that the probability of presenting high TG was greater among those who took unintentional naps compared with those who did not nap during the week. Studies have reported that long naps (longer than 90 minutes)[14] and short sleep duration[28] were associated with elevated triglycerides. These factors were not measured in the present study; however, it should be considered that the presence of naps may be associated with short sleep duration.[15]

The probability of napping unintentionally during the week was higher in individuals who reported DM, another cardiovascular risk factor, and the probability of napping intentionally was higher in those who presented HbA1c values above 5.6%. Furthermore, unintentional naps both during the week and on the weekend were independently associated with higher mean HbA1c values; participants who napped on the weekend showed an increase in mean values compared with those who did not nap. In meta-analysis studies, prolonged napping during the afternoon was associated with an increased risk for elevated HbA1c values[36] and type-2 diabetes,[37] [38] although the authors did not address the intentionality of napping.

Until the conclusion of the present article, no studies had been found on the intentionality of napping associated with cardiovascular risk factors. Regarding intentional and unintentional napping, two recent studies were identified, one which verified the association of types of napping with cognition in older adults,[24] and another with restrictions on social activities such as visiting friends and family, lower levels of participation in recreational activities, and lower church attendance.[39]

Limitations and strengths can be highlighted in the current study. As it is a cross-sectional study, we could not investigate causal relationships involving the variables. There was no information about the place of residence and its distance from the workplace, which would be important, since living far from the workplace could be responsible for early arousals and naps during the day. Furthermore, the occurrence of CVD in participants was not investigated, but rather the risk factors for it. Neither did we evaluate the coexistence of different risk factors in the same individual, which is known to increase the probability of adverse cardiovascular events. The absence of data on nap duration, specifying whether they were short or long, made it difficult to compare the data herein obtained with data from the literature. However, as mentioned before, this characteristic of napping has been widely studied, to the detriment of others such as intentionality and allocation in the week, which were objects of the present study.

It should be considered that naps may represent a warning sign for healthcare providers to initiate or maintain monitoring of an individual, even independently of the presence of other risk factors for CVD. It is important to emphasize that the present study contributes to literature by identifying that the habit of napping intentionally, especially during the week, is associated with changes in the lipid profile, which are highly likely to harm individuals' CVH.

Conclusion

In the present study, we observed that participants who napped intentionally during the week presented the highest laboratory results, of the lipid profile, and those who napped unintentionally during the week and on the weekend presented higher HbA1c values. Traditional factors such as age, schooling, skin color/race, marital status, alcohol consumption, and physical activity were also associated with increased BMI, HbA1c, TC, non-HDL and HDL cholesterol, and TG; however, napping remained an independent factor for the increase in HbA1c and lipid profile variables.

Conflict of Interests

The authors have no conflict of interests to declare.

Ethical Considerations

The current study was approved by the institutional Ethics in Research Committee, under authorization number CAAE: 28971320.5.0000.5404, and followed the current ethical recommendations.

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Publication History

Received: 16 August 2024

Accepted: 09 January 2025

Article published online:
03 April 2025