Association of Dietary Behaviors with Poor Sleep Quality and Increased Risk of Obstructive Sleep Apnea in Korean Military Service Members

Figures & data

Table 1 Characteristics of Military Service Members

		Sleep Quality			OSA
		PSQI ≤ 5 (n=1810)	PSQI > 5 (n=2579)	p value	Low Risk (n=3775)	High Risk (n=614)	p value
Demographics and Lifestyle
Age, years	Mean (SD)	20.7 (1.2)	20.9 (1.3)	<0.001	20.8 (1.3)	20.9 (1.3)	0.022
Education	≤ High school	1704 (94.1)	2422 (93.9)	0.800	3548 (94.0)	578 (94.1)	0.957
	College or higher	106 (5.9)	157 (6.1)		227 (6.0)	36 (5.9)
BMI, kg/m^2	Mean (SD)	23.8 (2.9)	23.9 (2.8)	0.524	23.5 (2.5)	25.8 (3.7)	<0.001
Smoking	Never	1035 (57.2)	1288 (49.9)	<0.001	2014 (53.4)	309 (50.3)	0.363
	Past smoker	96 (5.3)	165 (6.4)		224 (5.9)	37 (6.0)
	Current smoker	679 (37.5)	1126 (43.7)		1537 (40.7)	268 (43.6)
Drinking	< 1/month	468 (25.9)	571 (22.1)	<0.001	900 (23.8)	139 (22.6)	0.010
	< 1/week	516 (28.5)	698 (27.1)		1039 (27.5)	175 (28.5)
	1–2/week	609 (33.6)	888 (34.4)		1311 (34.7)	186 (30.3)
	3–7/week	217 (12.0)	422 (16.4)		525 (13.9)	114 (18.6)
Exercise	< 1/week	265 (14.6)	444 (17.2)	0.128	576 (15.3)	133 (21.7)	<0.001
	1–2/week	436 (24.1)	622 (24.1)		897 (23.8)	161 (26.2)
	3–4/week	533 (29.4)	717 (27.8)		1098 (29.1)	152 (24.8)
	≥ 5/week	576 (31.8)	796 (30.9)		1204 (31.9)	168 (27.4)
Stress	Very low	268 (14.8)	98 (3.8)	<0.001	353 (9.4)	13 (2.1)	<0.001
	Low	377 (20.8)	233 (9.0)		577 (15.3)	33 (5.4)
	Moderate	870 (48.1)	1100 (42.7)		1721 (45.6)	249 (40.6)
	High	221 (12.2)	848 (32.9)		845 (22.4)	224 (36.5)
	Very high	74 (4.1)	300 (11.6)		279 (7.4)	95 (15.5)
Coffee	< 1/week	734 (40.6)	912 (35.4)	<0.001	1454 (38.5)	192 (31.3)	<0.001
	1–2/week	440 (24.3)	551 (21.4)		855 (22.6)	136 (22.1)
	3–6/week	291 (16.1)	439 (17.0)		631 (16.7)	99 (16.1)
	1/day	202 (11.2)	350 (13.6)		461 (12.2)	91 (14.8)
	2/day	98 (5.4)	214 (8.3)		251 (6.6)	61 (9.9)
	≥ 3/day	45 (2.5)	113 (4.4)		123 (3.3)	35 (5.7)
Occupational factors
Rank	Private	192 (10.6)	131 (5.1)	<0.001	291 (7.7)	32 (5.2)	0.095
	Private first class	807 (44.6)	1048 (40.6)		1594 (42.2)	261 (42.5)
	Corporal	583 (32.2)	1068 (41.4)		1403 (37.2)	248 (40.4)
	Sergeant	228 (12.6)	332 (12.9)		487 (12.9)	73 (11.9)
Position	Combat arms	1246 (68.8)	1725 (66.9)	<0.001	2531 (67.0)	440 (71.7)	0.001
	Driver	250 (13.8)	255 (9.9)		436 (11.5)	69 (11.2)
	Military chef	48 (2.7)	107 (4.1)		124 (3.3)	31 (5.0)
	Administration	266 (14.7)	492 (19.1)		684 (18.1)	74 (12.1)
Night shift with off- duty ^a	None	1071 (59.2)	1391 (53.9)	<0.001	2090 (55.4)	372 (60.6)	0.003
	<1/month	113 (6.2)	123 (4.8)		205 (5.4)	31 (5.0)
	2/month	167 (9.2)	205 (7.9)		329 (8.7)	43 (7.0)
	3/month	177 (9.8)	253 (9.8)		360 (9.5)	70 (11.4)
	4/month	122 (6.7)	177 (6.9)		277 (7.3)	22 (3.6)
	≥ 5/month	160 (8.8)	430 (16.7)		514 (13.6)	76 (12.4)
Night shift without off-duty ^a	None	1090 (60.2)	1333 (51.7)	<0.001	2093 (55.4)	330 (53.7)	0.832
	<1/month	59 (3.3)	95 (3.7)		129 (3.4)	25 (4.1)
	2/month	80 (4.4)	108 (4.2)		159 (4.2)	29 (4.7)
	3/month	80 (4.4)	99 (3.8)		157 (4.2)	22 (3.6)
	4/month	95 (5.2)	123 (4.8)		189 (5.0)	29 (4.7)
	≥ 5/month	406 (22.4)	821 (31.8)		1048 (27.8)	179 (29.2)
Dietary behaviors
Skipping breakfast	None	1392 (76.9)	1658 (64.3)	<0.001	2655 (70.3)	395 (64.3)	<0.001
	1–2/week	269 (14.9)	536 (20.8)		683 (18.1)	122 (19.9)
	3–4/ week	94 (5.2)	242 (9.4)		283 (7.5)	53 (8.6)
	5–6/week	29 (1.6)	91 (3.5)		100 (2.6)	20 (3.3)
	7/week	26 (1.4)	52 (2.0)		54 (1.4)	24 (3.9)
Overeating	None	1104 (61.0)	1312 (50.9)	<0.001	2143 (56.8)	273 (44.5)	<0.001
	1–2/week	549 (30.3)	922 (35.8)		1260 (33.4)	211 (34.4)
	3–4/ week	108 (6.0)	259 (10.0)		278 (7.4)	89 (14.5)
	5–6/week	20 (1.1)	42 (1.6)		43 (1.1)	19 (3.1)
	7/week	29 (1.6)	44 (1.7)		51 (1.4)	22 (3.6)
Snacking	None	218 (12.0)	200 (7.8)	<0.001	374 (9.9)	44 (7.2)	0.023
	1–2/week	484 (26.7)	681 (26.4)		1000 (26.5)	165 (26.9)
	3–4/week	408 (22.5)	569 (22.1)		861 (22.8)	116 (18.9)
	5–6/week	122 (6.7)	190 (7.4)		268 (7.1)	44 (7.2)
	1/day	314 (17.3)	470 (18.2)		664 (17.6)	120 (19.5)
	2/day	190 (10.5)	310 (12.0)		415 (11.0)	85 (13.8)
	≥ 3/day	74 (4.1)	159 (6.2)		193 (5.1)	40 (6.5)
Night meals	None	1101 (60.8)	1307 (50.7)	<0.001	2105 (55.8)	303 (49.3)	0.001
	1–3/month	275 (15.2)	419 (16.2)		599 (15.9)	95 (15.5)
	1–2/week	325 (18.0)	551 (21.4)		744 (19.7)	132 (21.5)
	3–4/ week	78 (4.3)	205 (7.9)		230 (6.1)	53 (8.6)
	5–6/week	7 (0.4)	45 (1.7)		41 (1.1)	11 (1.8)
	7/week	24 (1.3)	52 (2.0)		56 (1.5)	20 (3.3)
Sleep characteristics
Subjective sleep duration	Mean (SD)	7.7 (0.7)	6.6 (1.1)	<0.001	7.1 (1.1)	7.0 (1.0)	0.001
PSQI global score	Mean (SD)	3.5 (1.3)	8.9 (2.6)	<0.001	6.5 (3.3)	8.3 (3.4)	<0.001

Note: ^aGoing off duty right after night shift.

Abbreviations: OSA, obstructive sleep apnea; BMI, body mass index; PSQI, Pittsburgh sleep quality index; SD, standard deviation.

Figure 1 Distribution of global Pittsburgh sleep quality index (PSQI) scores.

Table 2 Multivariable Logistic Regression of Dietary Behaviors for Poor Sleep Quality (PSQI > 5)

		PSQI ≤ 5 (n=1810)	PSQI > 5 (n=2579)	Unadjusted Odds Ratio	Adjusted Odds Ratio^a	Overall Effect
Skipping breakfast	None	1392 (76.9)	1658 (64.3)	–	–	X^2 = 8.0 df = 4 p = 0.092
	1–2/week	269 (14.9)	536 (20.8)	1.67 (1.42–1.97, p<0.001)	1.23 (1.02–1.47, p=0.029)
	3–4/week	94 (5.2)	242 (9.4)	2.16 (1.69–2.78, p<0.001)	1.28 (0.97–1.70, p=0.082)
	5–6/week	29 (1.6)	91 (3.5)	2.63 (1.75–4.09, p<0.001)	1.42 (0.90–2.30, p=0.141)
	7/week	26 (1.4)	52 (2.0)	1.68 (1.05–2.74, p=0.033)	1.17 (0.69–2.04, p=0.564)
Overeating	None	1104 (61.0)	1312 (50.9)	–	–	X^2 = 8.6 df = 4 p = 0.073
	1–2/week	549 (30.3)	922 (35.8)	1.41 (1.24–1.61, p<0.001)	1.17 (1.00–1.36, p=0.048)
	3–4/week	108 (6.0)	259 (10.0)	2.02 (1.59–2.57, p<0.001)	1.39 (1.06–1.83, p=0.019)
	5–6/week	20 (1.1)	42 (1.6)	1.77 (1.05–3.09, p=0.038)	0.92 (0.51–1.73, p=0.796)
	7/week	29 (1.6)	44 (1.7)	1.28 (0.80–2.07, p=0.314)	0.87 (0.50–1.54, p=0.634)
Snacking	None	218 (12.0)	200 (7.8)	–	–	X^2 = 13.6 df = 6 p = 0.035
	1–2/week	484 (26.7)	681 (26.4)	1.53 (1.23–1.92, p<0.001)	1.50 (1.16–1.94, p=0.002)
	3–4/week	408 (22.5)	569 (22.1)	1.52 (1.21–1.91, p<0.001)	1.41 (1.08–1.85, p=0.011)
	5–6/week	122 (6.7)	190 (7.4)	1.70 (1.26–2.29, p<0.001)	1.40 (1.00–1.96, p=0.052)
	1/day	314 (17.3)	470 (18.2)	1.63 (1.28–2.07, p<0.001)	1.43 (1.09–1.89, p=0.010)
	2/day	190 (10.5)	310 (12.0)	1.78 (1.37–2.32, p<0.001)	1.40 (1.04–1.90, p=0.029)
	≥ 3/day	74 (4.1)	159 (6.2)	2.34 (1.68–3.29, p<0.001)	1.89 (1.29–2.80, p=0.001)
Night meals	None	1101 (60.8)	1307 (50.7)	–	–	X^2 = 22.3 df = 5 p < 0.001
	1–3/month	275 (15.2)	419 (16.2)	1.28 (1.08–1.53, p=0.004)	1.08 (0.89–1.31, p=0.436)
	1–2/week	325 (18.0)	551 (21.4)	1.43 (1.22–1.68, p<0.001)	1.14 (0.95–1.37, p=0.158)
	3–4/week	78 (4.3)	205 (7.9)	2.21 (1.69–2.92, p<0.001)	1.83 (1.35–2.48, p<0.001)
	5–6/week	7 (0.4)	45 (1.7)	5.42 (2.60–13.19, p<0.001)	5.54 (2.49–14.18, p<0.001)
	7/week	24 (1.3)	52 (2.0)	1.83 (1.13–3.03, p=0.016)	1.40 (0.81–2.47, p=0.241)

Notes: Odds ratio (OR), 95% confidence intervals, and p-value are presented. ^aMultivariable logistic regression: Dietary behaviors + Demographics and Lifestyle factors + Occupational factors (Detailed results of all variables are presented in Table S1).

Table 3 Multivariable Logistic Regression of Dietary Behaviors for Poor Sleep Quality (PSQI > 9)

		PSQI ≤ 9 (n=3486)	PSQI > 9 (n=903)	Unadjusted Odds Ratio	Adjusted Odds Ratio ^a	Overall Effect
Skipping breakfast	None	2533 (72.7)	517 (57.3)	–	–	X^2 = 20.9 df = 4 p < 0.001
	1–2/week	596 (17.1)	209 (23.1)	1.72 (1.43–2.06, p<0.001)	1.31 (1.06–1.62, p=0.011)
	3–4/week	229 (6.6)	107 (11.8)	2.29 (1.78–2.93, p<0.001)	1.36 (1.01–1.82, p=0.041)
	5–6/week	68 (2.0)	52 (5.8)	3.75 (2.57–5.43, p<0.001)	2.25 (1.45–3.45, p<0.001)
	7/week	60 (1.7)	18 (2.0)	1.47 (0.84–2.46, p=0.158)	0.72 (0.38–1.33, p=0.309)
Overeating	None	2000 (57.4)	416 (46.1)	–	–	X^2 = 11.2 df = 4 p = 0.025
	1–2/week	1144 (32.8)	327 (36.2)	1.37 (1.17–1.62, p<0.001)	1.15 (0.95–1.38, p=0.154)
	3–4/week	243 (7.0)	124 (13.7)	2.45 (1.92–3.12, p<0.001)	1.62 (1.21–2.17, p=0.001)
	5–6/week	44 (1.3)	18 (2.0)	1.97 (1.10–3.38, p=0.018)	1.03 (0.53–1.93, p=0.932)
	7/week	55 (1.6)	18 (2.0)	1.57 (0.89–2.65, p=0.102)	1.00 (0.51–1.87, p=0.991)
Snacking	None	353 (10.1)	65 (7.2)	–	–	X^2 = 10.6 df = 6 p = 0.1
	1–2/week	923 (26.5)	242 (26.8)	1.42 (1.06–1.93, p=0.021)	1.50 (1.07–2.13, p=0.019)
	3–4/week	783 (22.5)	194 (21.5)	1.35 (0.99–1.84, p=0.059)	1.36 (0.96–1.95, p=0.091)
	5–6/week	238 (6.8)	74 (8.2)	1.69 (1.17–2.45, p=0.006)	1.46 (0.95–2.24, p=0.083)
	1/day	638 (18.3)	146 (16.2)	1.24 (0.91–1.72, p=0.183)	1.14 (0.79–1.66, p=0.484)
	2/day	384 (11.0)	116 (12.8)	1.64 (1.18–2.31, p=0.004)	1.34 (0.91–1.98, p=0.140)
	≥ 3/day	167 (4.8)	66 (7.3)	2.15 (1.45–3.17, p<0.001)	1.71 (1.08–2.68, p=0.021)
Night meals	None	1986 (57.0)	422 (46.7)	–	–	X^2 = 22.2 df = 5 p < 0.001
	1–3/month	559 (16.0)	135 (15.0)	1.14 (0.91–1.41, p=0.244)	0.92 (0.72–1.18, p=0.522)
	1–2/week	653 (18.7)	223 (24.7)	1.61 (1.33–1.93, p<0.001)	1.39 (1.12–1.73, p=0.003)
	3–4/week	200 (5.7)	83 (9.2)	1.95 (1.48–2.57, p<0.001)	1.71 (1.24–2.36, p=0.001)
	5–6/week	34 (1.0)	18 (2.0)	2.49 (1.37–4.40, p=0.002)	2.08 (1.03–4.09, p=0.037)
	7/week	54 (1.5)	22 (2.4)	1.92 (1.13–3.14, p=0.012)	1.24 (0.67–2.25, p=0.483)

Notes: Odds ratio (OR), 95% confidence intervals, and p-value are presented. ^aMultivariable logistic regression: Dietary behaviors + Demographics and Lifestyle factors + Occupational factors (Detailed results of all variables are presented in Table S2).

Figure 2 Forest plot of the odds ratios of dietary behaviors on poor sleep quality. Adjusted odds ratios and 95% confidence intervals (CI) were calculated in the multivariable logistic model using demographic, lifestyle, and occupational factors as the covariates. The size of the square represents the number of participants in each item.

Table 4 Multivariable Logistic Regression of Dietary Behaviors for High Risk of OSA

		Low-Risk OSA (n=3775)	High-Risk OSA (n=614)	Unadjusted Odds Ratio	Adjusted Odds Ratio ^a	Overall Effect
Skipping breakfast	None	2655 (70.3)	395 (64.3)	-	-	X^2 = 9.3 df = 4 p = 0.054
	1–2/week	683 (18.1)	122 (19.9)	1.20 (0.96–1.49, p=0.103)	1.13 (0.88–1.45, p=0.329)
	3–4/week	283 (7.5)	53 (8.6)	1.26 (0.91–1.71, p=0.148)	0.94 (0.65–1.33, p=0.722)
	5–6/week	100 (2.6)	20 (3.3)	1.34 (0.80–2.15, p=0.238)	0.91 (0.51–1.55, p=0.734)
	7/week	54 (1.4)	24 (3.9)	2.99 (1.80–4.83, p<0.001)	2.28 (1.27–4.03, p=0.005)
Overeating	None	2143 (56.8)	273 (44.5)	-	-	X^2 = 9.1 df = 4 p = 0.06
	1–2/week	1260 (33.4)	211 (34.4)	1.31 (1.08–1.59, p=0.005)	0.94 (0.76–1.17, p=0.599)
	3–4/week	278 (7.4)	89 (14.5)	2.51 (1.91–3.28, p<0.001)	1.41 (1.02–1.95, p=0.036)
	5–6/week	43 (1.1)	19 (3.1)	3.47 (1.95–5.95, p<0.001)	1.65 (0.83–3.18, p=0.143)
	7/week	51 (1.4)	22 (3.6)	3.39 (1.99–5.60, p<0.001)	1.51 (0.79–2.80, p=0.204)
Snacking	None	374 (9.9)	44 (7.2)	-	-	X^2 = 7.8 df = 6 p = 0.25
	1–2/week	1000 (26.5)	165 (26.9)	1.40 (0.99–2.02, p=0.060)	1.35 (0.92–2.02, p=0.132)
	3–4/week	861 (22.8)	116 (18.9)	1.15 (0.80–1.67, p=0.470)	1.00 (0.67–1.53, p=0.994)
	5–6/week	268 (7.1)	44 (7.2)	1.40 (0.89–2.18, p=0.143)	1.11 (0.68–1.84, p=0.669)
	1/day	664 (17.6)	120 (19.5)	1.54 (1.07–2.24, p=0.022)	1.28 (0.85–1.96, p=0.247)
	2/day	415 (11.0)	85 (13.8)	1.74 (1.19–2.59, p=0.005)	1.42 (0.92–2.23, p=0.119)
	≥ 3/day	193 (5.1)	40 (6.5)	1.76 (1.11–2.80, p=0.016)	1.32 (0.77–2.25, p=0.307)
Night meals	None	2105 (55.8)	303 (49.3)	-	-	X^2 = 13.2 df = 5 p = 0.021
	1–3/month	599 (15.9)	95 (15.5)	1.10 (0.86–1.41, p=0.443)	1.02 (0.77–1.34, p=0.904)
	1–2/week	744 (19.7)	132 (21.5)	1.23 (0.99–1.53, p=0.063)	1.21 (0.94–1.55, p=0.145)
	3–4/week	230 (6.1)	53 (8.6)	1.60 (1.15–2.19, p=0.004)	1.61 (1.10–2.33, p=0.012)
	5–6/week	41 (1.1)	11 (1.8)	1.86 (0.90–3.54, p=0.071)	1.62 (0.70–3.48, p=0.238)
	7/week	56 (1.5)	20 (3.3)	2.48 (1.44–4.12, p=0.001)	2.30 (1.21–4.22, p=0.009)

Notes: Odds ratio (OR), 95% confidence intervals, and p-value are presented. OSA, obstructive sleep apnea. ^aMultivariable logistic regression: Dietary behaviors + Demographics and Lifestyle factors + Occupational factors (Detailed results of all variables are presented in Table S3).

Figure 3 Forest plot of the odds ratios of dietary behaviors on high risk of obstructive sleep apnea (OSA). Adjusted odds ratios and 95% confidence interval (CI) were calculated in the multivariable logistic model using demographic, lifestyle, and occupational factors as the covariates. The size of the square represents the number of participants in each item.