Factors related to self-rated health in teleworkers raising children: focusing on gender differences

Abstract

Objectives: Teleworking is a flexible means of working to effectively utilize one’s time and workplace using information and communication technology. However, teleworking can also lead to work–life conflict and health problems. To support the health of teleworkers, this study aimed to elucidate the factors correlated with the self-rated health of teleworkers raising children, focusing on differences between genders. Methods: The study sample included 1,000 teleworkers (500 women and 500 men). Results: The responses to questionnaire items about health differed between men and women. For men, “marital status,” “walks and exercises,” “keeps an uplifted state of mind as much as possible,” and “work-to-family negative spillover” were extracted. For women, “leads a disciplined life,” “keeps an uplifted state of mind as much as possible,” “eating speed compared with others: slower,” and “sufficiently rests through sleep” were found to affect self-rated health. Conclusions: For male teleworkers raising children, sufficient exercise and physical activity is a crucial aspect of health management. For female teleworkers raising children, self-discipline is needed.

Introduction

Teleworking is a flexible way of working to effectively utilize one’s time and workplace using information and communication technology. For workers raising children, teleworking can facilitate a greater work-life-balance (WLB) and allows work to be balanced with housework and childcare. Teleworking first developed as a reformed workstyle. Furthermore, the number of teleworkers increased after 2020 because of major changes in lifestyle and workstyles caused by the coronavirus disease 2019 (COVID-19) pandemic.

With teleworking, no time is spent commuting; thus, time for housework is increased¹⁾. Furthermore, teleworkers can freely control their time and easily switch between their work role and life, thereby making it easier to achieve WLB²⁾.

However, in teleworking, the starting and finishing times of work can easily become unclear, resulting in long working hours and working at night³⁾. Work becomes ambiguous with private life⁴⁾, and achieving WLB is difficult⁵⁾. When overwork and night working occur, the stress of trying to manage everything at once and the consequent work–life conflict can lead to health issues and poorer health management.

Generally, when the frequency of telework increases, the rhythm of life is disrupted; for example, eating habits tend to become irregular⁶⁾, and alcohol consumption increases⁷⁾. Furthermore, increased desk work exacerbates lower back pain⁸⁾. In telework, to weigh the WLB and lead a healthy lifestyle, teleworkers must manage their health, such as by leading a disciplined life, having good eating habits, and ensuring sleep and rest time.

Previous studies have shown a significant relationship between “self-rated health” and WLB. In Japan, Yamaguchi found that individuals with high “work-family conflict” have low self-rated health⁹⁾. Similarly, a strong relationship has been found between work–life conflict and deterioration in self-rated health. This effect was found to differ between genders¹⁰⁾. Among teleworkers, women are more concerned about their WLB than men⁵⁾. A Japanese study of teleworkers during the COVID-19 pandemic found that men and women have different stress reactions and stress coping skills¹¹⁾. The rates of work–life conflict in men and women have been found to differ significantly¹²⁾, and Yoshimura et al.¹³⁾ found women to have significantly higher levels of work–life conflict. Iwasaki¹⁴⁾ conducted a survey of married couples and reported significantly higher scores for “family-to-work negative spillover” among wives.

The WLB of teleworkers¹⁵⁾ and workers who are raising children are related to lifestyle¹⁶⁾. However, as far as we could find, no studies have elucidated the state of self-rated health of teleworkers raising children and factors associated with their self-rated health. This study aimed to identify the factors related to the self-rated health of teleworkers raising children, with a focus on the gender differences.

Methods

Participants

The sample in this study consisted of 1,000 teleworkers (500 women and 500 men). Based on the results of the FY2020 Teleworker Population Survey¹⁷⁾, the population of teleworkers was assumed to be 9,000. The required sample size, using a margin of error of 5%, a confidence level of 95%, and a response rate of 50%, was calculated as approximately 370. To allow for differences between the response rate and the effective response rate, the number of questionnaires distributed was set at 500 for each gender. We received no invalid responses, so 500 respondents were included in the analysis.

Participants were recruited through MyVoice Ltd. (Tokyo, Japan), which is an online survey company. Our inclusion criteria were raising children, living with at least one child (aged <18 years), having teleworking experience, and consenting to participation. Marital status, occupation, and form of employment did not affect inclusion.

Survey content

An anonymous online questionnaire survey was conducted between November and December, 2021. The following data were requested from respondents.

(1) Basic attributes: age, number of children, family structure, and occupation.

(2) Mean teleworking hours and mean housework/childcare hours per day.

(3) Self-rated health: to evaluate worker health, “self-rated health”¹⁸⁾ was used. Self-rated health is a tool that enables subjective evaluation of one’s overall health¹⁹⁾, and is included in questionnaires of comprehensive surveys of living conditions in Japan. The question “how do you feel about your general health?” was evaluated according to a four-point scale: “very healthy,” “somewhat healthy,” “not very healthy,” and “not healthy.” Responses were divided into groups: “very healthy” and “somewhat healthy” constituting the healthy group and “not very healthy” and “not healthy” constituting the unhealthy group.

(4) WLB: WLB depends on the relationship between work and family roles: the interrole effect (spillover). Spillover occurs when the situation and experience of one role (ie, either work or family) affects the situation and experience of the other role²⁰⁾.

In this study, the Japanese version of the Survey Work-Home Interaction–NijimeGen survey was used to assess WLB²¹⁾. This scale consists of 22 question items with confirmed reliability and validity. Subscales include “work-to-family negative spillover (8 items),” “family-to-work negative spillover (4 items),” “work-to-family positive spillover (5 items),” and “family-to- work positive spillover (5 items).” Responses include “never (0 points),” “sometimes (1 point),” “often (2 points),” and “always (3 points).” The scale was used with the permission of the Japanese developer.

(5) Healthy behaviors: we created nine closed questions, requiring “yes” or “no” answers, to assess the healthy behaviors of respondents. The questions were created with refrence to previous surveys²²⁾. They include “gets enough sleep and rest ,” “leads a disciplined life,” and “walks and exercises.”

(6) Lifestyle: question items were created based on the medical interview items for specific health checkups and specific health guidance in Japan. More specifically, there were 11 items, including “current smoking habit” and “weight gain of ≥10 kg since 20 years of age.” Responses were obtained as “yes” or “no.”

Statistical analyses

Gender comparisons of the time spent teleworking, time spent on housework and childcare, and WLB subscale scores were performed using Student t-tests. The relationship of marital status according to men and women with the healthy and unhealthy groups was examined using chi-square tests. Separate univariate and multiple logistic regression analyses assessing the variables related to self-rated health were performed for men and women. The dependent variable was health group (healthy group =1, unhealthy group =0). The independent variables were basic attributes, WLB scale scores, and responses to the healthy behaviors and lifestyle questions. Only those healthy behaviors and lifestyle variables found to differ significantly between the (members of the relevant gender of the) healthy and unhealthy groups were included in multiple logistic regression analyses using forward selection (likelihood ratios).

SPSS Statistics for Windows version 27 (IBM Corp., Armonk, NY, USA) was used for analyses, and p-values <0.05 were considered statistically significant.

Ethical considerations

The information sheet for this study noted the purpose and significance of the study and protection of personal information. Study participation was voluntary, and questionnaire responses were anonymous to de-identify participants. This study was conducted with the approval of the ethical review board of Mie Prefectural College of Nursing (approval no: 212602).

Results

Basic participant attributes

Basic characteristics are shown in Table 1. The mean participant age was 39.13 (standard deviation [SD], 6.4) years. The number of participants with just one child aged <18 years was the largest, at 477 (47.7%). The mean age was 8.40 (SD, 5.3) years for the first-born child, 6.61 (SD, 4.5) years for the second, 5.11 (SD, 3.9) years for the third, and 4.30 (SD, 3.5) years for the fourth.

Table 1. Basic participant attributes

n=1,000
Variable		Category	Mean ± SD
Age (years)			39.13 ± 6.4
Variables		Category	n (individuals)	%
Marital status		Not married (not married yet, or widowed)	64	6.4
		Married	936	93.6
Cohabiting family members		Spouse or partner	934	93.4
(Multiple Answers)		One’s own, or spouse/ partner’s parents	92	9.2
		Unmarried child(ren) aged 18 or younger	1000	100.0
		Unmarried child(ren) aged 19 or older	30	3.0
		Married child(ren)	0	0.0
		Other	15	1.5
No. of children aged 18 years or younger		1 child	477	47.7
		2 children	441	44.1
		3 children	72	7.2
		4 children or more	10	1.0
Employment status		Regular staff/ employee	790	79.0
		Part-time worker	109	10.9
		Dispatched worker from temporary labour agency	12	1.2
		Contract employee	19	1.9
		Temporary employee	5	0.5
		Company executive	6	0.6
		Self-employed worker	48	4.8
		Other	11	1.1
Self-rated health	Healthy group	Very healthy	211	21.1
		Somewhat healthy	655	65.5
	Unhealthy group	Not very healthy	121	12.1
		Not healthy	13	1.3
Regular hospital visits		Attending hospital	217	21.7
		Not attending hospital	783	78.3

Gender comparisons of the time spent teleworking, the time spent on housework and childcare, marital status, and self-rated health

Gender comparisons of time spent on telework, housework, and childcare, as well as marital status and self-rated health, are reported in Table 2. The mean time spent teleworking was 7.35 (SD, 2.4) hours/day for men and 6.06 (SD, 2.4) hours/day for women. The teleworking hours of men were significantly higher (p<0.001). The mean time spent on housework and childcare was 2.48 (SD, 1.8) hours/day for men and 4.94 (SD, 2.7) hours/day for women, with significantly longer hours among women (p<0.001).

Table 2. Gender comparisons of the time spent teleworking, the time spent on housework and childcare, marital status, and self-rated health

Mean ± SD
Variables		Men (n=500)	Women (n=500)	p-value
Marital status a	Married (individuals (%))	495 (99.0)	441 (88.2)	<0.001***
	Not married (individuals (%))	5 (1.0)	59 (11.8)
Age (years) b		39.44 ± 6.4	38.82 ± 6.3	0.126
Mean time spent teleworking (hours/day) b		7.35 ± 2.4	6.06 ± 2.4	<0.001***
Mean time spent on housework and childcare (hours/day)b		2.48 ± 1.8	4.94 ± 2.7	<0.001***
Telework frequency a	4-5 days per week (individuals (%))	104 (20.8)	137 (27.4)	0.030*
	2-3 days per week (individuals (%))	132 (26.4)	141 (28.2)
	Around once a week (individuals (%))	102 (20.4)	74 (14.8)
	Once or twice a month (individiuals (%))	64 (12.8)	66 (13.2)
	Several times a year (individiuals (%))	98 (19.6)	82 (16.4)
Number of years of telework experience a	Less than one year (individuals (%))	102 (20.4)	162 (32.4)	<0.010**
	One-to-three years (individuals (%))	359 (71.8)	273 (54.6)
	Three-to-five years (individuals (%))	22 (4.4)	26 (5.2)
	Five-to-ten years (individuals (%))	10 (2.0)	20 (4.0)
	Ten years or more (individuals (%))	7 (1.4)	19 (3.8)
Scores for the WLB subscales b	Work-to-family negative spillover	0.92 ± 0.6	0.84 ± 0.6	0.056
	Family-to-work negative spillover	0.70 ± 0.7	0.57 ± 0.7	0.002**
	Work-to-family positive spillover	1.13 ± 0.7	1.21 ± 0.7	0.052
	Family-to-work positive spillover	1.25 ± 0.7	1.31 ± 0.7	0.180
Self-rated health a	Healthy group (individuals (%))	422 (84.4)	444 (88.8)	0.041*
	Unhealthy group (individuals (%))	78 (15.6)	56 (11.2)

^a)χ² test ^b) t-test *p<0.05, **p<0.01, ***p<0.001

Average scores on the family-to-work negative spillover WLB were 0.70 (SD, 0.7) and 0.57 (SD, 0.7) for men and women, respectively. The scores for men were significantly higher (p=0.002). No significant differences were found between the scores of men and women on any of the other WLB subscales.

Gender comparisons of healthy behaviors and lifestyle

Gender comparisons of health behaviors and lifestyle are shown in Table 3. A significant difference was found between men and women for “gets enough sleep and rest,” “leads a disciplined life,” “eats a well-balanced diet,” “walks and exercises,” and “keeps an uplifted state of mind as much as possible.”

Table 3. Gender comparison of health behaviors and lifestyle

(n=1,000)
Variables		Category	Men (n=500)	Women (n=500)	p-value
			n (%)	n (%)
Healthy behaviors	Gets enough sleep and rest	Yes	415 (83.0)	447 (89.4)	0.003**
		No	85 (17.0)	53 (10.6)
	Leads a disciplined life	Yes	405 (81.0)	441 (88.2)	0.002**
		No	95 (19.0)	59 (11.8)
	Eats a well-balanced diet	Yes	374 (74.8)	446 (89.2)	<0.001***
		No	126 (25.2)	54 (10.8)
	Receives regular health checkups	Yes	433 (86.6)	426 (85.2)	0.525
		No	67 (13.4)	74 (14.8)
	Walks and exercises	Yes	372 (74.4)	326 (65.2)	0.002**
		No	128 (25.6)	174 (34.8)
	Participates in local activities	Yes	162 (32.4)	170 (34.0)	0.591
		No	338 (67.6)	330 (66.0)
	Keeps an uplifted state of mind as much as possible	Yes	368 (73.6)	423 (84.6)	<0.001***
		No	132 (26.4)	77 (15.4)
	Has a hobby	Yes	360 (72.0)	346 (69.2)	0.331
		No	140 (28.0)	154 (30.8)
	Goes out whenever possible	Yes	326 (65.2)	335 (67.0)	0.548
		No	174 (34.8)	165 (33.0)
Lifestyle	Current smoking habit	Yes	166 (33.2)	78 (15.6)	<0.001***
		No	334 (66.8)	422 (84.4)
	Weight gain of ≥10 kg since 20 years of age	Yes	182 (36.4)	115 (23.0)	<0.001***
		No	318 (63.6)	385 (77.0)
	Exercises to sweat lightly for ≥30 min a time, 2 times weekly, for over a year	Yes	170 (34.0)	109 (21.8)	<0.001***
		No	330 (66.0)	391 (78.2)
	Walking or physical activity of equivalent intensity for at least an hour a day in daily life	Yes	198 (39.6)	176 (35.2)	0.150
		No	302 (60.4)	324 (64.8)
	Walks faster than individuals of about the same age	Yes	281 (56.2)	255 (51.0)	0.099
		No	219 (43.8)	245 (49.0)
	Eating speed compared with others	Faster	225 (45.0)	195 (39.0)	0.126
		Normal	232 (46.4)	251 (50.2)
		Slower	43 (8.6)	54 (10.8)
	Eats supper 2 hours before bedtime more than 3 times a week	Yes	170 (34.0)	125 (25.0)	0.002**
		No	330 (66.0)	375 (75.0)
	Eats snacks or drinks sweet beverages between meals	Every day	121 (24.2)	211 (42.2)	<0.001***
		Sometimes	283 (56.6)	221 (44.2)
		Rarely eat	96 (19.2)	68 (13.6)
	Skips breakfast three or more times a week	Yes	116 (23.2)	101 (20.2)	0.250
		No	384 (76.8)	399 (79.8)
	Frequency of drinking alcohol	Every day	146 (29.2)	87 (17.4)	<0.001***
		Sometimes	216 (43.2)	193 (38.6)
		Rarely drink	138 (27.6)	220 (44.0)
	Sufficiently rests through sleep	Yes	326 (65.2)	311 (62.2)	0.324
		No	174 (34.8)	189 (37.8)

χ² test *p<0.05, **p<0.01, ***p<0.001

With regard to lifestyle, significant differences were found between men and women for “current smoking habit,” “weight gain of ≥10 kg since 20 years of age,” “exercises to sweat lightly for ≥30 min a time, 2 times weekly, for over a year,” “eats supper 2 hours before bedtime more than 3 times a week,” “eats snacks or drinks sweet beverages between meals,” and “frequency of drinking alcohol.”

Comparison of the basic attributes, healthy behaviors, lifestyle, and work-life balance scores of the healthy and unhealthy groups

Comparisons of factors related to healthy and unhealthy groups are shown in Table 4. Among the men, significant differences between the healthy and unhealthy groups were found for all of the healthy behaviors. Significant differences between the healthy and unhealthy groups were also found in responses to the lifestyle items “weight gain of ≥10 kg since 20 years of age,” “exercises to sweat lightly for ≥30 min a time, 2 times weekly, for over a year,” “walking or physical activity of equivalent intensity for at least an hour a day in daily life,” “walks faster than individuals of about the same age,” “eating speed compared with others,” and “sufficiently rests through sleep.” On the WLB measure, scores on the “work-to-family negative spillover” (p<0.001) and the “family-to-work negative spillover” (p=0.007) were significantly higher in the unhealthy group than in the healthy group. Conversely, “family-to-work positive spillover” (p=0.025) were significantly higher in the healthy group than in the unhealthy group.

Table 4. Comparison of the basic attributes, health behaviors, lifestyle, and work-life balance scores of the healthy and unhealthy groups

(n=1,000)
Variables		Category	Men (n=500)					Women (n=500)
			Healthy group (n=422)	Unhealthy group (n=78)	p-value	OR (95% CI)	p-value	Healthy group (n=444)	Unhealthy group (n=56)	p-value	OR (95% CI)	p-value
			n (%)	n (%)				n (%)	n (%)
Basic attributes	Marital status	Married	419 (99.2)	76 (97.4)	0.131	3.68 (0.60–22.37)	0.158	397 (89.4)	44 (78.6)	0.018*	2.30 (1.14–4.67)	0.021*
		Unmarried	3 (0.71)	2 (2.6)				47 (10.6)	12 (21.4)
	Age (years) a		39.17±6.40	40.90±6.45	0.015*	0.96 (0.92–0.996)	0.030*	38.74±6.26	39.52±6.39	0.19	0.98 (0.94–1.03)	0.380
	Mean time spent teleworking (hours/day) a		7.34±2.37	7.40±2.70	0.429	0.99 (0.90–1.10)	0.857	6.06±2.37	6.11±2.53	0.443	0.99 (0.88–1.12)	0.886
	Mean time spent on housework and childcare (hours/day)a		2.51±1.85	2.32±1.50	0.191	1.07 (0.92–1.24)	0.381	4.91±2.77	5.14±2.53	0.261	0.97 (0.88–1.07)	0.549
Healthy behaviors	Gets enough sleep and rest	Yes	365 (86.5)	50 (64.1)	<0.001***	0.28 (0.16–0.48)	<0.001***	406 (91.4)	41 (73.2)	<0.001***	0.26 (0.13–0.50)	<0.001***
		No	57 (13.5)	28 (35.9)				38 (8.6)	15 (26.8)
	Leads a disciplined life	Yes	352 (83.4)	53 (67.9)	0.001**	0.42 (0.25–0.72)	0.002**	405 (91.2)	36 (64.3)	<0.001***	0.17 (0.09–0.33)	<0.001***
		No	70 (16.6)	25 (32.1)				39 (8.8)	20 (35.7)
	Eats a well-balanced diet	Yes	333 (78.9)	41 (52.6)	<0.001***	0.30 (0.18–0.49)	<0.001***	401 (90.3)	45 (80.4)	0.024*	0.44 (0.21–0.91)	0.027*
		No	89 (21.1)	37 (47.4)				43 (9.7)	11 (19.6)
	Receives regular health checkups	Yes	371 (87.9)	62 (79.5)	0.045*	0.53 (0.29–0.99)	0.047*	379 (85.4)	47 (83.9)	0.776	0.90 (0.42–1.92)	0.776
		No	51 (12.1)	16 (20.5)				65 (14.6)	9 (16.1)
	Walks and exercises	Yes	325 (77.0)	47 (60.3)	0.002**	0.45 (0.27–0.75)	0.002**	300 (67.6)	26 (46.4)	0.002**	0.42 (0.24–0.73)	0.002*
		No	97 (23.0)	31 (39.7)				144 (32.4)	30 (53.6)
	Participates in local activities	Yes	152 (36.0)	10 (12.8)	<0.001***	0.26 (0.13–0.52)	<0.001***	157 (35.4)	13 (23.2)	0.071	0.55 (0.29–1.06)	0.074
		No	270 (64.0)	68 (87.2)				287 (64.6)	43 (76.8)
	Keeps an uplifted state of mind as much as possible	Yes	330 (78.2)	38 (48.7)	<0.001***	0.27 (0.16–0.44)	<0.001***	386 (86.9)	37 (66.1)	<0.001***	0.29 (0.16–0.54)	<0.001***
		No	92 (21.8)	40 (51.3)				58 (13.1)	19 (33.9)
	Has a hobby	Yes	317 (75.1)	43 (55.1)	<0.001***	0.41 (0.25–0.67)	<0.001***	314 (70.7)	32 (57.1)	0.038*	0.55 (0.31–0.97)	0.040*
		No	105 (24.9)	35 (44.9)				130 (29.3)	24 (42.9)
	Goes out whenever possible	Yes	289 (68.5)	37 (47.4)	<0.001***	0.42 (0.26–0.68)	<0.001***	301 (67.8)	34 (60.7)	0.288	0.73 (0.41–1.30)	0.290
		No	133 (31.5)	41 (52.6)				143 (32.2)	22 (39.3)
Lifestyle	Current smoking habit	Yes	136 (32.2)	30 (38.5)	0.283	1.31 (0.80–2.17)	0.284	66 (14.9)	12 (21.4)	0.202	1.56 (0.78–3.11)	0.205
		No	286 (67.8)	48 (61.5)				378 (85.1)	44 (78.6)
	Weight gain of ≥10 kg since 20 years of age	Yes	143 (33.9)	39 (50.0)	0.007**	1.95 (1.20–3.18)	0.007**	99 (22.3)	16 (28.6)	0.293	1.39 (0.75–2.60)	0.295
		No	279 (66.1)	39 (50.0)				345 (77.7)	40 (71.4)
	Exercises to sweat lightly for ≥30 min a time, 2 times weekly, for over a year	Yes	156 (37.0)	14 (17.9)	0.001**	0.37 (0.20–0.69)	0.002**	103 (23.2)	6 (10.7)	0.033*	0.40 (0.17–0.95)	0.039*
		No	266 (63.0)	64 (82.1)				341 (76.8)	50 (89.3)
	Walking or physical activity of equivalent intensity for at least an hour a day in daily life	Yes	181 (42.9)	17 (21.8)	<0.001***	0.37 (0.21–0.66)	<0.001***	162 (36.5)	14 (25.0)	0.09	0.58 (0.31–1.10)	0.093
		No	241 (57.1)	61 (78.2)				282 (63.5)	42 (75.0)
	Walks faster than individuals of about the same age	Yes	247 (58.5)	34 (43.6)	0.015*	0.55 (0.34–0.89)	0.015*	225 (50.7)	30 (53.6)	0.683	1.12 (0.64–1.96)	0.683
		No	175 (41.5)	44 (56.4)				219 (49.3)	26 (46.4)
	Eating speed compared with others	Faster	189 (44.8)	36 (46.2)	0.001**	2.81 (1.37–5.79)	0.005**	172 (38.7)	23 (41.1)	<0.001***	3.15 (1.52–6.52)	0.002**
		Normal	205 (48.6)	27 (34.6)		4.07 (1.93–8.56)	<0.001***	234 (52.7)	17 (30.4)		5.80 (2.70-12.44)	<0.001***
		Slower	28 (6.6)	15 (19.2)		reference		38 (8.6)	16 (28.6)		reference
	Eats supper 2 hours before bedtime more than 3 times a week	Yes	139 (32.9)	31 (39.7)	0.244	1.34 (0.82–2.21)	0.245	108 (24.3)	17 (30.4)	0.326	1.36 (0.74–2.50)	0.327
		No	283 (67.1)	47 (60.3)				336 (75.7)	39 (69.6)
	Eats snacks or drinks sweet beverages between meals	Every day	99 (23.5)	22 (28.2)	0.518	0.64 (0.30–1.38)	0.255	191 (43.0)	20 (35.7)	0.313	1.84 (0.83–4.07)	0.131
		Sometimes	239 (56.6)	44 (56.4)		0.78 (0.39–1.54)	0.468	196 (44.1)	25 (44.6)		1.51 (0.70–3.26)	0.291
		Rarely eat	84 (19.9)	12 (15.4)		reference		57 (12.8)	11 (19.6)		reference
	Skips breakfast three or more times a week	Yes	96 (22.7)	20 (25.6)	0.578	1.17 (0.67–2.04)	0.579	88 (19.8)	13 (23.2)	0.551	1.22 (0.63–2.37)	0.552
		No	326 (77.3)	58 (74.4)				356 (80.2)	43 (76.8)
	Frequency of drinking alcohol	Every day	125 (29.6)	21 (26.9)	0.112	1.58 (0.85–2.94)	0.145	78 (17.6)	9 (16.1)	0.169	1.42 (0.65–3.13)	0.381
		Sometimes	188 (44.5)	28 (35.9)		1.79 (1.01-3.16)	0.046*	177 (39.9)	16 (28.6)		1.81 (0.96–3.43)	0.067
		Rarely drink	109 (25.8)	29 (37.2)		reference		189 (42.6)	31 (55.4)		reference
	Sufficiently rests through sleep	Yes	301 (71.3)	25 (32.1)	<0.001***	0.19 (0.11–0.32)	<0.001***	294 (66.2)	17 (30.4)	<0.001***	0.22 (0.12–0.41)	<0.001***
		No	121 (28.7)	53 (67.9)				150 (33.8)	39 (69.6)
WLB	Work-to-family negative spillovera		0.86±0.61	1.28±0.70	<0.001***	0.37 (0.25–0.54)	<0.001***	0.80±0.64	1.16±0.73	<0.001***	0.46 (0.31–0.69)	<0.001***
	Family-to-work negative spillovera		0.67±0.67	0.88±0.76	0.007**	0.66 (0.47–0.92)	0.015*	0.56±0.65	0.63±0.69	0.242	0.86 (0.57–1.29)	0.458
	Work-to-family positive spillovera		1.15±0.66	1.04±0.68	0.091	1.29 (0.89–1.88)	0.182	1.23±0.66	1.09±0.66	0.066	1.40 (0.90–2.15)	0.133
	Family-to-work positive spillovera		1.28±0.73	1.10±0.72	0.025*	1.40 (1.00-1.98)	0.051	1.32±0.72	1.24±0.71	0.215	1.17 (0.79–1.74)	0.432

Chi-square test ^a t-test

CI, confildence interval; OR, odds ratio.

*p<0.05, **p<0.01, ***p<0.001

Among the women, sigificant differences between the healthy and unhealthy groups were found for “gets enough sleep and rest,” “leads a disciplined life,” “eats a well-balanced diet,” “walks and exercises,” “keeps an uplifted state of mind as much as possible,” “has a hobby,” “exercises to sweat lightly for ≥30 min a time, 2 times weekly, for over a year,” “eating speed compared with others,” “sufficiently rests through sleep,” and “work-to-family negative spillover.”

Factors related to self-rated health in each gender

We found no highly correlated combinations of independent variables in this study. A separate logistic regression analysis was conducted for each gender to identify the variables correlated with self-rated health. Table 5 presents results of the logistic regression analysis according to the male members of the healthy and unhealthy groups. The model chi-square test results were significant (p<0.001), and the discrimination accuracy was 85.4%. A relationship was found with “marital status,” “walks and exercises,” “keeps an uplifted state of mind as much as possible,” “weight gain of ≥10 kg since 20 years of age,” “walking or physical activity of equivalent intensity for at least an hour a day in daily life,” “eating speed compared with others” “sufficiently rests through sleep,” and “work-to-family negative spillover.”

Table 5. Results of the multivariate logistic regression analysis according to the male members of the healthy and unhealthy groups

Variables	Partial regression coefficient	p-value	AOR	95% Confidence Interval
				Lower limit	Upper limit
Marital status	2.18	0.040	8.82	1.11	70.26
Walks and exercises	0.61	0.048	1.84	1.01	3.37
Keeps an uplifted state of mind as much as possible	0.74	0.013	2.10	1.17	3.75
Weight gain of ≥10kg since 20 years of age	−1.09	<0.001	0.34	0.19	0.6
Walking or physical activity of equivalent intensity for at least an hour a day in daily life	0.86	0.011	2.36	1.21	4.61
Eating speed compared with others: slower	−1.13	0.012	0.32	0.13	0.78
Sufficiently rests through sleep	1.28	<0.001	3.58	2.00	6.43
Work-to-family negative spillover	−0.87	<0.001	0.42	0.27	0.66
Constant	−0.855	0.046

n=500

AOR, adjusted odds ratio.

Forward selection (likelihood method)

Dependent variable: Self-rated health (0= unhealthy group, 1= healthy group)

Model χ²test p<0.001

Hosmer-Lemeshow test 2.818, df=8, p=0.945

Model hit rate 85.4%

 

Covariates

age (continuous variable), marital status (married = 1, unmarried = 0), time spent teleworking a day (continuous variable), time spent on housework and childcare a day (continuous variable), gets enough sleep and rest (yes = 1, no = 0), leads a disciplined life (yes = 1, no = 0), eats a well-balanced diet (yes = 1, no = 0), receives reglar health checkups (yes= 1, no=0), walks and exercises (yes = 1, no = 0), participates in local activities (yes = 1, no=0), keeps an uplifted state of mind as much as possible (yes = 1, no = 0), has a hobby (yes = 1, no = 0), goes out whenever possible (yes = 1, no = 0), weight gain of ≥10 kg since 20 years of age (yes = 1, no = 0), exercises to sweat lightly for ≥30 min a time, 2 times weekly, for over a year (yes =1 , no = 0), walking or physical activity of equivalent intensity for at least an hour a day in daily life (yes = 1, no = 0), walks faster than individuals of about the same age (yes = 1, no = 0), eating speed compared with others (faster = 0, normal = 1, faster = 0, slower = 1), sufficiently rests through sleep (yes = 1, no = 0), work-to-family negative spillover (continuous variable), family-to-work negative spillover (continuous variable), work-to-family positive spillover (continuous variable), family-to-work positive spillover (continuous variable)

Table 6 presents results of the logistic regression analysis according to the female members of the healthy and unhealthy groups. The model chi-square test results were significant (p<0.001), and the discrimination accuracy was 89.2%. A relationship was found in “leads a disciplined life,” “keeps an uplifted state of mind as much as possible,” “eating speed compared with others: slower,” and “sufficiently rests through sleep.”

Table 6. Results of the multivariate logistic regression analysis according to the female members of the healthy and unhealthy groups

Variables	Partial regression coefficient	p-value	AOR	95% Confidence Interval
				Lower limit	Upper limit
Leads a disciplined life	1.15	0.001	3.16	1.56	6.4
Keeps an uplifted state of mind as much as possible	0.87	0.013	2.38	1.2	4.73
Eating speed compared with others: slower	−0.93	0.023	0.39	0.18	0.88
Sufficiently rests through sleep	1.16	<0.001	3.18	1.68	6.02
Constant	−0.14	0.734

n=500

Forward selection (likelihood method)

AOR, adjusted odds ratio.

Dependent variable: self-rated health (0= unhealthy group, 1= healthy group)

Model χ²test p<0.001

Hosmer-Lemeshow test 1.159, df=6, p=0.979

Model hit rate 89.2%

 

Covariates

age (continuous variable), marital status (married = 1, unmarried = 0), time spent teleworking a day (continuous variable), time spent on housework and childcare a day (continuous variable), gets enough sleep and rest (yes = 1, no = 0), leads a disciplined life (yes = 1, no = 0), eats a well-balanced diet (yes = 1, no = 0), receives reglar health checkups (yes= 1, no=0), walks and exercises (yes = 1, no = 0), participates in local activities (yes = 1, no=0), keeps an uplifted state of mind as much as possible (yes = 1, no = 0), has a hobby (yes = 1, no = 0), goes out whenever possible (yes = 1, no = 0), weight gain of ≥10 kg since 20 years of age (yes = 1, no = 0), exercises to sweat lightly for ≥30 min a time, 2 times weekly, for over a year (yes =1 , no = 0), walking or physical activity of equivalent intensity for at least an hour a day in daily life (yes = 1, no = 0), walks faster than individuals of about the same age (yes = 1, no = 0), eating speed compared with others (faster = 0, normal = 1, faster = 0, slower = 1), sufficiently rests through sleep (yes = 1, no = 0), work-to-family negative spillover (continuous variable), family-to-work negative spillover (continuous variable), work-to-family positive spillover (continuous variable), family-to-work positive spillover (continuous variable)

Discussion

This study analyzed the results of a survey conducted in November 2021. During the survey, COVID-19 was wreaking havoc, and this increased the number of teleworkers because of restrictions on interpersonal contact and activities outside the home. In this study, the number of years of telework experience was <3 years in 896 (89.6%) individuals, and it is thought that the majority of them started telework because of COVID-19. Furthermore, the mean age was 39.13 (SD, 6.4) years, and 866 (86.6%) individuals considered themselves healthy. Thus, this result suggests that the participants were healthy men and women in their late thirties.

Gender differences in the lifestyle characteristics of teleworkers raising children

Our male and female study particpants spent 2.48 (SD, 1.8) and 4.94 (SD, 2.7) hours/day, respectively, on housework and childcare, with significantly longer hours for women. According to the Basic Survey on Social Life conducted by the Statistics Bureau, Ministry of Internal Affairs and Communications²³⁾, the time spent on housework was 49 minutes for married men and 4 hours and 55 minutes for women. The male teleworkers raising children spent approximately 2 hours longer on housework and childcare than the results of the Basic Survey of Social Life. This may be because telework makes it easier for men to become involved in housework and childcare, but there is still a gap with women’s housework and childcare time.

Significant differences were found in many items between men and women, and apart from “walks and exercises,” more women had healthy behavior. Regarding lifestyle, men predominantly had smoking habits, which was similar to the general trend. Compared with women, more men “exercises to sweat lightly for ≥30 minutes a time, two times weekly, for over a year,” and were mindful of exercise habits; however, a larger proportion of the men “eats supper 2 hours before bedtime more than three times a week,” which indicates irregular eating habits. Furthermore, there were more women than men in the healthy group, and this result is similar to the results of Hirai et al. for all generations²⁴⁾. Moreover, women are more likely to engage in healthy behavior and lifestyle than men, which may have led to a higher self-rated health in women.

Factors that affect self-rated health in men and women

In a 2005 study of Japanese men and women, items that were strongly related to self-rated health included “exercise habit,” “eating properly,” and “habitual drinking”²⁵⁾. As shown in Table 4, in this study, a significant difference was observed between the healthy and unhealthy groups for “leads a disciplined life,” “eats a well-balanced diet,” and “exercises to sweat lightly for ≥30 minutes a time, two times weekly, for over a year”; these items are unrelated to gender but related to self-rated health.

In the logistic regression analysis of the healthy and unhealthy groups, items that were common in men and women include “keeps an uplifted state of mind as much as possible,” “eating speed compared with others,” and “sufficiently rests through sleep.” However, no significant associations were found between health and the average teleworking hours or the average time spent on household chores and childcare. While teleworking hours appeared to have little effect on health status, this is probably because the average number of teleworking hours in the healthy group (6.69 [SD, 2.46] hours/day) and the unhealthy group (6.86 [SD, 2.70] hours/day) were very similar. Hence, a uniformity in teleworking hours prevented a significant association.

Items that were noted in men only were “marital status,” “walks and exercises,” “weight gain of ≥10 kg since 20 years of age,” “walking or physical activity of equivalent intensity for at least an hour a day in daily life,” and “work-to-family negative spillover.” The time spent sitting increased with telework^26,27). When teleworking, the level of physical activity decreased²⁸⁾, and human communication and other factors associated with going to work also decreased. Usually, the rate of habitual exercise is higher in middle-aged men than in women²⁹⁾, and for men, health might have also been maintained by “walks and exercises” and “walking or physical activity of equivalent intensity for at least an hour a day in daily life” which may compensate for the interpersonal relationships and habitual exercise that have been prevented by telework. The WLB was related to “work-to-family negative spillover” in men only. In previous studies, the relationship between self-rated health and WLB also differred according to gender^10,30). Thus, the results of the present study are similar to those of a study indicating a relationship between “work-to-family conflict” and self-rated health³¹⁾; however, with regard to telework, men readily bring negative work matters into the home, and switching between work and private life may be difficult.

For women, the item noted in women only was “leads a disciplined life.” Women usually maintain an appropriate weight and are health conscious³²⁾, and the weight gain item is thought to be inapplicable. For women raising children, telework enables them to change their work and life hours to suit their children’s and family’s living pace⁴⁾; however, it also includes the risk of leading an irregular lifestyle. For female teleworkers, a regular lifestyle is important for health management.

In this study, items related to self-rated health differed between men and women. In teleworkers raising children, men need to maintain connections with the local community and maintain physical activity and exercise for health management. For women, a disciplined lifestyle is necessary.

Study limitations

This study has several limitations. First, the participants were drawn from the registrants of a single internet survey company. This may have introduced bias or resulted in an unrepresentative sample. Second, the cross-sectional nature of the study prevents the inference of any causal relationships between health and the correlated variables. Third, the long-term health status of participants was unknown. Some members of the unhealthy group may have suffered from chronic conditions for a long time, with their poor health predating telework initiation and therefore unrelated to it. This possibility makes the relationship between telework and health a little less clear. Nevertheless, despite these limitations, the lack of previous studies that address gender differences in health and associated factors among teleworkers means that this study offers novel data and fills a knowledge gap. Future research should select participants from a broad range of sources and consider the effects of different types of telework on health status.

Conclusions

This study suggests that those aiming to provide health support to teleworkers can optimize participation and motivation by keeping in mind that physical activity and exercise are the most important contributors to self-perceived health in men, while self-discipline is the most important for women.

Acknowledgments

This work was supported by JSPS KAKENHI Grant Number JP20K02327.

Conflicts of interest

The authors declare that there are no conflicts of interest.

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