The Impact of Long Working Hours on Cognitive Function: A Follow-Up Study with Gender Stratification 1

Abstract

Background:

Recent studies have shown that long working hours can have adverse consequences on health and possibly trigger biological processes that mediate the relationship between long working hours and cognitive decline.

Objective:

To investigate whether long working hours and the overall duration such exposure is associated with a decline in cognitive function.

Methods:

Data obtained during the Korean Longitudinal Study on Aging (n = 2,518) during the period 2006–2018 were used to explore the relationship between long working hours and cognitive decline. Korean version of the Mini-Mental State Examination (K-MMSE) scores were used to evaluate cognitive function. Cox proportional hazard regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs), which were used to evaluate declines in K-MMSE scores over the 12-year study period.

Results:

Overall HR (95% CI) for a decline in cognitive function in long working hours group was 1.13 (0.73–1.17). When categorized by sex, women with long working hours had an HR (95% CI) of 1.50 (1.05–2.22), K-MMSE scores decreased significantly after working long hours for 5 years (p < 0.01).

Conclusion:

The study furthers understanding of the effects of long working hours on cognitive decline among female workers. Further research is required to determine the effects of long working hours on cognitive functions.

Keywords

Alzheimer’s disease cognitive screening test cohort study dementia epidemiology KLoSA long working hours workers

INTRODUCTION

Cognitive impairments including those associated with dementia and Alzheimer’s disease, which are progressive neurodegenerative brain disorders, represent major public health problems. Globally, the number of individuals living with dementia is estimated to be approximately 50 million, and this number has been predicted to double by 2030 and to reach more than 150 million by 2050. The glo-bal annual medical expenditure on dementia has in-creased by a trillion dollars [1].

Cognitive impairment is defined as a deterioration in intellectual ability and that progressive cognitive decline leads to an inability to work or participate in social activities. Although cognitive impairment is viewed as an important disorder, it is not clear whether modifiable risk factors (i.e., environmental and occupational risk factors) contribute to its etiology.

Increasing evidence suggests that occupational characteristics influence cognitive function. For example, studies have reported that occupational demands and types may be risk factors of cognitive impairment [2, 3], and that occupations with high physical but low mental demands are related to poor cognitive ability and a high prevalence of dementia [4]. Furthermore, when occupational types were coded dichotomously, workers in the ‘blue-collar’ category, which including unskilled workers, tradesmen, and agricultural workers, had a high risk of dementia [2]. Interestingly, cohort studies have reported shift work and shift work duration are associated with elevated risks of incident dementia [5, 6].

Jobs involving regular overtime working or long working hours are common and have become one of the most important occupational health issues [7]. A considerable amount of literature has been published on long working hours and their adverse consequences on health and well being. Some have reported long working hours are causally associated with risks of hypertension, cardiovascular disease, stroke, and obesity [8 –10] and with psychological stressors such as anxiety, depression, and sleep disturbance [11 –13].

These adverse health outcomes can induce biological mechanisms that mediate the relationship between long working hours and cognitive decline, for example, hypertension induces cerebral damage and adversely affects brain cell metabolism [14]. Psychological stress linked to long working hours can affect neuroendocrine systems and increase norepinephrine cortisol secretion [15], whereas sleep deprivation caused by long working hours leads to significant increases in the serum levels of inflammatory markers such as interleukin 6 and C-reactive protein [16], and chronic inflammation has been linked to memory loss and dementia [17]. Furthermore, it has also been suggested that reduced mela-tonin synthesis due to lack of exposure to sunlight reduces vitamin D, and thus, to melatonin synthesis and sleep deprivation.

Recent systematic reviews and studies on work-related factors and cognitive function have revealed little of the relationship between long working hours and cognitive dysfunction [18 –23]. Furthermore, in these studies working hours-dependent cognitive decline was treated as a single independent variable.

Therefore, the primary aim of this study was to determine whether cognitive decline is associated with long working hours and the duration of such working using data obtained during a national representative survey, that is the Korean Longitudinal Study of Aging (KLoSA) study, an ongoing study performed by the Korean Ministry of Labor from 2006.

METHODS

Data and study participants

As mentioned above, we used data from the KLoSA study conducted by the Korean Labor Institute and the Korean Employment Institute Information Service. The current analysis included 12-year follow-up data—the first to seventh (2006–2018) surveys of the KLoSA. The KLoSA study provides a national overview of aging and has been conducted since 2006 using a nationally representative sample of Koreans older than 45 years biannually and provides a wide range of information, for example, on demographics, socioeconomic characteristics, health status (medical, physical, and psychosocial), property (work, pensions, income, assets, and housing), performance (cognitive and physical), and relationships (social participation and networks). Computer-assisted personal interview methods are used to interview participants and related family members.

Study participant data are presented in Fig. 1. To determine the association between cognitive im-pairment and long working hours during the first survey (n = 10,273), we excluded those not employed (n = 6,313), those diagnosed with a cerebrovascular or mental disease before participating in KLoSA (n = 55), those who did not answer the Mini-Mental State Examination (Korean version) (K-MMSE) in 2006 or 2018, or those with missing data, and those that refused to participate (n = 1,387). Finally, a total of 2,518 workers were included in the analysis.

Fig. 1

Schematic diagram of participant recruitment.

KLoSA data were collected after obtaining written informed consent from all participants. Data were anonymized. All procedures involving human subjects were performed in accordance with the ethical guidelines issued by the Institutional Review Board (IRB) of Gil Medical Center, Gachon University (IRB no. GFIRB2019-172) and with the Helsinki declaration (1964) and its later amendments.

Cognitive function

Cognitive function was evaluated using the K-MMSE, which includes 11 items in 7 domains of cognitive functions, which include orientation (time and place), registration, attention and calculation, recall, language, and visual construction [24, 25]. Total K-MMSE scores range from 0 to 30, and a low score indicates poor cognitive function. Reported sensitivities of the K-MMSE for detecting dementia range from 0.70 to 0.83 [24]. We followed the conventional classification criteria for cognitive function, that is, K-MMSE scores of≥24 were classified as “normal”, scores of 18 to 23 as “mild cognitive impairment”, and scores≤17 as “severe cognitive impairment”. K-MMSE data obtained in 2006 and 2018 were used in the present study. Decline in cognitive function was defined as change from “Normal” in 2006 to “Mild or Severe cognitive impairment” in 2018 or from “Mild cognitive impairment” in 2006 to “Severe cognitive impairment” in 2018.

Working hours

Working hours were assessed using self-reported total number of hours worked per week based on responses to the question: “How many hours do you work at your job per week on average, including overtime but excluding mealtimes?” We defined long working hours based on previously reported Korean labor standards. The Korean Labor Standard Act allows for 40 hours per week with an extension of 12 hours per week, although weekly working hours can be extended by agreement between parties [26]. Previous studies have indicated that the risks of various diseases increase significantly when working hours exceed 60 hours per week [27 –29]. We divided working hours per week into two categories, namely, non-long working hours (≤60) and long working hours (> 60). We also categorized overall duration of long working hours as 0, 1∼5, or more than 5 years during follow-up periods.

Covariates

In the current study, age, sex, educational level, and marital status were used as demographic characteristics. Marital status was divided into two categories (married versus separated/divorced/or never married), and education level was categorized as middle school, high school, or college or higher. Chronic diseases addressed included obesity, hypertension, diabetes, elevated triglycerides, and decreased high density lipoprotein-cholesterol. Smoking, alcohol consumption, and amount of exercise were considered covariates of health-related behavior. Smoking status was categorized as never/past smoker or current smoker. Alcohol consumption was divided into two categories: regular alcohol consumption and none. Subjects that exercised more than twice per week were classified as individuals who exercised regularly. Occupational classifications were categorized into four groups based on the 10 major categories of the International Standard Classifications of Occupations, as follows; white-collar workers (managers, professionals, technicians, and associate professionals), pink collar workers (clerical support, service, and sales workers), green-collar workers (skilled agricultural, forestry, and fishery workers), and blue-collar workers (crafts and related trades, plant and machine operators, assembly workers, and elementary occupations) [30].

Statistical analysis

Gender differences were observed for working conditions and cognitive functions, and thus, the analysis was conducted with gender stratification. Baseline characteristics in 2006 were estimated using a chi-square test according to long working hours. The hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox proportional hazard regression models to evaluate the association between cognitive declines over the 12-year study period and long working hours. Changes in K-MMSE mean score according to working hours from 2006 to 2018 were also calculated. The analysis was performed using SAS version 9.6 (SAS Institute, Cary, NC, USA). Two-tailed p-values of < 0.05 were considered to indicate statistical significance.

RESULTS

The baseline characteristics of those that participated in KLoSA are summarized in Table 1. The total number of participants was 2,518:1,579 (62.5%) males and 945 (37.55%) females. Most variables including age, sex, educational level, marital status, alcohol consumption, regular exercise, and occupational classification were significantly different in the long and non-long working hour groups. Five hundred and thirty-three (21.2%) participants were assigned to the long working hour group: 286 males and 247 females. K-MMSE scores show that 200 (7.9%) of the participants (long working hours: 53 and non-long working hours: 147) had mild cognitive impairment and that 34 (1.4%) (long working hours: 8 and non-long working hours: 26) had severe cognitive impairment.

Table 1

The baseline characteristics of study participants of the Korean Longitudinal Study on Aging according to weekly working hours, 2006

	Total, n (%)	Weekly working hours (> 60 h)		p
		No, n (%)	Yes, n (%)
Total participants	2,518 (100.0)	1,985 (78.8)	533 (21.2)	< 0.01
Male	1,573 (62.5)	1,287 (81.8)	286 (18.2)
Female	945 (37.5)	698 (73.9)	247 (26.1)
Age (y)				0.01
45–55	1,322 (52.5)	1,066 (80.6)	256 (19.4)
55–65	809 (32.1)	628 (77.6)	181 (22.4)
≥65	387 (15.4)	291 (75.2)	96 (24.8)
Educational level				< 0.01
Middle school	1,271 (50.5)	956 (75.2)	315 (24.8)
High school	898 (35.7)	716 (79.7)	182 (20.3)
College and more	349 (13.8)	313 (89.7)	36 (10.3)
Marital status				< 0.01
Married	2,278 (90.5)	1,812 (79.5)	466 (20.5)
Separated or divorced or never married	240 (9.5)	173 (72.1)	67 (27.9)
Number of chronic diseases				0.669
0	1,690 (67.1)	1,324 (78.3)	366 (21.7)
1	604 (24.0)	487 (80.6)	117 (19.4)
≥2	224 (8.9)	174 (77.7)	50 (22.3)
Smoking				0.06
Never or past	1,802 (71.6)	1,404 (77.9)	398 (22.1)
Current	716 (28.4)	581 (81.2)	135 (18.8)
Drinking				0.02
No	996 (39.6)	762 (76.5)	234 (23.5)
Yes	1,522 (60.4)	1,223 (80.4)	299 (19.6)
Regular exercise				< 0.01
No	1,614 (64.1)	1,237 (76.6)	377 (23.4)
Yes	904 (35.9)	748 (82.7)	156 (17.3)
Occupational classification				0.07
White collar	433 (17.2)	395 (91.2)	38 (8.8)
Pink collar	577 (22.9)	365 (63.3)	212 (36.7)
Green collar	386 (15.3)	280 (72.5)	106 (27.5)
Blue collar	1,122 (44.6)	945 (84.2)	177 (15.8)
K-MMSE score				0.09
Normal (≥24)	2,284 (90.7)	1,812 (79.3)	472 (20.7)
Mild cognitive impairment (18–23)	200 (7.9)	147 (73.5)	53 (26.5)
Severe cognitive impairment (≤17)	34 (1.4)	26 (76.5)	8 (23.5)

K-MMSE, The Korean version of the Mini-mental state examination. The Chi-square test was used to determine the significances of gender-associated differences. Statistical significance was accepted for p values < 0.05.

Table 2 presents Cox proportional hazard regression results for the risk of cognitive decline after 12 years of follow-up. The overall HR for the risk of cognitive decline was 1.13 (95% CI 0.73–1.17). When by sex, women had a higher HR than men (1.50 (95% CI 1.05–2.22) versus 0.86 (95% CI 0.60–1.24). Cox proportional hazard regression results for the risk of cognitive decline with respect to weekly working hours (> 40, > 45, > 50, > 55, > 60, and > 65) by gender are provided in Supplementary Table 1.

Table 2

Results of Cox proportional hazard regression analysis of working hours associated risks of cognitive decline after a 12-year follow-up

	Decline to cognitive function,
	Hazard ratios (95% CI) [cases]
	Non-long working hours	Long working hours
Total participants [422]	1.00 (reference) [316]	1.13 (0.73–1.17) [106]
Male [244]	1.00 (reference) [197]	0.86 (0.60–1.24) [47]
Female [178]	1.00 (reference) [119]	1.50 (1.05–2.22) [59]

All models were adjusted for age, educational level, marital status, chronic diseases, smoking status, drinking, exercise level, and occupational classification. Decline in cognitive function was defined as change from “Normal (K-MMSE≥24)” in 2006 to “Mild (18≤K-MMSE≤23) or Severe cognitive impairment (K-MMSE≤17)” in 2018 or from “Mild cognitive impairment (18≤K-MMSE≤23)” in 2006 to “Severe cognitive impairment (K-MMSE≤17)” in 2018.

Table 3 shows linear regression results for relations between K-MMSE scores and weekly working hours (> 40). Notably, a significant working hour associated decrease in K-MMSE scores was observed in women (B = –0.0332, p = 0.0157).

Table 3

Results of linear regression analysis of the relation between K-MMSE scores and weekly working hours

K-MMSE	Weekly working hours (> 40)
	B (SE)	p
Total participants	–0.0111 (0.0086)	0.1956
Male	0.0048 (0.0109)	0.6640
Female	–0.0332 (0.0137)	0.0157

B, effect value, SE, standard error. All models adjusted for age, educational level, marital status, chronic diseases, smoking status, drinking, exercise level, and occupational classification.

Fig. 2

Average change in mean K-MMSE scores according to duration of long working hours working over the 12-year follow-up period K-MMSE scores of≥24 were classified as “normal”, scores of 18 to 23 as “mild cognitive impairment”, and scores≤17 as “severe cognitive impairment”.

Average changes in mean K-MMSE scores according to long working hours during the 12-year follow-up are summarized in Fig. 2. Slight differences in mean K-MMSE scores between none and 1–5 years of experience of long working hours were observed for both genders. However, this decrease was significant for women (p for trend < 0.01) and marginally only significant for men (p for trend = 0.53).

DISCUSSION

This study was undertaken to assess the association between long working hours and their overall duration and decline in cognitive function. No association was detected between long work hours and cognitive decline among all participants or male participants. However, cognitive impairment did increase significantly among women. Furthermore, significant longitudinal changes in K-MMSE scores were observed among women that worked long hour, and the strength of this association was not attenuated after adjusting for various covariates.

Relatively few studies have addressed the relationship between cognitive impairment and long working hours in workers, and published results are inconsistent. Previous studies reported a significant association between long working hours and cognitive decline [21, 22], whereas Nabe-Nielsen et al. found no notable association between long working hours and the incidence of dementia among male workers [23]. In the present study, we included both male and female workers, and thus, were able to stratify results by gender.

Our results indicated that cognitive function is closely related with long working hours. A recent study investigated the roles that environmental factors play in diseases associated with cognitive decline [31] and reported that acquired lifestyle might prevent or trigger the development of cognitive impairment and that working conditions could be a key lifestyle factor.

The observed increases in risk of cognitive decline observed might be due to chronic psychosocial stress and sleep deprivation. Unfavorable life environments such as chronic stress or sleep deprivation caused by overtime might be linked with the overproduction of amyloid-β in plaques and misfolded tau protein in neurofibrillary tangles. According to an in vivo study on the mechanism responsible for the effect of chronic psychosocial stress on amyloid-β accumulation, amyloid-β production was induced by chronic stress in mice and exacerbated cognitive impairment [32]. Several studies have demonstrated that chronic sleep deprivation and poor sleep quality increase the amyloid-β and insoluble tau protein levels in brains [33 –36]. These findings suggest long working hours modulate the pathologies of neurodegenerative disorders through intermediate mechanisms.

This study supports evidence presented in a previous review that the risk of cognitive impairment is more pronounced in women [37]. Similarly, in a previous study, psychosocial and physical work factors, including working conditions, were found to be more closely linked to mental health problems in female workers [38]. Our findings also indicate that long working hours have a greater effect on cognitive dysfunction in women, which suggests men and women perceive and respond differently to work demands, which concurs with recent reviews and a meta-analysis on the effects of long working hours on mental impairment, in which it was concluded that these effects are often greater for women [19 , 40].

Long working hours have adverse effects on worker health and safety. According to Heinrich’s domino theory sequential accidents caused by unsafe or erratic human behavior in the presence of physical hazards result in preventable occupational injuries or loss [41]. Cognitive dysfunction leads to errors in simple tasks, and neurocognitive decline caused by extended working schedules increases the risks of unintentional occupational injuries and errors [42, 43].

Much progress has been made in establishing statutory restrictions on working hours. However, according to the Organization for Economic Cooperation and Development, South Korea ranks second to Mexico in terms of working hours [44], although the South Korean government introduced 40-hour-week legislation to reduce working hours in 2004. Studies have yet to reveal the impact of long working hours on cognitive function in South Korean workers.

In the present study, we investigated the relationship between long working hours and cognitive function decline in South Korean workers. Because long working hours are a modifiable factor, it is essential efforts be made to protect workers from their adverse health effects.

The findings of the present study importantly contribute to the association between long working hours and cognitive impairment. Nonetheless, reliance on KLoSA data introduces limitations. First, KLoSA is performed on the South Korean population, which restricts generalizations of our findings [45]. Second, MMSE scores do not provide the most efficient or accurate indicator of the presence or the severities of cognitive disorders [46]. However, this tool is commonly used for assessing cognitive disorders and is considered a valid benchmark [47]. Moreover, it has been reported cognitive disorders like Alzheimer’s disease, are affected by genetic as well as environmental factors [48], and in the present study, lack of data prevented our addressing genetic factors associated with cognitive impairment. Further basic and clinical research studies are required to investigate these issues. In addition, little is known of the mechanism by which long working hours lead to cognitive dysfunction, and thus, experimental, clinical, and epidemiological studies are needed to investigate the link between the two.

Summarizing, this study enhances understanding of the effects of long working hours on cognitive function decline in South Korean workers and shows that long working hours have a greater effect on female workers. Further proactive strategies are needed to prevent institutional reliance on long working hours, and clinical and epidemiological longitudinal studies are required to further investigate the topic.

Footnotes

ACKNOWLEDGMENTS

The authors thank all that participate in the KLoSA for the opportunity to perform this research.

Authors’ disclosures available online ().

The supplementary material is available in the electronic version of this article: .

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