Association Between Postacute Sequelae of COVID-19 Infection and Work Environment in a Semiconductor Packaging Plant in Taiwan

Night shift work and prolonged medical treatment were positively associated with postacute sequelae of COVID-19 (PASC). Female gender, night shift work, and medical treatment for >14 days were positively associated with subacute COVID-19 symptoms. On-site work environment and regular exercise were negatively associated with subacute COVID-19 and PASC, respectively.

Abstract

Objective

This study investigated the associations of lifestyle, work environment, and health status with subacute COVID-19 symptoms or postacute sequelae of COVID-19 (PASC).

Methods

The questionnaire was used to collect data on lifestyles, work environment, health status, and coronavirus infection history and sequelae symptoms in a semiconductor packaging plant workers in Taiwan. Univariate and multiple logistic regression analyses were performed to identify the factors associated with the risks of subacute COVID-19 and PASC.

Results

This study included 333 subjects, with an average age of 37.6 years. Multivariate logistic regression analysis indicated that night shift work, exercise habit, and prolonged treatment were significant independent predictors of PASC.

Conclusions

Night shift work and prolonged medical treatment were positively associated with PASC, and exercise was negatively associated with PASC. Optimizing work environments and shift schedules can reduce PASC risk.

LEARNING OUTCOMES

• Estimate the associations of lifestyle, work environment, and health status with subacute COVID-19 symptoms or postacute sequelae of COVID-19 (PASC) in individuals with COVID-19 in a semiconductor packaging plant in Taiwan.

• Understand that night shift work and prolonged medical treatment were positively associated with PASC development.

• Summarize that female gender, night shift work, and medical treatment for >14 days were positively associated with the development of subacute COVID-19 symptoms.

• Identify that the on-site work environment was negatively associated with subacute COVID-19 symptoms, and regular exercise was negatively associated with PASC.

After the first case of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection was reported in Wuhan, China, in December 2019, coronavirus disease 2019 (COVID-19) spread rapidly worldwide, leading to a severe pandemic. On March 11, 2020, World Health Organization (WHO) officially declared the COVID-19 outbreak caused by SARS-CoV-2 as a global pandemic. The global outbreak of COVID-19 strongly affected various industries and changed human life. As of February 2024, the cumulative number of confirmed COVID-19 cases worldwide was reported to be 770 million, with 7 million deaths.¹

COVID-19 infection is an atypical pneumonia and respiratory syndrome caused by a highly contagious and rapidly mutating coronavirus. The common symptoms of COVID-19 infection include respiratory symptoms, fever, and gastrointestinal symptoms. The severity of these symptoms varies, with most people experiencing mild to moderate symptoms and recovering within 2 weeks. However, individuals with severe symptoms require 3 to 6 weeks to recover, and some may be asymptomatic carriers.² More than 100 post–COVID-19 symptoms have been reported, with the most common ones being fatigue, difficulty breathing, chest pain, changes in smell and taste, and cognitive impairment.³

In the early stage of the pandemic, reducing the mortality and morbidity rates was the primary focus, and preventive strategies and vaccination were implemented to boost immunity in populations. Because vaccination has reduced the severity of COVID-19 symptoms, researchers are currently studying the potential long-term symptoms and diseases that can occur after acute COVID-19 infection.⁴ Expanding the scope of research can yield comprehensive insights into the long-term effects of COVID-19 infection.

An increasing number of studies have demonstrated that, in addition to acute symptoms, postacute sequelae of COVID-19 (PASC), also referred to as post–COVID-19 syndrome or long COVID, can occur in patients after their recovery from COVID-19 infection. These symptoms may persist for weeks or even months.^4,5 The symptoms of PASC include fatigue, insomnia, dyspnea on exertion, and even cardiac dysfunction and brain fog.^5,6 Recent studies have indicated that PASC risk is associated with factors such as gender, severity of COVID-19 infection, vaccination, age, and occupation.^4,7 However, the influence of work environment on the risk of PASC remains unclear. Therefore, this study evaluated the effects of occupational health and working conditions on the symptoms and risk of PASC.

METHODS

Study Design

This cross-sectional study was conducted at a semiconductor packaging company in southern Taiwan that had a workforce of 3027 employees aged 18 to 65 years. All participants were informed regarding the study's purpose, participated in interviews, and provided informed consent. The collection, processing, and storage of data were conducted in adherence to the ethical standards of the Declaration of Helsinki, and all precautions were taken to ensure participants' confidentiality. This study was approved by the Ethics Committee of Chang Gung Memorial Hospital (IRB number, 202400966B0).

This article is reported according to the STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) guidelines, which can be found in Supplementary Digital Content (Supplementary Data 1, http://links.lww.com/JOM/B992).

An anonymous survey was conducted. Employees were included if they had received a diagnosis of COVID-19 infection and were aged 18 to 65 years. The questionnaire was distributed from April to June 2023. Of 350 questionnaires distributed, 343 were returned. Of these, 10 questionnaires were excluded due to incomplete information. Thus, 333 questionnaires remained for final analysis (Fig. 1). The questionnaire encompassed the following sections:

FIGURE 1.

Flowchart of subjects screening process.

1. Demographic information: Gender, age, body mass index (BMI), marital status, education level, department, work shift, and work experience

2. Lifestyle and health Status: Smoking, alcohol consumption, betel nut chewing, exercise habit, meal timing, sleep pattern, and chronic diseases

3. COVID-19 infection history: Date of COVID-19 diagnosis, hospitalization status, and vaccination history. Vaccination details, including the number of doses received and PASC symptoms before and after vaccination, were also documented.

Outcome Measurement

We categorized post-COVID symptoms into acute (0–4 weeks), subacute (4–12 weeks), or ongoing. Ongoing post-COVID symptoms were defined as symptoms and abnormalities occurring within the 4 to 12 weeks following acute COVID-19 infection.⁸ Long COVID-19 syndrome (i.e., PASC) was defined as persistent or recurring symptoms and abnormalities lasting longer than 12 weeks after acute COVID-19 infection and that were not attributable to other diagnoses.⁹ The questionnaire was used to collect data on symptoms in various systems, including the respiratory, cardiovascular, gastrointestinal, neurological, psychological, ocular, musculoskeletal, dermatological, hair-related, and reproductive systems. The participants were asked to evaluate any new symptoms that arose following acute COVID-19 infection. They were also asked whether they suspected they had PASC and whether they had sought treatment for PASC symptoms or received a formal diagnosis for their persistent post-COVID symptoms.

Symptom severity was assessed on a four-point scale, ranging from “no symptoms” to “severe symptoms.” On the basis of symptom occurrence, the participants were categorized into five groups: an asymptomatic group and four groups whose symptoms presented before diagnosis and within the 1 month after diagnosis, 1 to 3 months after diagnosis, and 3 or more months after diagnosis. Corresponding scores were assigned to each category, with higher scores indicating a longer duration of PASC symptoms.

Statistical Analysis

Continuous variables are presented as the mean ± standard deviation (SD). The independent t test and Mann-Whitney test were used to examine between-group differences in the distributions of continuous variables. The χ² test was employed to assess intergroup differences in the distributions of categorical variables. Logistic regression was used to examine the potential associations of factors such as gender, BMI, age, department, work shift, and work environment with the risk of PASC. Initially, univariate analysis was conducted to identify potential confounders. Subsequently, a multivariate logistic regression model accounting for confounders was conducted. Odds ratios (ORs) with corresponding 95% confidence intervals (CIs) and P values were calculated. All statistical analyses were conducted using SPSS software, version 25.0 (IBM Corp., Armonk, NY) and JMP software (version 10.0; SAS Institute Inc., Cary, NC).

RESULTS

Demographic Characteristics of Participants

Table 1 presents the demographic characteristics of the study participants. This study enrolled 333 participants, 172 (51.7%) of whom were male. Regarding BMI, 116 individuals (34.8%) were classified as being overweight or obese (BMI, ≥25 kg/m²). The majority of the participants were young to middle-aged (<40 years; n = 198, 59.5%). In terms of their department, most participants (n = 260, 78.1%) were engaged in an on-site role (manufacturing or equipment). Regarding work shifts, 192 participants (57.7%) were assigned to rotating or night shifts (working times of 19:30–07:30). A total of 208 participants (62.4%) reported sleeping ≥7 hours per night, and 290 participants (87.1%) had received three or more COVID-19 vaccine doses. Additionally, 29 participants (8.8%) reported a history of chronic diseases, such as diabetes, heart disease, hypertension, cancer, chronic respiratory disease, or kidney disease.

TABLE 1.

Demographic Characteristics of Study Participants

Characteristic	Category	Total Sample (n = 333, %)
Sex	Male	172 (51.7)
	Female	161 (48.3)
BMI (kg/m2)	≥25	116 (34.8)
	<25	217 (65.2)
Age	<40 y	198 (59.5)
	≥40 y	135 (40.5)
Marital status	Single	154 (46.2)
	Married	167 (50.1)
	Divorced	9 (2.7)
	Widowed	3 (1.0)
Education level	Junior high school or below	6 (1.8)
	High school/vocational	115 (34.5)
	University/college	183 (54.7)
	Graduate school or above	30 (9.0)
Department	On-site (manufacturing or equipment)	260 (78.1)
	Administration (facilities or logistics)	73 (21.9)
Work experience (y)	<1	15 (4.6)
	1–5	78 (23.4)
	6–10	96 (28.8)
	11–20	87 (26.1)
	>20	57 (17.1)
Shift work	Night shift	46 (13.8)
	Fixed day shift	197 (59.2)
	Rotating shift	90 (27.0)
Work environment	Clean room	259 (77.8)
Vaccination status	Not vaccinated	6 (1.8)
	1 Dose	2 (0.6)
	2 Doses	35 (10.5)
	≥3 Doses	290 (87.1)
Lifestyle
	Current smoker	63 (18.9)
	Alcohol consumption	31 (9.4)
	Exercise habit
	None (<1 time/week)	221 (66.4)
	Sometimes (1–2 times/week)	90 (27.0)
	Often (≥3 times/week)	22 (6.6)
	Sleeping ≥7 h	208 (62.4)
	Comorbidity	29 (8.8)
	Prolonged medical treatment (≥14 d)	63 (18.9)

Distribution and Comparison of Variables During Subacute Phase and PASC

Of the participants, 310 (93.1%) experienced acute COVID-19 symptoms (<4 weeks), 82 (24.6%) reported subacute COVID-19 symptoms (4–12 weeks), and 48 (14.4%) developed PASC symptoms (>12 weeks). Table 2 presents a summary of the demographic characteristics of the participants with subacute COVID-19 symptoms and PASC. Subacute COVID-19 symptoms were significantly associated with female gender (P < 0.001), age <40 years (P = 0.033), not being engaged in an on-site role (P < 0.001), night shift work (P = 0.014), non-cleanroom work environment (P = 0.001), and prolonged medical treatment (≥14 days; P < 0.001). The individuals who developed PASC were more likely to be female (P = 0.034), work night shifts (P < 0.001), lack a regular exercise habit (P = 0.036), sleep <7 hours per night (P = 0.004), receive fewer than three vaccine doses (P = 0.025), and be under prolonged medical treatment (≥14 days; P < 0.001).

TABLE 2.

Distribution and Comparison of Variables During Subacute Phase (4–12 Weeks) and PASC (>12 Weeks)

Parameters	Subacute Phase(n = 82, %)	P Value	PASC(n = 48, %)	P Value
Male sex	26 (31.7)	<0.001	18 (37.5)	0.034
BMI ≥25 kg/m2	25 (30.5)	0.457	17 (35.4)	0.927
Age >40 y	25 (30.5)	0.033	23 (47.9)	0.261
On-site work environment	52 (63.4)	<0.001	41 (85.4)	0.184
Night or rotating shift	20 (24.4)	0.014	17 (35.4)	<0.001
Vaccination (≥3 doses)	73 (89.0)	0.547	37 (77.1)	0.025
Clean room	53 (64.6)	0.001	40 (83.3)	0.317
Current smoker	17 (20.7)	0.233	7 (14.6)	0.687
Alcohol drinking (≥12 drinks/year)	5 (6.1)	0.249	3 (6.3)	0.43
Exercise habit	27 (32.9)	0.166	7 (14.6)	0.036
Sleeping ≥7 h	52 (63.4)	0.837	21 (43.8)	0.004
Comorbidity	4 (4.9)	0.156	5 (10.4)	0.206
Prolonged medical treatment (≥14 d)	34 (41.5)	<0.001	23 (47.9)	<0.001

BMI, body mass index.

Subacute COVID-19 Symptoms and PASC

Table 3 lists the symptoms of subacute COVID-19 and PASC. Respiratory symptoms were the most prevalent subacute COVID-19 symptoms, accounting for 48.8% of these symptoms, followed by perceived functional symptoms (43.9%) and neurological symptoms (26.8%). Similarly, among participants with PASC, respiratory symptoms were the most common, accounting for 50% of all reported PASC symptoms, followed by musculoskeletal symptoms (20.8%), perceived functional symptoms (18.8%), and psychological symptoms (18.8%).

TABLE 3.

Symptoms of Subacute COVID-19 and PASC

	Subacute COVID-19 Symptoms (n = 82)		PASC Symptoms (n = 48)
Symptoms	Counts	% of Symptomatic Individuals	Counts	% of Symptomatic Individuals
Respiratory symptoms	40	48.8	24	50
Cardiovascular symptoms	12	14.6	4	8.3
Gastrointestinal symptoms	10	12.2	6	12.5
Ear, nose, and throat symptoms	12	14.6	3	6.3
Neurological symptoms	22	26.8	3	6.3
Perceived functional symptoms	36	43.9	9	18.8
Psychological symptoms	11	13.4	9	18.8
Eye symptoms	3	3.7	7	14.6
Musculoskeletal symptoms	13	15.9	10	20.8
Skin-related symptoms	4	4.9	6	12.5
Hair-related symptoms	4	4.9	3	6.3
Other fatigue symptoms	21	25.6	6	12.5

Predictors of Subacute COVID-19 Symptoms

Table 4 presents the results of univariate and multivariate logistic regression analyses of the predictors of subacute COVID-19 symptoms. After adjustment for confounders, the analyses revealed that female gender (OR, 4.3; 95% CI, 2.18–8.94), on-site work environment (OR, 0; 95% CI, 0–0.62), night shift work (OR, 3.2; 95% CI, 1.41–7.24), alcohol consumption (OR, 0.26; 95% CI, 0.06–0.91), comorbidities (OR, 0.28; 95% CI, 0.06–0.92), and prolonged medical treatment (OR, 5.42; 95% CI, 2.72–11.07) were significantly associated with subacute COVID-19 symptoms.

TABLE 4.

Odds Ratios for Predictors of Subacute COVID-19 Symptoms

	Univariate Analysis		Multivariate Analysis
	Unadjusted	P Value	Adjusted	P Value
			OR (95% CI)		OR (95% CI)
Female	2.99 (1.78–5.14)	<0.001*	4.30 (2.18–8.94)	<0.001*
BMI ≥25 kg/m2	0.77 (0.45–1.31)	0.338	0.82 (0.42–1.56)	0.555
Age >40 y	0.56 (0.33–0.95)	0.031*	0.54 (0.28–1.01)	0.053
On-site work environment	0.36 (0.21–0.63)	<0.001*	0 (0–0.62)	0.023*
Night shift	2.79 (1.45–5.32)	0.002*	3.20 (1.41–7.24)	0.005*
Clean room	0.40 (0.23–0.70)	0.001*	—	0.168
Smoker	1.17 (0.61–2.14)	0.632	2.17 (0.91–5.20)	0.081
Alcohol consumption (≥12 drinks/year)	0.56 (0.19–1.40)	0.229	0.26 (0.06–0.91)	0.034*
Exercise habit	0.96 (0.56–1.62)	0.876	0.74 (0.38–1.40)	0.366
Sleeping >7 h	1.06 (0.63–1.78)	0.837	1.40 (0.73–2.74)	0.308
Comorbidity	0.46 (0.13–1.24)	0.134	0.28 (0.06–0.92)	0.035*
Vaccination (≥3 doses)	0.19 (0.04–0.78)	0.022*	1.0 (0.40–2.74)	0.998
Prolonged medical treatment (≥14 d)	5.42 (3.03–9.81)	<0.001*	5.42 (2.72–11.07)	<0.001*

*Statistically significant (P < 0.05). Multivariate logistic regression model accounting for confounders, including gender, BMI, age, department, work shift, and work environment with the risk of subacute COVID-19 symptoms was conducted.

Predictors of PASC

Table 5 presents the results of univariate and multivariate logistic regression analyses of the predictors of PASC. After adjustment for confounders, the analyses indicated that night shift work (OR, 4.41; 95% CI, 1.79–10.93), exercise habit (OR, 0.36; 95% CI, 0.13–0.85), and prolonged medical treatment (OR, 4.31; 95% CI, 2.03–9.16) were significantly associated with PASC.

TABLE 5.

Odds Ratios for Predictors of PASC

	Univariate Analysis		Multivariate Analysis
	Unadjusted	P Value	Adjusted	P Value
			OR (95% CI)		OR (95% CI)
Female	1.96 (1.05–3.73)	0.0334*	2.05 (0.96–4.51)	0.0606
BMI ≥25 kg/m 2	1.03 (0.53–1.93)	0.9272	1.04 (0.48–2.18)	0.9182
Age >40 y	1.42 (0.77–2.63)	0.2636	1.23 (0.59–2.53)	0.5753
On-site department	1.77 (0.80–4.47)	0.1669	12.82 (0.47–381.41)	0.1176
Night shift	4.84 (2.37–9.77)	<0.0001*	4.41 (1.79–10.93)	0.0014*
Clean room environment	1.51 (0.70–3.6)	0.3033	0.09 (0–2.26)	0.1257
Current smoker	0.70 (0.27–1.55)	0.3943	0.62 (0.18–1.87)	0.405
Alcohol consumption	0.61 (0.14–1.82)	0.4084	1.28 (0.25–5.11)	0.7451
Exercise habit	0.29 (0.12–0.64)	0.0013*	0.36 (0.13–0.85)	0.0190*
Sleeping >7 h	0.41 (0.22–0.76)	0.0044*	0.58 (0.27–1.20)	0.1394
Comorbidity	1.26 (0.41–3.25)	0.6575	1.51 (0.41–4.72)	0.5103
Vaccination (≥3 doses)	0.27 (0.06–1.34)	0.1017	0.18 (0.03–1.07)	0.058
Prolonged medical treatment (≥14 d)	5.64 (2.92–10.92)	<0.0001*	4.31 (2.03–9.16)	0.0002*

*Statistically significant (P < 0.05). Multivariate logistic regression model accounting for confounders, including gender, BMI, age, department, work shift, and work environment with the risk of PASC was conducted.

DISCUSSION

This study found that female gender, night shift work, and prolonged medical treatment were positively associated with subacute COVID-19 symptoms. Night shift work and prolonged medical treatment were positively associated with PASC. By contrast, the on-site work environment was negatively associated with subacute COVID-19 symptoms, and regular exercise (≥3 times per week) was negatively associated with PASC. Our findings confirm the relationships of work environment and shift work with PASC.

The mechanisms underlying the development of PASC remain incompletely understood. However, the mechanisms may involve persistent inflammatory responses, autoimmune reactions, viral persistence, and long-term organ damage. Chronic immune activation and inflammation may contribute to the development of symptoms such as fatigue, muscle and joint pain, and brain fog.¹⁰ Additionally, viral remnants in the body may lead to sustained activation of the immune system, resulting in chronic symptoms such as persistent inflammation and autoimmune responses. One study demonstrated that certain biomarkers, such as C-reactive protein and D-dimer, remain elevated long after acute infection in patients with PASC, indicating persistent inflammation.¹¹ This persistent inflammation is likely a key contributor to PASC symptoms. Furthermore, the virus may directly damage the nervous system, resulting in cognitive impairment and other neurological symptoms.¹⁰ PASC symptoms also include microvascular injury and endothelial dysfunction. Research indicates that patients with PASC may experience long-term impairments, including microvascular injury and endothelial function, which may explain symptoms of chronic fatigue and cardiovascular manifestations.⁸ Additionally, localized inflammation and tissue damage caused by viral persistence in certain organs such as the lungs or in the nervous system may exacerbate PASC symptoms and prolong disease.¹⁰ Work environment and job pattern may influence immune function and PASC occurrence. Limited studies have highlighted the potential influence of occupational factors on the risk of PASC. For example, Shukla et al. analyzed data from 206 healthcare workers with PASC, and they found that doctors exhibited a lower risk of PASC than did other healthcare workers.⁷ However, the current study is the first to compare the effects of different work environments and shift patterns on the risk of PASC. Our findings suggest that night shift work is associated with higher risks of subacute COVID-19 symptoms and PASC, with ORs of 3.2 and 4.4, respectively. Night shift work may affect regulation of the immune system, leading to adverse health outcomes. Research has demonstrated that night shift work disrupts the circadian clock, which regulates various cellular processes such as metabolic homeostasis and innate immunity.¹² Consequently, night shift work has been linked to the development of several immune and metabolic diseases, such as cancer, infection, and cardiovascular diseases.¹³ Additionally, a recent study found that night shift work may influence the methylation of genes regulating immunity, such as ERVFRD-1 and HERV-L, potentially altering immune function.¹⁴ Moreover, compared with day shift workers, night shift workers tend to have a shorter sleep duration, which may lead to immune dysregulation. One study found decreased levels of total lymphocytes and fewer T-helper cells in night shift workers, potentially compromising immune function and increasing the risk of PASC.¹⁵

The acute phase of SARS-CoV-2 infection typically lasts several weeks; the duration and severity of acute infection vary depending on the patient's age, underlying health conditions, and viral load. Most patients recover within 2 to 6 weeks, although recovery may take longer for those who experience severe illness or require hospitalization.¹⁶ The time needed to recover from acute infection is also influenced by the patient's immune function and the treatment strategies implemented.¹⁶ By contrast, the course of PASC is much longer, with symptoms persisting for months or even years.¹⁷ A study indicated that approximately 10% to 30% of patients with COVID-19 infection develop PASC.¹⁸ A recent review of 76 studies reported that >20% of patients experienced at least one symptom consistent with PASC.⁵ In our study, approximately 14.4% of participants developed PASC symptoms; this proportion is slightly lower than the proportions reported in other studies. This discrepancy may be attributable to our study population, which consisted of employees in a semiconductor packaging factory. The study participants were all aged <65 years, and only 29 individuals (8.8%) had a history of chronic diseases. These factors may have contributed to the lower prevalence of PASC in this investigation compared with in previous studies.

Gender seems to play a critical role in the development of PASC. Bai et al. conducted a multivariate logistic regression analysis of data from 260 patients with PASC. They found that female gender, advanced age, and active smoking were associated with a higher risk of PASC.¹⁹ Another study monitored 3094 patients hospitalized for COVID-19 infection, and the results similarly indicated that female patients and those who had been admitted to the ICU for COVID-19 infection had a higher risk of PASC.²⁰ Physiological differences between men and women influence infection severity and autoimmune responses. Men have higher risks of hospitalization and mortality from COVID-19 infection, likely due to the influence of male hormones, which predispose men to severe disease.¹¹ Compared with men, women may be at higher risk of PASC, potentially due to differences in immune responses and hormonal fluctuations.¹⁹ Second, the levels of inflammation-related cytokine expression differ between men and women. For example, the expression of inflammation-related receptors, such as toll-like receptor 7, differs between men and women; the expression levels of cytokines, including IL-6, are higher in women than in men. Patients with elevated IL-6 level following COVID-19 infection have a higher PASC risk.²¹ Differences in inflammatory responses may also contribute to the differing risk of PASC between men and women. Our results indicate that, compared with men, women have a higher risk of PASC.²¹

The COVID-19 pandemic has significantly influenced the risk of PASC, particularly for employees in high-risk occupations such as health care, public transportation, and logistics. Workers in these sectors have an increased risk of contracting COVID-19 due to their frequent contact with patients and the public.^22,23 A previous study indicated that healthcare workers, who are exposed to high viral loads for long periods, are at higher PASC risk than are workers in other industries. Furthermore, employees in this high-risk sector experience greater psychological and work-related stress, which may make PASC symptoms more likely and severe. Logistics operators and transportation workers, such as couriers and truck drivers, often interact with large numbers of people in crowded work environments, where maintaining social distancing is challenging, further increasing the risk of viral transmission.²² Vaccination has played a pivotal role in diminishing the COVID-19 pandemic, not only reducing viral transmission and the severity of acute infection but also preventing and mitigating PASC. Thus, vaccination is critical for individuals working in high-risk industries, such as the health care, logistics, transportation, and service industries. Studies have identified vaccination as a key strategy for preventing the exacerbation of PASC symptoms in these populations.^23,24 However, the effectiveness of COVID-19 vaccination in preventing PASC remains controversial. A retrospective study monitoring 10,024 patients with COVID-19 infection found that receiving at least one COVID-19 vaccine dose was associated with a significantly lower risk of adverse outcomes, such as respiratory failure, ICU admission, and intubation or ventilation. However, the study did not discover a significant effect of COVID-19 vaccination on the risk of PASC.²⁵ Another study analyzed data from the COVID Symptom Study mobile phone app, which had 1,240,009 users, and the results revealed that COVID-19 vaccination was associated with lower risks of hospitalization and having more than five symptoms. Moreover, receiving a second vaccine dose was linked to a decreased risk of PASC.²⁶ Our study found a marginal association between receiving three or more vaccine doses and a reduced risk of PASC in analyses adjusted for confounders. This result may reflect the characteristics of our study population, which consisted of employees aged 18 to 65 years working in a semiconductor packaging plant. Research has suggested that the protective effects of COVID-19 vaccination against PASC development are stronger in older adults than in younger individuals.²⁵ Furthermore, in Taiwan, most individuals were vaccinated before they could contract COVID-19. In our study, the majority of participants (54.4%) had received three vaccine doses, and only 3.6% had not been vaccinated. In addition, 4.8% had received a single vaccine dose. The characteristics of our study population thus differ from those of populations examined in previous studies. Although the protective effects of vaccination against PASC development are controversial, the well-documented benefits of vaccination for preventing severe short-term outcomes, such as ICU admission and respiratory failure, are indisputable. Therefore, COVID-19 vaccination continues to be a crucial measure for ensuring public health and should be widely promoted.

Lifestyle factors, such as smoking, alcohol consumption, diet, and physical activity, significantly influence the development and severity of PASC. A study analyzing data from 68,896 participants in the UK Biobank cohort examined the relationship between lifestyle factors, such as alcohol intake, BMI, sleep duration, and physical activity, and post-COVID symptoms. The findings revealed that a healthy lifestyle (characterized by the presence of 6–10 health-related factors, such as moderate alcohol intake, BMI <30 kg/m², at least 150 minutes of moderate or 75 minutes of vigorous physical activity per week, little sedentary time, and sufficient sleep duration) was associated with decreased risks of COVID-19 sequelae, hospitalization, and mortality.²⁷ Scholars have reported that nearly 80% of patients with PASC exhibited a decline in physical activity along with reduced peak aerobic capacity.^28,29 Consistent with these findings, our study discovered that physical activity was associated with a decreased risk of PASC. These results indicate that adopting a healthy lifestyle may reduce the risk of PASC.

The US Census Bureau reported that, as of November 2022, >3.8 million Americans had experienced COVID-19 symptoms lasting for >3 months and that had significantly affected their daily lives. Additionally, 9.2 million individuals reported prolonged COVID-19 symptoms with weak effects on daily functioning.³⁰ A study of 1378 workers found that those with COVID-19 symptoms persisting for >4 weeks had lower sleep quality, felt more fatigue, and had lower work ability than workers who were asymptomatic after 4 weeks.³¹ Research has highlighted that improving workplace environments, for example, providing adequate personal protective equipment and enhancing ventilation systems, can effectively reduce viral transmission risks and ensure employee health and safety.³² For workers affected by PASC, management should communicate with these workers regarding the issues they face, provide support, and offer work accommodations to assist them in resuming their role.³³ Our results indicate that night shift work is associated with an increased risk of PASC, whereas regular physical activity is linked to a decreased risk of PASC. Therefore, protective measures should be implemented for night shift workers, for example, encouraging them to engage in regular exercise and providing health guidance and tailored support for individuals affected by PASC.

This study has several limitations. First, the sample was limited to employees of a semiconductor packaging plant in southern Taiwan; this may have restricted the generalizability of the findings. Second, data were collected through self-reported questionnaires, which are subject to response bias. Third, recall bias was a concern because PASC symptoms may develop months or even years after COVID-19 infection. The participants may have had difficulty accurately recalling their symptoms and experiences, affecting the reliability of the findings. Finally, although we adjusted for factors such as age, gender, work shift, and vaccination status, unmeasured confounders, including baseline health conditions, lifestyle factors (e.g., diet, exercise, and smoking), and psychological state, may still have influenced the occurrence and severity of PASC.

CONCLUSIONS

This study found that night shift work and prolonged medical treatment were positively associated with PASC development. Moreover, female gender, night shift work, and medical treatment for >14 days were positively associated with the development of subacute COVID-19 symptoms. By contrast, an on-site work environment was negatively associated with subacute COVID-19 symptoms, and regular exercise (≥3 times per week) was negatively associated with PASC. Therefore, companies should optimize their work environments and shift schedules to mitigate PASC symptoms, enhance employee health, and improve work efficiency.