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SAGE Open Med
SAGE Open Med
SMO
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SAGE Open Medicine
2050-3121
SAGE Publications Sage UK: London, England

10.1177/20503121241278828
10.1177_20503121241278828
Original Research Article
Pilot study of musculoskeletal discomfort in Indonesian pregnant workers during COVID-19 pandemic era
https://orcid.org/0000-0001-6320-0403
Hasiholan Bonardo Prayogo 12
https://orcid.org/0000-0001-9903-5331
Susilowati Indri Hapsari 1
Withers Mellissa 3
1 Department of Occupational Health and Safety, Faculty of Public Health, Universitas Indonesia, Depok, West Java, Indonesia
2 Directorate of Productive Age and Elderly Health, Ministry of Health Republic of Indonesia, Jakarta, South Jakarta, Indonesia
3 Department of Population and Health Sciences, University of Southern California, Los Angeles, CA, USA
Indri Hapsari Susilowati, Department of Occupational Health and Safety, Faculty of Public Health, Universitas Indonesia, Kampus UI Depok, Depok, West Java 16424, Indonesia. Email: indri@ui.ac.id
9 9 2024
2024
12 2050312124127882811 4 2024
13 8 2024
© The Author(s) 2024
2024
SAGE Publications
https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
Objective:

This pilot study aims to analyze the factors influencing musculoskeletal discomfort in pregnant workers in Indonesia from occupational aspects, especially during the pandemic, to recommend further interventions and policies for a safer and healthier workplace.

Methods:

This study was a cross-sectional study. It used an online questionnaire to collect data on individual, occupational, and work environmental factors and musculoskeletal discomfort. We used Chi-square and logistic regression analysis to determine associations between the risk factors and the musculoskeletal discomfort.

Results:

A total of 126 women from multiple employment sectors participated. About 59% of respondents reported discomfort, with the majority having pain in the lower back (62.2%). Chi-square analysis revealed that age, history of injury, subjective agility and speed, length of working days in a week, and subjective temperature conformity were associated with the prevalence of musculoskeletal discomfort. Logistic regression revealed that age (p = 0.018 and OR = 2.218) and temperature conformity (p = 0.049 and OR = 2.157) were the most significant independent predictors of musculoskeletal discomfort.

Conclusion:

This study shows that temperature conformity is a predictor of musculoskeletal discomfort. Employers should consider this when determining whether their workplace is suitable for pregnant women. The treatment of younger workers needs attention, especially during pregnancy, they may need extra accommodation during pregnancy.

Pregnancy
workers
discomfort
musculoskeletal
ergonomics
Direktorat Riset and Pengembangan, Universitas Indonesia https://doi.org/10.13039/501100021726 Hibah Publikasi Ilmiah Terindeks Internasional (PU cover-dateJanuary-December 2024
typesetterts1
==== Body
pmcIntroduction

The Indonesian National Labour Force Survey 2020 states that 40% or at least 52 million of the Indonesian workforce is female, with 57.35% in the informal sector and 34.60% in the formal sector. 1 The increase in women’s participation in the labor force is due to the rise in their education and technological developments that make it possible for them to participate. 2 However, women’s physiological capacities and limitations are different than men’s. One of the life events that women may experience while working is pregnancy.

Like workers in general, pregnant workers are also at risk of experiencing musculoskeletal discomfort. Previous studies show that pregnant workers experience it from various fields of work, including small-medium enterprise workers, civil servants, tailors, education, and healthcare workers.3–5 Their complaints include low back pain, pelvic girdle pain, wrist pain, muscle spasms, sprains, leg cramps, and pedal edema.4,6–8

According to the model developed by Karsh, 9 the emergence of musculoskeletal complaints among workers is caused by multiple physical, psychological, and organizational factors. Previous studies have proven the theory that working pregnant women experience more musculoskeletal complaints than those who do not work.4,10 Research in Turkey also showed that environmental hazards increase musculoskeletal symptoms among pregnant workers. 5

In ergonomics, pregnant workers need specific accommodations, considering their temporary changes in body dimensions and capacity, especially when doing physical work. Most dimensional changes become evident after 2 or 3 months of gestation and increase throughout the pregnancy. 11 The most noticeable increases are in body weight and abdominal circumference. Physiologically, bodily changes directly increase the risk of musculoskeletal discomfort during pregnancy because weight gain and weakened ligaments can be associated with joint disorders. A 20% increase in body weight during pregnancy increases the pressure exerted on the joints by up to 100%. 11

Since the majority of workers’ time is spent at the workplace, policy, and workplace design interventions must be carried out to reduce musculoskeletal discomfort especially in Indonesia. Previous studies show that the consequences of musculoskeletal problems that are not intervened immediately for pregnant workers result in musculoskeletal injuries, which have impacts on other aspects of life such as physical health, psychological, social relationship, and environment. 8 However, there is a limited number of study about musculoskeletal discomfort in Indonesian pregnant workers, especially concerning the risk from occupational factors. In addition, many companies do not provide particular interventions and have limited policies for pregnant workers to address musculoskeletal disorders. Therefore, the pilot study aims to analyze the frisk actors influencing musculoskeletal discomfort in pregnant workers in Indonesia from occupational aspects, especially during the pandemic, to recommend further interventions and policies that are relevant or appropriate within the Indonesian context for a safer and healthier workplace.

Methods

Study design

This cross-sectional study utilized an online survey distributed throughout Indonesia in April and May 2022.

Study population

The sample calculation uses the Lemeshow hypothesis test formula at a 95% confidence level and 90% power. 12 It includes the proportion of pregnant women reported by previous studies to have experienced musculoskeletal complaints in urban 13 and rural areas. 14 The participants were recruited by snowball sampling. We included pregnant women working in Indonesia in the formal and informal sectors. Still, we excluded those with a gestational age of under 2 months (or 8 weeks) because there was no significant ergonomic effect. 11

Data collection

An online survey was chosen to prevent the transmission of COVID-19 in the pregnant population. We collected individual factors, occupational factors, environmental factors, and musculoskeletal discomfort data with various instruments that has been tested for validity and reliability.

For individual factors, we collected by questionnaire (age, gestational age, education, location, history of disease and injury, frequency of physical activity, and stretching habits) and the fitness level by a validated instrument, The International Fitness Scale through five criteria: general fitness, cardiorespiratory fitness, muscle strength, agility/speed, and flexibility for subjective fitness. 15

For occupational factors, we collected by questionnaire that consist of occupation, job sectors, history of work, working days in a week, working hour in a day, work shift, majority posture, and additional work.

For environmental factors, we collected subjective suitability for lighting using the Subjective Lighting Suitability Questionnaire. 16 It consists of 13 questions, 12 of which were tested for validity and reliability and gave a Cronbach alpha value of 0.893. We also assessed the temperature using The Temperature Suitability Questionnaire, 17 which consists of two questions, one of which was tested for validity and reliability and gave a Cronbach’s alpha value of 0.797. Thus, these two instruments have been validated for this research. Validity and reliability tests were carried out for instruments that assess environmental factors to 30% of the respondents because no validity and reliability tests were found in previous research.

For musculoskeletal discomfort, we collected musculoskeletal discomfort in general and the specific body parts by a validated instrument, the Nordic Musculoskeletal Questionnaire. 18 This questionnaire asks respondents about muscle discomfort (including pain, soreness, and tingling) felt in 27 sites of the human body. Respondents gave tick marks to body parts that were uncomfortable during pregnancy.

Statistical analysis

The data were analyzed using the Statistical Package for Social Science (SPSS) version 26. Descriptive statistics summarized musculoskeletal discomfort and individual, occupational, and environmental factors. A chi-square test was conducted to show the association between individual factors and the outcome of interest: musculoskeletal discomfort. All significant associations were evaluated at p-value <0.05. A logistic regression model with a backward selection procedure was performed, including variables with p-value <0.05 in the chi-square analysis.

Results

A total of 126 working women who were pregnant at the time participated in this study. The median age was 28 years, ranging from 22 to 38 years old. When their pregnancy risk levels were categorized based on age, 19 49.2% of the women were in the nonrisk group, with an age range of 20–27 years. However, the ages of 5.6% of the pregnant women put them at risk (>35 years old). More lived in West Java (30.95%), followed by Jakarta (23.81%), and East Java (11.11%). The vast majority lived in urban areas (81%) compared to rural areas. Most of the respondents were graduated from the university (92.8%) and had gestation age in the third trimester (46.03%). Most (84.9%) worked in the formal employment sector. The largest proportion of respondent in this study worked in the health sector (34.9%), followed by the governmental sector (18.3%), and the education sector (13.5%).

Regarding work environment, just over one-half of respondents (51.58%) felt that the lighting in their workplace was appropriate. Most (57.1%) strongly agreed that the targets of their vision were clear under the existing lighting. Many also agreed that the lighting was bright (41.3%) and suitable for work (40.5%), that the color of the light matched the work (40.5%) and made the work objects clear (39.7%), and that they were able to concentrate properly (40.5%). While most of the respondents (61.9%) stated that the temperature in their workplaces was appropriate, more than one-third (38.1%) found that it was too hot (or cold) to an extent that interfered with their activities.

More than half of respondents (58.7%) reported suffering from musculoskeletal discomfort. The lower back was the site of most of this discomfort (62.2%), followed by the left shoulder (47.3%), hip (39.2%), right shoulder (39.19%), and upper back (37.8%). Chi-square analysis (Table 1) was conducted to determine which independent factors had a significant relationship with the presence of musculoskeletal complaints in pregnant workers in Indonesia.

Table 1. Correlation between musculoskeletal discomfort and individual, occupational, and environmental factors.

Variables	Musculoskeletal discomfort	p	
Yes	No	
N	%	N	%	
Individual factors	
 Age	
  20–27-year old	44	71	18	29	0.022*	
  28–35-year old	27	47	30	53		
  >35-year old	3	43	4	57		
 Gestation age	
  First trimester	13	76	4	24	0.273	
  Second trimester	28	55	23	45		
  Third trimester	33	57	25	43		
 Education	
  High school	6	67	3	33	0.636	
  University	68	59	48	41		
 Location	
  Rural	56	55	46	45	0.72	
  Urban	18	75	6	25		
 History of diseases	
  Yes	20	69	9	31	0.202	
  No	54	56	43	44		
 History of injury	
  Yes	11	100	0	0	0.004*	
  No	63	55	52	45		
 Physical activity	
  <150 min/week	40	56	31	44	0.287	
  150 min/week	11	50	11	50		
  >150 min/week	23	70	10	30		
 Stretching habits	
  Routine	11	61	7	39	0.642	
  When feeling uncomfortable	58	60	39	40		
  No	5	45	6	55		
 Subjective fitness in agility	
  Very poor	0	0	0	0	0.025*	
  Poor	1	14	6	86		
  Sufficient	31	72	12	28		
  Good	32	56	25	44		
  Very good	10	53	9	47		
Occupational factors	
 Occupation	
  Construction	0	0	1	100	0.274	
  Energy	0	0	2	100		
  Health	30	68	14	32		
  Finance	3	60	2	40		
  Interior contractor	1	100	0	0		
  Environment	0	0	1	100		
  Manufacture	2	40	3	60		
  Media	1	100	0	0		
  Automotive	1	100	0	0		
  Transportation	0	0	1	100		
  Government	10	43	13	57		
  Education	11	65	6	35		
  Trading	5	63	3	38		
  Mining	0	0	3	100		
  Agriculture	2	100	0	0		
  Retail	1	100	0	0		
  Social	2	67	1	33		
  Technology	1	50	1	50		
  Small and medium enterprises	4	67	2	33		
 Job sector	
  Formal	64	60	43	40	0.558	
  Informal	10	53	9	47		
 History of work	
  3 Months to 1 Year	16	64	9	36	0.594	
  1 Year to 5 Years	40	59	28	41		
  5 Years to 10 Years	12	63	7	37		
  >10 Years	6	43	8	57		
 Working days in a week	
  2 Days	1	100	0	0	0.042*	
  3 Days	0	0	3	100		
  4 Days	3	100	0	0		
  5 Days	41	53	37	47		
  6 Days	27	73	10	27		
  7 Days	2	50	2	50		
 Working hour in a day	
  <8 h	3	50	3	50	0.173	
  8 h	49	54	41	46		
  >8 h	22	73	8	27		
 Work shift	
  Yes	15	75	5	25	0.107	
  No	59	56	47	44		
 Majority posture in working	
  Standing	8	62	5	38	0.465	
  Sitting	16	70	7	30		
  Squatting	0	0	0	0		
  Mix	50	56	40	44		
 Additional job	
  Yes	19	65	10	35	0.397	
  No	55	56	42	44		
Environmental factors	
 Subjective lighting conformity	
  Yes	35	57	26	43	0.765	
  No	39	60	26	40		
 Subjective temperature conformity	
  Yes	40	51	38	49	0.03*	
  No	34	71	14	29		
* Significant association through significant p-values (<0.05).

Significant musculoskeletal discomfort determinants in chi-square analysis were evaluated using logistic regression model. Age (p = 0.022), history of injury (p = 0.004), subjective fitness in agility (p = 0.025), and subjective temperature conformity (p = 0.03) were found to be significantly positively associated with musculoskeletal discomfort. A logistic regression model with backward selection procedure was performed including variables with p-value < 0.05 in the chi-square analysis. At the logistic regression model, age (OR [95% CI]) = 2.218 [1149–4.283], p = 0.018) and temperature conformity (OR [95% CI]) = 2.157 [1.943–4.935], p = 0.049) were the only independent variables associated with the outcome (Table 2)

Table 2. Logistic regression analysis.

Variables	p	OR (95% CI)	
Age	0.018*	2.218 (1.149–4.283)	
History of injury	0.999	—	
Fitness in agility	0.085	0.626 (0.367–1.067)	
Working days in a week	0.087	0.624 (0.363–1.071)	
Temperature conformity	0.049*	2.157 (1.943–4.935)	
* Significant association through significant p-values (<0.05).

Discussion

The majority (58.7%) of the pregnant workers in this study complained of musculoskeletal discomfort. This study also revealed that the most common body part of discomfort was the lower back (62.12%). Pregnant women may be especially at risk for this problem, as discomfort is caused by the relaxation of the ligaments (the connective tissue that holds bones together at the joints) caused by the production of the hormone relaxin, which loosens the joints as part of the body’s natural mechanism to prepare for childbirth. 20 The ligaments and muscles around the pelvis that support the spine are also loosened by this hormone, giving rise to back pain. In addition, as the pregnancy progresses, body mass increases and applies pressure to the lower spine, causing further complaints. 21

Even though the majority complained of discomfort, a significant proportion reported no discomfort, suggesting that things other physiological factors influence the emergence of musculoskeletal discomfort. For example, this study showed a relationship between temperature and a younger age of experiencing musculoskeletal complaints.

Age and musculoskeletal discomfort

This study showed that younger workers have a 2.2 times higher risk of experiencing musculoskeletal discomfort than older workers. The 20–27 age group had the highest proportion (71%) of musculoskeletal complaints compared to the other age groups. However, this can be explained by the fact that most of the Indonesian workers in this age group occupy jobs in the education, health, and government sectors, holding executive or technical positions (e.g., administrators, teachers, and call center operators) with higher physical work demands than the over-35 age group.22,23 This study’s findings aligned with other previous research that found that younger people tend to have a greater risk of experiencing musculoskeletal discomfort.24,25

Further analysis showed a significant relationship between age and site of discomfort in the body: hips, upper back, and neck. This may be related to using office chairs, tables, and computers. Previous research has found that these complaints may also be caused by young workers who tend to ignore good work posture or take adequate breaks because they are focused on completing their work.26–28

Subjective temperature conformity and musculoskeletal discomfort

Most respondents (61.9%) felt the workplace temperature was appropriate, while the rest (38.1%) felt too hot or cold. Further investigation showed that those who complained of a temperature imbalance said the temperature was too hot (75%). The third-trimester group is the most often complained that the temperature felt too hot (45%). This result is relevant because the natural processes of pregnancy tend to increase body temperature, making the woman feel hotter than usual. 29 This study also revealed that an uncomfortable workplace temperature has a 2.1 times risk of experiencing musculoskeletal complaints compared to a comfortable workplace temperature. We did not find previous research regarding the influence of temperature on pregnant workers, but research in the general population explains that uncomfortable temperature influences musculoskeletal discomfort.30,31

We found a significant relationship between subjective temperature suitability and musculoskeletal complaints (p 0.03). Of those who stated that the temperature at work was inappropriate, 71% reported musculoskeletal complaints. These results align with a study by Magnavita et al., 32 who found temperature significantly related to musculoskeletal complaints. Vos et al. 33 also noted the impact of ambient temperature on thermoregulation and muscle fatigue in workers engaged in sedentary tasks. Further inferential analysis in our study showed a significant relationship between temperature and discomfort in the upper back, lower back, left leg, and right leg. Previous research supported this result, which found that workplace temperature discrepancies were significantly related to low back complaints. 34 Other studies have shown that the sensitivity of the leg muscles increases with temperature. 35

Comparison with similar studies

Similar studies regarding pregnant workers and risk factors for musculoskeletal complaints are very limited, but we found them in Turkey and Oman. When compared to a study on various pregnant workers in Turkey shows that the amount of work-related physical damage, environmental hazards, and psychosocial hazards increase musculoskeletal complaints and problems. 5 This is in line with the results of this study regarding environmental factors, where this study specifically mentions temperature as a risk factor. In another study in a group of pregnant healthcare workers in Oman, stressors that were risk factors for musculoskeletal complaints included prolonged bending, lifting, moving, transferring, and posture issues. 6 The results of this study in Oman can be used as variable development in future research to analyze work postures in detail.

Limitation

The data were collected during the COVID-19 pandemic through an online survey. Therefore, no physical assessments or direct measurements were conducted. While some data collected are subjective, the instruments used are validated in numerous other studies. The number of respondents was also influenced by several factors, including women deciding not to work while pregnant, minimal internet access in rural areas, and gaps in the ability to use technology. Since the study is a pilot, the results may be helpful to shed light on the working conditions of pregnant workers in Indonesia. However, more research is still needed in rural areas and informal sectors. Further research should focus on one sector or field of industry to gain specific insights into the relationships between the dependent and independent variables. In addition, a qualitative study would lead to a better explanation of relationships with existing risk factors.

Conclusion

This study shows that 58.7% of the respondents experienced musculoskeletal discomfort. Most are young workers aged 20–27 years and gestation in the third semester. The multivariate test found that younger workers have a 2.2 times risk of experiencing musculoskeletal complaints than older workers. Besides, an uncomfortable workplace temperature has a 2.1 times risk of experiencing musculoskeletal complaints compared to a comfortable workplace temperature. This study shows that temperature conformity is a predictor of musculoskeletal discomfort. Employers should take this into consideration when determining whether their workplace is suitable for pregnant women. The treatment of younger workers needs greater attention, especially during pregnancy, so that pregnant workers receive appropriate accommodations to ensure a safe workplace.

None.

Author contributions: B.P.H.: Study conception and design, acquisition of data, drafting the manuscript. I.H.S.: Study conception and design, drafting of manuscript, critical revision. M.W.: Drafting manuscript, critical revision.

Availability of data and materials: None.

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The study is funded by Hibah Publikasi Ilmiah Terindeks Internasional (PUTI) Universitas Indonesia Q2 Tahun 2022 with number NKB-623/UN2.RST/HKP.05.00/2022.

Ethics approval: This research received clearance from the Research and Community Engagement Ethical Committee Faculty of Public Health Universitas Indonesia, number Ket-113/UN2.F10.D11/PPM.00.02/2022.

Consent to participate: All participants in this study gave their written informed consent through the informed consent form that was requested at the beginning of the questionnaire. The participant has also consented to the submission of the case report to the journal.

Consent for publication: Not applicable.

Trial registration: Not applicable.

ORCID iDs: Bonardo Prayogo Hasiholan https://orcid.org/0000-0001-6320-0403

Indri Hapsari Susilowati https://orcid.org/0000-0001-9903-5331
==== Refs
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