Abstract
Women in sea food processing units were involved in pre processing, grading, cleaning, freezing and packaging and they adopted static and awkward posture which results in low back pain. The aim of the present study is to analyze the factors that contribute to low back pain among women workers. A total of 244 women workers participated in the study. Socio economic background and frequency of musculoskeletal discomforts were studied. Descriptive statistics, chi square analysis and factor analysis were carried out to identify the factors contributing to low back pain. Women were involved in peeling (48.8%), setting (26.6%) and grading (24.6%) activity. Factor analysis indicated that work environment contributed to 33%, personal factors contributed to19%, work organization contributed to 16% and socio economic factors contributed to 11% for the low back pain. Worker education and periodical health surveillance will help to minimize the risk of low back pain among the women in industrial settings.
Keywords: Factor analysis, low back pain, musculoskeletal discomforts, sea food processing, women workers, work environment
INTRODUCTION
Fisheries are still one of the oldest and most important food production systems in the world. India is the second largest fish producer in the world and the second largest in inland fish production. The fisheries sector contributes 1% GDP to our country. According to the 2018 census, 59.51 million people were engaged in fisheries and aquaculture, of which 14% of them are women.[1] Women are often involved in post-harvest activities like cleaning, processing, freezing, bottling, and drying, and also marketing of fish.[2,3] Ratio of women to men in these units is 4:1 in Tamil Nadu.
Women who worked in seafood processing units reported occupational health problems. These include physical hazard (sprain, cuts), biological hazards (infections, increased IgE), and chemical hazard (skin irritation) depression.[4,5] Musculoskeletal discomforts such as leg pain, low back pain, and hand pain have also been reported.[6,7,8] Ergonomic hazards such as repetitive movements, vibrations, low temperature, and posture leads to low back pain.[9,10] Since several studies focus on the occupational health and very few studies investigate the factors related to ergonomic hazards, an attempt has been made to investigate the underlying causes for low back pain in sea food processing units.
METHODOLOGY
Study subjects
The employees in the study worked in ten sea food processing units in Tamil Nadu, India. Women workers who have worked for more than six months in the sea food processing units were invited to participate in the study. Random sampling method was adopted to select 10 percent of the samples. All the participants were permitted to decline or withdraw at any time during the study and only those participants who agreed were selected and their consent was obtained. Thus, a total of 244 workers comprised the present study samples.
Tools and data collection
A questionnaire was used to gather data on socio-economic background, job history and discomforts experienced by the workers. Consent was taken from the employer to interview the workers during the work time. Care was taken to maintain confidentiality of the responses. The discomforts were gathered using Corlett and Bishop (1976)[11] method of body mapping which indicates different body parts. A body map was used to identify the different body parts. The body part discomfort details were collected at five intervals namely before the start of the work, mid-morning, before lunch, mid-afternoon, and before the cessation of work. Nordic questionnaire by Kuorinka et al. (1996)[12] was used to analyze the periodicity of the pain.
Statistical analysis
Descriptive statistics, Chi-square, and factor analysis were used to identify the factors that contribute to the low back pain. SPSS—16.0 software was used to carry out the statistical analysis.
RESULTS
Table 1 presents the baseline information of women employed in small scale seafood processing unit. The age (median) of the women worker was 19 years with IQR of 2.5. About 94.2% of the women completed schooling and only 4.3% were illiterate. Majority (89.3%) of the women workers employed in seafood processing unit were unmarried. Age of entry was below 20 years for more than 85% with experience (median) of 3 years in the sea food processing units. About one half of the women performed peeling activity, 26.6% were involved in setting of fish in packing section and 24.6% were doing grading of fish. Most of the employers had job rotation (72.1%). Earlier studies reports that workers in the units were mostly young age and had less than five years of experience.[13,14]
Table 1:
Baseline information of women workers in sea food industry
| Particulars | Values | |
|---|---|---|
| Age (yrs) | Median (IQR) | 19 (2.5) |
| Education (%) | Illiterate School Graduation |
4.3 94.2 1.4 |
| Family type (%) | Nuclear Joint |
50 50 |
| Family size (%) | 1-4 members 5-7 members >8 members |
48.6 48.5 2.9 |
| Marital status (%) | Married Unmarried |
10.7 89.3 |
| Work hours per day (%) | <1 1-3 3-6 6-9 >9 |
24.3 37 21.4 12.1 5.2 |
| Age of entry (%) | <20 20-30 >30 |
87 9.4 3.6 |
| Work experience (yrs) | Median (IQR) | 3 (2) |
| Nature of activity (%) | Peeling Grading Setting |
48.8 24.6 26.6 |
| Job rotation (%) | Yes No |
72.1 27.9 |
| Income (Rs.) | Median (IQR) | 4000 (1000) |
It could be observed from Table 2 that more than 80% of the women reported different levels of discomforts ranging from mild to extreme level in low back. More than 70% of the workers reported pain in thighs (79.1%) and knees (71.8%). Those workers who had to stand for long hours reported extreme discomfort in the thighs (12%), legs (4.1%), head (3.7%), and low back regions (3.7%). More than 10% of them reported extremely severe discomfort in head (19.3%), low back (13.1%), upper (12.7%), shoulders (11.5%), and knees (10.2%).
Table 2:
Discomfort levels of women workers during various activities
| Body parts | No discomforts |
Mild |
Moderate |
Severe |
Extremely severe |
|||||
|---|---|---|---|---|---|---|---|---|---|---|
| No | % | No | % | No | % | No | % | No | % | |
| Head | 113 | 46.3 | 43 | 17.6 | 32 | 13.1 | 47 | 19.3 | 9.0 | 3.7 |
| Neck | 150 | 61.5 | 81 | 33.2 | 6.0 | 2.5 | 7.0 | 2.8 | - | - |
| Shoulders | 90 | 36.9 | 91 | 37.3 | 31 | 12.7 | 28 | 11.5 | 4.0 | 1.6 |
| Upper back | 49 | 20.1 | 83 | 34 | 73 | 29.9 | 31 | 12.7 | 8.0 | 3.3 |
| Low back | 47 | 19.3 | 85 | 34.8 | 71 | 29.1 | 32 | 13.1 | 9.0 | 3.7 |
| Upper arm | 181 | 74.2 | 41 | 16.8 | 14 | 5.7 | 6.0 | 2.5 | 2.0 | 0.8 |
| Forearm | 200 | 80 | 29 | 11.9 | 10 | 4.1 | 4.0 | 1.6 | 1.0 | 0.4 |
| Fingers and palms | 169 | 69.3 | 64 | 26.2 | 4.0 | 1.6 | 7.0 | 2.9 | - | - |
| Buttocks | 238 | 97.5 | 6.0 | 2.5 | - | - | - | - | - | - |
| Thighs | 51 | 20.8 | 78 | 32 | 62 | 25.4 | 24 | 9.8 | 29 | 12 |
| Knees | 69 | 28.2 | 102 | 41.8 | 42 | 17.3 | 25 | 10.2 | 6.0 | 2.5 |
| Legs | 82 | 33.6 | 64 | 26.2 | 56 | 23.0 | 32 | 13.1 | 10 | 4.1 |
| Feet | 204 | 83.6 | 30 | 12.3 | 6.0 | 2.5 | 4.0 | 1.6 | - | - |
Details of the periodicity of the pain are shown in Table 3. Forty three percent of the women reported that they suffered from back pain for the more than 30 days. Different methods of remedial measures were used by women to overcome this pain such as, taking pain relieving tablets and change of job if that was possible and lastly resorted to cessation of task or absenteeism from work. Table 4 presents association of discomforts with the independent variables such as age and work experience. A strong association between the discomforts in different body parts was observed with age and work experience in the present study as well in earlier study.[15]
Table 3:
Periodicity of discomfort level of selected women workers
| Discomforts* | 0 day |
1-7 days |
8-30 days |
>30 days but not every day |
>30 days but every day |
|||||
|---|---|---|---|---|---|---|---|---|---|---|
| No. | % | No. | % | No. | % | No. | % | No. | % | |
| Head ache | 142 | 58.2 | 16 | 6.5 | 7.0 | 2.9 | 78 | 32 | 1.0 | 0.4 |
| Neck pain | 214 | 87.7 | 23 | 9.4 | 1.0 | 0.4 | 6.0 | 2.5 | - | - |
| Shoulder pain | 131 | 53.7 | 50 | 20.5 | 18 | 7.4 | 43 | 17.6 | 2.0 | 0.8 |
| Back pain | 69 | 28.3 | 47 | 19.3 | 24 | 9.8 | 104 | 42.6 | - | - |
| Leg pain | 126 | 51.6 | 42 | 17.2 | 17 | 7.0 | 58 | 23.8 | 1.0 | 0.4 |
| Knee pain | 150 | 61.5 | 52 | 21.3 | 10 | 4.1 | 32 | 13.1 | - | - |
| Pain in arms | 136 | 55.7 | 84 | 34.4 | 13 | 5.4 | 11 | 4.5 | - | - |
| Elbow pain | 216 | 88.5 | 28 | 11.5 | - | - | - | - | - | - |
| Wrist pain | 150 | 61.5 | 79 | 32.4 | 12 | 4.9 | 3.0 | 1.2 | - | - |
| Pain in fingers | 155 | 63.5 | 76 | 31.2 | 9.0 | 3.7 | 4.0 | 1.6 | - | - |
Multiple response*
Table 4:
Chi-square analysis of musculoskeletal symptoms by age and work experience
| Body region | Age | Work experience |
|---|---|---|
| Neck | 14.188NS | 20.507NS |
| Shoulders | 35.947* | 69.154** |
| Upper back | 74.365** | 1.5002** |
| Low back | 79.511** | 1.497** |
| Upper arm | 32.741* | 52.880** |
| Forearm | 34.730* | 45.190** |
| Fingers and palms | 58.950* | 98.467** |
| Buttocks | 2.042NS | 3.468NS |
| Thighs | 36.868** | 44.136** |
| Legs | 36.654** | 70.893** |
| Knees | 48.758** | 38.062* |
| Feet | 23.049NS | 35.122* |
**P<0.01, *P<0.05, NS - Non significant
Factor analysis as shown in Table 5 and Figure 1 was carried out using 23 factors which were thought to be influencing the low back pain among the workers. Factors having higher correlation values were selected and the factors that had more than one value as Eigen values were categorized as factor-1 to 4. Analysis indicated that 80% of the factors that contributed to the low back pain have been identified and grouped as work environment (factor-1) contributing 33%, personal factor (factor-2) contributing to 19%, work organization (factor-3) accounting to 16% and socio-economic factors (factor-4) contributing to 11%.
Table 5:
Factor analysis of low back pain of women in seafood processing units
| Factor | Component | Loading | Eigen values | |||
|---|---|---|---|---|---|---|
| Work environment | ||||||
| 1. | Name of the section | 0.723 | 33.80 | |||
| Nature of work in the unit | 0.818 | |||||
| Work hours | 0.854 | |||||
| Work Shift | 0.806 | |||||
| Work at a stretch after lunch | 0.840 | |||||
| Personal factors | ||||||
| 2. | Respondent age | 0.894 | 52.15 | |||
| Marital status | 0.879 | |||||
| Age of entry into seafood processing center | 0.912 | |||||
| Work organization | ||||||
| 3. | Time slots of the shift with rest periods | 0.970 | 68.49 | |||
| Do you have change of jobs in rotation basis? | 0.858 | |||||
| Work at stretch before lunch | 0.970 | |||||
| Socio-economic | ||||||
| 4 | Work years | 0.926 | 79.23 | |||
| Individual income | 0.869 | |||||
Extraction Method: Principal Component Analysis
Figure 1:
Scree plot and factor analysis of low back pain
Work environment included the section, nature of work, work hours, work shift, and work at a stretch before lunch. The type of sections includes, preprocessing, processing, squid washing, and individual quick freezing. The nature of work includes peeling, grading, and setting. Work hours and work shifts also contribute to a greater extent toward low back pain.
Personal factors included age, marital status, and age of entry into the processing units. Prevalence of low back disorders increased significantly with age.[10] The nature of work necessitated awkward postures that have been identified as causative factors for occupational low back pain.
Work organization comprised time slots with rest periods, change of job, and work at a stretch which contribute to the low back pain. Continuous work with short rest breaks helps in alleviating fatigue to a greater extent and job rotation also enhances the workers’ productivity.
Socio-economic factors namely individual income and work experience has contributed to 11%. A positive significant association between the low back pain and number of years of work observed among handloom weavers.[16]
DISCUSSION
The present study attempts to categorize the factors responsible for low back pain among workers in sea food processing units into four major groups namely work environment, personal factors, work organization, and socio-economic factors. Work environment in seafood processing units mainly involves working on wet floors, long hours of standing, lifting of heavy loads, long work hours, and extended work shifts to process the perishables. Low back pain is more pronounced among women[6] working in industrial sector. Earlier studies have highlighted exposure time, long work hours, duration of bending, twisting, lateral bending, and reaching[10] resulted in increased low back pain. Prolonged standing during work,[17] lifting, and carrying heavy load from fish containers within the work area[18] may be the causative factors for low back pain. Personal factors such as age, marital status, and age of entry have been identified as one of the contributory factors for low back pain. Study on the risk factors among migrant sea food processing workers indicated that low back pain was associated with factors such as age over 40 years,[1,4,10] and poor health status and history of back injury.[16] Work organization factors such as lack of job rotation, working at a stretch without rest breaks and long hours of shift have contributed to low back pain among workers in the present study. The present study is in confirmation with findings of earlier studies were repetitive motion patterns, forceful exertion,[2] adopting non-neutral postures[5] to carry out the task for longer periods resulted in lack of rest periods/job rotation leading to low back pain. Socio-economic factors such as income and experience are also identified to be contributing to the low back pain among the workers. The workers are paid on the quantity of sea foods processed by the individual workers, majority of them due to poor socio-economic background tend to work in constrained postures for longer periods which results in musculoskeletal disorders. Multiple sites of pain have been reported by workers who work for long hours to earn higher wages. Thus the work environment, personal factors, work organization, and socio-economic conditions need to be addressed to minimize the low back pain among workers.
CONCLUSION
The present study is an attempt to identify the major factors that resulted in low back pain among women in small scale sea food processing industries. Work in the seafood processing units includes variety of tasks, starting from pre-processing, to packing which results in several musculoskeletal discomforts. Factor analysis indicated that work environment; personal factors, work organization, and socio-economic factors contribute to 80 percent of the low back pain.
Attempts are needed at this juncture to translate the findings of the study to the stake holders and also jointly carry out periodical health surveillance at work site, worker education to minimize the risk of low back pain among the women in these sections. Such interventions in improving the occupational health of workers results in minimizing musculoskeletal disorders have shown success.
Financial support and sponsorship
University Grant Commission, New Delhi.
Conflicts of interest
There are no conflicts of interest.
Acknowledgement
The authors wish to acknowledge the proprietors and the workers of the sea food units.
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