WORK-RELATED MUSCULOSKELETAL DISORDERS AMONG CASHEW …€¦ · cashew processing industry situated in Kollam district of Kerala state in India. The socio- demographic factors of

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International Journal of Advanced Research in Engineering and Technology (IJARET) Volume 9, Issue 4, July – August 2018, pp. 162–173, Article ID: IJARET_09_04_018

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ISSN Print: 0976-6480 and ISSN Online: 0976-6499

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WORK-RELATED MUSCULOSKELETAL

DISORDERS AMONG CASHEW INDUSTRY

WORKERS IN KERALA, INDIA

M. Satheeshkumar

Research scholar, College of Engineering Trivandrum Thiruvananthapuram, Kerala, India

K. Krishnakumar

Professor in Mechanical Engineering, College of Engineering Trivandrum,

Thiruvananthapuram, Kerala, India

ABSTRACT

In this article, the prevalence of work- related musculoskeletal disorders

(WMSDs) among cashew processing industry workers in Kerala state, India were

studied. A cross sectional study by a detailed questionnaire on symptoms of socio-

demographic factors, musculoskeletal disorders, working postures and work history

was administered to 350 subjects. A modified Nordic Musculoskeletal Questionnaire

(NMQ) was used for the survey. The subjects are randomly selected from three

cashew processing industry situated in Kollam district of Kerala state in India. The

socio- demographic factors of workers were analysed and demonstrated in the first

part of the article. Past 12-month prevalence of WMSDs at nine body regions were

demonstrated in the next part of the article. The result shows that the lower back was

the most prevalent disorders among the subjects (54.6%). Knee (54.3%) is the second

most prevalent body region where affects the disorder followed by neck (46%),

shoulder (40%), upper back (36.6%), elbow (32.6%), ankle (26.8%), hip (16.9%) and

wrist (13.1%). Significant relationships were existing to the variables gender, age,

duration of employment, section of work, and BMI with WMSD symptoms at all or

certain body regions. Also, it was identified that significant relationships existed to

the physical factors such as heat, noise, dust and odour except light with WMSDs. The

data collected were analysed by SPSS V20.0 package.

Keywords: Cashew industry workers, Prevalence, Ergonomics, and Work related

musculoskeletal disorders.

Cite this Article: M. Satheeshkumar and K. Krishnakumar, Work-Related

Musculoskeletal Disorders among Cashew Industry Workers in Kerala, India,

International Journal of Advanced Research in Engineering and Technology, 9(4),

2018, pp 162–173.

http://www.iaeme.com/ijaret/issues.asp?JType=IJARET&VType=9&IType=4

Work-Related Musculoskeletal Disorders among Cashew Industry Workers in Kerala, India


1. INTRODUCTION

Musculoskeletal disorder is a type of disorder includes a wide range of inflammatory and

degenerative conditions affecting the different parts of the body associated with movement of

upper and lower limbs and the trunk. The musculoskeletal system provides form, support,

stability, and movement to the human body, which is made up of bones, muscles, tendons,

peripheral nerves, supporting blood vessels, ligaments and other connective tissues. Work-

related musculoskeletal disorder (WMSDs) is one of the major problems in industrialized

countries [1]. Most of the WMSDs are cumulative disorders, resulting from repeated

exposures to high or low intensity loads over a long period of time. The physical and

psychosocial factors present in a work environment are the reasons for the development of

WMSDs among workers. The physical factors which affect the WMSDs are awkward

posters, repetitive movement over exertion of forces, the time sequence of work etc. The

individual characteristics such as gender, age, physical capacity, lifestyle, household

activities, inclination to musculoskeletal diseases, personality traits etc., have an indirect

effect on the occurrence of WMSDs [2]. WMSDs are associated with high costs to employers

such as absenteeism, lost productivity, and increased health care, disability, and worker’s

compensation costs. Musculoskeletal disorders account for nearly 70 million consultations with physicians in the United States annually and National Research Council and the Institute

of Medicine reports that the economic burden of WMSDs, as measured by compensation

costs, lost wages, and lost productivity, are between $45 and $54 billion annually [3].

WMSDs constitute a major component of occupational diseases, accounting for

approximately 38.1% of all occupational diseases in Europe [4]. In a report regarding

WMSDs by Australian safety and compensation council, industries with the highest number

of cases of WMSDs were from manufacturing, construction, retail trade, transport & storage

and health & community Services sectors [5]. The causes of WMSDs are poor working

postures of workers, lack of job rotation, ergonomically poor design of workstations, poor

design of plant layout, absence of training, poor condition environment etc. A poor

ergonomically and unscientifically designed work environment and workstation may badly

affect physical stress of workforce, productivity and quality of work. Proper application of

ergonomic principles in the design of workstation and scientifically designed work

environment will reduce WMSDs. Physical measurement of workstation should match with

human anthropometric measurements to avoid awkward postures of workers [6].

Cashew industry is the traditional industry in Kerala state in India and mainly

concentrated in Kollam District. The Kerala accounts 11% of cashew production and 35% of

all cashew nut processing units in India. The industry is highly labour intensive and employs

more than 0.2 million workers; most of them were women (above 90%). It contributed

around 750 million US$ worth of exports during 2015-2016 financial year. India is the largest

producer of Cashew nut in the world followed by the Ivory Coast, Vietnam, Guinea Bissau,

Tanzania, Nigeria, Brazil, Indonesia and Mozambique. In India more than 50% of the cashew

productions are carried out in the unorganised sector. There are nearly 1800 medium to large

and 2200 on farm level processing units [7].

The cashew nut processing has different stages. Drying is the first stage of processing;

raw cashew nuts are properly dried to remove excess moisture by spread over the open yard

and are dried in sunlight for 2 to 3 days. Roasting is the second stage of processing, heat the

cashews with high pressure/temperature. The roasting time depends upon the characteristic of

raw cashew nuts. Shelling or Cutting, is the third stage of processing, removing of the outer

shell from the cashew nut. For this the workers use a specially designed hand and leg

operated cutting machines to cut raw cashew nuts. Heating is the fourth stage; the kernels are

heated to 70-85 degree centigrade. The main purpose of heating is to eliminate moisture and

M. Satheeshkumar and K. Krishnakumar


gumming between cashew kernels and adhering testa, the outer covering of the seed. Peeling

is the fifth stage of processing; cashew kernels are blanched using a small knife. The adhering

testa is carefully removed by ensuring minimum damage to the cashew kernels. Due to the

unique shape of the cashews, the process is mostly manual. Grading is the sixth stage of

processing, cashew kernels are graded according to their size, colour, appearance etc. Packing

is the last stage of processing; cashew kernels are fumigated before packing. Then, it is

passes through a cleaning line, where dead insects and foreign particles if any, are removed

[8].

Cashew industry workers adopt awkward postures, repetitive movements, which are the

important factor that affect their poor working efficiency and musculoskeletal disorders. Most

of the cashew industries are using traditional equipment and tools. Modern cashew

manufacturing equipment is not widely accepted in this type of industry, even though it is

available market.

The study of prevalence of WMSDs in different sectors is conducted and published by a

number of researchers and some relevant works in this regard are pointed out here.

Prevalence was determined by the percentage of positive responses to questions on

musculoskeletal symptoms [9]. Several articles reported that, the low back pain (LBP) was

the most prevalent body region.

In a cross-sectional study, about cashew factory workers (n=246), working in a factory

located in Udupi district of Karnataka state, studied the demographic factors and pain and

discomfort status [10]. The article reported that around 28.5% have pain, whereas 71.5% of

workers did not have any pain. Most of the workers (32.4%) complained pain in the knee,

followed by lower back (30.9%) and then shoulder (11.8%). Seventy percent of the workers

who reported pain were having more than 5 years of work experience. About 68.6% of the

workers who reported pain were in the cutting category, followed by the grading (17%),

boiling (8.6%), and peeling (5.7%) categories. WMSDs problem among workers in

traditional industry were reported in some articles. The results from such relevant papers are

included in the following paragraphs.

In a study of WMSDs among handloom textile weavers (n=175) of West Bengal state in

India, to determine the prevalence and identify the risk factors of WMSDs reported that, the

most prevalent body part was the lower back (68%), followed by arm (49.7%), upper back

(44%), knee (38%), shoulder (39.4%), wrist (35.4%) and neck (35.4%) [11]. In another study

of WMSDs among textile weaving workers (n=375) in state of Andhra Pradesh in India,

reported that the most commonly affected body regions were lower back (60.6%), ankles/feet

(59.0%), knee (58.1%) and upper back (54.6%). Female workers were significantly more

affected than male workers in the upper back, lower back, shoulders, wrists and ankles (P <

0.05) [12]. In another study of WMSDs among Iranian hand-woven carpet industry workers

(n=1439), reported the most commonly affected body region are neck (35.2%), shoulders

(47.8%), upper back (37.7%), lower back (45.2%), wrists (38.2%), and knees (34.6%) [13].

in a study among Nepalese textile workers the one-month prevalence reported at LBP was

35% (n = 324), being higher in females than males (45% versus 28%; P < 0.001) [14].

2. MATERIALS AND METHODS

In literature, the prevalence of work musculoskeletal disorder was measured by means of

administrated data (e.g. compensation claims or absenteeism), clinical examinations or

diagnoses, and self-reported symptoms. The administrative data of cashew workers are

incomplete and not reliable because, not all the compensations are claimed or sanctioned and

there are several reasons for absenteeism. Since the clinical examination and diagnosis are

very difficult, costly and time consuming, in this study a self-administrated questionnaire was



used. A cross-sectional type of survey was conducted a questionnaire based on Nordic

musculoskeletal questionnaires during the period of March 2018 to April 2018. The Nordic

Musculoskeletal Questionnaire (NMQ) was a standardized questionnaire methodology

allowing comparison of low back, neck, shoulder and general complaints for use in

epidemiological studies [15]. The printed questionnaire was distributed among the workers

directly during the working time and it was collected back within two days. 382 numbers of

questionnaires were distributed to all the workers in selected cashew nut processing factory.

Finally, 350 (response rate: 95.8%) workers responded to the questionnaires positively. The

inclusion criteria were full-time cashew workers from cashew nut processing factory. Two

cashew nut processing factories are selected by convenient sampling method from the list of

cashew factory in Kollam district in Kerala. The questionnaire consists of a front page

explaining the purpose of the study, general directions to fill up the questionnaire, contact

mobile phone number and the second page was a consent form. The questionnaire consists of

five different parts (i) demographic characteristics of workers (age, gender, etc.) enquired

with 7 questions, (ii) WMSD symptoms like to perceive pain and discomfort at nine body

areas was enquired with 2 questions its sub questions. The nine body segments include three

upper limb segments (shoulder, elbows, wrists/hands) three lower limb segments (hip/thighs,

knees, ankles/feet) and three trunk segments (neck, upper back and lower back) (iii) Physical

condition in the factory enquired with 6 questions and its sub questions (iv) working posture

information- 2 questions and its sub questions (v) Questions related habits enquired with 2

questions. The questionnaire was prepared in the mother tongue of the target population,

Malayalam. Even though the validity and reliability of the NMQ were investigated in

different studies, a thorough validation was conducted by a pilot study by circulating the

questionnaire among 30 targeted workers and the questionnaire was modified on discussion

with experts. Statistical analyses were conducted using the SPSS 20.0 package with a

significance level set at p < 0.05 for all tests. The data collected was systematically entered,

cleaned and analysed with the software. Pearson’s chi-square analysis was applied to

determine the association of the prevalence of musculoskeletal symptoms with personal

characteristics, duration of employment of workers and different task performed by the

workers. The chi-square statistic helps us to decide whether the prevalence of WMSDs

symptoms with different demographic characteristics were associated or not. In this study,

logistic regression analysis was carried out to find the odds ratio (OR) to quantify factors that

were likely to affect WMSDs at different body regions. It is obvious that the odds ratio is a

more interpretable statistic than the chi-square because which gives a quantified result [16].

For the regression analysis, one of the variables (WMSDs at the neck, upper back, lower back

etc.) taken as depended variable and all independent variables are taken as covariates in

SPSS.

3. RESULTS AND DISCUSSION

The demographic characteristics of the subjects are summarised in Table 1. The male and

female workers participated in this study were 28 (50.8%) and female 322 (49.2%), n=350.

The percentage of workers whose age below 30 years was only 2.85%, age between 31 and

40 years was 32.57%, age between 41 and 50 was 48.85%, and age between 51 and 60 was

15.71%. The ages below 30 years were very few compared to the other industries. This

indicates that the youngsters are not opting cashew industry as a career opportunity. The

reason for this is low income compared to the other jobs available in Kerala. In the case of

educational qualification of workers, 14 female workers were fallen under the group no

education (4%). About 22.6% workers have primary education (up to 7th

standard) or Most of

the workers have secondary (66.6%) education (above 7th

to10th

standard). A worker beyond

secondary education was comparatively less in number (6.9%). From the analysis, it is



observed that the association with educational qualification and WMDS are not significant. In

the case of monthly income of workers, the majority of the workers (68%) having monthly

income below ₹2500 ($38 approx.). The percentage of workers who, having monthly income

between ₹2500 and ₹5000 ($77 approx.), ₹5000 and ₹7500 ($116 approx.) and above ₹7500

was 27.7%, 2.3%, 2% respectively. It was noticed that most of the workers are having very

low income compared to similar workers and hence this is the one of the reasons for

demotivation of workers. The percentage of workers having duration of employment less

than 10years, between 11 years and 20 years, between 21 years and 30 years and beyond 31

years are 1.7%, 46.9%, 38% and 3.4% respectively. It shows that the newly joined workers

are very few in numbers, because of this industry is not attractive to the young generation.

The Body Mass Index (BMI) of most of the workers (63.7%) falls under normal category.

13.1% workers fall under the category of underweight. 21.7% of workers fall under the

category of overweight. 1.4% of workers fall under the category of obese. It was noticed that

most of the workers have normal BMI.

The WMSDs in different body region are shown in Table 2. The 12-month prevalence

rate of WMSDs was highest at lower back (54.6%). The region at knee (54.3%) was the

second most prevalent WMSDs reported followed by neck (46.0 %), shoulder (40.0%), upper

back (36.6%), elbow (32.6 %), ankle (26.8%), hip (16.9%) and wrist (13.1%). In this study, a

high proportion of the population (81.7%) had experienced some form of WMSDs at one or

other body region during the past 12 months. For the female population, it was 82% and for

male population it was 78.5%. Workers have no WMSDs symptoms affected was 18.3%.

About 17.1% of workers have WMSDs symptoms at any one body region.

WMSDs affected in more than one body region are given in the Table 3. The high rate of

WMSDs indicates that immediate ergonomic intervention is required in this industry to

protect the workers’ health.

From the Table 4 it is shown that the prevalence of WMSDs at the neck (p=0.035), upper

back (p=0.026), lower back (p=0.011), shoulder (p=0.026), elbow (p=0.046), wrist (p=0.016),

hip (p=0.017), knee (p=0.025) and ankle (p=0.020) was significantly associated with gender.

The WMSDs at neck, upper back, lower back, shoulder, elbow, wrist, hip, knee and ankle of

male workers was 2.368 (OR),2.421, 3.310, 2.455, 2.20, 2.952, 2.796, 2.739 and 2.523 times

higher that of female workers. The WMSDs for male were significantly more affected than

female in all the body regions.

In this study workers are grouped into four groups based on the age. The WMSDs at

different body regions was not significantly associated with age group.

In this study the duration of employment of the workers was categorized into four groups.

Group A consist of 0 to 10 years, Group B consists of 11 to 20 years, Group C consists of 21

to 30 years, Group D consists of more than 31 years. The prevalence of WMSDs at the body

region, neck (p=0.044), shoulder (p=0.019), elbow (p=0.039), wrist (p=0.018) hip (p=0.013),

knee (p=0.042) and ankle (p=0.037) was significantly associated with different categories of

duration of employment. The WMSD at body region upper back and lower back are not

significantly associated with the duration of employment. The WMSDs at neck of workers

having employment duration between 11 and 20 years are 0.561 (OR) times less than workers

having less than 10 years of duration of employment. The WMSDs at neck of workers in the

group C and group D were 0.699 and 1.854 (OR) times less and higher than workers in the

group A respectively. The WMSDs at neck of workers in the group C and group D were

1.254 and 3.220 (OR) times less than workers in the group B, respectively. The WMSDs at

neck of workers in the group D were 2.667 (OR) times less than workers in the group C.

From the Table 6 it may conclude that, when the duration of employment increases, the



symptoms of WMSDs were also found to be generally increasing in the body region,

shoulder, elbow, wrist, hip, knee and ankle.

In this study, the body mass index (BMI) of the workers was categorized to four groups

viz. underweight (group A), normal (B), overweight (C) and obese (D). The prevalence of

WMSDs at the body region, neck (p=0.036), upper back (0.027), lower back (p=0.025),

shoulder (p=0.041), Elbow (p=0.046), knee (p=0.048), and ankle (p=0.048) was significantly

associated with different categories of BMI. The prevalence of WMSDs at wrist and hip was

not significantly associated with different categories of BMI. The WMSDs at neck of workers

in the category A, category C and category D were 2.217 (OR), 1.582 and 1.356 times higher

than workers having normal BMI (category B). The WMSDs at upper back, lower back,

shoulder, elbow, knee and ankle were also higher for category A, C and D than category B,

the OR vales are given in the table 7.

In this study four major tasks are considered and they are shelling (Section A), Peeling

(B), Grading (C), Roasting (D). The prevalence of WMSDs in the body region upper back

(p=0.022), lower back (p=0.015), shoulder (p=0.045), elbow (p=0.037), wrist (p=0.040), hip

(p=0.022), knee (p=0.006) and ankle (p=0.039) was significantly associated with the task.

The prevalence of WMSDs of the neck was not significantly associated with the task. The

WMSDs at lower back of Peeling, Roasting workers were 1.018, and 2.781 (OR) times

higher than shelling workers respectively.

The WMSDs at lower back of grading workers are 0.587 times lower than shelling

workers. The Table gives the value of adjusted OR at different body region. The prevalence

of WMSDs in none of the body region was not significantly associated with the education of

workers. It is also identified that the significant relationships were existing with physical

factors such as heat (p=0.011), noise (p=0.012), dust (p=0.021) and odour (p=0.022) except

light (p=0.182) at 95% CI.

Table 1 Demographics of workers

Variable

Frequency

Gender Total

(%)

(n=350) Female

n=322

Male

n=28

Age (Years)

Less than 30 10 0 10

(2.86%)

Between 31& 40 114 0

114

(32.57%

)

Between 41& 50 151 20

171

(48.85%

)

Between 51& 60 47 8

55

(15.71%

)

Level of Education

No Education 14 0 14(4%)

Primary 69 10 79(22.6

%)

Secondary 221 12 233(66.6

%)



Higher Sec./ above 18 6 24(6.9%

)

Monthly Income (Rupees)

Less than 2500($38) 224 14 238(68

%)

Between

2500&5000($77) 85 12

97(27.7

%)

Between 5001&7500($

116) 8 0 8(2.3%)

Above 7500($116) 5 2 6(2%)

Duration of employment (Years)

Between 5&10 6 0 6(1.7%)

Between 11& 20 152 12 164(46.9

%)

Between 21 and 30 123 10 133(38

%)

Above 31 41 6 10(13.4

%)

Body Mass Index

Underweight, BMI ≤

18.5 46 0

46(13.1

%)

Normal, BMI = 18.5 to

24.9 203 20

22363.7

%)

Overweight, BMI=25

to 29.9 68 8

76(21.7

%)

Obesity BMI ≥ 30 5 0 7(1.4%)

Section of Work

Roasting 0 28 28(8%)

Shelling 137 0 137(39.1

%)

Peeling 128 0 158(36.6

%)

Grading 57 0 57(16.3

%)

Table 2 Frequency of reported WMSD symptoms in different body regions of the male and female

workers during the 12 months prior to the study.

Body

region

Female

(n=322)

Male

(n=28)

Total

(n=350)

Neck 143

(44.4%) 18 (64.3%)

161

(46.0%)

Upper Back 112

(34.8%) 16 (57.1%)

128

(36.6%)

Lower Back 169

(52.5%) 22(78.6%)

191

(54.6%)

Shoulder 127

(39.4%) 13 (46.4%)

140

(40.0%)

Elbow 100

(31.0%) 14 (50.0%)

114

(32.6%)



Wrist 38 (11.8%) 8 (28.6%) 46 (13.1%)

Hip 50 (15.5%) 9 (32.1%) 59 (16.9%)

Knee 169

(52.5%) 21 (75.0%)

190

(54.3%)

Ankle 81 (25.1%) 13 (46.4%) 94 (26.8%)

Table 3 Prevalence WMSD reported with number of body regions affected.

Number of

Body regions

affected the

WMSD

No of workers

reported (%) Total (%)

(n=350) Gender

Female

(n=322)

Male

(n=28)

No WMSD 58(18.0%) 6(21.4%

) 64(18.3%)

1 58(18.0%) 2(7.1%) 60(17.1%)

2 39(12.1%) 2(7.1%) 41(11.7%)

3 34(10.6%) 4(14.3%

) 38(10.9%)

4 37(11.5%) 4(14.3%

) 41(11.9%)

5 32(9.9%) 0(0%) 32(9.1%)

6 26(8.1%) 4(14.3%

) 30(8.6%)

7 24(7.5%) 4(14.3%

) 28(8.0%)

8 11(3.4%) 0(0%) 11(3.1%)

9 3(0.9%) 2(7.1%) 5(1.4%)

Have

WMSD

264(82.0%

)

22(78.5

%) 286(81.7%)

Table 4 Association of WMSD symptoms at different body region with gender.

Body Region P* Value OR (at 95% CI)

Neck 0.035** 2.368 (1.063-5.278)

Upper Back 0.026** 2.421(1.110-5.280)

Lower Back 0.011** 3.310 (1.310-8.361)

Shoulder 0.026** 2.455(1.116-5.398)

Elbow 0.046** 2.200 (1.014-4.472)

Wrist 0.016** 2.952 (1.223-7.125)

Hip 0.017** 2.796 (1.119-6.520

Knee 0.025** 2.739 (1.135-6.608)

Ankle 0.020** 2.523 (1.156-5.506)

* χ2 analysis of prevalence of MSD symptoms at

different body region with gender.

** Statistically significant with p < 0.05, † Not

significant

OR- Odds Ratio with female as reference category



Table 5 Association of WMSD symptoms at different body region with age groups.

Body region P*

Value

Statistically significant

with p < 0.05,

Neck 0.439 Not Significant

Upper Back 0.982 Not Significant

Lower Back 0.294 Not Significant

Shoulder 0.816 Not Significant

Elbow 0.400 Not Significant

Wrist 0.053 Not Significant

Hip 0.482 Not Significant

Knee 0.059 Not Significant

Ankle 0.255 Not Significant

* χ2 analysis of prevalence of WMSD symptoms

between age groups

Table 6 Association of WMSD symptoms at different body regions with duration of employment.

Body

region

PP*

Value

Adjusted OR (at 95% Confidence Interval)

A-B# A-C

# A-D

# B-C

# B-D

# C-D

#

Neck 00.044*

*

0.561

(0.354-0.891)

0.699

(0.335-1.456)

1.864

(0.541-

6.423)

1.245

(0.585-2.651)

3.320

(0.951-

11.59)

2.667

(0.675-

10.54)

Upper Back 00.553† - - - - - -

Lower

Back 00.202† - - - - - -

Shoulder 00.019*

*

0.449

(0.307-0.779)

0.768

(0.366-1.610)

1.613

(0.492-

5.283)

1.550

(0.717-3.351)

3.255

(0.975-

10.872

2.100

(0.554-

7.957)

Elbow 00.039*

*

0.503

(0.303-0.836)

1.104

(0.525-2.324)

1.183

(0.360-

3.884)

2.194

(0.999-4.871)

2.350

(0.697-

7.927)

1.071

(0.283-

4.059)

wrist 00.018*

*

1.414

(0.684-2.909)

3.850

(1.572-9.432)

3.208

(0.788-

13.068)

2.729

(1.118-6.664)

2.275

(0.560-

9.245)

0.883

(0.186-

3.729)

Hip 00.013*

*

0.736

(0.316-1.713)

2.319

(1.040-5.170)

1.349

(0.415-

4.380)

1.967

(0.733-5.278)

2.622

(0.638-

10.77)

1.333

(0.284-

6.623)

Knee 00.042*

*

0.728

(0.462-1.147)

1.764

(0.864-3.829)

2.426

(0.634-

5.032)

2.424

(1.100-5.345)

3.333

(0.864-

12.86)

1.375

(0.310-

6.094)

Ankle 00.037*

*

0.809

(0.476-1.375)

1.852

(0.868-3.949)

1.984

(0.599-

6.958)

2.289

(1.040-5.039)

2.452

(0.726-

8.286)

1.071

(0.283-

4.059)

* χ2

analysis of prevalence of WMSD symptoms at different body regions against

different categories duration of employment. ** Statistically significant with p < 0.05, † Not

significant. # A- duration of employment less than 10 years, B- between 11 and 20 years, C-

between 21 and 30 years, D- more than 31 years.



Table 7 Association of WMDS symptoms at different body regions with BMI groups

Body

region

PP*

Value

Adjusted OR (at 95% Confidence Interval)

B-A# B-C B-D A-C# A-D# C-D

Neck 00.036

**

2.217

(0.236-3.864)

1.582

(0.938-2.670)

1.356

(0.039-3.237)

0.714

(0.399-1.503)

0.161

(0.017-

1.155)

0.225

(0.024-2.107)

Upper Back 00.027

**

2.604

(0.202-3.733)

1.506

(0.879-2.578)

1.457

(0.238-8.916)

0.579

(0.276-1.211)

0.560

(0.085-

3.673)

0.968

(0.153-6.135)

Lower Back 00.025

**

2.857

(0.172-3.710)

1.387

(0.820-2.347)

1.673

(0.110-4.104)

0.485

(0.218-1.080)

0.235

(0.035-

1.585)

0.485

(0.077-3.072)

Shoulder 00.041

**

1.607

(0.328-2.180)

1.578

(0.932-2.671)

1.438

(0.048-3.988)

0.982

(0.872-2.044)

0.273

(0.028-

2.630)

0.278

(0.030-2.602)

Elbow 00.046

**

3.030

(0.192-4.556)

1.538

(0.897-2.634)

2.558

(0.061-5.084)

0.186

(0.889-1.376)

0.820

(0.089-

2.924)

0.363

(0.039-3.404)

Wrist 00.998

† - - - - - -

Hip 00.987

† - - - - - -

Knee 00.048

**

2.202

(0.231-4.892)

1.413

(0.864-2.395)

2.243

(0.027-3.212)

0.645

(0.298-1.410)

0.114

(0.012-

1.117)

0.172

(0.018-1.615)

Ankle 00.048

**

1.612

(0.305-3.259)

1.518

(0.854-2.696)

1.330

(0.192-2.556)

0.933

(0.418-2.081)

0.930

(0.192-

1.556)

0.186

(0.089-2.376)

* χ2 analysis of prevalence of WMSD symptoms at different body regions with BMI

groups. ** Statistically significant with p < 0.05, † Not significant. #A-Under Weight (Less

than 18.4), B-Normal Weight (BMI=18.5- 24.9), C-Over Weight (BMI



2.406) 2.652) 8.367) 5.760)

Elbow 00.037*

*

1.359

(0.814-

2.269)

0.624

(0.300-

1.301)

2.341

(1.025-

5.349)

0.460

(0.221-0.955)

1.723

(0.756-3.926)

3.750

(1.412-

9.960)

Wrist 00.040*

*

1.176

(0.525-

2.34)

1.260

(0.461-

3.442)

3.694

(1.310-

10.416)

0.544

(0.031-1.909)

1.871

(0.308-3.462)

2.857

(0.914-

8.907)

Hip 00.022*

*

0.744

(0.375-

1.476)

0.318

(0.102-

0.989)

2.276

(0.872-

5.940)

0.433

(0.140-1.336)

2.717

(1.071-6.893)

6.276

(1.729-

22.781)

Knee 00.006*

*

0.692

(0.425-

1.126)

0.422

(0.224-

0.794)

2.012

(0.801-

5.055)

0.609

(0.323-1.151)

2.908

(1.155-7.318)

4.773

(1.742-

13.078)

Ankle 00.039*

*

0.932

(0.538-

1.615)

0.558

(0.255-

1.221)

2.474

(1.067-

5.736)

0.588

(0.268-1.293)

2.396

(1.035-5.550)

4.073

(1.486-

11.169)

* χ2 analysis of prevalence of WMSD symptoms at different body region with different

section of work. ** Statistically significant with p < 0.05, † Not significant. # A-Shelling, B-

Peeling, C- Grading, D-Roasting.

Table 9 Association of WMDS symptoms at different body regions with education.

Body

region P* Value

Comment (at

95% CI) Body region P* Value

Comment (at

95% CI)

Neck 0.103 Not Significant Wrist 0.679 Not Significant

Upper Back 0.392 Not Significant Hip 0.869 Not Significant

Lower Back 0.338 Not Significant Knee 0.114 Not Significant

Shoulder 0.616 Not Significant Ankle 0.178 Not Significant

Elbow 0.352 Not Significant

* χ2

analysis of prevalence of WMSD symptoms at different body regions against

education.

Table 10 Association of WMSD at any of the body region with the physical condition.

Body region P* Value Comment (at 95%

CI) Body region P* Value

Comment (at

95% CI)

Light 0.182 Not Significant Dust 0.021 Significant

Heat 0.011 Significant Odor 0.022 Significant

Noise 0.012 Significant

* χ2 analysis of prevalence of WMSD symptoms at different body regions with physical

condition.

5. CONCLUSION

WMSDs are an important health risk among the cashew industry workers. This study

provides data on the prevalence of WMSDs in the cashew industry workers in the state of

Kerala, India. The present investigation showed that there was a high rate of WMSDs



problems among the workers in all sections of cashew industry. Therefore, it can be

concluded that to improve the working conditions and reduce the WMSDs problems in this

industry, we should be focused on designing of workstations with the application of

ergonomic principles.

ACKNOWLEDGMENTS

The authors express sincere gratitude to the management and the workers of the cashew

industries for their cooperation and support for the completion of this study.

REFERENCES

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WORK-RELATED MUSCULOSKELETAL DISORDERS AMONG CASHEW …€¦ · cashew processing industry situated in Kollam district of Kerala state in India. The socio- demographic factors of