|Author(s) & Year of publication (Country)||Title||Methodology||Theme/focusing point||Findings/outcomes||Limitations||Quality grading|
|Padmini & Venmathi, 2012  (India)||Unsafe work environment in garment industries, Tirupur, India||
Sample size: 514.
Respondents (participated in a face to face confidential interview) were included from 13 small, medium & large scale garment industries for this study.
|To measure correlations between workplace safety issues (i.e. hazards) & health status of the respondents.||
The percentage of experiencing different kinds of hazards (by the RMG workers) which have negative impacts on workers’ health status are given below:|
(a) Ergonomic hazards (e.g. inadequate seating & standing arrangements for the workers, obsolete machinery, improper lifting or movement of heavy loads): 67.5%.
(b) Physical hazards (e.g. noise, lighting problem, electric shock, hot conditions inside the factory, ventilation problems etc.): 34.6%.
(c) Psychological hazards (e.g. monotonous type of work, feeling of risks at workplace, long working hours, lack of recognition etc.): 32.6%.
(d) Mechanical hazards (e.g. fire hazard): 25%.
(e) Chemical hazards (e.g. dust, fumes, mist, smoke etc.): 11.6%.
Respondents were not identified clearly (whether the study respondents were male or female were not clearly mentioned).|
Sampling procedure is not clear.
|Khan et al., 2015  (Bangladesh)||Occupational health hazards among workers of garment factories in Dhaka city, Bangladesh||
Sample size: 145.
Study location: Dhaka.
Purposive sampling procedure was followed.
Structured questionnaire was used to collect the data through face to face interview.
Data were analyzed using SPSS 17.
|To focus on how physical settings (i.e. dirty, inadequate light, noise pollution, overcrowding, problem with safe drinking water, etc.) of factories create health hazards (e.g., headache or shoulder pain, backache, joint pain, eye strain, hearing problem, gastroenteritis, chest pain, breathing difficulty, skin disease, tuberculosis, insomnia etc.) among the respondents.||
Prevalence of occupational health hazards among the respondents: 88.28%.|
Symptoms of health vulnerabilities:
Headache (51%), Joint pain (31%), General weakness (28.3%), Chest pain (26.2%), Backache (24.8%), Gastroenteritis (21.4%), Jaundice (20.7%), Insomnia (20%), Eye strain/problem (13.8%), Hearing problem (8.3%), Skin disease (5.5%), Breathing problem (3.4%), Tuberculosis (2.8%).
Causes identified: Bad physical environment; such as noise pollution (33.8%), problem with safe drinking water (15.9%), overcrowding (13.8%), inadequate light (9.7%), dirty (9%), unavailability of separate toilets (5.5%), inadequate ventilation (4.1%); & dusty raw materials of the factories.
|Psychological health issues are ignored while psychological health is also similarly important such as physical health.||Moderate|
Chumchai et al., 2015 |
|Prevalence and risk factors of respiratory symptoms among home-based garment workers in Bangkok, Thailand||
Sample size: 300.
Male: 66 (22%).
Female: 232 (78%).
Respondents were selected randomly.
Used SPSS for data analysis. Logistic regression analysis was applied to identify risk factors associated with respiratory symptoms.
|To determine the prevalence and risk factors related to respiratory symptoms.||
Prevalence of respiratory problems among the respondents is: 22.3%.|
Common symptoms of respiratory problems:
Abnormal lung function (29.3%)
Nasal congestion (17.3%)
Cough with sputum (1.7%)
Chest tightness (0.03%).
Allergic symptoms: 25.3%.
Causes of respiratory problems/factors associated with respiratory symptoms:
Allergic reaction (61.8%) &
Fabric dust (61.5%).
|Ambiguity about sample size: the abstract and methodology say that the size of respondents is 300, however, Table 1 shows that the sample size is 298 (male: 232; female: 66). RMG factory workers were not included, which could give a broader perspective on the existing respiratory problems of the workers working in the factories.||Strong|
Steinisch et al., 2014 |
|Work stress and hair cortisol levels among workers in a Bangladeshi ready-made garment factory-results from a across-sectional study||
Cross-sectional interview-based study.|
Sample size: 175.
Study location: Dhaka.
Hair Cortisol Concentrations (HCC) were analyzed by liquid chromatography-mass spectrometry.
|To explore associations between work stress (work-related demands, interpersonal resources, & work-related values) & long-term integrated cortisol levels in hair among the respondents.||
Causes of HCC (Hair Cortisol Concentrations):|
(a) Lack of job security, &
(b) Lack of promotion prospects
Lack of job promotion prospect may cause poorer mental health because it is a rare case in RMG sector and requires exceptional job related demands (i.e. promotion prospects are strongly associated with high work stress).
|Only 34% of the respondents, who were interviewed, gave their hair samples. Therefore, the HCC test is questionable.||Strong|
Ahmed & Raihan, 2014 |
|Health status of the female workers in the garment sector of Bangladesh||
Sample size: 200 (female).
Respondents were selected from 15 leading garment factories. Study location: Gazipur, Savar (Dhaka).
Respondents were interviewed using structured questionnaire.
Data were analyzed using SPSS (both descriptive & inferential analyses were done with survey data).
|To show respondents’ experiences of major diseases due to working in the RMG sector of Bangladesh.||
15 diseases were identified that are mainly responsible for health vulnerabilities of the respondents:|
Fever (81.5%), Common cold (79%), Abdomen pain (75.5%), Fatigue (75%), Gastric pain (71.5%), Back pain (68%), Malnutrition (65.5%), Pruritus (59%), Helminthiasis (58%), Dermatitis (57%), Problems in bones (57%), Eye stain/problem (56.5%), Hepatitis (Jaundice) (51.5%), Respiratory problems (46%), Abortion due to retain job (35.5%).
Psychological problem: Trauma (52%).
Causes: unhealthy environment, long working hours, imbalanced diet, & sexual contact.
|Issues on psychological health were not focused broadly & male workers were not included in the study||Strong|
Shanbhag & Bobby, 2012 |
|Mental health status of female workers in private apparel manufacturing industry in Bangalore city, Karnataka, India||
Sample size: 350 (female).
Respondents were selected randomly from 3 units of a private garment factory.
Chi-square test was done.
|To assess factors affecting the mental health status of the respondents.||
Prevalence of mental illness among the respondents: 39%|
Somatic illness (11%)
Social dysfunction (7.1%)
The causes of mental health problems were not explored.|
Male workers were excluded.
Chen et al., 2017 |
|Survey of occupational allergic contact dermatitis and patch test among clothing employees in Beijing||
Sample size: 529.
Respondents were selected from 12 clothing factories through using quota sampling procedure.
Self-administered questionnaire was used for face to face interviewing.
Skin of all respondents were tested by a dermatologist.
|To investigate the prevalence of occupational allergic contact dermatitis and causes of allergy among the respondents.||
Overall 1 year prevalence of occupational allergic contact dermatitis (OACD) among the clothing employees: 8.5%.|
(a) Prevalence among the workers: 10.8%
(b) Prevalence among managers: 3.2%
Locations of skin complaints: Hand/wrists, Forearms, Face/neck, & Trunk.
Causes: Work materials.
Note: OACD is less prevalent among the managers compared to the workers.
|Sampling procedure is not well explained.||Strong|
Steinisch et al., 2013 |
Work stress: its components and its association with self-reported|
health outcomes in a garment factory in Bangladesh-Findings
from a cross-sectional study
Cross-sectional epidemiological study.|
Sample size: 332.
Study location: Dhaka.
|To identify the causes & consequences of work stress among the respondents.||
Self-reported poor health: 41%.|
Cold (51.8%), Headache (48.2%), Back pain (26.2%), Muscle cramps (26%), Sleeplessness (22.3%), Stomach problem (16.3%), Breathing problem (13%), Jaundice (6%).
Components/causes of work stress:
(a) Work related demands: Physical demand (62%), Time pressure (59.6%), Worries about making mistakes (62.3%), Exposure to abusive language (33.4%)
(b) Work related values: Lack of freedom at work (43.1%), Lack of promotion prospects (42.2%), & Lack of job security (38.9%).
|Workers’ feelings of stress/risk, which can be produced from a sudden disaster such as collapse of factory building & fire in the factory building, was not considered in this research.||Strong|
Fatema et al., 2014 |
|Cardiovascular risk factors among Bangladeshi ready-made garment workers||
Sample size: 614.
Respondents were recruited from 6 garments following simple random sampling.
(Epidemiological study conducted through screening of the workers in the medical service centre of EPZ area).
|To estimate the prevalence & identifying the correlation between anthropometry & the clinical risk factor for cardiovascular diseases (CVDs) among the respondents.||
80.6% of the respondents had at least one of the CVDs risk factors.|
Prevalence of CVDs risk factors:
Obesity (27.9%), Overweight (23%), Triglyceride (19.7%), Hypertension (14.5%), Cholesterol (9.1%), Diabetes (7.3%).
• Male workers are vulnerable to hypertension due to excessive smoking habit.
• Female workers are at risks to diabetes due to over-weight & central obesity.
|The causes of CVDs were not addressed in this study.||Moderate|
Makurat et al., 2016 |
|Nutritional and micronutrient status of female workers in a garment factory in Cambodia||
Sample size: 223 (female only).
Used semi-structured questionnaire.
Blood samples of the respondents were tested to obtain nutritional and micronutrient status.
Bivariate analysis was done.
|To examine nutritional, hemoglobin as well as the micronutrient status of the respondents.||
Symptoms of health risks:|
Marginal iron store (46.5%)
Iron deficiency (22.1%).
Self-reported sickness for which respondents took 14 days sick leave:
Respiratory tract infection (45.7%)
The cause of these diseases: Poor nutritional status.
The cause of poor nutritional status: Minimum salaries.
|Exclusion of male respondents is not justified.||Strong|
Fitch et al., 2017 |
|Prevalence and risk factors of depression among garment workers in Bangladesh||
Sample size: 308 (female only).
Study location: Dhaka.
Respondents were purposively chosen for the survey.
Snowball sampling procedure was applied.
Data were analyzed using univariate & multivariate analysis.
|To explore the incidence of depression and its related risk factors among the female garment workers.||
Prevalence of depression (moderate to severe) among the garment workers: 20.9%.|
Risk factors associated with depression (moderate to severe):
Joint pain (44.1%), Anxiety (43.8%), Vision/eye problems (41.9%), Dysuria (41.7%), Insomnia (39.5%), Gout (39.3%), Hypertension (33.3%), Diabetes (31.6%), Asthma (28.6%), Heart attack (25%).
Causes: Work related risk factors such as pat-time work, low income, job insecurity, unhealthy workplace conditions.
|Number of factories, from where data were collected, were not mentioned clearly||Strong|
Hasnain et al., 2014 |
|Morbidity patterns, nutritional status, and healthcare-seeking behavior of female garment workers in Bangladesh||
Sample size: 300 (female only).
Respondents were purposively selected for interviewing using semi-structured questionnaire from 2 factories.
Study location: Dhaka.
Respondents’ heights & weights were measured according to the guideline of WHO.
The Chi-square test was used & data were analyzed by SPSS 16.01.
|To determine female garment workers’ nutritional status, their different types of health-related problems, & healthcare-seeking behavior.||
Prevalence of different kinds of health problems: 53.67%.|
Symptoms & signs:
Underweight (43.33%), Anemia (31%), Anorexia (22.33%), Nausea (14.33%), Fever (11.67%), Epigastric pain (11.33%), Dysmenorrhea (10.33%), Burning micturition (10.67%), Lower abdominal pain (7%), Headache (7.67%), Cough (8%), Runny nose (5.67%), Diarrhea (4.33%), Vertigo (4.67%), Vomiting (4%), Menorrhagia (3%), Leg pain (2.33%).
Causes of more vulnerable to illness: Poor economic status & low educational levels.
• 96% of the underweight respondents had one or more health-related problems in the last three months.
• Only 11.67% of the respondents go to receive healthcare services from the qualified private & government doctors.
Questions regarding malnutrition were not included in the semi-structured interview questionnaire.|
Male workers were excluded from the study.
Parimalam et al., 2007 |
|Knowledge, attitude, practices related to occupational health problems among garment workers in Tamil Nadu, India.||
Cross sectional study.|
Sample size: 216.
Male: 91 (42%).
Female: 125 (58%).
Respondents were selected by following stratified random sampling from 3 different sections (cutting, stitching, & finishing sections) of the garment industry for face to face confidential interview.
The Chi-square test was used to analyze the data.
|To understand the common health problems of the garment workers & to assess their level of awareness about these problems.||
Major types of health problems faced by garment workers from different sections:|
Cutting (18.5%), Stitching (84.7%), Finishing (25%).
(b) Hearing disability:
Cutting (11.1%), Stitching (34.4%), Finishing (6.9%).
Cutting (11.1%), Stitching (9.9%), Finishing (6.9%).
Cutting (84%), Stitching (21.4%), Finishing (10.3%).
(e) Musculoskeletal discomforts:
Cutting (33.3%), Stitching (83.2%), Finishing (34.5%).
Causes of these health problems: Work environment, workstation design, constrained work posture, lack of safety related training & safety tools, & other occupational risk factors such as force, task duration, frequency or repetitiveness of movement etc.
|Comparative discussion on whether the diseases affect men and women workers in different ways could be focused, & comparative discussion on which section’s workers are more vulnerable could also give more apprehended results on the existing health problems of the RMG workers.||Strong|
Rahman & Rahman, 2013 |
|Sickness and treatment: a situation analysis among the garments workers.||
Descriptive type of cross-sectional study.|
Sample size: 522.
Study location: Dhaka.
Respondents were selected using purposive sampling procedure for face to face interviews.
Structured questionnaire was used.
Data were analyzed manually & also using computer.
|To Identify morbidity pattern, duration of illness among garment workers & to determine their treatment seeking behavior during illness.||
79% respondents were suffering from illness during the last 02 months:|
• Female sufferers: 33.6%.
• Male sufferers: 10%.
Symptoms of common illness:
Loose motion (38%), Cough (29%), Breathlessness (28%).
Most diagnosed diseases:
Diarrhea (40.54%), Common cold (22.5%), Respiratory tract infections (15.1%).
No statistical test was done.|
The causes of health vulnerabilities were overlooked.
Akhter et al., 2010 |
|Health and occupational safety for female workforce of garment industries in Bangladesh.||
Sample size: 300 (female only).
Study location: Dhaka.
Data were collected from 20 factories based on questionnaire.
SPSS was used to analyze the data.
|The study focused on the common health problems of the respondents and also the causes of these problems.||
Common health problems:|
Back pain (54%)
Upper back pain (36%)
Eye problem (30%)
Causes of health problems & unsafety at workplace:
Lack of congenial & hygienic working atmospheres, sexual harassment, unavailability of toilet washroom facilities, lack of supply pure drinking water, unawareness of the management regarding safety issues, not enough exit doors.
Exclusion of male workers from the study was not rationalized.|
Data analyses were weak.
Fitch et al., 2015 |
|The prevalence and risk factors of post-traumatic stress disorder among workers injured in rana plaza building collapse in Bangladesh.||
Sample size: 181.
Multivariable logistic regression was used to analysis the data.
|To know the prevalence and risk factors of post-traumatic stress disorder (PTSD) among the Rana Plaza survivors.||
Prevalence of PTSD among the Rana Plaza survivors is: 60.2%.|
Injuries produced from the collapse of Rana Plaza:
Fracture (42.5%), Crush/pressure injury (40.3%), Superficial (26%), Concussion (internal injury) (21.6%), Dislocation/sprain/strain (21%), Amputation (4.4%).
Body parts injured:
Back (51.4%), Lower extremities (47%), Face/head (24.3%), Trunk/internal organ (21.6%), Upper extremities (20.4%), Neck (7.7%), Whole body (1.7%).
|Other diseases/health problems (such as trauma, psychological trauma, nervous breakdown, eye sight problem etc.), except to injuries, produced from the Rana Plaza collapse could also be focused.||Strong|