International Journal of Industrial Ergonomics 82 (2021) 103096
Contents lists available at ScienceDirect 
International Journal of Industrial Ergonomics 
journal homepage: http://www.elsevier.com/locate/ergon 
A preliminary assessment of physical work exposures among electronic 
waste workers at Agbogbloshie, Accra Ghana 
Augustine A. Acquah a,*, Clive D’Souza b, Bernard J. Martin b, John Arko-Mensah a, 
Paul K. Botwe a, Prudence Tettey a, Duah Dwomoh a, Afua Amoabeng Nti a, 
Lawrencia Kwarteng a, Sylvia Takyi a, Isabella A. Quakyi a, Thomas G. Robins c, Julius N. Fobil a 
a Department of Biological Environmental and Occupational Health Sciences, School of Public Health, University of Ghana, Accra, Ghana 
b Center for Ergonomics, Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI, USA 
c Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI, USA   
A R T I C L E  I N F O   A B S T R A C T   
Keywords: Occupational exposure associated with unstructured, informal e-waste recycling has received very limited 
E-waste attention. This study aimed to quantify the occupational physical exposures among informal e-waste workers at 
Informal recycling the largest e-waste site in Africa. 
e-waste collection A cross-sectional field survey of 163 male e-waste workers was conducted using a self-report occupational 
Physical activity exposure 
OPAQ physical activity questionnaire, along with direct work observations, and pedometer estimates of walking activity 
Agbogbloshie for a subset of workers (n = 42). 
Results indicated significant differences in self-reported 7-day work exposures among the three main e-waste 
job categories, namely, collectors (n = 70), dismantlers (n = 73) and burners (n = 20). Prolonged walking, sitting 
and standing on five or more days in the workweek was frequently reported by collectors (87%), dismantlers 
(82%) and burners (60%), respectively. Nearly 90% of collectors and burners and 60% of dismantlers reported 
lifting and carrying on five or more days in the workweek. 
The exposure combinations identified suggest a risk for musculoskeletal disorders (MSDs). Findings call 
attention to the need for research examining potential associations between physical exposures and MSDs 
affecting e-waste workers in Agbogbloshie. The high exposure variability both between and within workers has 
implications for future exposure assessments conducted in unregulated, informal work settings.   
1. Introduction or very close to their end-of-life and end up in dumpsites (Maphosa and 
Maphosa, 2020). Subsequently, sustainable management of these waste 
Electrical and electronic waste (e-waste) poses a new global health in a manner that is environmentally and occupationally safe has become 
challenge (Bakhiyi et al., 2018; Perkins et al., 2014). Rapid technolog- a challenge (Adanu et al., 2020; Bakhiyi et al., 2018). 
ical advances and high demand for new electronic and electrical E-waste recycling activities in middle- and low-income countries is 
equipment has led to accelerated obsolescence and a shorter lifespan for particularly challenging due to the lack of appropriate recycling infra-
modern-day electronic appliances, devices and gadgets (Shamim and structure and policy (Maphosa and Maphosa, 2020). Safe work methods 
Mursheda, 2015). Consequently, managing and recycling the sheer and equipment required for efficient extraction of re-usable and/or 
volume of discarded e-waste has created a global environmental and valuable constituents from old, discarded electronic appliances and 
occupational health problem. Each year, large volumes of e-waste from devices are lacking (Zhang and Xu, 2016). The recycling process is 
Europe and North America get shipped to developing countries such as almost exclusively manual, informal, unregulated and conducted by 
Ghana, Nigeria and South Africa (Maphosa and Maphosa, 2020; Oten- low-skilled workers, with little or no attention to occupational health 
g-Ababio, 2012). While a small fraction of these electronics get put to and safety practices such as the use of personal protective equipment or 
second-hand use, the majority (estimated over 80%) are either unusable properly designed workstations. Manual e-waste recycling is 
* Corresponding author. Department of Biological, Environmental and Occupational Health Sciences, P.O. Box LG 13, School of Public Health, CHS, University of 
Ghana, Ghana. 
E-mail address: aaacquah@st.ug.edu.gh (A.A. Acquah).  
https://doi.org/10.1016/j.ergon.2021.103096 
Received 9 January 2020; Received in revised form 11 October 2020; Accepted 21 January 2021   
Available online 23 February 2021
0169-8141/© 2021 Elsevier B.V. All rights reserved.
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labour-intensive and has become an emerging global health problem skilled workers who engage in non-structured, informal work such as 
due to the health risks it presents (Perkins et al., 2014). Prior studies waste collection and sorting is relatively scarce (Emmatty and Panicker, 
describe manual waste collection as requiring varying levels of manual 2019; Todd, 2009). To date, most studies on occupational exposures to 
material handling (MMH) combined with long periods of sitting and/or injury risk factors have largely focused on formal industrial settings such 
standing in non-neutral postures, and/or walking in unfavourable out- as manufacturing (Bao et al., 2015; Dickerson et al., 2018; Lavender 
door environmental conditions (Emmatty and Panicker, 2019; Kuijer et al., 1999; Marshall et al., 2000; Mossa et al., 2016; Silverstein et al., 
et al., 2010). These forms of physical activities are likely to have adverse 1987), construction (Buchholz et al., 1996; Parida and Ray, 2012), 
effects on the health of workers (Kwon et al., 2011), and more partic- agriculture (Kong et al., 2018) healthcare (Czuba et al., 2012; Janowitz 
ularly when performed under harsh environmental conditions (Kong et al., 2006; Punnett and Bergqvist, 1999; Robertson et al., 2012; Stucke 
et al., 2018). Studies specific to informal e-waste recycling work at and Menzel, 2007) or office work (Armstrong et al., 1994; Wærsted 
worksites in China (Chi et al., 2011), India (Wath et al., 2011), Brazil et al., 2010), to cite only a few. The main focus of these physical work 
(Gutberlet and Baeder, 2008). and Nigeria (Ohajinwa et al., 2018) exposure assessments include quantifying the magnitude of the exposure 
collectively suggest diverse socioeconomic realities and work conditions (e.g., intensity of force exertions, weight of loads carried, non-neutral 
across locations, while highlighting the pervasive problem of informal postures), the repetitions involved, and the duration of the exposure 
e-waste recycling faced by many countries around the world. (Andreas and Grooten, 2018; Chiasson et al., 2012; Li and Buckle, 1999; 
Takala et al., 2010). These physical exposures are predisposing factors to 
1.1. Background on E-waste recycling at agbogbloshie, Ghana the development of work-related MSDs (Eatough et al., 2012; Kuorinka 
et al., 1995; Marras, 2008) and potentially interact with a range of other 
Over the last 20 years, Agbogbloshie in Accra, Ghana, has become organisational, psychosocial and individual factors (Bongers et al., 
one of the largest dumping grounds for electronic waste in the world 2002; Kuorinka et al., 1995; Oakman et al., 2014; Bongers et al., 2002; 
(Heacock et al., 2016), making it one of the most polluted places on Jaffar et al., 2011) to cause or aggravate MSDs. 
earth (Bernhardt and Gysi, 2013; Oteng-Ababio, 2012). E-waste workers A critical aspect of selecting a suitable method for physical exposure 
at this site are among the poorest and the most vulnerable members of assessment is the structure or regularity of the job content. Structured 
the urban populations in Ghana (Akormedi et al., 2013; Amankwaa, work environments such as manufacturing assembly lines are more 
2013). The site is occupied mainly by migrants from the northern part of straightforward to characterize based on a limited amount of exposure 
Ghana. Among them are farmers who have travelled to Southern Ghana data. In contrast, exposure assessment in non-repetitive manual work (i. 
including Agbogbloshie to look for alternate sources of income. The e., where the intensity, repetitions, and duration of the tasks vary over 
primary goal of e-waste recycling at Agbogbloshie is to recover valuable time and between workers) is challenging because the assessments may 
scrap metals such as copper, gold, iron and aluminium for sale (Acquah need to be performed across multiple workers and over long durations in 
et al., 2019; Akormedi et al., 2013). The major processes consist of order to develop a representative profile of the exposure. Thus, assess-
scavenging and collecting e-waste items, then manually dismantling ment of physical work exposures in informal and unstructured work 
irreparable and/or non-functional items, and finally open-air burning of settings often require a preliminary job analysis (Acquah et al., 2019) 
insulated wires and other components that cannot be dismantled in and use of multiple measurement methods in order to understand their 
order to extract valuable metals. Engaging in informal e-waste recycling variability (Neitzel et al., 2013). Methods for quantifying physical work 
at Agbogbloshie is known to adversely affect the health of workers due exposures include self-reported questionnaires, observational methods, 
to high exposure to toxic chemicals (Basu et al., 2016; Feldt et al., 2014; direct measurements (Burdorf and van der Beek, 1999; Li and Buckle, 
Srigboh et al., 2016; Wittsiepe et al., 2015), elevated noise (Akormedi 1999) and biomechanical analyses involving specific tools such as the 
et al., 2013; Burns et al., 2016; Carlson and Krystin, 2016), and harsh NIOSH lifting guide or the University of Michigan’s 3D Static Strength 
environmental conditions (Akormedi et al., 2013; Burns et al., 2016; Yu Prediction Program (Chaffin et al., 2006). Direct measurements and 
et al., 2017). biomechanical analyses provide more accurate results; however, these 
Prior studies on the physical work conditions and work-related methods tend to be expensive (Juul-Kristensen et al., 2001) and their 
physical activity exposures of e-waste workers at Agbogbloshie have application to non-repetitive work settings can be challenging (Chaffin 
only provided qualitative interview-based descriptions (Acquah et al., et al., 2006). Compared to direct measurements, assessments relying on 
2019; Akormedi et al., 2013; Yu et al., 2017). These studies offer observational methods and self-reported questionnaires are more 
evocative summaries of the physical work conditions and various cost-effective and easier to implement in applied settings, and thus are 
work-related illnesses and injuries. For example, a recent qualitative still widely used despite their subjective nature and lower accuracy and 
study by Acquah et al. (2019) reported both acute injuries (e.g., burns, precision (Takala et al., 2010). 
lacerations) and chronic health issues such as musculoskeletal pains, 
coughs, and headaches across the three main categories of e-waste 1.3. Study aims 
workers: collectors, dismantlers and burners. The adverse work-related 
health effects were compounded by the lack of use of personal protec- The primary aim of this study was to quantify the occupational 
tive equipment, low level of health risk awareness, and by evidence of physical activity (OPA) exposures of e-waste workers engaged in 
psychosocial stressors associated with e-waste recycling. The latter in- informal e-waste recycling at Agbogbloshie, and to compare these ex-
cludes psychological demands, poor social support, low income, and posures among the three main e-waste job categories, namely, collec-
limited opportunities for other types of gainful employment (Acquah tors, dismantlers and burners. 
et al., 2019; Akormedi et al., 2013; Yu et al., 2017). However, reliable 
quantitative data on the nature of the physical exposures at the 2. Methods 
Agbogbloshie work site is lacking. Hence, we undertook an initial step to 
quantifying these physical work exposures in order to understand the 2.1. Study site and population 
magnitude of the risk of developing work-related musculoskeletal dis-
orders (MSDs) towards the longer-term goal of developing appropriate The Agbogbloshie e-waste site is about 0.5 km2 (Laskaris et al., 
ergonomic interventions adapted to the local context. 2019). It is located close to the central business district of Accra 
(Oteng-Ababio, 2012) near the Agbogbloshie food market, and along the 
1.2. Occupational exposure assessment in informal work banks of the Korle lagoon and Odaw river (Davis et al., 2019). The 
workforce largely consists of itinerant workers who collect scrap metal 
Ergonomics studies on occupational physical exposures among low- and e-waste items, dismantle items to extract valuable constituents and 
2
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burn items that cannot be dismantled (Davis et al., 2019). The workers indicated that their estimation of the proportion of time spent sitting, 
are almost exclusively males, primarily young adults and occasionally standing and walking or performing MMH activities was not reliable 
minors (<18 years old). (poor estimation of exact time), the questionnaire was modified to 
obtain a binary response (Yes/No) to whether each activity was per-
2.2. Study design formed for (1) at least 1 h continuously during the workday, and (2) a 
total of 4 h in a workday. Second, the frequencies of work-related 
A cross-sectional study involving the use of a questionnaire, sup- standing and walking were assessed separately as opposed to the orig-
plementary field observations, and pedometry measurements was con- inal OPAQ which assesses standing and walking together. Third, the 
ducted between August to October 2018. Direct field observations were assessment of MMH activities (labelled “heavy labour” in the original 
conducted on random days throughout the study period in order to OPAQ), which form the core component of e-waste recycling, was 
contextualize and supplement the data obtained from questionnaires assessed by asking participants to rate on an ordinal scale how often they 
and direct field measurements. E-waste workers were recruited for the performed lifting, carrying, and pushing and/or pulling activities within 
study by word of mouth. They were recruited from different locations of a workweek. The modified version of the OPAQ (Appendix-A) was 
the site in an attempt to obtain a diverse sample in terms of job category administered to the participants, their verbal responses were docu-
(i.e. collecting, dismantling and burning). Following a verbal descrip- mented on the paper questionnaire by the researcher, and subsequently 
tion of the study objectives and methods, a self-selected sample of 163 coded into Stata V15 for analysis. When responding to the question-
male e-waste workers agreed to participate in the study. Written naire, participants were instructed to use the full workweek prior to 
informed consent was obtained from all adult participants. For minors, when the questionnaire was presented as the reference period (i.e., a 
written informed consent was obtained from the adult relatives they 7-day period starting Monday morning). 
work with or their immediate adult work supervisors. These work su-
pervisors typically served as guardians for the minors while they were at 2.3.3. Pedometer measurements 
the e-waste site. From the 163 participants, a random subset of 47 participants were 
The study was approved by the College of Health Sciences Ethical provided a waist belt instrumented with a pedometer (Omron HJ-321) at 
Review Committee at the University of Ghana, Accra. Participants were the start of their workday and collected at the end of the workday for 
compensated 30 Ghana Cedis (approximately 5.26 US dollars) after data two consecutive workdays randomly selected in the study period. The 
collection was completed. average readings from both workdays were used in the analysis. Ten 
pedometers were acquired for the study; however, 5 pedometers were 
2.3. Assessment tools not returned by participants early in the study. Thus, data collection was 
limited to using 5 pedometers. This also caused a decrease in sample size 
2.3.1. Demographic questionnaire from 47 down to 42 of 163 participants equipped with a pedometer on 
A brief questionnaire was developed to obtain information about two consecutive workdays. Overall, pedometry data obtained from 9 
demographic characteristics (e.g., age, gender), primary job category, collectors, 27 burners and 6 dismantlers were used in data analysis. The 
main work activities performed, and work history of participants (e.g. pedometers provided data about total steps count, aerobic step counts, 
number of years and/or months having worked in e-waste recycling, average steps per minute, distance walked, and energy expenditure 
average number of days and hours of work per week). A team of 5 re- (kilocalories; kcal) over an entire workday. Aerobic steps were recorded 
searchers serving as interviewers fluent in English as well as Dagbani, whenever a minimum of 60 steps were taken within a 10-min period 
which is the local dialect spoken by e-waste workers, administered the (Duchečková and Forejt, 2014). The Omron pedometer has been vali-
questionnaire and recorded participant responses on paper. In addition dated against other well-known physical activity monitors (Battenberg 
to the questionnaire, participants’ weight, stature, and stride length et al., 2017; Kendall et al., 2019) and has an accuracy greater than 90% 
were measured and used later to calibrate the pedometers used in the for measuring step counts (Battenberg et al., 2017). This specific 
measurement of cumulative step counts. Stride length was computed pedometer model has been used widely in other studies that monitored 
using procedures recommended by the device manufacturer, namely, by physical activity (Olzenak and Byrne, 2017; Owoeye et al., 2016; Sam-
measuring the total distance walked for 10 steps (i.e., measured from the paio et al., 2016; Yusoff et al., 2018). 
heel of the foot taking the first step to the toe of the foot taking the last 
step) and dividing the distance by 10 (Omron, 2019). 2.4. Statistical analysis 
2.3.2. Modified occupational physical activity questionnaire (OPAQ) All measures were analysed using the Stata V15 software package 
The OPAQ (Reis et al., 2005), which is a seven-item survey ques- (StataCorp LLC, TX). Descriptive statistics were used to summarise de-
tionnaire, was used to collect information on the average time spent per mographic variables and the proportion of workers who performed 
week in work-related sitting or standing, walking, and in performing different types of OPA. Separate one-way ANOVA tests were used to 
heavy labour activities such as lifting, carrying, pushing and pulling. For examine statistical differences in age, years on the job, days worked per 
the purposes of this study, we collectively refer to lifting, carrying, week, and hours worked per day across the three primary job categories 
pulling and pushing activities as MMH in place of the less common term (i.e., collectors, dismantlers, and burners). Separate Chi-square (χ2) tests 
‘heavy labour activities’ used in the OPAQ. Modelled on questions from were conducted to examine differences in the proportion of participants 
the OPAQ and Quick Exposure Checklist (QEC; Stanton et al., 2004), by primary job category that reported long durations of sitting, standing, 
participants were also asked to indicate the maximum weight handled in and walking postures, frequent MMH activities of lifting, carrying, 
the workweek during MMH on an ordinal scale as either light (5 kg or pushing and/or pulling, and maximum load handled, which were 
less), moderate (6–10 kg), heavy (11–20 kg), or very heavy (>20 kg). assessed on ordinal rating scales. Significant main effects of job category 
Participants were considered quite adept at estimating weight since they were further analysed using Chi-square pairwise tests with a Bonferroni 
often weigh e-waste items to determine its financial value (i.e., price adjustment for multiple comparisons (p < 0.05). Pedometer measure-
when buying or selling) as part of their typical workflow. A pilot study ments (total and aerobic step counts, steps per minute, distance walked, 
was conducted in December 2017 to determine the feasibility of using and energy expenditure) were not normally distributed, and thus me-
the OPAQ, specifically, to determine whether participants understood dians and interquartile ranges (IQR) were reported in order to reduce 
the questions and could respond appropriately to obtain the desired the influence of data outliers. Separate non-parametric Kruskal-Wallis 
information. Based on the results and feedback from 15 e-waste workers, tests were used to examine significant differences across the three e- 
three modifications to the OPAQ were implemented. First, since workers waste job categories for each of the five pedometer measures. 
3
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Qualitative data obtained from direct observations were used to sup- category (p = 0.013). Years of e-waste work experience was significantly 
plement and contextualize the quantitative results where possible. higher among dismantlers (7.9 ± 5.4) compared to collectors (5.3 ± 5.7; 
p = 0.014) and burners (5.5 ± 3.2; p = 0.176). There was no significant 
3. Results difference in the average number of workdays per week (p = 0.292) or 
average hours worked per day (p = 0.277) among the three categories of 
3.1. Participant demographics e-waste workers (Table 1). 
The age of participants ranged from 11 years to 43 years. Of the 163 3.2. Occupational physical exposures of E-waste workers 
participants, 25 (15.3%) were minors while 6 (3.6%) did not know their 
age. The majority of participants (63.1%) were in the 18–29 years age 3.2.1. Sitting, standing and walking 
range. Only 6 participants (3.8%) out of those knowing their age were Direct field observations indicated that all of the participants per-
older than 40 years. Work experience represented as the number of years formed their work while either sitting, standing or walking during the 
worked in e-waste recycling ranged from 1 week to 25 years with an workday. The corresponding proportions are detailed after the following 
average ± standard deviation (SD) of 6.48 ± 5.44 years. Participants contextual description to contrast with what is usually assumed in 
worked for at least 2 days in a week but the majority reported working at regulated industrial work. Dismantlers were observed usually sitting on 
least 6 days (88%) or 7 days (54%) per week. The mean ± SD reported a very low stool or a dismantled appliance such as an old cathode ray 
work duration per day was 9.95 ± 2.43 h and ranged from 2 h to 14 h tube television or microwave oven. Hence, sitting was more of a 
depending on the availability of work and the type of e-waste recycling squatting posture such that the included angles at the knees and hips 
activity performed. Direct field observation data revealed an were less than 90◦. Observations also revealed a diverse range of sitting 
average ± SD work duration of 6.26 ± 2.63 h per day with a range of durations between dismantlers. When not walking to search for and 
2–12 h per day with intermittent breaks that varied considerably from collect items, the collectors’ mode of sitting varied widely. It involved 
10 min to about 4 h such as when waiting for recycling products from sitting on their collection cart that corresponded to a sit-stand posture 
other e-waste workers (i.e., from collectors to dismantlers, or from dis- with the included angle at the hips and knees exceeding 90◦. Collectors 
mantlers to burners). also occasionally sat on the ground or on a piece of log or rock along the 
Based on the primary job performed, 70 (42.9%) of the participants route travelled in search of e-waste. A considerable amount of sitting 
were categorized as collectors, 73 (44.8%) as dismantlers, and 20 was observed during workers idle time. Dismantlers and burners took 
(12.3%) as burners. A few of these participants also reported performing rest breaks seated under a shed after they exhausted their stock of items 
tasks associated with a secondary job category. For instance, 9 collectors to dismantle or burn and waited for supplies. Collectors were also 
(5.5%) engaged in occasional dismantling of e-waste, 3 collectors (1.8%) observed sitting to rest at random intervals and for varying durations 
and 2 dismantlers (1.2%) also reported performing burning-related while in search of e-waste in nearby communities. For all workers, 
tasks. Due to the small number of such cases, only the primary job standing and walking were done on uneven surfaces. These surfaces 
category was used in the subsequent statistical data analysis. were soft and muddy during rainy periods or hard and bumpy during the 
Table 1 summarizes the age distribution, the number of years of dry season. Walking performed by dismantlers was primarily for trans-
experience in e-waste work, number of workdays per week and hours of porting insulated components, cables, and wires to the burners for the 
work per day stratified by the three e-waste job categories. Collectors extraction of metal, e.g., gold, copper, aluminium. Due to toxic fumes 
had the broadest age range (11–43 years). Notably, all the minors in the generated during open-air burning this task was done at short distances 
study were collectors. The average age differed significantly by job away from the sites where dismantling and other ancillary tasks of 
category (p = 0.004). The mean age was significantly higher for dis- weighing and selling of e-waste products were performed (Laskaris 
mantlers (26.7 ± 6.6 years) compared to collectors (23.4 ± 6.2; et al., 2019; Nti et al., 2020; Takyi et al., 2020). In addition to burning 
p = 0.007) and burners (22.8 ± 3.9; p = 0.055). Years of work experi- insulated copper wire for dismantlers at a fee, some burners also spent 
ence in e-waste recycling also differed significantly by the primary job time in extreme torso flexion picking and gathering leftover pieces of 
metal scrap littered across the burning sites for sale. This was observed 
more commonly among entry-level burners. 
Table 1 
Participant primary job category and demographic characteristics.  Table 2 summarizes the proportion of collectors, dismantlers and 
burners who reported engaging in sitting, standing or walking for 1 h or 
Variable Job Category Range Mean ± SD ANOVA more continuously in a workday, and separately for a total of 4 h or more 
(n) results in the workday during the previous workweek. Sitting continuously for 
Age in years Collectors 11–43 23.4 ± 6.2 F = 5.77, p = ≥1 h in a workday was reported mostly by dismantlers (91.8%) while 
(69) 0.004 * 
Dismantlers 18 42 26.7 6.6 standing continuously for ≥ 1 h during a workday was reported mostly – ±
(70) by burners (95%). Chi-square test of proportions indicated no statisti-
Burners (18) 18–30 22.8 ± 3.9 cally significant differences in the proportion of participants across the 
Years of work at e- Collectors 0.02 5.3 5.7 F 4.45, p three job categories who reported sitting (p = 0.119) or standing ± = =
waste site (70) (1wk) - 22 0.013 * (p = 0.070) continuously for ≥ 1 h in a workday. However, the propor-
Dismantlers 1–25 7.9 ± 5.4 tion of participants who reported ≥1 h of continuous walking differed 
(73) significantly (p = 0.018) across job categories. Post hoc comparisons 
Burners (20) 1–13 5.5 ± 3.2 revealed that the proportion of participants reporting continuous 
No. of workdays Collectors 4–7 6.3 ± 0.7 F = 1.24, walking ≥1 h in a workday was significantly higher for collectors 
per week (70) p = 0.292 (92.9%) compared to dismantlers (78.1%; p = 0.038) but not signifi-
Dismantlers 2–7 6.1 ± 1.0 
(73) cantly different from burners (75.0%). 
Burners (20) 2–7 6.0 ± 1.1 The proportion of participants that spent ≥4 h per workday sitting, 
No. of working Collectors 6–14 10.3 1.8 F 1.30, standing and walking differed significantly by job category (p < 0.001) ± =
hours per day (70) p = 0.277 for each of the three postures (Table 2). The proportion of participants 
Dismantlers 4–14 9.8 ± 2.9 that reported sitting for ≥4 h was significantly higher for both dis-
(71) mantlers (82.2%) and burners (65.0%) compared to collectors (30.0%; 
Burners (20) 2–12 9.4 ± 2.7 p < 0.001 and p = 0.013, respectively). The difference in proportions 
* indicates significance at p < 0.05. between dismantlers and burners was not statistically significant 
4
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Table 2 e-waste site to assist other workers until they gained some experience 
Proportion of e-waste workers stratified by job category engaged in work-related and accumulated enough capital prior to working independently. Loads 
sitting, standing and walking activities.  handled by dismantlers mainly consisted of the weight of items being 
Variable Job Proportion of Chi-square dismantled and occasionally the weight of the wheelbarrow used to 
Category (n) participants statistic and p- convey items such as insulated metal components and wires to the 
value 
Yes (%) No (%) burning site for metal recovery. Manual dismantling also involved re-
2 petitive forceful exertions in non-neutral postures using tools such as Sitting continuously Collectors 56 14 χ = 4.487, 
for ≥ 1 h during a (70) (80.0%) (20.0%) p = 0.106, hammers, chisel and screwdrivers. The load handled by burners was 
workday Dismantlers 67 6 (8.2%) Fisher’s exact mainly from the weight of components (e.g., insulated cables, wires) 
(73) (91.8%) p = 0.119 being burnt. Lifting and carrying among burners involved using a long 
Burners (20) 18 2 metal rod to lift and flip wires/cables during burning. This was usually 
(90.0%) (10.0%) done with the trunk in slight flexion. Occasionally, burners would lift, 
Standing Collectors 53 17 χ2 = 4.881, carry and lower items from a wheelbarrow onto the ground for burning 
continuously (70) (75.7%) (24.3%) p = 0.087, and this involved moderate to severe forward flexion of the trunk for 
for ≥ 1 h during a Dismantlers 52 21 Fisher’s exact 
workday (73) (71.2%) (28.8%) p = 0.070 short intervals. 
Burners (20) 19 1 (5.0%) Table 3 summarizes the proportion of participants by job category 
(95.0%) based on their self-reported frequency of performing the three different 
Walking Collectors 65 5 (7.1%) χ2 = 7.211, MMH activities, namely, lifting, carrying, and pushing-pulling in the 
continuously (70) (92.9%) p = 0.027, previous workweek. Chi-square test of proportions indicated statistically 
for ≥ 1 h during a Dismantlers 57 16 Fisher’s exact p significant differences across job categories for each of the three MMH 
workday (73) (78.1%) (21.9%) = 0.018* activities (p < 0.001). In term of lifting activities, a high proportion of 
Burners (20) 15 5 
(75.0%) (25.0%) collectors (91.2%) and burners (94.1%) reported performing lifts on ≥ 5 
2 days in a week compared to dismantlers (65.8%), with the difference Sitting for a total of Collectors 21 49 χ = 40.376, 
≥4 h during a (70) (30.0%) (70.0%) p 0.001, between collectors and dismantlers being statistically significant =
day’s work Dismantlers 60 13 Fisher’s exact p (p = 0.001). In contrast, the proportion of dismantlers that reported 
(73) (82.2%) (17.8%) = 0.001* lifting activities 3–4 times a week (24.7%) was significantly higher than 
Burners (20) 13 7 collectors (4.4%; p = 0.001). Carrying activities on ≥ 5 days per week 
(65.0%) (35.0%) were performed mostly by collectors (91.2%) compared to burners 
Standing for a total Collectors 13 57 χ2 = 19.384, (82.4%) and dismantlers (62.5%), with the difference between collec-
of ≥4 h during a (70) (18.6%) (81.4%) p = 0.001, tors and dismantlers being statistically significant (p < 0.001). However, 
day’s work Dismantlers 36 37 Fisher’s exact p 
(73) (49.3%) (50.7%) 0.001* the proportion of participants that reported carrying on 3–4 days a =
Burners (20) 12 8 weeks was significantly higher among dismantlers (22.5%) compared to 
(60.0%) (40.0%) collectors (2.9%; p = 0.001). Pushing and/or pulling of a hand-drawn 
Walking for a total Collectors 62 8 χ2 = 19.961, cart on ≥ 5 days per week was significantly more frequent among col-
of ≥4 h during a (70) (88.6%) (11.4%) p = 0.001, lectors (68.2%) compared to dismantlers (26.4%; p < 0.001) and 
day’s work Dismantlers 40 33 Fisher’s exact p burners (26.3%; p = 0.003). The proportion of burners that reported 
(73) (54.8%) (45.2%) = 0.001* infrequent or no pushing/pulling activities (63.2%) was significantly 
Burners (20) 13 7 
(65.0%) (35.0%) higher than the proportion of collectors (28.8%; p = 0.018). 
Table 4 summarizes the number and proportion of participants 
* indicates significant main effects at p < 0.05. stratified by their self-reported level of maximum weight handled during 
the prior workweek coded on an ordinal scale from light (≤5 kg) to very 
(p = 0.204). The proportion of participants that reported standing for heavy (>20 kg). Over 86% of all study participants reported handling an 
≥4 h was also significantly higher among dismantlers (49.3%) and object weighing heavier than 20 kg (i.e., labelled ‘Very heavy’). Results 
burners (60.0%) compared to collectors (18.6%; p < 0.001 and from the Chi-square test of proportions indicated a statistically signifi-
p = 0.001, respectively). In contrast, walking for a >=4 h was reported cant difference among job categories in the level of maximum weight 
at a higher proportion by collectors (88.5%) compared to both dis- handled (p = 0.011). The proportion of participants that reported 
mantlers (54.8%; p < 0.001) and burners (65%; p = 0.038). Differences handling weights heavier than 20 kg was significantly higher for col-
in proportions between dismantlers and burners for both prolonged lectors (95.6%) compared to dismantlers (81.9%, p = 0.034) and 
standing and walking were not statistically significant (p > 0.05). burners (68.4%, p = 0.002). The proportion of participants that reported 
handling moderate weights between 6 and 10 kg was significantly 
3.2.2. Manual material handling activities higher for burners (15.8%) compared to collectors (1.5%, p = 0.025). 
Manual material handling activities identified by direct observations None of the other paired comparisons within weight category were 
included lifting and carrying of loads as well as pushing and pulling statistically significant. 
hand-drawn carts used for transporting e-waste. Descriptions of obser-
vations are followed by quantitative results. The frequency and magni- 3.2.3. Pedometer measurements 
tude of the load handled differed between tasks and job categories. Table 5 summarizes the median and IQR values for regular steps, 
Loads handled by collectors included the force to tow or move the hand- aerobic steps, steps per minute, distance covered and energy expendi-
drawn collection cart, which is a function of the design of the cart used, ture (kcal) among the subset of collectors, dismantlers and burners. 
the load on the cart, and the terrain (Jung et al., 2005). The weight of the Kruskal-Wallis tests indicated no statistically significant differences 
cart and the items collected varied from day to day as a function of items across the three job categories for any of the five pedometer measures 
identified for recycling. Collectors also lifted and carried items when (p > 0.05). The small sample sizes for collectors (n = 9) and burners 
loading and unloading the cart. All 25 (15.3%) minors in the study (n = 6) may have contributed to reduced statistical power in detecting 
self-identified as collectors. These minors were observed walking behind any differences. The median number of regular and aerobic steps were 
their supervisors, typically an older or senior worker, pushing the slightly higher for collectors than burners and dismantlers (Table 5), 
hand-drawn cart from the rear as the senior worker pulled the cart from while the median aerobic step count was lowest (zero) for dismantlers. 
the front. It is typical for younger entry-level workers arriving at the The median distance walked by participants in each category was 5.4 km 
5
A.A. Acquah et al.                                                                                                                                                              I n t  e r n  a  t i o  n a  l  J  o u  r n  a  l  o  f  I n  d u  s t r  i a l  E  r  g o  n  o m   i c s 82 (2021) 103096
Table 3 
Self-reported frequency of manual material handling activities related to e-waste work performed by participants and stratified by job category within a workweek.  
Activity type Job Category (n) None or rarely 1–2 days per week 3–4 days per week ≥5 days per week Chi-square statistic & p-value 
Lifting Collectors (68) 1 (1.5%) 2 (2.9%) 3 (4.4%) 62 (91.2%) χ2 = 20.524, p = 0.002, 
Dismantlers (73) 0 (0.0%) 7 (9.6%) 18 (24.7%) 48 (65.8%) Fisher’s exact p = 0.001* 
Burners (17) 0 (0.0%) 1 (5.9%) 0 (0.0%) 16 (94.1%) 
Carrying Collectors (68) 0 (0.0%) 4 (5.9%) 2 (2.9%) 62 (91.2%) χ2 = 26.656, p < 0.001, 
Dismantlers (72) 2 (2.8%) 9 (12.5%) 16 (22.2%) 45 (62.5%) Fisher’s exact p < 0.001* 
Burners (17) 2 (11.8%) 1 (5.9%) 0 (0.0%) 14 (82.4%) 
Pushing and/or Pulling Collectors (66) 19 (28.8%) 0 (0.0%) 2 (3.0%) 45 (68.2%) χ2 = 37.053, p < 0.001, 
Dismantlers (72) 32 (44.4%) 15 (20.8%) 6 (8.3%) 19 (26.4%) Fisher’s exact p < 0.001* 
Burners (19) 12 (63.2%) 1 (5.3%) 1 (5.3%) 5 (26.3%) 
* indicates significant main effects at p < 0.05. 
mostly descriptive accounts (Acquah et al., 2019; Akormedi et al., 2013; 
Table 4 Yu et al., 2017), which although insightful, failed to provide meaningful 
Number and proportion of participants reporting different categories of 
maximum weight handled within a workweek, stratified by job category.  quantitative information about the source and magnitude of physical 
activity exposures. The latter is necessary to enable comparisons with 
Job Maximum weight handled, n (%) Chi-square other work settings and/or other informal e-waste recycling sites in 
Category statistic & 
(n) Light (< Moderate Heavy Very p-value developing countries, to estimate the potential for developing MSDs, 
5 kg) (6–10 kg) (10–20 kg) heavy and to guide the design and implementation of tailored ergonomics in-
(> 
20 kg) terventions (e.g., engineering controls, health and safety policy, worker 
training). More broadly, the study adds to the growing knowledge-base 
Collectors 0 (0.0%) 1 (1.5%) 2 (2.9%) 65 χ2 = 15.686, documenting exposure of e-waste workers at Agbogbloshie to various 
(68) (95.6%) p = 0.016, 
Dismantlers 2 (2.8%) 5 (6.9%) 6 (8.3%) 59 Fisher’s occupational hazards such as toxic chemicals, air pollutants, and noise 
(72) (81.9%) exact p = (Akormedi et al., 2013; Basu et al., 2016; Srigboh et al., 2016; Wittsiepe 
Burners (19) 2 3 (15.8%) 1 (5.3%) 13 0.011* et al., 2015; Yu et al., 2017). 
(10.5%) (68.4%) Our results corroborate qualitative findings by Akormedi et al. 
* indicates significant main effects at p < 0.05. (2013) and Yu et al. (2017) about e-waste worker characteristics, the 
challenging work environment, and the physically strenuous work 
for collectors, 4.9 km for burners and 3.2 km for dismantlers, respec- conditions prevailing at Agbogbloshie. We discuss the ergonomics im-
tively. The median calorie expenditure from walking was marginally plications of these findings. 
higher for burners (190 kcal) compared to collectors (170 kcal) and 
dismantlers (122 kcal), however the small sample sizes for collectors and 4.1. E-waste workers 
burners make their respective median estimates relatively unstable. 
Participants in this study were mostly collectors (43%) and dis-
4. Discussion mantlers (45%), while burners comprised only 12% of the study sample. 
The latter may have reduced statistical power in pair-wise comparisons 
This study quantified the OPA exposures of e-waste workers at of proportions involving burners for some of the exposure variables, e.g., 
Agbogbloshie with an emphasis on differences among the three main between collectors and burners for continuous walking ≥1 h. Differ-
categories of workers, namely, collectors, dismantlers, and burners. ences in job content and financial prospects may explain the smaller 
Notably, the results indicated that the type and level of self-reported number of burners at Agbogbloshie and in our study sample. Akormedi 
exposures vary substantially between and within worker categories. et al. (2013) reported that burners earned substantially less income per 
Despite its preliminary and cross-sectional nature, this study is only one day compared to collectors and dismantlers (i.e., USD 16 compared to 
of few conducted at Agbogbloshie, Ghana that focuses on the physical USD 26 and USD 52 respectively, on a good day). The reliance on dis-
demands of informal e-waste recycling. Prior exposure studies were mantlers to provide items for burning and the high exposure to smoke 
Table 5 
Pedometer measurements obtained from a sub-set of study participants (n = 42) averaged over 2 workdays and stratified by job category.  
Variable Job Category Median Lower Quartile Upper Quartile Kruskal-Wallis test 
Total Step Count Collectors (9) 9482 5282 10812 χ2 = 3.688, p = 0.158 
Dismantlers (27) 5556 3504 8412 
Burners (6) 8964 5042 9870 
Aerobic Step Count Collectors (9) 1531 0 2756 χ2 = 3.526, p = 0.172 
Dismantlers (27) 0 0 1520 
Burners (6) 607 0 1883 
Steps per minute Collectors (9) 91.3 0 102.1 χ2 = 2.859, p = 0.240 
Dismantlers (27) 0 0 97 
Burners (6) 47.1 0 101.2 
Distance (km) Collectors (9) 5.4 3.0 5.9 χ2 = 4.049, p = 0.132 
Dismantlers (27) 3.2 2.0 4.6 
Burners (6) 4.9 3.0 5.4 
Energy expenditure (kcal) Collectors (9) 170 95 296 χ2 = 3.334, p = 0.189 
Dismantlers (27) 122 71 182 
Burners (6) 190 107 207  
6
A.A. Acquah et al.                                                                                                                                                              I n t  e r n  a  t i o  n a  l  J  o u  r n  a  l  o  f  I n  d u  s t r  i a l  E  r  g o  n  o m   i c s 82 (2021) 103096
and toxic fumes from open air burning made this task less appealing to potentially valuable metal scrap and remnants littered about the 
workers (Acquah et al., 2019; Akormedi et al., 2013). Workers at this burning sites. Overall, the lack of temporal structure and definitive roles 
site did not have assigned roles or designations. On few occasions, presents methodological challenges when comparing exposures across 
participants reported performing e-waste recycling activities other than time or between work sites and work domains (e.g., manufacturing, 
their primary job. For example, a dismantler who did not have enough office work). 
items to dismantle may temporarily assume the role of collector and 
walk/travel into the community in search of more e-waste items to 4.2. Occupational physical exposures 
dismantle. Likewise, a burner who did not have items to burn may as-
sume a dismantling role by helping other dismantlers to disassemble Participants’ exposures to sitting, standing, walking and MMH ac-
their items for a small fee or in exchange for some of the extracted metal tivities differed substantially by the primary job category. Particularly 
(e.g., copper wires). Since such secondary activities were infrequent and concerning were the high proportion of workers that reported exposure 
with limited impact on exposure estimates in the present context, these durations ≥4 h in the workday (e.g., prolonged sitting, standing, 
were not distinguished or differentiated in the present study. However, walking) and frequent exposure to lifting and carrying on ≥ 5 days per 
the potential for fluid roles wherein worker change their main activities week. The health implications of these specific combinations of expo-
(and hence related exposures) on their own over time may have impli- sures and job category are discussed in relation to prior research. 
cations for prospective longitudinal studies. However, we advise caution for direct comparisons with activity ques-
Our study also confirmed prior reports that e-waste recycling at tionnaires from other work settings since most studies base their expo-
Agbogbloshie is performed mainly by men (Akormedi et al., 2013). The sures on an 8-h workday and/or a 5-day workweek (e.g. Reis et al., 
absence of women has been attributed to the high physical demands of 2005). 
manual e-waste recycling and a preference for less strenuous supportive 
roles such as vending food and water to workers (Ahlvin, 2012). The 4.2.1. Sitting 
worker population at this site was also relatively young (mean age of Prolonged sitting was most frequent among dismantlers (Table 2), 
24.8 years) and included 25 minors (15.3%). All minors in the study who assumed largely deviated postures from sitting on a low stool or 
sample were collectors and assisted older workers in scavenging and non-functional appliance, with excessive forward flexion and twisting of 
gathering e-waste items. The substantial proportion of minors working the trunk while performing their task. Prolonged sitting (Hoogendoorn 
at the site is particularly concerning since Ghana is a signatory to mul- et al., 1999), and in non-neutral postures (Roffey et al., 2010) have been 
tiple international instruments that prohibit child labour (UNICEF, associated with chronic low back pain. Biomechanical studies have also 
2019). Our finding suggests broader concerns about poorly enforced shown possible adverse effects on spinal structures from sustained 
legislation and policies prohibiting child labour. UNICEF-Ghana esti- non-neutral trunk postures (Chaffin et al., 2006). Sitting for long periods 
mates that about 21% of children in Ghana aged between 5 and 17 years at work changes the activation patterns of a number of weight-bearing 
were involved in child labour and 14% were engaged in hazardous forms muscles, which in the long term affects the curvature of the back 
of labour (UNICEF, 2019). However, the problem of child labour is not resulting in back pain (Beach et al., 2005; Callaghan and McGill, 2001). 
unique to Agbogbloshie but plagues waste picking/collecting in many Prolonged sitting is also associated with lower bone mineral density due 
developing countries around the world (ILO, 2004). to a limited physical stress (see Chaffin et al., 2006) and osteoporosis 
The experience level of workers recruited for this study varied from (Kolbe-Alexander et al., 2004). Thus, prolonged sitting among e-waste 
as little as 7 days to as high as 22 years. Experience in e-waste recycling dismantlers could increase their risk of work-related low back pain and 
work for the study cohort was least among collectors (5.3 ± 5.7 years) disorders, as suggested by the high prevalence of low back disorders 
and highest among dismantlers (7.9 ± 5.4 years). Prior studies suggest among informal waste collection and processing workers (Emmatty and 
that low-skilled migrants from northern Ghana seeking a means of Panicker, 2019; Ohajinwa et al., 2018). 
livelihood were often drawn to e-waste recycling at Agbogbloshie and 
often start out as collectors (Akormedi et al., 2013). These collectors 4.2.2. Standing 
overtime progress to more technical and lucrative roles of e-waste Standing at work may be advantageous to the worker in that it 
recycling such as dismantling. Collecting of e-waste requires extensive provides a large degree of freedom and ensures a wide range of mobility 
walking (e.g., over 75% of collectors performed over 10,000 steps daily) in the lower limb thereby increasing efficiency and productivity (Halim 
with a low prospect of obtaining e-waste items on any day, as observed and Rahman Omar, 2011). That notwithstanding, prolonged standing 
in this study. may also lead to muscle fatigue and discomfort (Garcia et al, 2015, 
E-waste recycling was performed every day of the week. Most par- 2016, 2018, 2020), chronic venous insufficiency and other occupational 
ticipants worked six days per week and rested either on Fridays or injuries (Garcia et al, 2015, 2016, 2018, 2020; Lafond et al., 2009; 
Sundays. Akormedi et al. (2013) suggested that rest days may corre- Madeleine et al., 1997; Tomei et al., 1999). E-waste recycling activities 
spond to workers religious affiliation with Muslims more likely to take such as burning involve a considerable amount of standing (see Table 2) 
Fridays off while Christians took Sundays off. Furthermore, e-waste and significant associations between prolonged standing and 
workers reported to spend between 2 and 14 h a day performing various work-related low back, lower leg and shoulder MSDs have been pointed 
recycling tasks, with a computed average of about 9 h per day. This out (Chandrasakaran et al., 2003; Musa et al., 2000). Prolonged standing 
finding corroborates prior reports of a typical 10–12 h of work per day transfers the load of the upper body to the lower parts resulting in low 
among workers at Agbogbloshie (Akormedi et al. (2013). Variability in back pain (Halim and Rahman Omar, 2011) and pain in the feet 
the number of hours and work distribution can be explained by our (Messing and Kilbom, 2001). Furthermore, standing during burning of 
observations. We noticed that the workday duration depended on the e-waste is compounded with forward flexion and twisting of the trunk 
recycling task being performed and the availability of work to be done. pose further harm to the low back. Bending and twisting of the spine 
For example, a dismantler who had few items to dismantle, could during work is associated with low back pain (Chaffin et al., 2006; 
complete the task in about 2 h and would be idle for the rest of the day Marras, 2008; Marras et al., 1998; Wai et al., 2010a). 
until a new batch of items were available for dismantling from the col- Reducing the time spent in standing could help decrease the risk of 
lectors. On the other hand, collectors would spend longer time wan- adverse health effect. For example, the use of cable strippers to extract 
dering in search of e-waste. Burners were also engaged in less active copper from insulated wires instead of burning could reduce work- 
work times as burning of a pile of copper wires took under 20 min and related standing in addition to alleviating some of the health risks to 
required occasional manipulation during burning despite continuous burners from smoke inhalation and environmental contamination from 
standing and stepping/walking. Some burners kept busy by gathering open-air burning. However, such interventions had limited success at 
7
A.A. Acquah et al.                                                                                                                                                              I n t  e r n  a  t i o  n a  l  J  o u  r n  a  l  o  f  I n  d u  s t r  i a l  E  r  g o  n  o m   i c s 82 (2021) 103096
Agbogbloshie (Adanu et al., 2020; Little, 2016) for sociocultural reasons dismantlers and 8964 steps for burners) among these otherwise more 
that fall outside the scope of the present study. sedentary groups. It is also possible that the many short bouts of walking 
caused burners and dismantlers to underreport their frequency of 
4.2.3. Walking continuous walking and thus not adequately captured by the question-
Prolonged walking (i.e., walking for hours without taking a break) naire. While these initial study findings may not be decisive, it does 
increases energy expenditure (Patton et al., 1991) and induces fatigue provide evidence that frequent exposure to prolonged sitting, standing 
(Morrison et al., 2016; Pinto Pereira and Gonçalves, 2011; Walsh et al., and walking is present at levels that should raise concern. Further sys-
2018; Yoshino et al., 2004) which may increase the risk of physical tematic study is needed to quantify the variability in these exposures 
discomfort, pain and MSDs. The associated risks may be exacerbated by both between and within workers over time. 
walking over uneven, unpaved terrain, in a harsh outdoor environment 
including hot and humid climate, and/or with poor air quality due to 4.2.4. Manual material handling activities 
toxic fumes from open burning and sewage (Akormedi et al., 2013; Yu E-waste recycling at Agbogbloshie involved different types and in-
et al., 2017). Prolonged walking was most prominent for collectors tensities of MMH activities. However, the present study only quantified 
(88.5%). Numerous studies have reported an association between pro- the self-reported frequency of performing MMH activities in a work-
longed walking and low back pain (Garcia et al., 2016; Roffey et al., week. The frequency of MMH activities differed both between and 
2010). Thus, e-waste of the trunk while performing their long hours of within job categories. Lifting and carrying were notably more frequent 
walking such as when collecting e-waste is likely to pose serious health for burners and collectors than dismantlers, with 80–90% of burners and 
risks to workers. Walking for prolonged periods subjects the spine to collectors performing these activities on ≥ 5 days per week. Although 
prolonged biomechanical loading with detrimental effects on spinal the frequency of lifting and carrying was lower for dismantlers than 
structures (Callaghan and McGill, 2001). Furthermore, collectors often collectors or burners, they reported a high intensity of load handling 
walk these long distances while pulling a hand-drawn cart which exerts suggesting interactions between hand load frequency, intensity, and 
additional compressive and shear stresses on the spine and the shoulder possibly duration across job categories. Understandably, pulling and 
as predicted by biomechanical analyses (see Chaffin et al., 2006 for re- pushing activities was more prevalent among collectors by definition of 
view). Appropriate measures to reduce the adverse effects of these their job. However, not all collectors operated carts and instead walked 
health risks are necessary. with a cloth sack to carry e-waste items. The 68% of collectors that re-
Pedometry generally provides more accurate and reliable estimates ported performing pushing and/or pulling on 5 or more days in the 
of physical activity exposures than self-report questionnaires (Sitthi- preceding workweek was in sharp contrast to the nearly 29% of col-
pornvorakul et al., 2014; Takala et al., 2010). However, direct mea- lectors who reported no pushing and/or pulling in the week. This re-
surements are challenging in non-repetitive work settings such as the inforces the high variability in work exposures among collectors, with 
unregulated, informal e-waste recycling work investigated in this study. much of this variability potentially related to the choice of MMH 
Furthermore, statistical comparisons between self-reported walking and equipment and from success or failure in locating items for recycling on 
pedometer measurements were not considered meaningful here since a given day. 
the former assessed the perceived frequency of continuous walking MMH activities may be a source of work-related MSD among e-waste 
during the workweek preceding the administration of the questionnaire, workers. Although not exactly e-waste recycling, manual collection and 
while the pedometers measured the effective walking on 2 consecutive handling of solid waste performed in informal settings is associated with 
but randomly selected workdays of the study. The high day-to-day a high prevalence of shoulder and low back MSDs (Abou-Elwafa et al., 
variability in physical activity exposure discussed above further di- 2012; Kuijer et al., 2010; Mehrdad et al., 2008). Additionally, there is 
minishes the validity of direct comparisons between the pedometry and strong evidence in the ergonomics literature that identifies MMH 
self-reported data. For instance, some workers were observed perform- including lifting, carrying, pushing and pulling as a leading cause of 
ing secondary e-waste recycling tasks that differ from their primary job work-related shoulder and low back disorders (Hoogendoorn et al., 
during periods of low work volume. 1999; Hoozemans et al., 2002; Roffey et al., 2010; Wai et al., 2010b). 
Non-parametric statistical analysis indicated no significant differ- Hoozemans et al. (2002) have also reported a dose-response relationship 
ences between pedometer measurements of the three e-waste job cate- between pushing and/or pulling and shoulder complaints among in-
gories. Thus, these data need to be interpreted with caution. However, dustry workers. Although some of these physical activities may not be 
trends in self-report-based walking and pedometer measurements strenuous when considered on their own, their repetition and combi-
among job categories provide useful insights that might have implica- nation with extreme postures contribute to the development of MSDs, as 
tions for future research at Agbogbloshie. Median pedometer steps and widely acknowledged in previous studies (Chaffin et al., 2006; Fan et al., 
distances walked were higher for collectors than burners and dis- 2014; Latko et al., 1999). Collectively these studies suggest that the 
mantlers. Aerobic steps count and cadence (steps/min) were also extent of MMH activities performed could predispose e-waste workers at 
slightly higher for collectors than burners and dismantlers (see Table 5). Agbogbloshie to developing work-related MSDs; thus, calling for addi-
These trends were compatible with the self-reported questionnaire data tional research to examine associations between specific physical work 
and were not surprising considering that collectors travelled long dis- exposures and MSDs in this worker population. 
tances between the e-waste scrapyard and adjacent communities. In 
contrast, the pedometer-based total step counts for dismantlers and 4.3. Study limitations 
burners were higher than expected based on trends in the observations 
and self-reported data. Compared to burners, the aerobic step counts for The unregulated nature of e-waste recycling at Agbogbloshie made it 
dismantlers and burners were also low suggesting multiple short bouts difficult to employ sampling strategies used in regular industrial work. 
of walking. About 50% of dismantlers recorded no aerobic steps likely However, attempts were made to sample participants at different loca-
due to the predominance of sitting or standing in place to perform their tions within the e-waste site and on different days to obtain a repre-
task. On a few occasions, when dismantlers had few parts to work with, sentative sample. This study had a modest sample size but was 
they were observed walking to neighbouring communities in search of e- comparable to other survey studies conducted at Agbogbloshie (n ~ 142 
waste instead of waiting for collectors to return with e-waste items. to 180; Adanu et al., 2020; Laskari et al., 2019). Another limitation was 
Similarly, burners were observed switching to dismantling tasks for that the accuracy of the self-reported data relies on the ability of par-
short durations to earn some income while waiting for new items to ticipants to recall the duration and frequency of their typical exposures 
burn. This may explain the relatively high pedometer readings on some to the different work activities. This is particularly challenging in un-
days which increased the median step counts (i.e., 5360 steps for regulated unstructured work, wherein the exposures vary considerably 
8
A.A. Acquah et al.                                                                                                                                                              I n t  e r n  a  t i o  n a  l  J  o u  r n  a  l  o  f  I n  d u  s t r  i a l  E  r  g o  n  o m   i c s 82 (2021) 103096
among workers, and for the same worker within days and between days. study due to their low cost. Future studies could consider using 
For example, some participants did not have a response to questions GPS-enabled activity monitors (i.e., as a way to potentially track the 
about MMH activities, which reduced the effective sample size in Ta- devices and minimize the risk of loss or theft) and could measure 
bles 3 and 4 additional physiological data (e.g., heart rate) to provide better infor-
Bias in workers responses to the questions could also stem from self- mation about the physical workload experienced. However, regardless 
perceptions about their work activity exposures as well as low literacy, of choice of direct instrumentation, this approach would not capture the 
nuances in local dialects, and differences in comprehension and inter- sociotechnical and environmental interactions and economic constraints 
pretation of the questionnaire. To minimize this effect, the present study on workers that influence their choice of job category, work methods 
employed professional research staff who were familiar with English and and equipment used, and consequently their work-related exposures. 
the local language as to conduct the field interviews. The format of the To understand these realities facing low-skilled, low-income workers 
self-report questionnaire responses, whether continuous, ordinal or in an unregulated, informal work setting, qualitative direct observations 
categorical, was also important to consider because of the low literacy in this study proved just as valuable as the quantitative questionnaire 
and language diversity. During the pilot phase of the study, participants data. As such, development of a direct observation technique to sys-
found it difficult to accurately estimate their proportion of time spent tematically sample work content and quantify physical work exposures 
performing the different OPAs. Thus, a categorical scheme was among e-waste workers may be most ideal. Direct observation and 
employed in the modified OPAQ. For example, the time spent in sitting, quantification of workers physical exposures have proven successful in 
standing and walking was presented in two ways: (1) 1-h of continuous other non-repetitive work settings such as construction (e.g., the Posture 
activity, and (2) a total of 4 h of activity during the workday (Appendix Activity and Tools Handled (PATH) work-sampling based approach by 
A). As an initial step, this format to the questionnaire helped reduce Buchholz et al. (1996)) and could provide a template for similar ap-
participant’s wavering or indecision about the responses and shorter proaches suited to unregulated, informal e-waste recycling. More 
response times. Although this format made it relatively easy for workers broadly, our study findings provide important lessons and motivation 
to provide information on their OPA exposures, a more reliable direct for future research to examine physical activity exposures and associ-
form of quantification of these OPA levels could be explored in future ated work-related injury prevalence in the informal e-waste recycling 
studies. sector. 
This study was also limited by its inability to continuously observe 
workers that were instrumented with pedometers in order to document 5. Conclusion 
the activities they performed which could help explain the trends in 
pedometer measurements. There could be a small possibility of some This study contributes to the limited literature on work-related ac-
participants with pedometers being involved in additional activities tivity exposures and work conditions of e-waste workers at the largest e- 
other than their primary job. However, our observations of other waste dumpsite in sub-Saharan Africa. While prior studies at Agbog-
workers suggested this was infrequent and as such was not considered in bloshie emphasized exposures to toxic chemicals, poor air quality, and 
our statistical data analysis. noise, this initial study draws unique attention to the physical work 
exposures associated with informal e-waste recycling. E-waste recycling 
4.4. Methodological implications involves varying levels of sitting, standing, walking and a range of MMH 
activities that collectively may be detrimental to the musculoskeletal 
From a methodological perspective, the current study draws atten- health of the worker. Self-reported work exposures examined in this 
tion to the need for new, validated methods to measure physical work study differed substantially between the three primary e-waste job cat-
exposures among workers engaged in informal e-waste recycling. Due to egories. Long hours of sitting were common among dismantlers while 
the challenges of studying informal work settings, in this study we opted burners and collectors were more likely to be engaged in prolonged 
for a multi-method approach, namely, direct observations, self-report standing and walking respectively. All job categories had a high pro-
questionnaires, and pedometry. The modified version of the OPAQ portion of workers performing manual material handling activities on 
was appropriate in capturing information about some of the most five or more days in the week. Dismantlers and burners engaged in 
common physical activity exposures among e-waste workers in a short frequent lifting and carrying tasks while pushing and/or pulling were 
period of time. However certain quantitative exposure data were missed. most frequent among collectors. Frequent exposure to these physically 
First, information about the frequency of force exertions associated with demanding activities may compound the musculoskeletal health effects 
using hand tools (e.g., hammers, chisels, screwdrivers), which is typical of prolonged sitting, standing and walking. 
among dismantlers, was not assessed in the OPAQ. Second, information Achieving proper balance between sitting, standing, walking and 
about whole-body postures (e.g., standing, seated, squat, stooped) performing MMH activities in informal e-waste work may help reduce its 
associated with MMH activities such as lifting, pushing and/or pulling, potential negative health effects. However, the development of appro-
and magnitude of hand force exertions during tool use was not obtained. priate and context adapted ergonomics interventions relies on accurate 
Additional research is needed to quantify the relationships between the and reliable quantitative information about work exposures and asso-
MMH activities performed (type, magnitude or intensity, duration, and ciated work-related injuries. Our study highlights the need for further 
frequency) and the postures used during those activities specific to work occupational safety and ergonomics research in the informal e-waste 
methods in low-resource informal settings. recycling sector. Specifically, more objective and reliable assessment 
Direct instrumentation-based methods have advantages in terms of methods that can account for the between and within worker variability 
accuracy and reliability (Chaffin et al., 2006; Neitzel et al., 2013), in exposures inherent to informal e-waste work are required. Future 
however, the variable nature of informal e-waste recycling at Agbog- studies also need to consider the local economic realities and social 
bloshie presented some challenges. Pedometers were time and context encountered in an unregulated, low resource and multi-ethnic 
cost-prohibitive to use and as such not all participants in the study were work environment. 
instrumented with pedometers. Unfortunately, the pedometers were 
also perceived by participants as valuable and inexplicably would go Funding 
missing during data collection. Five pedometers were not returned in the 
early stage of the study, which further limited data collection from more The study was supported by the 1⁄2 West Africa-Michigan CHARTER 
workers. These realities and trade-offs in field research can limit the in GEOHealth with funding from the United States National Institutes of 
ability to fully capture the variability in exposures between workers and Health/Fogarty International Center (US NIH/FIC) (paired grant no 
within workers over time. Simple pocket pedometers were used for this 1U2RTW010110-01/5U01TW010101) and Canada’s International 
9
A.A. Acquah et al.                                                                                                                                                              I n t  e r n  a  t i o  n a  l  J  o u  r n  a  l  o  f  I n  d u  s t r  i a l  E  r  g o  n  o m   i c s 82 (2021) 103096
Development Research Center (IDRC) (grant no. 108121-001). Co- Kwarteng: Investigation, Writing - review & editing. Sylvia Takyi: 
authors CD and BM were supported in part by the training grant T42- Investigation, Writing - review & editing. Isabella A. Quakyi: 
OH008455 from the National Institute for Occupational Safety and Conceptualization, Writing - review & editing, Supervision. Thomas G. 
Health (NIOSH, Centers for Disease Control and Prevention (CDC). The Robins: Writing - review & editing, Resources, Supervision, Funding 
views expressed in this publication do not necessarily reflect the official acquisition. Julius N. Fobil: Conceptualization, Investigation, Re-
policies of nor endorsement by NIH, NIOSH, CDC, and/or the Canadian sources, Writing - review & editing, Supervision, Funding acquisition. 
and US Governments. 
CRediT authorship contribution statement Declaration of competing interest 
Augustine A. Acquah: Conceptualization, Methodology, Investiga- The authors declare that they have no known competing financial 
tion, Formal analysis, Writing - original draft, Writing - review & edit- interests or personal relationships that could have appeared to influence 
ing, Resources. Clive D’Souza: Conceptualization, Methodology, the work reported in this paper. 
Writing - original draft, Writing - review & editing, Supervision, Vali-
dation. Bernard J. Martin: Conceptualization, Methodology, Writing - Acknowledgements 
original draft, Writing - review & editing, Supervision, Validation. John 
Arko-Mensah: Conceptualization, Investigation, Writing - review & We acknowledge all workers at the Agbogbloshie e-waste site for 
editing, Supervision. Paul K. Botwe: Writing - review & editing, Su- their cooperation and dedicated contribution towards this study. We 
pervision. Prudence Tettey: Writing - review & editing, Supervision. also acknowledge the hard work of our field team at the University of 
Duah Dwomoh: Formal analysis, Writing - review & editing. Afua Ghana School of Public Health who assisted in organising field visits and 
Amoabeng Nti: Investigation, Writing - review & editing. Lawrencia conducting worker interviews.  
Appendix A. Supplementary data 
Supplementary data to this article can be found online at https://doi.org/10.1016/j.ergon.2021.103096. 
AppendixA: Modified version of the OPAQ used for data collection 
Q1. In the last workweek, did you do the following during your work schedule? 
* Sitting activities.    
Yes No 
Prolonged sitting (4 h or more per day) □ □ 
Sitting continuously for 1 h or more □ □  
* Standing activities.    
Yes No 
Prolonged standing (4 h or more per day) □ □ 
Standing continuously for 1 h or more □ □  
* Walking.    
Yes No 
Prolonged walking (4 h or more per day) □ □ 
Walking for 1 h or more □ □  
* Manual material handling activities. 
Q2. In the last work week, how often did you do the following during your work schedule?    
Never or rarely 1–2 days last week 3–4 days last week 5 or more days last week 
Lifting items □ □ □ □ 
Carrying load □ □ □ □ 
Pushing or pulling a cart or truck □ □ □ □  
10
A.A. Acquah et al.                                                                                                                                                              I n t  e r n  a  t i o  n a  l  J  o u  r n  a  l  o  f  I n  d u  s t r  i a l  E  r  g o  n  o m   i c s 82 (2021) 103096
Q3. If you did any of the above, what is the maximum weight you usually handle while performing these tasks?   
□ Light (5 kg or less) □ Moderate (6–10 kg) □ Heavy (11–20 kg) □ Very heavy (>20 kg)  
References Chandrasakaran, A., Chee, H.L., Rampal, K.G., Tan, G.L.E., 2003. The prevalence of 
musculoskeletal problems and risk factors among women assembly workers in the 
semiconductor industry. Med. J. Malaysia. 
Abou-Elwafa, H.S., El-Bestar, S.F., El-Gilany, A.-H., Awad, E.E.-S., 2012. Musculoskeletal 
disorders among municipal solid waste collectors in Mansoura, Egypt: a cross- Chi, X., Streicher-Porte, M., Wang, M.Y.L., Reuter, M.A., 2011. Informal electronic waste recycling: a sector review with special focus on China. Waste Manag. 31, 731–742. 
sectional study. BMJ Open 2. https://doi.org/10.1136/bmjopen-2012-001338. https://doi.org/10.1016/J.WASMAN.2010.11.006. 
Acquah, A.A., D’Souza, C., Martin, B., Arko-Mensah, J., Nti, A.A., Kwarteng, L., Takyi, S., 
Quakyi, I.A., Robins, T.G., Fobil, J.N., 2019. Processes and challenges associated Chiasson, M. ève, Imbeau, D., Aubry, K., Delisle, A., 2012. Comparing the results of eight methods used to evaluate risk factors associated with musculoskeletal disorders. Int. 
with informal electronic waste recycling at Agbogbloshie, a suburb of Accra, Ghana. 
Proc. Hum. Factors Ergon. Soc. Annu. Meet. 63, 938 942. https://doi.org/10.1177/ J. Ind. Ergon. 42, 478–488. https://doi.org/10.1016/j.ergon.2012.07.003. – Czuba, L.R., Sommerich, C.M., Lavender, S.A., 2012. Ergonomic and safety risk factors in 
1071181319631219. 
Adanu, S.K., Gbedemah, S.F., Attah, M.K., 2020. Challenges of adopting sustainable home health care: exploration and assessment of alternative interventions. Work 42, 341–353. https://doi.org/10.3233/WOR-2012-1433. 
technologies in e-waste management at Agbogbloshie, Ghana. Heliyon 6 (8), Davis, J.M., Akese, G., Garb, Y., 2019. Beyond the pollution haven hypothesis: where and 
e04548. 
Ahlvin, K., 2012. The burden of the Kayayei: cultural and socio-economic difficulties why do e-waste hubs emerge and what does this mean for policies and interventions? Geoforum 98, 36–45. https://doi.org/10.1016/j.geoforum.2018.09.020. 
facing female porters in Agbogbloshie. Pure Insights 1 (1), 4. 
Akormedi, M., Asampong, E., Fobil, J.N., 2013. Working conditions and environmental Dickerson, C.R., Alenabi, T., Martin, B.J., Chaffin, D.B., 2018. Shoulder muscular activity in individuals with low back pain and spinal cord injury during seated manual load 
exposures among electronic waste workers in Ghana. Int. J. Occup. Environ. Health transfer tasks. Ergonomics 61, 1094–1101. https://doi.org/10.1080/ 
19, 278–286. https://doi.org/10.1179/2049396713Y.0000000034. 
Amankwaa, E.F., 2013. Livelihoods in risk: exploring health and environmental 00140139.2018.1447690. Duchečková, P., Forejt, M., 2014. Aerobic steps as measured by pedometry and their 
implications of e-waste recycling as a livelihood strategy in Ghana. J. Mod. Afr. Stud. 
51, 551–575. https://doi.org/10.1017/S0022278X1300058X. relation to central obesity. Iran. J. Public Health 43, 1070–1078. Eatough, E.M., Way, J.D., Chang, C.H., 2012. Understanding the link between 
Andreas, W.J., Grooten, J.E., 2018. Observational methods for assessing ergonomic risks 
for work-related musculoskeletal disorders. A Scoping Review. Rev. Ciencias la Salud psychosocial work stressors and work-related musculoskeletal complaints. Appl. 
16, 8–38. https://doi.org/10.12804/revistas.urosario.edu.co/revsalud/a.6840. Ergon. 43, 554–563. https://doi.org/10.1016/j.apergo.2011.08.009. Emmatty, F.J., Panicker, V.V., 2019. Ergonomic interventions among waste collection 
Armstrong, T.J., Foulke, J.A., Martin, B.J., Gerson, J., Rempel, D.M., 1994. Investigation 
of applied forces in alphanumeric keyboard work. Am. Ind. Hyg. Assoc. J. 55, 30 35. workers: a systematic review. Int. J. Ind. Ergon. 72, 158–172. https://doi.org/ – 10.1016/J.ERGON.2019.05.004. 
https://doi.org/10.1080/15428119491019230. 
Bakhiyi, B., Gravel, S., Ceballos, D., Flynn, M.A., Zayed, J., 2018. Has the question of e- Fan, Z.J., Silverstein, B.A., Bao, S., Bonauto, D.K., Howard, N.L., Smith, C.K., 2014. The association between combination of hand force and forearm posture and incidence of 
waste opened a Pandora’s box? An overview of unpredictable issues and challenges. lateral epicondylitis in a working population. Hum. Factors 56, 151–165. https:// 
Environ. Int. 110, 173–192. https://doi.org/10.1016/j.envint.2017.10.021. 
Bao, S.S., Kapellusch, J.M., Garg, A., Silverstein, B.A., Harris-Adamson, C., Burt, S.E., doi.org/10.1177/0018720813492327. Feldt, T., Fobil, J.N., Wittsiepe, J., Wilhelm, M., Till, H., Zoufaly, A., Burchard, G., 
Dale, A.M., Evanoff, B.A., Gerr, F.E., Hegmann, K.T., Merlino, L.A., Thiese, M.S., 
Rempel, D.M., 2015. Developing a pooled job physical exposure data set from Göen, T., 2014. High levels of PAH-metabolites in urine of e-waste recycling workers from Agbogbloshie. Ghana. Sci. Total Environ. 466–467, 369–376. https://doi.org/ 
multiple independent studies: an example of a consortium study of carpal tunnel 10.1016/j.scitotenv.2013.06.097. 
syndrome. Occup. Environ. Med. 72, 130–137. https://doi.org/10.1136/oemed- 
2014-102396. Garcia, M.G., Läubli, T., Martin, B.J., 2015. Long-term muscle fatigue after standing work. Hum. Factors 57, 1162–1173. https://doi.org/10.1177/0018720815590293. 
Basu, N., Ayelo, P.A., Djogbénou, L.S., Kedoté, M., Lawin, H., Tohon, H., Oloruntoba, E. 
O., Adebisi, N.A., Cazabon, D., Fobil, J., Robins, T., Fayomi, B., 2016. Occupational Garcia, M.G., Wall, R., Steinhilber, B., Läubli, T., Martin, B.J., 2016. Long-lasting changes in muscle twitch force during simulated work while standing or walking. Hum. 
and environmental health risks associated with informal sector activities—selected 
case studies from West Africa. NEW solut. A J. Environ. Occup. Heal. Policy 26, Factors 58, 1117–1127. https://doi.org/10.1177/0018720816669444. Garcia, M.G., Läubli, T., Martin, B.J., 2018. Muscular and vascular issues induced by 
253–270. https://doi.org/10.1177/1048291116651726. prolonged standing with different work–rest cycles with active or passive breaks. 
Battenberg, A.K., Donohoe, S., Robertson, N., Schmalzried, T.P., 2017. The accuracy of 
personal activity monitoring devices. Semin. Arthroplasty 28, 71 75. https://doi. Hum. Factors 60, 806–821. https://doi.org/10.1177/0018720818769261. – Garcia, M.-G., Tapia, P., Läubli, T., Martin, B.J., 2020. Physiological and neuromotor 
org/10.1053/J.SART.2017.07.006. 
Beach, T.A.C., Parkinson, R.J., Stothart, J.P., Callaghan, J.P., 2005. Effects of prolonged changes induced by two different stand-walk-sit work rotations. Ergonomics 63, 163–174. https://doi.org/10.1080/00140139.2019.1677949. 
sitting on the passive flexion stiffness of the in vivo lumbar spine. Spine J. 5, Gutberlet, J., Baeder, A.M., 2008. Informal recycling and occupational health in Santo 
145–154. https://doi.org/10.1016/j.spinee.2004.07.036. 
Bernhardt, A., Gysi, N., 2013. The Worlds Worst 2013: the Top Ten Toxic Threats. Clean- André, Brazil. Int. J. Environ. Health Res. 18, 1–15. https://doi.org/10.1080/ 09603120701844258. 
up, Progress and Ongoing Challenges. Blacksmith Institute and Green Cross 
Switzerland, New York City. Retrieved October 10, 2020, from: http://www.worstpo Halim, I., Rahman Omar, A., 2011. A Review on Health Effects Associated with Prolonged Standing in the Industrial Workplaces. IJRRAS. 
lluted.org/docs/TopTenThreats2013.pdf.  
Bongers, P.M., Kremer, A.M., Laak, J. Ter, 2002. Are psychosocial factors, risk factors for Heacock, M., Kelly, C.B., Asante, K.A., Birnbaum, L.S., Bergman, Å.L., Bruné, M.-N., Buka, I., Carpenter, D.O., Chen, A., Huo, X., Kamel, M., Landrigan, P.J., Magalini, F., 
symptoms and signs of the shoulder, elbow, or hand/wrist?: a review of the Diaz-Barriga, F., Neira, M., Omar, M., Pascale, A., Ruchirawat, M., Sly, L., Sly, P.D., 
epidemiological literature. In: American Journal of Industrial Medicine. John Wiley 
Sons, Ltd, pp. 315 342. https://doi.org/10.1002/ajim.10050. Van den Berg, M., Suk, W.A., 2016. E-Waste and harm to vulnerable populations: a & – growing global problem. Environ. Health Perspect. 124, 550–555. https://doi.org/ 
Buchholz, B., Paquet, V., Punnet, L., Lee, D., Moir, S., 1996. PATH: a work-sampling 
based approach to ergonomic job analysis for construction and other non-repetitive 10.1289/ehp.1509699. Hoogendoorn, W.E., Poppel, M.N. van, Bongers, P.M., Koes, B.W., Bouter, L.M., 1999. 
work. Appl. Ergon. 27, 177–187. Physical load during work and leisure time as risk factors for back pain. Scand. J. 
Burdorf, A., van der Beek, A., 1999. Exposure assessment strategies for work-related risk 
factors for musculoskeletal disorders. Scand. J. Work. Environ. Health 25 (Suppl. 4), Work. Environ. Health. https://doi.org/10.2307/40966920. Hoozemans, M.J.M., van der Beek, A.J., Frings-Dresen, M.H.W., van der Woude, L.H.V., 
25–30. 
Burns, K., Sun, K., Fobil, J., Neitzel, R., 2016. Heart rate, stress, and occupational noise van Dijk, F.J.H., 2002. Pushing and pulling in association with low back and shoulder complaints. Occup. Environ. Med. 59, 696–702. https://doi.org/10.1136/ 
exposure among electronic waste recycling workers. Int. J. Environ. Res. Publ. 
Health 13, 140. https://doi.org/10.3390/ijerph13010140. oem.59.10.696. Ilo, I.L.O., 2004. Addressing the Exploitation of Children in Scavenging (Waste Picking): 
Callaghan, J.P., McGill, S.M., 2001. Low back joint loading and kinematics during A Thematic Evaluation on Action on Child Labour. A global report for the ILO, 
standing and unsupported sitting. Ergonomics 44, 280–294. https://doi.org/ 
10.1080/00140130118276. Geneva.  Jaffar, N., Abdul-Tharim, A.H., Mohd-Kamar, I.F., Lop, N.S., 2011. A Literature Review 
Carlson, K., Krystin, 2016. Electronic waste worker health. In: Proceedings of the Eighth 
International Conference on Information and Communication Technologies and of Ergonomics Risk Factors in Construction Industry. In: Procedia Engineering, pp. 89–97. https://doi.org/10.1016/j.proeng.2011.11.142. 
Development - ICTD ’16. ACM Press, New York, New York, USA, pp. 1–4. https:// Janowitz, I.L., Gillen, M., Ryan, G., Rempel, D., Trupin, L., Swig, L., Mullen, K., 
doi.org/10.1145/2909609.2909618. 
Chaffin, D.B., Andersson, G.B.J., Martin, B.J., 2006. Occupational Biomechanics, fourth Rugulies, R., Blanc, P.D., 2006. Measuring the physical demands of work in hospital settings: design and implementation of an ergonomics assessment. Appl. Ergon. 37, 
ed. 641–658. https://doi.org/10.1016/J.APERGO.2005.08.004. 
Jung, M.C., Haight, J.M., Freivalds, A., 2005. Pushing and pulling carts and two-wheeled 
hand trucks. Int. J. Ind. Ergon. 35 (1), 79–89. 
11
A.A. Acquah et al.                                                                                                                                                              I n t  e r n  a  t i o  n a  l  J  o u  r n  a  l  o  f  I n  d u  s t r  i a l  E  r  g o  n  o m   i c s 82 (2021) 103096
Juul-Kristensen, B., Hansson, G.A., Fallentin, N., Andersen, J.H., Ekdahl, C., 2001. Ohajinwa, C.M., Van Bodegom, P.M., Vijver, M.G., Olumide, A.O., Osibanjo, O., 
Assessment of work postures and movements using a video-based observation Peijnenburg, W., 2018. Prevalence and injury patterns among electronic waste 
method and direct technical measurements. Appl. Ergon. 32, 517–524. https://doi. workers in the informal sector in Nigeria. Inj. Prev. 24, 185–192. https://doi.org/ 
org/10.1016/s0003-6870(01)00017-5. 10.1136/injuryprev-2016-042265. 
Kendall, B., Bellovary, B., Gothe, N.P., 2019. Validity of wearable activity monitors for Olzenak, K.J., Byrne, J.L., 2017. The Effect of Nutrition Education and Pedometer Use on 
tracking steps and estimating energy expenditure during a graded maximal treadmill Type 2 Diabetes Risk Factors in Latino Immigrants. 
test. J. Sports Sci. 37, 42–49. https://doi.org/10.1080/02640414.2018.1481723. Omron, 2019. Omron pedometer instruction manual [WWW Document]. URL. www. 
Kolbe-Alexander, T.L., Charlton, K.E., Lambert, E.V., 2004. Lifetime physical activity and register-omron.com. accessed 11.12.19.  
determinants of estimated bone mineral density using calcaneal ultrasound in older Oteng-Ababio, M., 2012. When necessity begets ingenuity: E-waste scavenging as a 
South African adults. J. Nutr. Health Aging 8, 521–530. livelihood strategy in Accra, Ghana. Afr. Stud. Q. ume 13. 
Kong, Y.-K., Lee, S., Lee, K.-S., Kim, D.-M., 2018. Comparisons of ergonomic evaluation Owoeye, O., Tomori, A., Akinbo, S., 2016. Pedometer-determined physical activity 
tools (ALLA, RULA, REBA and OWAS) for farm work. Int. J. Occup. Saf. Ergon. 24, profile of healthcare professionals in a Nigerian tertiary hospital. Niger. Med. J. 57, 
218–223. https://doi.org/10.1080/10803548.2017.1306960. 99–103. https://doi.org/10.4103/0300-1652.182070. 
Kuijer, P.P.F.M., Sluiter, J.K., Frings-Dresen, M.H.W., 2010. Health and safety in waste Parida, R., Ray, P.K., 2012. Study and analysis of occupational risk factors for ergonomic 
collection: towards evidence-based worker health surveillance. Am. J. Ind. Med. 53, design of construction worksystems. Work 41, 3788–3794. https://doi.org/10.3233/ 
1040–1064. https://doi.org/10.1002/ajim.20870. WOR-2012-0679-3788. 
Kuorinka, I., Forcier, L., Hagberg, M., Silverstein, B., Wells, R., 1995. Work Related Patton, J.F., Kaszuba, J., Mello, R.P., Reynolds, K.L., 1991. Physiological responses to 
Musculoskeletal Disorders (WMSDs): a Reference Book for Prevention. Taylor & prolonged treadmill walking with external loads. Eur. J. Appl. Physiol. Occup. 
Francis, London.  Physiol. 63, 89–93. https://doi.org/10.1007/BF00235175. 
Kwon, B.K., Roffey, D.M., Bishop, P.B., Dagenais, S., Wai, E.K., 2011. Systematic review: Perkins, D.N., Brune Drisse, M.-N., Nxele, T., Sly, P.D., 2014. E-Waste: a global hazard. 
occupational physical activity and low back pain. Occup. Med. (Chic. Ill). 61, Ann. Glob. Heal. 80, 286–295. https://doi.org/10.1016/J.AOGH.2014.10.001. 
541–548. https://doi.org/10.1093/occmed/kqr092. Pinto Pereira, M., Gonçalves, M., 2011. EffEcts of fatiguE inducEd by prolongEd gait 
Lafond, D., Champagne, A., Descarreaux, M., Dubois, J.-D., Prado, J.M., Duarte, M., whEn walking on thE EldErly. Hum. Mov. 12, 242–247. https://doi.org/10.2478/ 
2009. Postural control during prolonged standing in persons with chronic low back v10038-011-0025-7. 
pain. Gait Posture 29, 421–427. https://doi.org/10.1016/J.GAITPOST.2008.10.064. Punnett, L., Bergqvist, U., 1999. Musculoskeletal disorders in visual display unit work: 
Laskaris, Z., Milando, C., Batterman, S., Mukherjee, B., Basu, N., O’Neill, M.S., Robins, T. gender and work demands. Occup. Med. 14, 113–124. 
G., Fobil, J.N., 2019. Derivation of time-activity data using wearable cameras and Reis, J.P., Dubose, K.D., Ainsworth, B.E., Macera, C.A., Yore, M.M., 2005. Reliability and 
measures of personal inhalation exposure among workers at an informal electronic- validity of the occupational physical activity questionnaire. Med. Sci. Sports Exerc. 
waste recovery site in Ghana. Ann. Work Expo. Heal. https://doi.org/10.1093/ 37, 2075–2083. https://doi.org/10.1249/01.mss.0000179103.20821.00. 
annweh/wxz056. Robertson, M.M., Boiselle, P., Eisenberg, R., Siegal, D., Chang, C.H., Dainoff, M., 
Latko, W.A., Armstrong, T.J., Franzblau, A., Ulin, S.S., Werner, R.A., Albers, J.W., 1999. Garabet, A., Garza, J.B., Dennerlein, J., 2012. Examination of comptuer task 
Cross-sectional study of the relationship between repetitive work and the prevalence exposures in radiologists: a work systems approach. In: Work. IOS Press, 
of upper limb musculoskeletal disorders. Am. J. Ind. Med. 36, 248–259. https://doi. pp. 1818–1820. https://doi.org/10.3233/WOR-2012-0391-1818. 
org/10.1002/(SICI)1097-0274(199908)36:2<248::AID-AJIM4>3.0.CO;2-Q. Roffey, D.M., Wai, E.K., Bishop, P., Kwon, B.K., Dagenais, S., 2010. Causal assessment of 
Lavender, S.A., Oleske, D.M., Nicholson, L., Andersson, G.B.J., Hahn, J., 1999. awkward occupational postures and low back pain: results of a systematic review. 
Comparison of five methods used to determine low back disorder risk in a Spine J. 10, 89–99. https://doi.org/10.1016/j.spinee.2009.09.003. 
manufacturing environment. Spine 24, 1441. https://doi.org/10.1097/00007632- Roffey, D.M., Wai, E.K., Bishop, P., Kwon, B.K., Dagenais, S., 2010. Causal assessment of 
199907150-00009. Phila. Pa. 1976.  occupational standing or walking and low back pain: results of a systematic review. 
Li, G., Buckle, P., 1999. Current techniques for assessing physical exposure to work- Spine J. 10, 262–272. https://doi.org/10.1016/j.spinee.2009.12.023. 
related musculoskeletal risks, with emphasis on posture-based methods. Ergonomics Roffey, Darren M., Wai, E.K., Bishop, P., Kwon, B.K., Dagenais, S., 2010. Causal 
42, 674–695. https://doi.org/10.1080/001401399185388. assessment of occupational pushing or pulling and low back pain: results of a 
Little, P.C., 2016. On Electronic Pyropolitics and Pure Earth Friction in Agbogbloshie. systematic review. Spine J. 10, 544–553. https://doi.org/10.1016/j. 
Toxic News. Nov, 8. Retrieved from: https://toxicnews.org/2016/11/08/on-electro spinee.2010.03.025. 
nic-pyropolitics-and-pure-earth-friction-in-agbogbloshie/. Sampaio, L.M.M., Subramaniam, S., Arena, R., Bhatt, T., 2016. Does virtual reality-based 
Madeleine, P., Voigt, M., Arendt-Nielsen, L., 1997. Subjective, physiological and kinect dance training paradigm improve autonomic nervous system modulation in 
biomechanical responses to prolonged manual work performed standing on hard and individuals with chronic stroke? J. Vasc. Interv. Neurol. 9, 21–29. 
soft surfaces. Eur. J. Appl. Physiol. 77, 1–9. https://doi.org/10.1007/ Shamim, A., Mursheda, K.A., 2015. E-waste trading impact on public health and 
s004210050292. ecosystem services in developing countries. Int. J. Waste Resour. https://doi.org/ 
Maphosa, V., Maphosa, M., 2020. E-waste management in Sub-Saharan Africa: a 10.4172/2252-5211.1000188, 05.  
systematic literature review. Cogent Business & Management 7 (1), 1814503. Silverstein, B.A., Fine, L.J., Armstrong, T.J., 1987. Occupational factors and carpal 
Marras, W., 2008. The Working Back: A Systems View. John Wiley and Sons. tunnel syndrome. Am. J. Ind. Med. 11, 343–358. https://doi.org/10.1002/ 
Marras, W.S., Davis, K.G., Granata, K.P., 1998. Trunk muscle activities during ajim.4700110310. 
asymmetric twisting motions. J. Electromyogr. Kinesiol. 8, 247–256. https://doi. Sitthipornvorakul, E., Janwantanakul, P., van der Beek, A.J., 2014. Correlation between 
org/10.1016/S1050-6411(98)00011-X. pedometer and the Global Physical Activity Questionnaire on physical activity 
Marshall, M.M., Armstrong, T.J., Martin, B.J., Foulke, J.A., Grieshaber, D.C., Malone, G., measurement in office workers. BMC Res. Notes 7, 280. https://doi.org/10.1186/ 
2000. Exposure to forceful exertions and vibration in a foundry. Proc. Hum. Factors 1756-0500-7-280. 
Ergon. Soc. Annu. Meet. 44, 17–20. https://doi.org/10.1177/ Srigboh, R.K., Basu, N., Stephens, J., Asampong, E., Perkins, M., Neitzel, R.L., Fobil, J., 
154193120004402905. 2016. Multiple elemental exposures amongst workers at the Agbogbloshie electronic 
Mehrdad, R., Majlessi-Nasr, M., Aminian, O., Malekahmadi, S. a S.F., 2008. waste (e-waste) site in Ghana. Chemosphere 164, 68–74. https://doi.org/10.1016/j. 
Musculoskeletal disorders among municipal solid waste workers. Acta Med. Iran. 46, chemosphere.2016.08.089. 
233–238. Stanton, N.A., Hedge, A., Brookhuis, K., Salas, E., Hendrick, H.W., 2004. Quick exposure 
Messing, K., Kilbom, A., 2001. Standing and very slow walking: foot pain-pressure checklist (QEC) for the assessment of workplace risks for work-related 
threshold, subjective pain experience and work activity. Appl. Ergon. 32, 81–90. musculoskeletal disorders (WMSDs). In: Handbook of Human Factors and 
https://doi.org/10.1016/s0003-6870(00)00030-2. Ergonomics Methods. CRC Press, pp. 74–85. 
Morrison, S., Colberg, S.R., Parson, H.K., Neumann, S., Handel, R., Vinik, E.J., Stucke, S., Menzel, N.N., 2007. Ergonomic assessment of a critical care unit. Crit. Care 
Paulson, J., Vinik, A.I., 2016. Walking-Induced fatigue leads to increased falls risk in Nurs. Clin. 19, 155–165. https://doi.org/10.1016/J.CCELL.2007.02.005. 
older adults. J. Am. Med. Dir. Assoc. 17, 402–409. https://doi.org/10.1016/j. Takala, E.-P., Pehkonen, I., Forsman, M., Hansson, G.-Å., Erik Mathiassen, S., Patrick 
jamda.2015.12.013. Neumann, W., Sjøgaard, G., Bo Veiersted, K., Westgaard, R.H., Winkel, J., 2010. 
Mossa, G., Boenzi, F., Digiesi, S., Mummolo, G., Romano, V.A., 2016. Productivity and Systematic evaluation of observational methods assessing biomechanical exposures 
ergonomic risk in human based production systems: a job-rotation scheduling model. at work, Source. Scandinavian Journal of Work. 
Int. J. Prod. Econ. 171, 471–477. https://doi.org/10.1016/J.IJPE.2015.06.017. Takyi, S.A., Basu, N., Arko-Mensah, J., Botwe, P., Amoabeng Nti, A.A., Kwarteng, L., 
Musa, R., Kyi, W., Rampal, K.G., 2000. Work-related musculoskeletal symptoms among Acquah, A., Tettey, P., Dwomoh, D., Batterman, S., Robins, T., Fobil, J.N., 2020. 
batik workers in kelantan. Malays. J. Med. Sci. 7, 13–17. Micronutrient-rich dietary intake is associated with a reduction in the effects of 
Neitzel, R.L., Crollard, A., Dominguez, C., Stover, B., Seixas, N.S., 2013. A mixed- particulate matter on blood pressure among electronic waste recyclers at 
methods evaluation of health and safety hazards at a scrap metal recycling facility. Agbogbloshie, Ghana. BMC Publ. Health 20, 1067. https://doi.org/10.1186/s12889- 
Saf. Sci. 51, 432–440. https://doi.org/10.1016/j.ssci.2012.08.012. 020-09173-8. 
Nti, A.A.A., Arko-Mensah, J., Botwe, P.K., Dwomoh, D., Kwarteng, L., Takyi, S.A., Todd, A.I., 2009. Distinctive Ergonomics requirements of developing regions: economic 
Acquah, A.A., Tettey, P., Basu, N., Batterman, S., Robins, T.G., Fobil, J.N., 2020. costs and benefits. In: Scott, Patricia A. (Ed.), Ergonomics in Developing Regions: 
Effect of particulate matter exposure on respiratory health of e-waste workers at Needs and Applications. Taylor and Francis Group, Boca Raton, London, New York, 
Agbogbloshie, Accra, Ghana. Int. J. Environ. Res. Publ. Health 17, 3042. https://doi. pp. 171–184. 
org/10.3390/ijerph17093042. Tomei, F., Baccolo, T.P., Tomao, E., Palmi, S., Rosati, M.V., 1999. Chronic venous 
Oakman, J., Macdonald, W., Wells, Y., 2014. Developing a comprehensive approach to disorders and occupation. Am. J. Ind. Med. 36, 653–665. https://doi.org/10.1002/ 
risk management of musculoskeletal disorders in non-nursing health care sector (SICI)1097-0274(199912)36:6<653::AID-AJIM8>3.0.CO;2-P. 
employees. Appl. Ergon. 45, 1634–1640. https://doi.org/10.1016/j. UNICEF, 2019. UNICEF Ghana: Prevention of Child Labour. UNICEF Country Office, 
apergo.2014.05.016. Accra-North, Ghana.  
12
A.A. Acquah et al.                                                                                                                                                              I n t  e r n  a  t i o  n a  l  J  o u  r n  a  l  o  f  I n  d u  s t r  i a l  E  r  g o  n  o m   i c s 82 (2021) 103096
Wai, E.K., Roffey, D.M., Bishop, P., Kwon, B.K., Dagenais, S., 2010a. Causal assessment of in blood of informal e-waste recycling workers from Agbogbloshie, Ghana, and 
occupational bending or twisting and low back pain: results of a systematic review. controls. Environ. Int. 79, 65–73. https://doi.org/10.1016/J.ENVINT.2015.03.008. 
Spine J. 10, 76–88. https://doi.org/10.1016/j.spinee.2009.06.005. Yoshino, K., Motoshige, T., Araki, T., Matsuoka, K., 2004. Effect of prolonged free- 
Wai, E.K., Roffey, D.M., Bishop, P., Kwon, B.K., Dagenais, S., 2010b. Causal assessment of walking fatigue on gait and physiological rhythm. J. Biomech. 37, 1271–1280. 
occupational carrying and low back pain: results of a systematic review. Spine J. 10, https://doi.org/10.1016/j.jbiomech.2003.11.031. 
628–638. https://doi.org/10.1016/j.spinee.2010.03.027. Yu, E.A., Akormedi, M., Asampong, E., Meyer, C.G., Fobil, J.N., 2017. Informal 
Walsh, G.S., Low, D.C., Arkesteijn, M., 2018. The effect of prolonged level and uphill processing of electronic waste at Agbogbloshie, Ghana: workers’ knowledge about 
walking on the postural control of older adults. J. Biomech. 69, 19–25. https://doi. associated health hazards and alternative livelihoods. Glob. Health Promot 24, 
org/10.1016/j.jbiomech.2018.01.015. 90–98. https://doi.org/10.1177/1757975916631523. 
Wærsted, M., Hanvold, T.N., Veiersted, K.B., 2010. Computer work and musculoskeletal Yusoff, N.A.M., Ganeson, S., Ismail, K.F., Juahir, H., Shahril, M.R., Lin, L.P., Ahmad, A., 
disorders of the neck and upper extremity: a systematic review. BMC Muscoskel. Wafa, S.W., Harith, S., Rajikan, R., 2018. Physical activity level among 
Disord. 11 (1), 79. undergraduate students in Terengganu, Malaysia using pedometer. J. Fund. Appl. 
Wath, S.B., Dutt, P.S., Chakrabarti, T., 2011. E-waste scenario in India, its management Sci. 10, 512–522. 
and implications. Environ. Monit. Assess. 172, 249–262. https://doi.org/10.1007/ Zhang, L., Xu, Z., 2016. A review of current progress of recycling technologies for metals 
s10661-010-1331-9. from waste electrical and electronic equipment. J. Clean. Prod. 127, 19–36. https:// 
Wittsiepe, J., Fobil, J.N., Till, H., Burchard, G.-D., Wilhelm, M., Feldt, T., 2015. Levels of doi.org/10.1016/J.JCLEPRO.2016.04.004. 
polychlorinated dibenzo-p-dioxins, dibenzofurans (PCDD/Fs) and biphenyls (PCBs) 
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