ArticlePDF Available

Abstract and Figures

Occupational exposure associated with unstructured, informal e-waste recycling has received very limited attention. This study aimed to quantify the occupational physical exposures among informal e-waste workers at the largest e-waste site in Africa. A cross-sectional field survey of 163 male e-waste workers was conducted using a self-report occupational physical activity questionnaire, along with direct work observations, and pedometer estimates of walking activity 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.
Content may be subject to copyright.
Authors: Augustine A. Acquah1,*, Clive D'Souza2, Bernard J. Martin2, John Arko-Mensah1, Paul
K. Botwe1, Prudence Tettey1, Duah Dwomoh1, Afua Amoabeng Nti1, Lawrencia Kwarteng1,
Sylvia Takyi1, Isabella A. Quakyi1, Thomas G. Robins3, Julius N. Fobil1
1. Department of Biological Environmental and Occupational Health Sciences, School of
Public Health, University of Ghana, Accra, Ghana.
2. Center for Ergonomics, Department of Industrial and Operations Engineering, University
of Michigan, Ann Arbor, MI, USA.
3. Environmental Health Sciences, School of Public Health, University of Michigan, Ann
Arbor, MI, USA.
* Corresponding Author: Augustine A. Acquah, Department of Biological, Environmental and
Occupational Health Sciences, P.O. Box LG 13, School of Public Health, CHS, University of
Ghana; email:
Acquah, A. A., D'Souza, C., Martin, B. J., Arko-Mensah, J., Botwe, P., Tettey, P., Dwomoh, D.,
Nti, A. A., Kwarteng, L., Tyaki, S., Quaki, I., Robins, T., & Fobil, J. N. (2021). A Preliminary
Assessment of Physical Work Exposures among Electronic Waste Workers at Agbogbloshie,
Accra Ghana. International Journal of Industrial Ergonomics, 82 (2021), 103096. DOI:
This study examined physical work exposures associated with informal e-waste recycling
at the largest dumpsite in Africa.
Data on self-reported work activity (n = 163), pedometry (n = 42) and from observations
at the e-waste site were analyzed.
Duration of work-related sitting, standing and walking differed significantly between
collectors, dismantlers, and burners.
E-waste collectors (91%), dismantlers (66%) and burners (94%) reported manual material
handling on ≥5 days per week.
Exposure assessment methods adapted to environmental and socioeconomic conditions of
informal e-waste recycling are needed.
Occupational exposure associated with unstructured, informal e-waste recycling has received very
limited attention. This study aimed to quantify the occupational physical exposures among
informal e-waste workers at the largest e-waste site in Africa.
A cross-sectional field survey of 163 male e-waste workers was conducted using a self-report
occupational physical activity questionnaire, along with direct work observations, and pedometer
estimates of walking activity 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.
Keywords: E-waste; informal recycling; e-waste collection; physical activity exposure; OPAQ;
Electrical and electronic waste (e-waste) poses a new global health challenge (Bakhiyi et al., 2018;
Perkins et al., 2014). Rapid technological advances and high demand for new electronic and
electrical equipment has led to accelerated obsolescence and a shorter lifespan for modern-day
electronic appliances, devices and gadgets (Shamim and Mursheda, 2015). Consequently,
managing and recycling the sheer volume of discarded e-waste has created a global environmental
and occupational health problem. Each year, large volumes of e-waste from Europe and North
America get shipped to developing countries such as Ghana, Nigeria and South Africa (Maphosa
and Maphosa, 2020; Oteng-Ababio, 2012). While a small fraction of these electronics get put to
second-hand use, the majority (estimated over 80%) are either unusable or very close to their end-
of-life and end up in dumpsites (Maphosa and Maphosa, 2020). Subsequently, sustainable
management of these waste in a manner that is environmentally and occupationally safe has
become a challenge (Adanu et al. 2020; Bakhiyi et al., 2018).
E-waste recycling activities in middle- and low-income countries is particularly challenging due
to the lack of appropriate recycling infrastructure and policy (Maphosa and Maphosa, 2020). Safe
work methods and equipment required for efficient extraction of re-usable and/or valuable
constituents from old, discarded electronic appliances and devices are lacking (Zhang and Xu,
2016). The recycling process is almost exclusively manual, informal, unregulated and conducted
by low-skilled workers, with little or no attention to occupational health and safety practices such
as the use of personal protective equipment or properly designed workstations. Manual e-waste
recycling is labour-intensive and has become an emerging global health problem due to the health
risks it presents (Perkins et al., 2014). Prior studies describe manual waste collection as requiring
varying levels of manual material handling (MMH) combined with long periods of sitting and/or
standing in non-neutral postures, and/or walking in unfavourable outdoor environmental
conditions (Emmatty and Panicker, 2019; Kuijer et al., 2010). These forms of physical activities
are likely to have adverse effects on the health of workers (Kwon et al., 2011), and more
particularly when performed under harsh environmental conditions (Kong et al., 2018). Studies
specific to informal e-waste recycling work at worksites in China (Chi et al., 2011), India (Wath
et al., 2011), Brazil (Gutberlet and Baeder, 2008), and Nigeria (Ohajinwa et al., 2018) collectively
suggest diverse socioeconomic realities and work conditions across locations, while highlighting
the pervasive problem of informal e-waste recycling faced by many countries around the world.
1.1. Background on E-waste Recycling at Agbogbloshie, Ghana.
Over the last 20 years, Agbogbloshie in Accra, Ghana, has become one of the largest dumping
grounds for electronic waste in the world (Heacock et al., 2016), making it one of the most polluted
places on earth (Bernhardt and Gysi, 2013; Oteng-Ababio, 2012). E-waste workers at this site are
among the poorest and the most vulnerable members of the urban populations in Ghana (Akormedi
et al., 2013; Amankwaa, 2013). The site is occupied mainly by migrants from the northern part of
Ghana. Among them are farmers who have travelled to Southern Ghana including Agbogbloshie
to look for alternate sources of income. The primary goal of e-waste recycling at Agbogbloshie is
to recover valuable scrap metals such as copper, gold, iron and aluminium for sale (Acquah et al.,
2019; Akormedi et al., 2013). The major processes consist of scavenging and collecting e-waste
items, then manually dismantling irreparable and/or non-functional items, and finally open-air
burning of insulated wires and other components that cannot be dismantled in order to extract
valuable metals. Engaging in informal e-waste recycling at Agbogbloshie is known to adversely
affect the health of workers due to high exposure to toxic chemicals (Basu et al., 2016; Feldt et al.,
2014; Srigboh et al., 2016; Wittsiepe et al., 2015), elevated noise (Akormedi et al., 2013; Burns et
al., 2016; Carlson and Krystin, 2016), and harsh environmental conditions (Akormedi et al., 2013;
Burns et al., 2016; Yu et al., 2017).
Prior studies on the physical work conditions and work-related physical activity exposures of e-
waste workers at Agbogbloshie have only provided qualitative interview-based descriptions
(Acquah et al., 2019; Akormedi et al., 2013; Yu et al., 2017). These studies offer evocative
summaries of the physical work conditions and various work-related illnesses and injuries. For
example, a recent qualitative study by Acquah et al., (2019) reported both acute injuries (e.g.,
burns, lacerations) and chronic health issues such as musculoskeletal pains, coughs, and headaches
across the three main categories of e-waste workers: collectors, dismantlers and burners. The
adverse work-related health effects were compounded by the lack of use of personal protective
equipment, low level of health risk awareness, and by evidence of psychosocial stressors
associated with e-waste recycling. The latter includes psychological demands, poor social support,
low income, and limited opportunities for other types of gainful employment (Acquah et al., 2019;
Akormedi et al., 2013; Yu et al., 2017). However, reliable quantitative data on the nature of the
physical exposures at the Agbogbloshie work site is lacking. Hence, we undertook an initial step
to quantifying these physical work exposures in order to understand the magnitude of the risk of
developing work-related musculoskeletal disorders (MSDs) towards the longer-term goal of
developing appropriate ergonomic interventions adapted to the local context.
1.2 Occupational Exposure Assessment in Informal Work
Ergonomics studies on occupational physical exposures among low-skilled workers who engage
in non-structured, informal work such as waste collection and sorting is relatively scarce (Emmatty
and Panicker, 2019; Todd, 2009). To date, most studies on occupational exposures to injury risk
factors have largely focused on formal industrial settings such as manufacturing (Bao et al., 2015;
Dickerson et al., 2018; Lavender et al., 1999; Marshall et al., 2000; Mossa et al., 2016; Silverstein
et al., 1987), construction (Buchholz et al., 1996; Parida and Ray, 2012), agriculture (Kong et al.,
2018) healthcare (Czuba et al., 2012; Janowitz et al., 2006; Punnett and Bergqvist, 1999; Robertson
et al., 2012; Stucke and Menzel, 2007) or office work (Armstrong et al., 1994; Wærsted et al.,
2010), to cite only a few. The main focus of these physical work exposure assessments include
quantifying the magnitude of the exposure (e.g., intensity of force exertions, weight of loads
carried, non-neutral postures), the repetitions involved, and the duration of the exposure (Andreas
and Grooten, 2018; Chiasson et al., 2012; Li and Buckle, 1999; Takala et al., 2010). These physical
exposures are predisposing factors to the development of work-related MSDs (Eatough et al.,
2012; Kuorinka et al., 1995; Marras, 2008) and potentially interact with a range of other
organisational, psychosocial and individual factors (Bongers et al., 2002; Kuorinka et al., 1995;
Oakman et al., 2014, Bongers et al., 2002; Jaffar et al., 2011) to cause or aggravate MSDs.
A critical aspect of selecting a suitable method for physical exposure assessment is the structure
or regularity of the job content. Structured work environments such as manufacturing assembly
lines are more straightforward to characterize based on a limited amount of exposure data. In
contrast, exposure assessment in non-repetitive manual work (i.e., where the intensity, repetitions,
and duration of the tasks vary over time and between workers) is challenging because the
assessments may need to be performed across multiple workers and over long durations in order
to develop a representative profile of the exposure. Thus, assessment of physical work exposures
in informal and unstructured work settings often require a preliminary job analysis (Acquah et al.,
2019) and use of multiple measurement methods in order to understand their variability (Neitzel
et al., 2013). Methods for quantifying physical work exposures include self-reported
questionnaires, observational methods, direct measurements (Burdorf and van der Beek, 1999; Li
and Buckle, 1999) and biomechanical analyses involving specific tools such as the NIOSH lifting
guide or the University of Michigan’s 3D Static Strength Prediction Program (Chaffin et al., 2006).
Direct measurements and biomechanical analyses provide more accurate results; however, these
methods tend to be expensive (Juul-Kristensen et al., 2001) and their application to non-repetitive
work settings can be challenging (Chaffin et al., 2006). Compared to direct measurements,
assessments relying on observational methods and self-reported questionnaires are more cost-
effective and easier to implement in applied settings, and thus are still widely used despite their
subjective nature and lower accuracy and precision (Takala et al., 2010).
1.3 Study Aims
The primary aim of this study was to quantify the occupational physical activity (OPA) exposures
of e-waste workers engaged in informal e-waste recycling at Agbogbloshie, and to compare these
exposures among the three main e-waste job categories, namely, collectors, dismantlers and
2.1. Study Site and Population
The Agbogbloshie e-waste site is about 0.5km2 (Laskaris et al., 2019). It is located close to the
central business district of Accra (Oteng-Ababio, 2012) near the Agbogbloshie food market, and
along the banks of the Korle lagoon and Odaw river (Davis et al., 2019). The workforce largely
consists of itinerant workers who collect scrap metal and e-waste items, dismantle items to extract
valuable constituents and burn items that cannot be dismantled (Davis et al., 2019). The workers
are almost exclusively males, primarily young adults and occasionally minors (< 18 years old).
2.2. Study Design
A cross-sectional study involving the use of a questionnaire, supplementary field observations,
and pedometry measurements was conducted between August to October 2018. Direct field
observations were conducted on random days throughout the study period in order to contextualize
and supplement the data obtained from questionnaires and direct field measurements. E-waste
workers were recruited for the study by word of mouth. They were recruited from different
locations of the site in an attempt to obtain a diverse sample in terms of job category (i.e. collecting,
dismantling and burning). Following a verbal description of the study objectives and methods, a
self-selected sample of 163 male e-waste workers agreed to participate in the study. Written
informed consent was obtained from all adult participants. For minors, written informed consent
was obtained from the adult relatives they work with or their immediate adult work supervisors.
These work supervisors typically served as guardians for the minors while they were at the e-waste
The study was approved by the College of Health Sciences Ethical Review Committee at the
University of Ghana, Accra. Participants were compensated 30 Ghana Cedis (approximately 5.26
US dollars) after data collection was completed.
2.3. Assessment Tools
2.3.1. Demographic Questionnaire: A brief questionnaire was developed to obtain information
about demographic characteristics (e.g., age, gender), primary job category, main work activities
performed, and work history of participants (e.g. number of years and/or months having worked
in e-waste recycling, average number of days and hours of work per week). A team of 5 researchers
serving as interviewers fluent in English as well as Dagbani, which is the local dialect spoken by
e-waste workers, administered the questionnaire and recorded participant responses on paper. In
addition to the questionnaire, participants’ weight, stature, and stride length were measured and
used later to calibrate the pedometers used in the measurement of cumulative step counts. Stride
length was computed using procedures recommended by the device manufacturer, namely, by
measuring the total distance walked for 10 steps (i.e., measured from the 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,
2.3.2. Modified Occupational Physical Activity Questionnaire (OPAQ): The OPAQ (Reis et
al., 2005), which is a seven-item survey questionnaire, was used to collect information on the
average time spent per week in work-related sitting or standing, walking, and in performing heavy
labour activities such as lifting, carrying, pushing and pulling. For the purposes of this study, we
collectively refer to lifting, carrying, pulling and pushing activities as MMH in place of the less
common term ‘heavy labour activities used in the OPAQ. Modelled on questions from the OPAQ
and Quick Exposure Checklist (QEC; Stanton et al., 2004), participants were also asked to indicate
the maximum weight handled in the workweek during MMH on an ordinal scale as either light
(5kg or less), moderate (6-10kg), heavy (11-20kg), or very heavy (>20kg). Participants were
considered quite adept at estimating weight since they often weigh e-waste items to determine its
financial value (i.e., price when buying or selling) as part of their typical workflow. A pilot study
was conducted in December 2017 to determine the feasibility of using the OPAQ, specifically, to
determine whether participants understood the questions and could respond appropriately to obtain
the desired information. Based on the results and feedback from 15 e-waste workers, three
modifications to the OPAQ were implemented. First, since workers indicated that their estimation
of the proportion of time spent sitting, standing and walking or performing MMH activities was
not reliable (poor estimation of exact time), the questionnaire was modified to obtain a binary
response (Yes/No) to whether each activity was performed for (1) at least 1 hour continuously
during the workday, and (2) a total of 4 hours in a workday. Second, the frequencies of work-
related standing and walking were assessed separately as opposed to the original OPAQ which
assesses standing and walking together. Third, the assessment of MMH activities (labelled “heavy
labour” in the original OPAQ), which form the core component of e-waste recycling, was assessed
by asking participants to rate on an ordinal scale how often they performed lifting, carrying, and
pushing and/or pulling activities within a workweek. The modified version of the OPAQ
(Appendix-A) was administered to the participants, their verbal responses were documented on
the paper questionnaire by the researcher, and subsequently coded into Stata V15 for analysis.
When responding to the questionnaire, participants were instructed to use the full workweek prior
to when the questionnaire was presented as the reference period (i.e., a 7-day period starting
Monday morning).
2.3.3. Pedometer measurements: From the 163 participants, a random subset of 47 participants
were provided a waist belt instrumented with a pedometer (Omron HJ-321) at the start of their
workday and collected at the end of the workday for two consecutive workdays randomly selected
in the study period. The average readings from both workdays were used in the analysis. Ten
pedometers were acquired for the study; however, 5 pedometers were 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 from 47 down to 42 of 163 participants equipped with a pedometer on two
consecutive workdays. Overall, pedometry data obtained from 9 collectors, 27 burners and 6
dismantlers were used in data analysis. The pedometers provided data about total steps count,
aerobic step counts, average steps per minute, distance walked, and energy expenditure
(kilocalories; kcal) over an entire workday. Aerobic steps were recorded whenever a minimum of
60 steps were taken within a 10-minute period (Duchečková and Forejt, 2014). The Omron
pedometer has been validated against other well-known physical activity monitors (Battenberg et
al., 2017; Kendall et al., 2019) and has an accuracy greater than 90% for measuring step counts
(Battenberg et al., 2017). This specific pedometer model has been used widely in other studies that
monitored physical activity (Olzenak & Byrne, 2017; Owoeye et al., 2016; Sampaio et al., 2016;
Yusoff et al., 2018).
2.4. Statistical Analysis
All measures were analysed using the Stata V15 software package (StataCorp LLC, TX).
Descriptive statistics were used to summarise demographic variables and the proportion of workers
who performed different types of OPA. Separate one-way ANOVA tests were used to examine
statistical differences in age, years on the job, days worked per week, and hours worked per day
across the three primary job categories (i.e., collectors, dismantlers, and burners). Separate Chi-
square (χ2) tests were conducted to examine differences in the proportion of participants by primary
job category that reported long durations of sitting, standing, and walking postures, frequent MMH
activities of lifting, carrying, pushing and/or pulling, and maximum load handled, which were
assessed on ordinal rating scales. Significant main effects of job category were further analysed
using Chi-square pairwise tests with a Bonferroni adjustment for multiple comparisons (p < 0.05).
Pedometer measurements (total and aerobic step counts, steps per minute, distance walked, and
energy expenditure) were not normally distributed, and thus medians and interquartile ranges
(IQR) were reported in order to reduce the influence of data outliers. Separate non-parametric
Kruskal-Wallis tests were used to examine significant differences across the three e-waste job
categories for each of the five pedometer measures. Qualitative data obtained from direct
observations were used to supplement and contextualize the quantitative results where possible.
3.1. Participant Demographics
The age of participants ranged from 11 years to 43 years. Of the 163 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 range. Only 6 participants (3.8%) out of those knowing their age were older than
40 years. Work experience represented as the number of years worked in e-waste recycling ranged
from 1 week to 25 years with an average ± standard deviation (SD) of 6.48 ± 5.44 years.
Participants worked for at least 2 days in a week but the majority reported working at least 6 days
(88%) or 7 days (54%) per week. The mean ± SD reported work duration per day was 9.95 ± 2.43
hours and ranged from 2 hours to 14 hours depending on the availability of work and the type of
e-waste recycling activity performed. Direct field observation data revealed an average ± SD work
duration of 6.26 ± 2.63 hours per day with a range of 2 to 12 hours per day with intermittent breaks
that varied considerably from 10 minutes to about 4 hours such as when waiting for recycling
products from other e-waste workers (i.e., from collectors to dismantlers, or from dismantlers to
Based on the primary job performed, 70 (42.9%) of the participants were categorized as collectors,
73 (44.8%) as dismantlers, and 20 (12.3%) as burners. A few of these participants also reported
performing tasks associated with a secondary job category. For instance, 9 collectors (5.5%)
engaged in occasional dismantling of e-waste, 3 collectors (1.8%) and 2 dismantlers (1.2%) also
reported performing burning-related tasks. Due to the small number of such cases, only the primary
job category was used in the subsequent statistical data analysis.
Table 1 summarises the age distribution, the number of years of experience in e-waste work,
number of workdays per week and hours of work per day stratified by the three e-waste job
categories. Collectors had the broadest age range (11 - 43 years). Notably, all the minors in the
study were collectors. The average age differed significantly by job category (p = 0.004). The
mean age was significantly higher for dismantlers (26.7 ± 6.6 years) compared to collectors (23.4
± 6.2; p = 0.007) and burners (22.8 ± 3.9; p = 0.055). Years of work experience in e-waste recycling
also differed significantly by the primary job category (p = 0.013). Years of e-waste work
experience was significantly 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 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 e-waste workers (Table 1).
Table 1 Participant primary job category and demographic characteristics
Job Category(n)
Mean ± SD
ANOVA results
Age in years
Collectors (69)
11 - 43
23.4 ± 6.2
F = 5.77, p = 0.004 *
Dismantlers (70)
18 - 42
26.7 ± 6.6
Burners (18)
18 - 30
22.8 ± 3.9
Years of work
at e-waste site
Collectors (70)
0.02 (1wk) - 22
5.3 ± 5.7
F = 4.45, p = 0.013 *
Dismantlers (73)
1 - 25
7.9 ± 5.4
Burners (20)
1 - 13
5.5 ± 3.2
No. of
workdays per
Collectors (70)
4 - 7
6.3 ± 0.7
F = 1.24, p = 0.292
Dismantlers (73)
2 - 7
6.1 ± 1.0
Burners (20)
2 - 7
6.0 ± 1.1
No. of working
hours per day
Collectors (70)
6 - 14
10.3 ± 1.8
F = 1.30, p = 0.277
Dismantlers (71)
4 - 14
9.8 ± 2.9
Burners (20)
2 - 12
9.4 ± 2.7
* indicates significance at p < 0.05
3.2. Occupational Physical Exposures of E-waste Workers
3.2.1. Sitting, standing and walking
Direct field observations indicated that all of the participants performed their work while either
sitting, standing or walking during the workday. The corresponding proportions are detailed after
the following contextual description to contrast with what is usually assumed in regulated
industrial work. Dismantlers were observed usually sitting on a very low stool or a dismantled
appliance such as an old cathode ray tube television or microwave oven. Hence, sitting was more
of a squatting posture such that the included angles at the knees and hips were less than 90 degrees.
Observations also revealed a diverse range of sitting durations between dismantlers. When not
walking to search for and collect items, the collectors’ mode of sitting varied widely. It involved
sitting on their collection cart that corresponded to a sit-stand posture with the included angle at
the hips and knees exceeding 90 degrees. Collectors also occasionally sat on the ground or on a
piece of log or rock along the route travelled in search of e-waste. A considerable amount of sitting
was observed during workers idle time. Dismantlers and burners took rest breaks seated under a
shed after they exhausted their stock of items to dismantle or burn and waited for supplies.
Collectors were also observed sitting to rest at random intervals and for varying durations while in
search of e-waste in nearby communities. For all workers, standing and walking were done on
uneven surfaces. These surfaces were soft and muddy during rainy periods or hard and bumpy
during the dry season. Walking performed by dismantlers was primarily for transporting insulated
components, cables, and wires to the burners for the extraction of metal, e.g., gold, copper,
aluminium. Due to toxic fumes generated during open-air burning this task was done at short
distances away from the sites where dismantling and other ancillary tasks of weighing and selling
of e-waste products were performed (Laskaris et al., 2019; Nti et al., 2020; Takyi et al., 2020). In
addition to burning insulated copper wire for dismantlers at a fee, some burners also spent 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 2 summarizes the proportion of collectors, dismantlers and burners who reported engaging
in sitting, standing or walking for 1 hour or more continuously in a workday, and separately for a
total of 4 hours or more in the workday during the previous workweek. Sitting continuously for
1 hour in a workday was reported mostly by dismantlers (91.8%) while standing continuously for
1 hour during a workday was reported mostly by burners (95%). Chi-square test of proportions
indicated no statistically significant differences in the proportion of participants across the three
job categories who reported sitting (p = 0.119) or standing (p = 0.070) continuously for 1 hour
in a workday. However, the proportion of participants who reported ≥ 1 hour of continuous
walking differed significantly (p = 0.018) across job categories. Post hoc comparisons revealed
that the proportion of participants reporting continuous walking ≥ 1 hour in a workday was
significantly higher for collectors (92.9%) compared to dismantlers (78.1%; p = 0.038) but not
significantly different from burners (75.0%).
The proportion of participants that spent 4 hours per workday sitting, standing and walking
differed significantly by job category (p < 0.001) for each of the three postures (Table 2). The
proportion of participants that reported sitting for 4 hours was significantly higher for both
dismantlers (82.2%) and burners (65.0%) compared to collectors (30.0%; p < 0.001 and p = 0.013,
respectively). The difference in proportions between dismantlers and burners was not statistically
significant (p = 0.204). The proportion of participants that reported standing for 4 hours was also
significantly higher among dismantlers (49.3%) and burners (60.0%) compared to collectors
(18.6%; p < 0.001 and p = 0.001, respectively). In contrast, walking for a total of 4 hours was
reported at a higher proportion by collectors (88.5%) compared to both dismantlers (54.8%; p <
0.001) and burners (65%; p = 0.038). Differences in proportions between dismantlers and burners
for both prolonged standing and walking were not statistically significant (p > 0.05).
Table 2: Proportion of e-waste workers stratified by job category engaged in work-related
sitting, standing and walking activities.
Job Category (n)
Proportion of participants
Chi-square statistic and
Yes (%)
No (%)
Sitting continuously
for 1 hour during a
Collectors (70)
56 (80.0%)
14 (20.0%)
χ2 = 4.487, p = 0.106,
Fisher’s exact p = 0.119
Dismantlers (73)
67 (91.8%)
6 (8.2%)
Burners (20)
18 (90.0%)
2 (10.0%)
Standing continuously
for 1 hour during a
Collectors (70)
53 (75.7%)
17 (24.3%)
χ2 = 4.881, p = 0.087,
Fisher’s exact p = 0.070
Dismantlers (73)
52 (71.2%)
21 (28.8%)
Burners (20)
19 (95.0%)
1 (5.0%)
Walking continuously
for 1 hour during a
Collectors (70)
65 (92.9%)
5 (7.1%)
χ2 = 7.211, p = 0.027,
Fisher’s exact p = 0.018*
Dismantlers (73)
57 (78.1%)
16 (21.9%)
Burners (20)
15 (75.0%)
5 (25.0%)
Sitting for a total of
4 hours during a day’s
Collectors (70)
21 (30.0%)
49 (70.0%)
χ2 = 40.376, p = 0.001,
Fisher’s exact p = 0.001*
Dismantlers (73)
60 (82.2%)
13 (17.8%)
Burners (20)
13 (65.0%)
7 (35.0%)
Standing for a total of
4 hours during a
day’s work
Collectors (70)
13 (18.6%)
57 (81.4%)
χ2 = 19.384, p = 0.001,
Fisher’s exact p = 0.001*
Dismantlers (73)
36 (49.3%)
37 (50.7%)
Burners (20)
12 (60.0%)
8 (40.0%)
Walking for a total of
4 hours during a
day’s work
Collectors (70)
62 (88.6%)
8 (11.4%)
χ2 = 19.961, p = 0.001,
Fisher’s exact p = 0.001*
Dismantlers (73)
40 (54.8%)
33 (45.2%)
Burners (20)
13 (65.0%)
7 (35.0%)
* indicates significant main effects at p < 0.05
3.2.2. Manual Material Handling Activities
Manual material handling activities identified by direct observations included lifting and carrying
of loads as well as pushing and pulling hand-drawn carts used for transporting e-waste.
Descriptions of observations are followed by quantitative results. The frequency and magnitude
of the load handled differed between tasks and job categories. Loads handled by collectors
included the force to tow or move the hand-drawn collection cart, which is a function of the design
of the cart used, the load on the cart, and the terrain (Jung et al., 2005). The weight of the cart and
the items collected varied from day to day as a function of items identified for recycling. Collectors
also lifted and carried items when loading and unloading the cart. All 25 (15.3%) minors in the
study self-identified as collectors. These minors were observed walking behind their supervisors,
typically an older or senior worker, pushing the hand-drawn cart from the rear as the senior worker
pulled the cart from the front. It is typical for younger entry-level workers arriving at the e-waste
site to assist other workers until they gained some experience and accumulated enough capital
prior to working independently. Loads handled by dismantlers mainly consisted of the weight of
items being dismantled and occasionally the weight of the wheelbarrow used to convey items such
as insulated metal components and wires to the burning site for metal recovery. Manual
dismantling also involved repetitive forceful exertions in non-neutral postures using tools such as
hammers, chisel and screwdrivers. The load handled by burners was mainly from the weight of
components (e.g., insulated cables, wires) being burnt. Lifting and carrying among burners
involved using a long metal rod to lift and flip wires/cables during burning. This was usually done
with the trunk in slight flexion. Occasionally, burners would lift, carry and lower items from a
wheelbarrow onto the ground for burning and this involved moderate to severe forward flexion of
the trunk for short intervals.
Table 3 summarizes the proportion of participants by job category based on their self-reported
frequency of performing the three different MMH activities, namely, lifting, carrying, and
pushing-pulling in the previous workweek. Chi-square test of proportions indicated statistically
significant differences across job categories for each of the three MMH activities (p < 0.001). In
term of lifting activities, a high proportion of collectors (91.2%) and burners (94.1%) reported
performing lifts on 5 days in a week compared to dismantlers (65.8%), with the difference
between collectors and dismantlers being statistically significant (p = 0.001). In contrast, the
proportion of dismantlers that reported lifting activities 3-4 times a week (24.7%) was significantly
higher than collectors (4.4%; p = 0.001). Carrying activities on 5 days per week were performed
mostly by collectors (91.2%) compared to burners (82.4%) and dismantlers (62.5%), with the
difference between collectors and dismantlers being statistically significant (p < 0.001). However,
the proportion of participants that reported carrying on 3-4 days a weeks was significantly higher
among dismantlers (22.5%) compared to collectors (2.9%; p = 0.001). Pushing and/or pulling of a
hand-drawn cart on ≥ 5 days per week was significantly more frequent among collectors (68.2%)
compared to dismantlers (26.4%; p < 0.001) and burners (26.3%; p = 0.003). The proportion of
burners that reported infrequent or no pushing/pulling activities (63.2%) was significantly higher
than the proportion of collectors (28.8%; p = 0.018).
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.
Job Category
None or
1-2 days
per week
3-4 days
per week
5 days
per week
statistic &
Collectors (68)
1 (1.5%)
2 (2.9%)
3 (4.4%)
62 (91.2%)
χ2 = 20.524,
p = 0.002,
Fisher’s exact
p = 0.001*
Dismantlers (73)
0 (0.0%)
7 (9.6%)
18 (24.7%)
48 (65.8%)
Burners (17)
0 (0.0%)
1 (5.9%)
0 (0.0%)
16 (94.1%)
Collectors (68)
0 (0.0%)
4 (5.9%)
2 (2.9%)
62 (91.2%)
χ2 = 26.656,
p < 0.001,
Fisher’s exact
p < 0.001*
Dismantlers (72)
2 (2.8%)
9 (12.5%)
16 (22.2%)
45 (62.5%)
Burners (17)
2 (11.8%)
1 (5.9%)
0 (0.0%)
14 (82.4%)
Collectors (66)
19 (28.8%)
0 (0.0%)
2 (3.0%)
45 (68.2%)
χ2 = 37.053,
p < 0.001,
Fisher’s exact
p < 0.001*
Dismantlers (72)
32 (44.4%)
6 (8.3%)
19 (26.4%)
Burners (19)
12 (63.2%)
1 (5.3%)
1 (5.3%)
5 (26.3%)
* indicates significant main effects at p < 0.05
Table 4 summarizes the number and proportion of participants 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 heavy (>20 kg). Over 86% of all study participants reported handling an object
weighing heavier than 20 kg (i.e., labelled ‘Very heavy). Results from the Chi-square test of
proportions indicated a statistically significant difference among job categories in the level of
maximum weight handled (p = 0.011). The proportion of participants that reported handling
weights heavier than 20 kg was significantly higher for collectors (95.6%) compared to dismantlers
(81.9%, p = 0.034) and burners (68.4%, p = 0.002). The proportion of participants that reported
handling moderate weights between 6 10 kg was significantly higher for burners (15.8%)
compared to collectors (1.5%, p = 0.025). None of the other paired comparisons within weight
category were statistically significant.
Table 4: Number and proportion of participants reporting different categories of maximum
weight handled within a workweek, stratified by job category.
Job Category (n)
Maximum weight handled, n (%)
statistic & p-value
(< 5 kg)
(6 10 kg)
(10 20 kg)
Very heavy
(> 20 kg)
Collectors (68)
0 (0.0%)
1 (1.5%)
2 (2.9%)
65 (95.6%)
χ2 = 15.686, p =
0.016, Fishers
exact p = 0.011*
Dismantlers (72)
2 (2.8%)
5 (6.9%)
6 (8.3%)
59 (81.9%)
Burners (19)
2 (10.5%)
3 (15.8%)
1 (5.3%)
13 (68.4%)
* indicates significant main effects at p < 0.05
3.2.3. Pedometer Measurements
Table 5 summarizes the median and IQR values for regular steps, aerobic steps, steps per minute,
distance covered and energy expenditure (kcal) among the subset of collectors, dismantlers and
burners. Kruskal-Wallis tests indicated no statistically significant differences across the three job
categories for any of the five pedometer measures (p > 0.05). The small sample sizes for collectors
(n = 9) and burners (n = 6) may have contributed to reduced statistical power in detecting any
differences. The median number of regular and aerobic steps were slightly higher for collectors
than burners and dismantlers (Table 5), while the median aerobic step count was lowest (zero) for
dismantlers. The median distance walked by participants in each category was 5.4 km for
collectors, 4.9 km for burners and 3.2 km for dismantlers, respectively. The median calorie
expenditure from walking was marginally higher for burners (190 kcal) compared to collectors
(170 kcal) and dismantlers (122 kcal), however the small sample sizes for collectors and burners
make their respective median estimates relatively unstable.
Table 5: Pedometer measurements obtained from a sub-set of study participants (n = 42)
averaged over 2 workdays and stratified by job category.
Job Category
Total Step
Collectors (9)
χ2 = 3.688,
p = 0.158
Dismantlers (27)
Burners (6)
Aerobic Step
Collectors (9)
χ2 = 3.526,
p = 0.172
Dismantlers (27)
Burners (6)
Steps per
Collectors (9)
χ2 = 2.859,
p = 0.240
Dismantlers (27)
Burners (6)
Distance (km)
Collectors (9)
χ2 = 4.049,
p = 0.132
Dismantlers (27)
Burners (6)
Collectors (9)
χ2 = 3.334,
p = 0.189
Dismantlers (27)
Burners (6)
This study quantified the OPA exposures of e-waste workers at Agbogbloshie with an emphasis
on differences among the three main categories of workers, namely, collectors, dismantlers, and
burners. Notably, the results indicated that the type and level of self-reported exposures vary
substantially between and within worker categories. Despite its preliminary and cross-sectional
nature, this study is only one of few conducted at Agbogbloshie, Ghana that focuses on the physical
demands of informal e-waste recycling. Prior exposure studies were mostly descriptive accounts
(Acquah et al., 2019; Akormedi et al., 2013; Yu et al., 2017), which although insightful, failed to
provide meaningful quantitative information about the source and magnitude of physical activity
exposures. The latter is necessary to enable comparisons with other work settings and/or other
informal e-waste recycling sites in developing countries, to estimate the potential for developing
MSDs, and to guide the design and implementation of tailored ergonomics interventions (e.g.,
engineering controls, health and safety policy, worker training). More broadly, the study adds to
the growing knowledge-base documenting exposure of e-waste workers at Agbogbloshie to
various occupational hazards such as toxic chemicals, air pollutants, and noise (Akormedi et al.,
2013; Basu et al., 2016; Srigboh et al., 2016; Wittsiepe et al., 2015; Yu et al., 2017).
Our results corroborate qualitative findings by Akormedi et al. (2013) and Yu et al. (2017) about
e-waste worker characteristics, the challenging work environment, and the physically strenuous
work conditions prevailing at Agbogbloshie. We discuss the ergonomics implications of these
4.1. E-waste Workers
Participants in this study were mostly collectors (43%) and dismantlers (45%), while burners
comprised only 12% of the study sample. The latter may have reduced statistical power in pair-
wise comparisons of proportions involving burners for some of the exposure variables, e.g.,
between collectors and burners for continuous walking 1 hour. Differences in job content and
financial prospects may explain the smaller number of burners at Agbogbloshie and in our study
sample. Akormedi et al. (2013) reported that burners earned substantially less income per day
compared to collectors and dismantlers (i.e., USD 16 compared to USD 26 and USD 52
respectively, on a good day). The reliance on dismantlers to provide items for burning and the high
exposure to smoke and toxic fumes from open air burning made this task less appealing to workers
(Acquah et al., 2019; Akormedi et al., 2013). Workers at this site did not have assigned roles or
designations. On few occasions, participants reported performing e-waste recycling activities other
than their primary job. For example, a dismantler who did not have enough items to dismantle may
temporarily assume the role of collector and walk/travel into the community in search of more e-
waste items to dismantle. Likewise, a burner who did not have items to burn may assume a
dismantling role by helping other dismantlers to disassemble their items for a small fee or in
exchange for some of the extracted metal (e.g., copper wires). Since such secondary activities were
infrequent and with limited impact on exposure estimates in the present context, these were not
distinguished or differentiated in the present study. However, the potential for fluid roles wherein
worker change their main activities (and hence related exposures) on their own over time may have
implications for prospective longitudinal studies.
Our study also confirmed prior reports that e-waste recycling at Agbogbloshie is performed mainly
by men (Akormedi et al., 2013). The absence of women has been attributed to the high physical
demands of manual e-waste recycling and a preference for less strenuous supportive roles such as
vending food and water to workers (Ahlvin, 2012). The worker population at this site was also
relatively young (mean age of 24.8 years) and included 25 minors (15.3%). All minors in the study
sample were collectors and assisted older workers in scavenging and gathering e-waste items. The
substantial proportion of minors working at the site is particularly concerning since Ghana is a
signatory to multiple international instruments that prohibit child labour (UNICEF, 2019). Our
finding suggests broader concerns about poorly enforced legislation and policies prohibiting child
labour. UNICEF-Ghana estimates that about 21% of children in Ghana aged between 5 to17 years
were involved in child labour and 14% were engaged in hazardous forms of labour (UNICEF,
2019). However, the problem of child labour is not unique to Agbogbloshie but plagues waste
picking/collecting in many developing countries around the world (ILO, 2004).
The experience level of workers recruited for this study varied from as little as 7 days to as high
as 22 years. Experience in e-waste recycling work for the study cohort was least among collectors
(5.3 ± 5.7 years) and highest among dismantlers (7.9 ± 5.4 years). Prior studies suggest that low-
skilled migrants from northern Ghana seeking a means of livelihood were often drawn to e-waste
recycling at Agbogbloshie and often start out as collectors (Akormedi et al., 2013). These
collectors overtime progress to more technical and lucrative roles of e-waste recycling such as
dismantling. Collecting of e-waste requires extensive walking (e.g., over 75% of collectors
performed over 10,000 steps daily) with a low prospect of obtaining e-waste items on any day, as
observed in this study.
E-waste recycling was performed every day of the week. Most participants worked six days per
week and rested either on Fridays or Sundays. Akormedi et al. (2013) suggested that rest days may
correspond to workers religious affiliation with Muslims more likely to take Fridays off while
Christians took Sundays off. Furthermore, e-waste workers reported to spend between 2 and 14
hours a day performing various recycling tasks, with a computed average of about 9 hours per day.
This finding corroborates prior reports of a typical 10-12 hours of work per day among workers at
Agbogbloshie (Akormedi et al. (2013). Variability in the number of hours and work distribution
can be explained by our observations. We noticed that the workday duration depended on the
recycling task being performed and the availability of work to be done. For example, a dismantler
who had few items to dismantle, could complete the task in about two hours and would be idle for
the rest of the day until a new batch of items were available for dismantling from the collectors.
On the other hand, collectors would spend longer time wandering in search of e-waste. Burners
were also engaged in less active work times as burning of a pile of copper wires took under 20
minutes and required occasional manipulation during burning despite continuous standing and
stepping/walking. Some burners kept busy by gathering potentially valuable metal scrap and
remnants littered about the burning sites. Overall, the lack of temporal structure and definitive
roles presents methodological challenges when comparing exposures across time or between work
sites and work domains (e.g., manufacturing, office work).
4.2. Occupational Physical Exposures
Participants exposures to sitting, standing, walking and MMH activities differed substantially by
the primary job category. Particularly concerning were the high proportion of workers that reported
exposure durations 4 hours in the workday (e.g., prolonged sitting, standing, walking) and
frequent exposure to lifting and carrying on 5 days per week. The health implications of these
specific combinations of exposures and job category are discussed in relation to prior research.
However, we advise caution for direct comparisons with activity questionnaires from other work
settings since most studies base their exposures on an 8-hour workday and/or a 5-day workweek
(e.g. Reis et al. 2005).
4.2.1. Sitting: Prolonged sitting was most frequent among dismantlers (Table 2), who assumed
largely deviated postures from sitting on a low stool or non-functional appliance, with excessive
forward flexion and twisting of the trunk while performing their task. Prolonged sitting
(Hoogendoorn et al., 1999) and in non-neutral postures (Roffey et al., 2010a) have been associated
with chronic low back pain. Biomechanical studies have also shown possible adverse effects on
spinal structures from sustained non-neutral trunk postures (Chaffin et al., 2006). Sitting for long
periods at work changes the activation patterns of a number of weight-bearing muscles, which in
the long term affects the curvature of the back resulting in back pain (Beach et al., 2005; Callaghan
& McGill, 2001). Prolonged sitting is also associated with lower bone mineral density due to a
limited physical stress (see Chaffin et al. 2006) and osteoporosis (Kolbe-Alexander et al., 2004).
Thus, prolonged sitting among e-waste dismantlers could increase their risk of work-related low
back pain and disorders, as suggested by the high prevalence of low back disorders among informal
waste collection and processing workers (Emmatty and Panicker, 2019; Ohajinwa et al., 2018).
4.2.2. Standing: Standing at work may be advantageous to the worker in that it provides a large
degree of freedom and ensures a wide range of mobility in the lower limb thereby increasing
efficiency and productivity (Halim and Rahman Omar, 2011). That notwithstanding, prolonged
standing may also lead to muscle fatigue and discomfort (Garcia et al., 2020, 2018, 2016, 2015),
chronic venous insufficiency and other occupational injuries (Garcia et al., 2020, 2018, 2016,
2015; Lafond et al., 2009; Madeleine et al., 1997; Tomei et al., 1999). E-waste recycling activities
such as burning involve a considerable amount of standing (see Table 2) and significant
associations between prolonged standing and work-related low back, lower leg and shoulder MSDs
have been pointed out (Chandrasakaran et al., 2003; Musa et al., 2000). Prolonged standing
transfers the load of the upper body to the lower parts resulting in low back pain (Halim and
Rahman Omar, 2011) and pain in the feet (Messing and Kilbom, 2001). Furthermore, standing
during burning of e-waste is compounded with forward flexion and twisting of the trunk pose
further harm to the low back. Bending and twisting of the spine during work is associated with low
back pain (Chaffin et al., 2006; Marras, 2008; Marras et al., 1998; Wai et al., 2010a).
Reducing the time spent in standing could help decrease the risk of adverse health effect. For
example, the use of cable strippers to extract copper from insulated wires instead of burning could
reduce work-related standing in addition to alleviating some of the health risks to burners from
smoke inhalation and environmental contamination from open-air burning. However, such
interventions had limited success at Agbogbloshie (Adanu et al., 2020; Little, 2016) for
sociocultural reasons that fall outside the scope of the present study.
4.2.3. Walking: Prolonged walking (i.e., walking for hours without taking a break) increases
energy expenditure (Patton et al., 1991) and induces fatigue (Morrison et al., 2016; Pinto Pereira
and Gonçalves, 2011; Walsh et al., 2018; Yoshino et al., 2004) which may increase the risk of
physical discomfort, pain and MSDs. The associated risks may be exacerbated by walking over
uneven, unpaved terrain, in a harsh outdoor environment including hot and humid climate, and/or
with poor air quality due to toxic fumes from open burning and sewage (Akormedi et al., 2013;
Yu et al., 2017). Prolonged walking was most prominent for collectors (88.5%). Numerous studies
have reported an association between prolonged walking and low back pain (Garcia et al., 2016;
Roffey et al., 2010). Thus, e-waste recycling activities that involve long hours of walking such as
when collecting e-waste is likely to pose serious health risks to workers. Walking for prolonged
periods subjects the spine to prolonged biomechanical loading with detrimental effects on spinal
structures (Callaghan and McGill, 2001). Furthermore, collectors often walk these long distances
while pulling a hand-drawn cart which exerts additional compressive and shear stresses on the
spine and the shoulder as predicted by biomechanical analyses (see Chaffin et al. 2006 for review).
Appropriate measures to reduce the adverse effects of these health risks are necessary.
Pedometry generally provides more accurate and reliable estimates of physical activity exposures
than self-report questionnaires (Sitthipornvorakul et al., 2014; Takala et al., 2010). However, direct
measurements are challenging in non-repetitive work settings such as the unregulated, informal e-
waste recycling work investigated in this study. Furthermore, statistical comparisons between self-
reported walking and pedometer measurements were not considered meaningful here since the
former assessed the perceived frequency of continuous walking during the workweek preceding
the administration of the questionnaire, while the pedometers measured the effective walking on
2 consecutive but randomly selected workdays of the study. The high day-to-day variability in
physical activity exposure discussed above further diminishes the validity of direct comparisons
between the pedometry and self-reported data. For instance, some workers were observed
performing secondary e-waste recycling tasks that differ from their primary job during periods of
low work volume.
Non-parametric statistical analysis indicated no significant differences between pedometer
measurements of the three e-waste job categories. Thus, these data need to be interpreted with
caution. However, trends in self-report-based walking and pedometer measurements among job
categories provide useful insights that might have implications for future research at
Agbogbloshie. Median pedometer steps and distances walked were higher for collectors than
burners and dismantlers. Aerobic steps count and cadence (steps/min) were also slightly higher for
collectors than burners and dismantlers (see Table 5). These trends were compatible with the self-
reported questionnaire data and were not surprising considering that collectors travelled long
distances between the e-waste scrapyard and adjacent communities. In contrast, the pedometer-
based total step counts for dismantlers and burners were higher than expected based on trends in
the observations and self-reported data. Compared to burners, the aerobic step counts for
dismantlers and burners were also low suggesting multiple short bouts of walking. About 50% of
dismantlers recorded no aerobic steps likely due to the predominance of sitting or standing in place
to perform their task. On a few occasions, when dismantlers had few parts to work with, they were
observed walking to neighbouring communities in search of e-waste instead of waiting for
collectors to return with e-waste items. Similarly, burners were observed switching to dismantling
tasks for short durations to earn some income while waiting for new items to burn. This may
explain the relatively high pedometer readings on some days which increased the median step
counts (i.e., 5360 steps for dismantlers and 8964 steps for burners) among these otherwise more
sedentary groups. It is also possible that the many short bouts of walking caused burners and
dismantlers to underreport their frequency of continuous walking and thus not adequately captured
by the questionnaire. While these initial study findings may not be decisive, it does provide
evidence that frequent exposure to prolonged sitting, standing and walking is present at levels that
should raise concern. Further systematic study is needed to quantify the variability in these
exposures both between and within workers over time.
4.2.4. Manual Material Handling Activities: E-waste recycling at Agbogbloshie involved
different types and intensities of MMH activities. However, the present study only quantified the
self-reported frequency of performing MMH activities in a workweek. The frequency of MMH
activities differed both between and within job categories. Lifting and carrying were notably more
frequent for burners and collectors than dismantlers, with 80 to 90% of burners and collectors
performing these activities on 5 days per week. Although the frequency of lifting and carrying
was lower for dismantlers than collectors or burners, they reported a high intensity of load handling
suggesting interactions between hand load frequency, intensity, and possibly duration across job
categories. Understandably, pulling and pushing activities was more prevalent among collectors
by definition of their job. However, not all collectors operated carts and instead walked with a
cloth sack to carry e-waste items. The 68% of collectors that reported performing pushing and/or
pulling on 5 or more days in the preceding workweek was in sharp contrast to the nearly 29% of
collectors who reported no pushing and/or pulling in the week. This reinforces the high variability
in work exposures among collectors, with much of this variability potentially related to the choice
of MMH equipment and from success or failure in locating items for recycling on a given day.
MMH activities may be a source of work-related MSD among e-waste workers. Although not
exactly e-waste recycling, manual collection and handling of solid waste performed in informal
settings is associated with a high prevalence of shoulder and low back MSDs (Abou-Elwafa et al.,
2012; Kuijer et al., 2010; Mehrdad et al., 2008). Additionally, there is strong evidence in the
ergonomics literature that identifies MMH including lifting, carrying, pushing and pulling as a
leading cause of work-related shoulder and low back disorders (Hoogendoorn et al., 1999;
Hoozemans et al., 2002; Roffey et al., 2010; Wai et al., 2010b). Hoozemans et al. (2002) have also
reported a dose-response relationship between pushing and/or pulling and shoulder complaints
among industry workers. Although some of these physical activities may not be strenuous when
considered on their own, their repetition and combination with extreme postures contribute to the
development of MSDs, as widely acknowledged in previous studies (Chaffin et al., 2006; Fan et
al., 2014; Latko et al., 1999). Collectively these studies suggest that the extent of MMH activities
performed could predispose e-waste workers at Agbogbloshie to developing work-related MSDs;
thus, calling for additional research to examine associations between specific physical work
exposures and MSDs in this worker population.
4.3. Study Limitations
The unregulated nature of e-waste recycling at Agbogbloshie made it difficult to employ sampling
strategies used in regular industrial work. However, attempts were made to sample participants at
different locations within the e-waste site and on different days to obtain a representative sample.
This study had a modest sample size but was comparable to other survey studies conducted at
Agbogbloshie (n ~ 142 to 180; Adanu et al, 2020; Laskari et al., 2019). Another limitation was
that the accuracy of the self-reported data relies on the ability of participants to recall the duration
and frequency of their typical exposures to the different work activities. This is particularly
challenging in unregulated unstructured work, wherein the exposures vary considerably among
workers, and for the same worker within days and between days. For example, some participants
did not have a response to questions about MMH activities, which reduced the effective sample
size in Tables 3 and 4.
Bias in workers responses to the questions could also stem from self-perceptions about their work
activity exposures as well as low literacy, nuances in local dialects, and differences in
comprehension and interpretation of the questionnaire. To minimize this effect, the present study
employed professional research staff who were familiar with English and the local language as to
conduct the field interviews. The format of the self-report questionnaire responses, whether
continuous, ordinal or categorical, was also important to consider because of the low literacy and
language diversity. During the pilot phase of the study, participants found it difficult to accurately
estimate their proportion of time spent performing the different OPAs. Thus, a categorical scheme
was employed in the modified OPAQ. For example, the time spent in sitting, standing and walking
was presented in two ways: (1) one-hour of continuous activity, and (2) a total of 4 hours of activity
during the workday (Appendix A). As an initial step, this format to the questionnaire helped reduce
participant’s wavering or indecision about the responses and shorter response times. Although
this format made it relatively easy for workers to provide information on their OPA exposures, a
more reliable direct form of quantification of these OPA levels could be explored in future studies.
This study was also limited by its inability to continuously observe workers that were instrumented
with pedometers in order to document the activities they performed which could help explain the
trends in pedometer measurements. There could be a small possibility of some participants with
pedometers being involved in additional activities other than their primary job. However, our
observations of other workers suggested this was infrequent and as such was not considered in our
statistical data analysis.
4.4. Methodological Implications
From a methodological perspective, the current study draws attention to the need for new,
validated methods to measure physical work exposures among workers engaged in informal e-
waste recycling. Due to the challenges of studying informal work settings, in this study we opted
for a multi-method approach, namely, direct observations, self-report questionnaires, and
pedometry. The modified version of the OPAQ was appropriate in capturing information about
some of the most common physical activity exposures among e-waste workers in a short period of
time. However certain quantitative exposure data were missed. First, information about the
frequency of force exertions associated with using hand tools (e.g., hammers, chisels,
screwdrivers), which is typical among dismantlers, was not assessed in the OPAQ. Second,
information about whole-body postures (e.g., standing, seated, squat, stooped) associated with
MMH activities such as lifting, pushing and/or pulling, and magnitude of hand force exertions
during tool use was not obtained. Additional research is needed to quantify the relationships
between the MMH activities performed (type, magnitude or intensity, duration, and frequency)
and the postures used during those activities specific to work methods in low-resource informal
Direct instrumentation-based methods have advantages in terms of accuracy and reliability
(Chaffin et al., 2006; Neitzel et al., 2013), however, the variable nature of informal e-waste
recycling at Agbogbloshie presented some challenges. Pedometers were time and cost-prohibitive
to use and as such not all participants in the study were instrumented with pedometers.
Unfortunately, the pedometers were also perceived by participants as valuable and inexplicably
would go missing during data collection. Five pedometers were not returned in the early stage of
the study, which further limited data collection from more workers. These realities and trade-offs
in field research can limit the ability to fully capture the variability in exposures between workers
and within workers over time. Simple pocket pedometers were used for this study due to their low
cost. Future studies could consider using GPS-enabled activity monitors (i.e., as a way to
potentially track the devices and minimize the risk of loss or theft) and could measure additional
physiological data (e.g., heart rate) to provide better information about the physical workload
experienced. However, regardless of choice of direct instrumentation, this approach would not
capture the sociotechnical and environmental interactions and economic constraints on workers
that influence their choice of job category, work methods and equipment used, and consequently
their work-related exposures.
To understand these realities facing low-skilled, low-income workers in an unregulated, informal
work setting, qualitative direct observations in this study proved just as valuable as the quantitative
questionnaire data. As such, development of a direct observation technique to systematically
sample work content and quantify physical work exposures among e-waste workers may be most
ideal. Direct observation and quantification of workers physical exposures have proven successful
in other non-repetitive work settings such as construction (e.g., the Posture Activity and Tools
Handled (PATH) work-sampling based approach by Buchholz et al., (1996)) and could provide a
template for similar approaches suited to unregulated, informal e-waste recycling. More broadly,
our study findings provide important lessons and motivation for future research to examine
physical activity exposures and associated work-related injury prevalence in the informal e-waste
recycling sector.
This study contributes to the limited literature on work-related activity exposures and work
conditions of e-waste workers at the largest e-waste dumpsite in sub-Saharan Africa. While prior
studies at Agbogbloshie emphasized exposures to toxic chemicals, poor air quality, and noise, this
initial study draws unique attention to the physical work exposures associated with informal e-
waste recycling. E-waste recycling involves varying levels of sitting, standing, walking and a range
of MMH activities that collectively may be detrimental to the musculoskeletal health of the worker.
Self-reported work exposures examined in this study differed substantially between the three
primary e-waste job categories. Long hours of sitting were common among dismantlers while
burners and collectors were more likely to be engaged in prolonged standing and walking
respectively. All job categories had a high proportion of workers performing manual material
handling activities on five or more days in the week. Dismantlers and burners engaged in frequent
lifting and carrying tasks while pushing and/or pulling were most frequent among collectors.
Frequent exposure to these physically demanding activities may compound the musculoskeletal
health effects of prolonged sitting, standing and walking.
Achieving proper balance between sitting, standing, walking and performing MMH activities in
informal e-waste work may help reduce its potential negative health effects. However, the
development of appropriate and context adapted ergonomics interventions relies on accurate and
reliable quantitative information about work exposures and associated work-related injuries. Our
study highlights the need for further occupational safety and ergonomics research in the informal
e-waste recycling sector. Specifically, more objective and reliable assessment methods that can
account for the between and within worker variability in exposures inherent to informal e-waste
work are required. Future studies also need to consider the local economic realities and social
context encountered in an unregulated, low resource and multi-ethnic work environment.
The study was supported by the 1⁄2 West Africa-Michigan CHARTER in GEOHealth with funding
from the United States National Institutes of Health/Fogarty International Center (US NIH/FIC)
(paired grant no 1U2RTW010110-01/5U01TW010101) and Canada’s International Development
Research Center (IDRC) (grant no. 108121-001). Co-authors CD and BM were supported in part
by the training grant T42-OH008455 from the National Institute for Occupational Safety and
Health (NIOSH), Centers for Disease Control and Prevention (CDC). The views expressed in this
publication do not necessarily reflect the official policies of nor endorsement by NIH, NIOSH,
CDC, and/or the Canadian and US Governments.
CRediT authorship contribution statement
Augustine A. Acquah: Conceptualization, Methodology, Investigation, Formal analysis, Writing
- original draft, Writing review & editing, Resources. Clive D'Souza: Conceptualization,
Methodology, Writing - original draft, Writing - review & editing, Supervision, Validation.
Bernard Martin: Conceptualization, Methodology, Writing - original draft, Writing - review &
editing, Supervision, Validation. John Arko-Mensah: Conceptualization, Investigation, Writing
- review & editing, Supervision. Paul K. Botwe: Writing - review & editing, Supervision.
Prudence Tettey: Writing - review & editing, Supervision. Duah Dwomoh: Formal analysis,
Writing - review & editing. Afua Amoabeng Nti: Investigation, Writing - review & editing.
Lawrencia Kwarteng: Investigation, Writing - review & editing. Sylvia Takyi: Investigation,
Writing - review & editing. Isabella A. Quakyi: Conceptualization, Writing - review & editing,
Supervision. Thomas G. Robins: Writing - review & editing, Resources, Supervision, Funding
acquisition. Julius N. Fobil: Conceptualization, Investigation, Resources, Writing - review &
editing, Supervision, Funding acquisition.
Declaration of competing interests
The authors declare that they have no known competing financial interests or personal
relationships that could have appeared to influence the work reported in this paper.
We acknowledge all workers at the Agbogbloshie e-waste site for their cooperation and dedicated
contribution towards this study. We also acknowledge the hard work of our field team at the
University of Ghana School of Public Health who assisted in organising field visits and conducting
worker interviews.
Appendix A: 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
Prolonged sitting (4 hours or more per day)
Sitting continuously for 1 hour or more
* Standing activities
Prolonged standing (4 hours or more per day)
Standing continuously for 1 hour or more
* Walking
Prolonged walking (4 hours or more per day)
Walking for 1 hour 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
1-2 days last
3-4 days last
5 or more days
last week
Lifting items
Carrying load
Pushing or pulling a cart
or truck
Q3. If you did any of the above, what is the maximum weight you usually handle while
performing these tasks?
Light (5kg or less)
Moderate (6-10kg)
Heavy (11-20 kg)
Very heavy (>20kg)
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-sectional
study. BMJ Open 2.
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 with
informal electronic waste recycling at Agbogbloshie, a suburb of Accra, Ghana. Proc. Hum.
Factors Ergon. Soc. Annu. Meet. 63, 938942.
Adanu, S. K., Gbedemah, S. F., & Attah, M. K. (2020). Challenges of adopting sustainable
technologies in e-waste management at Agbogbloshie, Ghana. Heliyon, 6(8), e04548.
Ahlvin, K., 2012. The burden of the Kayayei: cultural and socio-economic difficulties facing
female porters in Agbogbloshie. Pure Insights, 1(1), p.4.
Akormedi, M., Asampong, E., Fobil, J.N., 2013. Working conditions and environmental
exposures among electronic waste workers in Ghana. Int. J. Occup. Environ. Health 19,
Amankwaa, E.F., 2013. Livelihoods in risk: exploring health and environmental implications of
e-waste recycling as a livelihood strategy in Ghana. J. Mod. Afr. Stud. 51, 551575.
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 16, 8
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, 3035.
Bakhiyi, B., Gravel, S., Ceballos, D., Flynn, M.A., Zayed, J., 2018. Has the question of e-waste
opened a Pandora’s box? An overview of unpredictable issues and challenges. Environ. Int.
110, 173192.
Bao, S.S., Kapellusch, J.M., Garg, A., Silverstein, B.A., Harris-Adamson, C., Burt, S.E., 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 multiple independent
studies: An example of a consortium study of carpal tunnel syndrome. Occup. Environ.
Med. 72, 130137.
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 and
Environmental Health Risks Associated with Informal Sector ActivitiesSelected Case
Studies from West Africa. NEW Solut. A J. Environ. Occup. Heal. Policy 26, 253270.
Battenberg, A.K., Donohoe, S., Robertson, N., Schmalzried, T.P., 2017. The accuracy of
personal activity monitoring devices. Semin. Arthroplasty 28, 7175.
Beach, T.A.C., Parkinson, R.J., Stothart, J.P., Callaghan, J.P., 2005. Effects of prolonged sitting
on the passive flexion stiffness of the in vivo lumbar spine. Spine J. 5, 145154.
Bernhardt A, Gysi N. 2013. The worlds worst 2013: The top ten toxic threats. Clean‐up, progress
and ongoing challenges. New York City: Blacksmith Institute and Green Cross Switzerland.
Retrieved October 10, 2020, from:
Bongers, P.M., Kremer, A.M., Laak, J. Ter, 2002. Are psychosocial factors, risk factors for
symptoms and signs of the shoulder, elbow, or hand/wrist?: A review of the
epidemiological literature, in: American Journal of Industrial Medicine. John Wiley & Sons,
Ltd, pp. 315342.
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 work. Appl.
Ergon. 27, 177187.
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, 2530.
Burns, K., Sun, K., Fobil, J., Neitzel, R., 2016. Heart Rate, Stress, and Occupational Noise
Exposure among Electronic Waste Recycling Workers. Int. J. Environ. Res. Public Health
13, 140.
Callaghan, J.P., McGill, S.M., 2001. Low back joint loading and kinematics during standing and
unsupported sitting. Ergonomics 44, 280294.
Carlson, K., Krystin, 2016. Electronic Waste Worker Health, in: Proceedings of the Eighth
International Conference on Information and Communication Technologies and
Development - ICTD ’16. ACM Press, New York, New York, USA, pp. 1–4.
Chaffin, D. B, Andersson, G.B.J., Martin, B.J., 2006. Occupational Biomechanics, 4th Edition.
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.
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, 731742.
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. J. Ind.
Ergon. 42, 478488.
Czuba, L.R., Sommerich, C.M., Lavender, S.A., 2012. Ergonomic and safety risk factors in
home health care: Exploration and assessment of alternative interventions. Work 42, 341
Davis, J.M., Akese, G., Garb, Y., 2019. Beyond the pollution haven hypothesis: Where and why
do e-waste hubs emerge and what does this mean for policies and interventions? Geoforum
98, 3645.
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 transfer
tasks. Ergonomics 61, 10941101.
Duchečková, P., Forejt, M., 2014. Aerobic steps as measured by pedometry and their relation to
central obesity. Iran. J. Public Health 43, 10708.
Eatough, E.M., Way, J.D., Chang, C.H., 2012. Understanding the link between psychosocial
work stressors and work-related musculoskeletal complaints. Appl. Ergon. 43, 554563.
Emmatty, F.J., Panicker, V. V., 2019. Ergonomic interventions among waste collection workers:
A systematic review. Int. J. Ind. Ergon. 72, 158172.
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 lateral
epicondylitis in a working population. Hum. Factors 56, 151165.
Feldt, T., Fobil, J.N., Wittsiepe, J., Wilhelm, M., Till, H., Zoufaly, A., Burchard, G., Göen, T.,
2014. High levels of PAH-metabolites in urine of e-waste recycling workers from
Agbogbloshie, Ghana. Sci. Total Environ. 466467, 369376.
Garcia, M.-G., Tapia, P., Läubli, T., Martin, B.J., 2020. Physiological and neuromotor changes
induced by two different stand-walk-sit work rotations. Ergonomics 63, 163174.
Garcia, M.G., Läubli, T., Martin, B.J., 2018. Muscular and Vascular Issues Induced by
Prolonged Standing With Different WorkRest Cycles With Active or Passive Breaks.
Hum. Factors 60, 806821.
Garcia, M.G., Läubli, T., Martin, B.J., 2015. Long-term muscle fatigue after standing work.
Hum. Factors 57, 11621173.
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. Factors 58,
Gutberlet, J., Baeder, A.M., 2008. Informal recycling and occupational health in Santo André,
Brazil. Int. J. Environ. Health Res. 18, 115.
Halim, I., Rahman Omar, A., 2011. A review on health effects associated with prolonged
standing in the industrial workplaces., IJRRAS.
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., Diaz-Barriga,
F., Neira, M., Omar, M., Pascale, A., Ruchirawat, M., Sly, L., Sly, P.D., Van den Berg, M.,
Suk, W.A., 2016. E-Waste and Harm to Vulnerable Populations: A Growing Global
Problem. Environ. Health Perspect. 124, 550555.
Hoogendoorn, W.E., Poppel, M.N. van, Bongers, P.M., Koes, B.W., Bouter, L.M., 1999.
Physical load during work and leisure time as risk factors for back pain. Scand. J. Work.
Environ. Health.
Hoozemans, M.J.M., van der Beek, A.J., Frings-Dresen, M.H.W., van der Woude, L.H. V., van
Dijk, F.J.H., 2002. Pushing and pulling in association with low back and shoulder
complaints. Occup. Environ. Med. 59, 696702.
ILO, I.L.O., 2004. Addressing the exploitation of children in scavenging (waste picking): A
thematic evaluation on action on child labour. A global report for the ILO. Geneva.
Jaffar, N., Abdul-Tharim, A.H., Mohd-Kamar, I.F., Lop, N.S., 2011. A literature review of
ergonomics risk factors in construction industry, in: Procedia Engineering. pp. 8997.
Janowitz, I.L., Gillen, M., Ryan, G., Rempel, D., Trupin, L., Swig, L., Mullen, K., 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, 641658.
Juul-Kristensen, B., Hansson, G.A., Fallentin, N., Andersen, J.H., Ekdahl, C., 2001. Assessment
of work postures and movements using a video-based observation method and direct
technical measurements. Appl. Ergon. 32, 51724.
Kendall, B., Bellovary, B., Gothe, N.P., 2019. Validity of wearable activity monitors for tracking
steps and estimating energy expenditure during a graded maximal treadmill test. J. Sports
Sci. 37, 4249.
Kolbe-Alexander, T.L., Charlton, K.E., Lambert, E. V, 2004. Lifetime physical activity and
determinants of estimated bone mineral density using calcaneal ultrasound in older South
African adults. J. Nutr. Health Aging 8, 52130.
Kong, Y.-K., Lee, S., Lee, K.-S., Kim, D.-M., 2018. Comparisons of ergonomic evaluation tools
(ALLA, RULA, REBA and OWAS) for farm work. Int. J. Occup. Saf. Ergon. 24, 218223.
Kuijer, P.P.F.M., Sluiter, J.K., Frings-Dresen, M.H.W., 2010. Health and safety in waste
collection: Towards evidence-based worker health surveillance. Am. J. Ind. Med. 53, 1040
Kuorinka, I., Forcier, L., Hagberg, M., Silverstein, B., Wells, R., 1995. Work related
musculoskeletal disorders (WMSDs): a reference book for prevention. Taylor & Francis,
Kwon, B.K., Roffey, D.M., Bishop, P.B., Dagenais, S., Wai, E.K., 2011. Systematic review:
Occupational physical activity and low back pain. Occup. Med. (Chic. Ill). 61, 541548.
Lafond, D., Champagne, A., Descarreaux, M., Dubois, J.-D., Prado, J.M., Duarte, M., 2009.
Postural control during prolonged standing in persons with chronic low back pain. Gait
Posture 29, 421427.
Laskaris, Z., Milando, C., Batterman, S., Mukherjee, B., Basu, N., O’Neill, M.S., Robins, T.G.,
Fobil, J.N., 2019. Derivation of Time-Activity Data Using Wearable Cameras and Measures
of Personal Inhalation Exposure among Workers at an Informal Electronic-Waste Recovery
Site in Ghana. Ann. Work Expo. Heal.
Latko, W.A., Armstrong, T.J., Franzblau, A., Ulin, S.S., Werner, R.A., Albers, J.W., 1999.
Cross-sectional study of the relationship between repetitive work and the prevalence of
upper limb musculoskeletal disorders. Am. J. Ind. Med. 36, 248259.<248::AID-AJIM4>3.0.CO;2-Q
Lavender, S.A., Oleske, D.M., Nicholson, L., Andersson, G.B.J., Hahn, J., 1999. Comparison of
Five Methods Used To Determine Low Back Disorder Risk in a Manufacturing
Environment. Spine (Phila. Pa. 1976). 24, 1441.
Li, G., Buckle, P., 1999. Current techniques for assessing physical exposure to work-related
musculoskeletal risks, with emphasis on posture-based methods. Ergonomics 42, 674695.
Jung, M.C., Haight, J.M. and Freivalds, A., 2005. Pushing and pulling carts and two-wheeled
hand trucks. International Journal of Industrial Ergonomics, 35(1), pp.79-89.
Little, P.C., 2016. On electronic pyropolitics and pure earth friction in Agbogbloshie. Toxic
News Nov, 8. Retrieved from:
Madeleine, P., Voigt, M., Arendt-Nielsen, L., 1997. Subjective, physiological and biomechanical
responses to prolonged manual work performed standing on hard and soft surfaces. Eur. J.
Appl. Physiol. 77, 19.
Maphosa, V. and Maphosa, M., 2020. E-waste management in Sub-Saharan Africa: A systematic
literature review. Cogent Business & Management, 7(1), p.1814503.
Marras, W., 2008. The working back: A systems view.John Wiley and Sons.
Marras, W.S., Davis, K.G., Granata, K.P., 1998. Trunk muscle activities during asymmetric
twisting motions. J. Electromyogr. Kinesiol. 8, 247256.
Marshall, M.M., Armstrong, T.J., Martin, B.J., Foulke, J.A., Grieshaber, D.C., Malone, G., 2000.
Exposure to Forceful Exertions and Vibration in a Foundry. Proc. Hum. Factors Ergon. Soc.
Annu. Meet. 44, 1720.
Mehrdad, R., Majlessi-Nasr, M., Aminian, O., Malekahmadi, S. a S.F., 2008. Musculoskeletal
Disorders Among Municipal Solid Waste Workers. Acta Med. Iran. 46, 233238.
Messing, K., Kilbom, A., 2001. Standing and very slow walking: foot pain-pressure threshold,
subjective pain experience and work activity. Appl. Ergon. 32, 8190.
Morrison, S., Colberg, S.R., Parson, H.K., Neumann, S., Handel, R., Vinik, E.J., Paulson, J.,
Vinik, A.I., 2016. Walking-Induced Fatigue Leads to Increased Falls Risk in Older Adults.
J. Am. Med. Dir. Assoc. 17, 402409.
Mossa, G., Boenzi, F., Digiesi, S., Mummolo, G., Romano, V.A., 2016. Productivity and
ergonomic risk in human based production systems: A job-rotation scheduling model. Int. J.
Prod. Econ. 171, 471477.
Musa, R., Kyi, W., Rampal, K.G., 2000. Work-related musculoskeletal symptoms among batik
workers in kelantan. Malays. J. Med. Sci. 7, 137.
Neitzel, R.L., Crollard, A., Dominguez, C., Stover, B., Seixas, N.S., 2013. A mixed-methods
evaluation of health and safety hazards at a scrap metal recycling facility. Saf. Sci. 51, 432
Nti, A.A.A., Arko-Mensah, J., Botwe, P.K., Dwomoh, D., Kwarteng, L., Takyi, S.A., Acquah,
A.A., Tettey, P., Basu, N., Batterman, S., Robins, T.G., Fobil, J.N., 2020. Effect of
Particulate Matter Exposure on Respiratory Health of e-Waste Workers at Agbogbloshie,
Accra, Ghana. Int. J. Environ. Res. Public Health 17, 3042.
Oakman, J., Macdonald, W., Wells, Y., 2014. Developing a comprehensive approach to risk
management of musculoskeletal disorders in non-nursing health care sector employees.
Appl. Ergon. 45, 16341640.
Ohajinwa, C.M., Van Bodegom, P.M., Vijver, M.G., Olumide, A.O., Osibanjo, O., Peijnenburg,
W.J.G.M.G.M., 2018. Prevalence and injury patterns among electronic waste workers in the
informal sector in Nigeria. Inj. Prev. 24, 185192.
Olzenak, K.J., Byrne, J.L., 2017. The Effect of Nutrition Education and Pedometer Use on Type
2 Diabetes Risk Factors in Latino Immigrants.
Omron, 2019. Omron Pedometer Instruction manual [WWW Document]. URL www.register- (accessed 11.12.19).
Oteng-Ababio, M., 2012. When Necessity Begets Ingenuity: E-Waste Scavenging as a
Livelihood Strategy in Accra, Ghana. African Stud. Q. Volume 13.
Owoeye, O., Tomori, A., Akinbo, S., 2016. Pedometer-determined physical activity profile of
healthcare professionals in a Nigerian tertiary hospital. Niger. Med. J. 57, 99103.
Parida, R., Ray, P.K., 2012. Study and analysis of occupational risk factors for ergonomic design
of construction worksystems. Work 41, 37883794.
Patton, J.F., Kaszuba, J., Mello, R.P., Reynolds, K.L., 1991. Physiological responses to
prolonged treadmill walking with external loads. Eur. J. Appl. Physiol. Occup. Physiol. 63,
Perkins, D.N., Brune Drisse, M.-N., Nxele, T., Sly, P.D., 2014. E-Waste: A Global Hazard. Ann.
Glob. Heal. 80, 286295.
Pinto Pereira, M., Gonçalves, M., 2011. EffEcts of fatiguE inducEd by prolongEd gait whEn
walking on thE EldErly. Hum. Mov. 12, 242247.
Punnett, L., Bergqvist, U., 1999. Musculoskeletal disorders in visual display unit work: gender
and work demands. Occup Med 14, 113124.
Reis, J.P., Dubose, K.D., Ainsworth, B.E., Macera, C.A., Yore, M.M., 2005. Reliability and
validity of the occupational physical activity questionnaire. Med. Sci. Sports Exerc. 37,
Robertson, M.M., Boiselle, P., Eisenberg, R., Siegal, D., Chang, C.H., Dainoff, M., Garabet, A.,
Garza, J.B., Dennerlein, J., 2012. Examination of comptuer task exposures in radiologists:
A work systems approach, in: Work. IOS Press, pp. 18181820.
Roffey, D.M., Wai, E.K., Bishop, P., Kwon, B.K., Dagenais, S., 2010. Causal assessment of
awkward occupational postures and low back pain: results of a systematic review. Spine J.
10, 8999.
Roffey, D.M., Wai, E.K., Bishop, P., Kwon, B.K., Dagenais, S., 2010. Causal assessment of
occupational standing or walking and low back pain: results of a systematic review. Spine J.
10, 262272.
Roffey, D. M., Wai, E.K., Bishop, P., Kwon, B.K., Dagenais, S., 2010. Causal assessment of
occupational pushing or pulling and low back pain: results of a systematic review. Spine J.
10, 54453.
Sampaio, L.M.M., Subramaniam, S., Arena, R., Bhatt, T., 2016. Does Virtual Reality-based
Kinect Dance Training Paradigm Improve Autonomic Nervous System Modulation in
Individuals with Chronic Stroke? J. Vasc. Interv. Neurol. 9, 2129.
Shamim, A., Mursheda, K.A., 2015. E-Waste Trading Impact on Public Health and Ecosystem
Services in Developing Countries. Int. J. Waste Resour. 05.
Silverstein, B.A., Fine, L.J., Armstrong, T.J., 1987. Occupational factors and carpal tunnel
syndrome. Am. J. Ind. Med. 11, 343358.
Sitthipornvorakul, E., Janwantanakul, P., van der Beek, A.J., 2014. Correlation between
pedometer and the Global Physical Activity Questionnaire on physical activity
measurement in office workers. BMC Res. Notes 7, 280.
Srigboh, R.K., Basu, N., Stephens, J., Asampong, E., Perkins, M., Neitzel, R.L., Fobil, J., 2016.
Multiple elemental exposures amongst workers at the Agbogbloshie electronic waste (e-
waste) site in Ghana. Chemosphere 164, 6874.
Stanton, N. A., Hedge, A., Brookhuis, K., Salas, E., & Hendrick, H. W. (2004). Quick exposure
checklist (QEC) for the assessment of workplace risks for work-related musculoskeletal
disorders (WMSDs). In Handbook of human factors and ergonomics methods (pp. 74-85).
CRC Press.
Stucke, S., Menzel, N.N., 2007. Ergonomic Assessment of a Critical Care Unit. Crit. Care Nurs.
Clin. North Am. 19, 155165.
Takala, E.-P., Pehkonen, I., Forsman, M., Hansson, G.-Å., Erik Mathiassen, S., Patrick
Neumann, W., Sjøgaard, G., Bo Veiersted, K., Westgaard, R.H., Winkel, J., 2010.
Systematic evaluation of observational methods assessing biomechanical exposures at work,
Source: Scandinavian Journal of Work.
Takyi, S.A., Basu, N., Arko-Mensah, J., Botwe, P., Amoabeng Nti, A.A., Kwarteng, L., Acquah,
A., Tettey, P., Dwomoh, D., Batterman, S., Robins, T., Fobil, J.N., 2020. Micronutrient-rich
dietary intake is associated with a reduction in the effects of particulate matter on blood
pressure among electronic waste recyclers at Agbogbloshie, Ghana. BMC Public Health 20,
Todd, A.I., 2009. Distinctive Ergonomics requirements of developing regions: Economic costs
and benefits, in: Patricia A. Scott (Ed.), Ergonomics in Developing Regions: Needs and
Applications. Taylor and Francis Group, Boca Raton, London, New York, pp. 171184.
Tomei, F., Baccolo, T.P., Tomao, E., Palmi, S., Rosati, M.V., 1999. Chronic venous disorders
and occupation. Am. J. Ind. Med. 36, 653665.
UNICEF, 2019. UNICEF Ghana: Prevention of Child Labour. UNICEF Country Office, Accra-
North, Ghana.
Wærsted, M., Hanvold, T.N. and Veiersted, K.B., 2010. Computer work and musculoskeletal
disorders of the neck and upper extremity: a systematic review. BMC musculoskeletal
disorders, 11(1), p.79.
Wai, E.K., Roffey, D.M., Bishop, P., Kwon, B.K., Dagenais, S., 2010a. Causal assessment of
occupational bending or twisting and low back pain: results of a systematic review. Spine J.
10, 7688.
Wai, E.K., Roffey, D.M., Bishop, P., Kwon, B.K., Dagenais, S., 2010b. Causal assessment of
occupational carrying and low back pain: results of a systematic review. Spine J. 10, 628
Walsh, G.S., Low, D.C., Arkesteijn, M., 2018. The effect of prolonged level and uphill walking
on the postural control of older adults. J. Biomech. 69, 1925.
Wath, S.B., Dutt, P.S., Chakrabarti, T., 2011. E-waste scenario in India, its management and
implications. Environ. Monit. Assess. 172, 249262.
Wittsiepe, J., Fobil, J.N., Till, H., Burchard, G.-D., Wilhelm, M., Feldt, T., 2015. Levels of
polychlorinated dibenzo-p-dioxins, dibenzofurans (PCDD/Fs) and biphenyls (PCBs) in
blood of informal e-waste recycling workers from Agbogbloshie, Ghana, and controls.
Environ. Int. 79, 6573.
Yoshino, K., Motoshige, T., Araki, T., Matsuoka, K., 2004. Effect of prolonged free-walking
fatigue on gait and physiological rhythm. J. Biomech. 37, 12711280.
Yu, E.A., Akormedi, M., Asampong, E., Meyer, C.G., Fobil, J.N., 2017. Informal processing of
electronic waste at Agbogbloshie, Ghana: workers’ knowledge about associated health
hazards and alternative livelihoods. Glob. Health Promot. 24, 9098.
Yusoff, N.A.M., Ganeson, S., Ismail, K.F., Juahir, H., Shahril, M.R., Lin, L.P., Ahmad, A.,
Wafa, S.W., Harith, S., Rajikan, R., 2018. Physical activity level among undergraduate
students in Terengganu, Malaysia using pedometer. J. Fundam. Appl. Sci. 10, 512522.
Zhang, L., Xu, Z., 2016. A review of current progress of recycling technologies for metals from
waste electrical and electronic equipment. J. Clean. Prod. 127, 1936.
... Participation in the informal e-waste sector is a physically demanding job that entails a great deal of walking, lifting, carrying, pushing and pulling (Acquah et al., 2021). In Agbogbloshie, Ghana, 62 of 70 collectors surveyed reported walking at least four hours per day (Acquah et al., 2021). ...
... Participation in the informal e-waste sector is a physically demanding job that entails a great deal of walking, lifting, carrying, pushing and pulling (Acquah et al., 2021). In Agbogbloshie, Ghana, 62 of 70 collectors surveyed reported walking at least four hours per day (Acquah et al., 2021). There are a number of practices that increase the risk of hazards for workers; these include unsafe dismantling and processing practices such as breaking and smashing, as well as open burning. ...
... Consequently, informal workers in the e-waste industry are subject to many health risks, including respiratory issues, neurological and genetic disorders and musculoskeletal disorders (MSDs) (Yu et al., 2017). A study conducted among informal waste workers in Agbogbloshie, Ghana, found that they are at high risk of developing MSDs and work-related disabilities (Acquah et al., 2021). Despite the hazards posed by their work, e-waste workers often do not wear personal protective equipment (Oteng-Ababio et al., 2014;Acquah et al., 2019;Acquah et al., 2021;Adanu et al., 2020). ...
Electronic waste (e-waste) recycling and artisanal and small-scale mining (ASM) are activities that are increasingly finding uptake as a means of providing livelihoods in the face of high unemployment, especially in the developing world. Informal e-waste recycling is typically practiced by individuals or groups of people who collect end-of-use and end-of-life electronic and electrical equipment which they can repair or refurbish and resell as well as break down to sell valuable components. E-waste recycling is a form of urban mining; thus, the intention of the paper is to draw parallels between this form of mining and artisanal gold mining. Artisanal miners extract virgin minerals while 'urban miners' reclaim metals from various waste streams. Both sectors are characterized by high levels of informality and their activities are largely practiced as a means of livelihood. We used the sustainable livelihoods framework (SLF) as a tool to draw this comparison based on available literature on the two sectors, complemented by anecdotal field data. It was found that the livelihood capitals are similar between the two sectors and that there are strong similarities in the vulnerability contexts, with a notable difference being that informal ASM, which has a more significant interaction with the natural environment, places higher demands on natural and physical capital such as land and water pollution and limited access to transport. Recommendations are made on how to strengthen the different capitals of sustainable livelihoods in the hope that these will inform policy decisions on informal sector activities.
... Informal e-waste recycling includes scavenging for end-of-life electronics, manual disassembly of e-waste items to separate the different metal constituents, and open air burning of insulated components (e.g., copper cables) to retrieve valuable metals for sale (Acquah et al., 2019b). The rudimentary methods used in informal e-waste recycling presents enormous health risks to workers and the nearby population (Fischer et al., 2020;Grant et al., 2013) due to exposure to air pollutants (Amoabeng Kwarteng et al., 2020), excessive noise levels (Burns et al., 2019;Burns et al., 2016) and physical agents associated with poor work methods (Acquah, et al., 2021b;Acquah et al., 2019b). ...
... Agbogbloshie, in Accra Ghana is one of the largest e-waste dumpsites and informal e-waste processing hubs in Africa. A recent assessment of physical work exposures at this site found that prolonged walking (often over uneven terrain), sitting, standing and performing manual material handling (MMH) tasks such as carrying, lifting, and pushing of loaded collection carts were prominent among e-waste workers (Acquah et al., 2021b). These exposures are known risk factors for the development of WRMSDs (Jaffar et al., 2011;Kwon, et al., 2011;Marshall et al., 2000;Wai et al., 2010) and might explain the high prevalence (~90%) of MSD symptoms in this population (Acquah et al., 2019a;Acquah, et al., 2021a). ...
... However, handling of heavy loads even for short durations could contribute to the development of LBP if performed with an incorrect posture (e.g., stooped vs. squat posture). Acquah et al. (2021b) found that e-waste workers perform lifting, carrying, and pushing/pulling tasks on five or more days in a work week; however, their study relied on self-reported data unlike the present study which used direct observations. Hence, the cumulative effect of MMH activities may be worth considering in future studies. ...
Full-text available
Rudimentary methods for electronic waste (e-waste) recycling employed in developing countries are a source of work-related musculoskeletal disorders (WRMSDs). A summarized comparison of WRMSDs and preliminary exposure assessment among e-waste dismantlers (D) and burners (B) in Agbogbloshie, Ghana is presented. A cross-sectional study was conducted to investigate WRMSDs and associated risk factors using the Cornell Musculoskeletal Discomfort Questionnaire and a newly developed ergonomic assessment tool. Results indicated higher WRMSDs prevalence in the lower back (68% D vs. 52% B; p = 0.172), shoulder (41% D vs. 29% B; p = 0.279) and upper arm (33% D vs 5% B; p = 0.010). Moderate to severe trunk flexion, high force exertion, repetition and vibration were prevalent risk factors among workers and were significantly higher in dismantlers than burners ( p ≤ 0.001). Detailed ergonomic studies investigating the relationship between physical exposures and WRMSDs are needed to provide a deeper understanding of WRMSD causation in e-waste workers and more particularly in unstructured, unregulated work.
... It is a physically demanding job requiring lots of pushing, pulling, lifting, walking and standing for long periods of time. 62 In addition, unsafe dismantling and processing practices expose workers to more hazards including smashing and breaking goods and open burning of materials. In Cape Town, respondents had a superficial understanding of the risks associated with their work. ...
... A multitude of serious health risks have been identified for those working in e-waste, including respiratory issues as well as musculoskeletal, neurological and genetic disorders. 33,62 Workers are also at risk of developing disabilities. ...
Full-text available
Waste pickers are widely acknowledged as an integral part of the formal and informal economy, diverting waste into the secondary resource economy through urban mining. Urban mining in itself is considered to be a source of livelihoods. We investigated the livelihoods of e-waste pickers through 110 surveys in Cape Town, South Africa. Waste pickers often indicated that they were engaged in the sector not by choice but by necessity, expressing that earning money is the only enjoyable aspect of their job. The results from the study substantiate that it is unlikely that waste pickers could survive on e-waste picking alone as 83.3% of reported incomes were below minimum wage, with 22.9% below the food poverty line. Thus, the majority of waste pickers collected a wide array of recyclables. We also found that the waste pickers in Cape Town engage in multiple e-waste related activities, including collection, dismantling and processing to a lesser extent. They work long hours in arduous working conditions which present multiple hazards for their health and safety. Ultimately, e-waste pickers’ incomes cannot be considered commensurate with the nature of the work. Further, e-waste picking cannot be regarded to significantly contribute to livelihoods, but is rather a survivalist strategy. The survivalist nature of the work does not allow for waste pickers to move upwards in the waste value chain and benefit from greater income opportunities. Furthermore, their lack of skills prohibits waste pickers’ transition to formal employment. With a lack of options, it is necessary to ensure that the waste sector provides opportunities for decent work to enable workers to lift themselves out of poverty. Significance: • E-waste pickers participate in multiple activities across the e-waste value chain including collection, dismantling, processing, and repair and refurbishment. • E-waste pickers in Cape Town cannot make a living on e-waste alone, and supplement their income from collecting other recyclables. • E-waste pickers work long hours in difficult working conditions which pose a threat to their health and safety. • E-waste picking is a survivalist strategy.
... However, most of these assessment methods are timeconsuming (Chaffin et al., 2006;Takala et al., 2010), expensive, and difficult to use due to intense training requirements prior to their use (Buchholz et al., 1996). Other drawbacks of these tools include their lack of flexibility in unregulated work environments wherein the type and intensity of work performed, even by the same individual, are highly variable within and between days (Acquah et al., 2021). Thus, applying the existing ergonomic exposure assessment tools to investigate ergonomic risks in informal, unstructured, and unregulated work setting may be problematic. ...
Existing ergonomic assessment tools have been designed for routine and structured work making their use in informal work setting challenging due to the high variability in tasks performed by informal workers. The Ergonomic Assessment tool for Unstructured Work (EAUW) was developed by Acquah and colleagues to address this challenge. The tool is efficient and has good inter-observer reliability, but little information is known about its other psychometric properties. This paper assesses the reliability and validity of EAUW. Criterion validity was determined by comparing the EAUW with existing tools for a selected number of e-waste recycling tasks. Intra-observer reliability was determined by comparing observations from the same assessor 5 days apart. Results indicated a high intra-observer agreement for all exposure variables. Compared to existing tools which provide a snapshot of ergonomic exposures, the EAUW provides a more detailed estimate of work exposures between- and within-workers across time.
... Table S1: PRISMA 2020 checklist, Table S2: Search strategies and results from different electronic databases, Table S3: Methodological quality of included cross-sectional studies, Table S4: Methodological quality of included cohort studies, Table S5: List of excluded studies at full-text screening stage with brief reasons, Table S6: JBI Critical Appraisal Checklist for Analytical Cross Sectional Studies, Table S7: JBI Critical Appraisal Checklist for Cohort Studies. References [62][63][64][65][66][67][68][69][70] are cited in the supplementary materials. ...
Full-text available
Informal electronic waste (e-waste) recycling in Africa has become a major public health concern. This review examined studies that report on the association between e-waste exposure and adverse human health outcomes in Africa. The review was conducted following the updated version of the Preferred Items for Systematic Review and Meta-analysis (PRISMA 2020) statement checklist. We included papers that were original peer-reviewed epidemiological studies and conference papers, written in English, and reported on e-waste exposure among human populations and any health-related outcome in the context of Africa. Our results from the evaluation of 17 studies found an association between informal e-waste recycling methods and musculoskeletal disease (MSD) symptoms and physical injuries such as back pains, lacerations, eye problems, skin burns, and noise-induced hearing loss (NIHL). In addition, the generation and release of particulate matter (PM) of various sizes, and toxic and essential metals such as cadmium (Cd), lead (Pb), zinc (Zn), etc., during the recycling process are associated with adverse systemic intermediate health outcomes including cardiopulmonary function and DNA damage. This systematic review concludes that the methods used by e-waste recyclers in Africa expose them to increased risk of adverse health outcomes. However, there is a need for more rigorous research that moves past single pollutant analysis.
... In addition, Ohajinwa et al. [29] reported that cuts on the hands/fingers of e-waste workers were the most common injuries. The results in this study showed symptoms related to eye irritation, skin rashes/inflammation, skin peeling symptoms, nasal irritation/nasal stings, coughing/sneezing, inconvenient breathing/jamming symptoms [30] and muscle aches [31][32][33]. ...
Full-text available
To study the knowledge, attitudes and perceptions, to study the health effects, and to investigate the concentration of Pb and Cd in indoor dust samples, drinking water samples, and personal air samples and to assess the health risk among workers who worked at e-waste recycling shops in the southern region, Thailand. This cross-sectional descriptive study was conducted among workers from 136 electronic waste recycling stores in Southern Thailand, between January and July 2021. The study questionnaire was given to the 272 e-waste workers participating. Indoor dust, drinking water, and personal air samples were collected 27 e-waste shops and the concentrations of Pb and Cd in all samples were determined by graphite furnace atomic absorption spectrometry. Descriptive statistics and the simple linear regression were used to analyze. Overall, 176 employees (64.7%) suffered nasal irritation, 181 employees (66.5%) reported coughing/sneezing, and 163 employees (59.9%) had inconvenient breathing/jamming symptoms. Also, 158 employees (58.1%) had skin peeling symptoms, and 188 employees (69.1%) had muscle aches. The results indicate the positive influence of increasing knowledge and attitudes on the average practice score. The hazardous index (HI)-values of indoor dust samples, drinking water samples, and personal air samples were less than 1, was considered health-protective. The results will provide the direct evidence needed by e-waste managers to warn learners. Thus, there is a need for education programme to increase knowledge among the workers. In addition, information dissemination, involvement with organizations and associations is a necessity for workers in this study.
... The uncontrolled burning, disassembly and disposal of e-wastes in Nigeria cause a variety of environmental problems such as ground water contamination atmospheric pollution and water pollution [4]. Each year, large volumes of e-waste from Europe and North America are shipped to developing countries such as Ghana, Nigeria and South Africa [5,6]. In the 1980s, 70% of the world's e-waste was disposed of in China, causing serious and persistent pollution by PBDEs [7]. ...
Full-text available
In this paper, a combination of modification of the source and regulation of the process was used to control the degradation of PBDEs by plants and microorganisms. First, the key proteins that can degrade PBDEs in plants and microorganisms were searched in the PDB (Protein Data Bank), and a molecular docking method was used to characterize the binding ability of PBDEs to two key proteins. Next, the synergistic binding ability of PBDEs to the two key proteins was evaluated based on the queuing integral method. Based on this, three groups of three-dimensional quantitative structure-activity relationship (3D-QSAR) models of plant-microbial synergistic degradation were constructed. A total of 30 PBDE derivatives were designed using BDE-3 as the template molecule. Among them, the effect on the synergistic degradation of six PBDE derivatives, including BDE-3-4, was significantly improved (increased by more than 20%) and the environment-friendly and functional evaluation parameters were improved. Subsequently, studies on the synergistic degradation of PBDEs and their derivatives by plants and microorganisms, based on the molecular docking method, found that the addition of lipophilic groups by modification is beneficial to enhance the efficiency of synergistic degradation of PBDEs by plants and microorganisms. Further, while docking PBDEs, the number of amino acids was increased and the binding bond length was decreased compared to the template molecules, i.e., PBDE derivatives could be naturally degraded more efficiently. Finally, molecular dynamics simulation by the Taguchi orthogonal experiment and a full factorial experimental design were used to simulate the effects of various regulatory schemes on the synergistic degradation of PBDEs by plants and microorganisms. It was found that optimal regulation occurred when the appropriate amount of carbon dioxide was supplied to the plant and microbial systems. This paper aims to provide theoretical support for enhancing the synergistic degradation of PBDEs by plants and microorganisms in e-waste dismantling sites and their surrounding polluted areas, as well as, realize the research and development of green alternatives to PBDE flame retardants.
Full-text available
The study was carried to give a comprehensive overview of different types of ergonomic risks among refuse collectors at Chitungwiza Municipality of Harare District. Descriptive cross-sectional design was used to collect data during the study because it applies both quantitative and qualitative techniques. During the study data was collected using observations, questionnaires and interviews as well as secondary data sources. Generally, 100% of the refuse collectors who participated as questionnaire respondents indicated that they are exposed to musculoskeletal disorders notably muscular strain, shoulder pain and back injuries. Poor lifting techniques, manual loading of waste, awkward postures and carrying of heavy loads were indicated as factors which expose refuse collectors to ergonomic risks at Chitungwiza Municipality in Harare. Causes of ergonomic risks raised by the respondents of the study causes the paper to put attention on measures used to manage risks at the municipalities. Safety training, medical examination and induction were some of the measures used to manage ergonomic risks raised by the refuse collectors. Based on the findings of this research paper, several recommendations were provided notably, continuous training and education, regular health monitoring, improvement of work organisation and collaboration and stakeholder engagement.
Full-text available
The study was carried to give a comprehensive overview of different types of ergonomic risks among refuse collectors at Chitungwiza Municipality of Harare District. Descriptive cross-sectional design was used to collect data during the study because it applies both quantitative and qualitative techniques. During the study data was collected using observations, questionnaires and interviews as well as secondary data sources. Generally, 100% of the refuse collectors who participated as questionnaire respondents indicated that they are exposed to musculoskeletal disorders notably muscular strain, shoulder pain and back injuries. Poor lifting techniques, manual loading of waste, awkward postures and carrying of heavy loads were indicated as factors which expose refuse collectors to ergonomic risks at Chitungwiza Municipality in Harare. Causes of ergonomic risks raised by the respondents of the study causes the paper to put attention on measures used to manage risks at the municipalities. Safety training, medical examination and induction were some of the measures used to manage ergonomic risks raised by the refuse collectors. Based on the findings of this research paper, several recommendations were provided notably, continuous training and education, regular health monitoring, improvement of work organisation and collaboration and stakeholder engagement.
Full-text available
The vulnerability occupational health hazard of ragpickers has emerged as a serious public health threat and has had a tremendous impact on all spheres of the environment nearby landfill and other side of solid waste locations. Since 1970, large numbers of studies have been carried out on the impact of health conditions on ragpickers around the world, but no studies have been carried out on the scientific/systematic review on the impact of health due to their occupational impact at global level. This study aims to systematically assess the scientific review on the impact of occupation on ragpickers and their environmental conditions. For this study, total 339 studies were identified after rigorous review, and 134 studies met the criteria for the review. The literature was surveyed from Scopus, Google Scholar, Research gate, Web of Science, semantic scholar and the Google search engine. The results reveal that (i) most of the studies were carried out continent wise on: Asia, followed by Europe, Africa, and South America. About 69 (51.5%) of the total studies were surveyed from Asia, followed by Africa 32 (23.88%), South America 30 (22.39%), and Europe is only 3 (2.23%) has found in the open database on related to the topic. (ii) in the case of countries, the highest number of studies was performed on India (30.60%), followed by Brazil (19.40), South Africa (14%), Bangladesh (8%), Ghana (6%), Study results out that chemical, biological work place hazard are more risky environmental hazard in their occupations.
Full-text available
The developing world has become the primary destination for used electrical and electronic equipment (EEE) exported by the developed world, making e-waste management critical. This paper aims to determine the state of e-waste management in Sub-Saharan Africa by critically reviewing the corpus on electronic waste (e-waste) management in the region. Even though many studies were conducted on e-waste management, very few are conducted on developing countries who are significant recipients of used EEE. We applied a systematic literature review (SLR) process on research articles retrieved from Web of Science, EBSCO Host and Sabinet databases. Using the keywords that included e-waste management or recycling or policy in Sub-Saharan Africa or Africa, we searched for articles from these databases. We analysed 25 papers selected from 151,558 papers initially retrieved to answer the research questions. The findings revealed that about 80% of research on e-waste management in the Sub-Saharan Africa region was undertaken in three countries: Ghana, Nigeria, and South Africa. The review of the selected articles revealed that lack of policy and limited recycling infrastructure were the main barriers to effective e-waste management. The SLR revealed that most countries in the region practice informal and rudimentary recycling methods. Based on the common barriers identified, our recommendations can provide insight to policymakers, contribute to theory, and offer opportunities for future research.
Full-text available
The study investigated why sustainable technologies are not used to collect, dismantle and sell e-waste at Agbogbloshie given the risk of injury and extensive environmental pollution associated with handling of electronic waste. The study objectives were to examine the nature of technologies adopted to manage e-waste, assess challenges faced in adopting sustainable technologies; determine the missing links between formal and informal e-waste workers. Research questions were; what is the current level of technology adopted to manage e-waste and challenges limiting the adoption of sustainable technologies; and what are the missing links between the formal and informal sectors that limit adoption of sustainable e-waste management strategies. Data collection involved use of questionnaire to gather data on technologies used for e-waste management, challenges faced in using such technologies and what the workers consider as solutions to sustainable e-waste management. Field observations helped to explain waste management operations and questionnaire responses were analyzed using descriptive statistics. Study results show most of the e-waste workers are youthful and not much educated. The use of unsustainable technologies to manage e-waste has contributed to physical injuries to workers and pollution of the environment. A major challenge limiting the use of sustainable technologies is lack of financial resources to acquire modern equipment despite the laborious nature of the work. The paper concludes that sustainable solutions to electronic waste management requires support from government to subsidize the cost of sustainable technologies in e-waste management.
Full-text available
Background: Informal recycling of electronic waste (e-waste) releases particulate matter (PM) into the ambient air. Human exposure to PM has been reported to induce adverse effects on cardiovascular health. However, the impact of PM on the cardiovascular health of e-waste recyclers in Ghana has not been studied. Although intake of micronutrient-rich diet is known to modify these PM-induced adverse health effects, no data are available on the relationship between micronutrient status of e-waste recyclers and the reported high-level exposure to PM. We therefore investigated whether the intake of micronutrient-rich diets ameliorates the adverse effects of ambient exposure to PM2.5 on blood pressure (BP). Methods: This study was conducted among e-waste and non-e-waste recyclers from March 2017 to October 2018. Dietary micronutrient (Fe, Ca, Mg, Se, Zn, and Cu) intake was assessed using a 2-day 24-h recall. Breathing zone PM2.5 was measured with a real-time monitor. Cardiovascular indices such as systolic BP (SBP), diastolic BP (DBP), and pulse pressure (PP) were measured using a sphygmomanometer. Ordinary least-squares regression models were used to estimate the joint effects of ambient exposure to PM2.5 and dietary micronutrient intake on cardiovascular health outcomes. Results: Fe was consumed in adequate quantities, while Ca, Se, Zn, Mg, and Cu were inadequately consumed among e-waste and non-e-waste recyclers. Dietary Ca, and Fe intake was associated with reduced SBP and PP of e-waste recyclers. Although PM2.5 levels were higher in e-waste recyclers, exposures in the control group also exceeded the WHO 24-h guideline value (25 μg/m3). Exposure to 1 μg/m3 of PM2.5 was associated with an increased heart rate (HR) among e-waste recyclers. Dietary Fe intake was associated with a reduction in systolic blood pressure levels of e-waste recyclers after PM exposure. Conclusions: Consistent adequate dietary Fe intake was associated with reduced effects of PM2.5 on SBP of e-waste recyclers overtime. Nonetheless, given that all other micronutrients are necessary in ameliorating the adverse effects of PM on cardiovascular health, nutrition-related policy dialogues are required. Such initiatives would help educate informal e-waste recyclers and the general population on specific nutrients of concern and their impact on the exposure to ambient air pollutants.
Full-text available
Background: Direct and continuous exposure to particulate matter (PM), especially in occupational settings is known to impact negatively on respiratory health and lung function. Objective: To determine the association between concentrations of PM (2.5, 2.5-10 and 10 µm) in breathing zone and lung function of informal e-waste workers at Agbogbloshie. Methods: To evaluate lung function responses to PM (2.5, 2.5-10 and 10 µm), we conducted a longitudinal cohort study with three repeated measures among 207 participants comprising 142 healthy e-waste workers from Agbogbloshie scrapyard and 65 control participants from Madina-Zongo in Accra, Ghana from 2017-2018. Lung function parameters (FVC, FEV1, FEV1/FVC, PEF, and FEF 25-75) and PM (2.5, 2.5-10 and 10 µm) concentrations were measured, corresponding to prevailing seasonal variations. Socio-demographic data, respiratory exposures and lifestyle habits were determined using questionnaires. Random effects models were then used to examine the effects of PM (2.5, 2.5-10 and 10 µm) on lung function. Results: The median concentrations of PM (2.5, 2.5-10 and 10 µm) were all consistently above the WHO ambient air standards across the study waves. Small effect estimates per IQR of PM (2.5, 2.5-10 and 10 µm) on lung function parameters were observed even after adjustment for potential confounders. However, a 10 µg increase in PM (2.5, 2.5-10 and 10 µm) was associated with decreases in PEF and FEF 25-75 by 13.3% % [β = −3.133; 95% CI: −0.243, −0.022) and 26.6% [β = −0.266; 95% CI: −0.437, 0.094]. E-waste burning and a history of asthma significantly predicted a decrease in PEF by 14.2% [β = −0.142; 95% CI: −0.278, −0.008) and FEV1 by 35.8% [β = −0.358; 95% CI: −0.590, 0.125] among e-waste burners. Conclusions: Direct exposure of e-waste workers to PM predisposes to decline in lung function and risk for small airway diseases such as asthma and COPD.
Full-text available
Electronic waste (e-waste) is a worldwide problem in terms of increasing production rate in the global waste stream. Its recycling is known to be associated with adverse health outcomes. The recycling site at Agbogbloshie is a major e-waste recycling hub which presents enormous health threats to the residents in this community as a result of exposure to complex mixtures of chemicals associated with the poor work methods employed. This paper describes the processes involved in e-waste recycling at Agbogbloshie and discusses some of the associated health and psychosocial challenges. Direct field observations and in-depth interviews of eight e-waste workers were conducted from November, 2017 to December, 2017. Results from a thematic analysis of the data gathered; suggest that inappropriate recycling methods, financial constraints, and the high physical demands of e-waste recycling work were associated with adverse musculoskeletal health conditions among the workers. A more systematic ergonomic study is currently being undertaken to quantify the associations between physical work exposures and worker musculoskeletal health among e-waste workers in Agbogbloshie. Further studies that focus on locally adapted ergonomic interventions for effective recycling of e-waste and reducing the health risk to workers are needed.
Full-text available
Objectives: Approximately 2 billion workers globally are employed in informal settings, which are characterized by substantial risk from hazardous exposures and varying job tasks and schedules. Existing methods for identifying occupational hazards must be adapted for unregulated and challenging work environments. We designed and applied a method for objectively deriving time-activity patterns from wearable camera data and matched images with continuous measurements of personal inhalation exposure to size-specific particulate matter (PM) among workers at an informal electronic-waste (e-waste) recovery site. Methods: One hundred and forty-two workers at the Agbogbloshie e-waste site in Accra, Ghana, wore sampling backpacks equipped with wearable cameras and real-time particle monitors during a total of 171 shifts. Self-reported recall of time-activity (30-min resolution) was collected during the end of shift interviews. Images (N = 35,588) and simultaneously measured PM2.5 were collected each minute and processed to identify activities established through worker interviews, observation, and existing literature. Descriptive statistics were generated for activity types, frequencies, and associated PM2.5 exposures. A kappa statistic measured agreement between self-reported and image-based time-activity data. Results: Based on image-based time-activity patterns, workers primarily dismantled, sorted/loaded, burned, and transported e-waste materials for metal recovery with high variability in activity duration. Image-based and self-reported time-activity data had poor agreement (kappa = 0.17). Most measured exposures (90%) exceeded the World Health Organization (WHO) 24-h ambient PM2.5 target of 25 µg m-3. The average on-site PM2.5 was 81 µg m-3 (SD: 94). PM2.5 levels were highest during burning, sorting/loading and dismantling (203, 89, 83 µg m-3, respectively). PM2.5 exposure during long periods of non-work-related activities also exceeded the WHO standard in 88% of measured data. Conclusions: In complex, informal work environments, wearable cameras can improve occupational exposure assessments and, in conjunction with monitoring equipment, identify activities associated with high exposures to workplace hazards by providing high-resolution time-activity data.
The potential of rotating postures to alleviate the effects of prolonged standing and sitting postures has been advocated to attenuate the accumulation of muscle fatigue, considered a precursor to musculoskeletal disorders. We aimed to evaluate the effects of two posture rotations, both including standing, walking, sitting, on physiological and neuromotor measures. Twenty-two participants followed two posture rotations, with different rest-break distributions, for 5.25 hrs. Lower-leg muscle twitch force, volume, force control and discomfort perception were evaluated during and after work exposure on two non-consecutive days. Significant changes in all measures indicate a detrimental effect in lower-leg long-lasting muscle fatigue, edema, performance and discomfort after 5 hours for both exposures. However, for both exposures recovery was significant 1-hour and 15 hours post-workday. Differences between the two rotation schedules were not significant. Hence, stand-walk-sit posture rotation promotes recovery of the tested measures and is likely to better prevent muscle fatigue accumulation. Practitioner Summary: Lower-leg muscle twitch force, volume, force control, and discomfort were quantified during and after 5 hours of stand-walk-sit work rotations with two different rest-break distributions. Measures revealed similar significant effects of work exposures regardless of rotation; which did not persist post-work. This beneficial recovery contrasts with the standing only situations.
Waste collection workers are frequently exposed to significant occupational hazards. Even though ergonomic interventions can mitigate these occupational hazards, only a few studies have attempted to study the importance of the interventions. The current review identifies the gaps in ergonomic interventions among waste collection workers. A systematic review and a bibliometric analysis of the literature on the assessment of occupational hazards and ergonomic interventions in different countries were performed to identify the scope of the interventions. A literature search was carried out in Web of Science, PubMed and Scopus for articles published until December 2018. The search yielded seventy articles on the assessment of occupational health and ten articles on ergonomic interventions among waste collection workers. Based on the review, this paper proposes a hierarchical framework for the implementation of ergonomic interventions in waste associated occupations. The problems faced by formal and informal waste collectors are critical, particularly in developing countries and there is a growing need for low-cost interventions. It is suggested that the potential interventions have to be implemented based on the nature of occupational hazard considering social, cultural and economic factors.
The cost of occupational health and safety problems remains substantial in both developed and developing countries. For example, according to the Department of Labor in the United States (United States Department of Labour, 2007a and b), there were 5703 fatalities and 1.2 million cases of injury or illness requiring time off work (with a median number of days away of seven) in 2006, while the Health and Safety Executive (HSE) (2007) indicates that there were 241 fatalities and in excess of 400,000 cases of injury at work (accounting for a total of 36 million working days lost) in Britain. Even in smaller economies such as New Zealand, the costs are significant, with a total of 235,200 occupational injuries costing in excess of 225 million New Zealand Dollars being shown for 2006 (Statistics New Zealand, 2007). Unfortunately such statistics are significantly harder to come by in developing countries. For example in 2008, the International Labor Organisation (2008) only reports on occupational injuries for India in the mining and quarrying sector (38 fatalities and 162 nonfatal injuries per 100,000 workers). According to the South African Department of Labor (2007), a total of 2070 million South African Rands (approximately equivalent to 258.75 million U.S. dollars) was spent on 886,511 workers’ compensation claims.
Initial, and still dominant, explanations of transboundary e-waste flows have relied on the Pollution Haven Hypothesis (PHH), which theorizes that pollution intensive economic activities will relocate to jurisdictions with the most relaxed environmental regulations. This hypothesis has influenced the parameters of the BAN Amendment to the Basel Convention, which uniformly restricts the movement of hazardous waste (including e-waste) from the global North-to-South. Recent research, however, has shown that e-waste does not simply flow to less regulated areas with cheaper labor: for example, flows are not simply from North-to-South, and e-waste processing areas are only in a subset of developing countries and very specific regions within these. Specifically, e-waste processing tends to be done very largely within “hubs,” regional concentrations of firms and organizations, which, though overwhelmingly informal, exhibit many of the characteristics of other kinds of industrial clusters. Thus, a more nuanced theory of e-waste destinations is overdue, promising greater explanatory power as well as more granular and effective policy stances and tools. This paper contributes to these goals by synthesizing indications from the literature on e-waste hubs in Africa and Asia of recurring factors shaping their emergence, and further elaborating these on the basis of our own extensive field research in two very different informal e-waste hubs in Palestine and Ghana. This analysis offers an initial theory of place-specific characteristics and circumstances that attract and facilitate the emergence and agglomeration of such industries. Our findings thus allow us to move beyond the PHH first pass macro conceptualizations to more nuanced and dynamic accounts of e-waste destinations at a regional and even micro-level, as well to challenge and improve upon the policies derived from the PHH framing.