Assessment of Heat Stress Exposure among Construction Workers in the Hot Desert Climate of Saudi Arabia

Abstract

Objectives:
Excessive heat exposure poses significant risks to workers in hot climates. This study assessed the intensity and duration of heat stress exposure among workers performing residential construction in southeastern Saudi Arabia (SA) during the summer, June-September 2016. Objectives were to: identify work factors related to heat stress exposure; measure environmental heat exposure at the construction sites; assess the heat stress risk among workers using the wet bulb globe temperature (WBGT) index; and determine if temperature-humidity indices can be appropriate alternatives to WBGT for managing heat stress risk at the construction sites.

Methods:
Worksite walkthrough surveys and environmental monitoring were performed, indoors and outdoors, at 10 construction sites in Al-Ahsa Province. A heat stress exposure assessment was conducted according to the American Conference of Governmental Industrial Hygienists (ACGIH®) guidelines, which uses the WBGT index. WBGT measurements from two instruments were compared. Alternative heat stress indices were compared to the WBGT: the heat index (HI) and humidex (HD) index.

Results:
Construction workers were exposed to excessive heat stress, indoors and outdoors over a large part of the work day. Complying with a midday outdoor work ban (12-3 p.m.) was not effective in reducing heat stress risk. The highest intensity of exposure was outdoors from 9 a.m. to 12 p.m.; a period identified with the highest hourly mean WBGT values (31-33°C) and the least allowable working time according to ACGIH® guidelines. Comparison of the alternative indices showed that the HI is more reliable than the HD as a surrogate for the WBGT index in the climate studied.

Conclusion:
The extreme heat exposure represents a serious risk. The severity of heat stress and its impact are projected to increase due to climate change, emphasizing the need for immediate improvement of the current required protective measures and the development of occupational heat stress exposure guidelines in SA.

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Original Article
Assessment of Heat Stress Exposure among
Construction Workers in the Hot Desert Climate
of SaudiArabia
Mohammed Al-Bouwarthan1,2,*,, MargaretM. Quinn1, David Kriebel1
and DavidH. Wegman1
1Department of Public Health, College of Health Sciences, University of Massachusetts Lowell, Lowell, MA
01854, USA; 2Department of Environmental Health, College of Public Health, Imam Abdulrahman Bin Faisal
University, P.O. Box 1982, Dammam 31441, Saudi Arabia
*Author to whom correspondence should be addressed. Tel: +1-978-934-3196; E-mail: mohammed_albouwarthan@student.uml.edu
Submitted 10 December 2018; revised 23 February 2019; editorial decision 6 April 2019; revised version accepted 25 April 2019.
Abstract
Objectives: Excessive heat exposure poses significant risks to workers in hot climates. This study as-
sessed the intensity and duration of heat stress exposure among workers performing residential con-
struction in southeastern Saudi Arabia (SA) during the summer, June–September 2016. Objectives
were to: identify work factors related to heat stress exposure; measure environmental heat exposure
at the construction sites; assess the heat stress risk among workers using the wet bulb globe tem-
perature (WBGT) index; and determine if temperature-humidity indices can be appropriate alterna-
tives to WBGT for managing heat stress risk at the construction sites.
Methods: Worksite walkthrough surveys and environmental monitoring were performed, indoors
and outdoors, at 10 construction sites in Al-Ahsa Province. Aheat stress exposure assessment was
conducted according to the American Conference of Governmental Industrial Hygienists (ACGIH®)
guidelines, which uses the WBGT index. WBGT measurements from two instruments were com-
pared. Alternative heat stress indices were compared to the WBGT: the heat index (HI) and humidex
(HD) index.
Results: Construction workers were exposed to excessive heat stress, indoors and outdoors over a
large part of the work day. Complying with a midday outdoor work ban (12–3p.m.) was not effective
in reducing heat stress risk. The highest intensity of exposure was outdoors from 9 a.m. to 12p.m.;
a period identified with the highest hourly mean WBGT values (31–33°C) and the least allowable
working time according to ACGIH® guidelines. Comparison of the alternative indices showed that
the HI is more reliable than the HD as a surrogate for the WBGT index in the climate studied.
Conclusion: The extreme heat exposure represents a serious risk. The severity of heat stress and
its impact are projected to increase due to climate change, emphasizing the need for immediate
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doi: 10.1093/annweh/wxz033
Advance Access publication 3 May 2019
Original Article

improvement of the current required protective measures and the development of occupational heat
stress exposure guidelines in SA.
Keywords: climate change; construction industry; extreme heat; heat stress; heat stress indices
Introduction
Workers in the construction industry are exposed to nu-
merous health and safety hazards leading to the illness
and death of thousands of workers every year (Ringen
etal., 1995; Snashall, 2005; The Center for Construction
Research and Training (CPWR), 2018). Exposure to cli-
matic heat is among the hazards of growing concern in
construction work around the globe (Yang, 2017). Like
many workers in other industries, construction workers
are not in full control of their assigned job activities
(Buchholz etal., 1996), nor do they have full control of
their work environments (Schulte etal., 2016).
Environmental heat exposure is especially relevant
for construction work such as site preparation, construc-
tion or demolition of buildings and infrastructure, and
building decoration and nishing (Rowlinson and Jia,
2015). These types of activities are classied as physic-
ally demanding (Arndt etal., 2005; van der Molen etal.,
2007; Chang etal., 2009; Tak etal., 2011) and their exe-
cution in a safe and productive manner is affected by
many factors including weather conditions (Benjamin
and Greenwald, 1973; Moselhi etal., 1997; Li etal.,
2016; Liu etal., 2018). Performing these activities under
conditions of excessive heat can increase the risk of heat
stress (Rowlinson etal., 2014), which is a combination
of heat gained from the surrounding work environment,
the metabolic cost of the work (workload), and clothing
(Krake, 2018). Exposure to an excessive heat load over
time causes signicant heat strain, which impedes work
performance (mentally and physically; Rodahl, 2003; Yi
and Chan, 2017; Wittbrodt etal., 2018) and increases
the risks of accidents (Sheng etal., 2018), heat-related
illness (Wallace etal., 2005), and fatality (Petitti etal.,
2013).
The negative impacts of heat stress will likely in-
crease due to climate change (Spector and Sheffield,
2014; Acharya etal., 2018), particularly in countries in
arid and tropical zones (Kjellstrom etal., 2009; Andrews
etal., 2018). Saudi Arabia (SA) is among these coun-
tries; it is one of the hottest, sunniest, and largest arid
countries in the world (Alkolibi, 2002; Dargin, 2009;
Krishna, 2014). The weather of SA is becoming hotter,
with average temperatures increasing 0.72°C per decade
since 1990 (Almazroui etal., 2012).Temperatures are
projected to rise further, reaching levels incompatible
with human habitation, particularly in the coastal areas
along the Arabian Gulf (Husain and Chaudhary, 2008;
Pal and Eltahir, 2016). The escalation and persistence
of hot weather during the summer currently poses a sig-
nicant threat to the health and safety of the working
population in SA (Jefri etal., 1990; Noweir etal., 1996;
Noweir and Bafail, 2008). This is particularly true for
the 3.6 million workers employed in the construction
sector (39% of the total workforce in the Saudi private
sector; General Authority for Statistics of Saudi Arabia,
2018), which has a high reported rate of occupational
injuries (Alasamri etal., 2012).
In response to the potential threat of heat stress,
in 2010, the Saudi Ministry of Labor and Social
Development (MLSD) enacted a regulation that bans
outdoor work activities between 12 and 3p.m. each day
during the summer. However, despite the necessity and
practicality of this administrative safety measure, em-
pirical data are lacking about the effectiveness of the
ban in mitigating heat stress. The lack of empirical data
contributes to poor awareness among employers, super-
visors, and workers regarding the potential impacts of
heat stress exposure and to the absence of appropriate
training programs on heat safety and other preventive
interventions in the workplace (Saudi Press Agency,
2014, 2015, 2016).
To address these challenges, we conducted an as-
sessment of heat stress exposure among residential
construction workers in the province of Al-Ahsa in
southeastern SA along the Arabian Gulf, occupying ap-
proximately 24% of the country’s land area (Abdelatti
etal., 2017). It is classied as one of the hottest and
driest regions in the country (Al-Jabr, 1984), with an
average daily maximum temperature ranging from 44
to 46°C during the summer (Presidency of Meteorology
and Environment, 2017). The need for construction in
Al-Ahsa has resulted in the growth of many small- and
medium-sized construction companies, with approxi-
mately 3700 such enterprises employing more than
68000 construction workers (General Organization
for Social Insurance of Saudi Arabia, 2018), the vast
majority of whom are expatriate workers (General
Authority for Statistics of Saudi Arabia, 2018) from
South Asian countries, mainly India, Pakistan, and
Bangladesh.
506 Annals of Work Exposures and Health, 2019, Vol. 63, No. 5

Specic objectives of this study were to: identify work
factors related to heat stress exposure for the main con-
struction jobs; measure environmental heat exposure at
the construction sites; assess the extent of heat stress risk
among workers using the wet bulb globe temperature
(WBGT) index; and determine if temperature-humidity
indices can be appropriate alternatives to WBGT for
managing heat stress risk at the construction sites.
Methods
Studydesign
Qualitative and quantitative data were obtained via
onsite walkthrough surveys and monitoring of work
activities and environmental parameters at 10 residen-
tial construction sites in Al-Ahsa province during the
summer months, June–September 2016. The data were
used to calculate the potential for heat stress among
workers at these sites and to identify time periods to
manage the heat stress. Three heat stress indices were
used to calculate the heat stress potential and recom-
mendations for workable hours derived from each index
were compared. Each index has different strengths and
shortcomings for future use by employers. All study
protocols and materials were approved by the University
of Massachusetts Lowell Institutional Review Board.
Walkthroughsurvey
Ten residential construction sites run by four enterprises
were surveyed (see Supplementary Fig. S1, available at
Annals of Occupational Hygiene online). Walkthrough
surveys were performed at each site on each day en-
vironmental measurements were taken. We gathered
qualitative information about heat stress exposure that
included: work activities performed by each job title;
frequency of worker exposure to direct sun; clothing re-
quirements; and characteristics of onsite lunch and rest
facilities. Additionally, appropriate locations for col-
lecting the environmental measurements were identied.
Hours of work outdoors and indoors by time intervals
and by work effort were estimated based on the sum of
all observations over the 81 sample days. The same job
(for example, plasterer) was observed to have similar
work effort across all of the sites.
Measurement of environmental heat exposure
Indoor and outdoor environmental heat exposure were
assessed using WBGT, which integrates into a single em-
pirical index the main environmental parameters (air
temperature, humidity, wind speed, and solar radiation)
that inuence the body’s thermal balance (Macpherson,
1962). It is calculated by combining the measurements
of dry bulb (air) temperature (Tdb), natural wet bulb
temperature (Tnwb), and globe temperature (Tg) as fol-
lows (International Organization for Standardization
(ISO), 2017).
With solar radiation (outdoors):
WBGToutdoor =0.7 ×Tnwb +0.2 ×Tg+0.1 ×Tdb
(1)
Without solar radiation (indoors):
WBGTindoor =0.7 ×Tnwb +0.3 Tg
(2)
Instruments to measure the WBGT vary in cost, ease
of use, and durability, features that can impact usability
for small enterprises. We compared the performance
of two WBGT instruments, the QUESTemp44 (Quest
Technologies, WI, USA), an instrument used in pre-
vious heat stress studies, and the Kestrel5400 (Nielsen-
Kellerman Co., PA, USA), much smaller in size and
lower in cost (approximately one-sixth the price of the
QUESTemp44 at the time of purchase). Both instru-
ments were equipped with sensors to measure relative
humidity (RH), Tg, and Tdb, which are then utilized to
calculate Tnwb based on the empirical method developed
by Bernard and Pourmoghani (1999). These instruments
were validated to measure WBGT and used in heat
stress exposure research (Bernard and Barrow, 2013;
Cheuvront etal., 2015).
Prior to full-scale environmental monitoring, a pilot
study was conducted at one of the construction sites,
outdoors and indoors, to compare the measurements
obtained by the two instruments collected over 14
consecutive days (1–14 June 2016). The WBGT meas-
urements were recorded at 5-min intervals during the
hottest part of the day, from 7 a.m. to 3p.m. The rst
week (7days), the two instruments were placed side-by-
side indoors, and the second week (7days), they were
placed side-by-side outdoors. Each day, the instruments
were placed at abdominal level, within 2 m of each other
and away from anything that might block or add to ra-
diant heat or air ow. They were allowed to stabilize for
approximately 15min before the measurements were re-
corded. The measurements were compared with a scatter
plot and best-t linear regression line (Supplementary
Fig. S2, available at Annals of Occupational Hygiene on-
line). The results showed a strong correlation between
the WBGT measurements produced by the two instru-
ments (r2=0.99; P <0.05).
Accordingly, both instruments were located in similar
fashion at each of the 10 construction sites throughout
the study to monitor WBGT. The monitoring was per-
formed simultaneously outdoors and indoors for three
consecutive days at each of the 10 sites, starting at site
1; site 2; site 3…; and ending at site 10. This monitoring
Annals of Work Exposures and Health, 2019, Vol. 63, No. 5 507

approach was implemented repetitively, starting
on 15 June through 30 September 2016 excluding
Fridays (n=15)—a non-work day—and public holi-
days (n=12), where the monitoring stopped and re-
sumed thereafter, yielding a total of 81days of WBGT
data (Supplementary Table S1, available at Annals of
Occupational Hygiene online). The QUESTemp44 was
used to measure WBGT outdoors, while the Kestrel5400
was used indoors. Measurements of WBGT were re-
corded every 15min from 5 a.m. to 5p.m.
The possible use of simpler indices that depend on
standard meteorological variables rather than measure-
ments from complicated and expensive devices to guide
future heat stress management programs in SA was
examined by comparing the WBGT estimates of hourly
exposure risks to two commonly used temperature-
humidity indices: the heat index (HI) and the humidex
(HD) using measurements generated from the Tdb and
RH sensors on our WBGT instruments. Since 1905,
over 160 heat indices have been proposed each with
strengths and limitations depending on purpose, setting,
time scale, and health consequences (Gao etal., 2018;
Roghanchi and Kocsis, 2018). We selected the HI and
HD to compare with the WBGT index because they re-
quire only easily available climatic measures and are
associated with recommended guidelines for their appli-
cation in occupational settings.
The HI integrates Tdb and RH to determine the ap-
parent temperature (Steadman, 1979). Bernard and
Iheanacho (2015) provide guidelines for calculating this
index for the assessment of occupational heat stress ex-
posure. While calculation of the HI is complex (Anderson
etal., 2013), a free software program (Weathermetrics
version 1.2.2) readily calculates HI from the Tdb and RH
(Anderson and Peng, 2016).
The HD, based on the combined effects of Tdb and
water vapor pressure (Vp), is commonly used to quantify
thermal comfort in the general population (Masterton
and Richardson, 1979). It was used by the Occupational
Health Clinics for Ontario Workers (OHCOW) to de-
velop a heat response plan for worksite heat stress ex-
posure (OHCOW, 2014). Its calculation is shown in the
equationbelow.
HD =Tdb +0.555 ×(Vp −10)
(3)
where Tdb is in °C, and Vp is in hPa= 6.11 ×
10[(7.5Tdb)/(237.7+Tdb)] × RH/100.
Radiant heat is a major source of heat exposure for
those working outdoors under direct sunlight or indoors
in heat-generating manufacturing processes (e.g. foun-
dries, smelters, and bakeries). The WBGT index incorp-
orates radiant heat, while the other two indices do not.
OHCOW (2014) and Bernard and Iheanacho (2015)
suggested adding an adjustment factor to HD and HI in
the range of 2–3°C to account for the effect of radiant
heat. The adjustment factor is dependent on the intensity
of radiant heat, which reects the increase of globe tem-
perature above dry bulb temperature (ΔTg-db) (Bernard
and Iheanacho, 2015). In this study, the adjustment was
applied as 1°C for ΔTg-db < 4°C; 2°C for ΔTg-db ≥ 4°C, <
7°C; and 3°C for ΔTg-db ≥ 7°C, reecting low, moderate,
and high radiant heat, respectively. These adjustments to
HD and HI indices were applied only for the outdoor
setting, given that the hourly ΔTg-db average was 6°C,
while indoors, the ΔTg-db was 1°C, indicating that the
effect of radiant heat indoors was minimal.
Exposure limits for heatstress
The American Conference of Governmental Industrial
Hygienists (ACGIH®) Threshold Limit Value (TLV®)
was used to determine the risk of heat stress in the study
population. The TLV is calculated for specic heat ex-
posures, as measured by the WBGT, and for specific
work intensity levels performed by acclimatized workers
(ACGIH, 2009). The construction work activities ob-
served in this study (Supplementary Table S2, available
at Annals of Occupational Hygiene online, provides de-
tails and examples) were classied according to ACGIH
guidelines as having workloads (metabolic rates) mainly
in the moderate to heavy range (see Table 1). ACGIH
guidelines provide a simple qualitative framework to
classify workloads (referred to as ‘metabolic work rates’)
as: rest, light, moderate, heavy, and very heavy (ACGIH,
2009).
Exposure above the TLV can result in increased
core body temperature (>38°C). When this occurs, the
ACGIH species hourly work limits, an administrative
control intended to reduce the heat stress exposure to a
safe level (Supplementary Table S3, available at Annals
of Occupational Hygiene online) (ACGIH, 2009). Both
OHCOW (2014) and Bernard and Iheanacho (2015) es-
tablished similar work limits for the HD and HI indices
(Supplementary Tables S4 and S5, available at Annals of
Occupational Hygiene online). The safe work limits es-
timated from each of the three indices were compared.
Data analysis
The four environmental heat parameters (Tdb, Tnwb, Tg,
and RH) that comprise the WBGT index were recorded
over 81days at the 10 construction sites and summar-
ized as hourly WBGT averages, outdoors and indoors,
for daily 12-h periods. Additionally, the four parameters
were assessed individually to evaluate the inuence of
each on the WBGT daily trends. The hourly data were
508 Annals of Work Exposures and Health, 2019, Vol. 63, No. 5

computed by averaging values measured at each 15min
(i.e. 5:00–5:45 a.m.; 6:00–6:45 a.m.…4:00-4:45p.m.).
The hourly occupational risk of heat stress exposure
for light, moderate, and heavy workloads was estimated
as the percentage of time when the WBGT value ex-
ceeded the TLV during each 60-min interval through the
work day. No adjustments to WBGT values were made
for clothing because all workers in the study were ob-
served wearing normal summer (light) clothing (see
below; ACGIH, 2009).
To analyze the effectiveness of the midday work
ban, the number of minutes per hour that work was
permitted (hourly workability, HWA) wasdetermined
based on the ACGIH guidelines. Then, the mean values
of HWA for workers performing moderate and heavy
construction work activities outdoors and indoors
during four consecutive periods of the day (6–9 a.m.;
9 a.m.–12p.m.; 12–3p.m.; and 3–5p.m.) were esti-
mated to compare HWA during the work ban period
with other times in the day. The accumulated propor-
tion of working time spent beyond the HWA was cal-
culated according to two daily work shift scenarios for
both outdoor and indoor exposures. The rst scenario
was a 10-h continuous work shift (5 a.m.–3p.m.),
with two meal breaks (approximately 30min each),
as practiced by some contractors who did not comply
with the afternoon work ban. The second scenario was
a 7-h continuous work shift (5 a.m.–12p.m.), with a
15–20min break, as practiced by compliant contrac-
tors. The impact of the afternoon work ban on reducing
exposure risk was estimated as the difference between
the accumulated allowable working time in these two
scenarios.
Finally, the mean values of the HWA as estimated by
the HI and HD were compared to that of the WBGT-
based index using Cohen’s weighted kappa coefcient
(κw) with quadratic weight to determine the overall
agreement among the indices for workers performing
moderate and heavy construction work activities. This
statistical test assesses agreement for categorical data
on an ordinal scale (Cohen, 1968). The estimated HWA
values were assigned ordinal scale values ranging from
1 to 5.These weights corresponded to HWAs of 60, 45,
30, 15, and 0min, respectively. Agreement between the
indices was examined after stratification by outdoor
and indoor work. The interpretation of κw values was
based on the following criteria: ≤0.20=slight agree-
ment, 0.21–0.40=fair agreement, 0.41–0.60=mod-
erate agreement, 0.61–0.80=substantial agreement, and
0.81–1.00=almost perfect agreement (Landis and Koch,
1977). Data analysis was performed with SPSS Statistics
software version 24 (IBM, 2016).
Table 1. Description of the observed work activities and classification of workload for 10 residential construction sites in
Al-Ahsa Province, SA, June–September2016.
Activity Location Jobs Tasks observed Classication
of workloada
Site preparation Outdoors Laborers
and machine
operators
Demolition, excavation, shoveling, pulling, and pushing
heavy loaded wheelbarrows; surface leveling
Heavy
Formwork Outdoors Carpenters
and laborers
Moderate arm and trunk work to assemble and install
formwork
Moderate
Steel reinforcementOutdoors Steel xers Intense hand, arm, and trunk work to modify and shape
reinforcing steel bars
Heavy
Pouring and n-
ishing concrete
Outdoors All workers Pouring, shoveling, pushing, and leveling of concrete
mix at fast pace
Heavy
Masonry work Outdoors Block layers Intense use of hand, arm, and trunk to lay concrete
blocks
Heavy
Install insulation Indoors/outdoors Insulation
workers
Light manual work involving handling and xing of
insulation material
Light
Install utilities Indoors/outdoors Electricians
and plumbers
Light pushing and pulling, hammering, cutting, and as-
sembly of piping, electric wiring system, and appliances
Moderate
Plastering Indoors/outdoors Plasterers Sustained moderate arm and trunk work to plaster
building surfaces
Moderate
Tiling Indoors/outdoors Tilers Sustained moderate hand and arm work to install tiles Moderate
aLevels of workload for the observed work task activities were estimated utilizing ACGIH guidelines (ACGIH, 2009).
Annals of Work Exposures and Health, 2019, Vol. 63, No. 5 509

Results
Working environment
Nine major jobs and work activities involved in con-
structing residential buildings were identied based on
field observations and onsite discussion with workers
and management (Supplementary Table S2, available at
Annals of Occupational Hygiene online). All construc-
tion workers were Indian nationals, while all construc-
tion managers were Saudi nationals. These construction
activities were performed 6days per week by teams of
2–10 workers. Depending on arrival time at the site,
the typical work day began between 5 a.m. and 6 a.m.
and was supposed to end at 12p.m. as required by the
3-h midday outdoor work ban. Early start times were
designed to take advantage of cooler morning hours
to maintain productivity while complying with the
midday work ban. However, it was observed that four
of the worksites (owned by two of the companies) did
not comply with the work ban; their onsite work activ-
ities, both indoor and outdoor, continued until 3p.m.
Workers at companies that complied with the work
ban worked a maximum of 7h with only a breakfast
break (15–20min). Workers at companies that did not
comply with the ban worked 10h with two meal breaks
(30min each). The latter companies provided workers
with breakfast at approximately 8 a.m. and lunch at
approximately 1p.m. At each site, in general, workers
were provided access to one 19-l drinking water cooler
for a team of 2–4 workers or two water coolers for 5 or
more workers. Commonly, we observed two coolers for
a team of <10 workers. Water coolers were lled with
water once at the start of the work day. On study days,
bottles of water kept in a cooler were made available to
workers being observed. Access to and consumption of
water during the study will be addressed in a separate
publication. All the worksites lacked air-conditioned
resting facilities, onsite toilets, and nearby sources
of water for refilling drinking water containers. The
availability of shaded rest areas varied by job and site.
Generally, all workers wore the same clothing, consisting
of long-sleeved shirts, long pants, work boots or shoes,
baseball caps or head scarves, and polyester or rubber
gloves.
Environmental conditions
Among the 10 construction sites, the indoor and out-
door WBGT values differed by less than 2.0 and 3.4°C,
respectively. Accordingly, subsequent analyses com-
bined the data across all 10 sites, outdoors and indoors.
Detailed presentations of WBGT and Tdb, Tg, Tnwb, and
RH measured hourly at each site are in Supplementary
Table S1, available at Annals of Occupational Hygiene
online.
The hourly mean values of WBGT, for all sites (Fig.
1) show that the workday started with a relatively low
WBGT <26.0°C, both indoors and outdoors, which was
sustained for 2h (5–7 a.m.). Then, the outdoor WBGT
values increased, reaching a peak of 33.0± 3.1°C at 9
a.m., after which the measurements decreased until
a plateau between 12 and 5p.m. (measurements end),
when the outdoor WBGT was 29.6± 1.8°C. Similarly,
the indoor WBGT values began to increase at approxi-
mately 7 a.m. but at a slower rate, until a peak value of
28.8°C was reached between 9 a.m. and 12p.m. and re-
mained at that level through the rest of the afternoon be-
fore dropping to 27.1± 2.8°C in the last hour (4–5p.m.;
Fig. 1).
Assessment of heat stress exposurerisk
The hourly average WBGT values were compared with
heat stress TLVs for the intensity of workload performed
(26.6°C=TLV for heavy work; 28.2°C=TLV for mod-
erate work; and 30.8°C=TLV for light work). Then the
percentage of each hour that WBGT values exceeded the
TLV for a given workload was calculated for outdoors
versus indoors (Fig. 2A,B). During the period from 8
a.m. to 5p.m., when a heavy workload was performed
outdoors, the TLV was exceeded 92–100% of the time.
Exceedances with moderate workload outdoors ranged
from 77 to 93%, while exceedances at a light workload
outdoors ranged between 23 and 71% (Fig. 2A). Indoor
exposures also exceeded the heat stress TLV: for a heavy
workload it was exceeded 61–84% of the time; for mod-
erate and light workloads the risk was 34–50% and
9–17%, respectively (Fig. 2B).
According to the WBGT heat stress exposure limits,
the mean values of HWA during the day indicate that
the 3-h period ‘prior to the ban’ had the lowest HWA
values for both moderate and heavy outdoor work activ-
ities (15 and 9min of allowable work time, respectively;
Table 2). In contrast, for indoor work, the ban period
and the periods before and after had similar HWA
values for moderate and heavy work (~44 and ~30min,
respectively). Regardless of whether the employer com-
plied with the midday work ban, all workers worked
far beyond the HWA for many hours over the summer
months. Workers employed by compliant companies
worked a total of 548h compared with 733h for those
employed by non-compliant companies over the study
period. The cumulative exceedance of the HWA during
these working hours was found to be 60 and 61%, re-
spectively, when performing heavy work activities out-
doors and 49 and 47%, respectively, with moderate
510 Annals of Work Exposures and Health, 2019, Vol. 63, No. 5

work activities. Indoors, the HWA was exceeded for
heavy work by 32 and 33%, work ban compliant versus
non-compliant companies, respectively, and 17 and 14%,
respectively, for moderate work. These exceedances indi-
cate the limited effectiveness of the ban in the preven-
tion of hourly heat stress exposure. However, complying
with the ban led to a reduction in total exposure time
of 185h over the summer months for employees who
worked for compliant companies.
A comparison of the HWA for moderate and heavy
workloads, outdoors and indoors, as determined by the
three heat stress indices (WBGT, HI, and HD) showed
similarities in the uctuations in the outdoor HWA, with
more consistency in the mean HWA values for heavy
workloads than for moderate workloads (Fig. 3A,B).
The differences between the HWA based on the WBGT
compared to the HI ranged from −6 to +2min, while
differences between the WBGT and HD ranged from −3
to +5min (Fig. 3B). Indoors, where the effect of radiant
heat was minimized, all indices demonstrated a similar
gradual decrease in the mean HWA for a heavy work-
load until 3p.m.; for a moderate workload, the HWA
values based on the WBGT and HI were in much closer
agreement throughout the day than those indicated by
the HD (Fig. 4A,B). Overall, all three indices determined
that performing continuous moderate or heavy construc-
tion work in the summer weather, as characterized in
this study, is not advised.
The results of the weighted kappa analysis showed
almost perfect agreement between the WBGT and HI
in the estimates of the HWA, indoors and outdoors,
for both moderate (κw=0.85 and 0.89, respectively)
and heavy workloads (κw=0.88 and 0.90, respect-
ively) (Supplementary Table S6, available at Annals of
Occupational Hygiene online). The comparison between
the HWA using the WBGT and HD indices showed
substantial agreement for moderate workloads indoors
and outdoors (κw=0.71 and 0.80, respectively) and al-
most perfect agreement for heavy workloads performed
both indoors and outdoors (κw=0.88 and 0.91, respect-
ively; Supplementary Table S7, available at Annals of
Occupational Hygiene online).
Discussion
In this study, continuous monitoring of environmental
conditions was conducted June–September 2016 to char-
acterize the daily summer heat trends, indoors and out-
doors, at 10 residential construction sites in the Al-Ahsa
Province, SA, and to assess the corresponding risk of
heat stress among the construction workers. The sites
selected for this study are typical of construction sites
in SA in terms of the onsite work environment and types
of construction work activities. Differences from other
sites in other parts of SA would be attributed mainly
to the size of the construction project and the inuence
Figure 1. Hourly WBGT averaged for 10 residential construction sites in Al-Ahsa Province, SA, June–September 2016. Grey
shading indicates indoor measurements; white indicates outdoor measurements.
Annals of Work Exposures and Health, 2019, Vol. 63, No. 5 5 11

Figure 2. (A) Outdoor and (B) indoor work: percentage of each work hour that heat stress exposure was exceeded by work inten-
sity, as determined by the WBGT-based TLV, for 10 residential construction sites in Al-Ahsa Province, SA, June–September 2016.
Table 2. HWA outdoors and indoors stratified by workload and time of day using WBGTdata.
Time interval 6–9 a.m. 9 a.m.–12p.m. 12–3p.m.a3–5p.m.
HWA (minutes) Mean ± SD [95% CI]
Setting Workload
Outdoors Moderate 37± 26 [33,40] 15± 21 [13,18] 27± 21 [24,29] 30± 20 [27,33]
Heavy 29± 25 [26,32] 9± 15 [7,11] 15± 16 [13,17] 18± 17 [15,20]
Indoors Moderate 50± 19 [47,52] 44± 22 [41,46] 43± 21 [40,45] 45± 21 [41,48]
Heavy 42± 21 [39,45] 32± 22 [30,35] 30± 20 [27,32] 33± 21 [30,37]
aMandatory afternoon outdoor work ban (12–3p.m.).
512 Annals of Work Exposures and Health, 2019, Vol. 63, No. 5

of geographical location on climatic conditions. The
workers monitored in this study were all of Indian na-
tionality; Indian nationals constitute the majority of the
workforce in SA. Accordingly, these workers could be
considered representative of the construction workforce
in the country.
The WBGT values in the outdoor construction work
environment exceeded the ACGIH TLV by high percent-
ages (>75%), indicating a high level of heat stress for
both moderate and heavy workloads starting at 7 a.m.
and continuing throughout the day and following a dis-
tinct daily trend, with the highest exceedances attained
during the period before noon. Two earlier summer heat
assessment studies conducted outdoors on the western
coast of SA reported elevated WBGT values in the range
of our ndings in the ground service operations area of
King Abdul-Aziz International Airport in Jeddah City
(Noweir and Bafail, 2008) and at different locations in
Makkah City, where pilgrims perform Islamic rituals
during the Hajj season (Noweir etal., 2008). At the
global level, our findings are consistent with the level
of summer heat exposure (hourly mean WBGT values)
reported at outdoor construction sites in other studies
in tropical and subtropical countries (Kähkönen etal.,
1992; Inaba and Mirbod, 2007; Miller and Bates, 2007;
Maiti, 2008; Pérez-Alonso etal., 2011; Rowlinson and
Jia, 2014; Venugopal etal., 2016).
The unexpected peak in WBGT values in the early
morning hours identified in our study resembled the
early peak occurring well before noon in a study of
heat stress exposure among sugarcane harvesters in
Guanacaste, a coastal province in Costa Rica (Crowe
Figure 3. Outdoor work: number of work minutes permitted in each hour of the work day (HWA), a comparison of estimates
using the WBGT-based TLV, the HI, and the HD adjusted for radiant heat (ΔTg-db) for (A) moderate and (B) heavy construction work
activities for 10 residential construction sites in Al-Ahsa Province, SA, June–September 2016.
Annals of Work Exposures and Health, 2019, Vol. 63, No. 5 513

etal., 2013). In our study, the early peak was inuenced
by the high values of two heat exposure parameters, Tg
and Tnwb, which account for 90% of the total outdoor
WBGT, and reect the high radiant heat and humidity
in the early morning (Supplementary Fig. S3, available
at Annals of Occupational Hygiene online). Long-term
monitoring and analysis of solar radiation trends in SA
have indicated that the solar radiation intensity increases
with sunrise, reaching its maximum at 12p.m., then de-
creases as the elevation of the sun decreases (Al-Dhari
etal., 2000). Higher RH in the morning than in the
afternoon is a result of the lower air temperature during
the morning, which in turn decreases the ability of the
air to hold water compared to later in the day (Davis
etal., 2016). This phenomenon in the study area is in-
uenced in part by the land and sea breezes, a thermally
driven circulation system that develops in coastal areas
and is a common characteristic of the regional climate in
the Arabian Gulf (Eager etal., 2008).
Although the indoor environmentwas sheltered from
direct sun exposure, this study found that workers with
moderate and heavy workloads were at risk of heat
stress; the WBGT values exceeded the TLV for moderate
and heavy workloads 38 and 66% of the time, respect-
ively. Similar levels of risk were observed for indoor con-
struction workers in India and Japan (Chinnadurai and
Venugopal, 2016; Ueno etal., 2018). Apossible explan-
ation for the high indoor WBGT values in this study is
Figure 4. Indoor work: number of work minutes permitted in each hour of the work day (HWA), a comparison of estimates using
the WBGT-based TLV, the HI, and the HD for (A) moderate and (B) heavy construction work activities for 10 residential construction
sites in Al-Ahsa Province, SA, June–September 2016.
514 Annals of Work Exposures and Health, 2019, Vol. 63, No. 5

that the houses were built from cement blocks, which
makes them good conductors of thermal energy, with
little ability to maintain cooler indoor temperatures in
the absence of mechanical ventilation at this stage of
construction. The lack of ventilation is clearly reected
in the difference in RH indoors versus outdoors. The
relatively high indoor humidity was partially caused by
the indoor construction activities that used water, such
as cement mixing. The high RH inuences the value of
Tnwb, which represents 70% of the WBGT calculation.
Most of the construction activities observed were
judged to require moderate or high workloads according
to the reference table in the ACGIH guidelines (ACGIH,
2009). This is consistent with what has been perceived
and described by construction workers (Chan and Yang,
2016; Venugopal etal., 2016) and conrmed by observa-
tion and measurement (Abdelhamid and Everett, 2002;
Maiti, 2008; Rowlinson and Jia, 2014; Chinnadurai
and Venugopal, 2016; Meade etal., 2016; Roja etal.,
2016). Workers were determined to work far beyond
the time allowed by the ACGIH TLV throughout their
work shift, particularly outdoors and when performing
heavy work activities indoors. The effectiveness of the
midday work ban was demonstrated to limit the cumu-
lative exposure risk over the course of the summer, but
it does not prevent daily excessive heat stress exposure
according to international guidelines. Working in condi-
tions of such long TLV exceedance increases the risk of
heat strain, which can lead to acute health effects such
as dehydration, heat cramps, heat exhaustion, and heat-
stroke (Larrañaga and Bernard, 2011). Cases of these
acute health effects are well-documented among workers
in construction jobs (Inaba and Mirbod, 2007; Miller
and Bates, 2007; Horie, 2013; Montazer etal., 2013;
Dutta etal., 2015; Gubernot etal., 2015; Jia etal.,
2016; El-Shafei etal., 2018). Additionally, heat stress
exposure has been identied as a contributor to chronic
health problems, such as psychological distress (Smith
etal., 1997; Tawatsupa etal., 2010) and cardiovascular
(Vangelova etal., 2006) and kidney diseases (Tawatsupa
etal., 2012; Luo etal., 2014).
The short- and long-term health impacts of con-
tinuous work during all or part of a 12-h workday (5
a.m.–5p.m.) were not investigated in this study. Apartial
explanation for the capability of these workers to sus-
tain their work activities in the extreme heat is that they
are heat-acclimated, having been employed in the Saudi
construction sector for years. Many were from regions
in India, such as Gujarat, Tamil Nadu, and Maharastra,
where mean WBGT values ranging from 28.7 to 34.1°C
have been reported for outdoor construction worksites
(Maiti, 2008; Dutta etal., 2015; Venugopal etal., 2016).
To some degree, those still working under the studied
conditions may be survivors who practice self-pacing to
withstand extreme heat and sustain their work activities.
The practice of self-pacing by workers through the re-
duction of their metabolic rate to a safe level has been
identied as a protective response to heat stress exposure
in construction and other work settings (Mairiaux and
Malchaire, 1985; Miller etal., 2011; Nag etal., 2013;
Peiffer and Abbiss, 2013; Methner and Eisenberg, 2018).
Not accounting for self-pacing could have resulted in
an overestimation of the risk. The variability in work-
load intensity within and between construction work
activities and the differences in physiological character-
istics among workers are other inuential factors of heat
stress that have not been accounted for in this study.
Without monitoring of workers’ physiological response
and actual metabolic rate, it is impossible to account for
these factors and their impact on workers (Havenith and
van Middendorp, 1990; Havenith etal., 1998; Havenith
etal., 2002).
The WBGT-based TLV has high sensitivity for
detecting unsustainable exposure (an inability to main-
tain thermal equilibrium) but relatively low specicity
(Garzón-Villalba etal., 2017). The TLV has been iden-
tied as being overly protective in actual work settings
because this measure was developed based on labora-
tory studies without considering personal factors that
might require higher protection (e.g. age, gender, health
status, obesity, smoking, alcohol consumption habits,
and other unmeasured physiological differences), which
affect workers’ ability to tolerate heat strain (Chan
etal., 2012; Jia etal., 2016; Lamarche etal., 2017).
From this perspective, the use of the WBGT-based TLV
could have contributed to the overestimation of risk in
this study. To evaluate this possibility as well as to ex-
plore a convenient, reliable index to manage heat stress
risk in construction work, we performed a comparative
assessment of the HWA estimated by the WBGT with
HWA estimations based on the HI and HD adjusted for
radiant heat. This comparison showed that all indices
classied the levels of heat exposure corresponding to
the summer months as high risk and performing con-
tinuous moderate and heavy construction work activities
is not advised outdoors. The outdoor mean HWA values
based on the WBGT were more constrained than those
based on the HI and HD for moderate and heavy work-
loads during the early and late morning periods, while
in the subsequent hours, the WBGT became the least re-
strictive of the three indices for heavy workloads, and
the HD was the least restrictive for moderate workloads.
Indoors, where the environmental conditions were more
uniform and radiant heat was minimized, the differences
Annals of Work Exposures and Health, 2019, Vol. 63, No. 5 515

in the mean values of the HWA among all indices were
reduced signicantly for heavy workloads and for mod-
erate workloads, with the exception of the HD, which
had relatively large differences compared to theWBGT.
Our ndings demonstrate a high degree of consist-
ency (κw ≥ 0.85) between WBGT and the HI in the es-
timate of the HWA as an indicator of heat exposure
risk. The weaker correlation between WBGT and HD
aligns with results of a previous study, where HD was
found to be less reliable than WBGT in the assessment
of heat stress exposure risk with a moderate workload
under simulated hot working conditions (D’ambrosio
Alfano etal., 2011). We conclude that the HI is reason-
ably reliable and potentially a practical surrogate for the
WBGT index in the climate studied. As demonstrated
in this study, the effect of radiant heat has a large in-
uence on the outdoor heat stress exposure level during
the day, which makes the adjustment of the HI highly
recommended for use in guiding heat stress management
programs in Saudi work environments.
Conclusions
The intensity and duration of heat stress exposure
among workers in this study were very high throughout
the majority of the workday, both indoors and outdoors.
These results warrant immediate action, particularly in
view of the limited effectiveness of the midday outdoor
work ban in preventing heat stress risk and the notice-
able absence of other heat stress-preventive measures.
The HI, which for most Saudi employers is easier to
measure than the WBGT, can be used to identify heat
stress exposure risk in construction settings similar to
those in thisstudy.
For future research, it would be valuable to expand
this study to other regions of SA. Increasing the moni-
toring period to include all months of the year and
24h per day will provide an in-depth analysis of occu-
pational heat stress exposure across all work periods.
Additionally, it is important to assess the physiologic
responses of workers to the measured heat exposures
in order to determine their actual heat stress and to im-
prove their capability to withstand extreme heat and
sustain work productivity. The short- and long-term
health impacts of prolonged heat exposure should be
assessed, particularly chronic health problems, which
could be a hidden threat to these workers’ health and
safety. The results obtained from this and future studies
can contribute to the development of a threshold based
on the WBGT or the HI to guide the management of in-
door and outdoor heat stress risk in SA, thus supporting
the goal of the National Transformation Program 2020
(Saudi Vision 2030, 2016). However, until such ef-
forts are achieved, the present regulatory midday work
ban is a minimum necessity. Shifting it earlier in the
day should be considered. Additionally, implementa-
tion of other administrative and engineering controls
is recommended to reduce heat stress exposure risk in
occupational settings, including pre-work heat acclima-
tization, work organization that promotes worker self-
pacing, the provision of cool potable water and toilet
facilities, anti-heat stress clothing, portable fans, and
onsite shaded resting areas with scheduled rest periods
(National Institute for Occupational Safety and Health
(NIOSH), 2016).
SupplementaryData
Supplementary data are available at Annals of Work
Exposures and Health online.
Acknowledgements
The authors thank Laurie A.Blanchard, biomedical
engineer, for advice related to the development of the
environmental monitoring strategy and selection of in-
strumentation. We are grateful to Ali Al-Bouwarthan,
agricultural engineer (retired), for assistance with
the collection of the environmental monitoring data.
Particular gratitude is extended to the companies and
the workers for their participation in this study.
Funding
This study was funded in part by a scholarship for graduate
studies in occupational and environmental hygiene awarded by
the Saudi Ministry of Education and Imam Abdulrahman Bin
Faisal University to M.A.
Conflict of interest
The provision of nancial support does not in any way infer or
imply endorsement of the research ndings by either agency. The
authors declare no conict of interest relating to the material
presented in this article. Its contents, including any opinions
and/or conclusions expressed, are solely those of the authors.
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