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Exploring the structure and
emerging trends of construction
health management: a bibliometric
review and content analysis
Huakang Liang
School of Economics and Management, Beijing Jiaotong University,
Beijing, China, and
Xiaoxiao Shi
School of Economics and Management, Beihang University, Beijing, China
Abstract
Purpose –The demanding nature of construction industry poses serious health risks to construction workers.
In recent years, construction health management (CHM) has gained much attention to ensure a healthier and
safer workplace. However, there is still lack of a systematic review to bring together the disaggregated studies
and determine the development status of this research field. As essential for addressing health issues in
construction industry, a bibliometric and content-based review on of previous CHM studies would be presented
in this paper.
Design/methodology/approach –In total, 753 journal articles published in Web of Science core collection
from 1990 to 2020 were examined using a systematic review. Bibliometric analysis concentrated on the analysis
of publication and citation pattern of CHM research while content analysis was employed to identify main
health hazards, levels of analysis and topical focuses.
Findings –The results indicated that the USA was the leading country in this research domain. Five health
hazards together with 17 research topics at different levels of analysis were classified to allow researchers to
track the structure and temporal evolution of the research field. Finally, three emerging trends and a set of
research agenda were proposed to guide future research directions.
Originality/value –It is the first to highlight the issues of occupational health management from the
perspective of construction workers. It contributes to the field of construction health management by clarifying
the knowledge structure, emerging trends and future research directions. It offers valuable guidance and
in-depth understanding to researchers, practitioners and policymakers to further promote construction
workers’health performance.
Keywords Occupational health management, Bibliometric analysis, Content analysis, Construction workers,
Emerging trends
Paper type Literature review
1. Introduction
The health risks such as cancers, respiratory diseases, musculoskeletal disorders (MSDs) and
noise-induced hearing loss (NIHL) are disproportionately high across the construction sectors
of many countries in worldwide (Dabirian et al., 2020;Dong et al., 2020;Jonsson et al., 2019).
For instance, previous epidemiological investigation revealed that, globally, about 77% of
construction workers suffer from the symptoms of MSDs (Dong et al., 2020). The poor health
records have caused sizable economic costs for workers, employers, insurers and society as
whole, attributing to the sickness absenteeism, healthcare costs, loss of productivity and
increased possibility of construction accidents (Peters et al., 2018;Chung et al., 2018).
Especially considering the depleting aging construction workforce, it is urgently required to
prevent deterioration of construction workers’health status, serving as one way to improve
workers’wellbeing and project’s performance (Chung et al., 2018;Eaves et al., 2016).
Recently, occupational health management has begun to receive widespread attention
from both academicians and practitioners in the construction industry (Chan et al., 2016).
Structure and
emerging
trends of CHM
Received 26 January 2021
Revised 13 March 2021
23 March 2021
1 April 2021
Accepted 3 April 2021
Engineering, Construction and
Architectural Management
© Emerald Publishing Limited
0969-9988
DOI 10.1108/ECAM-01-2021-0080
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0969-9988.htm
Various health interventions have been implemented in construction industry, such as Total
Work HealthR in United States (Peters et al., 2018;Lee et al., 2017) and “Pilot Medical
Examination Scheme for Construction Workers”in Hong Kong (Yi and Chan, 2016), which
are critical for mitigating and reducing the health hazards. According to the International
Labour Organization (ILO) and World Health Organization (WHO), occupational health
management aims at prevention of disease and maintenance of workers’physical, mental and
social well-being (WHO, 1994). Construction health management (CHM) represents multiple
activities for preventing workers from adverse health effects including identifying health
hazards, performing health training and education, and promoting health performance,
motivation and behaviors (Lee et al., 2017)
In past decades, numerous studies on CHM have been published, forming a foundation for
promoting health performance in the construction industry. Thus, a comprehensive literature
review is indispensable for assisting major stakeholders in construction industry to gain an
in-depth understanding of the status of scientific developments in CHM research domain.
Although there have been some review studies on CHM research in the past (e.g. Chan et al.,
2020;Acharya et al., 2018;Roche et al., 2015), the overall analysis of CHM research is relatively
scant and previous reviews tended to have narrow research focus, sample and type of
analysis. For instance, ergonomic assessment reviews were primarily concerned with
available techniques and their limitations for assessing risk factors of musculoskeletal
disorders (MSDs) suffered by construction workers (Valero et al., 2016). Psychological health
studies concentrated on the state and risk factors of mental ill-health among workers (Chan
et al., 2020). Other health problems were also reviewed such as heat stress (Acharya et al.,
2018) and alcohol use (Roche et al., 2015). Although Jaafar et al. (2018) conducted a
comprehensive review on occupational health and safety management in construction
industry, they merely concentrated on the casual factors of limited health issues.
Furthermore, the majority of previous review studies are of a narrative type, which, in
contrast to systematic reviews, are difficult to gain a principled, transparent and reproducible
assessment of CHM research area (Abedinnia et al., 2017). To fill these gaps, a systematic
review based on bibliometric and content analyses was conducted in this research: (1)
bibliometric analysis (i.e., co-occurrence and frequency analysis) was carried out to identify
the most cited journals, the most productive countries and institutions, and hot topics in CHM
research; (2) content analysis (i.e., research subjects, levels of analysis and topics) was
eventually conducted to identify the knowledge structure of CHM and to guide potential
research directions in the future. Therefore, the current research goes even further than other
reviews as it provides a holistic and visualized analysis of various parameters, such as
country, publication sources and research topics. This research could assist researchers and
practitioners, especially new researchers in the field, to obtain an overview of CHM research
and potential research frontiers. The remainder of the paper is organized as follows. The
review process starts with the research methodology, followed by a detailed systematic
analysis. Finally, a qualitative discussion is provided to identify emerging trends in CHM,
along with the research gaps and potential future directions.
2. Methodology and data source
2.1 Methodology
This research used a systematic review that integrates the bibliometric and content analyses
to search and classify the intellectual knowledge of CHM research. The systematic review
could take advantages of two complementary approaches: bibiometric and content analyses.
The bibliometric analysis method is essential, especially for new researchers, to obtain a
broad picture of a research domain by exploring trends related to keywords, journals,
countries and institutes, while the content analysis could obtain more in-depth information
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about the subjects, research levels and topical focuses of related studies. Currently, the
systematic review has become a common approach in assessing the scientific status of
various disciplines, like supply chain management (Kazemi et al., 2019), construction safety
management (Liang et al., 2020), building information modelling (BIM) (Oraee et al., 2017).
Similar to previous studies, the review process follows a four-step methodology suggested by
Mayring (2010), namely (1) material collection, (2) bibliometric analysis, (3) content analysis
and (4) material discussion. The research process was presented in Figure 1. The database
and retrieval strategy were determined first to prepare a reliable and representative data
source. Irrelevant documents were then excluded through a series of screening criteria.
Bibliometric analyses were carried out to assess the publication and citation characteristics of
CHM research. Next, content analysis was provided to summarize main research themes.
Finally, potential research trends and gaps were discussed, and potential research directions
were recommended to guide future research.
(1) Bibliometric analysis
Bibliometric analysis, firstly introduced by Pritchard (1969), is an effective method to
quantitatively assess scientific activities in a research domain using statistical and
mathematical techniques. Bibliometric analysis combines two main procedures:
performance analysis and science mapping. The former assesses the performance and
Figure 1.
Main research process
for systematic review
on CHM studies
Structure and
emerging
trends of CHM
impact of scientific productions based on various indicators like frequency, citation and
network centrality, while the latter visualizes the general knowledge structure of one research
field (Liang et al., 2020). In this research, both bibliometric procedures were conducted to gain
insights into publication and citation patterns, and main research topics in CHM field.
VOSViewer version 1.6.3, Gephi version 0.9.2, and CiteSpace version 5.7.R2, three
powerful bibliometric analysis software tools, were applied to perform the co-citation and
co-occurrence analyses to visualize and explore the emerging trends in the CHM research
domain (Van Eck and Waltman, 2009;Bastian et al., 2009). VOSViewer and Gephi could create
distance-based maps of networks where distances among nodes indicate the level of
similarity among them (Van Eck and Waltman, 2009). The burst detection was performed by
CiteSpace to examine the temporal evolution of hot topics over the whole investigative period.
Some basic statistical analyses of citations and publications in terms of counties, institutes
and journals were supported by HistCite version 2.0. Multiple indicators were used to assess
the development of the knowledge domain. The h-index, introduced by Hirsch (2005), means
that a subject, which can be one author, country, institute or journal, has published at least h
papers that have more than hcitations. In this research, the h-index was used to represent the
impact of a subject’s cumulative publications on CHM research. Weighted degree is a
frequently used indicator reflecting the centrality of each node in the network, which is equal
to the sum of edge weights associated with a given node (Feng et al., 2016). The higher the
weighed degree, the more influential one node is in the CHM field.
(2) Content analysis
Although bibliometric analysis could analyze a large set of data and provide the general
publication trend of a specific domain, it does not give detailed information regarding the
content of studies of interest (Esen et al., 2020). Therefore, the content analysis was further
performed to acquire an in-depth understanding of the CHM research and explore the
temporal evolutions of research topics (Abedinnia et al., 2017). The content analysis
concentrated on the publication distribution of health hazards investigated, research levels
and topical focuses of each CHM article. Both conventional and directed content analysis
suggested by Hsieh and Shannon (2005) were implemented, where the coding categories of
health hazards and research levels were mainly from previous studies, while topical focuses
were codded directly from the text data. Each author would perform all the selection and
coding procedures independently to increase the validity and reliability of these assessment
(Aliyev et al., 2019).
2.2 Data source
Occupational health is a broad concept involving workers’physical, psychological and
behavioral aspects (Jones et al., 2019). Specifically, physical health is concerned with the
biological and physiological issues such as low back pain, cardiovascular and respiratory
diseases; mental health involves some poor psychological symptoms such as anxiety, tension,
depression and burnout; behavioral health focuses on health-risk behaviors and lifestyles
such as smoking, alcohol-drinking and substance abuse (Leung et al., 2012,2016b;Shirom,
2003). More importantly, this review concentrated on the health issues of frontline
construction workers rather than the project managers because the former seems to be much
more vulnerable to health harms than the latter (Nwaogu et al., 2020). Based on the systematic
analysis of the potential terms, a three-level keyword structure is adopted to cover diverse
and large-scale search terms for comprehensively and reliably obtaining CHM articles
(shown as Table 1). The context keywords define the search context which is limited to
construction industry; the subject keywords limit the search subject to construction workers;
topical keywords further narrow the search scope. In addition, the research timespan was set
1990–2020 and the article language was limited to English.
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This research selected the Thomson Reuters’s Web of Science (WoS) core collection database
because it offers a useful source for standardized and high-quality academic publications.
Moreover, the data format of the WoS core collection database could meet the requirement of
various bibliometric techniques. Especially, the CiteSpace only supports the WoS database.
This research conducted the online retrieval and obtained 2,294 bibliographic data records. In
terms of the initial screening, 62 proceedings papers, 20 early access and 1 retracted
publication were removed from the dataset. Next, a total of 2,211 candidate articles were
subjected to the following manual screening process. The information provided in titles,
abstracts and even the full text (if necessary) of these articles were reviewed to remove the
articles which were not really related to the topic of construction health management. After a
careful screening process, a total of 753 CHM-related articles were identified for the following
literature review.
The distribution of annual publications from 1990 to 2020 is shown in Figure 2. Interests in
construction health management increased slowly before 2002, then had an incredible
Search levels Retrieval strategies
Context
keywords
TS5(“construction industr*”OR “construction work*”OR “construction compan*”OR
“construction organization*”OR “construction project*”OR “building project*”OR
“construction site*”OR “construction management”OR “construction activit*”OR
“construction task*”)
Subject
keywords
TS5(worker* OR employee* OR labo* OR carpenter* OR apprentice*)
Topical
keywords
TS5(health OR disease* OR illness* OR pain OR wellbeing OR “musculoskeletal
disorder*”OR burnout OR anxiety OR depression OR distress OR exhaustion OR fatigue
or stress* OR satisfaction OR obesity OR drink* OR smok*)
Note(s):“*”denotes the fuzzy search strategy that is used to capture the variation in terms. “TS”represents
the topic research strategy where an article is included when required terms are identified in any positions of
the title, abstract and keywords
Table 1.
The used three-level
keyword structure
Figure 2.
CHM publications in
the WoS Core
Collection
Structure and
emerging
trends of CHM
development where about 83% of the literature was published between 2003 and 2020. The
increased number of publications indicated that CHM research had attracted extensive
attentions and become a critical domain in construction management. The total 753 articles,
had received a total of 12,658 citations, an average of 16.81 citation per paper. Average
citations of papers reached the peak in 1992 with a record of 70.29 and then dropped arguably
due to the time required for the accumulated effects of new publications (shown as Figure 2).
3. Bibliometric analysis
3.1 Countries/institutions cooperation analysis
A total of 58 countries/territories were found to contribute papers related to CHM, while
67.24% of these countries/territories contributed more than one paper. The span of
geographical area, to some extent, indicates that construction workers’health issues are
global concerns. Gephi software was used to visualize the cooperation relationship among
these countries/territories. The threshold was set at 5, which means that only countries/
territories that published more than 5 articles are included in the resultant networks. The
cooperation network was shown in Figure 3. Weighted degree is a comprehensive measure
for evaluating the level of influence of nodes in the control of information flow across the
whole network (Prell, 2012). The weighted degree values were used to resize and recolor the
nodes in the network in Figure 3, where darker and larger nodes represent higher weighted
degree values. In the cooperation network, thicker edges denotes closer cooperative
relationship between two countries or research institutions.
Table 2 lists the top 10 most productive countries, together with their weighted degree,
citation and h-index. Computing the Pearson product moment correlation coefficient (r) shows
that the counts of publication have strong positive correlations with other indicators. Thus,
productive countries tend to have higher performance in citation, weighted value and h-index.
For instance, the USA leads this research field with 270 articles, and also has the highest
Figure 3.
Country territories
cooperation network in
CHM research
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scores in terms of citation (4,617), weighted degree (74.0) and h-index (34), indicating the
domination position of the USA in CHM research area. Indicated by darker and thicker edges
between them in Figure 3, the USA and Sweden are also two influential countries in CHM
which have frequent international cooperation. In practice, China is the only one developing
country among the leading contributors. With repaid economic development and huge
infrastructure construction in past decades, Chinese government and society have attached
great importance to the occupational health of massive labors onsite to obtain a sustainable
workforce (Chen et al., 2018).
A total of 791 institutions contributed to the CHM research, and 80 institutions of them
published more than 5 articles. The cooperation network among top 21 institutions with
citation was shown as Figure 4.Table 3 gives the top 10 most productive institutes, together
Country (Pearson
correlation)
Publication
()
Citation
(0.882
**
)
Weighted degree
(0.840
**
)h-index (0.788
**
)
USA 270 4,617 74.0 34
China 100 770 53.0 16
Netherlands 82 1926 39.0 25
Sweden 81 3089 67.0 31
Australia 40 237 30.0 10
Germany 37 759 28.0 16
England 40 324 31.0 11
Canada 34 445 26.0 11
South Korea 23 107 18.0 6
Norway 22 447 21.0 11
Note(s): Pearson correlation only gives the correlation between publication counts and other four indicators,
respectively; **represents the correlation is significant under the level of 0.01; n.s. represents the correlation is
not significant. Publication, citation and h-index were determined using HistCite version 2.0, and weighted
degree was determined using Gephi version 0.9.2
Table 2.
Top 10 productive
countries in CHM
research
Figure 4.
Institution cooperative
network in CHM
research
Structure and
emerging
trends of CHM
with the scores of citation, weighted degree, and h-index. The ranking of the institutions
differs significantly according different indicators, where the correlation between publication
and other indicators are not significant. For the publication counts, Hong Kong Polytechnic
University ranks the first with publication of 50. However, it has relatively low values of
citation (371) and h-index (13). This is primarily due to that Hong Kong Polytechnic
University is a recently emergent contributor in CHM research, and published most of CHM
articles around 2016, which makes it difficult to have strong accumulative citations. Based on
the citation, most influential institutions are Karolinska Institute (1225) and Harvard
University (1133), while based on the weighted degree, most influential institution is
University of Amsterdam (20), which is reflected by the dark color in Figure 4. Regarding the
cooperation relationships, two research groups could be identified based on the darkness of
connections between nodes: one group primarily consists of University of Amsterdam
(Netherlands) and Arbouw (Netherlands); anther one involves Umea University (Sweden),
Karolinska Institute (Sweden) and International Agency for Research on Cancer (France).
Above statistical analysis could provide valuable information for researchers who have
interests in the field of CHM to choose the potential collaborators.
3.2 Journal co-citation analysis
The selected 753 articles were published in 225 different journals, while most of these journals
(63.11%) published only one paper. The journal co-citation directed network was visualized
by the Gephi (shown as Figure 5). Only top 30 journals with the most citations are included in
the resultant network. Table 4 lists top 10 productive journals together with values of citation,
weighted degree, h-index and Impact Factor (IF). Based on the Pearson correlation analysis, it
shown that publication counts have strong positive correlations with citation, and h-index,
suggesting that each of these indicators could be effective to assess the importance and
contribution of these journals (Wuni et al., 2019). American Journal of Industrial Medicine is
the leading journal in CHM research in terms of the scores of publication (68), citation (1222),
weighted degree (155,523.0) and h-index (21). As indicated in Figure 5, this journal has amount
of information outflow (through citation relationships) to Occupational and Environmental
Medicine, Scandinavian Journal of Work Environment & Health and Journal of Occupational
and Environmental Medicine. The Pearson correlation coefficient (r) between IF and
publication (r50.002, p50.995) is not significant. This could be explained that IF reflects the
Institutions (Pearson correlation)
Publication
()
Citation
(n.s.)
Weighted
degree(n.s.)
h-index
(n.s.)
Hong Kong Polytechnic University, China 50 371 6.0 13
Harvard University, USA 33 1133 13.0 16
Umea University, Sweden 36 863 13.0 18
University of Amsterdam, Netherlands 29 563 20.0 19
Karolinska Institute, Sweden 24 1225 17.0 19
University of Michigan, USA 24 335 6.0 10
University of Washington, USA 21 539 4.0 14
Duke University, USA 19 360 3.0 9
National Institute of Occupational Health,
Norway
19 360 11
National Institute for Occupational Safety
and Health (NIOSH), USA
19 385 5.0 9
Note(s): Pearson correlation only gives the correlation between publication counts and other four indicators,
respectively; n.s. represents the correlation is not significant. Publication, citation and h-index were calculated
using HistCite version 2.0, and weighted degree was determined using Gephi version 0.9.2
Table 3.
Top 10 productive
institutions in CHM
research
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comprehensive influence of one journal in multiple domains, which could not be always
consistent with its influence in the domain of CHM. For instance, Automation in Construction
ranks first in terms of IF scores (4.313) which is influential in general application of
automation and robotics in construction industry but it has relatively low scores in other
indicators like publication, citation and weighted degree in CHM research. In practice,
Automation in Construction is recently emergent in CHM research area with average
publication year of 2017, indicating that it had increasing interests in the occupational health
issues and has published more CHM-related articles recently. Other emergent journals
include Journal of Cleaner Production (2017) and Journal of Computing in Civil Engineering
(2016). Knowledge of these above measures of impact could guide researchers on the choice of
suitable journals to submit research articles. Engineering, Construction and Architectural
Management has paid increasing attention on CHM-related issues recently, primarily about
the intervention of infectious virus and the effectiveness of health programs (Loudoun and
Townsend, 2017;Edwards and Bowen, 2019).
3.3 Keyword co-occurrence analysis
Topics were detected using keyword co-occurrence analysis provided by VOSViewer, which
was shown as Figure 6.Table 5 lists top 20 most frequently studied keywords together with
their scores of weighted degree. A correlation analysis shows that there is a strong positive
correlation between occurrence and weighted degree (r50.929, p50.000). Ergonomics
(occurrences 538, weighted degree 567.0), musculoskeletal disorders (38, 67.0) and posture
(27, 37.0) are the most influential keywords indicating the dominant position of topics related
to workers’musculoskeletal disorders in CHM research. From the topics identified from
keyword analysis, it could find that most CHM research were conducted specifically for
Figure 5.
Journal co-citation
network in CHM
research
Structure and
emerging
trends of CHM
eliminating various health hazards in terms of physical, chemical, behavioral, psychological
and biological aspects. Three clusters were generated according the proximity of various
topics.
Journals (Pearson correlation )
Publication
(–)
Citation
(0.7816
*
)
Weighted
degree (0.652
*
)
h-index
(0.648
*
)
IF
(n.s.)
American Journal of Industrial
Medicine
68 1222 15523.0 21 1.902
Journal of Construction Engineering
and Management
42 306 4596.0 11 2.734
Occupational and Environmental
Medicine
41 1230 11608.0 21 3.556
Applied Ergonomics 31 565 10499.0 16 2.61
Journal of Occupational and
Environmental Medicine
30 296 9152.0 12 1.591
International Journal of
Environmental Research and Public
Health
30 98 –5 2.468
Scandinavian Journal of Work
Environment & Health
28 829 12025.0 18 3.491
Automation in Construction 26 215 4717.0 10 4.313
Work-A Journal of Prevention
Assessment & Rehabilitation
20 44 –4 1.009
International Archives of
Occupational and Environmental
Health
19 275 3968.0 10 2.025
Note(s): Pearson correlation only gives the correlation between publication counts and other four indicators,
respectively; *represents the correlation is significant under the level of 0.05; n.s. represents the correlation is
not significant. Publication, citation and h-index were calculated using HistCite version 2.0, weighted degree
was determined using Gephi version 0.9.2, and IF was determined by the WoS
Table 4.
Top 10 influential
journals for CHM
research
Figure 6.
The keyword co-
occurrence analysis
within CHM research
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Cluster Keywords Occurrences Weighted degree Cluster Keywords Occurrences Weighted degree
1# Ergonomics 38 67.0 1# Noise 10 11.0
1# Musculoskeletal disorders 38 67.0 1# Injuries 9 15.0
1# Posture 27 37.0 1# Musculoskeletal pain 8 20.0
2# Epidemiology 20 42.0 2# Surveillance 8 20.0
1# Low back pain 20 27.0 1# Stressors 8 14.0
1# Heat stress 17 13.0 1# Machine learning 8 12.0
3# Mental health 16 35.0 2# Risk factors 8 11.0
2# Mortality 15 28.0 1# Wearable devices 8 9.0
2# Smoking 14 17.0 3# Job satisfaction 8 5.0
2# Carpenters 11 20.0 3# Suicide 7 17.0
Note(s): Occurrences was determined using VOSViewer version 1.6.3, and weighted degree was determined using Gephi version 0.9.2
Table 5.
Top 20 influential
keywords under three
clusters
Structure and
emerging
trends of CHM
Cluster 1#, marked by green color, is primarily about the physical health. This cluster
involves topics related to ergonomic and environmental hazards that may cause harms to
workers, which is indicated by keywords “musculoskeletal disorders,”“low back pain”and
“noise.”Musculoskeletal disorders were one of the most serious physical health problems
among construction workers. For instance, low back is the most vulnerable body part for
MSDs, and more than 50% of the construction workers suffer from symptoms of low back
MSDs annually around the world (Umer et al., 2018). Other progress has been made in
understanding the causal factors of musculoskeletal injuries involving three aspects:
physical exposure (e.g., awkward postures, repetitive motions, forceful exertions),
psychological stressors (e.g., work-family conflict, time pressure and safety worries) and
individual factors (e.g., gender, age, poor physical/mental health conditions) (Ekpenyong and
Inyang, 2014;Wang et al., 2015;Inyang et al., 2012;Zhang et al., 2021;Zhang and Lin, 2020). In
addition, within this cluster, “wearable devices,”“machine learning”and “electromyography”
represent potential technologies to monitor health status of construction workers in a much
automatic and accurate manner.
Cluster 2#, marked by red color, which covers studies related to epidemiology
investigation. Multiple epidemiology studies have focused on assessing the characteristics
and health impacts of occupational exposure and unhealthy behaviors among construction
workers (Lewkowski et al., 2018;Li et al., 2016). As shown in Figure 6,“asbestos,”“diesel
exhaust,”“lead exposure”and “respirable dust”were frequently investigated chemical
hazards. Other hot keywords represents behavioral hazards like smoking, alcohol and
substance abuse, poor diet-related behaviors and physical inactivity, which have been found
prevalent among construction workers causing serious health problems (e.g. cardiovascular
and respiratory diseases, lung cancers, diabetes and obesity) (Flannery et al., 2019;Asfar et al.,
2018;Chin et al., 2012;Okechukwu et al., 2012). For instance, Loudoun and Markwell (2017)
found that soft drinks (e.g., caffeine) were consumed widely and regularly on site which could
influence the hydration and cause risk of heat stress.
Cluster 3#, marked by blue color, is primarily about psychological heath involving
keywords like “mental health,”“suicide”and “job satisfaction.”Mental health, such as
sadness, depression, and anxiety, represents another adverse health conditions, which has
been investigated in terms of their prevalence and adverse effects (Lim et al., 2017a). Previous
studies have found that about 20% of construction workers suffered from substantial mental
distress (Boschman et al., 2014;Jacobsen et al., 2013). Psychological health could influence
work motivation, job satisfaction and even cause suicide (Langdon and Sawang, 2018;Lee
et al., 2017;Leung et al., 2010). Recently, elevated suicide rates among construction workers
deriving from psychological problems have caught the attention of CHM researchers (Milner
et al., 2019).
4. Content analysis
4.1 Health hazards
The health causes were examined in detail through reviewing the content of each CHM
article. A total of 521 articles provided the specific health hazards which were summarized
in Figure 7. Based on the above keyword cluster analysis and previous health research,
various health hazards were identified among construction workers onsite, including
physical, chemical, behavioral, psychological and biological aspects (Sivakumar et al., 2012;
Epp and Waldner, 2012). Consistent with Aarhus et al. (2018), physical hazards have
received the most attention among previous CHM-related studies, accounting for 51.4% of
all papers. Among these studies on physical hazards, most concentrated on ergonomic risks
with a percentage of 71.6%, followed by heat strain (12.2%), noise (9.6%), and solar
ultraviolet-radiation (3.3%). Studies on chemical hazards occupy the second place
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accounting for 19.5%. Chemical hazards represent these harmful substances generated
during construction activities including solid particles, toxic gases and organic solvents. It
is found that lead (with a percentage of 14.8%), silica (14.8%), dust (13.0%) and asphalt
(11.3%) were four most frequently investigated chemical hazards. Behavioral hazards
ranking third (15.4%), refer to health-risk behaviors such as smoking, alcohol and
substance abuse, poor diet-related behaviors, etc., and smoking draws the most interest
with a percentage of 38.5%. Psychological hazards, ranking forth in CHM research (12.0%),
are those factors that can cause stress, strain, and other mental issues. Job stress (e.g., time
pressure, injustice and conflicts) and work environment (e.g. high altitude or elevation) are
two most investigated factors accounting for 32.4% and 12.7%, respectively. Finally,
biological hazards, representing infectious agents that can cause harm to human body,
have received the least attentions with percentage of only 1.7%, where scholars have paid
attention to HIV, Tetanus and especially the new coronavirus (COVID-19) among
construction workers.
Figure 8 gives the temporal evolution of health hazards investigated in CHM research. It
could be found that physical hazard is a long-lasting topic and shows an upward trend over
the whole investigative period. Psychological hazards began after 2000, and has a significant
increase recently. It could be primarily explained that occupational stress, mental health and
wellbeing have received more attention considering the intensification of job stress and aging
workforce as well as the increasing risks of suicide witnessed in the construction industry
(Milner et al., 2018;Langdon and Sawang, 2018). By contrast, there are few studies that
investigated the biological hazards in the construction industry over the whole investigative
period. Considering increased occurrence of infectious disease has been reported among
construction workforce, especially for the COVID-19 pandemic (Amoah and Simpeh, 2020),
more biological health research should be strengthened in the future.
Figure 7.
The distribution of
hazards categories and
associated typical
diseases
Structure and
emerging
trends of CHM
4.2 Levels of analysis
Based on the general categories of research levels in construction industry (Zhou et al., 2015;
Goel et al., 2019), four research levels were defined in this research, including population,
industry, organization and task levels. Population level studies primarily concentrated on the
demographic characteristics of occupational illnesses or hazards among construction
workers. Industry level represented the studies on various agents’health practices in the
construction industry, like government, insurance companies and health service centers. By
contrast, organization level studies investigated the implementation of health interventions
within construction companies or projects. Studies at the task level further limited the scope
into the health risks of some specific construction tasks. The distribution of publications
according to the five levels was shown in Figure 9. Population level accounted for almost half
of all the studies (42.1%), followed by organization level (33.8%) and task level (20.7%). It was
noted that only 3.3% of the papers were focused on industry level. The studies at population
level primarily investigated the prevalence and severity of health problems among specific
1990 1995 2000 2005 2010 2015 2020
Publication year
Article counts
0
5
10
15
20
25
30
35
40 Physical hazards
Chemical hazards
Behavioral hazards
Psychological hazards
Biological hazards
20.72%
42.14%
3.3%
33.83%
Population Level
Industry Level
Organization Level
Task Level
Figure 8.
The temporal evolution
of health hazards
investigated in CHM
research
Figure 9.
The distribution of
research levels within
CHM research
ECAM
groups of construction workers, such as migrant construction workers (Susseret et al., 2019),
older construction workers (Dement et al., 2018), and elementary workers (Hamid et al., 2019).
The studies at organization level included investigation into projects of different types, such
as residential project (Nussbaum et al., 2009), prefabricated project (Kim et al., 2011), railway
project (Yang et al., 2015), electrical transmission and distribution project (Techera et al.,
2019), as well as some small construction companies (Dale et al., 2016). The tasks investigated
in task level studies were demolition (Bello et al., 2019), rebar tying (Umer et al., 2017b),
asphalt pavement (Hammond et al., 2016) and wall plastering (Rahman et al., 2012).
4.3 Topical focuses
The topics in CHM research at different levels were further investigated to summarize the
distribution and temporal trends of CHM research. 753 studies at population, industry,
organization and task levels were considered to summarize the multilevel health
interventions, which was shown in Table 6. Among two topics at the population level,
“health data statistics (T1)”is the largest, accounting for 22.3% of the total papers, which
conducted statistics of health records to identify prevalence and trends of health hazards or
diseases among construction workers. For instance, Dong et al. (2019) explored heat-deaths
among the American construction workers from 1992 to 2016 and found that heat risk has
increased with climate change over time. For the industry level, “health practice (T3)”is the
most frequently studied topic (1.7%), which aims at exploring the status of health practices in
construction industry. For instance, Jones et al. (2019) investigated current approaches to
managing occupational health in the construction industry and their limitations such as
lower priority than safety, lack of ownership and poor health service provision. For the
organization level, studies on “health program (T8)”are the most cited, accounting for 12.2%
of the total, which focused on assessing the effectiveness of health programs, such as
participatory ergonomics (Visser et al., 2019), nutrition training (Chung et al., 2019) and
smoking cessation services (Asfar et al., 2019).
Two health intervention perspectives were identified, namely behavior-driven health
intervention and technology-driven health intervention. Behavior-driven health intervention
focuses on preventing ill-health behaviors, which includes three main topics, namely “health
behavior (T12)”(1.7%), “health knowledge (T14)”(0.3%) and “health leadership (T15)”
Levels of analysis Topical focuses Count (percentage)
Population level (PHM) Health data statistics (T1) 168 (22.3%)
Health investigation (T2) 146 (19.4%)
Industry level (IHM) Health practice (T3) 13 (1.7%)
Health regulation (T4) 6 (0.8%)
Health insurance (T5) 4 (0.5%)
Adoption of health innovation (T6) 1 (0.1%)
Health vaccines (T7) 1 (0.1%)
Organization level (OHM) Health program (T8) 92 (12.2%)
Health performance (T9) 76 (10.1%)
Health monitoring (T10) 45 (6.0%)
Health planning (T11) 13 (1.7%)
Health behaviors (T12) 13(1.7%)
Prevention through design (T13) 5 (0.7%)
Health knowledge (T14) 2 (0.3%)
Health leadership (T15) 1 (0.1%)
Task level (THM) Risk assessment (T16) 141 (18.7%)
Health measures (T17) 26 (3.5%)
Table 6.
The distribution of
research topics in CHM
research
Structure and
emerging
trends of CHM
(0.1%). In contrast, technology-driven health intervention focuses on the adoption of
innovative technologies to promote occupational health. Innovative technologies that have
potentials for promotion in construction, including BIM, 4D computer-aided design (CAD),
virtual reality (VR), online databases, location, sensing, imaging and warning technologies
(Zhou et al., 2012,2015).
Topics on technology-driven intervention include “health monitoring (T10)”(6.0%),
“health planning (T11)”(1.7%) and “prevention through design (T13)”(0.7%). “Health
monitoring (T10)”focused on the construction process, involving vision-based monitoring
and sensing-based monitoring. Vision-based technologies consist of the depth camera (Zhu
and Cao, 2014) and RGB camera (Yu et al., 2019); while wearable sensors include motion
sensors such as inertial measurement unit (IMU) (Chen et al., 2017;Yan et al., 2017), and
physiological sensors such as electromyography and heart rate (EMG) (Umer et al., 2017b;
Hwang et al., 2016). “Health planning (T11)”and “prevention through design (T13)”
concentrated on promoting occupational health in a proactive manner. For instance,
construction site layout could be optimized before construction to reduce noise pollution
(Ning et al., 2019). Automated biomechanical simulation approach could be applied for job
analysis to eliminate ergonomic hazards during the workplace design (Golabchi et al., 2015).
4.4 Temporal trend analysis
With regards to the time dimension, Figure 10 demonstrates the temporal evolution of four
research levels together with 17 topics (denoted by symbols from T1 to T17, respectively) in
(a) (b)
(c) (d)
1990-1998 1999-2006 2007-2013 2014-2020
1990-1998 1999-2006 2007-2013 2014-2020
1990-1998 1999-2006 2007-2013 2014-2020
1990-1998 1999-2006 2007-2013 2014-2020
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
0%
5%
10%
15%
20%
0%
5%
10%
15%
20%
25%
0%
10%
20%
30%
40%
50%
60%
70%
Occurence frequency
Occurence frequency
Occurence frequency
Occurence frequency
Time interval Time interval
Time intervalTime interval
T1
T2
T3
T4
T5
T6
T7
T8
T9
T10
T11
T12
T14
T15
T16
T17
PHM
IHM
OHM
THM
Figure 10.
Temporal evolution of
research topics in CHM
ECAM
terms of their occurrence ratios in four time periods (1990–1998, 1999–2006, 2007–2013,
2014–2020). This shows that the percentages of some established health interventions had
significant decreases over the whole investigative periods. As an illustration, research topic
“health investigation (T2)”at population level dropped from 40.3% of the total in the first time
period to 11.0% in the last time period. In contrast, some topics expanded rapidly, especially
at the organization level. The topic “health monitoring (T10)”witnessed a significant growth
in past 6 years, increasing from 1.4% to 11.9%, and “health performance (T9)”(from 9.3% to
13.8%) and “health planning (T11)”(from 1.4% to 2.3%) also had a steady increase.
To further verify the temporal evolution trend identified through above content analysis,
the burst detection provided by CiteSpace software was carried out to examine strong burst
terms extracted from the title, abstract and keywords of 753 articles. Totally, 55 strong burst
terms were identified, the detailed information of which has been provided in Supplementary
Material. The terms with strong burst strength represent that associated studies have
notably increased over a short time, and often predict the emerging trends. CHM research
initially focused on the epidemiological investigation of illnesses or injuries suffered by
construction workers, which was indicated by dominant ratio of PHM (66.1%) during the first
time period (from 1990 to 1998), which was consistent with strong burst terms “epidemiology
(with a burst strength of 5.32, from 1992 to 2007)”and “neck shoulder pain (4.16, 1992–2007).”
Health risks at the task level has received more attentions during the second time period
(1999–2006), which could be indicated by the steady increase of topic “risk assessment (T16)”
and “health measures (T17).”Representative burst keywords in this period included “risk
(4.61, 2002–2004)”and “exposure assessment (4.44, 2001–2004).”Based on the theories of
organizational behaviors and engineering techniques, CHM research had further
development during the third period (2007–2013). During this period, some health
interventions were frequently explored like the topic “health insurance (T5),”“adoption of
health innovation (T6),”“prevention through design (T13)”and “health behavior (T14).”In
the last period, innovation techniques have attracted more interests to improve the accuracy
and efficiency of onsite health management. The terms with high burst strength included
“wearable devices (5.77, 2017–2018)”and “machine learning (3.75, 2018–2020),”which was
consistent with the fast increase of topics “health monitoring (T10)”and “health planning
(T11).”At the same time, psychological health has become a hot area, indicated by the strong
burst terms of “mental health (3.92, 2018–2020)”and “mental fatigue (3.57, 2017–2020),”
which was aligned to the increasing trends of psychological hazards as mentioned earlier.
5. Discussion
5.1 Emerging trends of CHM research
5.1.1 Increasing diversity of research topics. Research topics in the CHM field have become
diversified during the whole investigative period, which was shown in Figure 10. With the
continuous improvement of health awareness among construction practitioners, CHM
research has shifted from merely assessing the characteristics of health hazards or diseases
at task level or population level to proactively promoting occupational health at project level
or industry level (shown as Figure 10). CHM research has applied the general management
theories to address occupational health problems. For instance, the social network and health
leadership have been explored to achieve a sustainable improvement of construction
workers’health status (Yuan et al., 2018;Zuo et al., 2017). Construction workers’knowledge
and attitude towards vaccine were found to be critical to increase the coverage of immunity
towards infectious diseases such as tetanus (Ricco et al., 2016). Furthermore, some topics
emerged with the development of new construction practices. With the application of new
products in construction like nanomaterials and green products, the possibility of new
chemical exposure has attracted attention to eliminate associated negative health effect
Structure and
emerging
trends of CHM
(D
ıaz-Soler et al., 2019;Al-Bayati Ahmed and Al-Zubaidi Hazim, 2018). In addition, in
response to “greenhouse effect”and changing global temperature, heat stress has become a
critical health risk in CHM research (Rowlinson et al., 2014).
5.1.2 Increasing application of innovation technologies. High burst terms like “wearable
device (5.77, 2017–2018)”and “machine learning (3.75, 2018–2020)”indicated that innovation
technologies represented one emerging trend in CHM research. Compared with other
industries, construction industry exists several unique characteristics, including the
transitory and diverse nature of construction activities (Zhang and Fang, 2013), the
complex and unstructured construction sites (Zhou et al., 2015), and the difficulties of
management because work crews are spatially dispersed and have responsibility for various
tasks away from the contractor’s office (Liang et al., 2018a). In addition, due to construction
workers’unique characteristics (e.g. age, experience, physiological characteristic and gender),
they might have different psychological and physiological responses towards a certain task
demand (Jebelli et al., 2019). Therefore, construction health management practices need the
application of innovation technologies to capture and deal with these novel, various and
personalized health hazards and risks (Antwi-Afari et al., 2019). There are increasing
application of innovative technologies in health monitoring (T10) and health planning (T11)
in the last two time periods, as shown in Figure 10. This reflects that the potential of
innovation technologies to enhance CHM has been recognized, and more application of novel
technologies would be a future trend in CHM research.
5.1.3 Increasing concern of workers’psychological health. Given the new forms of
employment and intensification of work, the construction industry become more stressful in
recent years (Boschman et al., 2013). As indicated by Figure 8, CHM studies have shown more
interests on the psychological hazards of health because of the increasing mental-ill health
problems among front-line workers found recently including stress disorders, anxiety,
depression and suicidality (Nwaogu et al., 2020;Jones et al., 2019). High burst terms “mental
fatigue (3.57, 2017–2020)”and “mental health (3.92, 2018–2020)”also indicated that
psychological health represented one hot topic recently. CHM researchers have investigated
the risk factors and coping behaviors that might influence the metal ill-health among
construction workers (Hsu et al., 2016;Liang et al., 2018b;Langdon and Sawang, 2018).These
risk factors can be grouped into three categories: personal characteristics (such as age (King
et al., 2019) and masculinity (Kotera et al., 2019)), organizational factors (such as job demand,
job control and social support (Chan et al., 2020)) and environmental conditions (such as
extreme weather (Liang et al., 2018b) and financial crisis (Navarro-Abal et al., 2018)). As for
the consequence of mental health, the spillover effect models of mental health have been
developed, which link mental ill-health to other project outcomes such as safety performance
(Leung et al., 2010,2012;Wu et al., 2018;Wang et al., 2018) and productivity (Maqsoom et al.,
2019). As one way to obtain a sustainable workforce, more empirically supported mental
health studies will be carried out in the future as guides for managers to select most effective
interventions for mental-ill health.
5.2 Research gaps and agenda
5.2.1 Lack of clear definition of health management system. Current CHM research suffers
from serious fragmentation which often concentrated on the management of one specific
health hazard in terms of physical, chemical, psychological, biological and behavioral aspects
(shown as Figure 7). However, there is still lack of systematic studies to identify main
components and their interrelationships of health management system, which could supply
suitable and general framework to guide how to improve the health management
performance (Li et al., 2017). Despite it is mentioned together with occupational safety in
international standards OHSAS 18001 and the latest ISO 45001, occupational health seems
ECAM
often not to be equally treated like safety in whether academic studies or practices (Dahler-
Larsen et al., 2020). Previous studies on the occupational health and safety tend to focus
exclusively on safety hazards, and if any, only include some acute illnesses (Jones et al., 2019;
Jaafar et al., 2018). In industry practice, there is also no effective occupational health system
primarily due to the invisibility and latency of health effects, and managers’and workers’
lack of knowledge on how to promote occupational health (Jones et al., 2019). Therefore, much
clearer definition and key dimensions of health management system (e.g. management
support and worker engagement as well as other organizational aspects like risk
management) and their relative effectiveness for various occupational health issues should
be explored empirically in the future (Li et al., 2017).
5.2.2 Lack of wide adoption of innovation technologies. The adoption and implementation
of innovation technologies, such as vision-based technologies and wearable sensing
technologies, presents great potential to improve construction health performance (Ahn et al.,
2019;Zhu et al., 2017). However, despite slight increase in technology adoption has been
witnessed, a notable resistance regarding the continuous use remains an issue in construction
industry (Zhou et al., 2015;Nnaji and Karakhan, 2020). On the one hand, the technologies
developed in laboratory environment are still not adequate to adapt to the complexity onsite
(Antwi-Afari et al., 2019). For instance, vision-based technologies (e.g., RGB camera) are
limited by the fact that a direct line of sight is required to monitor the movements (Antwi-
Afari et al., 2018); while wearable sensors(e.g., IMU and EMG) are difficult to detect the
ground reaction force data of the whole body, and may make worker feel uncomfortable and
inconvenient while performing a give task (Chen et al., 2017a;Umer et al., 2017a). On the other
hand, the extra expense for purchase and required training, the lack of technology support
and concern of the usefulness of innovation technologies also hinder the wide adoption of
innovation technologies (Nnaji and Karakhan, 2020). Therefore, barriers of technology use in
the construction industry and corresponding strategies to overcome barriers need to be
further explored in the future. Furthermore, the current technology-driven CHM research
tends to focus on one specific hazard such as awkward posture, mental stress and noise
(Valero et al., 2017;Jebelli et al., 2018;Ning et al., 2019). In order to improve the efficiency and
cover most of health hazards, the integrative platform that supports the interoperation of
different information technologies should be studied in the future (Jin et al., 2019).
5.2.3 Lack of multilevel behavior-driven health research. Despite the importance of
technological improvement and working environment, health issues could not be absolutely
eliminated without workers’health behaviors (e.g. their compliance with health rules and
actively participation in health programs). However, only 1.7% CHM studies paid attention to
workers’health-related behaviors (shown as Table 6). There is still lack of behavior-driven
health research to explore workers’health behaviors from multi-levels, including individual,
group and organization. For the individual level, current studies have not given a clear
definition on health behaviors, and future studies could develop the scale of health behaviors
from various dimensions like health compliance and health participation. The individual
factors (e.g. personality traits, health knowledge, motivation and attitude) that directly
determine workers’health behaviors should be empirically explored. For the group level, it is
well-documented that social norms could exert potential effects on individual workers’
behavioral decisions (Choi et al., 2017a,b). Future studies should compare the social contagion
effects of coworkers’and supervisors’health behaviors (e.g., use of health protection and
healthy lifestyles) on individuals (Liang and Zhang, 2019;Liang et al., 2018a). For the
organizational level, the health leadership could be explored to guide the managers’health
awareness and responsibilities (Zuo et al., 2017;Umeokafor, 2018). The core dimensions of
health-specific organizational culture, namely the health culture, could be further determined
to promote the continuous improvement of health performance onsite (Parker et al., 2017).
Structure and
emerging
trends of CHM
5.2.4 Lack of effective biological health interventions. Construction workers tend to be
vulnerable to the biological hazards, especially the viral transmission, considering the labor-
intensive nature, poor working and living conditions, and physical proximity required by
many construction tasks (Pasco et al., 2020). Unfortunately, it was found that few previous
CHM studies have focused on biological hazards exposed to construction workers (shown as
Figure 7). With the pandemic outbreak of the new coronavirus (COIVD-19) globally, more
attentions should be paid to the biological health interventions such as social distancing and
other healthy protocol (e.g., wearing a face mask, limits number of workers onsite and
disinfecting shared equipment) to curve the spread of coronavirus among construction
workers. Although the government and health organizations have issued guidelines to cope
with the impact of COVID-19 pandemic, it seems that no specific interventions are available
for construction industry(Amoah and Simpeh, 2020). In response to this gap, a robust spread
model of COVID-19 among construction workers considering different mitigation procedures
should be established and empirically verified to identify effective solutions for project
managers (Araya, 2021). In addition, considering workers’increased psychological stress
during this pandemic (Xiong et al., 2020), some protective psychological factors like
mindfulness, resilience and psychological capital, need to be further studied to help workers
combat negative psychological issues during the pandemic period (Chen et al., 2017b;Leung
et al., 2016a;Yuan et al., 2018).
6. Conclusions
In the past decades, numerous CHM studies have been conducted in order to understand the
characteristics of occupational health issues among construction workers and propose
feasible mitigation measures. However, there is still lack of a comprehensive review to
summarize the existing CHM studies. This research employed a systematic approach
consisting of bibliometric research (e.g., co-occurrence analysis, co-citation analysis) and an
in-depth content analysis to review 753 CHM-related articles collected from Web of Science
core database from 1990 to 2020. This research could provide researchers and practitioners
with a holistic understanding of the intellectual structure in CHM research, and identify the
emerging trends to guide future research directions.
Bibliometric review showed that CHM research has been increasingly popular among
researchers, with a constantly growth in the number of publications over the investigative
period. The USA was found to be the predominant country in CHM research. In addition,
Hong Kong Polytechnic University and Harvard University were two most productive
institutions, and two academic groups were identified in this domain according to cooperative
relationship among these institutes. American Journal of Industrial Medicine was the most
influential journals in the CHM research. Keyword analysis revealed the most frequent
keywords, including musculoskeletal disorders, ergonomics, posture, low back pain, which
are grouped into three clusters, which were associated with physical health, psychological
health and epidemiology investigation, respectively.
Content analysis obtained the publication distribution of five health hazards, four levels of
analysis and identified 17 research topics which were beneficial to understand the structure
and temporal evolution of CHM research. Then, three emerging trends were revealed,
including: increasing diversity of research topics; increasing application of innovation
technologies; increasing concern of workers’psychological health. The corresponding
research gaps were discussed namely: lack of clear definition of health management system;
lack of wide adoption of innovation technologies; lack of multilevel behavior-driven health
research; lack of effective biological health interventions. A set of research agenda was
provided to guide future research directions.
ECAM
This research is the first to highlight the issues of occupational health management from
the perspective of construction workers. Researchers would follow the recommended
directions to fill the research gaps and extend the body of CHM knowledge domain.
Nevertheless, the findings are to be considered in light of certain limitations. First, the
analysis was based on limited literature samples published in Web of Science core collection
and only English journal articles were included due to a consistent data format required by
the bibliometric techniques. It might have potentially excluded some latest studies in other
languages and literature types, and those studies merely published in other databases such
as Scopus. In the future, more comprehensive data can be collected by combining data from
various sources to fully assess the current status of CHM research.
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Supplementary material
The supplementary file is available online for this article.
Corresponding author
Xiaoxiao Shi can be contacted at: xxshi@buaa.edu.cn
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Structure and
emerging
trends of CHM
