Manuela De Sario1*
Francesca Katherine de'Donato1
Michela Bonafede2
Alessandro Marinaccio2
Miriam Levi3
Filippo Ariani4
Marco Morabito5
Paola Michelozzi1 on behalf of the Worklimate Collaborative Group- 1Department of Epidemiology Lazio Regional Health Service, Rome, Italy
- 2Occupational and Environmental Medicine, Epidemiology and Hygiene Department, Italian Workers' Compensation Authority (INAIL), Rome, Italy
- 3Epidemiology Unit, Department of Prevention, Central Tuscany Local Health Authority, Florence, Italy
- 4Regional Centre for the Analysis of Data on Occupational and Work-Related Injuries and Diseases, Central Tuscany Local Health Authority, Florence, Italy
- 5Institute of Bioeconomy, National Research Council (IBE-CNR), Florence, Italy
Introduction: While there is consistent evidence on the effects of heat on workers' health and safety, the evidence on the resulting social and economic impacts is still limited. A scoping literature review was carried out to update the knowledge about social and economic impacts related to workplace heat exposure.
Methods: The literature search was conducted in two bibliographic databases (Web of Science and PubMed), to select publications from 2010 to April 2022.
Results: A total of 89 studies were included in the qualitative synthesis (32 field studies, 8 studies estimating healthcare-related costs, and 49 economic studies). Overall, consistent evidence of the socioeconomic impacts of heat exposure in the workplace emerges. Actual productivity losses at the global level are nearly 10% and are expected to increase up to 30–40% under the worst climate change scenario by the end of the century. Vulnerable regions are mainly low-latitude and low- and middle-income countries with a greater proportion of outdoor workers but include also areas from developed countries such as southern Europe. The most affected sectors are agriculture and construction. There is limited evidence regarding the role of cooling measures and changes in the work/rest schedule in mitigating heat-related productivity loss.
Conclusion: The available evidence highlights the need for strengthening prevention efforts to enhance workers' awareness and resilience toward occupational heat exposure, particularly in low- and middle-income countries but also in some areas of developed countries where an increase in frequency and intensity of heat waves is expected under future climate change scenarios.
1. Introduction
There is a consistent body of evidence that high outdoor and indoor temperatures have adverse health effects in exposed workers (1–4). Workers are normally healthier than the general population, but they, especially those severely exposed and engaged in heavy workloads, may be equally affected by heat stress when the thermoregulatory capacity of the body is disrupted, and physiological pathways resulting in heat-related illness, acute outcomes (e.g., myocardial infarction), or exacerbations of pre-existing diseases (e.g., cardiovascular and respiratory outcomes) are activated (2). Individuals working in the heat are also prone to physical strength losses and cognitive function impairments, leading to work-related injuries (3), missed workdays, and productivity reductions (4) and, in the long term, may develop chronic kidney impairment (5, 6). Health and productivity outcomes related to heat strain have a huge impact in terms of social and economic costs on the different actors involved (7): the workers themselves due to the temporary or permanent health and quality of life impairments and missed wages, the farm or factory due to necessity of maintaining production despite employees absences or output reductions, the healthcare system due to the healthcare expenditures due to workers seeking care, the social security or insurance system due to reimbursements to laborers for injuries, permanent disability, or occupational diseases, and the whole country or region in terms of reductions of the gross domestic product due to production losses in specific economic sectors. Moreover, climate change is expected to worsen heat exposure in some regions exceeding work-related productivity thresholds (8).
Heat exposure in the workplace is a growing hazard throughout the world, considering climate change scenarios showing a universal increase in heat extremes virtually in every region, but larger in Central and South America, the Mediterranean region, north Africa, the Arabian Peninsula, India, and Southeast Asia (9). Most of the affected regions are low-income economies mostly relying on manual labor and manufacturing work with agriculture and construction being the economic sectors at higher risk of heat exposure and at higher workload intensity than others. The quantification of economic impacts of heat exposure in the workplace is of worth for individual companies, labor policymakers, insurance companies, but also for occupational safety and healthcare systems and should be taken into account when analyzing markets and economies at both the local and global scale. The knowledge of economic losses related to heat may serve as a basis to plan prevention measures at company level with a view on cost–benefit analysis, to set up specific heat adaptation policies, or to strengthen social security systems by enclosing climate risk concerns, especially toward poorer population and countries (10).
Differently from the strong evidence available on the effects of heat on workers' health and safety, there is still limited but growing evidence on the resulting social (7, 11) and economic impacts (12). The lack of standardized methodologies for evaluation (epidemiological vs. econometric studies), as well as in the operational definitions of productivity loss (lost worktime, reported physical and cognitive performance reductions, and work output reductions in case of manual workers), heat-related productivity losses, and economic costs (i.e., lost salaries and wages due to fatigue/sickness, cost per compensable claim, and healthcare costs related to treatment and rehabilitation) make it difficult to have consistent findings and clear trends. Despite the close connection between indicators of social and economic heat-related impacts and the common underlying causal pathways, no previous literature review considered both social and economic losses related to heat at the same time.
As part of the Italian WORKLIMATE Project (https://www.worklimate.it) funded by the Italian Workers' Compensation Authority (INAIL), a literature review was carried out to update the evidence on both social and economic impacts related to workplace heat exposure. To address such a comprehensive research question, a scoping review was considered to be more suitable, as suggested also by other authors (13), to address the whole body of evidence deriving from different type of studies (i.e., epidemiological and economic modeling studies).
2. Methods
The scoping literature search was conducted in two bibliographic databases (Web of Science and PubMed), using both free terms and controlled vocabulary (Supplementary Table 1) to select studies published since 2010 to April 2022. Since previous reviews considered impacts of occupational heat stress on workers' productivity (7, 11, 14) and on economic losses (12) separately, and in consideration of the interconnections between work performance, workers' health and safety, and monetary costs, the outcomes of interest were both social impacts related to workers (i.e., work hours losses and work absences), and economic impacts for a specific group of workers or economic sector (i.e., monetary costs associated to production losses) or for social security systems (i.e., compensation for work-related injuries and diseases). Both indoor and outdoor occupational heat exposure and all potentially exposed economic sectors and tasks (e.g., manual workers) were considered. The first group of relevant studies were from epidemiological studies (both qualitative and quantitative) on workers estimating productivity losses in the field or estimating costs related to occupational heat-related illnesses and injuries. The second category of suitable studies was represented by recently conducted economic studies adopting several approaches such as structural economic models and econometric models, to estimate the impacts of climate change on labor productivity and related economic costs, using occupational health and safety recommendations in an entire economic sector and for regional or global economies. Experimental studies (e.g., on physiological responses), epidemiological studies on occupational heat-related illnesses not estimating economic implications, studies focusing only on the impact of heat exposure on workers' cognitive functions, and studies on other occupational exposures (e.g., cold, air pollution) were excluded. Only original studies were retrieved, while literature reviews (7, 11, 12, 14–16) were excluded but used to screen for additional relevant studies, as well as the 6th assessment report of the Intergovernmental Panel on Climate Change (https://www.ipcc.ch/report/ar6/wg2/) (8). The selection of studies and data extraction were conducted according to PRISMA guidelines (17). The outcomes considered were as follows:
- Lost productivity estimated or perceived by the worker associated with the heat exposure.
- Economic costs associated with heat-related injuries or hospitalizations in workers.
- Projections of productivity losses due to heat and related economic costs for current climate or under climate change scenarios.
Given the heterogeneity of study designs, methods for estimating costs or productivity, outcomes considered, and occupational sectors investigated, a narrative synthesis was undertaken by grouping studies by design (epidemiological vs. economic studies).
3. Results
A total of 8,151 potentially relevant records were identified after duplicates were removed, of which 104 were identified from previous reviews on the topic (7, 11, 12, 14–16) or other sources (Supplementary Figure 1). Out of these, 137 were assessed as full texts because potentially relevant, and, finally, 89 studies were included in the qualitative synthesis. The largest number of studies was carried out in Asia (49 studies) and the lowest in Central and South America (24 studies) (all totals include the 21 global economic modeling studies) (Figure 1). Field studies accounted for a larger proportion of studies in Asia, Oceania, and Europe, healthcare-related studies were more prevalent in North America and Oceania, and regional modeling studies were mostly conducted in North America, Europe, and Asia.
Figure 1. Geographical distribution of included studies based on the study design by continents.
Table 1 describes the results of the epidemiological studies (n = 40), including 32 field studies and 8 studies estimating healthcare-related costs.
Table 1. Results of epidemiological studies estimating productivity, social, or economic losses related to occupational heat exposure.
3.1. Field studies
Most field studies (20 out of 32) were conducted in low- or middle-income countries (18, 20–22, 24, 27, 29–31, 33, 37, 38, 40–42, 45–47, 49), with only 11 studies from Europe, the USA, and Australia/New Zealand (19, 23, 25, 26, 28, 34, 35, 39, 43, 44, 48) and 1 multicenter study (36). Three studies were qualitative, based on interviews or focus groups (28, 33, 43), while the other studies were quantitative with 27 cross-sectional and 2 longitudinal studies (26, 42) and provided an estimation of the association between heat and labor productivity measured in the field or perceived by workers. The study size overall ranging from 16 (30) to 4,095 workers (21) in different occupational sectors (9 on agriculture, 4 on construction, 1 on mining, and 18 from several sectors) also includes indoor workers (13 studies). Two main approaches were followed by studies in estimating heat impacts on productivity. The first approach provides an estimation of productivity and then evaluates the losses due to heat by comparing productivity data collected at different WBGT levels. In these studies, productivity was estimated in different ways: by worktime (direct, indirect, and non-productive) (22, 30), cognitive and physical performance (e.g., time to complete task/work extra hour absenteeism/taken sick leave) self-reported from questionnaires or interviews (26, 30, 32, 38), clinical examinations (e.g., walking speed) (42), daily output reported or measured by field instruments (e.g., tally counters) (21, 25), and premature worker attrition (21). In the second approach, productivity was not measured by itself, but in terms of productivity losses due to heat in different ways: published physiological models (31), self-reported by workers (29, 49), and prediction models of economic losses due to heat based on number of laborers and the given laborers salary when exceeding WBGT thresholds (44). All studies used individual productivity measures except Amini et al. (18), which evaluated productivity at area level.
Despite the great heterogeneity in the work sectors and study size, nearly all field studies consistently showed a reduction in productivity due to occupational heat exposure. The only exception was one study on office workers not providing evidence of influence of thermal stress on work performance, possibly due to the fact that the thermal stress variable evaluated included both heat and cold temperature; therefore, their single contributions on work performance could not be disentangled (26). The estimated productivity losses ranged between 0.3% and 10% reduction for an increase of 1°C in WBGT (30, 40–42, 47). Considering the whole summer season, the prevalence of workers reporting heat-related productivity loss varied among studies from 11% (46) to 81% (35). Some studies also found an association of heat with an increase in indirect non-productive time at work (30), an increase in idle time at work (30), or in personal household time needed to rest to adapt to heat stress (22). Four studies (36, 44, 48, 49) also provided an estimate of the related economic costs by applying the productivity losses to the gross wages or income of workers with an estimated cost of 6–8 euros per hour worked in Italy (36), 1100 Canadian dollars annually per worker in Ontario (44), 655 USD annually per worker in Australia (48), and 257 euros annually per worker in Malaysia (49). In one study (45), 25% of the workers self-referred a loss in their wages due to fatigue or sickness related to heat. The study by Langkulsen et al. (27) showed a reduction in productivity only in two of the occupational sectors considered (pottery and construction) but not in the others. Only Li et al. (30) and Yi and Chan (47) adjusted for individual worker characteristics such as age and BMI. Given the cross-sectional approach adopted in most studies, the results do not allow causal inference on the association between occupational heat exposure and work productivity.
In some field studies, specific worker subgroups appeared to be more susceptible to the productivity losses due to occupational heat exposure: men (38, 40, 45, 48), females (31), younger, less educated or less experienced workers (37), workers exposed to direct sun (36), workers performing heavy tasks (45, 48), those using personal protective equipment (PPE), such as face masks (23, 29, 35), those affected by comorbidities such as kidney failure or other conditions (21, 22), migrant workers (32, 34), and workers not following safety protocols such as hydrating or taking breaks in cooling places (20, 24, 37).
3.2. Studies evaluating healthcare-related costs
In contrast to the field-based studies, the eight studies estimating healthcare-related costs due to occupational heat exposure used data from administrative databases; therefore, they were mostly conducted in western countries such as Europe, Australia, the US, and Canada (50–52, 54, 56–58), with only one study from China (53). Six studies considered all occupational sectors, while three studies only considered specific sectors, such as agriculture and construction. Five studies were descriptive analyses of occupational injuries or diseases identified as heat-related and consequent compensation costs in specific occupational sectors (50–52, 56, 57), while the other three were etiological studies estimating the occupational injuries attributable to heat exposure through time-series or case-crossover analysis and then quantifying the related costs (53, 54, 58).
The national Spanish study from Martinez-Solanas et al. (54) was the only one to estimate heat-related injuries corresponding costs including not only the direct costs attributable to social or private insurance refund to the workers (for long-term losses) or to the healthcare system but also the indirect costs associated with maintaining production, and costs of pain and suffering. The total economic impact of heat-related injuries in the study period was 320 million euros, with the costs associated with pain and suffering higher than other types of costs. The study conducted by Ma et al. (53) in China evaluated the attributable fraction of insurance pay-out related to occupational heat exposure (temperatures above the limit of the Wet Bulb Globe Temperature (WBGT) in accordance with international standards) of 4.1% (95% CI 0.2%–7.7%). In an Australian study, an increase of 1°C in maximum temperature above 33.8°C was associated with an increase of 41.6% in healthcare costs and 74.8% in working days lost due to heat-related injuries (58).
Two descriptive studies conducted in Washington State, US (50, 52), reported an increase in both the median cost per heat-related injury over time (from 537 USD in 1995–2005 to 909 USD in 2006–2017) and the number of working days lost due to injury (from 46 to 93 days per claim on average). The studies also reported an increase in temperatures over time associated with the injuries. In the same study area, Spector et al. (57) estimated a median cost per claim of 654 USD specifically for the agricultural and forestry sectors similar to the previous study conducted in the area (50). These studies suggest a higher median costs related with non-compensable claims for heat-related than for total injuries suggesting a possible under-reporting of work-related accidents in this sector (50, 52, 57). Another South Australian study on construction industry (56) calculated average cost during heat waves higher than in control periods (26,381 vs. 12,747 Australian dollars), with higher costs in the urban area than in the suburbs and for specific agents of injury (i.e., work platform, electricity, and equipment). Finally, a Canadian study in Ontario (51) estimated the rate of injuries related to loss of productive worktime (injury loss time), which is equal to 1.7 cases per million full-time equivalent months in the period 2004–2010.
Studies estimating healthcare-related costs identified some worker subgroups are related to higher costs or worktime losses such as manual workers (51), Black or Latinos workers (52), new workers (56, 58), workers aged 15–24 years (51), men (53), and workers of small- (56) or medium-sized companies (53, 58).
3.3. Results from economic studies
Table 2 describes the results of the 49 economic studies at the global (59–70, 72, 74–80) and regional level (73, 81–107). Most studies focused on impacts of current and projected heat on workers' productivity, with the exception of some studies estimating production output reductions due to heat (59, 72, 83) or studies evaluating heat-related impact on both workers and farm production output (66, 70, 100, 101). Climate change scenarios were considered in most studies, with only few studies providing estimated economic impacts for current climate only (66, 73, 77, 78, 91, 97, 98, 100, 101, 105). Studies based on economic models have used different approaches to estimate the economic costs associated with heat-associated reductions in worker productivity. The majority of studies starts from the working time losses estimated based on occupational health and safety standards at different work intensities and sectors. Most included studies estimated productivity as a function of the ISO 7243 standard on the risk associated with thermal stress, by considering exceeding a threshold of the Wet Bulb Globe Temperature indicator (WBGT) at the workplace or on the basis of the standard of indoor thermal comfort, the Predicted Mean Vote Index, and associating climate data with economic data or on the basis of previous studies (e.g., Hothaps models) (65, 67, 69, 91, 108). Worktime losses per day/worker are then rescaled to the entire worker population and expressed in terms of percent productivity loss, converted into monetary terms (e.g., by multiplying for average wages) or as portion of gross domestic product (GDP) considering the share to which each labor sector contributes to GDP. For studies on climate change scenarios, the incremental change relative to baseline is estimated compared to future scenarios usually at the middle (2050) and the end of the century (2100) comparing low and high emissions scenarios. With regards of studies focusing on farm production output, some of them applied structural economic models based on the so-called computable general equilibrium (CGE) model or general equilibrium models that allowed to consider the relationships and influence between economic sectors (70, 73, 74, 87, 97, 105). General equilibrium models are a class of economic models that use actual economic data to estimate how an economy might react to changes in policy, technology, or other external factors (109). Other studies quantified production output using empirical or literature data (66, 72, 100, 101). Some studies included in the economic modeling also an adaptation measure such as air conditioning for indoor work, or shifting work hours or lightening workloads (83, 84, 91, 94, 103, 104).
Table 2. Results of economic modeling studies estimating productivity, social, or economic losses related to occupational heat exposure present and future at the regional and global level.
3.3.1. Global studies
Studies evaluating global economic impacts of current and future occupational heat (n = 21) were both scientific publications (59, 60, 63–65, 67–70, 72, 74–80) and gray literature (16, 61, 62, 66), providing evidence of heat-related reductions in work productivity at the global level. Productivity losses associated with climate change by 2100 under the worst-case scenario (high emissions) range from nearly 10% (68) to 30–40% (15, 65, 67, 97) at the global level. GDP losses for the same period and scenario varied between 1.8% compared to baseline (75) to 23% (59). In specific sectors such as agriculture, the loss of productivity expressed as a percentage reduction in GDP is even >30–50% (64, 74). Global studies provided also estimates for the different world regions, by highlighting higher impacts from both current and future climates in low- and middle-income countries (60–62, 67, 68, 78), like sub-Saharan Africa (63, 64, 80), very hot countries (59, 66), and high-intensity work in low-latitude countries (75).
3.3.2. Regional studies
Regional studies (n = 28) were also considered both from peer-reviewed journals (73, 81, 82, 87–89, 91, 93–97, 99, 101–103, 105–107) and the gray literature (83–86, 90, 92, 98, 100, 104) confirming a heterogeneous impact of heat on work productivity not only among countries but also within the same country (82, 95, 99, 102). As seen in the global studies, low-latitude, high-intensity labor settings were the most affected such as West Africa, Southeast Asia, and Central and South America. Moreover, specific local studies suggest an impact also in other regions such as southern European countries (92, 97, 103), some parts of the US (especially agricultural areas in Southeast and Southwest) (94, 96, 106), and Australia (86). For example, under medium-high emission scenario by the end of the century, a 0.4–0.9% loss in productive days was shown for Southern Europe (92), 10.2% of wages lost were estimated in the US (94), and a 16–17% labor capacity loss was predicted in China (95). Agriculture was the sector most affected by heat stress, both considering the current climate and future scenarios and among non-agricultural sectors, construction, manufacturing, transportation, service, and mining (73, 83, 86, 98, 104, 105). Agriculture (97) and manufacturing sector are also expected to be impacted in terms of farm production output losses (100, 101).
The evaluation of adaptation measures was marginally evaluated: Air conditioning was effective in reducing labor productivity losses in indoor settings in two European studies (84, 103), with one study suggesting also a potential role for technological measures such as robotic exoskeletons (103), while measures affecting the work/rest schedule have been shown to reduce productivity loss in outdoor workers in one study in Ethiopia, Ghana, India, Jordan, and Tanzania (104) and in one US study (94) while another US study provided uncertain results (91).
4. Discussion
This literature review provides an updated summary of the evidence on socioeconomic impacts of occupational heat exposure and confirms the results of previous reviews (7, 11, 12, 14–16) and of the latest IPCC report (8). The review also provides further evidence on the association between indoor and outdoor heat exposure and socioeconomic impacts in terms of productivity loss or costs. Throughout the different study types, a coherent picture of the social and economic impacts of heat exposure in the workplace emerges, highlighting the main pathways for heat-related productivity losses. One pathway is in common with the general population and is related to the increased risk of acute heat-related illnesses and deaths (1) and the emergence of chronic illnesses consequences such as renal impairment (5, 6). Underlying biological mechanisms include thermoregulatory failure with cardiovascular fatigue and respiratory distress, dehydration with progressive kidney dysfunction in case of sustained chronic exposure. Another pathway is related to changes in vigilance and cognitive performance that may enhance the risk of distraction, impairment in risk perception, and reaction time leading to improper operation and injury (3). The third pathway directly related to work productivity and physical performance reductions and to the physiological need to rest during heat exposure, leading to a reduction in work hours and work output (16). All these pathways are strongly interconnected, and it is difficult to identify which plays a major role in productivity loss.
The most robust evidence in the present review derives from time-series or case-crossover studies (53, 54, 58). Such methods are the “gold-standard” study design to evaluate the short-term effects of environmental exposures at the population level while controlling for time-varying confounders. Field studies represent an important piece of evidence about heat-related productivity loss, but they have the limitation of providing evidence on a small sample and related to given setting at a specific time interval (110) and only a limited number of studies adjust for potential confounders (22, 39, 40, 47). Studies are consistent in reporting labor productivity loss perceived by the workers (19, 20, 23, 29, 32–35, 43, 45, 46, 48, 49) and have negative impacts in terms of physical performance (42) and work output (21, 25).
The largest body of evidence from the present review comes from economic modeling studies. These are mostly global or regional studies which apply modeled spatially resolved temperature data for the current or future climate change scenarios to risk functions from physiological studies (65, 71, 89, 91, 108) to obtain an estimation of loss in working hours which is then converted to economic costs via workers' wages or as portion of gross domestic product (GDP). Studies combining economic and climate modeling have the added value of providing current and future impact estimates which are useful for the definition of adaptation and mitigation actions. However, these models are dependent on the scenarios selected and assumptions made; thus, it is important that the uncertainty is adequately reported (71). More complex economic models, i.e., the general equilibrium models (109), are able to account for the interdependencies among sectors but also have a number of methodological challenges in particular in accounting for societal welfare changes (different by GDP), non-linear damages, and micro- and macro-adaptation processes (8). Although methodological differences limit comparability, actual productivity losses at the global level are nearly 10% (62, 65) and under the worst-case scenario (high emissions) by 2100 are expected to increase up to 30–40% (62, 65, 67, 75). GDP losses for the same period and scenario varied between 1.8% compared to baseline (75) and 23% (59). Scenarios suggest that in regions like sub-Saharan Africa, India, Southeast Asia, and South America, productivity losses may be even greater as they will experience significant warming and a high share of the economy entails labor-intensive occupations (59–64, 66–68, 75, 78, 80), experiencing over a 10 times increase in work hours lost under the worst emission scenario (62). Some studies also report substantial reductions in work capacity in the United States, Europe, and Australia (86, 92, 94, 96, 97, 103, 106).
Vulnerability factors increasing the risk of heat-related productivity loss may differ according to the underlying causal pathway, with potential differences among factors increasing vulnerability for heat-related diseases, heat-related injuries, and heat-related productivity loss. However, the link with socioeconomic impacts is less clear. Individual factors such as age (53, 56), gender (31, 37, 45, 49), race (52), education level (37, 53), immigration status (34), and comorbidities such as kidney failure or other conditions (21, 22) have been related to higher reduction in work productivity in some studies, but the evidence is limited. The work environment may also affect worker susceptibility to productivity losses related to heat, as consistently shown in the literature. Some occupational sectors, primarily agriculture and construction, appear more affected than others, suggesting a higher impact on productivity loss due to more intense physical activities. The agricultural sector alone accounts for two-thirds of all labor hours lost globally in 2021 at the global level (78). Other sectors or workers affected include transportation and utilities (83, 98), miners (37, 58, 83, 86, 105), and indoor workers with no air conditioning (19, 100, 101). Furthermore, performing heavy tasks (45, 48, 68, 70, 75, 89, 93), direct sunlight exposure (36, 63, 89), and use of personal protective equipment (PPE) (23, 29, 35) have been associated with productivity loss. In some cases, the work sector and task may be a multiplier of existing individual vulnerabilities, as in the case of migrant agricultural workers (34) or young manual workers (51).
Awareness of heat-related risks, health and safety actions and training, as well as workers behaviors play a key role productivity loss due to heat among workers (37). The heterogeneous perception of heat-related occupational risks and causes of productivity loss (35, 37, 45, 46) suggests that more efforts are needed to enhance risk perception and heat-protective behaviors. Work management policies need to have a holistic approach by addressing all potential pathways linking heat exposure to workers' health, safety, and productivity (37). Specific information tools aimed to increase adaptive capacity and protective behavior especially in the most vulnerable workers can reduce impacts on productivity, as suggested by the work carried out in Italy within the Worklimate project (https://www.worklimate.it/en/home-english/).
Some strengths and limitations are worth mentioning: the quality of studies was not formally evaluated, and the search was restricted to only two bibliographic databases (PubMed and Web of Science) and only to English language studies that may have restricted the geographical coverage of some areas of the world such as Central and South America and Africa. To partially counterbalance this, the inclusion of a significant number of studies (14 out of 89) from the gray literature (from academia, NGOs, or economic or policy organizations) (16, 46, 61, 62, 66, 83–86, 90, 92, 98, 100, 104) retrieved from reviews in the field (7, 11, 12, 14–16) ensures to include a greater number of studies from low- and middle-income countries where the issue is particularly relevant. Moreover, the scoping review was limited to studied published since 2010, but this was also the publication horizon from previous reviews (11, 12, 14).
Due to the heterogeneity of studies in terms of methodologies used, heat exposure indicators, and economic cost measures, a quantitative synthesis was not possible. However, the present literature review provides a clear and consistent indication of the effects of heat on productivity and costs for employers and employees, economic sectors, social security systems, and national economies. The impacts are coherent across a range of study designs and study areas although we cannot exclude that some relevant papers are missing, the possibility that publication bias could distort these results is low thanks to the inclusion of a relevant piece of gray literature as specified above. This large body of evidence can support decision-making process in terms of improving and protecting worker safety, health, and wellbeing following the Total Worker Health approach (111) also in the context of climate change resilience and response by involving all relevant stakeholders both at the policy level and at the workplace level (i.e., nurses or other healthcare practitioners and workers' compensation professionals) (112). A number of initiatives in this field have been taken, but more efforts are needed in terms of prevention, employer and employee information, and training to raise awareness and increase resilience and behavioral adaptation. The evidence suggests that the expected impacts of climate change may be even greater and that investing resources in prevention actions in occupational settings has both social and economic benefits. Despite the consistent evidence on productivity impacts, some knowledge gaps emerge. Future research needs to address them such as the role of individual and work-related factors in increasing worker's vulnerability to productivity losses, and the evaluation of adaptation measures such as work schedule adjustments and work-level reductions only little evaluated in terms of productivity improvements (91, 94, 104).
5. Conclusion
In conclusion, much knowledge has been accumulated about heat-related reduction in work capacity in recent years. There is an urgent need for holistic work management policies such as the Total Worker Health approach and for climate change adaptation and mitigation efforts to protect workers' health from future warming and climate extremes, especially in most vulnerable agriculture, manufacturing, and construction sectors and in very hot countries with high-intensity work.
Author contributions
MDS: literature review, conceptualization, and paper writing. Fd'D: literature review, conceptualization, design, supervision, interpretation, and paper writing. MB, ML, and MM: interpretation and paper writing. AM and FA: paper writing. PM: conceptualization, supervision, and interpretation. All authors contributed to the article and approved the submitted version.
Funding
This work was funded by INAIL, Research Plan 2019–2021, Project P1O4, BRIC n. ID 06; Project Worklimate: B14I19003320005 and HORIZON 2020 ENBEL Project no. 101003966 – ENBEL - H2020-LC-CLA-2018-2019-2020/H2020-LC-CLA-2020-1.
Acknowledgments
The authors would like to thank the members of the WORKLIMATE Collaborative Group: Alessandra Binazzi, Andrea Bogi, MB, Raimondo Buccelli, Tiziano Costantini, Alfonso Crisci, Fd'D, Simona Del Ferraro, Chiara Di Blasi, Tiziana Falcone, Luca Fibbi, Claudio Gariazzo, Bernardo Gozzini, Valentina Grasso, Daniele Grifoni, Giulia Guerri, ML, AM, Alessandro Messeri, Gianni Messeri, PM, Vincenzo Molinaro, Stefano Monti, MM, Antonio Moschetto, Pietro Nataletti, Francesco Pasi, Francesco Picciolo, Emma Pietrafesa, and Iole Pinto.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpubh.2023.1173553/full#supplementary-material
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Keywords: productivity loss, workers, climate change, occupational heat exposure, economic costs, scoping review
Citation: De Sario M, de'Donato FK, Bonafede M, Marinaccio A, Levi M, Ariani F, Morabito M and Michelozzi P (2023) Occupational heat stress, heat-related effects and the related social and economic loss: a scoping literature review. Front. Public Health 11:1173553. doi: 10.3389/fpubh.2023.1173553
Received: 24 February 2023; Accepted: 01 June 2023;
Published: 02 August 2023.
Edited by:
Alpo Juhani Vuorio, University of Helsinki, FinlandReviewed by:
Kristiina Patja, University of Helsinki, FinlandFaming Wang, Soochow University, China
Copyright © 2023 De Sario, de'Donato, Bonafede, Marinaccio, Levi, Ariani, Morabito and Michelozzi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Manuela De Sario, bS5kZXNhcmlvJiN4MDAwNDA7ZGVwbGF6aW8uaXQ=