Workplace Health and Safety under Climate Stress in Sri Lankan Apparel SMEs

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This mixed‑methods study assessed how climate‑related hazards affect the health, safety and productivity of workers in Sri Lankan small‑ and medium‑scale apparel manufacturing companies (SMAMCs). A survey of 384 employees in Biyagama and Katunayake Export Processing Zones captured quantitative data on exposure to excessive heat, flooding, indoor air pollution and mosquito‑borne diseases, and elicited qualitative accounts of workplace experiences. Heat waves and high humidity were the most pervasive stressors: 81 % of respondents reported heat stress, with headaches, dehydration, and diminished concentration frequently linked to needle‑prick injuries. Flood events damaged infrastructure and heightened respiratory, gastrointestinal and dermatological illnesses, while inadequate ventilation compounded air‑quality problems; 95 % of workers complained of persistent coughing. Dengue incidence over the preceding five years reached 11 %, reflecting expanding vector habitats. Chi‑square analysis confirmed statistically significant associations between each hazard and adverse health outcomes. The study underscores the need for integrated adaptation measures, improved ventilation, low‑cost cooling, drainage upgrades and systematic vector control, supported by enforceable regulations and targeted financial assistance. Enhancing climate resilience in SMAMCs is essential for safeguarding worker wellbeing and sustaining Sri Lanka’s export competitiveness, while contributing to global goals on decent work and climate action targets. Climate Change Impacts Workplace Health and Safety Sri Lankan Apparel Industry Small and Medium Manufacturing Companies Figures Figure 1 Figure 2 Key Highlights Mandate climate-resilient occupational‑safety standards covering heat, flood, air‑quality and vector risks in small and medium apparel factories to protect worker health and sustain productivity. Offer targeted grants and technical advice to retrofit ventilation, passive cooling and flood‑proofing, enabling resource-constrained SMEs to adopt cost-effective adaptations without losing competitiveness. Require real-time heat and air‑quality monitoring alongside staggered shifts and hydration breaks to reduce dehydration, cognitive fatigue and respiratory illness among apparel workers. Integrate occupational‑health rules with public vector‑control programmes to curb dengue in export zones, reducing absenteeism, safeguarding health and productivity, and supporting Sustainable Development Goals 8 and 13 1.0 INTRODUCTION The global apparel industry plays a critical role in economic development and employment generation, particularly in developing countries such as Bangladesh, Sri Lanka, Vietnam, and Ethiopia, where it accounts for a substantial share of exports and labour participation [ 1 ]. The apparel sector, given its highly labour-intensive nature, not only acts as an engine of economic growth but also supports millions of livelihoods, underpinning broader socio-economic stability in these nations. Consequently, the sustainability and resilience of this sector are paramount, especially against the backdrop of escalating environmental threats. Nevertheless, despite its considerable economic significance, the global apparel industry faces increasing exposure to climate-induced hazards such as floods, heatwaves, and droughts, which disrupt operations, damage infrastructure, and threaten worker health and productivity [ 2 ]. The vulnerability of the apparel industry to climate hazards emerges from multiple factors, including geographical susceptibility, inadequate infrastructure, limited resources allocated to climate adaptation, and systemic weaknesses in policy implementation [ 3 , 2 ]. These factors intensify risks, especially in countries reliant on this sector for economic stability and employment continuity. The implications of these risks are particularly profound in labour-intensive environments, where workplace health and safety are intrinsically linked to environmental stability. The apparel industry’s workforce is predominantly concentrated in developing regions, where workers often experience precarious working conditions compounded by limited access to adequate health and safety provisions [ 4 ]. Factories, particularly small- and medium-scale enterprises, frequently lack the structural and operational capacity to effectively manage climate-induced occupational hazards, thereby significantly compromising worker well-being. In South Asia, apparel production countries such as Bangladesh, India, and Sri Lanka are especially reliant on this sector for economic growth, foreign exchange earnings, and employment generation. Bangladesh, for instance, exemplifies the critical role apparel exports play, comprising approximately 80% of its total exports [ 1 ]. India and Sri Lanka similarly depend substantially on apparel manufacturing to drive economic growth and employment, yet all three countries grapple with persistent issues concerning workplace safety standards. Despite significant international attention following high-profile disasters, such as Bangladesh's Rana Plaza collapse, many factories across the region still face inadequate fire prevention systems, poor ventilation, and deficient emergency protocols [ 4 , 5 ]. These shortcomings are particularly pronounced within small and medium-scale enterprises, which typically possess limited financial and technical capacities, thus exacerbating their susceptibility to climate-induced hazards. Smaller apparel factories, notably those operating in Bangladesh, frequently experience critical gaps in structural integrity, emergency exits, and air quality management, placing workers at continual risk of occupational hazards [ 5 ]. Enforcement of safety standards across the apparel sector remains inconsistent, influenced significantly by governance challenges such as corruption, regulatory fragmentation, and inadequate oversight, disproportionately impacting smaller and subcontracted facilities [ 3 ]. Thus, addressing climate-induced health and safety concerns within smaller apparel manufacturing firms demands focused policy intervention and sustained institutional support. Several climate-induced hazards pose escalating threats to apparel-producing regions. Excessive heat, a widely documented hazard, considerably contributes to worker fatigue, dehydration, cognitive impairment, and significant productivity losses, particularly in factories lacking adequate thermal management systems. For example, research from Bangladesh and India highlights how increasing indoor temperatures directly correlate with higher incidents of heat stress among apparel workers, substantially reducing both worker well-being and operational efficiency [ 6 ]. These studies underscore the critical need for industry-specific adaptation measures to mitigate heat-related health risks. Poor air quality within enclosed factory spaces constitutes another significant occupational hazard, exacerbated by climate variability. Emissions from textile dyes, chemical processing, and insufficient ventilation systems have been strongly associated with chronic respiratory diseases, cardiovascular ailments, and reduced overall worker health [ 7 ]. While large-scale factories might employ sophisticated ventilation solutions, smaller factories frequently rely on rudimentary ventilation methods, which are insufficient to effectively mitigate air pollutants, especially during periods of elevated external temperatures or extreme weather conditions [ 3 , 4 ]. Vector-borne diseases such as dengue, malaria, and chikungunya represent an additional climate-induced hazard significantly impacting worker health in apparel-producing regions. Changing precipitation patterns, increasing temperatures, and inadequate drainage infrastructures intensify mosquito breeding, substantially heightening the risk of outbreaks. Increased rainfall events and prolonged periods of stagnant water, particularly common during monsoonal seasons, create ideal conditions for disease transmission. These vector-borne health threats disproportionately affect regions with inadequate environmental health infrastructure, posing severe risks to the health and productivity of the apparel workforce in Sri Lanka and similar countries in the region [ 8 ]. 1.2 Climate Change and The Sri Lankan Apparel Industry Sri Lanka’s apparel sector serves as a cornerstone of its industrial economy, contributing approximately 40% of the country’s total exports and generating over USD 5 billion in annual revenue [ 9 , 10 ]. Directly employing more than 350,000 workers, predominantly women, the sector also indirectly supports approximately 600,000 additional individuals through ancillary industries such as logistics, packaging, and services [ 11 ]. This substantial socio-economic role underscores the critical importance of maintaining operational continuity, resilience, and worker safety within the industry, particularly under mounting climatic pressures. The majority of apparel production in Sri Lanka occurs within small and medium-scale apparel manufacturing companies (SMAMCs), which are notably vulnerable to climate hazards due to several systemic challenges. These enterprises often function within older infrastructures with minimal adaptive capacities, lacking modern heating, ventilation, and air-conditioning (HVAC) systems [ 4 , 3 ]. Furthermore, limited financial and technical resources hinder their capacity to implement robust health and safety measures, significantly amplifying their vulnerability to climate-induced occupational hazards [ 5 , 3 ]. Sri Lanka’s climatic conditions are changing rapidly, with projections indicating a mean annual temperature rise of between 1.0 and 1.5°C by 2050, with pronounced impacts expected particularly in the northern and eastern provinces [ 12 ]. Concurrently, monsoonal rainfall patterns have become increasingly unpredictable, exacerbating the frequency and intensity of floods and droughts within shorter intervals [ 13 , 14 ]. These climatic shifts directly threaten apparel factory operations, impair infrastructure stability, disrupt supply chains, and significantly compromise worker health. Small and medium-scale enterprises within Sri Lanka’s apparel sector experience disproportionately severe impacts due to their characteristic operational environments, which include limited air circulation, high-density working conditions, and insufficient capacity to manage environmental health risks [ 7 , 15 ]. While large-scale apparel firms typically benefit from international partnerships and greater financial flexibility to implement comprehensive climate-adaptive strategies, SMAMCs lack such resources and institutional support [ 3 , 4 ]. Consequently, they are often neglected by policy frameworks and broader industry interventions, representing a critical oversight given their substantial contribution to sector-wide production and employment. Despite increasing evidence of these vulnerabilities, existing research and policy efforts in Sri Lanka predominantly focus on large-scale, export-oriented factories, marginalising the specific and heightened risks faced by SMAMCs. The continued neglect of SMAMCs undermines the overall resilience of Sri Lanka’s apparel sector, posing risks to worker safety, economic output, and the industry's global competitiveness. The urgency to bridge this policy and research gap is underscored by the dual imperatives of safeguarding worker health and maintaining economic stability in the face of escalating climate hazards. Accordingly, this study aims explicitly to examine the impacts of climate-induced occupational hazards on worker health and workplace safety within SMAMCs located in Sri Lanka’s Biyagama and Katunayake Export Processing Zones. It seeks to identify and analyse the most prevalent climate hazards faced by these enterprises, assess their specific health implications, and critically evaluate the effectiveness of current safety management practices in mitigating climate-related risks. Through targeted analysis of an often-overlooked segment of the apparel industry, this research will provide essential evidence to inform policymakers, industry stakeholders, and health professionals. In doing so, the study seeks to contribute meaningfully to the development of climate-resilient workplace strategies in alignment with global sustainability targets, specifically the United Nations Sustainable Development Goals: Goal 8 (Decent Work and Economic Growth) and Goal 13 (Climate Action). By foregrounding the unique challenges of Sri Lanka's SMAMCs within broader regional and global discourses on climate resilience, the research underscores both the necessity and feasibility of integrating climate considerations into workplace health and safety governance frameworks, ultimately aiming to foster sustainable, safe, and resilient working environments in the face of ongoing climate change. 2.0 MATERIALS AND METHODS This study was conducted within the Sri Lankan apparel manufacturing sector, focusing on small and medium-scale apparel manufacturing companies (SMAMCs) located in the Biyagama and Katunayake Free Trade Zones. These zones collectively host around 200 apparel companies and employ approximately 100,000 workers, forming the basis of the study population. Data collection was carried out over six months, from 4 October 2023 to 27 March 2024, allowing the study to capture seasonal and environmental variations relevant to climate-related workplace risks. A mixed-methods research design was adopted to investigate how climate-induced hazards affect workplace health and safety in SMAMCs. The quantitative component comprised a structured survey designed and developed specifically for this study to assess workers’ exposure to climate-related hazards and associated health risks. To complement and deepen these findings, open-ended questions were integrated within the survey instrument, enabling the collection of qualitative responses for thematic analysis. This methodological integration allowed for a more comprehensive understanding of both measurable trends and individual perceptions. A total of 384 employees participated in the survey. The sample size was determined using the Krejcie and Morgan [ 16 ] table, ensuring a 95% confidence level and a 5% margin of error. Participants included a diverse range of roles such as team members, multi-skilled operators, assistant team leaders, team leaders, and sectional heads, capturing variation in workplace exposure and responsibilities. While gender was not a selection criterion, it is well established that over 80% of the Sri Lankan apparel workforce is female, with more than 300,000 women employed directly [ 10 , 17 ]. Observations during site visits by the first author confirmed the predominance of women on production floors, aligning with national employment patterns [ 18 ]. The primary focus of this study was on the interaction between climate change and workplace health and safety, rather than gender-based analysis. 2.1 Data Collection Methods To assess current health and safety risks in the context of climate hazards, a pre-tested and pilot-validated questionnaire was used. It comprised both closed-ended (quantitative) and open-ended (qualitative) items. The survey was conducted in person within selected factories, targeting employees aged 18 and above with a minimum of two years’ experience. This ensured participants had sufficient exposure to factory operations and climatic variations to meaningfully contribute to the study. 2.2 Statistical and Qualitative Analysis Techniques The quantitative data were analysed using IBM SPSS version 29 (Armonk, New York, USA). Descriptive statistics were used to summarise demographic attributes and key safety-related variables. Inferential analysis was conducted using Pearson’s Chi-square test to identify associations between categorical variables such as job role, work experience, and perceived health risks. To assess internal reliability, Cronbach’s Alpha was applied for Likert-type items, while the Kuder-Richardson Formula 20 (KR-20) was used for binary items, confirming the validity and consistency of the dataset. The qualitative responses from open-ended survey questions were processed using NVivo version 15 (Denver, Colorado, USA) for thematic analysis. Coding was performed based on key phrases and recurrent terminology to identify dominant themes and sub-themes. This enabled the development of a thematic framework reflecting climate change-induced hazards. The integration of these qualitative insights with the quantitative findings provided a more nuanced understanding of how climate change is influencing occupational health and safety dynamics in Sri Lanka’s apparel manufacturing context. 3.0 RESULTS The analysis quantified the impacts of four major climate-related hazards on employees in Sri Lankan SMAMCs. Adverse weather events such as floods, cyclones, landslides, lightning, and strong winds were reported by 80.73% of respondents. Excessive heat impacted 81.25%, air pollution 44.53%, and mosquito-borne diseases 83.07% (Table 01 ). Pearson chi-square tests confirmed the statistical significance of these impacts: adverse weather (χ² = 28.380, p < 0.001), heat waves (χ² = 29.790, p < 0.001), air pollution (χ² = 36.050, p < 0.001), and mosquito-borne diseases (χ² = 7.280, p < 0.007). The Phi values indicate moderate to strong associations: 0.272 (adverse weather), 0.279 (excessive heat), 0.306 (air pollution), and 0.138 (mosquito-borne diseases). Table 01 Statistical significance of main climate change-induced natural hazards Climate Hazard Percentage Affected (%) Pearson Chi-Square P-Value Phi Value Adverse Weather Conditions 80.73 28.38 0.000 0.272 Excessive Heat 81.25 29.79 0.000 0.279 Air Pollution 44.53 36.05 0.000 0.306 Mosquito-borne Diseases 83.07 7.28 0.007 0.138 When detailing each climate change-induced hazard following risks and impacts have been experienced by the participants in their workplaces due to respective climate change-induced hazards. A.) Adverse Weather Conditions Adverse weather conditions were linked to several health issues among SMAMCs employees. Reported symptoms included respiratory problems (75.52%), asthma (77.08%), diarrhoea (47.40%), sinus issues (73.70%), and throat infections (81.25%). Mental health effects included stress (29.95%) and tension (26.82%). Pearson chi-square tests confirmed statistically substantial associations (Table 02 ). Table 02 Statistical significance of adverse weather-related health impacts Health Impact Percentage Affected (%) Pearson Chi-Square P-Value Phi Value Respiratory Issues 75.52 5.63 0.018 0.121 Asthma Symptoms 77.08 4.7 0.003 0.111 Diarrhoea 47.4 6.81 0.009 0.133 Sinus 73.7 15.82 0.000 0.203 Throat Infections 81.25 5.58 0.018 0.121 Stress 29.95 16.0 0.000 0.204 Analysis of qualitative responses identified two primary themes relating to the impacts of flooding on workplace health and safety in Sri Lanka’s SMAMCs: Physical Safety Risks: Workers frequently reported experiencing physical injuries due to unsafe conditions exacerbated by flooding events. Commonly described hazards included slippery communal areas, structural instability, and falling debris from compromised building infrastructure. One participant highlighted the immediate risk associated with wet floors, stating, “I fell near the canteen area after the rain, the floor was wet and no sign.” Another respondent detailed structural failure, noting, “The wall behind the packing section cracked and part fell during the last flood.” These examples underscore how inadequate maintenance and poor structural integrity significantly elevate physical injury risks during adverse weather conditions. Flood-related Health Issues: Participants also described a range of health complications arising from flood exposure, notably sore eyes, ringworm, hepatitis, respiratory infections, and flu-like symptoms. Workers commonly associated these illnesses with contact with contaminated floodwater and prolonged exposure to cold and damp conditions inside factories. One respondent noted, “When it rains, we walk through the flood to transport, later we get throat pain and fever.” Another participant highlighted respiratory health risks linked to poor infrastructure, stating, “Windows are not properly fixed, mist comes, we get breathing difficulties while raining, later we get sick.” Gastrointestinal issues were also prevalent, particularly during the monsoon season, as reflected by another worker's comment: “Most employees experience loose motion issues after the flood season due to well water usage.” B.) Excessive Heat Table 03 illustrates the substantial health risks posed by excessive heat in Sri Lanka’s SMAMCs, with the majority of participants reporting adverse symptoms: 89.58% reported excessive sweating, 85.67% reported headaches, 84.89% felt faint, 89.84% developed heat rashes, and 80.46% reported dehydration. Additionally, 85.41% reported reduced focus, 84.89% reported extreme fatigue, and 60.15% encountered workplace hazards. Chi-square analysis confirmed statistically substantial associations across all symptoms (p < 0.001), with Phi values (χ² ) ranging from 0.336 to 0.553, indicating moderate to strong correlations. Table 03 Statistical significance of excessive heat-induced risks. Risk Type Percentage Affected (%) Chi-Square P-Value Phi Value Excessive Sweating 89.58 69.66 0.000 0.426 Severe Headache 85.67 53.99 0.000 0.375 Feeling Faintness 84.89 77.59 0.000 0.450 Heat Rash 89.84 72.61 0.000 0.553 Dehydration 80.46 43.23 0.000 0.336 Reduced Focus 85.41 75.78 0.000 0.444 Extreme Fatigue 84.89 75.32 0.000 0.443 Workplace Hazards 60.15 53.2 0.000 0.372 Qualitative responses, participants described multiple physical health issues directly attributed to working in excessively hot conditions. Commonly reported symptoms included extreme fatigue, reduced physical strength, persistent tiredness, and energy depletion during work shifts. Workers frequently mentioned physical ailments such as sore eyes, cuts and grazes, insomnia, and a notable loss of appetite. One participant specifically stated, “Sore eyes are spreading during the hot season in the factory.” Additionally, several workers highlighted dermatological problems, describing episodes of skin irritation, blisters, and rashes exacerbated by heat exposure. As one worker explained, “I keep scratching my calf on hot days, and then the rash turns into blisters.” Workers further reported that fatigue and reduced concentration due to heat significantly increased the risk of workplace injuries, particularly needle-prick incidents among sewing operators. A worker described her experience: “I pricked my finger twice last week, it happens when we are too tired and sweaty.” Manual handling activities in high-temperature environments were also associated with fainting episodes and headaches, symptoms frequently experienced by employees across different factory departments. Moreover, access to drinking water was often limited, exacerbating dehydration and related symptoms. In addition to physical issues, workers reported considerable mental health and cognitive challenges linked to excessive heat exposure. Commonly mentioned mental health effects included difficulty concentrating on tasks, reduced motivation, and feelings of irritability directed both at themselves and their colleagues. One participant succinctly described these emotional impacts, noting, “When it’s too hot, I get angry.” Such emotional responses highlight the profound influence that sustained heat exposure has on workers' psychological well-being and workplace interpersonal dynamics. C.) Indoor Air Pollution Table 04 highlights the substantial health impacts of air pollution on SMAMCs employees, particularly respiratory issues. Participants reported coughing (95.05%), other respiratory problems (94.79%), allergies (94.01%), shortness of breath (70.31%), and eye diseases (70.57%). Pearson chi-square tests confirmed statistically substantial associations for shortness of breath (χ² = 21.779, p < 0.001) and eye diseases (χ² = 18.950, p < 0.001), with moderate Phi values of 0.238 and 0.222, respectively. Other symptoms, despite high prevalence, did not show statistical significance. Table 04 Statistical significance of air pollution-related health impacts. Health Impact Percentage Affected (%) Pearson Chi-Square P-Value Phi Value Coughing 95.05 1.358 0.244 0.0595 Shortness of Breath 70.31 21.779 0.000 0.238 Respiratory Issues Symptoms 94.79 3.258 0.071 0.092 Allergies 94.01 0.941 0.332 0.050 Eye Diseases 70.57 18.95 0.000 0.222 Qualitative responses, participants frequently reported respiratory health concerns directly associated with their work environment, often beginning shortly after joining the apparel industry. Commonly reported symptoms included wheezing, asthma-like conditions, and chronic breathing difficulties. One respondent clearly articulated this health impact, stating, “I never had asthma before, but now I wheeze almost every day after work.” Participants further emphasised that respiratory discomfort intensified on hot days due to increased air pollution from surrounding industrial activities. One worker described this scenario, stating, “When the heat is high, the outside smoke comes in, we can’t breathe properly and feel tired by noon.” These responses illustrate how industrial emissions, compounded by climatic conditions, significantly compromise respiratory health among apparel workers. Workers consistently highlighted eye and skin-related health problems caused by poor indoor air quality, particularly in factories reliant on natural ventilation systems. Eye irritation, commonly referred to by workers as “sore eyes”, was frequently attributed to the influx of dust through open windows during the dry season. One participant noted, “The dust gets in through the windows, my eyes turn red and start feeling burning.” Workers also described allergic responses, including conjunctivitis and skin irritations, which reportedly worsened when handling particular fabrics under hot and dusty conditions. Another respondent remarked, “Some materials make my skin itch and turn red; it’s worse when it’s hot and the place is dusty. D.) Mosquito-Borne Diseases Study highlights a significant prevalence of Dengue, affecting 10.68% of the population over the past five years, emphasising its extensive health implications. Statistical analysis with a Pearson chi-square result of r = 8.356, p < 0.003, shows a statistically significant link between Dengue and Environmental Factors. The conditions conducive to mosquito breeding, with a Phi value of 0.148, indicate a weak positive relationship. Qualitative responses, participants consistently noted an increased presence of mosquitoes and insects during hot and dry periods, causing considerable discomfort and negatively impacting their ability to concentrate and maintain productivity at work. One participant explained, “In the hot season, the mosquitoes don’t let us work, they keep biting.” Such conditions often resulted in visible skin irritations, rashes, and bite marks on workers' limbs. Another worker remarked, “We get rashes and marks on our arms and legs after bites.” The frequent scratching and irritation from insect bites often led to secondary health complications, such as open wounds, increased risk of infection, and subsequent absenteeism. Employees expressed particular concern regarding these complications and the implications for their longer-term health. One participant described a specific incident, stating, “I had to see the doctor because the bite turned into a sore, and I had to take leave.” 4.0 DISCUSSION AND CONCLUSIONS This study examined the multifaceted impacts of climate change-induced hazards flooding, excessive heat, indoor air pollution, and mosquito-borne diseases, on worker health, safety, and productivity within Sri Lanka’s small and medium apparel manufacturing companies (SMAMCs). The findings demonstrate direct, substantial, and cascading effects, highlighting a critical policy gap and emphasising the urgency of implementing integrated, climate-resilient workplace safety strategies. Adverse weather, notably flooding, emerged as a significant threat to worker health, with respiratory issues (75.52%), asthma (77.08%), diarrhoea (47.40%), and throat infections (81.25%) prominently reported. These findings align closely with global research demonstrating that flooding exacerbates respiratory conditions due to mould proliferation and damp indoor environments [ 19 , 20 ]. Additionally, psychological stress linked to extreme weather (29.95%) resonates with broader studies that underline mental health risks following floods [ 21 ]. The frequent physical injuries and illnesses (such as hepatitis, ringworm, and sore eyes) reported by respondents reflect the vulnerability of SMAMCs to infrastructure deficiencies and inadequate maintenance during floods, echoing findings by Saatchi et al. [ 22 ] in similar industrial contexts. Figure 01 illustrates this cascading nexus, confirming Tefera et al.’s [ 23 ] observation that a single climatic trigger can amplify multiple occupational risks. The net effect is a multi-hazard environment where traditional single-risk controls offer diminishing returns. Heat exposure also posed significant health risks, notably excessive sweating (89.58%), severe headaches (85.67%), and dehydration (80.46%), correlating closely with international evidence from tropical manufacturing environments, as reported by Moda et al. [ 24 ], ILO [ 20 ], and EU-OSHA [ 25 ]. These impacts are compounded by cognitive and psychological burdens such as reduced concentration (85.41%) and extreme fatigue (84.89%), which significantly heighten occupational injury risks, confirming previous findings from the NIOSH [ 26 ] and EU-OSHA [ 25 ]. Limited workplace hydration access intensified these effects, underlining a crucial policy oversight requiring immediate intervention. Indoor air pollution, particularly severe in factories reliant on natural ventilation, was associated with widespread respiratory and ocular irritation. Although coughing (95.05%) and general respiratory discomfort (94.79%) were prevalent yet statistically inconclusive, eye diseases showed significant associations (70.57%). These results are consistent with previous research linking particulate matter and industrial emissions to occupational eye and skin irritations [ 27 , 28 ]. Respondents’ qualitative feedback specifically highlighted the exacerbation of respiratory and ocular symptoms on hot days, supporting existing studies that associate poor ventilation with deteriorating worker health in textiles [ 23 , 29 ]. Mosquito-borne diseases, particularly dengue fever, were identified as a rising occupational hazard, correlating statistically with increased mosquito breeding conditions due to climatic variability. Dengue occurrences among workers substantiate earlier evidence highlighting climate-driven vector expansion [ 30 , 7 ]. Outbreaks observed in industrially dense regions, such as Colombo and Kurunegala, reinforce the need for targeted environmental surveillance and proactive vector control measures [ 31 , 32 ]. Additionally, the mental health implications associated with dengue and related infectious diseases align with findings from Gunathilaka et al. [ 33 ], reinforcing the importance of comprehensive, climate-sensitive occupational health strategies. Importantly, hazards were not isolated. Flood damage to buildings increased mould exposure and impeded ventilation, compounding heat stress and dust inhalation; heat, in turn, volatilised chemicals, aggravating respiratory symptoms; and both flooding and heat drove mosquito abundance. 4.2 Policy Implications for SMAMCs and Regulatory Authorities This study provides critical insights for immediate policy action (see Fig. 02 ). Firstly, the pronounced health impacts of flooding necessitate updating national occupational safety guidelines to incorporate specific flood-resilience measures. Regulators should mandate regular structural assessments, improved drainage systems, and emergency response training, explicitly tailored to the vulnerabilities of SMAMCs. A clear lesson for policymakers, factory owners, and Factory Inspecting Engineers (FIEs) is to prioritise infrastructure upgrades as part of broader climate adaptation investments, as recommended by the ILO [ 20 ]. Regarding excessive heat, the findings underline an urgent policy need to enforce comprehensive heat-management strategies. Practical policy measures include mandated provision of accessible drinking water, scheduled rest breaks during peak heat hours, and adoption of affordable cooling technologies such as evaporative coolers, supported by grant schemes. Integration of heat-stress metrics into routine factory inspections and labour compliance audits could significantly mitigate occupational heat risks, aligning with global best practices outlined by NIOSH [ 26 ] and EU-OSHA [ 25 ]. The pervasive issue of indoor air pollution highlights the need for regulatory frameworks promoting improved ventilation standards in SMAMCs. Policy recommendations should encompass minimum indoor air quality thresholds, incentivisation of dust-extraction technology investments, and training initiatives promoting awareness of occupational respiratory and ocular health risks. Enhanced enforcement of existing air quality and environmental regulations, particularly in industrially dense zones such as Katunayake and Biyagama, is essential to reduce exposure risks highlighted by workers. Finally, the rising incidence of dengue underscores the necessity for systematic vector-control audits during periods of drought and rainfall variability. Factory management should be mandated to conduct routine environmental surveillance and vector control measures, supported by clear regulatory guidance and periodic health inspections by Public Health Inspectors. Such integrated policy initiatives are essential to safeguarding worker health amidst evolving climate threats. While providing comprehensive insights, this study acknowledges limitations inherent in its methodology. The cross-sectional nature restricts causal inference and longitudinal tracking of health outcomes. Additionally, although the sample was statistically robust, recall bias and self-reporting limitations must be considered. Nonetheless, qualitative data triangulation and statistical significance across multiple health dimensions confirm the robustness of findings. The insights presented are transferable primarily to similarly structured Low- and Middle-Income Countries' (LMIC) apparel sectors but warrant cautious extrapolation beyond industrial contexts facing comparable climatic and infrastructural challenges. Future research should adopt longitudinal designs, allowing comprehensive tracking of climate-induced occupational health trends and the effectiveness of implemented policy interventions. Cost–benefit analyses evaluating engineering controls such as improved ventilation systems, flood-proofing infrastructures, and cooling technologies would substantially strengthen the business case for climate resilience investments in the apparel sector. Cross-national comparisons could further provide insights into regional variations in policy effectiveness, adaptation strategies, and regulatory frameworks, enabling the identification of best practices and knowledge transfer opportunities. Additionally, integrating qualitative assessments with quantitative models would enhance understanding of worker perceptions and organisational behaviour, ensuring that interventions are both scientifically robust and socially acceptable. Declarations 6.1 Ethics approval and consent to participate Ethical approval for this study was obtained from the Manchester Metropolitan University Health and Education Ethics Committee on 30 June 2023 (Ethos application number 45145). All participants received a participant information sheet outlining the study’s purpose, procedures, potential risks, and benefits. Participant consent was obtained prior to data collection. Participation was entirely voluntary, and all data were collected anonymously to ensure confidentiality. 6.2 Consent for publication All participants provided written informed consent for publication of the study findings. Participation was voluntary, data was collected anonymously, and confidentiality and privacy were fully safeguarded. 6.3 Availability of data and materials The data that support the findings of this study are available from the corresponding author (DS), upon reasonable request. 6.4 Competing interests The authors declare that they have no competing interests. 6.5 Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. 6.6 Authors' contributions Conceptualisation was undertaken by Devathanthrige Senadeera and Abu Sayem. Methodology was developed by Devathanthrige Senadeera, Abu Sayem, Haruna Moda, Grace Farhat and Walter Filho; formal analysis by Devathanthrige Senadeera, Abu Sayem, Grace Farhat and Walter Filho; and investigation by Devathanthrige Senadeera, Abu Sayem and Grace Farhat. Data curation was carried out by Abu Sayem, Grace Farhat and Walter Filho. The original draft was prepared by Devathanthrige Senadeera, Abu Sayem and Grace Farhat, with review and editing by all authors. Research administration was undertaken by Devathanthrige Senadeera, Abu Sayem, Haruna Moda, Grace Farhat and Walter Filho. 6.6 Acknowledgements I would also like to acknowledge the apparel factories that granted access to data collection and the participants who took part in the surveys. 6.7 Authors' information Devathanthrige Janaka Chamara Harshana SENADEERA 1 * Devathanthrige Janaka Chamara Harshana SENADEERA is a final-stage PhD candidate in Occupational Safety, Health, and Environment at Manchester Metropolitan University, UK. With over a decade of leadership in health and safety across manufacturing, agriculture, and telecommunications sectors, his research focuses on climate-change impact on workplace health and safety in Sri Lanka’s apparel industry. He has developed the HSCR Tool and Unified Climate Resilience Framework and contributed to peer-reviewed publications and international conferences. A Graduate Member of IOSH, Chamara also lectures in OHS and sustainability, integrating industry practice with academic rigour to improve safety standards and resilience across global industrial contexts. Abu Sadat Muhammad SAYEM 2 Dr Abu Sadat Muhammad Sayem is a Senior Lecturer and Project Lead of the AHRC-funded “Digital Fashion Network” at Manchester Fashion Institute, Manchester Metropolitan University. His research spans digital fashion innovation, smart textiles, and material sustainability. A Fellow of the Textile Institute, Royal Society of Arts, and Higher Education Academy, he earned his PhD in Fashion Technology from the University of Manchester. Dr Sayem sits on the UKRI Peer Review College and the Circular Fashion Network Plus Assessment Panel. He has prior industry experience in fashion sourcing and has held academic leadership roles in Bangladesh, fostering global research and education collaborations. Walter LEAL FILHO 3 Professor Walter Leal is Chair of Climate Change Management at Hamburg University of Applied Sciences and holds concurrent posts in the UK, Sweden, and Poland. A globally recognised scholar in sustainable development and climate change, he has authored over 800 publications, including the Encyclopedia of the UN SDGs, and serves as Editor-in-Chief of Discover Sustainability as well as multiple other journals and Springer book series. He is the founder of IUSDRP and ICCIRP and has coordinated over €84 million in research funding. Professor Leal has advised major global institutions and supervised over 120 students across disciplines linked to sustainability, climate resilience, and environmental health. Grace FARHAT 4 Dr Grace Farhat is a UK-registered dietitian (RD) and nutritionist (RNutr) with a PhD in Public Health Nutrition. She leads MSc programmes in Human Nutrition, Sport Nutrition, and Dietetics at Manchester Metropolitan University, where she also co-leads placements and admissions. Her research focuses on obesity, Type 2 diabetes remission, and the cardiometabolic effects of antioxidants, particularly pomegranate extract. A Senior Fellow of the Higher Education Academy, Dr Farhat is an active peer reviewer and guest editor for several international journals and serves as an external examiner across UK institutions in the field of nutrition and metabolic health. Haruna Musa MODA 5 Dr Haruna Moda is an Associate Professor and Head of the Department of Environmental Health and Safety at the University of Doha for Science and Technology, Qatar. He holds a PhD in Occupational Health and Safety from Glasgow Caledonian University and postgraduate qualifications from Manchester Metropolitan and Strathclyde Universities. A Chartered Member of IOSH and Fellow of the Higher Education Academy, his research focuses on climate change adaptation, occupational health among outdoor workers, e-waste management, and safety behaviours. He has published extensively, supervised multiple PhD students, and led consultancy and knowledge exchange projects across the UK, West Africa, and the Middle East. . References Chowdhury VR, Ahmed N, Lucky BP, Greeshma S. Bangladesh: a rising force in textile and garment production. In: Sadhna R, Kumar R, Memon H, Greeshma S, editors. Consumption and production in the textile and garment industry: SDGs and textiles. Singapore: Springer; 2024. p. 137–160. doi:10.1007/978-981-97-6577-5_7. United Nations Development Programme (UNDP). Making our future: new directions for human development in Asia and the Pacific. New York: UNDP; 2024. Available at: https://knowledge4policy.ec.europa.eu/publication/making-our-future-new-directions-human-development-asia-pacific_en. Accessed 31 December 2024. Mahmood, M.S.; Ruma, N.H.; Ahmed, T.; Nagai, Y. Exploring Suppliers’ Approaches toward Workplace Safety Compliance in the Global Garment Sector: From Bangladesh Perspective. Soc. Sci. 2021, 10, 90. doi.org/10.3390/socsci10030090 Ginige, K., Mendis, K. and Thayaparan, M. An assessment of structural measures for risk reduction of hydrometeorological disasters in Sri Lanka. Progress in Disaster Science. 2022;14:100232. doi.org/10.1016/j.pdisas.2022.100232 Akhter, S., Rutherford, S. & Chu, C. Exploring the system capacity to meet occupational health and safety needs: the case of the ready-made garment industry in Bangladesh. BMC Health Serv Res 19, 435 (2019). doi.org/10.1186/s12913-019-4291-y Nabi, M.H., Hasan, M., Chowdhury, A.T. et al. The impact of climate change on the lives and livelihoods of readymade garment (RMG) workers: an exploratory study in selected readymade garment factories in Bangladesh. BMC Public Health 23, 2292 (2023). doi.org/10.1186/s12889-023-17165-7 World Health Organization (WHO). Climate change and health. Geneva: WHO; 2023. Available at: https://www.who.int/news-room/fact-sheets/detail/climate-change-and-health Accessed 5 March 2025. Intergovernmental Panel on Climate Change (IPCC). Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the IPCC. Pörtner, H.-O., Roberts, D.C., Tignor, M., Poloczanska, E.S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A. and Rama, B. (eds.). Cambridge University Press, Cambridge, UK and New York, NY, USA, 3056 pp. 2022. Available at: https://doi.org/10.1017/9781009325844Central Bank of Sri Lanka. Annual economic review 2023. Colombo: CBSL; 2023. doi.org/10.1017/9781009325844 Central Bank of Sri Lanka. Annual economic review 2023. Colombo: CBSL; 2023. Available at: https://www.cbsl.gov.lk/en/publications/economic-and-financial-reports/annual-economic-review/annual-economic-review-2023. Accessed 31 December 2023. Ministry of Industries. Industrial data book 2023: textile and apparel sector. Colombo: Ministry of Industries; 2023. Available at: https://www.industry.gov.lk/web/wp-content/uploads/2024/11/Appreal-and-Texttile-2023.pdf. Accessed 18 March 2025. Sri Lanka Export Development Board (SLEDB). Industry capability report: apparel 2024. Colombo: SLEDB; 2022. Available at: https://www.srilankabusiness.com/ebooks/industry-capability-report-apparel-2024.pdf. Accessed 5 March 2025. Mani, M., Bandyopadhyay, S., Chonabayashi, S., Markandya, A. and Mosier, T. (South Asia’s Hotspots: The Impact of Temperature and Precipitation Changes on Living Standards: South Asia Development Matters. Washington, DC: The World Bank, 2018. doi.org/10.1596/978-1-4648-1155-5 World Bank Group, Asian Development Bank. Climate risk country profile: Sri Lanka. Washington, DC: World Bank Group & Asian Development Bank; 2021. Available at: http://www.worldbank.org. Accessed 21 July 2024 Alahacoon, N. and Edirisinghe, M. Spatial variability of rainfall trends in Sri Lanka from 1989 to 2019 as an indication of climate change. ISPRS International Journal of Geo-Information. 2021;10(2):84. doi.org/10.3390/ijgi10020084 Intergovernmental Panel on Climate Change (IPCC). Sections. In: Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Core Writing Team, Lee, H. and Romero, J. (eds.). IPCC, Geneva, Switzerland, pp. 35–115, 2023.doi.org/10.59327/IPCC/AR6-9789291691647. Krejcie RV, Morgan DW. Determining sample size for research activities. Educational and Psychological Measurement. 1970;30(3):607–610. Ministry of Industry and Commerce. Industrial development report 2023. Colombo: Ministry of Industry and Commerce; 2023. Available at: https://www.industry.gov.lk/web/wp-content/uploads/2024/06/3.-Annual-Performance-Report-2023_English.pdf. Accessed 19 March 2025. UN Women. Gender disparities and labour market challenges: the demand for women workers in Sri Lanka. New York: UN Women; 2022. Available at: https://asiapacific.unwomen.org/sites/default/files/2022-03/lk-Gender-Disparities-and-Labour-Market-Challenges_Full-Report.pdf. Accessed 26 March 2025. Azimi P, Allen J. Respiratory health harms often follow flooding: taking these steps can help. Harvard Health Publishing [Blog]. 9 November 2022. Available at: https://www.health.harvard.edu/blog/respiratory-health-harms-often-follow-flooding-taking-these-steps-can-help-202211092848. Accessed 3 July 2025. International Labour Organization (ILO). Ensuring safety and health at work in a changing climate: global report. Geneva: ILO; 2024. Available at: https://www.ilo.org/wcmsp5/groups/public/---ed_protect/---protrav/---safework/documents/publication/wcms_858792.pdf. Accessed 8 June 2024. Fisk, W.J., Eliseeva, E.A. & Mendell, M.J. Association of residential dampness and mold with respiratory tract infections and bronchitis: a meta-analysis. Environ Health 9, 72 (2010). doi.org/10.1186/1476-069X-9-72 Saatchi, M., et al. Communicable diseases outbreak after natural disasters: a systematic scoping review for incidence, risk factors and recommendations. Progress in Disaster Science. 2024;23:100334. doi.org/10.1016/j.pdisas.2024.100334 Tefera, Y., et al. Personal inhalable dust and endotoxin exposure among workers in an integrated textile factory. Journal of Occupational and Environmental Hygiene. 2020;17(9):415–421. doi.org/10.1080/19338244.2020.1743958 Moda, H.M., Filho, W.L. and Minhas, A. Impacts of climate change on outdoor workers and their safety: some research priorities. International Journal of Environmental Research and Public Health. 2019;16:3458. doi.org/10.3390/ijerph16183458 European Agency for Safety and Health at Work (EU-OSHA). Heat at work – guidance for workplaces. Bilbao: EU-OSHA; 2023. Available at: https://osha.europa.eu/sites/default/files/Heat-stress-guideguidance-for-workplaces_en.pdf (Accessed 12 January 2025). Centres for Disease Control and Prevention, National Institute for Occupational Safety and Health (NIOSH). Heat-related illnesses. Washington, DC: CDC/NIOSH; 2024. Available at: https://www.cdc.gov/niosh/heat-stress/about/illnesses.html (Accessed 3 January 2025). Bhat, M.A., Eraslan, F.N., Gedik, K. and Gaga, E.O. Impact of textile product emissions: toxicological considerations in assessing indoor air quality and human health. In: Malik, J.A. and Marathe, S. (eds.), Ecological and Health Effects of Building Materials. Cham: Springer; 2022. doi.org/10.1007/978-3-030-76073-1_27 Parvin, F., Islam, S., Akm, S.I. and Urmy, Z. A study on the solutions of environment pollutions and worker’s health problems caused by textile manufacturing operations. Biomedical Journal of Scientific & Technical Research. 2020;28:21831–21844. doi.org/10.26717/BJSTR.2020.28.004692. Thet Wai, T.W., et al. Assessment of respiratory dust exposure and lung functions among workers in textile mill (Thamine), Myanmar: a cross-sectional study. BMC Public Health. 2021;21:10712. doi.org/10.1186/s12889-021-10712-0 Wang, Y., Lee, H.S., Tan, K.W. and Chong, C.K. Projection of dengue fever transmissibility under climate change in South and Southeast Asian countries. PLoS Neglected Tropical Diseases. 2024;18:e0012158. doi.org/10.1371/journal.pntd.0012158. Ranasinghe, K., Liyanage, P., Pathirana, S. and Lakkumar, F. Breeding habitat distribution of medically important mosquitoes in Kurunegala, Gampaha, Kegalle, and Kandy districts of Sri Lanka and potential risk for disease transmission: a cross-sectional study. Journal of Tropical Medicine. 2020;2020:7915035. doi.org/10.1155/2020/7915035. Chathurangika, P., Premadasa, L.S., Perera, S.S.N. and De Silva, K. Determining dengue infection risk in the Colombo district of Sri Lanka by inferencing the genetic parameters of Aedes mosquitoes. BMC Infectious Diseases. 2024;24:944. doi.org/10.1186/s12879-024-09878-w. Gunathilaka, N., Chandradasa, M., Champika, L., Siriwardana, S. and Wijesooriya, L. Delayed anxiety and depressive morbidity among dengue patients in a multi-ethnic urban setting: first report from Sri Lanka. International Journal of Mental Health Systems. 2018;12:20. doi.org/10.1186/s13033-018-0202-6. Additional Declarations No competing interests reported. Supplementary Files ReaserchQuestionnaire.docx Cite Share Download PDF Status: Published Journal Publication published 20 Jan, 2026 Read the published version in BMC Public Health → Version 1 posted Editorial decision: Revision requested 21 Oct, 2025 Reviews received at journal 19 Oct, 2025 Reviews received at journal 19 Oct, 2025 Reviewers agreed at journal 13 Oct, 2025 Reviewers agreed at journal 12 Oct, 2025 Reviewers invited by journal 10 Oct, 2025 Editor assigned by journal 09 Sep, 2025 Editor invited by journal 09 Sep, 2025 Submission checks completed at journal 09 Sep, 2025 First submitted to journal 08 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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1","display":"","copyAsset":false,"role":"figure","size":101525,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eInterconnection of climate change-induced natural hazards (Source: Author)\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7539308/v1/7471e7ffbd051f6f7a080e43.png"},{"id":94366006,"identity":"bad85610-13ed-4afd-9a21-1016a700152c","added_by":"auto","created_at":"2025-10-27 13:09:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":156171,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePolicy implications for SMAMCs and regulatory authorities(Source: Author)\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7539308/v1/32f5df2fe044c20b8a5bbaa0.png"},{"id":101151905,"identity":"91fd47d4-96c1-48a4-bcbb-5a22b690fa60","added_by":"auto","created_at":"2026-01-26 16:07:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1085969,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7539308/v1/038bfb64-fc5e-438d-898c-64f1628c8d19.pdf"},{"id":94365456,"identity":"c64e2f12-a700-4bef-a072-05c8f3e1a586","added_by":"auto","created_at":"2025-10-27 13:09:15","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":43116,"visible":true,"origin":"","legend":"","description":"","filename":"ReaserchQuestionnaire.docx","url":"https://assets-eu.researchsquare.com/files/rs-7539308/v1/d70da429c8ede54a0ff9a954.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Workplace Health and Safety under Climate Stress in Sri Lankan Apparel SMEs","fulltext":[{"header":"Key Highlights ","content":"\u003cul type=\"disc\"\u003e\n \u003cli\u003eMandate climate-resilient occupational‑safety standards covering heat, flood, air‑quality and vector risks in small and medium apparel factories to protect worker health and sustain productivity.\u003c/li\u003e\n \u003cli\u003eOffer targeted grants and technical advice to retrofit ventilation, passive cooling and flood‑proofing, enabling resource-constrained SMEs to adopt cost-effective adaptations without losing competitiveness.\u003c/li\u003e\n \u003cli\u003eRequire real-time heat and air‑quality monitoring alongside staggered shifts and hydration breaks to reduce dehydration, cognitive fatigue and respiratory illness among apparel workers.\u003c/li\u003e\n \u003cli\u003eIntegrate occupational‑health rules with public vector‑control programmes to curb dengue in export zones, reducing absenteeism, safeguarding health and productivity, and supporting Sustainable Development Goals 8 and 13\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"1.0 INTRODUCTION","content":"\u003cp\u003eThe global apparel industry plays a critical role in economic development and employment generation, particularly in developing countries such as Bangladesh, Sri Lanka, Vietnam, and Ethiopia, where it accounts for a substantial share of exports and labour participation [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The apparel sector, given its highly labour-intensive nature, not only acts as an engine of economic growth but also supports millions of livelihoods, underpinning broader socio-economic stability in these nations. Consequently, the sustainability and resilience of this sector are paramount, especially against the backdrop of escalating environmental threats.\u003c/p\u003e\u003cp\u003eNevertheless, despite its considerable economic significance, the global apparel industry faces increasing exposure to climate-induced hazards such as floods, heatwaves, and droughts, which disrupt operations, damage infrastructure, and threaten worker health and productivity [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The vulnerability of the apparel industry to climate hazards emerges from multiple factors, including geographical susceptibility, inadequate infrastructure, limited resources allocated to climate adaptation, and systemic weaknesses in policy implementation [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. These factors intensify risks, especially in countries reliant on this sector for economic stability and employment continuity.\u003c/p\u003e\u003cp\u003eThe implications of these risks are particularly profound in labour-intensive environments, where workplace health and safety are intrinsically linked to environmental stability. The apparel industry\u0026rsquo;s workforce is predominantly concentrated in developing regions, where workers often experience precarious working conditions compounded by limited access to adequate health and safety provisions [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Factories, particularly small- and medium-scale enterprises, frequently lack the structural and operational capacity to effectively manage climate-induced occupational hazards, thereby significantly compromising worker well-being.\u003c/p\u003e\u003cp\u003eIn South Asia, apparel production countries such as Bangladesh, India, and Sri Lanka are especially reliant on this sector for economic growth, foreign exchange earnings, and employment generation. Bangladesh, for instance, exemplifies the critical role apparel exports play, comprising approximately 80% of its total exports [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. India and Sri Lanka similarly depend substantially on apparel manufacturing to drive economic growth and employment, yet all three countries grapple with persistent issues concerning workplace safety standards. Despite significant international attention following high-profile disasters, such as Bangladesh's Rana Plaza collapse, many factories across the region still face inadequate fire prevention systems, poor ventilation, and deficient emergency protocols [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThese shortcomings are particularly pronounced within small and medium-scale enterprises, which typically possess limited financial and technical capacities, thus exacerbating their susceptibility to climate-induced hazards. Smaller apparel factories, notably those operating in Bangladesh, frequently experience critical gaps in structural integrity, emergency exits, and air quality management, placing workers at continual risk of occupational hazards [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Enforcement of safety standards across the apparel sector remains inconsistent, influenced significantly by governance challenges such as corruption, regulatory fragmentation, and inadequate oversight, disproportionately impacting smaller and subcontracted facilities [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Thus, addressing climate-induced health and safety concerns within smaller apparel manufacturing firms demands focused policy intervention and sustained institutional support.\u003c/p\u003e\u003cp\u003eSeveral climate-induced hazards pose escalating threats to apparel-producing regions. Excessive heat, a widely documented hazard, considerably contributes to worker fatigue, dehydration, cognitive impairment, and significant productivity losses, particularly in factories lacking adequate thermal management systems. For example, research from Bangladesh and India highlights how increasing indoor temperatures directly correlate with higher incidents of heat stress among apparel workers, substantially reducing both worker well-being and operational efficiency [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These studies underscore the critical need for industry-specific adaptation measures to mitigate heat-related health risks.\u003c/p\u003e\u003cp\u003ePoor air quality within enclosed factory spaces constitutes another significant occupational hazard, exacerbated by climate variability. Emissions from textile dyes, chemical processing, and insufficient ventilation systems have been strongly associated with chronic respiratory diseases, cardiovascular ailments, and reduced overall worker health [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. While large-scale factories might employ sophisticated ventilation solutions, smaller factories frequently rely on rudimentary ventilation methods, which are insufficient to effectively mitigate air pollutants, especially during periods of elevated external temperatures or extreme weather conditions [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eVector-borne diseases such as dengue, malaria, and chikungunya represent an additional climate-induced hazard significantly impacting worker health in apparel-producing regions. Changing precipitation patterns, increasing temperatures, and inadequate drainage infrastructures intensify mosquito breeding, substantially heightening the risk of outbreaks. Increased rainfall events and prolonged periods of stagnant water, particularly common during monsoonal seasons, create ideal conditions for disease transmission. These vector-borne health threats disproportionately affect regions with inadequate environmental health infrastructure, posing severe risks to the health and productivity of the apparel workforce in Sri Lanka and similar countries in the region [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003e1.2 Climate Change and The Sri Lankan Apparel Industry\u003c/h2\u003e\u003cp\u003eSri Lanka\u0026rsquo;s apparel sector serves as a cornerstone of its industrial economy, contributing approximately 40% of the country\u0026rsquo;s total exports and generating over USD 5\u0026nbsp;billion in annual revenue [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Directly employing more than 350,000 workers, predominantly women, the sector also indirectly supports approximately 600,000 additional individuals through ancillary industries such as logistics, packaging, and services [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. This substantial socio-economic role underscores the critical importance of maintaining operational continuity, resilience, and worker safety within the industry, particularly under mounting climatic pressures.\u003c/p\u003e\u003cp\u003eThe majority of apparel production in Sri Lanka occurs within small and medium-scale apparel manufacturing companies (SMAMCs), which are notably vulnerable to climate hazards due to several systemic challenges. These enterprises often function within older infrastructures with minimal adaptive capacities, lacking modern heating, ventilation, and air-conditioning (HVAC) systems [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Furthermore, limited financial and technical resources hinder their capacity to implement robust health and safety measures, significantly amplifying their vulnerability to climate-induced occupational hazards [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSri Lanka\u0026rsquo;s climatic conditions are changing rapidly, with projections indicating a mean annual temperature rise of between 1.0 and 1.5\u0026deg;C by 2050, with pronounced impacts expected particularly in the northern and eastern provinces [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Concurrently, monsoonal rainfall patterns have become increasingly unpredictable, exacerbating the frequency and intensity of floods and droughts within shorter intervals [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. These climatic shifts directly threaten apparel factory operations, impair infrastructure stability, disrupt supply chains, and significantly compromise worker health.\u003c/p\u003e\u003cp\u003eSmall and medium-scale enterprises within Sri Lanka\u0026rsquo;s apparel sector experience disproportionately severe impacts due to their characteristic operational environments, which include limited air circulation, high-density working conditions, and insufficient capacity to manage environmental health risks [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. While large-scale apparel firms typically benefit from international partnerships and greater financial flexibility to implement comprehensive climate-adaptive strategies, SMAMCs lack such resources and institutional support [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Consequently, they are often neglected by policy frameworks and broader industry interventions, representing a critical oversight given their substantial contribution to sector-wide production and employment.\u003c/p\u003e\u003cp\u003eDespite increasing evidence of these vulnerabilities, existing research and policy efforts in Sri Lanka predominantly focus on large-scale, export-oriented factories, marginalising the specific and heightened risks faced by SMAMCs. The continued neglect of SMAMCs undermines the overall resilience of Sri Lanka\u0026rsquo;s apparel sector, posing risks to worker safety, economic output, and the industry's global competitiveness. The urgency to bridge this policy and research gap is underscored by the dual imperatives of safeguarding worker health and maintaining economic stability in the face of escalating climate hazards.\u003c/p\u003e\u003cp\u003eAccordingly, this study aims explicitly to examine the impacts of climate-induced occupational hazards on worker health and workplace safety within SMAMCs located in Sri Lanka\u0026rsquo;s Biyagama and Katunayake Export Processing Zones. It seeks to identify and analyse the most prevalent climate hazards faced by these enterprises, assess their specific health implications, and critically evaluate the effectiveness of current safety management practices in mitigating climate-related risks. Through targeted analysis of an often-overlooked segment of the apparel industry, this research will provide essential evidence to inform policymakers, industry stakeholders, and health professionals.\u003c/p\u003e\u003cp\u003eIn doing so, the study seeks to contribute meaningfully to the development of climate-resilient workplace strategies in alignment with global sustainability targets, specifically the United Nations Sustainable Development Goals: Goal 8 (Decent Work and Economic Growth) and Goal 13 (Climate Action). By foregrounding the unique challenges of Sri Lanka's SMAMCs within broader regional and global discourses on climate resilience, the research underscores both the necessity and feasibility of integrating climate considerations into workplace health and safety governance frameworks, ultimately aiming to foster sustainable, safe, and resilient working environments in the face of ongoing climate change.\u003c/p\u003e\u003c/div\u003e"},{"header":"2.0 MATERIALS AND METHODS","content":"\u003cp\u003eThis study was conducted within the Sri Lankan apparel manufacturing sector, focusing on small and medium-scale apparel manufacturing companies (SMAMCs) located in the Biyagama and Katunayake Free Trade Zones. These zones collectively host around 200 apparel companies and employ approximately 100,000 workers, forming the basis of the study population. Data collection was carried out over six months, from 4 October 2023 to 27 March 2024, allowing the study to capture seasonal and environmental variations relevant to climate-related workplace risks.\u003c/p\u003e\u003cp\u003eA mixed-methods research design was adopted to investigate how climate-induced hazards affect workplace health and safety in SMAMCs. The quantitative component comprised a structured survey designed and developed specifically for this study to assess workers\u0026rsquo; exposure to climate-related hazards and associated health risks. To complement and deepen these findings, open-ended questions were integrated within the survey instrument, enabling the collection of qualitative responses for thematic analysis. This methodological integration allowed for a more comprehensive understanding of both measurable trends and individual perceptions.\u003c/p\u003e\u003cp\u003eA total of 384 employees participated in the survey. The sample size was determined using the Krejcie and Morgan [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] table, ensuring a 95% confidence level and a 5% margin of error. Participants included a diverse range of roles such as team members, multi-skilled operators, assistant team leaders, team leaders, and sectional heads, capturing variation in workplace exposure and responsibilities. While gender was not a selection criterion, it is well established that over 80% of the Sri Lankan apparel workforce is female, with more than 300,000 women employed directly [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Observations during site visits by the first author confirmed the predominance of women on production floors, aligning with national employment patterns [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The primary focus of this study was on the interaction between climate change and workplace health and safety, rather than gender-based analysis.\u003c/p\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Data Collection Methods\u003c/h2\u003e\u003cp\u003eTo assess current health and safety risks in the context of climate hazards, a pre-tested and pilot-validated questionnaire was used. It comprised both closed-ended (quantitative) and open-ended (qualitative) items. The survey was conducted in person within selected factories, targeting employees aged 18 and above with a minimum of two years\u0026rsquo; experience. This ensured participants had sufficient exposure to factory operations and climatic variations to meaningfully contribute to the study.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Statistical and Qualitative Analysis Techniques\u003c/h2\u003e\u003cp\u003eThe quantitative data were analysed using IBM SPSS version 29 (Armonk, New York, USA). Descriptive statistics were used to summarise demographic attributes and key safety-related variables. Inferential analysis was conducted using Pearson\u0026rsquo;s Chi-square test to identify associations between categorical variables such as job role, work experience, and perceived health risks. To assess internal reliability, Cronbach\u0026rsquo;s Alpha was applied for Likert-type items, while the Kuder-Richardson Formula 20 (KR-20) was used for binary items, confirming the validity and consistency of the dataset.\u003c/p\u003e\u003cp\u003eThe qualitative responses from open-ended survey questions were processed using NVivo version 15 (Denver, Colorado, USA) for thematic analysis. Coding was performed based on key phrases and recurrent terminology to identify dominant themes and sub-themes. This enabled the development of a thematic framework reflecting climate change-induced hazards. The integration of these qualitative insights with the quantitative findings provided a more nuanced understanding of how climate change is influencing occupational health and safety dynamics in Sri Lanka\u0026rsquo;s apparel manufacturing context.\u003c/p\u003e\u003c/div\u003e"},{"header":"3.0 RESULTS","content":"\u003cp\u003eThe analysis quantified the impacts of four major climate-related hazards on employees in Sri Lankan SMAMCs. Adverse weather events such as floods, cyclones, landslides, lightning, and strong winds were reported by 80.73% of respondents. Excessive heat impacted 81.25%, air pollution 44.53%, and mosquito-borne diseases 83.07% (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e01\u003c/span\u003e). Pearson chi-square tests confirmed the statistical significance of these impacts: adverse weather (χ\u0026sup2; = 28.380, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), heat waves (χ\u0026sup2; = 29.790, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), air pollution (χ\u0026sup2; = 36.050, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and mosquito-borne diseases (χ\u0026sup2; = 7.280, p\u0026thinsp;\u0026lt;\u0026thinsp;0.007). The Phi values indicate moderate to strong associations: 0.272 (adverse weather), 0.279 (excessive heat), 0.306 (air pollution), and 0.138 (mosquito-borne diseases).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 01\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eStatistical significance of main climate change-induced natural hazards\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClimate Hazard\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePercentage Affected (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePearson Chi-Square\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP-Value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePhi Value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdverse Weather Conditions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e80.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e28.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.272\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExcessive Heat\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e81.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.279\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAir Pollution\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e44.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e36.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.306\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMosquito-borne Diseases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e83.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.138\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWhen detailing each climate change-induced hazard following risks and impacts have been experienced by the participants in their workplaces due to respective climate change-induced hazards.\u003c/p\u003e\u003cp\u003eA.) Adverse Weather Conditions\u003c/p\u003e\u003cp\u003eAdverse weather conditions were linked to several health issues among SMAMCs employees. Reported symptoms included respiratory problems (75.52%), asthma (77.08%), diarrhoea (47.40%), sinus issues (73.70%), and throat infections (81.25%). Mental health effects included stress (29.95%) and tension (26.82%). Pearson chi-square tests confirmed statistically substantial associations (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e02\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 02\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cb\u003eStatistical significance of adverse weather-related health impacts\u003c/b\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealth Impact\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePercentage Affected (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePearson Chi-Square\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP-Value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePhi Value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRespiratory Issues\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e75.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.121\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAsthma Symptoms\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e77.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.111\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiarrhoea\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e47.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.133\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSinus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e73.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.203\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThroat Infections\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e81.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.121\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStress\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e29.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.204\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAnalysis of qualitative responses identified two primary themes relating to the impacts of flooding on workplace health and safety in Sri Lanka\u0026rsquo;s SMAMCs:\u003c/p\u003e\u003cp\u003ePhysical Safety Risks: Workers frequently reported experiencing physical injuries due to unsafe conditions exacerbated by flooding events. Commonly described hazards included slippery communal areas, structural instability, and falling debris from compromised building infrastructure. One participant highlighted the immediate risk associated with wet floors, stating, \u0026ldquo;I fell near the canteen area after the rain, the floor was wet and no sign.\u0026rdquo; Another respondent detailed structural failure, noting, \u0026ldquo;The wall behind the packing section cracked and part fell during the last flood.\u0026rdquo; These examples underscore how inadequate maintenance and poor structural integrity significantly elevate physical injury risks during adverse weather conditions.\u003c/p\u003e\u003cp\u003eFlood-related Health Issues: Participants also described a range of health complications arising from flood exposure, notably sore eyes, ringworm, hepatitis, respiratory infections, and flu-like symptoms. Workers commonly associated these illnesses with contact with contaminated floodwater and prolonged exposure to cold and damp conditions inside factories. One respondent noted, \u0026ldquo;When it rains, we walk through the flood to transport, later we get throat pain and fever.\u0026rdquo; Another participant highlighted respiratory health risks linked to poor infrastructure, stating, \u0026ldquo;Windows are not properly fixed, mist comes, we get breathing difficulties while raining, later we get sick.\u0026rdquo; Gastrointestinal issues were also prevalent, particularly during the monsoon season, as reflected by another worker's comment: \u0026ldquo;Most employees experience loose motion issues after the flood season due to well water usage.\u0026rdquo;\u003c/p\u003e\u003cp\u003eB.) Excessive Heat\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e03\u003c/span\u003e illustrates the substantial health risks posed by excessive heat in Sri Lanka\u0026rsquo;s SMAMCs, with the majority of participants reporting adverse symptoms: 89.58% reported excessive sweating, 85.67% reported headaches, 84.89% felt faint, 89.84% developed heat rashes, and 80.46% reported dehydration. Additionally, 85.41% reported reduced focus, 84.89% reported extreme fatigue, and 60.15% encountered workplace hazards. Chi-square analysis confirmed statistically substantial associations across all symptoms (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with Phi values (χ\u0026sup2; ) ranging from 0.336 to 0.553, indicating moderate to strong correlations.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 03\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eStatistical significance of excessive heat-induced risks.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRisk Type\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePercentage Affected (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChi-Square\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP-Value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePhi Value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExcessive Sweating\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e89.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e69.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.426\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSevere Headache\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e85.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e53.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.375\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFeeling Faintness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e84.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e77.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.450\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeat Rash\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e89.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e72.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.553\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDehydration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e80.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e43.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.336\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReduced Focus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e85.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e75.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.444\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExtreme Fatigue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e84.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e75.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.443\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWorkplace Hazards\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e60.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e53.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.372\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eQualitative responses, participants described multiple physical health issues directly attributed to working in excessively hot conditions. Commonly reported symptoms included extreme fatigue, reduced physical strength, persistent tiredness, and energy depletion during work shifts. Workers frequently mentioned physical ailments such as sore eyes, cuts and grazes, insomnia, and a notable loss of appetite. One participant specifically stated, \u0026ldquo;Sore eyes are spreading during the hot season in the factory.\u0026rdquo; Additionally, several workers highlighted dermatological problems, describing episodes of skin irritation, blisters, and rashes exacerbated by heat exposure. As one worker explained, \u0026ldquo;I keep scratching my calf on hot days, and then the rash turns into blisters.\u0026rdquo;\u003c/p\u003e\u003cp\u003eWorkers further reported that fatigue and reduced concentration due to heat significantly increased the risk of workplace injuries, particularly needle-prick incidents among sewing operators. A worker described her experience: \u0026ldquo;I pricked my finger twice last week, it happens when we are too tired and sweaty.\u0026rdquo; Manual handling activities in high-temperature environments were also associated with fainting episodes and headaches, symptoms frequently experienced by employees across different factory departments. Moreover, access to drinking water was often limited, exacerbating dehydration and related symptoms.\u003c/p\u003e\u003cp\u003eIn addition to physical issues, workers reported considerable mental health and cognitive challenges linked to excessive heat exposure. Commonly mentioned mental health effects included difficulty concentrating on tasks, reduced motivation, and feelings of irritability directed both at themselves and their colleagues. One participant succinctly described these emotional impacts, noting, \u0026ldquo;When it\u0026rsquo;s too hot, I get angry.\u0026rdquo; Such emotional responses highlight the profound influence that sustained heat exposure has on workers' psychological well-being and workplace interpersonal dynamics.\u003c/p\u003e\u003cp\u003eC.) Indoor Air Pollution\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e04\u003c/span\u003e highlights the substantial health impacts of air pollution on SMAMCs employees, particularly respiratory issues. Participants reported coughing (95.05%), other respiratory problems (94.79%), allergies (94.01%), shortness of breath (70.31%), and eye diseases (70.57%). Pearson chi-square tests confirmed statistically substantial associations for shortness of breath (χ\u0026sup2; = 21.779, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and eye diseases (χ\u0026sup2; = 18.950, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with moderate Phi values of 0.238 and 0.222, respectively. Other symptoms, despite high prevalence, did not show statistical significance.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 04\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eStatistical significance of air pollution-related health impacts.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealth Impact\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePercentage Affected (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePearson Chi-Square\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP-Value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePhi Value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCoughing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e95.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.358\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.244\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0595\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eShortness of Breath\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e70.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e21.779\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.238\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRespiratory Issues Symptoms\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e94.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.258\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.071\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.092\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAllergies\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e94.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.941\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.332\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.050\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEye Diseases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e70.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.222\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eQualitative responses, participants frequently reported respiratory health concerns directly associated with their work environment, often beginning shortly after joining the apparel industry. Commonly reported symptoms included wheezing, asthma-like conditions, and chronic breathing difficulties. One respondent clearly articulated this health impact, stating, \u0026ldquo;I never had asthma before, but now I wheeze almost every day after work.\u0026rdquo; Participants further emphasised that respiratory discomfort intensified on hot days due to increased air pollution from surrounding industrial activities. One worker described this scenario, stating, \u0026ldquo;When the heat is high, the outside smoke comes in, we can\u0026rsquo;t breathe properly and feel tired by noon.\u0026rdquo; These responses illustrate how industrial emissions, compounded by climatic conditions, significantly compromise respiratory health among apparel workers.\u003c/p\u003e\u003cp\u003eWorkers consistently highlighted eye and skin-related health problems caused by poor indoor air quality, particularly in factories reliant on natural ventilation systems. Eye irritation, commonly referred to by workers as \u0026ldquo;sore eyes\u0026rdquo;, was frequently attributed to the influx of dust through open windows during the dry season. One participant noted, \u0026ldquo;The dust gets in through the windows, my eyes turn red and start feeling burning.\u0026rdquo; Workers also described allergic responses, including conjunctivitis and skin irritations, which reportedly worsened when handling particular fabrics under hot and dusty conditions. Another respondent remarked, \u0026ldquo;Some materials make my skin itch and turn red; it\u0026rsquo;s worse when it\u0026rsquo;s hot and the place is dusty.\u003c/p\u003e\u003cp\u003eD.) Mosquito-Borne Diseases\u003c/p\u003e\u003cp\u003eStudy highlights a significant prevalence of Dengue, affecting 10.68% of the population over the past five years, emphasising its extensive health implications. Statistical analysis with a Pearson chi-square result of r\u0026thinsp;=\u0026thinsp;8.356, p\u0026thinsp;\u0026lt;\u0026thinsp;0.003, shows a statistically significant link between Dengue and Environmental Factors. The conditions conducive to mosquito breeding, with a Phi value of 0.148, indicate a weak positive relationship.\u003c/p\u003e\u003cp\u003eQualitative responses, participants consistently noted an increased presence of mosquitoes and insects during hot and dry periods, causing considerable discomfort and negatively impacting their ability to concentrate and maintain productivity at work. One participant explained, \u0026ldquo;In the hot season, the mosquitoes don\u0026rsquo;t let us work, they keep biting.\u0026rdquo; Such conditions often resulted in visible skin irritations, rashes, and bite marks on workers' limbs. Another worker remarked, \u0026ldquo;We get rashes and marks on our arms and legs after bites.\u0026rdquo; The frequent scratching and irritation from insect bites often led to secondary health complications, such as open wounds, increased risk of infection, and subsequent absenteeism. Employees expressed particular concern regarding these complications and the implications for their longer-term health. One participant described a specific incident, stating, \u0026ldquo;I had to see the doctor because the bite turned into a sore, and I had to take leave.\u0026rdquo;\u003c/p\u003e"},{"header":"4.0 DISCUSSION AND CONCLUSIONS","content":"\u003cp\u003eThis study examined the multifaceted impacts of climate change-induced hazards flooding, excessive heat, indoor air pollution, and mosquito-borne diseases, on worker health, safety, and productivity within Sri Lanka\u0026rsquo;s small and medium apparel manufacturing companies (SMAMCs). The findings demonstrate direct, substantial, and cascading effects, highlighting a critical policy gap and emphasising the urgency of implementing integrated, climate-resilient workplace safety strategies.\u003c/p\u003e\u003cp\u003eAdverse weather, notably flooding, emerged as a significant threat to worker health, with respiratory issues (75.52%), asthma (77.08%), diarrhoea (47.40%), and throat infections (81.25%) prominently reported. These findings align closely with global research demonstrating that flooding exacerbates respiratory conditions due to mould proliferation and damp indoor environments [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Additionally, psychological stress linked to extreme weather (29.95%) resonates with broader studies that underline mental health risks following floods [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The frequent physical injuries and illnesses (such as hepatitis, ringworm, and sore eyes) reported by respondents reflect the vulnerability of SMAMCs to infrastructure deficiencies and inadequate maintenance during floods, echoing findings by Saatchi et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] in similar industrial contexts. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e01\u003c/span\u003e illustrates this cascading nexus, confirming Tefera et al.\u0026rsquo;s [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] observation that a single climatic trigger can amplify multiple occupational risks. The net effect is a multi-hazard environment where traditional single-risk controls offer diminishing returns.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eHeat exposure also posed significant health risks, notably excessive sweating (89.58%), severe headaches (85.67%), and dehydration (80.46%), correlating closely with international evidence from tropical manufacturing environments, as reported by Moda et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], ILO [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and EU-OSHA [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. These impacts are compounded by cognitive and psychological burdens such as reduced concentration (85.41%) and extreme fatigue (84.89%), which significantly heighten occupational injury risks, confirming previous findings from the NIOSH [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] and EU-OSHA [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Limited workplace hydration access intensified these effects, underlining a crucial policy oversight requiring immediate intervention.\u003c/p\u003e\u003cp\u003eIndoor air pollution, particularly severe in factories reliant on natural ventilation, was associated with widespread respiratory and ocular irritation. Although coughing (95.05%) and general respiratory discomfort (94.79%) were prevalent yet statistically inconclusive, eye diseases showed significant associations (70.57%). These results are consistent with previous research linking particulate matter and industrial emissions to occupational eye and skin irritations [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Respondents\u0026rsquo; qualitative feedback specifically highlighted the exacerbation of respiratory and ocular symptoms on hot days, supporting existing studies that associate poor ventilation with deteriorating worker health in textiles [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMosquito-borne diseases, particularly dengue fever, were identified as a rising occupational hazard, correlating statistically with increased mosquito breeding conditions due to climatic variability. Dengue occurrences among workers substantiate earlier evidence highlighting climate-driven vector expansion [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Outbreaks observed in industrially dense regions, such as Colombo and Kurunegala, reinforce the need for targeted environmental surveillance and proactive vector control measures [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Additionally, the mental health implications associated with dengue and related infectious diseases align with findings from Gunathilaka et al. [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], reinforcing the importance of comprehensive, climate-sensitive occupational health strategies.\u003c/p\u003e\u003cp\u003eImportantly, hazards were not isolated. Flood damage to buildings increased mould exposure and impeded ventilation, compounding heat stress and dust inhalation; heat, in turn, volatilised chemicals, aggravating respiratory symptoms; and both flooding and heat drove mosquito abundance.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Policy Implications for SMAMCs and Regulatory Authorities\u003c/h2\u003e\u003cp\u003eThis study provides critical insights for immediate policy action (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e02\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e Firstly, the pronounced health impacts of flooding necessitate updating national occupational safety guidelines to incorporate specific flood-resilience measures. Regulators should mandate regular structural assessments, improved drainage systems, and emergency response training, explicitly tailored to the vulnerabilities of SMAMCs. A clear lesson for policymakers, factory owners, and Factory Inspecting Engineers (FIEs) is to prioritise infrastructure upgrades as part of broader climate adaptation investments, as recommended by the ILO [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eRegarding excessive heat, the findings underline an urgent policy need to enforce comprehensive heat-management strategies. Practical policy measures include mandated provision of accessible drinking water, scheduled rest breaks during peak heat hours, and adoption of affordable cooling technologies such as evaporative coolers, supported by grant schemes. Integration of heat-stress metrics into routine factory inspections and labour compliance audits could significantly mitigate occupational heat risks, aligning with global best practices outlined by NIOSH [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] and EU-OSHA [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe pervasive issue of indoor air pollution highlights the need for regulatory frameworks promoting improved ventilation standards in SMAMCs. Policy recommendations should encompass minimum indoor air quality thresholds, incentivisation of dust-extraction technology investments, and training initiatives promoting awareness of occupational respiratory and ocular health risks. Enhanced enforcement of existing air quality and environmental regulations, particularly in industrially dense zones such as Katunayake and Biyagama, is essential to reduce exposure risks highlighted by workers.\u003c/p\u003e\u003cp\u003eFinally, the rising incidence of dengue underscores the necessity for systematic vector-control audits during periods of drought and rainfall variability. Factory management should be mandated to conduct routine environmental surveillance and vector control measures, supported by clear regulatory guidance and periodic health inspections by Public Health Inspectors. Such integrated policy initiatives are essential to safeguarding worker health amidst evolving climate threats.\u003c/p\u003e\u003cp\u003eWhile providing comprehensive insights, this study acknowledges limitations inherent in its methodology. The cross-sectional nature restricts causal inference and longitudinal tracking of health outcomes. Additionally, although the sample was statistically robust, recall bias and self-reporting limitations must be considered. Nonetheless, qualitative data triangulation and statistical significance across multiple health dimensions confirm the robustness of findings. The insights presented are transferable primarily to similarly structured Low- and Middle-Income Countries' (LMIC) apparel sectors but warrant cautious extrapolation beyond industrial contexts facing comparable climatic and infrastructural challenges.\u003c/p\u003e\u003cp\u003eFuture research should adopt longitudinal designs, allowing comprehensive tracking of climate-induced occupational health trends and the effectiveness of implemented policy interventions. Cost\u0026ndash;benefit analyses evaluating engineering controls such as improved ventilation systems, flood-proofing infrastructures, and cooling technologies would substantially strengthen the business case for climate resilience investments in the apparel sector. Cross-national comparisons could further provide insights into regional variations in policy effectiveness, adaptation strategies, and regulatory frameworks, enabling the identification of best practices and knowledge transfer opportunities. Additionally, integrating qualitative assessments with quantitative models would enhance understanding of worker perceptions and organisational behaviour, ensuring that interventions are both scientifically robust and socially acceptable.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003e6.1 Ethics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eEthical approval for this study was obtained from the Manchester Metropolitan University Health and Education Ethics Committee on 30 June 2023 (Ethos application number 45145). All participants received a participant information sheet outlining the study’s purpose, procedures, potential risks, and benefits. Participant consent was obtained prior to data collection. Participation was entirely voluntary, and all data were collected anonymously to ensure confidentiality.\u003c/p\u003e\n\u003ch2\u003e6.2 Consent for publication\u003c/h2\u003e\n\u003cp\u003eAll participants provided written informed consent for publication of the study findings. Participation was voluntary, data was collected anonymously, and confidentiality and privacy were fully safeguarded.\u003c/p\u003e\n\u003ch2\u003e6.3 Availability of data and materials\u003c/h2\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author (DS), upon reasonable request.\u003c/p\u003e\n\u003ch2\u003e6.4 Competing interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003e6.5 Funding\u003c/h2\u003e\n\u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003ch2\u003e6.6 Authors' contributions\u003c/h2\u003e\n\u003cp\u003eConceptualisation was undertaken by Devathanthrige Senadeera and Abu Sayem. Methodology was developed by Devathanthrige Senadeera, Abu Sayem, Haruna Moda, Grace Farhat and Walter Filho; formal analysis by Devathanthrige Senadeera, Abu Sayem, Grace Farhat and Walter Filho; and investigation by Devathanthrige Senadeera, Abu Sayem and Grace Farhat. Data curation was carried out by Abu Sayem, Grace Farhat and Walter Filho. The original draft was prepared by Devathanthrige Senadeera, Abu Sayem and Grace Farhat, with review and editing by all authors. Research administration was undertaken by Devathanthrige Senadeera, Abu Sayem, Haruna Moda, Grace Farhat and Walter Filho.\u003c/p\u003e\n\u003ch2\u003e6.6 Acknowledgements\u003c/h2\u003e\n\u003cp\u003eI would also like to acknowledge the apparel factories that granted access to data collection and the participants who took part in the surveys.\u003c/p\u003e\n\u003ch2\u003e6.7 Authors' information\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eDevathanthrige Janaka Chamara Harshana SENADEERA\u003csup\u003e1\u003c/sup\u003e*\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDevathanthrige Janaka Chamara Harshana SENADEERA is a final-stage PhD candidate in Occupational Safety, Health, and Environment at Manchester Metropolitan University, UK. With over a decade of leadership in health and safety across manufacturing, agriculture, and telecommunications sectors, his research focuses on climate-change impact on workplace health and safety in Sri Lanka’s apparel industry. He has developed the HSCR Tool and Unified Climate Resilience Framework and contributed to peer-reviewed publications and international conferences. A Graduate Member of IOSH, Chamara also lectures in OHS and sustainability, integrating industry practice with academic rigour to improve safety standards and resilience across global industrial contexts.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbu Sadat Muhammad SAYEM\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDr Abu Sadat Muhammad Sayem is a Senior Lecturer and Project Lead of the AHRC-funded “Digital Fashion Network” at Manchester Fashion Institute, Manchester Metropolitan University. His research spans digital fashion innovation, smart textiles, and material sustainability. A Fellow of the Textile Institute, Royal Society of Arts, and Higher Education Academy, he earned his PhD in Fashion Technology from the University of Manchester. Dr Sayem sits on the UKRI Peer Review College and the Circular Fashion Network Plus Assessment Panel. He has prior industry experience in fashion sourcing and has held academic leadership roles in Bangladesh, fostering global research and education collaborations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWalter LEAL FILHO\u003csup\u003e3\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eProfessor Walter Leal is Chair of Climate Change Management at Hamburg University of Applied Sciences and holds concurrent posts in the UK, Sweden, and Poland. A globally recognised scholar in sustainable development and climate change, he has authored over 800 publications, including the Encyclopedia of the UN SDGs, and serves as Editor-in-Chief of Discover Sustainability as well as multiple other journals and Springer book series. He is the founder of IUSDRP and ICCIRP and has coordinated over €84 million in research funding. Professor Leal has advised major global institutions and supervised over 120 students across disciplines linked to sustainability, climate resilience, and environmental health.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGrace FARHAT\u003csup\u003e4\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDr Grace Farhat is a UK-registered dietitian (RD) and nutritionist (RNutr) with a PhD in Public Health Nutrition. She leads MSc programmes in Human Nutrition, Sport Nutrition, and Dietetics at Manchester Metropolitan University, where she also co-leads placements and admissions. Her research focuses on obesity, Type 2 diabetes remission, and the cardiometabolic effects of antioxidants, particularly pomegranate extract. A Senior Fellow of the Higher Education Academy, Dr Farhat is an active peer reviewer and guest editor for several international journals and serves as an external examiner across UK institutions in the field of nutrition and metabolic health.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHaruna Musa MODA\u003csup\u003e5\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDr Haruna Moda is an Associate Professor and Head of the Department of Environmental Health and Safety at the University of Doha for Science and Technology, Qatar. He holds a PhD in Occupational Health and Safety from Glasgow Caledonian University and postgraduate qualifications from Manchester Metropolitan and Strathclyde Universities. A Chartered Member of IOSH and Fellow of the Higher Education Academy, his research focuses on climate change adaptation, occupational health among outdoor workers, e-waste management, and safety behaviours. He has published extensively, supervised multiple PhD students, and led consultancy and knowledge exchange projects across the UK, West Africa, and the Middle East.\u003c/p\u003e\n\u003cp\u003e.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChowdhury VR, Ahmed N, Lucky BP, Greeshma S. Bangladesh: a rising force in textile and garment production. In: Sadhna R, Kumar R, Memon H, Greeshma S, editors. Consumption and production in the textile and garment industry: SDGs and textiles. Singapore: Springer; 2024. p. 137\u0026ndash;160. doi:10.1007/978-981-97-6577-5_7.\u003c/li\u003e\n\u003cli\u003eUnited Nations Development Programme (UNDP). Making our future: new directions for human development in Asia and the Pacific. New York: UNDP; 2024. Available at: https://knowledge4policy.ec.europa.eu/publication/making-our-future-new-directions-human-development-asia-pacific_en. 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Cham: Springer; 2022. doi.org/10.1007/978-3-030-76073-1_27\u003c/li\u003e\n\u003cli\u003eParvin, F., Islam, S., Akm, S.I. and Urmy, Z. A study on the solutions of environment pollutions and worker\u0026rsquo;s health problems caused by textile manufacturing operations. Biomedical Journal of Scientific \u0026amp; Technical Research. 2020;28:21831\u0026ndash;21844. doi.org/10.26717/BJSTR.2020.28.004692.\u003c/li\u003e\n\u003cli\u003eThet Wai, T.W., et al. Assessment of respiratory dust exposure and lung functions among workers in textile mill (Thamine), Myanmar: a cross-sectional study. BMC Public Health. 2021;21:10712. doi.org/10.1186/s12889-021-10712-0\u003c/li\u003e\n\u003cli\u003eWang, Y., Lee, H.S., Tan, K.W. and Chong, C.K. Projection of dengue fever transmissibility under climate change in South and Southeast Asian countries. PLoS Neglected Tropical Diseases. 2024;18:e0012158. doi.org/10.1371/journal.pntd.0012158.\u003c/li\u003e\n\u003cli\u003eRanasinghe, K., Liyanage, P., Pathirana, S. and Lakkumar, F. Breeding habitat distribution of medically important mosquitoes in Kurunegala, Gampaha, Kegalle, and Kandy districts of Sri Lanka and potential risk for disease transmission: a cross-sectional study. Journal of Tropical Medicine. 2020;2020:7915035. doi.org/10.1155/2020/7915035.\u003c/li\u003e\n\u003cli\u003eChathurangika, P., Premadasa, L.S., Perera, S.S.N. and De Silva, K. Determining dengue infection risk in the Colombo district of Sri Lanka by inferencing the genetic parameters of Aedes mosquitoes. BMC Infectious Diseases. 2024;24:944. doi.org/10.1186/s12879-024-09878-w.\u003c/li\u003e\n\u003cli\u003eGunathilaka, N., Chandradasa, M., Champika, L., Siriwardana, S. and Wijesooriya, L. Delayed anxiety and depressive morbidity among dengue patients in a multi-ethnic urban setting: first report from Sri Lanka. International Journal of Mental Health Systems. 2018;12:20. doi.org/10.1186/s13033-018-0202-6.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Climate Change Impacts, Workplace Health and Safety, Sri Lankan Apparel Industry, Small and Medium Manufacturing Companies","lastPublishedDoi":"10.21203/rs.3.rs-7539308/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7539308/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eClimate change poses escalating risks to labour‑intensive industries in South Asia. This mixed‑methods study assessed how climate‑related hazards affect the health, safety and productivity of workers in Sri Lankan small‑ and medium‑scale apparel manufacturing companies (SMAMCs). A survey of 384 employees in Biyagama and Katunayake Export Processing Zones captured quantitative data on exposure to excessive heat, flooding, indoor air pollution and mosquito‑borne diseases, and elicited qualitative accounts of workplace experiences. Heat waves and high humidity were the most pervasive stressors: 81 % of respondents reported heat stress, with headaches, dehydration, and diminished concentration frequently linked to needle‑prick injuries. Flood events damaged infrastructure and heightened respiratory, gastrointestinal and dermatological illnesses, while inadequate ventilation compounded air‑quality problems; 95 % of workers complained of persistent coughing. Dengue incidence over the preceding five years reached 11 %, reflecting expanding vector habitats. Chi‑square analysis confirmed statistically significant associations between each hazard and adverse health outcomes. The study underscores the need for integrated adaptation measures, improved ventilation, low‑cost cooling, drainage upgrades and systematic vector control, supported by enforceable regulations and targeted financial assistance. Enhancing climate resilience in SMAMCs is essential for safeguarding worker wellbeing and sustaining Sri Lanka’s export competitiveness, while contributing to global goals on decent work and climate action targets.\u003c/p\u003e","manuscriptTitle":"Workplace Health and Safety under Climate Stress in Sri Lankan Apparel SMEs","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-24 20:12:52","doi":"10.21203/rs.3.rs-7539308/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-21T09:31:19+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-19T13:40:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-19T10:35:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"242920791024252206451790965715928158132","date":"2025-10-13T06:35:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"74644781863464891943963045848530523479","date":"2025-10-12T14:08:04+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-10T13:48:41+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-09T15:12:21+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-09T09:52:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-09T05:43:28+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-09-09T02:19:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0630b77f-0a25-442e-bd6b-d22f4ed22272","owner":[],"postedDate":"October 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-26T16:04:00+00:00","versionOfRecord":{"articleIdentity":"rs-7539308","link":"https://doi.org/10.1186/s12889-026-26344-1","journal":{"identity":"bmc-public-health","isVorOnly":false,"title":"BMC Public Health"},"publishedOn":"2026-01-20 15:58:49","publishedOnDateReadable":"January 20th, 2026"},"versionCreatedAt":"2025-10-24 20:12:52","video":"","vorDoi":"10.1186/s12889-026-26344-1","vorDoiUrl":"https://doi.org/10.1186/s12889-026-26344-1","workflowStages":[]},"version":"v1","identity":"rs-7539308","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7539308","identity":"rs-7539308","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}