Sanitation workers play a crucial role in waste management and are at risk of significant occupational health hazards. This study aims to assess work-related musculoskeletal disorders along with other occupational health outcomes, knowledge and practices pertaining to occupational health risks among sanitation workers in five municipalities of Nepal and identify factors associated with musculoskeletal disorders.

A community-based quantitative cross-sectional survey was conducted among 790 sanitation workers using a non-probability sampling method. The study was conducted from December 2023 to December 2024, which involved structured face-to-face interviews with the participants and their health assessments by trained medical doctors. The study assessed socio-demographic characteristics, occupational health outcomes such as musculoskeletal disorders, and knowledge and practices pertaining to occupational health risks. A stepwise backward selection method was employed for conducting multiple logistic regression to identify the significant predictors of musculoskeletal disorders. Odds ratio and 95% CI were used to estimate the magnitude of association. p-value less than 0.05 was considered significant.

Of the total estimated sample size, 93% of the participants attended the health camp and completed the survey. Musculoskeletal disorders were observed in 36% (95% CI:35.5–39.7) of sanitation workers, with the highest prevalence among sweepers (38.8%), while needlestick injuries were common among the waste collectors (7.2%). Knowledge scores on occupational health risk prevention were moderate (70.7%), with 70.1% of workers reporting the use of personal protective equipment (PPE). Predictors of musculoskeletal disorders included age (OR:1.02, 95% CI:1.00-1.03), belonging to an underprivileged ethnic group (OR:2.14, 95% CI:1.01–5.53), education level (grade1–5) (OR:1.49, 95% CI:1.03–2.16) and employment in Pokhara municipality (OR:1.43, 95% CI:0.94–2.18).

Sanitation workers in Nepal face significant work-related occupational health risks, particularly musculoskeletal disorders, influenced by socio-demographic and job-specific factors. It is essential to implement targeted training programs for occupational safety, enforce workplace safety regulations, and conduct routine health screenings of sanitation workers by the municipality.

Sanitation workers play a key role in keeping the environment clean and promote human health by collecting waste directly from households, shops and small companies. The definition of sanitation workers encompasses a vast array of services with regional differences in terminology [3,2,3,4]. Despite the existence of several legal frameworks, the term sanitation worker has not been operationalized [5,6,7,8]. Various authors from Nepal have used different terminologies, such as informal waste workers, municipal solid waste handlers, waste workers, and sanitary workers to address these workers [9,10,11,12]. The term sanitation worker includes all individuals, whether formally employed or not, who are responsible for cleaning, maintaining, operating or emptying sanitation systems at any stage of the sanitation chain [13]. Their jobs also include cleaning toilets, emptying pits and septic tanks, cleaning sewers and manholes, operating pumping stations and treatment plants, and collecting, transporting and disposing health care and household waste. Often engaged in the informal sector, as an invisible, discriminated workforce, they are some of the most vulnerable workers exposed to occupational and environmental health hazards, while facing profound risks to their health and wellbeing, including illness, injury, and even death [14]. Musculoskeletal disorder is one of the common public health problem among the sanitation workers, which impacts their quality of life and contributes to their absenteeism, increased work restriction, transfer to other jobs, or disability more than any other group of diseases, with considerable economic toll on the individual, organization and society as a whole [15,16,17,18]. They are at risk of injuries due to heavy labor, poor posture, work-nature in confined spaces along with psychosocial stress [19, 20]. These risks are further exacerbated by different factors such as poverty, illness, malnutrition, poor housing conditions, child labor, substance abuse, social stigma, and societal neglect [13, 21]. Various empirical evidence suggests that age [18, 22], sex [23], education [18], work experience [24], substance abuse [22], mental health [22], working duration [25], location of work (slum vs. not slum) [24], job roles [26], body posture [25], body mass index [27], level of stress [23] and history of injuries [23] are the significant predictors of musculoskeletal disorders [28].

Besides musculoskeletal disorders, sanitation workers are also at risk of various other occupational health conditions, such as gastrointestinal problems, respiratory problems, injuries, and mental and social health problems [2, 29]. Most of the sanitation workers lack sufficient knowledge for maintaining personal hygiene and opportunities to practice hygiene at their workplace [30, 31]. On the other hand, personal protective equipment (PPE) is often inadequate, and many workers have never undergone training on occupational health and safety including usage and proper disposal of PPE, which is critical in preventing many occupational health risks [32].

The constitution of Nepal 2015 ensures health as a fundamental right and provides an essential premise for attaining, ensuring, and establishing the highest level of health and safety practices. The Local Governance Operation Act (2017), which is one of the major national legislations, empowers local government to manage and oversee sanitation services within their jurisdictions and underscores the welfare of sanitation workers [33]. Despite the existence of legal policy frameworks and the major role of local municipal government in solid waste management, the problem has still not been addressed in a comprehensive manner by taking into account those involved in solid waste management [34].Sanitation workers play an important role in delivering essential public services, often at the cost of their own dignity, health, and safety. However, sanitation workers are often invisible and are subjected to harsh conditions that expose them to the most severe impacts of inadequate sanitation, including debilitating infections, injuries and social stigma. Sanitation workers, particularly from low- and middle-income countries (LMICs), are particularly vulnerable due to unregulated or unenforced labor related policies, including lack of occupational health and safety measures [2, 13, 35]. It is essential to recognize their rights, provide them with support, and improve their working conditions. This also reflects the agenda of Sustainable Development Goal of decent working conditions, as called for by Sustainable Development Goal 8 [13].

Various literatures have highlighted that sanitation workers globally face similar risks, with high prevalence of musculoskeletal disorders and other occupational illnesses [36]. Studies conducted in Nepal are mostly focused on specific geographical locations and have failed to capture the broader occupational challenges faced by the sanitation workers in diverse settings across the country [9,10,11,12]. Moreover, there is a dearth of research examining the knowledge and practices related to occupational health risk prevention.

This study addresses this gap by assessing the work-related occupational health outcomes, knowledge, and practices of sanitation workers from five major municipalities of Nepal, i.e., Bharatpur, Janakpur, Pokhara, Biratnagar, and Nepalgunj. By focusing on the nationally representative sample, our study provides insights into the socio-demographic factors, health-related outcomes and identifies key predictors of musculoskeletal health disorder among the sanitation workers.

A community based quantitative cross-sectional study design was used to assess occupational health outcomes, including knowledge and practices pertaining to the prevention of occupational health risk among the sanitation workers, and identify the factors associated with musculoskeletal disorder.

The study was conducted in five major municipalities/metropolitan/sub-metropolitan, namely Bharatpur (Metropolitan), Nepalgunj (Sub-Metropolitan), Janakpur (Sub-Metropolitan), Pokhara (Metropolitan) and Biratnagar (Metropolitan), representing five out of seven provinces of Nepal. The term municipality is used throughout the paper. In terms of geographical distribution, these municipalities represent the two out of three ecological regions of Nepal i.e., terai (Bharatpur, Nepalgunj, Janakpur and Biratnagar) and hill (Pokhara). Regional variations exist in these study areas in terms of physical and socioeconomic aspects, including population, economic standing, and consumption patterns, as well as altitude, temperature, rainfall, and humidity. These factors affect the amount of waste generation as well as the technology used for waste treatment and disposal. These sites were selected based on the amount of municipal solid waste generation (Fig. 1), number of sanitation workers, and population density [34, 37, 38]. A free health camp was organized at specific locations in coordination with each of the municipalities where data was collected for the survey from February 2024 to July 2024. Sanitation workers were invited to attend health counseling and assessments by medical doctors and laboratory tests.

Municipal solid waste generation in the study site (Nepal)

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The sanitation workers from the five major municipalities who work for municipal solid waste management as well as those working for private companies attending our health camp were included in the study. The inclusion criteria for the study included those who have been involved in field-based solid waste management in the selected municipality regardless of their work duration as sanitation workers. Those who were not present during the free health camp or severely ill workers were excluded from our study.

Nonprobability total enumerative sampling was employed to recruit the study participants attending the health camp organized at the municipal level. The sample size was calculated using the formula n = Z²p(1-p)/d² [40]. Assuming the prevalence of occupational health conditions among sanitation workers to be 50% (p = 0.5). At 5% level of significance [z value equals to 1.96 (two-tailed test) and desired margin of error (d) equal to 5%], the sample size calculated was 385. Assuming the non-response rate of 10%, the estimated sample size calculated was 424. To mitigate selection bias in this sampling, the sample size was doubled [41, 42]. Hence, the final estimated sample size required for the study was 848. A health camp was organized in each of those municipalities in coordination with the municipal-level government, and prior information was delivered to invite the sanitation workers to attend the free health camp. A total of 790 sanitation workers attended the health camp and completed the survey.

A closed-ended structured questionnaire was employed for data collection via face-to-face interview through the trained research assistants. Research assistants from a health background were hired and trained/oriented on the research objectives, tools, and techniques for data collection. The questionnaire was designed to capture socio-demographic information and knowledge and practices of sanitation workers pertaining to work-related precautionary measures, hygiene, and occupational health problems. The tool for assessing the knowledge level of the study participants pertaining to preventing occupational health risk has been adopted from the previous research study [43]. Medical doctors were available for the observation and assessment of occupational health problems such as cuts or wounds in body parts, presence of infection in wounds, presence of skin rashes, allergies, sunburns in body parts, eye problems, musculoskeletal disorders, gastrointestinal problems, respiratory problems, presence of chronic diseases, and daily usage of medicine. Other clinical parameters, such as blood pressure and anthropometric data, were also collected during the medical examination. For BMI calculation, height and weight measuring instruments were checked and recalibrated prior to use. The final measurement for each anthropometric parameter was recorded as the mean of three measurements. The height and the body weight were measured by removing excess clothing such as jackets, scarves, and other accessories. For height measurement, participants were instructed to stand upright with their feet together, knees straight, and look straight into the horizontal plane. The blood pressure was measured using a digitally validated Omron device (model number HEM-7361T-EBK) [44] by the research assistants. Three separate readings were recorded (both systolic and diastolic readings) at least 60 s apart for the calculation of average blood pressure. The participants were instructed to be seated and rest for about 5 min and then requested to sit on the chair with an upright posture. The cuff was attached to the upper part of the arm, preferably on the left with the position placed at the heart level. The participant’s arm being used for the measurement was allowed to rest comfortably on the Table [45]. Appropriate lab testing was conducted for the diagnosis of possible medical conditions, such as sputum tests for tuberculosis, hepatitis B and C, and HIV antibody testing. Occupational health problems identified by the doctors along with the lab test results were entered into the observation sheet, which was then subsequently entered into the REDCap via mobile application.

The survey tool/questionnaire was developed by the research team in alignment with the study objective. The tool was designed based on an extensive literature review and expert consultation The questionnaire was first prepared in English and later translated into Nepali. The tools were pretested on approximately 5% of similar participants in Bharatpur municipality to ensure consistency and suitability for field-level data collection. The face validity of the tool was assessed by ensuring the questions aligned with study objectives and were easily understood by the participants. Construct validity was ensured by specifying the operational definition for each of the variables. To ensure external validity, we used the maximum variation sampling technique while recruiting study participants in terms of sex, types of sanitation workers, and location (municipalities from different provinces) [39]. Cronbach’s alpha was calculated to ensure the internal consistency of Likert-scaled thirteen sub questions that assessed the knowledge level of sanitation workers. The overall Cronbach’s alpha was 0.87, indicating good reliability.

The main dependent variable for the study is musculoskeletal disorder. The study constitutes six continuous variables, i.e., age, number of working days per week, number of working hours per day, personal monthly income (in NPR), body mass index (BMI), and blood pressure reading (both systolic and diastolic reading). The continuous variables such as body mass index and blood pressure was categorized based on external criteria such as protocols, guidelines, and journal paper [46,47,48]. The BMI was calculated as weight (kilogram) divided by height squared (meter), and categorized as underweight (BMI < 18.5 kg/m²), normal (BMI 18.5–22.9 kg/m²), overweight (BMI 23.0–27.4 kg/m²) and obese (BMI ≥ 27.5 kg/m²) based on the Asian BMI cutoff value [47]. The blood pressure reading was based on the systolic and diastolic readings, which were categorized as non-hypertensive (systolic < 140 or diastolic < 90) and hypertensive (systolic > = 140 or diastolic > = 90) [49].

Ethnicity was categorized as privileged (upper caste group, i.e., Brahmin and Chhetri) and underprivileged (Dalit, Janajati, Madhesi, Muslim) [50].All the work-related occupational health problems in the study were based on clinical confirmation or observation by medical doctors. The occupational health problem was dichotomized as having a problem or not having the problem. Musculoskeletal disorder was based on the conditions affecting muscle, bones, neck pain, low back pain, knee pain, elbow pain, and pain in hands and arms [51]. Clinical confirmation or observation, such as the presence of pricks or puncture marks on palms, arms, legs, feet and other body parts by medical doctors, denotes the needle stick injury. Gastrointestinal infection included the conditions such as gastroenteritis, including acute, persistent, inflammation of the stomach and intestines, diarrhea, including acute, persistent, bloody, and watery diarrhea, and dysentery. Diarrhea and vomiting are usual symptoms of gastrointestinal infections caused by bacterial, viral, or parasitic infections. This also includes infection with pathogens associated with any of the foregoing conditions [2]. The respiratory problem was based on the observation of conditions such as influenza-like symptoms, upper airway inflation, coughing, phlegm production, wheezing, shortness of breath, nasal congestion, and sore throat caused by inhalation of sewer gas (toxic or nontoxic), inhalation of gases from decayed household or industrial waste; inhalation of Hydrogen Sulfide, Carbon Dioxide, Ammonia, Methane, Sulfur Dioxide, fumes from chlorine bleach, gasoline [52]. Wounds and cuts in palms, arms, legs, feet, and other body parts mark the presence of wounds and cuts in skin. The knowledge level of sanitation workers on preventing occupational health risk was based on the Likert scaled thirteen sub questions, which included different aspects on preventing occupational health risk such as alcohol/tobacco consumption, personal protective equipment uses, body postures, and hygiene-related knowledge. Each of the sub questions had five response options, which included strongly agree (given 5 points), agree (4 points), not decided (3 points), disagree (2 points), and strongly disagree (1 point) [43]. Hence, the potential knowledge scores ranged from 13 to 65, which could be calculated by summing up the points obtained from each of these 13 sub questions. The calculation of the overall knowledge score ranged from 32 to 65, with mean knowledge obtained as 52.4 (6.2). Since the overall knowledge score showed normal distribution, we used mean and standard deviation as a cutoff value and categorized the knowledge level as having a low level of knowledge (below 46), a moderate level of knowledge (from 46 to 58), and a high level of knowledge (above 58). The practices of sanitation workers were based on their daily habits of PPE usage, hygiene, and eating habits.

The data from the study participants were collected using REDCap software, with possible checks to avoid errors. Coding of the item in the tool was done to simplify the data entry process. Data was then imported into StataSE 18 (StataCorp LP, USA) and analysis was made further. Descriptive statistics were used to characterize the study participants regarding sociodemographic characteristics, occupational health status, and knowledge and practices of study participants using frequency, percentage, mean value (standard deviation), and median (range). All the continuous variables were subjected to normality tests before further analysis. Normality tests were performed using the visual inspection method, i.e., the histogram and statistical skewness kurtosis test. A bivariate analysis was conducted for the independent variables across the types of sanitation workers having the four-response categories, i.e., sweepers, waste collectors, transporters, and pickers of dumping sites. A Chi-Square test was performed for categorical-to-categorical analysis, whereas one-way ANOVA (working hours per day) and Kruskal-Wallis test (age, working days per week, and personal monthly income) were performed for continuous-to-categorical analysis. All the assumptions for bivariate analysis were met before the analysis. We also conducted univariate and multivariate/multiple logistic regression analysis to assess the significant predictors for the musculoskeletal disorder. Initially, univariate logistic regression analysis was conducted to assess the degree of association of each independent variable with musculoskeletal disorder. Our multiple logistic regression model was based on the automated stepwise backward selection method. The significant predictive capacity of the model was assessed using likelihood ratio chi square statistics. Multicollinearity analysis and Hosmer-Lemeshow goodness of fit tests were further conducted to assess the validity of model. Multicollinearity test was conducted by generating the correlation matrix of the independent variables included in the model. The p value of the Hosmer and Lemeshow goodness of fit tests was used to assess the fitness of the model. Odds ratio and 95% CI were used to estimate the magnitude of the association. p-value less than 0.05 were considered significant.

Approval letters were obtained from each of the municipalities to conduct health camps. Ethical clearance was obtained from the Nepal Health Research Council (Reference number 1260) dated February 8, 2024. The participant information sheet and the consent form were provided to study participants to read or were verbally read by the research assistant explaining the objectives of the study. Written or verbal consent was obtained. Written consent was sought where possible. If participants were not literate, verbal consent was obtained in the presence of a witness. All sanitation workers attending the health camp were provided with medical services (health counseling and assessment by doctors, laboratory services, and medicine) at free of charge, depending upon their medical conditions and as per those provisioned by the project.

Out of 848 estimated sample size, only 790 samples participated in the study, with a response rate of 93.2%. Out of 790 study participants attending the health camp and consenting to medical checkups by the doctors, we included 692 samples for the statistical analysis. The remaining 98 samples from the mixed type of sanitation workers were excluded due to missing data points, declining to participate, and poor operational definition.

Table 1 shows the socio-demographic characteristics of the study participants. The total sample used for the analysis included 692 sanitation workers, with males (73.3%) significantly outnumbering females (26.7%). Gender distribution varied significantly across different job roles of sanitation workers, with sweeping roles predominantly handled by females (53.4%). Males were mostly involved in waste collection (97.0%), transportation (100%), and picking at the dumping sites (73.7%). The sanitation workers doing the picking role from the dumping sites were the lowest (8.3%) as compared to other roles such as sweeping (44.5%), waste collection (24.7%), and driving waste vehicles or transporters (22.5%). The median age among the sanitation workers also varied significantly (p < 0.001), with waste collectors being the youngest ones (median age 26 years) and transporters being the oldest ones (median age 35 years). Nearly 26% of the sanitation workers in our study were from Biratnagar, followed by Janakpur (21.2%) and Nepalgunj (20.2%). The geographical distribution was significantly associated with the job roles of the sanitation worker. Pickers of dumping site were mostly from Bharatpur (59.6%), while sweepers were predominantly from Janakpur (35.4%). Both waste collectors (32.5%) and transporters (29.2%) were predominantly from Pokhara. Most of the sanitation workers in our study were married (83%). A significant proportion of sanitation workers were illiterate (37%), with the highest being among the sweepers (56.4%) as compared to others. Educational levels showed significant differences among the different types of sanitation workers. Both ethnicity and religion showed significant variation among the sanitation workers. Most of the sanitation workers predominantly belonged to the Hindu community (nearly 93%) and were from underprivileged groups (93.4%). Sanitation workers from the non-Hindu community seemed to work mostly as pickers at the dumping site (15.8%). The median working days per week showed a similar pattern across all the types of sanitation workers with no significant differences. The mean working hours per day varied significantly across all the types of sanitation workers, with transporters and waste collectors working for the longest hours (9.3 and 9.0 h/day, respectively) compared to the sweepers (6.9 h/day).

Musculoskeletal disorders were the common health issues, affecting 36% of sanitation workers (Table 2). The problem was commonly observed among the sweepers (38.8%) and transporters (38.3%). Most of the sanitation workers reported low back pain (66.4%), followed by pain in the shoulder and neck (19%). Most of the sanitation workers reported mild (55.3%) to moderate (40.2%) levels of pain in the body part, whereas only 4.5% reported severe body pain (data not presented in table). We conducted multiple logistic regression analyses using an automated stepwise backward selection method. The regression model showed that age, ethnicity (underprivileged group), types of sanitation workers (pickers of dumping sites), and education level (grade 1–5) except municipality (Pokhara) were the significant predictors of musculoskeletal disorder (Table 3).

With reference to the multiple logistic regression model, every additional increase in age by one year was associated with a 1.02 times higher likelihood of reporting musculoskeletal disorder. The likelihood of musculoskeletal disorder among the sanitation workers from underprivileged ethnic groups was 2.14 times higher than those from the privileged ethnic group. Similarly, the likelihood of musculoskeletal disorder among the sanitation workers with an education level from grade 1–5 was 1.49 times higher than those who were illiterate. Sanitation workers involved as pickers from the dumping site were less likely to report having musculoskeletal disorder as compared to the ones who worked as sweepers. Being from the municipality (Pokhara) was not significantly associated but still contributed to the overall variation of the musculoskeletal disorder. The workers from the Pokhara municipality were at 1.43 times higher odds of having musculoskeletal disorder compared to those from Bharatpur.

A total of 655 observations were included in the multiple logistic regression model. The variables that did not contribute significantly (p > = 0.10) were iteratively removed based on the Wald test. The final model had a pseudo-R square value of 2.18%, which indicates that 2.18% variation in the outcome variable, i.e., musculoskeletal disorder, was explained by all the independent variables [age, ethnicity (underprivileged), education (grade 1–5), sanitation workers (pickers of dumping sites), and municipality (Pokhara)] in the model. According to the likelihood ratio test (LR χ² = 18.67, p < 0.05), all the independent variables in the model were significantly predictive of the musculoskeletal disorder, i.e., the proposed model is better than the null model. None of the variables in the model had the correlation ‘r’ value greater than 0.5 (multicollinearity assessment). The Hosmer and Lemeshow goodness of fit test showed the p value of the model 0.16, indicating that the model is good for the prediction of musculoskeletal disorder (observed and predicted values are close to each other).

Wounds and cuts in the skin were observed among 6.8% of the sanitation workers, with significantly higher prevalence seen among the pickers of dumping sites (14.0%) followed by waste collectors (10.7%), while sweepers (nearly 5%) and transporters (nearly 4%) reported much lower rates (Table 2). Though not very common (only 3.2%), needle stick injuries were found to be significantly higher among the waste collectors (7.2%), followed by pickers of dumping sites (7.0%). Wound infection was found to be very rare (1.2%). Similarly, skin problems such as rashes/sunburn/eczema were observed among 10.8% of the study participants, with no significant difference. Similarly, other occupational health-related problems were observed among the sanitation workers, such as eye problems (18.8%), respiratory problems (7.4%), and gastrointestinal problems (9.8%). These conditions did not show a significant association with the different types of sanitation workers.

The study also analyzed different risk factors for non-communicable disease. The presence of chronic diseases (the presence of either diabetes, COPD, cancer, or mental health problems) was observed among 10.3% of the participants, with a significantly high prevalence seen among the sweepers (14.1%) and transporters (9.1%). About 29.6% of the sanitation workers suffered from hypertension (BP > = 140/90), with the highest burden seen among the transporters (36.4%), followed by pickers of the dumping site (31.6%), and sweepers (31.1%). The distribution of blood pressure levels varied significantly across different sanitation workers. The BMI categories differed significantly across the sanitation workers. A significant proportion of sanitation workers had a normal BMI (40.8%). About 28.8% of the sanitation workers were overweight, whereas 20.8% were obese. The burden of obesity was higher among the sweepers (26.2%), whereas being overweight was seen higher among the transporters (33.1%). The highest prevalence of underweight was seen among the pickers of dumping sites (21.1%).

In addition, different serological tests such as HIV, hepatitis B, and C were conducted for all the sanitation workers (data not shown in the table). It was found that three samples were reactive against HIV antibodies, each from sweepers, waste collectors, and pickers of dumping sites. Similarly, four samples showed a Hepatitis B reactive test (three of the waste collectors and one transporter). None of the samples were hepatitis C reactive. Sputum test for tuberculosis detected tuberculosis bacilli in two of the samples (each from waste collectors and pickers of the dumping site).

The knowledge score of the sanitation workers on preventing occupational health risk ranged from 32 to 65, with the mean score being 52.4 (6.2). About 70.7% of the sanitation workers had moderate levels of knowledge, whereas nearly 17% of them showed a high level of knowledge on preventing occupational health risk (Table 4). The level of knowledge on preventing occupational health risk varied significantly across all the sanitation workers. The sweepers demonstrated the highest proportion of moderate level of knowledge (79.4%) whereas transporters (64.3%), waste collectors (63.3%) and pickers of dumping sites (62.7%) showed similar patterns of moderate level knowledge. The waste collectors (nearly 26%) and transporters (25.2%) demonstrated a high level of knowledge as compared to others on preventing occupational health risks.

The practices of sanitation workers relate to personal protective equipment (PPE) usage and hygiene habits. About 70% of the sanitation workers reported using PPE during work time. The usage of PPE during work varied significantly across all the sanitation workers. About 77% of the waste collectors reported using PPE during work time, followed by sweepers (73%), and transporters (62.3%). The data also shows the consistent use of PPE among sanitation workers during work time (76.1%). However, the consistent or inconsistent (frequency) usage of PPE during work time was not significantly associated with the different job roles of sanitation workers.

Masks were the most used items as PPE (93%), followed by gloves (81.7%) and shoes/boots (64.7%). Helmets (19.9%), protection glasses (14.3%), and a full body apron (12.9%) were reported as the least used PPE during working time. A similar pattern of mask usage rate was observed among the waste workers (96.1%) and transporters (95.8%). Similarly, waste collectors (93%) and pickers of dumping sites (90.6%) were among the highest, using the gloves.

In terms of hygiene practices, nearly 84% of the sanitation workers reported taking showers after work. Taking showers after work varied significantly across all the sanitation workers. Sweepers represented the highest among sanitation workers (89.8%) taking showers as compared to others. Washing hands before eating was reported by 89% of the sanitation workers, with significant differences observed across the sanitation workers. Similarly, about 90.8% of the sanitation workers preferred soap for handwashing, but significant differences were not observed across the groups. Only 44% of the sanitation workers reported eating food at the workplace.

About 58% of the sanitation workers reported using instruments for waste handling, with this practice being most prevalent among the sweepers (76.3%) and least among the transporters (35%). The usage of instruments for waste handling differed significantly across all the sanitation workers.

The survey highlights the work-related occupational health outcomes, knowledge and practices of sanitation workers from five major municipalities of Nepal. In addition, the study also identifies the major predictors affecting musculoskeletal disorders. The knowledge level of sanitation workers on preventing occupational health risk was not significantly associated with musculoskeletal disorder, which might indicate that the musculoskeletal disorder might not only be influenced by the knowledge level of the sanitation worker.

Our study revealed that musculoskeletal disorders were among the major occupational-related health hazards, affecting 36% of the overall sanitation workers. The occupational health problem was mostly observed among the sweepers (38.8%) and transporters (38.3%). A systematic review and meta-analysis showed that the global prevalence of musculoskeletal disorder among sanitary workers was 40.6%, with high income countries accounting for 43.3% and low-income countries accounting for 38.6% [36]. Our finding is comparable, particularly to the proportion of musculoskeletal disorder problems in low-income countries [43].

Our study showed that about 32.5% of waste collectors were affected by musculoskeletal disorder. Different studies revealed a wide range of musculoskeletal disorders among the waste collector from being as low as 19.7% [22] to being as high as 83.3% [53]. The pooled prevalence from systematic review and meta-analysis showed that solid waste collectors accounted for the highest proportion of musculoskeletal disorder (45.1%) as compared to other sanitation workers [36].

However, our study revealed sweepers being the topmost sanitation worker affected by musculoskeletal disorder (38.8%). The regression model in our study revealed pickers of dumping sites were less likely to have musculoskeletal disorder as compared to sweepers (OR = 0.52, p < 0.05). The same review showed musculoskeletal disorder in street sweepers being about 41.5% [36]. Sweepers tend to work for long hours in public places using long handled brooms and wheelbarrows. The repetitive nature of their job, manually sweeping in a standing position and, frequent bending for waste collection increases their chance of getting musculoskeletal disorder [24]. In addition, gender, age, and working duration also play an important role in determining musculoskeletal disorder. Our study revealed that females were mostly involved in sweeping role (53.4%). This could explain the burden of musculoskeletal disorder among the sweepers. Various biological factors (hormones, muscle mass, bone structure), workplace, and lifestyle factors make females more susceptible to musculoskeletal disorder [54].

Various factors such as age, sex, body mass index, education, working duration, and body postures are the important predictors of musculoskeletal disorder [55,56,57,58]. Our study revealed that age, ethnicity (underprivileged group), types of job roles as sanitation workers (pickers of dumping site), municipality (being from Pokhara), and education level (being in grade 1–5) were the potential risk factors that influenced the musculoskeletal disorder. The significant variables in our model showed that age, underprivileged ethnic group, and education level from grade 1–5 were associated with an increase in musculoskeletal health problems. Our findings align with the existing literature [55, 57], and also ageing is one of the biological factors that could be associated with decline in physical resilience and increased vulnerability to musculoskeletal issues, especially in physically demanding occupations. Musculoskeletal disorder/pain disproportionately impacts people from different ethnic backgrounds through higher burden and limited access to care [59].The higher risk of musculoskeletal disorder among the underprivileged ethnic group in our study might suggest broader socio-economic disparities that contribute to occupational health inequalities, such as limited access to health care, poor working conditions, and a higher level of occupational stress. The survey also revealed primary education level (grade 1–5) being the significant predictors for the musculoskeletal disorder. This is also in agreement with the study done in India, which shows workers with primary & secondary level education exhibited significantly higher odds of having musculoskeletal disorder [18]. The findings may suggest lower educational attainment with limited health literacy and behavior-related factors to adopt preventive measures against occupational health risk.

The study also highlights other different occupational health outcomes such as respiratory problems (7.4%), eye problems (18.8%), and skin problems (10.8%) among the sanitation workers. However, the findings were relatively low as compared to the study conducted in Kerala, India [29]. Although not very high, one of the notable findings of this study is the proportion of needle stick injuries among the waste collectors (7.2%), and pickers of dumping sites (7.0%) as compared to other sanitation workers. This could be mainly because of the nature of the job done by the waste collectors and pickers at the dumping site, which includes direct contact with the waste materials during handling and segregation.

Regarding the knowledge and practices of sanitation workers, our study showed that sanitation workers had moderate to high levels of knowledge in preventing occupation health risk (70.7% vs. 16.9%). A similar study conducted previously in Nepal showed that about 16.1% had knowledge to prevent work-related health risks [10]. Knowledge pertaining to personal protective equipment was particularly noteworthy in our findings. Sanitation workers strongly agreed on the protective benefits of using gloves (25.3%), masks (24.8%), and boots (30.7%) (data not presented in table). These results are consistent with the findings from a similar study conducted in Africa, which shows a similar pattern of knowledge/awareness regarding glove use (23.4%), masks (23.6%), and boots (32.3%) [43]. Despite the differences in geographic and socio-economic context, the overall pattern of the result shows the universal challenges sanitation workers face and the shared recognition of PPE as a critical component of occupational health risk prevention. The relatively low percentage of strong agreement might indicate that there are still significant gaps in adoption or awareness level on protective benefits of PPE. This could indicate the need for proper training, access to protective gear, and enforcement of safety protocols in workplace environments [13, 43]. In addition to assessing the knowledge level of sanitation workers, our study also examined the actual practices of sanitation workers regarding PPE usage and their hygiene routines. More than half of the sanitation workers in our survey practiced using personal protective equipment during their work (70.1%), used masks (93%), gloves (81.7%), and shoes/boots (64.7%). A study conducted in Bangladesh showed that above 90% of the sanitation workers practiced using PPE at their workplace [30]. Nearly 84% of the study participants in our survey reported taking showers after work, whereas the same study from Bangladesh showed that over 93% of the sanitary workers took showers with soap [30]. Such a high difference in the study of Bangladesh can be accounted for the fact that the study was conducted during the COVID-19 pandemic.

This study offers valuable insights into the occupational health conditions, knowledge, and practices of sanitation workers across the five major municipalities of Nepal, making it one of the few studies to address the underserved populations. The inclusion of a large sample size offers robust statistical power of the study. The study serves as a foundational framework for improving the occupational health, safety, and dignity of sanitation workers.

The major limitation of this study is the relatively low coefficient of determination (R²) for musculoskeletal disorder. Additionally, the reliance on self-reported data may have introduced recall biases, despite the effort to minimize the recall bias through probing. The possibility of measurement bias was mitigated using a well calibrated instrument and averaging multiple readings for anthropometric and blood pressure parameters. The use of the non-probability sampling method may have introduced selection bias, affecting the generalizability of the study.

PPE:

Personal Protective Equipment

BMI:

Body Mass Index

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GKS, EJ, KR, SK, KN and DN contributed to the conceptualization of the research project. Samip Khatri and SHK drafted the initial version of the manuscript. Samip Khatri finalized the manuscript. Samip Khatri and PB cleaned the dataset. Samip Khatri contributed to the overall analysis of the data and developed the study area map using QGIS. NB, SG and Samip Khatri supervised the overall data collection process at field level. SKS and GKS coordinated with local medical officers for the conduction of health camp at the municipality. BBT, SM, AK, MJ and SW coordinated with the local municipality and collected the data with the help of locally hired enumerators. GKS, EJ, KR, and DN edited the contents and gave overall feedback in the writing process. GKS, KN, and SK guided the overall research process. All the authors have read and approved the final manuscript.

Correspondence to Samip Khatri.

Ethical clearance for the study was approved by the ethical review board (ERB) of the Nepal Health Research Council (NHRC) [Ref No. 1260]. Since the study involved the participation of humans (study participants) in the health camps, we fully adhered to the National Ethical Guidelines for Health Research in Nepal 2022. The participant information sheet and consent form were provided to read or was verbally read by the research assistant. The objective of the study was clearly explained prior to obtaining the written/verbal consent from the study participants. Verbal consent was obtained from the illiterate participant in the presence of a witness. Written consent was obtained from the legally authorized representatives of minors (those younger than 18 years old). A written assent was also obtained from the participating minor. Approval letters were obtained from each of the municipalities before the conduction of the health camp. Confidentiality and privacy were maintained thoroughly via de-identification of data.

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The authors declare no competing interests.

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