Quality of life among municipal corporation sanitary workers

Introduction

Municipal Corporation Sanitary Workers (MCSWs) play a vital role in maintaining environmental sanitation and protecting public health through street sweeping, solid waste collection and drainage cleaning. Despite their indispensable contribution, the nature of their occupation and the prevailing socio-economic conditions may influence their overall wellbeing and quality of life. Quality of life is a multidimensional concept that reflects an individual's physical health, psychological well-being, social relationships and environmental conditions. The WHOQOL Group (1996) [7] defined quality of life as an individual's perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns. The quality of life of sanitary workers is influenced by occupational demands, sociodemographic characteristics and environmental conditions. Poor working conditions, inadequate occupational safety, social disadvantages and limited welfare measures may adversely affect different domains of quality of life. Studies conducted among sanitary workers have also highlighted the influence of occupational and socio-economic factors on their quality of life (Nazan et al., 2012; Marcial et al., 2015; Madhumithra et al., 2021) [3,2,1] . Assessment of quality of life provides a comprehensive understanding of the physical, psychological, social and environmental well-being of Municipal Corporation Sanitary Workers and helps identify areas requiring attention to improve overall welfare. However, information on quality of life in Karnataka is limited. Therefore, the present study was undertaken with the following objectives.

Materials and Methods

The present study was conducted during 2021-2023 in the Hubballi-Dharwad Municipal Corporation (HDMC), Karnataka. An exploratory research design was adopted for the study. A total of 300 Municipal Corporation Sanitary Workers (MCSWs) were selected through simple random sampling from the four zones of the Dharwad region under HDMC. Data were collected through personal interviews using a self-structured pre-tested interview schedule to obtain socio-demographic information. Quality of life of the sanitary workers was assessed using the WHOQOL-100 questionnaire developed by the WHOQOL Group (1996) [7] . The instrument consists of 100 items covering four domains, namely physical, psychological, social and environmental, comprising 24 facets of quality of life. Responses were recorded on a five-point Likert scale and scored according to the WHOQOL-100 guidelines. The collected data were coded, tabulated and analysed using Microsoft Excel and SPSS version 16. Frequency, percentage, weighted mean score and Karl Pearson's correlation coefficient were employed for data analysis.

Results

Table 1 presented the socio-demographic profile of Municipal Corporation Sanitary Workers (MCSWs). Among the respondents, 56.00 percent were females, while 44.00 percent were males. More than half of the respondents (52.33%) belonged to the <35 years age group, followed by 26.33 percent in the 35-45 years age group and 21.34 percent above 45 years. Regarding educational status, 41.00 percent of the respondents were illiterate, followed by 29.68 percent with primary education, 17.66 percent with middle school education, 9.00 percent with high school education and 2.66 percent with higher secondary education. The majority of the respondents (92.34%) belonged to the Hindu religion, whereas 7.66 percent were Muslims. Most of the respondents (78.33%) were married, followed by 10.33 percent widows, 7.00 percent unmarried and 4.34 percent divorced. More than half of the respondents (53.66%) belonged to nuclear families, whereas 46.34 percent belonged to joint families. Nearly half of the respondents (46.33%) had 11-20 years of work experience, followed by 36.00 percent with less than 10 years of experience and 17.67 percent with more than 21 years of experience. A majority of the respondents (85.67%) worked 8 hours per day, whereas 14.33 percent worked 9-10 hours per day. Table 2 presented the quality of life across different domains among MCSWs. In the physical domain, activities of daily living (3.45) recorded a good quality of life, whereas pain and discomfort (1.94), energy and fatigue (2.28), sleep and rest (2.21), mobility (2.48), dependence on medicinal substances and medical aids (2.47), and work capacity (2.47) were rated as poor. The physical domain mean score was 2.47, indicating poor quality of life. In the psychological domain, bodily image and appearance (3.67) recorded a good quality of life, whereas positive feelings (2.13), thinking, learning, memory and concentration (2.10), self-esteem (2.37), and negative feelings (2.36) were rated as poor. Spirituality/religion/personal beliefs (2.65) was rated as neither good nor poor. The psychological domain mean score was 2.54, indicating poor quality of life. The social domain showed that personal relationships (3.05) and sexual activity (3.14) were rated as neither good nor poor, whereas social support (2.57) was rated as poor. The social domain mean score was 2.92, indicating neither good nor poor quality of life. In the environment domain, home environment (1.61) and financial resources (1.67) were rated as very poor, whereas freedom, physical safety and security (1.86), services (2.23), information (2.08), leisure (1.91), physical environment (2.16), and transport (2.41) were rated as poor. The environment domain recorded the lowest mean score (1.99). The overall composite mean score was 2.37, indicating poor quality of life among MCSWs. Fig. 1 illustrated the quality of life levels among MCSWs. Nearly half (47.00%) of the respondents had poor quality of life, followed by 23.00 percent with very poor quality of life. Good quality of life was observed among 15.00 percent of the respondents, whereas 9.00 percent had neither good nor poor quality of life. Only 6.00 percent of the respondents had very good quality of life. Table 3 presented the relationship between independent variables and quality of life domains among MCSWs. The results revealed that age, number of children, family size, annual income, work experience, working hours and body mass index (BMI) had a positive and significant relationship with the physical, psychological, social and environment domains of quality of life at the one percent level of significance. Education showed a negative and significant relationship with all the quality of life domains at the one percent level of significance.

Discussion

The socio-demographic profile of the respondents revealed that more than half (56.00%) were females, while 44.00 percent were males. The majority of the respondents (52.33%) belonged to the below 35 years age group, whereas 41.00 percent were illiterate. Most of the respondents (92.34%) belonged to the Hindu religion and 78.33 percent were married. More than half of the respondents (53.66%) belonged to nuclear families. Nearly half of the respondents (46.33%) had 11-20 years of work experience, whereas the majority (85.67%) worked for 8 hours per day. These findings indicate that the sociodemographic and occupational characteristics of the respondents may have influenced their quality of life. Similar findings were reported by Yoganarasimhachari (2019) [8] , who observed that the majority of sanitation workers had low educational status. Comparable findings were also reported by Sudarshan and Dhanalaxmi (2021), who found that most respondents had 11-20 years of work experience. The quality of life profile of the MCSWs showed that the social domain recorded the highest composite mean score (2.92), followed by the psychological (2.54) and physical (2.47) domains, whereas the environment domain (1.99) recorded the lowest score. The overall quality of life score reflected poor quality of life among the respondents. Better personal relationships, family support and psychological well-being contributed to the relatively higher scores in the social and psychological domains, whereas persistent physical discomfort, inadequate energy, fatigue, poor home environment, inadequate financial resources and limited access to basic amenities adversely affected the physical and environmental domains of quality of life. Similar findings were reported by Syed et al. (2022) [6] , who observed poorer quality of life among sanitation workers due to adverse occupational conditions and inadequate occupational safety measures. Comparable findings were also reported by Madhumithra et al. (2021) [1] , who found that older age, lower educational status, chronic illness, tobacco use and alcohol consumption were associated with poorer quality of life among sewage workers. The majority of the respondents (70.00%) experienced poor to very poor quality of life, with 47.00 percent reporting poor quality of life and 23.00 percent reporting very poor quality of life. Only 15.00 percent had good quality of life, whereas 9.00 percent reported neither good nor poor quality of life and 6.00 percent had very good quality of life. The predominance of poor quality of life among the respondents reflects the cumulative effect of occupational strain, healthrelated problems, inadequate financial resources and unfavourable living and working conditions. Similar findings were reported by Norton et al. (2009), who observed that musculoskeletal symptoms adversely affected the physical, general health and vitality domains of quality of life among workers engaged in physically demanding occupations. The relationship between independent variables and quality of life domains indicated that age, number of children, family size, annual income, work experience, working hours and body mass index had a positive and significant association with the physical, psychological, social and environmental domains of quality of life, whereas education exhibited a negative and significant relationship with all the domains. These findings suggest that socio-demographic characteristics, occupational exposure and educational status significantly influenced the quality of life of the respondents. Similar findings were reported by Syed et al. (2022) [6] , who observed that age, educational status, marital status and income were significantly associated with different domains of quality of life among sanitation workers.

Conclusion

From the present study, it could be concluded that the respondents generally had poor quality of life. The sociodemographic profile revealed that they were predominantly female, belonged to the below 35 years age group, had low educational status and considerable work experience. Among the quality-of-life domains, the social domain recorded the highest composite mean score, whereas the environment domain recorded the lowest composite mean score. Nearly half of the respondents experienced poor quality of life, followed by those with very poor quality of life. Hence, the study highlights the need for appropriate occupational health, ergonomic and welfare interventions, along with improved working conditions and occupational safety measures, to enhance their quality of life and overall well-being.

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