Effect of Job Stress on Sleep Quality and Mental Health in Pink Collar Job Workers of Coastal areas of Puducherry District – A Cross-sectional Study

Abstract

Background:

Pink-collar workers are individuals engaged in care-oriented or service-based jobs, often historically associated with women's work. Anganwadi Workers (AWWs) in India are a key example of this group and serve as the first point of contact between rural communities and the public health system. These workers face high levels of mental stress due to demanding responsibilities, limited resources, and socio-economic pressures. Previous studies have reported a high prevalence of mental health issues among AWWs, with one study citing a staggering 72.9% prevalence of mental illness. Sleep quality has been increasingly recognized as a critical factor influencing mental health, particularly in vulnerable occupational groups. This study aimed to evaluate the impact of sleep quality on the mental health status of Anganwadi workers in the coastal areas of Puducherry district, while also exploring the correlation between mental health, sleep quality, and daytime sleepiness.

Methodology:

A cross-sectional study was conducted over six months from February 2024 to August 2024 in Puducherry district. The study population consisted of 227 Anganwadi workers selected through simple random sampling from a total of 546 eligible workers (those with at least one year of work experience). Participants were assessed using a semi-structured questionnaire that collected demographic and occupational information. Standardized tools such as the Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), and the 12-item General Health Questionnaire (GHQ-12) were used to assess sleep quality, daytime sleepiness, and mental health status, respectively. Data analysis involved descriptive statistics, inferential tests (independent t-test, ANOVA), and correlation analysis (Pearson’s correlation). Kruskal-Wallis H test and Dwass-Steel-Critchlow-Fligner pairwise comparisons were employed to compare mental health status across different levels of sleep quality.

Results:

The study found that poor sleep quality significantly affects the mental health of Anganwadi workers. Mental health status was measured using GHQ-12 scores, with higher scores indicating greater psychological distress. There was a statistically significant association between sleep quality and mental health (χ² = 8.64, df = 2, p = 0.013, ε² = 0.0417). Pairwise comparisons revealed that participants with good sleep quality had significantly better mental health compared to those with poor sleep quality (W = -4.052, p = 0.012). Additionally, excessive daytime sleepiness showed a positive correlation with poorer mental health outcomes (r = 0.128, p < 0.05). Socio-demographic factors such as joint family structure, lower educational level, and prior job training were associated with better mental health status, while no significant relationship was observed between mental health and age, work experience, or weekly working hours. Pearson correlation analysis confirmed a weak but significant positive relationship between sleep quality and mental health (r = 0.106), and between daytime sleepiness and mental health (r = 0.128).

Conclusion:

This study highlights the significant impact of sleep quality on the mental well-being of pink-collar workers, particularly Anganwadi workers in coastal Puducherry. Interventions aimed at improving sleep hygiene and addressing daytime sleepiness could play a crucial role in enhancing the mental health of this essential yet vulnerable workforce.