This study has been carried out mainly to explore the difference of WAI between formal and informal sector workers, the relations of socio-demographic, health and work-related factors, and WAI and its dimension. The results show that individual age group, presence of NCDs, occupational health behaviours are significantly associated with the WAI and WAI dimensions; perception of working ability, health status and mental resources of the study sample.
Age group and work ability. This study categorized worker’s age into two groups; less than 55 and 55 years and above. The effects of age group associated to the WAI and similar to the three dimensions. The workers of age 55 years and above have a higher risk to ‘poor to moderate WAI’ class. Age was a significant factor associated to WAI in many studies. Our results’ direction of association is consistent with many studies showing that age is significantly and negatively associated with WAI in various occupational sectors [22–25]. However, the data did not highlight gender and working ability, corresponded to the study of van den Berg et al. in 2009 [26], although there is the probability of low or poor work ability, which was higher in women’s WAI measurement [27]. The ageing of workers requires two issues that need consideration [28–29]: the first one involves worker’s health, and the second is job productivity and performance. A larger number of older workers implies, for example, an increasing number of people at work with minor and major health problems that occur more frequently after 55 years of age [30]. About 53% of both sectors in the study were ageing workers, and half were NCDs. Age and the presence of NCDs were the predominant factors of ageing workers’ productivity. The results show that the presence of NCDs is a strong and positive association among the ‘poor to moderate WAI’, especially in a ‘health status’ dimension (OR = 6.42). Our data explored the presence of NCDs (48.2%), with hypertension in the highest proportion. Complex interactions were proposed between ageing of working population and lifestyle risk factors such as low-level of physical activity, known as the risks of cardiovascular disease, and work-related risk factors [31]. Our data showed approximately 60%of workers had overweight or obesity status, in line with other reports [18, 26, 32–34]. However, the rate may not be different between the two sectors. Moreover, more than half of the workers (59%) reported a non-regular exercise group. Physical health, which is one of the intermediate determinants of individual lifestyle, directly affects worker’s health status and functional activity, which are base factors for working ability [35–36]. Then the declining of physical capability and increasing of risk to NCDs; obesity was the negative factor influencing working ability of the ageing workers. Other risk factors, including smoking and alcohol consumption, are not associated with WAI. We found the high proportion (more than 70%) of ‘non-smoker’ and ‘non-drinking’ workers in this study, especially in the informal sector. This association is not significant in bivariable and multivariable models, this result corresponds to Mehdi El Fassi et.al. (2013) [27] stating that workers’ smoking habit was reported as significant in a single study only [32].
Working conditions correspond to the fourth floor and consist of work, and all of its dimensions as described by WAI [35–36]. Our study explored working practices in various manners composed of personal hygiene, safety inspection, personal protective equipment (PPE) usage, simple working improvement, resting duration and housekeeping. The study results demonstrate that worker who was ‘unsafe’ had a higher probability of the ‘low to moderate’ WAI (OR = 2.11). The univariable analysis of working practices demonstrate the higher proportion (60%) of safety practices. The bivariable analysis also show the significant association of WAI and working practices. We also found that there is a statistically significant association of safety practices in the ‘good to excellent’ worker in the multivariable analysis. K Tuomi et. al. (2001) have shown that work environment factors, such as poor work postures, distracting work environment, poor physical climate, tool failure and work rooms were strongly associated with poor working ability [18]. On the other hand, improvements in the work and tasks, work environment and tools positively influenced working ability [18].
In Thailand, informal worker’s occupational health services were integrated in the primary healthcare system arranged by the Universal Health Coverage scheme (UCS). The formal workers in the public and private sectors utilize healthcare services by their health insurance scheme, which is Civil Servant Benefit Scheme (CSMBS) and Social Security Scheme (SSS), respectively. Those services promote health, are prevention and cure-based when it comes to general health and diseases, which cannot be separated from occupational problems and diseases, except in the SSS. However, worker’s health improvement issue is more complex and requires a holistic approach, especially in the ageing worker. The services have to set in at the early phase of physical and mental deterioration described by the decline of the WAI score. Work ability model is appropriate for an ageing workforce process based on the self-assessment of subjective experiences of personal resources, working context, and work-life interface [35–36]. The structure of work ability changes during a person’s life and career, such as the fact that ageing affects the individual’s resources [37]. The implementation of work ability assessment in the occupational health and safety program will provide preventive measures and early rehabilitation in the workplace and healthcare centre [38–40].
There are several limitations in this study. Firstly, the cross-sectional design by which exposure and outcome were measured concurrently does not certify the causal relationship model. In epidemiological studies, an association of exposure and outcomes is causal only if the study’s plausibility was explored. Secondly, self-reported measurements of the study’s variables—including working ability and occupational hazards—may lead to recall and information bias. Workers’ awareness of the occupational hazards could affect the measures’ correctness. Workers in the formal sector were familiar with their work conditions, and they were able to recognize the occupational hazards in their workplace, while informal workers may not. Lastly, we focused on the working abilities of ageing workers residing in sub-urban and rural communities because of the information access, which may not be representative of workers elsewhere in different settings. Generalization beyond the study population should be used with consideration.