According to the World Health Organization (2017), most middle-aged workers suffer from common occupational risks like injuries, airborne particles, ergonomic risk and noise which results in different types of chronic diseases. Based on the record, back pain has recorded 37% cases, deafness has 16% cases, 13% of cases for pulmonary diseases, 11% cases of asthma, 9% cases of lung cancer, 8% of injuries, 8% of depression and 2% of leukemia. Research shows that the employment growth declines for workers of this age in different industries and business sectors except for industries that require client interaction, similar to business-auto services, other personal services, medical services, educational services, and social services. (Wegman DH, 2014) Blue-collared jobs may prefer younger people since they are more capable to do work that requires heavy lifting and repetitive tasks. Career opportunities might decrease for middle-aged workers in other industries, particularly in the manufacturing industry. The manufacturing industry is a broad type of industry that involves processing of raw materials into finished goods. This business sector shares a significant part in the industry of different developed countries. Machines and people interact with this kind of industry, may it be manual, semi-automated, and automated. According to Aldaba (2014), labor-intensive products dominate the exports of the Philippines, followed by the machinery. This means that the manufacturing industry in the Philippines is mostly made up of human labor and machinery.
The production of footwear in the Philippines is described as largely manual or semi-automated. Majority of the local footwear manufacturers still impose the traditional or handmade processes with low-level of technology, which make less production output. A correlational research design, using linear regression analysis, aimed to understand the relationship between health issues, work environment, and efficiency that can affect the productivity of middle-aged and older workers in the shoe industry. There are 139 respondents from 16 shoe manufacturing companies within Marikina City participated in this study. Rapid Upper Limb Assessment and 10-point rating scale survey questionnaires, worker evaluation, and company evaluation checklists were used to gather data directly from the respondents and to assess their posture, tasks, and work environment. RULA scores show that 53 out of 139 workers (38%) experience medium to very high MSD risk. Chi-square test of significance and correlation test results show that there are fourteen (14) statistically significant factors with moderate linear relationships that affect the productivity of the workers. Safety measures, surface features, tool features, tool activities, illumination, and ventilation are the main categories that should be given utmost importance for improvement in every workplace. Health issues and efficiency have a weak degree of relationship with productivity, but further analysis show that there are factors under these variables that need consideration.
Keywords— Ergonomics; Shoe Manufacturing Industry; Linear Regression; Correlational Research; Health Issues