Predictors of health-promoting behaviour index among employees of different ages across adulthood
Faculty of Business and Management, Universiti Sultan Zainal Abidin (UniSZA), Gong Badak Campus, 21300 Kuala Nerus, Terengganu Darul Iman, Malaysia.
Research Article
World Journal of Advanced Research and Reviews, 2019, 04(01), 001-005
Article DOI: 10.30574/wjarr.2019.4.1.0072
Publication history:
Received on 31 September 2019; revised on 08 November 2019; accepted on 10 November 2019
Abstract:
Employees who have health problems are often less productive at work. Example of health behaviours are considered costly and risky are smoking, excessive alcohol consumption, poor diet, and lack of physical activity. To control costs and improve health, employers seek solutions that will enhance employee health habits and increase the appropriateness or coordination of their health care. Generation X of Malaysia’s population is expected to increase to 5.6 million, accounting for 15% per cent of the total population in Malaysia. Given the size of these generations, their continued health into older age is essential to ensure the stability of Malaysia’s workforce and economy. Studies on the influence of social support on the health-promoting of employees who maintain close contact with their family and friends associated themselves with better satisfaction. The aims of this study are to assess the predictors of social support on health-promoting behaviour and to develop a health-promoting behaviour index (HPBi) in a representative population. The study was designed as a questionnaire-based, cross-sectional analysis. A sample of 385 respondents comprising of generation X’ers from Kelantan and Terengganu were involved in this study. This study intends to show the effectiveness of Factor Analysis (FA) and Multiple Linear Regression (MLR) for assessing health-promoting behaviour indicator sources. The method of FA has identified five significant index categories- Excellent, Good, Moderate, Low and poor HPBi were generated from FA.
Keywords:
Social support; Mind; Mental health; Factor analysis; Multiple linear regression
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Copyright © 2019 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0