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Description
Abstract
This descriptive survey research focused on satisfaction in life and how it is affected by other variables. The respondents of the study are 115 personnel of the Maritime Academy of Asia and the Pacific (MAAP). The study was completed in the first quarter of 2024. The study determined the respondents’ demographic profile, lifestyle, health status, wellness, stress level, and job and life satisfaction. Results show that health status is associated with lifestyle factors such as food intake, physical exercise, and hours of sleep. The study also reveals that life satisfaction is influenced by marital status, health condition, and job satisfaction in terms of compensation. The study recommends further enhancement of the wellness program in order to promote a better health status and lifestyle to attain higher satisfaction in life.
Keywords: Effects, lifestyle, satisfaction, wellness
- Introduction
Personnel in any institution need to be fit in all aspects of life in order to perform their duties properly. Physical, mental, and even emotional facets of life have been the focal point of much research aiming to increase the productivity amongst personnel. Life satisfaction includes a variety of factors that enable a person to carry out any task to the best of his ability. Diener & Tay (2012), as cited by Unanue et al. (2017), explained that a growing body of research has shown that higher life satisfaction is associated with several desirable company' results, such as higher career satisfaction, organizational commitment, and especially job satisfaction.
The study analyzed the profile, lifestyle, health status, wellness, stress, and job and life satisfaction of the employees of the Maritime Academy of Asia and the Pacific. The study grounded its framework in the bottom-up theory of life satisfaction, which explained that life satisfaction is a result of satisfaction in the many domains of life (Ackerman, 2018). The attainment of life satisfaction cannot be attributed to a single domain or factor. Hence, this study explored the different contributing variables in achieving life satisfaction.
The study answered the questions: (1) Is there a significant association between health status and lifestyle? And (2) which among the variables, singly or in combination, significantly influence the satisfaction in life?
- Methods
2.1 Research Design
The study is descriptive-correlational research and employed a survey method which aims to measure life satisfaction and determine how it is influenced by other variables such as demographic profile, health status, lifestyle, wellness, stress level, and job satisfaction.
2.2 Participants and Procedures
The respondents of the study are the personnel of the Maritime Academy of Asia and the Pacific (MAAP) located in Mariveles, Bataan, Philippines. The questionnaires were handed out to the respondents. There were 131 retrieved accomplished questionnaires, but only 115 are considered due to incomplete responses. The study was completed in the first quarter of 2024.
2.3 Instruments and Materials Used
The instruments used in the study determined the demographic profile; lifestyle, adopted from Dubasi et al. (2019) and Fortier (2015); health status (in terms of BMI, waist-to-hip ratio, and physical and health conditions); wellness, based on items enumerated by Swarbrick and Yudof (2014); stress level, adopted from Cohen & Williamson in 1988; job satisfaction, based on ESS from Betterteam.com; and life satisfaction, adopted from Diener et al. in 1985. The Cronbach alpha coefficients of the instruments calculated from the first 15 randomly selected participants are .9498, .914, and .9178 for wellness, job satisfaction, and life satisfaction, respectively, showing ‘excellent’ internal consistencies, and .703 for the Stress level, interpreted as acceptable.
2.4 Data Analysis
The responses are encoded and treated using Excel and IBM SPSS. Descriptive statistics are used to analyze the responses. Relationships between variables are established using the Spearman Correlation test, while the Multiple Regression Analysis determined the influence of the independent variables on life satisfaction.
2.5 Ethical Considerations
Ethical guidelines are followed to protect the rights, dignity, and welfare of participants. Prior to participation, respondents were informed about the purpose of the study and the procedures involved. All data collected are used strictly for research purposes, and all personal identifiers are removed from the final dataset before analysis.
- Results and Discussion
The results show that the respondents have varying demographic profiles based on age, educational attainment, marital status, and number of years in the institution. Generally, respondents have normal health status (based on BMI) and moderate health risk (based on waist-to-hip ratio). They perceived themselves to be in good health. They sleep for 6 to 10 hours every day and do light to intense exercise at least 4 to more than 6 times a week. They are non-smokers and drink wine or liquor on special occasions only. They highly consume fruits and vegetables. They manifest high intellectual, emotional, social, spiritual, occupational, and financial wellness but with a moderate level of physical wellness. They have a moderate stress level and are highly satisfied in terms of benefits, career, work environment, and culture but moderately satisfied with compensation. Lastly, they are moderately satisfied in life.
Table 1
Spearman Correlation Coefficients (rho) between Lifestyle and Health Status
Lifestyle Health Status
BMI Waist-to-Hip Ratio Physical Condition Health Condition
Sugar and Honey intakes .318 .044 .134 .002
Saturated Fat intakes .250 -.089 .106 -.029
Dressings intakes .200 -.006 .096 -.012
Light exercise .093 -.193 -.012 .099
High intensity (Vigorous) exercise .219 -.102 -.079 .261
Wine Consumption -.040 .080 -.110 .305
Smoking Habits -.185 .209 -.004 -.191
Hours of Sleep -.158 .101 .020 .310*
p<.05, ** p<.01
The Spearman rank correlation coefficients reveal significant relationships. BMI has positive associations with high-intensity exercise and intakes of sugar, honey, saturated fat, and dressings, but it is negatively associated with smoking. The waist-to-hip ratio has a positive association with smoking but is negatively associated with light exercise. Lastly, health condition has positive associations with wine consumption, hours of sleep, and high-intensity exercise, but is negatively associated with smoking.
Multiple regression analysis uncovered significant influences on the respondents’ life satisfaction.
Table 2
Multiple Regression Analysis on Independent Variables Predicting Satisfaction in Life
Variable B SE β t-statistic Prob.
(Constant) -2.224 1.891 -1.176 .245
Marital Status .348 .166 .265 2.096 .041
Health Condition .433 .177 .261 2.445 .018
Compensation .345 .174 .293 1.984 .050
Dependent Variable: Satisfaction in Life
R-square: .675
Adjusted R-squared: .478
F-statistic: 3.423
Prob (F-statistic): .000
Marital status, health condition, and compensation significantly influence life satisfaction. Based on unstandardized beta (B), life satisfaction increases by .345 and .433 for every one-unit increase in compensation and in health condition, respectively. Lastly, the data reveals that the lowest life satisfaction is among singles, followed by separated and annulled, married, and widows. The disparities in each marital status are about .348. The study proved that life satisfaction is defined by combinations of factors.
- Conclusion
Health status is significantly associated with lifestyle, such as food intake, physical activities, and habits. Whereas, life satisfaction is influenced by combinations of factors that include marital status, health condition, and job satisfaction in terms of compensation.
In order to achieve maximum life satisfaction, the study recommends enhancement of the institution's wellness program for personnel.
Acknowledgment
The researchers wish to extend their deepest gratitude to the personnel of the Maritime Academy of Asia and the Pacific for participating in this study. Appreciation also goes to the Academics Research Unit as well as the printing office for the support in the completion of this study.
References
Ackerman, C. (2018). Life Satisfaction Theory and 4 Contributing Factors. https://positivepsychology.com/life-satisfaction/Betterteam (n. d.). Employee Satisfaction Survey. https://www.betterteam.com/employee-satisfaction-survey
Betterteam. Employee Satisfaction Survey. https://www.betterteam.com/employee-satisfaction-survey
Dubasi, SK, Ranjan, P., Arora, C., Vikram, N., Dwivedi, SN., Dwivedi, N.,
Kaloiya, G., & Shalimar (2019). Questionnaire to assess adherence to diet and exercise advices for weight management in lifestyle-related diseases. https://pmc.ncbi.nlm.nih.gov/articles/PMC6436250/
Fortier, J. (2015). The Simple Lifestyle Indicator Questionnaire and its association with health-related quality of life and well-being. https://core.ac.uk/download/pdf/33557183.pdf
NovoPsych (n. d.). Perceived Stress Scale by Cohen & Williamson in 1988. https://novopsych.com/assessments/well-being/perceived-stress-scale-pss-10/
NovoPsych (n. d.). Satisfaction with Life Scale by Diener, Emmons, Larsen, & Griffin in 1985. https://novopsych.com/assessments/well-being/perceived-stress-scale-pss-10/
Swarbrick, P., and Yudof, J. (2014). Wellness In Eight Dimensions. https://www.state.nj.us/humanservices/dmhas/resources/mental/CSP_Wellness_8_Dimensions.pdf
Unanue, et al. (2017). Revisiting the Link between Job Satisfaction and Life Satisfaction: The Role of Basic Psychological Needs. https://www.frontiersin.org/articles/10.3389/fpsyg.2017.00680/full
