THE INFLUENCE OF SOCIOECONOMIC CHARACTERISTICS ON QUALITY OF LIFE VARIATIONS IN RURAL COMMUNITY

Copyright © ISRG Publishers. All rights Reserved. DOI: 10.5281/zenodo.17519240 67 ISRG PUBLISHERS Abbreviated Key Title: ISRG J Arts Humanit Soc Sci ISSN: 2583-7672 (Online) Journal homepage: https://isrgpublishers.com/isrgjahss Volume– III Issue -VI (November - December) 2025 Frequency: Bimonthly THE INFLUENCE OF SOCIOECONOMIC CHARACTERISTICS ON QUALITY OF LIFE VARIATIONS IN RURAL COMMUNITY Amatari - Breford Sinclair Amatari (PhD)1* & Edith Ebinemi Imaitor (PhD)2 1 & 2 Department of Geography, Isaac Jasper Boro College of Education, Sagbama, Bayelsa State, Nigeria | Received: 25.10.2025 | Accepted: 01.11.2025 | Published: 04.11.2025 *Corresponding author: Amatari - Breford Sinclair Amatari (PhD) Department of Geography, Isaac Jasper Boro College of Education, Sagbama, Bayelsa State, Nigeria INTRODUCTION Socioeconomic characteristics such as age, education, occupation, income as well as access to resources plays a significant role in shaping the quality of life (QoL) in communities. QoL in communities connotes a multifaceted concept that encompasses diverse aspects of human well-being, including physical health, mental health, social relationships and economic stability. Abstract This study examined the influence of socioeconomic characteristics on quality of life variations in. fifteen (15) purposively selected communities in Southern Ijaw Local Government Area of Bayelsa State. To achieve set goal, three key objectives and a hypothesis was formulated. Survey method was used to collect primary data: a questionnaire was administered on 120 respondents extracted through the simple random sampling technique, where key socioeconomic factors such as age, income, education and occupation and their influence on overall quality of life were reviewed. Data collected were analyzed using both descriptive and statistical methods. The results of the descriptive analyses showed that socioeconomic characteristics largely influenced quality of life variations, with lower communities facing greater challenges in accessing health care, education and economic opportunities. Also, results of the statistical analysis of ANOVA showed that F-ratio value 822.935 was greater than tabulated value 3.84 and also the P-value 0.000 was less than the significant 0.005; suggesting that socioeconomic characteristics significantly influenced quality of life. Similarly, the coefficients revealed that all t-values were greater than tabulated value 1.645 and the p-value 0.000 was less than 0.05 level of significance, thus agreeing with the decision of the ANOVA test. The study results underscored the need for targeted interventions and policies that address the unique needs or diverse communities, promoting more equitable access to resource and opportunities for improved quality of life Keywords: Socioeconomic factors, Quality of Life, Rural communities and variations. Copyright © ISRG Publishers. All rights Reserved. DOI: 10.5281/zenodo.17519240 68 Researchers have constantly shown that individuals from lower socioeconomic backgrounds are more likely to experience poor health outcomes, limited educational opportunity and reduced economic mobility. For instance, low-income communities often lack access to quality healthcare services, healthy food options and safely environment, exacerbating health problems and reducing life expectancy. Similarly, limited access to quality education can hinder economic mobility and perpetrate cycle of poverty. Despite the importance of socioeconomic characteristics in determining QoL, significant variations persist across different communities. These variations can be attributed to various factors including systematic inequalities, discretionary policies and lack of access to resources. A good understanding of the relationship between socioeconomic characteristics and QoL is crucial for developing effective policies and intervention that address these variations and promote more equitable society, guaranteeing improved QoL. The United Nations (2010) QoL index study report showed their Nigeria is placed 156 out of 187 countries in QoL ranking. However, despite that poor ranking, QoL studies are noticeably rare (Solomom & Adewale,2011). Hence, it would be beneficial if QoL studies are carried out to unearth of dynamic nature as well as its determinants It is against this backdrop that this study is undertaken to examine the influence of socioeconomic characteristics on QoL variation by examining the complex interplay between such socioeconomic factors and QoL: to identify key determinants of QoL and suggest policy decisions that promote more equitable and sustainable development. The hypothesis of the study stated that socioeconomic characteristics of the people significantly affect QoL. THEORETICAL AND CONCEPTUAL REVIEW According to Offor, Epelle & Obiyai, (2017), the use of theories and concepts that support specific research is a key aspect of research design. Hence, this paper drew its theoretical framework from the cumulative disadvantages theory (CDT). The CDT emerged for the first time in sociology from the pioneering works of Merton (1968), focusing on intra cohort differentiations. Dennefer, (2003), stated that the CDT emphasized that socioeconomic disadvantages accumulate over time, leading to increase health risks and poor quality of life. Similarly, Seffersten, (1999), posited that the CDT provides a framework for understanding how socioeconomic factors intersect and impact individuals and communities; underscored that socioeconomic disadvantages such as low-income, inadequate education and unemployment can accumulate over time, exacerbating health problems and poor QoL. Also, Shrira & Litwin (2014), noted that the CDT considers the impact of socioeconomic disadvantages across life course from childhood to old age, stressing that corresponding targeted interventions addressing specific socioeconomic disadvantages can help mitigate such cumulative effects on individuals and communities. There are a lot of evidence which supports the effect of CDT on measures of IQ, income and status attainment among others (Crystal & Shea, 2003; O’Rand, 1996). Highlighting the causes of CDT Preston, Hill & Drevenstedt (1998), noted that people are disadvantaged because of genetic or environmental factors and those disadvantages also accumulate with far reaching implications for good QoL for individuals and communities. THE CONCEPT OF QUALITY OF LIFE The concept of QoL has attracted a lot of researches and policy attention in recent times amongst social scientists and other professionals (Olapegba, 2010); yet a universally acceptable definition is far-fetched (Du & Peter, 2016). However, the WHO defined QoL as the individuals’ perception of their position in life, in terms of the culture and value systems in which they live and in relation to their goals, expectations, standards, and concern (WHO, 2007). Hence, in order for measures of QoL to have meaning, individuals’ point of view must accurately represent (Pacione, 2003). Researchers contend that the construct of QoL is multidimensional and contains both objective and subjective aspects (Wills-Herrera et al, 2009). QoL can be described as a broad ranging concept that is affected by a person’s physical health, psychological state, level of independence and their relationships to Salient features of the environment (Solomon &. Adewale, 2022). They further noted that QoL focuses on all facets of life which includes cultural, social, environmental, physical, health, and the social value systems, etc. Likewise, Kele (2012) posted that QoL is affected by certain factors, which include housing, leisure and recreation, economic stability, neighbourhood environment and availability and access to basic goods and service. Also, he noted that community QoL connotes a group of socioeconomic and environmental indicators, including but not limited to income, educational attainment and social status. Boroah, Dineen and lunch (2011), reported that even within communities, it can be noted that variations in income, employment status, educational attainment and availability and access to basic amenities influences differences in QoL experiences. According to Stiglitz et al (2011), QoL can be measured using personal determinants such as age, education, income, occupation, marital status etc. Similarly, Boncinelli and Casini (2014), highlighted the basic determinants of QoL to include health, income, education, employment status, politics, environments, infrastructure, to mention a few. SOCIOECONOMIC CHARACTERISTICS AND QOL Socioeconomic characteristics strongly influence QoL by shaping access to resources and opportunities leading to better health outcomes and overall well-being for those with higher status, and poorer QoL for those with low status (Solomon & Adewale, 2022). they noted that key factors such as income, education and occupation largely determine access to quality housing, nutrition, healthcare and social support. A person’s socioeconomic characteristic are powerful indicators of their life opportunities and well-being. Higher socioeconomic status generally leads to better Qol by having greater access to essential goods and services, while lower socioeconomic status is associated with diminished Qol due to limited access to the same factors. Socioeconomic status is a major determinant of housing quality and living environment, which in turn influences health, safety and lifestyle choices that defines QoL. Samli, (2008), noted that without enhanced economic conditions, third world countries would face harsh condition that engenders poor QoL. Copyright © ISRG Publishers. All rights Reserved. DOI: 10.5281/zenodo.17519240 69 Some studies here addressed the socioeconomic characteristics of residents which affects QoL experiences at individual and community levels. For instance, Grammer et al (2003), concluded that subjective well-being was explained by sex, income, education marital status, health and low population density. According to Chulko and Choi (2015) there was correlation between income and QoL; an increase in economic benefits was most effective means of improving QOL in lower settlements. Likewise, Mohammad, Behjat & fatemeh (2011), studied QoL in relation to socioeconomic status in Isfahan. Results of their statistical analysis shown that there was direct and significant relationship between QoL and socioeconomic status and variables in Isfahan. Senlier, yidiz & Aktas (2008), undertook a comparative study of QoL in selected kocaeli communities in Turkey and European cities, measuring essential determinants of QoL such as occupation, education, income, cost of housing and safety and security, among others. The results of their analysis showed significant variation in QoL in the various cities. MATERIALS AND METHODS The Study Area: The study area has a total of fifteen (15) communities, which comprised of ten (10) bearing communities in the Nun River oil field and five (5) neigbouring communities, which are non-oil/gas bearing; all in Southern Ijaw Local Government Area of Bayelsa State. The sampled communities had a total population of 54,982 (NPC, 2006). The geographical coordinate of the central point of the study area was latitude 404811711 north and longitude 600414411 East. The study area is rich in natural resources which include oil/gas with oil wells in most communities and projects crisiscrossing the area. The major economic activities of the area are agriculture, including fishing, family, forestry/lumbering, gathering of wild forest products and tapping of palm wine and brewing of local gin are the primary economic activities is the areas. Allison – Oguru, Zuofa and Berepubo (1999). Research Design: As earlier stated, the research covered ten (10) oil/gas bearing communities and five (5) neighboring non-oil/gas bearing communities, totally fifteen (15) Communities, all in the Southern Ijaw Local Government Area of Bayelsa State. The total projected population of the research area was 103,608 and sample size for the study was 398, which was determined using the Taro Yamene formula for determining sample size. Consequently, a set of 398 questionnaires was administered to the selected respondents, who were mostly household heads. The questionnaire was administered to the respondents who were selected using simple random sampling technique. Data obtained were analyzed using both descriptive statistics and analysis of variance (ANOVA), been adopted to test the only hypotheses which state that Socioeconomic characteristics of respondents significantly affect their QoL. RESULTS AND DISCUSSIONS This section provides a clear understanding of the research findings and their significance as well as enlightens the audience on how the results are presented to achieve the objectives of the study. Analyses of data were presented under the following sub-headings: Age: Age is an important socioeconomic attribute, which has impact on the perception of residents’ QoL (Solomon & Adewale, 2022). According to Bovaird & Loffler (2005), the older and younger people perceive Qol differently based on their life experiences. The age of household heads was grouped into five categories for ease of analysis. Fig 1: Distribution of age for Nun River Oilfield Communities and their Neighbours. Source: Field Survey 2025 Age distribution of respondents in Fig 4.4 revealed that 50 (23%) of the respondents in the Nun River Oilfield Communities were less than 30 years, 113 (51%) were between 30-39 years, 37 (17%) were between 40-49 years, 12 (5%) of the respondents were between 50-59 years and 8 (4%) of respondents were 60 years and above. The table also showed that in the Neighboring Communities 15 (13%) of the respondents were less than 30 years, 78 (65%) were between 30-39 years, 17 (14%) were between 40-49 years, 5 (5%) were between 50 -’ 59 years and 4 (3%) of respondents were 60 years and above. Educational attainment: Educational attainment is an important socioeconomic factor with far reaching impact on QoL rating (Solomon & Adewale, 2022). Nussbaum (2020) posited that individuals with higher educational attainment tend to report better QoL, citing factors such as improved economic stability, better health outcomes and enhanced personal growth, satisfaction and social participation. Likewise, personal observation showed that Copyright © ISRG Publishers. All rights Reserved. DOI: 10.5281/zenodo.17519240 70 respondents with higher educational levels indicated higher QoL ratings. Fig 2: Educational attainment of respondents from Nun River Oilfield Communities and their Neighbours. Source: Field Survey 2025 As shown in Fig 2, in the Nun River Oilfield Communities 22 (10%) of the respondent’s highest educational qualification was informal education, 43 (20%) had FSLC, 72 (33%) had WAEC, 38 (17%) of the respondents had OND/NCE, 30 (14%) of the respondents had HND/B.Sc, 10 (5%) of the respondents had M Sc, and 3 (1%) of the respondents had PhD. On the other hand, in the Neighbouring Communities 7(6%) of the respondents had informal education, 14 (12%) had FSLC, 40 (33%) had WAEC, 33 (27%) had OND/NCE, 24 (20%) had HND/BSc, 1 (0, 8%) of the respondents had M.Sc and 1 (0.8%) of the respondents had PhD as their highest educational qualification. Income Level of Respondents Fig 3: Monthly income of respondents from Nun River Oilfield Communities and their Neighbours. Source: Field Survey 2025 Results from the Nun River Oilfield Communities on monthly income showed that 86 (39%) earned less than N70, 000; 12 (6%) earned between N70, 000 – N79, 000; 60 (27%) earned between N80, 000 – N89, 000; 24 (11%) earned between N90, 000 – N99, 000 and 38(17%) earned N100, 000 and above. On the other hand, in Neighbouring Communities 10 (8%) earned less than N70, 000; 16 (13%) earned between N70, 000 – N79, 000; 42 (36%) earned between N80, 000 – N89, 000; 22 (18%) earned between N90, 000 – N99, 000 and 30 (25%) earned N100, 000 and above. Studies have showed that income level impacts QoL. According to Kahneman and Deaton (2010), higher income can: provide basic needs, such a food, shelter and healthcare; offer financial security and enable access to education, leisure and resources. However, the authors noted not the relationship income and QoL is complex because excessive income does not always translate to greater happiness. Occupation of Respondents Fig 4: Occupations of respondents from Nun River Oilfield Communities and their Neighbours. Source: Field Survey 2025 Copyright © ISRG Publishers. All rights Reserved. DOI: 10.5281/zenodo.17519240 71 This Figure showed that 102 (46%) of the respondents in the Nun River Oilfield Communities were farmers, 36 (16%) were fishers, 34 (15%) were traders, 26 (13%) of the respondents were civil/public servants, 5(2%) were company workers; artisans were 10(5%), 5 (2%) were clergy and others were 2 (0.9%) of respondents. In the Neighbouring Communities 34(28%) were farmers, 24 (20%) were fishers, 27 (23%) were traders, 26 (22%) were civil/public servants and 9 (7%) were artisans. Results from cross sectional data analysis revealed that respondents in government employment showed better QoL rating compared to others in the non-formal sector. The occupation of an individual is part of his everyday life, thus, there is no gainsaying that the nature of the occupation or a change of it would affect the individual’s well-being and inadvertently the QoL. Maxwell, Chukwuemeka, Nneka and Kelechi (2014), concluded that occupational factors had negative impact on the QoL of respondents in the nongovernmental sectors than their counterparts in government sector. Testing of Hypotheses: The hypothesis was tested using an appropriate statistical tool i. Ho1: Socio-economic characteristics of the people significantly affect QoL Table 1: Multiple regression of the influence of socio-economic characteristics on QoL Model R R Square Adjusted R Square Std. Error of the Estimate 1 .962a .925 .924 .172 Source: Field Survey, 2025 a. Predictors: (Constant), Household size, Highest Educational Qualification, Age Bracket, Occupation, and Monthly Income. The multiple regression analysis was applied to assess the adequacy of the fitted regression model. It gives the overall prediction power of the model. The result indicates that 0.962(96.2%) of the variation in the model has been explained by the independent variable in the model. Table 2: F-statistics (ANOVA) of the Multiple Regression of the influence of socio-economic characteristics on QoL Model Sum of Squares Df Mean Square F Sig. 1 Regression 121.140 5 24.228 822.935 .000b Residual 9.833 334 .029 Total 130.974 339 Source: Field Survey, 2025 Dependent Variable: QOL Predictors: (Constant), Household size, Highest Educational Qualification, Age Bracket, Occupation, and Monthly Income. Test of goodness of fit for the regression model Y=B0 + B1x1 + B2x2 + B3x3 + B4x4 + B5x5 + e Y= 0.684 + 0.136x1 + 0.168x2 + 0.512x3 + 0.085x4 + 0.228x5 The ANOVA approach is applied to examine the overall influence of the explanatory variable X on the independent variable Y Y=Dependent variable X=Independent variable B0=Intercept B1=Regression coefficient e=Error The ANOVA revealed that F-ratio value 822.935 is greater than the tabulated value 3.84 at 5% level of significant and also, the pvalue 0.000 is less than the 0.05 significant levels. Therefore, the null hypothesis was rejected and the alternative accepted. Table 3: Coefficients of the Multiple Regression of the influence of socio-economic characteristics on QoL Model Unstandardized Coefficients Standardized Coefficients B Std. Error Beta T Sig. 1 (Constant) .684 .033 20.481 .000 Age Bracket .136 .031 .201 4.359 .000 Highest Educational Qualification .168 .025 .357 6.818 .000 Occupation .512 .018 1.284 27.972 .000 Monthly Income .085 .023 .199 3.728 .000 Source: Field Survey, 2025 Dependent Variable: QOL The coefficient table 3 revealed that all the tvalues for B1, B2, B3, and B4, were greater than the tabulated value 1.645 at 5% level of significant and also, the p-value 0.000 is less than 0.05 level of significant. This implies that all the coefficients are significant and this agrees with the decision of the ANOVA test. CONCLUSION This study revealed the influence of socioeconomic characteristics on quality of life (QoL) variations in selected communities. Particularly, the findings of the study highlighted the significant roles that socioeconomic factors, such as age, income, education and occupation play in shaping health outcomes and overall wellbeing of individuals, communities and environmental sustainability. Finally, the outcome of the study has implication for policy makers and community leaders seeking to promote QoL. RECOMMENDATIONS To address these variations, policy makers should consider the following recommendations. 1. Government and development partners should provide opportunities for individuals to acquire skills and knowledge that can improve their socioeconomic status. 2. Implement policies to address socioeconomic disparities, such as increasing access to healthcare, education and job training programmes. Copyright © ISRG Publishers. All rights Reserved. DOI: 10.5281/zenodo.17519240 72 3. Deliberately support community-based initiatives that promotes social capital, neighborhood safety, and community engagement. 4. Increase access to basic amenities, particularly for disadvantaged communities. REFERENCES 1. Allison-Oguru, E.A. Zuofa, K. & Berepubo, N.A. (1999). Agriculture in E.J. Alagoa (ed). The land and people of Bayelsa State, Central Niger Delta. Onyoma Research and publications, Port Harcourt, Rivers State, Nigeria 2. Boncinelli, F. Pagnotta, G. Ricilli, F. & Casini, L. (2014). The determinants of quality of life in rural areas from a geographic perspective: the case of Tuscany. Review of Urban and Regional Development Studies, Vo. 27, (2),82-89. 3. Boroah, V. K. Dineen, D.A. & Lynch, N. (2011). Health, employment and the quality of life in Ireland. Irish Journal of Sociology, 19 (2), 144-151. 4. Bovarid, T., and Loffler, E., (2003). Evaluating the quality for public governance: Indicators, models and methodologies. International Review of Administrative Science. Pp 313. 5. Chulko K M. & Choi S. O. (2015). The Effects of Community Quality of Life on Local Policy Decisions. Applied Research Quality of Life (2015) 10: 667-687. 6. Crystal, S & Shea, D (2003). Cumulative advantage, public policy and late-life inequality. In Crystal S, Shea D (Eds), Economic outcomes in later life: public policy, health and cumulative advantage, New York: Springer. 7. Dannefer D., (2003). Cumulative advantage/disadvantage and the life course: cross-fact loging age and social science theory. J. Gerontol 58:5327 8. Du, S. Bhattacharya, C. & Sein, S. (2010). Minimizing business returns to corporate social responsibility? The role of CSR communication. International Journal of Management Review, (2), 8-19. 9. Gramer V., Togersen. & Kringers E. (2004) Quality of Life in a City; The Effect of Population Density. Social Indicator Research 69: 106-116 (2009). 10. Kahneman, D. & Deaton, A. (2010). High income improves evaluation of life but not emotional wellbeing. Proceedings of the National Academy of Sciences, 107 (38) 16489-16493. 11. Kele, R. (2012). The quality of life and the environment. Social and Behavioural Sciences, 35, 23-32. 12. Kpolovie P. J (2011) Statistical Techniques for Advanced Research. Owerri, Imo State; Springfield Publishers Ltd. 13. Maxwell, O. A. Chukwuemeka M. U. & Nneka, I. (2014). Effect of occupational factors on the quality of life of workers in Government and Non-governmental sectors in Nigeria. Tropical Journal of Pharmaceutical Research, 13 (2) 287-293 14. Merton R.K., (1968). The Mathew effect in Science. Science. 159, 56-63 15. Mohammad K. Behjat Y. K and Fatemeh M. (2011) Study of the Relationship Between Quality of life and Socioeconomic Status in Isfahar.Journal of Education and Health Promotion (Wolters Kluwer-Medknow Publication, 2011). 16. National Population Commission (NPC), 2006 Census Figure, Nigeria 17. Nussbaum, M.C. (2020). The geopolitical tradition: a noble but flawed ideal. Cambridge, Mall, Harvard University Press, 2019, 321 pp 18. O’Rand, A. M., (1996). The precious and the precious: Understanding cumulative disadvantage and cumulative advantage over the life courses. The Gerontologis 36, 2338. 19. Offor I. J, Epelle P.A. & Obiyai K. K. (2017). Research instrument development for education and social sciences in M. Omoleva, B. O. Level, F. G. Paulley and A. Alyusuf (eds.) Theory and practice of education in Nigeria, 2, 601-614. Port Harcourt, University of Port Harcourt Press. 20. Olapegba, P.O., (2010). Perceived quality of life: Towards a generic measure in Nigeria culture, Ibadan. Journal of the Social Science (in press) 21. Pacuone M., (2003). Introduction on Urban environmental quality and human well-being. Lands Urban Plan. 65(1/2): 1-3. 22. Preston S., Hill, M. and Dreventsted T., (1998). Childhood conditions that product survival advanced ages among African Americans. Social Science and Medical, 47, 1231-46 23. Samli A. C. (2008) Entrepreneurship Economic Development and Quality of Life in Third-World Countries. Applied Research Quality of Life (2008) 3: 203-213. 24. Senlier, N. Yidiz, K. & Aletas, D. (2008). A perception survey for the evaluation of urban quality of life in Kocaeli and a comparison of the life satisfaction with the European cities. Soc. Indic. Res. (2009) 94:213-226. 25. Shrira, A & Litwin, H (2014). The effect of lifetime cumulative adversity and depressive symptoms on functional status. The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 69, 953-965 26. Solomon A. O., and Adewale, O.U., (2022). Impact of socioeconomic factors on resident’s quality of the life in metropolitan Ibadan, Nigeria. International Journal of Infrastructure Research and Management, 10 (2) 12-26 27. SPDC (1998) Environmental Impact Assessment for Drilling of New Wells in Nun River, Shell Petroleum Development Company of Nigeria. 28. Stiglitz, J., Sen, A., & Fitoussi, J. P. (2011). Report by the Commission on the Measurement of Economic Performance and Social Progress. 2009. Dostupné z: www. stiglitz-sen-fitoussi. fr. 29. Wills Herrera, E., Islam G., and Ham Hon M., (2009). Subjective well-being in cities: a multidimensional concept of individual, social and cultural variables. Applied Research Quality of life. 4(2) 201-221. 30. World Health Organization (2007). WHO AOC User Manual. WHO/MHN/MHP/98.4 downloaded from www.who.int/mental-health/evidence who. gol-usermanual 98 on December, 2008.