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- International Journal of Management (IJM) Volume 11, Issue 3, March 2020, pp. 166–174, Article ID: IJM_11_03_018 Available online at http://www.iaeme.com/ijm/issues.asp?JType=IJM&VType=11&IType=3 Journal Impact Factor (2020): 10.1471 (Calculated by GISI) www.jifactor.com ISSN Print: 0976-6502 and ISSN Online: 0976-6510 © IAEME Publication Scopus Indexed SOCIOECONOMIC AND DEMOGRAPHIC CORRELATES OF SELF RATED HEALTH AMONG ADULTS IN ALKHARJ AREA KSA, 2017 Dr. Ayman Mahgoub College of Business Administration Prince Sattam Bin Abdulaziz University, Saudi Arabia am.mohammed@psau.edu.sa ABSTRACT Aim: Self Rated Health (SRH) is a widely used measure of subjective assessment of health status. SRH has been found to carry predictive validity concerning future mortality among diseased and healthy individuals. Several socioeconomic and demographic characteristics of individuals found to have an association with their overall assessment of health. The objectives of this study are to estimate the proportion of the healthy adult population using SRH measure and to identify the socioeconomic, demographic and health correlates of SRH among the adult population. Methods: A cross-sectional study was conducted in the Alkharj area in the center of Saudi Arabia, using a questionnaire comprising the basic questions relating to SRH and the socioeconomic and demographic correlates of SRH. Univariate and logistic regression models were carried out to analyze the data. Results: Mode of living, age class, education, marital status, the prevalence of diseases and risky behavior of individuals were significantly associated with SRH in the study area. Individuals with diabetes and those who drink alcohol were more likely to be unhealthy compared with other individuals in the sample. Conclusion: The results reveal a correlation between socioeconomic and behavioral factors with SRH; these factors should be given high priority in the setting of health strategies and policies. Keywords: Self Rated Health, Cross-sectional, Adults in Alkharj, Saudi Arabia Cite this Article: Dr. Ayman Mahgoub, Socioeconomic and Demographic Correlates of Self Rated Health among Adults in Alkharj Area KSA, 2017, International Journal of Management (IJM), 11 (3), 2020, pp. 166–174. http://www.iaeme.com/IJM/issues.asp?JType=IJM&VType=11&IType=3 http://www.iaeme.com/IJM/index.asp 166 editor@iaeme.com
- Dr. Ayman Mahgoub 1. INTRODUCTION The concept of self-rated health (SRH) is considered a multidimensional concept that refers to an individual's assessment and perception of his\her own health status. The concept has been widely used in health surveys in recent decades. Of note, it is an inexpensive instrument and it also has trusted reliability among all age groups, for both men and women (Liang, 1986; Bombak, 2013). During the past decades, SRH has been increasingly involved in the national and international public health monitoring and has been recommended as a standard part of health surveys. Also, SRH has been used to measure clinical outcomes in epidemiological studies (Robine et al., 2003). Currently, it is proposed to be a critical tool in the clinical assessment as well as the primary prevention screening procedures (Bombak, 2013). Changing the life situation and lifestyle as well as the characteristics of individuals proposed to have an association with the overall health condition. SRH has been found to carry a predictive validity concerning future mortality, not only among diseased but also among healthy individuals. Several socioeconomic and demographic characteristics of individuals found to have an association with their overall assessment of health (Idler & Benyamini, 1997 ; Strawbridge & Wallhagen, 1999). A consistent inverse association was stabilized by age, sex and social status (Miilunpalo et al., 1997). Moreover, socioeconomic status was proved to influence the health status that may also attribute to psychosocial well- being (Richter et al., 2012; Moor et al., 2017). Various characteristics may affect the SRH; the age of specific gender, mode of living, educational level, marital status, work status, type of work, frequent diseases, as well as risky behavior of individuals such as smoking and obesity. The prevalence of harming health owing to demographic characteristics or socioeconomic status are considered to be high in the United States and the UK, especially the individuals with low income who were more likely to report poor/fair health (Kennedy et al., 1998 ; Weich et al., 2002). However, it is still under-studied in KSA. We conducted this study specifically in the Alkharj Area, because of its economical, strategical, and cultural importance in the Kingdome of Saudi Arabia. 2. OBJECTIVES The objectives of this present study are to estimate the proportion of the healthy adult population in the Alkharj area in the Kingdom of Saudi Arabia using SRH measure and to identify the socioeconomic, demographic and health correlates of SRH among this population. 3. HYPOTHESES • The mode of living is positively associated with the SRH. • The age groups of the cases will be significantly associated with SRH; older cases will have less SRH than younger cases. • The educational level, work status, and socioeconomically status were positively associated with the SRH. 4. METHODS AND MATERIALS 4.1. Participants A survey had been carried out to obtain the primary data needed to estimate a healthy population using the SRH method covering all the study areas in the Alkharj area. Al Kharj, also known locally as Al Saih, is a city in Al Kharj Governorate in central Saudi Arabia. The total population of the area is 425300 individuals. http://www.iaeme.com/IJM/index.asp 167 editor@iaeme.com
- Socioeconomic and Demographic Correlates of Self Rated Health among Adults in Alkharj Area KSA, 2017 4.2. Questionnaire Our primary exit was to measure SRH through a few simple questions. Respondents were asked to indicate how they rate their health in general and/or in comparison with other people of their age. The key question in SRH is "How would you describe your state of health these days or this year", Usually, SRH is measured on a five Points Likert-scale, with options been; "1 = very good, 2 = good, 3 = moderate, 4 = bad, 5 = very bad ", whereas 1,2,3 recorded in the tables as “healthy” and 4,5 recorded as “non-healthy”. The household questionnaire used was consistent of limited and specific questions that were asked to the head of the household and covered the following dimensions: (i) demographic characteristics: gender and age, (ii) social characteristics: mode of living, education, and maritime status, (iii) economic characteristics: occupation of the head of household, daily consumption, and work status, and (iv) health characteristics: health status, disability, diseases and risky behaviors such as smoking, obesity, and drinking. 4.3. Sample Size The equation to determine the simple random sampling was used depending on the population proportion, the equation takes the following form (Cochran, 1963) : z 2 * p * (1 − p) n *= d2 Where: n *: the initial sample size. Z: the standard variable of the normal distribution corresponding to a 95% confidence level. P: the anticipated population distribution of good SRH. D: the absolute statistical precision on either side of the anticipated population proportion. By taking P = 50% which gives the maximum possible sample size and d = 0.05 then, the initial sample size will be: 4 * 0.5* 0.5 = 400 0.0025 However, in the actual field survey, simple random sampling was not the method of data collection and the clustered random sampling had been used, this requires multiplying the sample size by the design effect which taken to be (2), hence, the actual sample size was calculated at 800. The response rate was about 75%; the sample was collected from the 800 participants through face to face questionnaire, in many clusters, such as universities, government associations, NGOs, markets and streets. 4.4. Data Analysis Analysis of the data was conducted using SPSS for Windows (IBM SPSS Statistics Version 20.0 Released 2011 Armonk, NY: IBM Corp.) and Excel software. Different methods of analysis were carried out to meet the study objectives including estimation of healthy proportion using SRH measure, the descriptive statistics, the inferential statistics which include the Chi-square test, and the binary logistic regression model (Hosmer & Lemeshow, 2000). http://www.iaeme.com/IJM/index.asp 168 editor@iaeme.com
- Dr. Ayman Mahgoub 5. RESULTS 5.1. The Association between SRH and Socioeconomic Status and Demographic Characteristics The results reveal that no significant association was found between SRH and mode of living, as shown in the (table 1), so that, the percentages of healthy respondents were (90.8%) and (89.6%) in urban and rural areas respectively, which indicates indifference in SRH according to the mode of living in the study area. SRH has a highly significant correlation with the gender of respondents, males have a higher percentage of good SRH (91.8%) compared with (88.1%) for females, as the P-value was (
- Socioeconomic and Demographic Correlates of Self Rated Health among Adults in Alkharj Area KSA, 2017 SRH and work status were significantly associated, the percentage was calculated at (89.2%) among individuals who were not working in a period of 12 months before the survey was conducted, whereas, the percentage was calculated at (92.5%) among those individuals who were working in the same period, as shown in (table 1), as the P-value was (
- Dr. Ayman Mahgoub The only significant category for the variable of marital status was the widowed individuals who were (2.884) times more likely to be unhealthy compared with the single respondents as a reference category, as the P-value = 0.018. Regarding the diseases among responders, pneumonia infected respondents were (5.113) times more likely to be unhealthy compared with the reference category, as the P-value > 0.001, while those individuals who were suffering from diabetes were (28.112) times more likely to be unhealthy compared with free-diseases individuals, as the P-value > 0.001. Smoking and drinking alcohol were significantly affecting SRH, smokers individuals were (1.724) times more likely to be unhealthy compared with free-risky behaviors individuals (the reference category), as the P-value = 0.012, while those individuals who drank alcohol were (7.094) times more likely to be unhealthy compared with the reference category, as the P-value = 0.003. Table 3. Odd Ratio of Binary Logistic Regression, SRH (1= unhealthy) variable Odds Ratio p value Mode of Living (1=Rural) 1.506 0.010* Gender (1= female) 1.363 0.014* Less 15 1.000 (ref) Age Class 15-64 1.237 0.365 65+ 3.181
- Socioeconomic and Demographic Correlates of Self Rated Health among Adults in Alkharj Area KSA, 2017 KSA. Our findings suggest outlining the possible risk factors for unhealthy SRH, that include living in rural areas, female gender, older age group (65+), individuals with basic educational level and widowed individuals as well as smokers, obese personnel, and who drinks alcohol. In spite of the significant difference between individual categorized based on work status, work status of respondents did not have any statistically significant effect on SRH. In a national health survey in Pakistan including 18135 individuals between 1990 and 1994, the authors concluded that older age groups more than 20 years, female gender, living in rural areas, low and middle socioeconomic status, illiterate individuals, widow or divorced individuals and current smoking participants are risk factors for poor/fair SRH. However, work status was not investigated in this study (Ahmad, 2005). In a short report of Spanish National Health Interview Surveys among 2261 adolescents, it was found that smoking is associated with suboptimal self-perceived health and health problems (Rius et al., 2004). Our study showed that smokers are 1.7 times more likely to have unhealthy SHR. Regarding gender, our results showed a significant difference between males and females, with a significant effect of female gender on unhealthy SRH, which is consistent with another cross-sectional report. This study was carried out among 6997 School-aged Children; the risk of having poor self-rated health was higher in low affluent girls than low affluent boys (Richter et al., 2012). In Europe, socio-economic status was found to affect SHR through several factors, concerning material and occupational conditions (Aldabe et al., 2011). In a comprehensive survey in Norwegian, lower education was attributed to poor health which suggested a deep focus on this particular group to improve the material and psychosocial conditions as well as the cessation of smoking (Kurtze et al., 2013). In a recent systematic review that included publications between 1996 and 2016, the results showed the dual role of material factors on self-rated health including its direct and indirect effect, through psychosocial and behavioral factors which indicated an improvement in the material circumstances among lower affluent groups (Moor et al., 2017). Regarding marital status, our results revealed a significant difference among all marital status categories; however, only widowed individuals were more likely to be unhealthy in comparison to single persons. This may have been explained by the protective and supportive role of marriage. It was also found that the duration of widowhood could have a negative impact on the health and the risk to develop diabetes, psychological distress and worse SRH (Perkins et al., 2016). The prediction value of SRH was significantly associated with the prevalence of diseases in our study, diabetes, and pneumonia infected respondents were more likely to have unhealthy SRH. Singh-Manoux et al. deduced that SRH is a good predictor of mortality especially along with the short term (Singh et al., 2007). Also, literature review and large wide analytic studies are consistent with the aforementioned findings that SHR could predict mortality more than the diagnosed disease phase (Idler& Benyamini, 1997 ; Strawbridge & Wallhagen, 1999). Also, it is currently found that subjective SHR is the best predictor of retirement over than diagnosed disease since physical and mental fatigue could be decreased and health conditions may improve after retirement (Nilsson et al., 2016 ; Laaksonen et al., 2012). This is the first study to investigate SHR value and the potential variables affecting its score in the Alkharj area in KSA. However, our study has several limitations; (1) we did not have any information regarding participants’ health on an extended follow-up, (2) lack of random sampling plan, hence the results represent the studied area, not all KSA. (3) Participants ‘age was varied which may affect other parameters. http://www.iaeme.com/IJM/index.asp 172 editor@iaeme.com
- Dr. Ayman Mahgoub 7. CONCLUSION Population health is one of the essential components of human development. The study of the health status of individuals and the impact of various diseases on mortality and disability is essential for health prevention planning and health promotion. The importance of this study stems from the value of identifying the variables correlated with the overall health of individuals. The study also achieved a pioneering step in applying the concept of self-rated health in the study area as well as identifying the socioeconomic, demographic and health correlates of self-rated health. This study revealed that the mode of living, age class, education, marital status, the prevalence of diseases and risky behavior of individuals were significantly associated with SRH in the study area. Also, individuals with diabetes and those who drink alcohol were more likely to be unhealthy compared with other individuals in the sample. Restrict follow-up and preventive measures are highly recommended in high-risk groups. ACKNOWLEDGMENT This project was supported by the Deanship of Scientific Research at Prince Sattam Bin Abdulaziz Unversity under the research project 2017/02/7565. REFERENCES [1] Ahmad, K., Jafar, T. H., & Chaturvedi, N. (2005). Self-rated health in Pakistan: results of a national health survey. BMC public health, 5(1), 51. [2] Aldabe, B., Anderson, R., Lyly-Yrjänäinen, M., Parent-Thirion, A., Vermeylen, G., Kelleher, C. C., & Niedhammer, I. (2011). Contribution of material, occupational, and psychosocial factors in the explanation of social inequalities in health in 28 countries in Europe. J Epidemiol Community Health, 65(12), 1123-1131. [3] Bombak, A. E. (2013). Self-rated health and public health: a critical perspective. Frontiers in public health, 1, 15. [4] Cochran 2nd, W. G. Sampling techniques 2nd Edition, 1963 New York. [5] Hosmer, D. W., & Lemeshow, S. (2000). Applied Logistic Regression. John Wiley & Sons. New York. [6] Idler, E. L., & Benyamini, Y. (1997). Self-rated health and mortality: a review of twenty- seven community studies. Journal of health and social behavior, 21-37. [7] Kennedy, B. P., Kawachi, I., Glass, R., & Prothrow-Stith, D. (1998). Income distribution, socioeconomic status, and self rated health in the United States: multilevel analysis. Bmj, 317(7163), 917-921. [8] Kurtze, N., Eikemo, T. A., & Kamphuis, C. B. (2013). Educational inequalities in general and mental health: differential contribution of physical activity, smoking, alcohol consumption and diet. The European Journal of Public Health, 23(2), 223-229. [9] Laaksonen, M., Metsä-Simola, N., Martikainen, P., Pietiläinen, O., Rahkonen, O., Gould, R., ... & Lahelma, E. (2012). Trajectories of mental health before and after old-age and disability retirement: a register-based study on purchases of psychotropic drugs. Scandinavian journal of work, environment & health, 409-417. [10] Liang, J. (1986). Self-reported physical health among aged adults. Journal of Gerontology, 41(2), 248-260. [11] Miilunpalo, S., Vuori, I., Oja, P., Pasanen, M., & Urponen, H. (1997). Self-rated health status as a health measure: the predictive value of self-reported health status on the use of http://www.iaeme.com/IJM/index.asp 173 editor@iaeme.com
- Socioeconomic and Demographic Correlates of Self Rated Health among Adults in Alkharj Area KSA, 2017 physician services and on mortality in the working-age population. Journal of clinical epidemiology, 50(5), 517-528. [12] Moor, I., Spallek, J., & Richter, M. (2017). Explaining socioeconomic inequalities in self- rated health: a systematic review of the relative contribution of material, psychosocial and behavioural factors. J Epidemiol Community Health, 71(6), 565-575. [13] Nilsson, K., Hydbom, A. R., & Rylander, L. (2016). How are self-rated health and diagnosed disease related to early or deferred retirement? A cross-sectional study of employees aged 55-64. BMC public health, 16(1), 886. [14] Perkins, J. M., Lee, H. Y., James, K. S., Oh, J., Krishna, A., Heo, J., & Subramanian, S. V. (2016). Marital status, widowhood duration, gender and health outcomes: a cross-sectional study among older adults in India. BMC public health, 16(1), 1032. [15] Richter, M., Moor, I., & van Lenthe, F. J. (2012). Explaining socioeconomic differences in adolescent self-rated health: the contribution of material, psychosocial and behavioural factors. J Epidemiol Community Health, 66(8), 691-697. [16] Rius, C., Fernandez, E., Schiaffino, A., Borras, J. M., & Rodríguez-Artalejo, F. (2004). Self perceived health and smoking in adolescents. Journal of Epidemiology & Community Health, 58(8), 698-699. [17] Robine, J. M., Jagger, C., & Euro-Reves Group. (2003). Creating a coherent set of indicators to monitor health across Europe: the Euro-REVES 2 project. European Journal of Public Health, 13(suppl_3), 6-14. [18] Singh-Manoux, A., Guéguen, A., Martikainen, P., Ferrie, J., Marmot, M., & Shipley, M. (2007). Self-rated health and mortality: short-and long-term associations in the Whitehall II study. Psychosomatic medicine, 69(2), 138. [19] Strawbridge, W. J., & Wallhagen, M. I. (1999). Self-rated health and mortality over three decades: results from a time-dependent covariate analysis. Research on Aging, 21(3), 402- 416. [20] Wei, L., Xu, X., Gurudayal, Bullock, J., & Ager, J. W. (2019). Machine Learning Optimization of p-Type Transparent Conducting Films. Chemistry of Materials, 31(18), 7340-7350. [21] Weich, S., Lewis, G., & Jenkins, S. P. (2002). Income inequality and self rated health in Britain. Journal of Epidemiology & Community Health, 56(6), 436-441. [22] Deni Nurdyana Hadimin and Yanyan Mochamad Yani, (2018), Democratization and Strengthening Local Politics Perspectives of Socioeconomic Standard in New Democracy Country. International Journal of Civil Engineering and Technology, 9(3), pp. 248-258 [23] WS Ebhota, (2019), Photovoltaic Solar Scheme in Sub Saharan Africa: Socioeconomic Booster. International Journal of Mechanical Engineering and Technology, 10(10), pp. 28-42 [24] Svetlana Kapitonovna Demchenko, Maxim Sergyeyevich Zlotnikov, Tatiana Alexandrovna Melnikova and Olga Sergeevna Demchenko, (2019), Theoretical and Methodological Bases of Improving the Assessment of the Effectiveness and Synchronous Functioning of a Country's Socioeconomic System Under Conditions of Transformation, International Journal of Civil Engineering and Technology, 10(2), pp. 1877–1884. http://www.iaeme.com/IJM/index.asp 174 editor@iaeme.com
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