International Journal of Current Medical And Applied Sciences, 2015, June, 7(1),43-46.
ORIGINAL RESEARCH ARTICLE
Assessment of Domain wise Quality of Life Among Elderly Population Using WHO-BREF Scale and its Determinants in a Rural Setting of Kerala. 1Assistant 3Professor
S. E. Thadathil1, R. Jose2 & S. Varghese3
Professor, 2Assistant Professor Department of Community Medicine, Govt Medical College, Thrissur, Kerala India . and Head, Department of Community Medicine, Govt Medical College, Thiruvanathapuram, Kerala India.
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Abstract:
Background- People of Kerala are experiencing high life expectancy. In this context, measuring the QOL and its determinants among the elderly gains importance. Objectives -To assess the domain wise QOL of elderly population living in a rural setting of Kerala and to compare the QOL across different socio-demographic factors and co-morbidity. Materials and methods - A community based cross-sectional study was conducted among 220 elderly subjects in panchayat area of Kollam district, Kerala. QOL was assessed using WHOQOL-BREF scale. Socio-demographic factors and co-morbid conditions were recorded by using a structured questionnaire. Statistical Analysis: Data was analysed in SPSS version 16. Proportions, Independent sample “t”test and Anova were done. Results - Majority (57%) were in the (60-69) years’ age-group. Mean age of sample is 69.65 years. Among the study participants, 61.4% were females, 90.4 % were unemployed, 55.9% were suffering from co-morbidity. The mean scores of QOL domains was maximum in physical health (42.44), followed by social relationship (42.16).The lowest mean score was seen in psychological domain (26.95). Occupation, higher income, 60-69 years age group, staying with partner and absence of co-morbidity were found to be the determinants of better QOL score (p>0.05).Conclusion- The mean score of quality of life was below average in all domains. Psychosocial domain was badly affected. Establish more recreational facilities for the elderly. As the numbers of economically independent elderly increases, we can expect better QOL scores. Key words: Elderly, QOL, socio-demographic factors, WHO-BREF.
Introduction:
Ageing is a normal, inevitable, biological and universal phenomenon, and it affects every individual irrespective of caste, creed, rich or poor. It is the outcome of certain structural and functional changes that takes place in the major parts of the body as the life span increases. As Sir James Sterling Ross said “You do not heal old age, you protect it, you promote it and you extend it [1]. Longevity has increased significantly in the last few decades, mainly due to the socio-economic and health care developments. These factors are responsible for the higher numerical presence of elderly people leading to higher dependency ratio. Demographers, researchers, and responsible citizens Address for correspondence: Dr. S. E. Thadathil, Assistant Professor, Department of community Medicine, Govt Medical College, Thrissur, Kerala , India. Email ID:
[email protected]
have started to think about the aged population and its problems, because of the demographic transition which is taking place in many countries of the third world now. Aging of the population will be one of the major challenges in the near future [2]. It is estimated that nearly 63% of the population aged 60 and above are living in developing countries, and further projected that by 2050 nearly 1.5 billion older people will reside in developing countries [3]. In India as per 2011 census 8% of population were 60 & above & in the rural setting it was 8.1% and in urban setting it was 7.9% [4].
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How to cite this article: S. E. Thadathil, R. Jose & S. Varghese; Assessment of domain wise quality of life among elderly population using WHO-BREF Scale and its Determinants in a rural setting of Kerala . International Journal of current Medical and Applied sciences; 2015, 7(1), 43-46. IJCMAAS,E-ISSN:2321-9335,P-ISSN:2321-9327.
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S. E. Thadathil, R. Jose & S. Varghese In Kerala it was 12.6%. The proportion of aged population in Kerala increased from 10.84% in 2001 census to 12.6% in 2011.There won`t be much of a difference in proportion in rural and urban areas [4]. Although increase in aging population is an indirect indication of improvement of health status of society, it raises many problems in the present set-up. Elderly people in the community experience multiple disadvantages and their physical, social mental and economic wellbeing are interrelated. Qualities of life (QOL) of elderly people are becoming even more relevant with demographic shift happening toward an ageing society. There are indications that concerns related to QOL in elderly people are different from that of the general population [5, 6]. The well being of an individual has both subjective and objective components. QOL is the subjective component of well being. WHO defines QOL as the condition of life resulting from the combination of the effects of the complete range of factors such as those determining health, happiness education, social and intellectual .attainments, freedom of action, justice and freedom of expression [7]. Kerala had the highest life expectancy among the states in India. Elderly population also has high morbidity due to both communicable and non communicable diseases; majority of ill health condition are in old age. Due to disruption of joint family system, family support is also on the decline. The subjective component of well being of elderly gains importance in this background. Today, the elderly demand that society should not only ensure independence and participation, but also provide care, fulfilment and dignity. There is limited understanding of factors influencing their quality of life available now. In this context we planned to assess the domains of quality of life of elderly population residing in Yeroor panchayat of Kollam district as well as to compare the quality of life across different socioeconomic factors and co-morbidity.
Materials and Methods:
A cross sectional study was done in Yeroor panchayat of Kollam district Kerala in which QOL among individuals ≥60 years of age was assessed using WHO-BREF scale .Individuals who cannot respond to the questions were excluded from the study. The sample size required for the study was calculated using (4×SD2) ÷prescision2 based on SD of QOL score obtained from a pilot study Table 1: Quality of life domain scores QOL domain Physical health Psychological Social relationship Environment
Mean 42.44 26.95 42.16 36
Median 44 25 44 38
conducted on 20 elderly individuals. A sample size of 110 was obtained (precision fixed at 4,SD from the pilot study =21). Since the sampling technique employed was cluster sampling, a design effect of 2 was used for the calculation and the final sample size of 220 was obtained. Yeroor panchayat was selected randomly from among the panchayats in Kollam district by lot method. This panchayat has 18 wards with a total population of 33942. 18 clusters were selected, one from each ward with a cluster size of 13. The study was started after getting ethical approval from the institution. The study subjects were interviewed after obtaining informed consent from them. The details collected include socio-demographic variables like age, sex, education, occupation, income, marital status, family type and co-morbidity. QOL was assessed using WHO BREF scale and it consisted of 4 domains. Domains were physical health, psychological, social relationship and environment. Domain scores were scaled in a positive direction (i.e. higher scores denoted higher quality of life). The mean score of items within each domain was used to calculate the domain score. Initially we converted the domain score in 0-100 scale using transformed score where 100 was the highest and 0 was the lowest value [8]. The study subjects were interviewed after obtaining written informed consent from them.
Statistical analysis: The collected data was entered in Microsoft Excel and analyzed by using SPSS (Statistical Package for Social Sciences) version 16.0. Mean and standard deviation were used to describe the QOL score in each domain. Independent t-test or Anova, were applied to compare the mean scores of different variables and domains. Pvalue less than 0.05 was considered significant.
Results:
The study was conducted on 220 elderly (≥60 years) persons in Yeroor panchyat of Kollam district of Kerala. Among the study participants, 16.8% were ≥ 80 years and mean age of the population was 69.65years. Among the general characteristics of the study population it was found that 51.8% were females, 90.4% of elderly were unemployed, 55.9% were having co-morbid condition, 67.72 % were living in joint family, 65.4% were staying with their partner and 33.18% were illiterate.
Std. deviation 20.95 17.5 23.09 12.59
The mean QOL scores were maximum in physical health domain (42.44), followed by social relationship (42.16). The lowest mean score was seen in psychological domain (26.95). The overall total mean score was 38.9. All the
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domain scores were below average. The scale used was found to have good reliability with a Cronbach’s alpha of 0.94. Table: 2 Comparison of WHO QOL-BREF domain score with socio-demographic factors and co morbidity Variables
Frequency (%)
Gender
QOL domain mean score Physical
Psychological
Social relationship
Enviornment
73(33.18) 70(31.81)
45.73 39.37 0.024 49.706 37.08 25.94 0.0001 36.8 38.9
30.55 23.61 0.003 32.39 21.33 17.1 0.0001 21.96 23.05
45.6 38.82 0.029 49.29 34.21 29.7 0.0001 37.6 39.14
36.84 35.21 0.336 38.43 32.73 32.72 0.04 34.1 35.52
38(17.27) 39(17.81)
49.97 51.9
33 37.44
44.2 53.69
36.7 39.67
0.0001 40.02 65.38 0.0001 38.98 42.12 59.37 0.0001 47.32 32.61
0.0001 25.12 44.38 0.0001 23.75 26.32 43.54 0.0001 31.9172 17.2466
0.002 39.84 63.38 0.0001 37.64 43.56 58.42 0.0001 48.3172 29.5069
0.157 34.88 46.52 0.0001 33.99 36.96 42.54 0.012 38.2069 31.9178
0.0001 52.78 34.28 0.001 45.08
0.0001 34.76 20.8 0.0001 29.62
0.001 50.57 35.39 0.001 50.51
0.001 41.64 31.54 0.0001 38.05
41.44 0.22
25.88 0.14
38.24 0.0001
34.97 0.092
Male Female p value from t test Age group 60-69 70-79 >=80 p value from ANOVA Education Illiterate upto lower primary upper primary high school and above p value from ANOVA Occupation unemployed employed p value from t test Income 1000 p value from ANOVA Marital having partner status not having partner p value from t test Co Absent morbidity Present p value from t test Family Nuclear
106(48.18) 114(51.18)
joint p value from t test
149(67.72)
126(57.27) 57(25.91) 37(16.8)
199(90.4) 21(9.6) 120(55.54) 74(33.63) 26(11.8) 145(65.4) 75(34.07) 97(44.09) 123(55.9) 71(32.28)
Table 2 has shown the comparison of scores in 4 domains of QOL WHO-BREF scale with sociodemographic variables and co-morbidity. On analyzing it, males in 60 to 65 years age group, high school and above education, higher income, absence of co-morbid condition and married persons staying with partners were having better score in domain of physical health and psychological. These association was statistically significant (p value
