|Year : 2007 | Volume
| Issue : 1 | Page : 51-53
Role of socio-economic factors in cataract surgery utilization in JIPMER Pondicherry
T Prasanna, SB Rotti
Deptt. of Preventive and Social Medicine, JIPMER, Pondicherry, India
|Date of Web Publication||6-Aug-2009|
Deptt. of Preventive and Social Medicine, JIPMER, Pondicherry
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background : This study was conducted in JIPMER & Kurusukuppam, Pondicherry.
Objectives : To identify the socioeconomic factors influencing the utilization of cataract surgery & to identify the persons motivating the patients to utilize these services.
This was a case-control study; cases were patients (age group 50-70 years) who were operated in JIPMER for senile cataract without complications and one control was selected for each case. Controls were also of the same age group residing at Kurusukuppam with complaints of dimness of vision and who had not undergone cataract surgery, selected by random sampling. Both the groups were interviewed using a pretested interview schedule.
Results : Subjects who were literate and with high school education and more and with income more than Rs.1050 (class III) utilized the cataract surgery services more. In majority of cases, motivation for getting operated comes from relatives. Peer groups who have undergone the surgery before, were the predominant sources of health information about the surgery.
Higher income & higher education affect the utilization significantly. Relatives & Previously operated peers play an important role.
Keywords: Socio-Economic Factors, Cataract, and Case-Control Study
|How to cite this article:|
Prasanna T, Rotti S B. Role of socio-economic factors in cataract surgery utilization in JIPMER Pondicherry. Indian J Community Med 2007;32:51-3
|How to cite this URL:|
Prasanna T, Rotti S B. Role of socio-economic factors in cataract surgery utilization in JIPMER Pondicherry. Indian J Community Med [serial online] 2007 [cited 2019 Sep 16];32:51-3. Available from: http://www.ijcm.org.in/text.asp?2007/32/1/51/53403
Blindness is one of the significant social problems in India with 7 million of the total 45 million blind people in the world residing in our country  . Prevalence of blindness  was found to be 1.49%, with cataract contributing to 77% of it. With the increasing life expectancy and expanding population, the number of cases is expected to increase in the near future.
Apart from health and status of vision, there are many other socio-economic factors and perceptions, which influence the decision making of the people for getting operated for cataract. But very few studies have been done on the social factors influencing the utilization of cataract surgery. Knowledge about these factors can improve the operational efficiency to reduce the prevalence of blindness to 0.5% by the year 2010 as aimed by NHP 2002  . This study is an attempt to identify the socioeconomic factors influencing the utilization of cataract surgery in JIPMER hospital and the persons motivating the patients to utilize the services.
| Material and Methods|| |
The study was a case-control study conducted in the department of Ophthalmology, JIPMER and Kurusukuppam area of Pondicherry. The ophthalmology department in JIPMER serves as a tertiary referral centre for Pondicherry and adjoining regions of Tamilnadu, performing about 20 to 30 cataract surgeries for senile cataract every week. Kurusukuppam is an urban slum area of Pondicherry, served by the Jawaharlal's Urban Health Center (Kurusukuppam) with a population of around 9500, of similar background as those who utilize the services of JIPMER. Study Period was from May 2004 to October 2004. A case was defined as any person between 50 and 70 years of age getting operated in the JIPMER hospital for senile cataract without any complications in the study period (100 cases). A control was defined as any person between 50 and 70 years of age residing in Kurusukuppam area with complaints of diminution of vision and who had not undergone cataract operation. From the enumeration register of JIUHC, Kurusukuppam, all people aged between 50 and 70 years were listed. With the help of the field staff and the Anganwadi worker, people with dimness of vision were short-listed and 100 age (±2 years) and sex-matched controls were selected by simple random sampling method. Information was collected from both the cases and controls by pretested interview schedule after taking informed written consent. The variables studied were age, sex, education, working status, per capita income, type of locality (rural/urban), knowledge about blindness and cataract, source of information about the surgery, availability of treatment near their residence, the person who motivated the patient (case) to undertake the cataract surgery, treatment alternatives known, treatment of their choice, reason for delay in treatment and choice of this hospital for treatment and details about whether cataract was diagnosed previously before reaching this tertiary centre. Clearance from the Institute Ethics Committee was obtained, before starting the study.
| Results|| |
[Table 1] shows the age group and sex distribution of the cases and controls. There was no significant difference between the groups based on age and sex. [Table 2] shows that majority in the case group were educated (79%) compared with the control group where majority were not (58%) The difference was statistically significant chi-square value 28.643(p<0.001), Among the educated, more people had high-school level education and above in the case group (43%) compared to the control group where the number of persons who have had high school education and above was less (16%) and this was statistically significant. Chi-square value 34.359 (p<0.001), [Table 2] shows that there is no significant difference between the cases and controls based on working status. Greater number of persons in the case group were in the high-income category (>Rs.1051) than the control group. Majority from control group (93%) were in the low-income category (< Rs.1050). This observation was associated with statistical significance. (Chi-square value 27.556; p < 0.001).Among the cases, majority were from the urban area (59%) and the remaining from the rural areas.
Most of them in both the groups believe that they are blind only when they are unable to pursue their routine activities at home. No statistical difference was associated with this observation between the cases and controls. For the questions about knowledge of cataract, majority answered correct among the cases, whereas majority among controls gave incorrect replies or not sure of the answer. Chisquare valve 49.449; p<0.001 and 72.832; p<0.001 for the two questions. Three - fourths of the cases (75%) accept surgery as the treatment of choice but majority in the control group were not sure about the treatment of choice nor were they aware of the treatment alternatives (79%). This observation was statistically significant. (Chi-square value=58.413; p<0.001). In the control group, 22% told glasses as the treatment of choice.
Majority in both the cases (57%) and the controls (54%) came to know about the surgery from previously operated neighbours and friends. [Table 3] shows that the health personnel as sources of information were seen more often in the case group than in the control group. This difference was statistically significant. (Chi-square value 15.789; p<0.001). A greater number of people in the case group (32%) had consulted an ophthalmologist when compared with the control group (17%). The difference was statistically significant (Chi-square value 5.373, p<0.05). However, majority in both the groups had not been diagnosed with cataract previously. Among those who motivated the cases to undertake the surgery, 49% were relatives of the cases. Motivation within the family was found only in 27% of the cases. 59% of the cases told that the treatment facilities were available near the residences.
Majority (71%) among the cases were not aware about the operation camps held in the villages. Nevertheless, majority (58%) had attended screening camps. About 81%of the cases preferred JIPMER for treatment in view of the quality of the services provided. However, 31% of the total cases were referred to the hospital. Only 12% of the cases migrated temporarily to Pondicherry for treatment for cataract in JIPMER.
[Table 4] shows discriminant analysis of the socio-economic factors. It was found that the following factors were significant - literacy (standard canonical coefficient, SCC=0.572), high school education (SCC=0.113) and income level above Rs.1050 (SCC=0.629). The Canonical Correlation was 0.450, with Wilks' Lambda of 0.797 and significance p<0.001. The group centroids were found to be -0.502 for Cases and 0.502 for Control.
| Discussion|| |
In our study, subjects between 50 & 70 years of age were studied, as people being operated for cataract were commoner in this age group. Community controls were taken, as they would give information that is more accurate since the investigator could also observe the socio-economic factors.
A study conducted in Karnataka and Tamilnadu by Vaidhyanathan et al revealed that the social determinants play a very important role in cataract surgery utilization. It identified that individuals who were aware of the surgery were males, literates and more affluent than those who were unaware of this treatment option  . The Snellingen study in Nepal revealed that low socio-economic status was a barrier to the utilization of cataract surgery  and our study also showed similar conclusions. Brilliant et al showed that cataract surgery utilization is less in illiterates  . The same was observed in our study also.
Multivariate discriminant analysis was used to examine the hypothesized factors that discriminate between those who utilize the cataract surgery and those who do not. Discriminant analysis uses multiple predictor variables to discriminate among individuals based upon a single dichotomous criterion variable. The single dichotomous criterion variable is the dummy variable (1=utilizing cataract surgery services, 2=not utilizing cataract surgery) that gauges individuals who utilized the surgery services. In this analysis, the multiple predictor variables are the variables measuring sociodemographic variables.
The canonical discriminant function is a linear combination of the predictor variables , . The canonical correlation coefficient provides information on the discriminating power of the function and is a measure of the association that summarizes the degree of relatedness between the groups and the discriminant function. The standardized canonical discriminant function coefficients are measures of the relative importance of each predictor variable; the larger the magnitude of the predictor variable, the greater the contribution of that variable, net the effect of the other predictor variables. The total canonical structure coefficients are analogous to bivariate correlations; they signify how closely a predictor variable and a function are interrelated and are not affected by relationships with other variables.
Discriminant analysis was chosen as the statistical technique to use, as the purpose of the analysis is to develop an equation that helps to discriminate between the two groups based on utilization of the cataract services; Discriminant analysis is a commonly used technique for this purpose , .We examine a series of variables to see how they combine to significantly discriminate between the two groups.
Cataract surgery utilization is greater in the educated and with high school education or more and those of higher income group (>Rs.1050 of percapita income). Motivation for getting operated for cataract comes from relatives. Peer groups, which have undergone cataract surgery previously, are the predominant sources of information about undergoing cataract surgery. Most of the people accept surgery as the treatment of choice. Factors like knowledge about cataract and the surgical remedy for it, the health personnel as sources of information and availability of treatment near the residence play a vital role in the utilization of services by the people.
| Acknowledgements|| |
We sincerely thank the Indian council of medical research for giving us an opportunity to take up this research studentship. Heartfelt thanks to Dr.K.S.V.K.Subba Rao, Director, JIPMER, Dr.K.S.Reddy, Dean, JIPMER for giving permission. Sincere thanks to Dr.K.A.Narayan, Professor and Head, P&SM department, Dr.Vasudev Anand Rao, Professor and Head, Department of Ophthalmology, Dr.K.B.V.P.Kumar Babu, CMO, JIUHC, Kurusukuppam for their kind support to undertake this study in their departments.
| References|| |
|1.||Govt. of India, National health policy 2002, New Delhi, Ministry of Health And Family Welfare. |
|2.||Govt. of India, Health Information of India 1995-1996, New Delhi, DGHS, Ministry of Health And Family Welfare. |
|3.||Vaidyanathan K, Limburg H, Foster A, Pandey RM. Changing Trends in Barriers to Cataract Surgery in India. WHO bulletin 1999; 77:104-9. |
|4.||Snellingen T, Shrestha BR, Gharti MP, Shrestha JK, Upadhyay MP, Pokhrel RP. Socioeconomic barriers to cataract surgery in Nepal: the south Asian cataract management study. Br J Ophthalmol 1998;82:1424-8. [PUBMED] [FULLTEXT]|
|5.||Brilliant E, James M. Lepkowsi, Beatriz Zurita, Thulsiraj RD. Social Determinants of Cataract Surgery Utilization In South India". Arch Ophthalmol - 1991; 109:584-9. |
|6.||Bibb R, Roncek DW. Investigating group differences: An explication of the sociological potential of discriminant analyses. Sociological Methods and Research 1976; 4: 329-79. |
|7.||Schulman M, Cotten S. Adaptations to the farm crisis: Macro level implications of micro level behaviors. Applied Behavioral Science Review 1993; 1: 93-111. |
|8.||Cleary, PD, Angel R. The analysis of relationships involving dichotomous dependent variables. Journal of Health and Social Behavior 1984; 25: 334-48. |
|9.||Huberty CJ, Lowman LL, Discriminant analysis via statistical packages. Educational and Psychological Measurement 1997; 57: 759-84. |
|10.||Prasad BG. Social classification of Indian families. Journal of Indian medical association, 1961; 37:250-51. |
[Table 1], [Table 2], [Table 3], [Table 4]