|Year : 2012 | Volume
| Issue : 1 | Page : 28-41
Prevalence and predictors of self-medication in a selected urban and rural district of Sri Lanka
Pushpa R Wijesinghe1, Ravindra L Jayakody2, Rohini de A Seneviratne3
1 Epidemiology Unit, Ministry of Health, 231, De Saram Place, Colombo 10, Sri Lanka
2 Department of Pharmacology, Faculty of Medicine, University of Colombo, Colombo, Sri Lanka
3 Department of Community Medicine, Faculty of Medicine, University of Colombo, Colombo, Sri Lanka
|Date of Web Publication||24-May-2017|
Pushpa R Wijesinghe
Epidemiology Unit, Ministry of Health, 231, De Saram Place, Colombo 10
Source of Support: None, Conflict of Interest: None
Background: Self-medication is widely practised in many developing countries. The determinants of self-medication need to be understood to design adequate medicine information policies and patient-dispenser education strategies. Hence, the prevalence of medicine use and predictors of self-medication were determined in Sri Lanka.
Methods: In a community-based cross- sectional study, data were collected from 1800 adults selected from Gampaha and Polonnaruwa districts respectively. Study participants were sampled using a multistage cluster sampling technique. Trained public health midwives administered the questionnaire. Two Likert scales provided information on access to medical care and satisfaction with available pharmacy services. About 95% of the sampled population participated in the study.
Results: Overall, prevalence of medication use (allopathic, traditional, home remedies) in urban and rural population was 33.9% and 35.3%, respectively. Self-medication prevalence of allopathic drugs in the urban sector (12.2%) was significantly higher than in the rural (7.9%) sector(p<0.05). In the urban sector, small household size and preference to have medicines from outside the pharmacies predisposed to self-medication. The higher acceptability of medical services and regularity of medical care decreased the likelihood of self-medication. In the rural sector, lower satisfaction about the healthcare providers’ concern for clients, lower satisfaction about affordability of medical care and higher satisfaction with technical competence of the pharmacy staff increased the likelihood of self-medication. In both urban and rural sectors, when symptom count increased, tendency to self-medicate decreased.
Conclusions: Self-medication prevalence was higher in urban compared to rural areas in Sri Lanka. Some aspects of access to medical care, satisfaction with pharmacy services and perceived severity of the disease were found to be important determinants of self-medication.
Keywords: Prevalence, predictors, self-medication, prescribed medication, access
|How to cite this article:|
Wijesinghe PR, Jayakody RL, de A Seneviratne R. Prevalence and predictors of self-medication in a selected urban and rural district of Sri Lanka. WHO South-East Asia J Public Health 2012;1:28-41
|How to cite this URL:|
Wijesinghe PR, Jayakody RL, de A Seneviratne R. Prevalence and predictors of self-medication in a selected urban and rural district of Sri Lanka. WHO South-East Asia J Public Health [serial online] 2012 [cited 2022 Aug 14];1:28-41. Available from: http://www.who-seajph.org/text.asp?2012/1/1/28/206911
| Introduction|| |
Self-medication, despite its negative outlook by some, is regarded as an important component of primary health care (PHC). It is a common practice even in places where health professionals are easily accessible. Self medication gets enhanced with increasing literacy and it is even encouraged so as to have self-reliance for curative, preventive, promotive and rehabilitative care. If practiced correctly, it may save expenses of health care seekers. Thus , considering the usefulness of self-medication, the World Health Organization (WHO) has developed guidelines for regulatory assessment of the medicines appropriate for self-medication.
Self-medication is a common practice to treat most episodes of illnesses in economically deprived communities., It is explained by the reduced demand for doctor consultations and subsequent costs for treating perceived self-limiting conditions. Prevalence of self- medication in developing countries is in the range of 12.7% to 95%., Estimates vary in the South-Asia Region. In Nepal, self-medication was 59% in the six-month period preceding the interview while the estimate in India was 31%. A wide variation has been reported in India. For example, in coastal regions of South India, the prevalence was 71%. In Pakistan, self-medication prevalence was around 51%. A study in Bangladesh revealed that for three most frequently reported illnesses, 81.3% of the young and 78.5% elderly health care seekers self-medicated.
Self-medication is more common among women, young people, those living alone, individuals of low socio-economic status (SES), sufferers of chronic ailments and psychiatric conditions., Poor SES, high medicine cost, non-availability of doctors in rural areas make health care inaccessible and consequently, pharmaceutical outlets serve as the first contact point of health care. In this context, pharmacists, pharmacy assistants, compounders and health assistants become instrumental in fostering self- medication.,,
In an urban setting of Sri Lanka nearly 64% of the households were reported to have practiced self-medication. In these households, for nearly one third of acute illnesses, self-medication acted as a source of care. Even mothers who self-medicate their children were as high as 85% in an urban area. Most studies in Sri Lanka were confined to urban areas which have well developed health and pharmaceutical care networks. Proxy indicators such as self-medication prevalence for malaria indicate that self-medication is relatively low in rural areas.
Self-medication is a self-initiated behaviour. Hence, knowledge on behavioural aspects related to medication use is required to improve and expand the knowledge base on health care seeking behaviour. Users’ subjective evaluation of behaviour-related variables has been identified as important. Hence, perceived satisfaction with health care service and access to care could have a strong association with medication use. However, an analytical epidemiological approach has not been applied in determining significant predictors of self-medication in community-based medication use studies in urban and rural settings in Sri Lanka. Therefore, a community-based, cross-sectional study was conducted to determine the prevalence of medicines use and predictors of self-medication among adults.
| Methods|| |
The estimated mid-year population of Sri Lanka was 20.7 million in 2010. The country has nine provinces and 25 administrative districts. We selected all urban/municipal council areas of the Gampaha district in the Western Province and exclusively agrarian Polonnaruwa District in the North Central Province to conduct this community-based cross-sectional study. These two non-adjacent districts differ in terms of provision of health/pharmaceutical care. In Gampaha district people have access to a wide variety of public and private health/pharmaceutical care facilities while Polonnaruwa district has very few health/ pharmaceutical facilities. The ethical clearance to conduct the study was granted by the Ethical Review Committee of the Faculty of Medicine of the University of Colombo.
Study population selection
The study population comprised of adults over 18 years of age, residing in respective districts for a period of at least one year. The sample size was calculated using the formula for estimating the difference between urban and rural prevalence of medication use with a specified absolute precision. The prevalence was assumed to be 50% in order to obtain the largest possible sample. The estimated sample size was 769 for an absolute precision of 5%. To account for a possibility of non-response, estimated sample size was increased to 846. This sample size was multiplied by a design effect of two as we used the cluster sampling technique. Thus, the required sample size was 1692 (846 each from urban and rural sectors).
Study participants were selected from 60 clusters (30 clusters from each urban and rural sector). The cluster size was 30 participants. Clusters were selected in a multi-stage, probability proportionate to size (PPS) sampling procedure. A Grama Niladhari (GN) division served as the primary sampling unit (PSU). GN division, a geographically well demarcated unit, is the lowest administrative division in a district in Sri Lanka. Within each PSU, 30 households were randomly selected using the voters’ lists. The household member eligible for the survey was selected using a Kish table.
Data was collected using a pre-tested questionnaire, which was administered by 15 trained Public Health Midwives (PHM) during a face-to-face interview. The English questionnaire was translated to Sinhala and Tamil languages. The data were collected on medication use (allopathic medicines, traditional or home remedies) by self or prescribed by doctors during the preceding two weeks prior to the interview. The socio-demographic details of study subjects and their attitudes towards medicines were also assessed. Other variables included information on the health status, morbidity status and the number of symptoms at the time of medication use.
In addition to the questionnaire, study participants completed two self-administered Likert-type scales to obtain information on selected domains of perceived satisfaction with private pharmacy services (scale I) and access to medical care (scale II). Instead of the conventional translation and back translation which is considered inadequate for ethnographic research, we used the combined qualitative and quantitative approach for translation suggested by Sumathipala and Murray.
The first Likert scale used for assessing the satisfaction with private pharmacy services was adapted from the scale prepared by MacKeigan and Larson which was validated for local use. This scale contained domains namely access to services, continuity with the same pharmacy services, availability of medicines, affordability of medicines, perceived efficacy of medications, general satisfaction, interpersonal aspects (explanations, considerateness) and technical competence of the pharmacy staff. These domains contained 41 items. The scale was validated using 178 clients of four private pharmacies and six hospital out-door pharmacies in Colombo and Anuradhapura districts. The construct validity was assessed using confirmatory factor analysis, item analysis and by measuring internal consistency. The factors extracted by the principal component analysis accounted for 20.8% of variance. In the defined scales, Cronbach’s alpha exceeded the expected value of 0.5 or more. Even if the very stringent Nunally’s criteria is used, three of the scales met the Nunally’s criteria of Cronbach’s alpha exceeding 0.7 (0.8, 0.75, 0.71) while 4 scales were close to 0.7 (0.65, 0.65, 0.67, 0.68). The inter-scale correlation coefficient of defined scales indicated that only Interpersonal I (explanation), Interpersonal II (considerateness) and general satisfaction which had values falling between Anastasi’s criteria of 0.5-0.7 were the sub-scales of the same theoretical concept while others were independent scales.
The second Likert scale for assessing the perceived access to medical care had domains of concern for clients, service availability, affordability, acceptability and regularity . This scale of 35 items was prepared on the basis of the theoretical concept of satisfaction by Ware and Snyder which was validated for local use in the same population used for validating the first scale. Construct validity was assessed using exploratory factor analysis, item-analysis and by measuring internal consistency. Exploratory factor analysis extracted four main factors which accounted for 41% of variance. All item-scale correlations above 0.3 and the higher correlation of the majority of items (33) with the tentative scale than with other scales confirmed the factor scales. Factor scales were internally consistent as Cronbach’s alpha for all factors (0.51, 0.78, 0.81, and 0.82) exceeded the accepted level of 0.5. None of the dimensions proved to be sub-scales of higher order scales as their inter-scale correlation coefficients did not fall between Anastasi’s criteria of 0.5-0.7.
Pre-testing of the questionnaire and two scales was carried out on a convenience sample of 30 patients attending a general practice and a medical clinic at a government hospital in Colombo district. The clarity and relevance of items were assessed and certain modifications were made on the basis of the findings of the pre-test.
Medication use was defined as “the use of any pharmaceutical product in any form with or without a prescription in order to cure, prevent, mitigate or diagnose a disease, abnormal physical state, symptom, abnormal physiological condition or to restore, modify or correct organic function in humans”.
We used the WHO definition of self-medication which considered self-medication as “use of pharmaceutical or medicinal products by the consumer to treat self-recognized disorders or symptoms, the intermittent or continued use of a medication previously prescribed by a physician for chronic or recurring disease or symptom, or the use of medication recommended by lay sources or health workers not entitled to prescribe medicine”.
In order to have a comprehensive pattern of medicines use, information on the use of allopathic medicines, traditional medicines and home remedies was collected. However, detailed analysis was performed on the use of allopathic medicines only.
A recall period of two weeks prior to the interview was used. If the respondent reported use of any medicines in the reference period, they were requested to provide prescriptions, labels, blister packs etc. In case they were unable to provide these evidences, respondents were asked to name the pharmaceutical product and or the purpose of its use. Additionally, the number of drugs, their doses, source of information and condition for which the drugs were used was also recorded.
Prevalence of medication use, self-medication, and prescribed medication were considered as dependent variables. Point estimates and 95% confidence intervals were calculated for these variables. When calculating the prevalence of medication use, self-medication and prescribed medication, the total number of study subjects enrolled was used as the denominator. Additionally, we calculated self-medication and prescribed medication as a proportion of the overall medication use also. The denominator for calculating the proportion of self-medication and prescribed medication was the number of subjects in the sample who used any medicine during the two week recall period. The significance of the difference in estimates in two distinct settings was tested using Z test.
‘Predisposing’, ‘enabling’, and ‘need’ variables as defined by Anderson and Newman’s Health Services Utilisation Model were used to identify best predictor variables. Pre-disposing (socio-demographic characteristics, beliefs and attitudes) and need variables (health status, chronic conditions and symptoms) were presented as proportions. Values for enabling variables namely domains of perceived access to care and satisfaction with pharmacy services were presented as mean scores with their standard deviations (SD).
In the bi-variate analysis statistical significance of the association was tested using the chi square or Z test. Logistic regression analysis was done using SPSS, version 9.05. Individual scores of access to care and satisfaction with private pharmacy services were categorized as binary variables on the basis of the mean score before including them as categorical variables in logistic regression analysis. The adjusted Odds Ratios (OR) and the 95% confidence intervals (CI) of the predictor variables for self medication were determined separately for urban and rural sectors.
| Results|| |
Of the 1800 respondents selected for the study from the two districts, 94.9% participated in the study. Socio-demographic characteristics of the respondents are presented in [Table 1]. Better education and higher income were observed in the pre-dominantly catholic, industry and service-oriented urban sector as opposed to the pre-dominantly Buddhist and agrarian rural district.
The overall prevalence of medication use (allopathic medicines, traditional medicines and home remedies) in urban and rural sectors was 33.9% (95%CI: 30.7%-37.1%) and 35.3% (95%CI: 32.1%-38.5%) respectively (p 0.5). In both the sectors, among those who had used any medicine in the past two weeks, most had used allopathic medicines (urban 91.4%, rural 84.6%). The users of traditional medicine were significantly higher in the rural (12.4%) than in the urban (3.8%) sector (p 0.0001). Among those who used allopathic medicines, a significantly higher proportion had self-medicated in the urban sector (37%) than in the rural sector (25%) (p 0.002).
The prevalence of allopathic self-medication in urban and rural sectors was 12.2% (95%CI: 10.0%-14.4%) and 7.9% (95%CI: 6.1%-9.7%) (p 0.0001) and prevalence of prescribed allopathic medication was 20.5% (95%CI: 17.8%-23.2%) and 23.1% (95%CI: 20.3%-25.9%) respectively (p >0.05).
[Table 2] shows the proportion of self-medication according to selected pre-disposing variables. Self-medication was found to be significantly higher among urban males (46%) than among urban females (33%) (p 0.04). Quite interestingly, in the rural district, those who disagreed to accept lay advice about self-medication were more likely to self-medicate (37.1%) than those who agreed (23.4%) (p 0.02). In the urban sector, those who preferred availability of medicines at informal places other than pharmacies had self-medicated (59.7%) more than those who did not think so (29.5%) (p 0.0001).
|Table 2: Distribution of selected pre-disposing variables among self-medicated and prescribed medicine users|
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[Table 3] shows the distribution of medication use by selected measures of access to health care and satisfaction with pharmacy services. Satisfaction scores for interpersonal aspects of “considerateness” (p 0.01) and “providing explanations” (p 0.03) were significantly lower in the self-medication group as compared to users of prescribed medicines in the urban sector. In the rural sector, the score for perceived satisfaction with “technical competence” of the pharmacy staff was significantly higher among the self-medication group than the users of prescribed medicines (p 0.01). When the access to medical care was taken into account, scores in all four dimensions were significantly higher among users of prescribed medicines in the urban sector. However, in the rural sector, only scores for ‘concern for clients’ (p 0.016) and ‘affordability’ (p 0.001) were significantly higher among users of prescribed medication than the self-medication group. [Table 4] describes reinforcing variables of medicines use. Among these variables, only the number of symptoms (symptom count) was significantly associated with the type of medicines use in both sectors (p 0.0001).
|Table 3: Distribution of mean (SD) perceived satisfaction with pharmacy services and access to medical care scores among self-medicated and prescribed medicine users|
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|Table 4: Distribution of reinforcing variables among self-medicated and prescribed medicine users|
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Logistic regression analysis is summarized in [Table 5]. Respondents from urban households having ≤2 members were more likely to self-medicate than those from larger households (OR: 4.33, 95% CI: 1.10-17.53). Having negative attitudes towards non-formal sources of medicines decreased the likelihood of self-medication (OR: 0.26, 95% CI: 0.08-0.84). Of all the enabling variables, higher satisfaction with acceptability of medical services including the regularity of service decreased the likelihood of self-medication (OR: 0.96, 95% CI: 0.93- 0.99) in the urban sector. Out of the reinforcing variables, only ‘having a symptom count of more than two’ reduced self-medication. In the rural sector, respondents highly satisfied with affordability of medical services (OR: 0.25, 95% CI: 0.08-0.80) and concern of the staff for clients (OR: 0.71, 95% CI: 0.52-0.94,) were less likely to self-medicate than those who were less satisfied with these aspects. However, higher satisfaction with technical competence of the pharmacy staff increased the likelihood of self -medication (OR: 1.53, 95% CI: 1.16-2.0). As in the urban sector, having a symptom count more than two decreased the likelihood of self-medication in comparison to those who had lesser counts in the rural sector also.
|Table 5: Adjusted odds ratios of factors associated with self-medication with allopathic drugs|
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| Discussion|| |
Our study revealed that prevalence of self-medication with allopathic drugs significantly differed in an urban (12.2%) and rural population (7.9%) in Sri Lanka though both types of districts had very similar prevalence of overall medication use (urban 33.9%, rural 35.3%). Interestingly, our estimates are lower than the figures reported from other countries. This substantiates the fact that there is wide variation in self-medication prevalence. The variation between and within countries is due to the use of different definitions of self-medication, difference in health seeking behaviour of people, socio-cultural factors, relative prevalence and the seasonal variation of illnesses.,
The prevalence of self-medication in developing countries is reported to be in the range of 12.7% to 95%., In Europe, estimates have been as high as 68%. Britain has reported prevalence estimates from 60% to 70%. In an urban community in Portugal, self-medication prevalence was 26.2% in urban and 21.5% in rural sectors., A study similar to our study in Spain reported a self-medication prevalence of 12.7% among adults with a recall period of two-weeks. A prevalence ranging from 9.7% to 39.9% in a two-day recall period has been reported in 12 cities in America and Europe. In Hong Kong prevalence of self-medication was 32.5% while in Jordan in the Middle East, it was 42.5%.
Self-medication is a widely practiced phenomenon in the South-East Asia Region also. Our estimates of self-medication are lower than estimates reported in South Asia. Similar to our finding, India too has reported an urban (37%) rural (17%) differential in self-medication. Nepal, Pakistan and Punjab in India have reported prevalence estimates of around 50%. However, it has to be borne in mind that in Nepal, the prevalence was estimated over a six month recall period while in Punjab, it was life-time prevalence. A low rate of prevalence is expected when the recall period is two weeks.
Our study confirmed the anticipated low prevalence of self-medication in the rural sector. So far only proxy indicators like relatively low self-medication prevalence for malaria medicine in Moneragala district had indicated low self-medication practice in a rural area. Though our population-based prevalence estimates are relatively low for both sectors, self-medication prevalence may be high in specific groups such as children (85%) of urban mothers. Similarly, another study using the same definition of self-medication and the same recall period used by us has reported that 49.6% of those who reported an episode of illness in an urban area in the Western Province had self-medicated.
Access to medical care and satisfaction with pharmacy services emerged as important predictors of self-medication. In many settings, patient’s satisfaction with the health care provider has been identified as an important factor affecting self-medication.,,, In the context of Sri Lanka, we found that despite the availability of a well-developed public-private health care network in the urban sector, when clients perceive available medical services to be irregular and unacceptable , they tend to resort to self-medication.
A majority of the respondents in our study self-medicated with one drug (urban 49%, rural 73%), for conditions that were perceived as mild and self-limiting (urban 55%, rural 64%). This was confirmed in the multivariate analysis where lower number of symptom count as a proxy measure of less severity of illness emerged as a strong predictor of self-medication. Thus, it is no wonder that due to perceived poor satisfaction with medical care, self-medication becomes a low cost alternative (no consultation fees, and direct/ indirect opportunity costs) particularly for mild illnesses among people with a busy urban lifestyle.
In contrast to the urban sector, perceived affordability of medical care decreased the likelihood of self-medication in the rural sector. It indicates that people in the economically weak rural area are more likely to consult a medical practitioner for a medical condition, than unnecessarily spending money on self-medication. This behaviour seems to be a way of rationally and efficiently spending hard-earned money on health in low-and middle-income areas. A similar behaviour has been demonstrated in a middle-income area of Brazil.
The fact that perceived technical competence of the pharmacy staff emerged as a predictor of self-medication in the rural sector leads to two implications. First, it reflects the central role a pharmacy plays as an alternative source of medical care in rural areas. Secondly, it indicates the extent to which clients in areas with scarce health services confide in the competency of the pharmacy staff as service providers for selected conditions. The symptom count acts as a proxy measure of the perceived severity of the illness for consumers to make a decision regarding physician consultation. Relying on staff of retail drug stores is a common phenomenon in the Region. In Nepal, drug retail shops frequently serve as the first point of contact with the health services. In India, pharmacists and pharmacy attendants fulfill this role.,, This fact is useful for policy makers as it enables designing policies and strategies on capacity building of pharmacy staff with a view to providing a better service to clients in rural areas.
This study has some limitations. Had a follow-up component been included it would have allowed an objective assessment of the disease conditions for which medicines were used. Use of a diary to collect information would have minimized the deficiencies of recall method. In this study, measures of access to medical care and satisfaction with pharmacy services were assessed in a general context. Relating their recent experiences to specific aspects of pharmacy care and specific pharmacies would have increased the validity of the data. More importantly, generalization of our study findings to other areas of the country may be limited since self-medication is a self-initiated behaviour which tends to vary from setting to setting.
In conclusion, it must be stated that self-medication, at comparatively low rates, exists in Sri Lanka with an urban-rural differential. Self-medication phenomenon should not be looked at negatively. The positive aspects of self-medication related to PHC should be recognized. However, policy makers and planners need to revisit policy and regulatory aspects to ensure restricting access to prescription-only drugs to minimize the negative impact of self-medication. To enable people to practice appropriate, safe and effective self-medication and obtain the maximum benefits, public information, communication and education packages should be developed. Pharmacy staff and dispenser capacity building programmes are other important activities in this regard. Given the finding that their perceived competence is a predictor of self-medication in rural areas, district health planners need to pay special attention to the strategy of empowering pharmacy staff as alternative prescribers for limited conditions/drugs.
Some measures of access to medical care play an important role in initiating self-medication behaviour.,,, Hence, measures to improve acceptability of services by clients, ensuring regular services and improving the focus on concerns for the client’s integrity by the staff are noteworthy considerations for reducing irrational and inappropriate medicines use. The national project for the improvement of quality and safety of healthcare institutions is an appropriate stepping stone to achieve this objective.
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[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]
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