Factors Affecting Medication Adherence among Elderly in Rural Areas, Sharkia Governorate, Egypt
Eman Shokry Abd Allah1, Sally Atia Mahmoud2, Mona Mostafa Abo Serea3
1Professor of Community Health Nursing and Gerontological Nursing, Faculty of Nursing, Zagazig University, Egypt, Email: [email protected]
2Clinical Instructor of Gerontological Nursing, Faculty of Nursing, Zagazig University, Egypt, Email: [email protected]
3Professor of Community Medicine, Faculty of Medicine, Zagazig University, Egypt, Email:
Corresponding Author: Sally Atia Mahmoud, Email: [email protected]
Abstract
Background: Medication non-adherence is a public health problem at every level of the population, especially in older adults. The aim of the current study was to assess the factors affecting medication adherence among elderly in rural areas, sharkia governorate. Subjects and methods: A cross-sectional study was carried out; the study was conducted at Sharkiat Mobasher Village, Elibrahemya District, Sharkia Governorate. A sample of 120 elderly subjects who fulfilled the study inclusion criteria was included in the study. Data collected by a structured interview questionnaire, Beliefs about Medicines Questionnaire (BMQ) and The General Medication Adherence Scale (GMAS). Results:The study results revealed that more than half (58.3%) of the studied elderly had poor adherence and the majorty of the studied sample (96.7%), (88.3%) had unsatisfactory disease& medication knowledge respectively.
Recommendations: Identifying specific barriers for each elderly patient, and adopting suitable techniques to overcome them, especially family member's involvement, will be necessary to improve medication adherence in further researches.
Keywords: Medication Adherence, Factors, Elderly, Rural areas.
Introduction
Population ageing is a human success story, reflecting the advancement of public health, medicine, and economic and social development, and their contribution to the control of disease, prevention of injury, and reduction in the risk of premature death. The extension of human longevity and subsequent reduction in levels of fertility lead inevitably to a shift in the population age distribution from younger to older ages (United Nation [UN], 2020). Egypt, along with other middle-income African countries is experiencing a great increase in the share of its population aged 65 and older. Population ageing is typically viewed as a minor concern in Egypt (Angeli & Novelli, 2019). Additionally,The number of older people reached 6.5 million of (3.5 million for males, 3.0 million for females), representing 6.7% of the total population (Central Agency for Public Mobilization and Statistics [CAPMAS], 2019). Rural seniors suffer from more chronic diseases than their urban counterparts.
Furthermore, the health of rural elders is influenced by a lack of health insurance, shortages of doctors, other health care workers, limited access to health care services and lack use of new medical technology in rural areas; which become barriers for rural seniors to get health care for prevention and treatment of diseases (Morken & Warner, 2012). Adherence to long- term therapy can be defined by the extent to which a person’s behavior taking medication, following a diet and/or executing lifestyle changes corresponds with agreed recommendations from a healthcare provider. It is a dynamic process in which the patient is involved to actively participate. It can be explained as a combination of the term "compliance" which means taking the right dose at the right time and the term "persistence" which means taking the
treatment continuously during the period of time prescribed (Lavielle et al., 2018). In developed countries, medication adherence rates for chronic disease were reported at 50% by the WHO, and were expected to be lower in developing countries with less access to health care. Overall, the estimated rates of non-adherence to medications in Arab countries range from 1.4% to 88% in the different studies (Hasan et al., 2019). Specific to the elderly, the rates of non-adherence to pharmacological treatments are estimated to vary from 41 to 74%
among older adults (Junior et al., 2013). The WHO report on medication adherence goes on to describe five categories of factors that affect medication adherence: patient-related factors, socioeconomic factors, health care provider and health care system factors, medication - related factors, and condition-related factors (Levy et al., 2018). To effectively increase adherence among older adults strategies should be formed to properly identify barriers to medication adherence (Saqlain et al., 2019). Poor adherence among older persons is a public health concern, as it accounts for adverse outcomes, medication wastage with increased cost of healthcare, and substantial worsening of the disease with increased disability or death. This poses a greater responsibility on the health services especially in developing countries; where there is a greater strain on available health infrastructure and delivery systems (Shruthi et al., 2016). So, The aim of the current study was to assess the factors affecting medication adherence among elderly in rural areas, sharkia governorate.
Study Questions
1. What is the prevalence of medication adherence among elderly in rural areas?
2. What are the factors affecting medication adherence among elderly in rural areas?
Subjects and Methods
A cross- sectional study was carried out. The study was used multistage random sampling technique to select Sharkiat Mobasher Village from Elibrahemya District, Sharkia governorate from the beginning of April 2020 up to the end of June 2020 with taking into account the preventive and precautionary measures to prevent COVID-19.
A cluster sample composed of 120 elderly who fulfilled the following inclusion criteria:
above the age of 60 years of both the sexes, Elderly is taking at least one medication by doctor’s prescription for more than 6 months for chronic diseases, Ability to self-administer medications or take with minimal assistance, Free from communication problems, and Willing to participate in the study.
Sample size; as the total number of elderly at the selected village is 540 CAPMAS, (2019)and assuming the frequency of high adherence to medication is 11.2%, with 5%
confidence limit and 1 design effect. So the calculated sample was 120 elderly using Open EPI program.
Tools of data collection
Tool I-A structured interview questionnaire was developed by the researcher which is consisted of three parts:
Part 1: Personal data of the studied elderly.
Part 2: Medical & medication history of the studied elderly.
Part 3: Elderly’s chronic disease & medication Knowledge to assess the study subject's knowledge regarding their disease & medication regimen used to treat their chronic disease.
Scoring system: The total number of disease knowledge questions is four, medication knowledge include ten questions; all items were scored 2 for "correct answer", 1 for ''don't know'', and Zero for "wrong answer".
The total grade of disease and medication knowledge questions was considered satisfactory if the percent score was 60% or more and unsatisfactory if less than 60% . Tool II concerning
the Beliefs about Medicines Questionnaire (BMQ): This tool was developed by Horne, et al., (1999) to assess the cognitive representations of medications. BMQ consists of two sections, general and specific. The specific section composed of specific-necessity and specific- concerns scales. The general section composed of the general-overuse and the general-harm scales. Higher scores indicate stronger beliefs in the concepts of the scale. Tool III concerning The General Medication Adherence Scale (GMAS): this tool was developed by Naqvi et al., (2018) to assess adherence to medication in patients with chronic conditions. Arabic version was obtained & approved to use by the questionnaire developers through e-mail communications. The GMAS consisted of 11 questions to measure adherence across three domains namely; 1) non-adherence due to patient behavior (PBNA), i.e., un-intentional and intentional non-adherence, 2) comorbidity and pill burden related non-adherence (ADPB), and 3) cost-related non-adherence (CRNA). Scoring system: Grading for cumulative medication adherence: high adherence(30–33),good adherence (27–29), partial adherence (17–26), low adherence (11–16)and Poor adherence (0–10). Administrative and ethical consideration were taken into consideration especially informed consent from the studied persons.
Results
Table (1) shows that, the studied elderly's age ranged between 60 - 88 years, 58.3% of them were illiterate. Concerning their income, 56.7% of the studied elderly had sufficient income, and the highest percentage 75 % of the studied elderly weren't having health insurance. Table (2) explains that, the mean number of chronic diseases among the studied elderly was 2.5 ± 1.3. The table also reveals that 50.0% of the studied elderly were taking 3-4 medication daily with mean 4.1 ± 1.5 drugs. Table (3) demonstrates that positive beliefs about the necessity of medication had recorded the lowest mean(10.74±2.1), While beliefs that medicines are generally overused recorded the highest mean level (16.39±1.42). Figure (1) illustrates that the majority of the studied elderly were having unsatisfactory disease knowledge (96.7%).
Figure (2) illustrates that the majority of the studied elderly were having unsatisfactory medication knowledge (88.3%). Figure (3) demonstrates that 58.3% of the studied elderly were poor adherent to their medications. Table (4) points to high statistically significant positive correlation between medication adherence, specific necessity, knowledge, education and income. Conversely, there was a statistically significant negative correlation between medication adherence, age, health insurance, number of disease, number of medications, specific concern, general-overuse and general-harm.
Discussion
Adherence to a medication regimen is central to the proper management of chronic health conditions in general. However, adherence to medications is not a simple task considering its multifactorial nature. Central to improving medication adherence is the understanding of a patient’s reasons for non-adherence (Jimenez, et al., 2017). Concerning the prevalence of medication adherence, the result of the current study showed that more than half (58.3%) of the studied elderly were low adherent to their medications. This result might be attributed to that high rural illiteracy, socio economic factors, lack of awareness regarding the importance of medication adherence. Also, increasing number of drug use in these individuals leads to an increase in the risk of side effects, risk of drug interactions, and toxicity, which may exacerbate cognitive and behavioral changes in the elderly, consequently disrupting the implementation of medication prescriptions, and non-adherence to medication regimen. The current study result was congruent with the finding of an Egyptian study conducted by Hussein et al., (2020) who found that the rate of non-adherence among the Egyptian elderly was (67.4%). This also consistent with Jin et al., (2016) in Korea, who mentioned that 52.5%
of the elderly was low adherent to the medication. Furthermore, Akoko et al., (2017) in Cameroon reported that the rate of non-adherence among participants was (56.1%). These countries with similar compliance rates are all developing countries might be attributed to that the health care systems are not the best in these countries, and when coupled with patient factors or the patients’ attitude towards health, adherence rates are likely to be low. Regarding personal characteristics of the studied elderly, according to table (1), the present study revealed that, approximately three- quarters of the studied elderly's were in the age group 60 to less than 70 years old; this might be due to that presence of larger number of individuals of this age group in our country. Additionally, more than half of them were illiterate; this finding might be attributed to living in rural areas associated with lack of interest in education thus the education is still low in many rural areas. Moreover, almost of the studied elderly weren't working; such results might be attributed to the elderly's beliefs about old age is the time to relax, worship and draw closer to God. Also, the present study sample had major preponderance of women. In the same context, Xu et al., (2020) in china, reported that more than half of the participants were in the age group 60 -69 years old, approximately three- quarters of them were illiterate and not working. Also,the majority of respondents were female. Additionally, the majority of the studied elderly were lived with their family could be explained by that Middle-Eastern cultures are considered to possess more collectivist values where societies tend to encourage interdependence and therefore traditionally provide support and care for older people within their families. On the same line, Xu et al., (2017) carried out a study in China; found that most of the study subjects were living with their families.
Moreover, Woodham et al., (2018) in rural area, Thailand found that almost all of the studied elderly were living with family members. According to the present study finding, more than half of the studied elderly had sufficient income. This finding might be due to strong family ties and social integration among the inhabitants of the village and majority of them depend on agriculture as a source of their income. The present finding was in agreement with the result of the study carried by Cho et al., (2018) in Korea, who found that the majority of the participants had middle &high income. As regards to health insurance, the present results indicated that, three quarters of the studied elderly weren't having health insurance. This finding in accordance with the result of the study carried by Ajibola & Timothy, (2018) in Nigeria, who found that the majority of the participants (61.8%) were uninsured. Concerning the frequency of various comorbidities, table (2) the present study findings revealed that more than half of the studied elderly had one or two chronic diseases. Additionally, the majority of them have HTN or DM from more than 5 years. The present finding was in agreement with the result of the study carried by Jin et al., (2016) in Korea, who mentioned that,three quarters of the studied elderly had 1-3 health condition. Conversely, other study carried by Paisansirikul et al., (2021) in Bangkok, revealed that more than half of the participants had three or more comorbidities. This discrepancy may be attributed to the differences in the population under the study. Regarding the medication history the current study (table 3), illustrated that more than half of the studied elderly were used < 5 types of medications daily, use non- prescribed medications and about three quarters of them spend 25% -50% of their monthly income for purchasing their medication. These results were consistent with Algabbani & Algabbani, (2020) who conducted a study in Saudi Arabia, and stated that the majority of participants reported taking less than four medications a day. Additionaly Sridhar etal.,(2018) in United Arab Emirates, reported that the prevalence of self‑medication practices among the studied subjects was 52.1% . Concerning Elderly’s disease Knowledge, the present study findings revealed that the majority of studied elderly had unsatisfactory disease knowledge. In the same line, a study conducted by Almadhoun & Alagha, (2018) in Palestine reported that (64.2%) of the participants had a low level of disease knowledge. Similarly, Jankowska-Polańska etal., (2016) in Poland who found that, 63% of patients showed a low
level of knowledge. Concerning medication knowledge, the present study findings revealed very deficient knowledge among studied elderly . The deficient knowledge depicted among the elderly in the present study might be attributed to the low level of education as well as their mental abilities, which could be affected by the aging process. Also, increase total number of medications. Supporting results were found by Mekonnen& Gelayee, (2020) in Ethiopia, who found that a majority of the participant had low level of medication knowledge.
According to table (4), the present results indicated that, there was a statistically significant negative correlation between medication adherence and the studied elderly's age. In agreement with the foregoing present study finding, Mamaghani, et al., (2020) in Iran, reported that a significant negative relationship existed between age and medication adherence. Similarly, study conducted in India by Shruthi et al., (2016) who found that the adherence level has decreased progressively with increasing age, with statistically significant difference (p<0.05). Thus, it appears that age may be an important factor which may affect the medication compliance, probably because of the age related functional decline. According to the present study findings there was a statistically significant positive correlation between adherence and education. The rationale of this phenomenon might be due to that the low level of education can hinder understanding regarding the use of medications and the adherence to prescribed therapy, resulting in harm to the health of the elderly.These results were consistent with Gautério-Abreu et al., (2015) who conducted a study in Brazil, and stated that the prevalence of non-adherence was 21% higher in those with low level of education. The present study findings showed that there was a statistically significant positive correlation between adherence and income. This result might be attributed to; the patients may be more adversely influenced by economic factors that lead them to not following drug regimens.
Thus, patients with more concerns of the medical cost are less likely to adhere to their drug regimens. The present finding was in agreement with the result of the study carried by Cho et al., (2018) in Korea, who found that a high income positively associated with medication adherence. Moreover, the negative corelation between medication adherence and health insurance was confirmed in the correlation matrix analysis. These findings might be due to that, patients with chronic diseases require lifelong continuous medical treatment; each patient needs to allocate a specific budget every month to purchase medications. Furthermore, there is a wide range of rural people without any medical insurance coverage, and the patients may have to pay out-of-pocket. In agreement with these foregoing present study findings Ajibola & Timothy, (2018) in Nigeria, reported that a significant association between adherence and health insurance. According to the present study results, there was a statistically significant negative correlation between adherence and number of chronic diseases. These results might be due to the high prevalence of multiple comorbidities in older populations, so elderly are more likely to be on multiple medications. Also, the long term therapy would lead to variability in motivation and thus medication adherence would also falter in the long run. The foregoing present results in the same context with Algabbani &
Algabbani, (2020) in Saudi Arabia, who found that, the presence of comorbid conditions is significantly associated with medication adherence (P < 0.001). similarly, Mamaghani, et al., (2020) in Iran, support this result. The present study showed a statistically significant negative correlation between total numbers of medication used and adherence to the medication regimen, with the elderly patients who had more medication less adhered to their medication regimen, These findings might be due to that, an increase in the number of drugs used may cause the elderly people to forget the time of some drugs, as well as make them unfamiliar with the medication instructions. In agreement with the present study finding, Shareinia et al., (2020) in Iran, reported that a significant association between polypharmacy and medication adherence. Based on the present study finding there was a statistically significant positive correlation between disease knowledge and adherence. The foregoing
present study finding was in agreement with previous studies, which demonstrated that there was a statistically significant association between disease knowledge and adherence with treatment. Participants who had adequate knowledge of their chronic disease were more adherent than those who had inadequate knowledge Akoko et al., (2017) in Cameroon and Jankowska-Polańska etal., (2016) in Poland. The present results indicated that, there was a statistically significant positive correlation between medication adherence and medication knowledge . On the same line, Okuyan et al., (2013) inTurkey, who stated that there was a statistically significant correlation exists between the medication knowledge score and the level of medication adherence. As revealed in the present study findings, there was a statistically significant positive correlation between medication adherence and the specific necessity beliefs .Hence, as the necessity beliefs increases, adherence also increases. On the same line, a study in Romania by Sipos et al., (2020) demonstrated that higher adherence was significantly correlated with higher necessity. The present study findings revealed that adherence had statistically significant negative correlation with the specific concerns, general- harm scale and general over use beliefs . These results were consistent with Alhewiti, (2014), who conducted a study in Saudi Arabia, and stated that there was a significant negative association between adherence score and BMQ specific concerns, general overuse, and harm.
In the current study, the mean score of specific necessity (10.74±2.1) is less than the mean score of specific concern (12.71±2.43). The finding is in congruence with Raza et al., (2020) in Pakistan reported that the mean score of specific necessity is less than the mean score of specific concern which indicates the expectation of lower medication adherence likely due to patients’ concerns about side effects.
Conclusion
In the light of the study findings, it can be concluded that, adherence to long-term treatments for chronic conditions remains a challenging issue in older adults. In the present study, more than half of the participants were nonadherent to medication. There was high statistically significant positive correlation between medication adherence, specific necessity, knowledge, education and income. On the other hand, there was a statistically significant negative correlation between medication adherence practices, age, health insurance, number of disease , number of medications and specific concern, general-overuse and general-harm.
Recommendations
- Identifying specific barriers for each elderly patient, and adopting suitable techniques to overcome them, especially family member's involvement, will be necessary to improve medication adherence.
- Further researches are suggested to examine the effectiveness of adherence enhancing intervention & develop more effective strategies suitable for different population, diseases and drug formulations to improve medication adherence among vulnerable elderly.
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Frequency Percent Age group: /year
60- 70-
≥80
86 26 8
71.7 21.7 6.6 Mean ± SD
(range)
66.7 ± 6.3 (60 – 88) Gender:
Male Female
44 76
36.7 63.3 Marital status:
Married Widow
60 60
50.0 50.0 Education:
Illiterate Read & write Basic
Preparatory
Intermediate (secondary) University/ post
70 24 8 4 8 6
58.3 20.0 6.7 3.3 6.7 5.0 Current occupation:
Working Not working
8 112
6.7 93.3 Living with whom:
Family Alone
116 4
96.7 3.3 Income:
Insufficient Sufficient
Sufficient and saving
48 68 4
40.0 56.7 3.3 Health insurance :
Governmental No insurance
30 90
25.0 75.0
Table 2: frequency distribution of diseases and medication related factors
Variables (no=120)
Frequency Percent Types of chronic diseases:@
HTN DM
GIT diseases Respiratory diseases Liver diseases Renal diseases Cardiac diseases
Other[cancer, disc, osteoarthritis]
60 60 26 20 30 26 44 20
50.0 50.0 21.7 16.7 25.0 21.7 36.7 16.7 Total no. of diseases:
1-2 3-4 > 4
62 46 12
51.7 38.3 10.0 Duration of (HTN or DM disease):
< 5 years ≥ 5 years
12 108
10.0 90.0 Number of all medications that were taken per day:
1-2 3-4
≥5
Mean ± SD (Range)
16 60 44
13.3 50.0 36.7
Type of medications@:
Anti-Hypertensive Anti-Diabetic Vitamins& minerals Sedatives[NSAIDs]
Anti-coagulants
Neurogenic medications
Cholesterol lowering medication
Others [respiratory, chemotherapy, hepatic, GIT, renal]
60 60 68 50 38 56 28 24
50.0 50.0 56.7 41.7 31.7 46.7 23.3 20.0 Usage of non- prescribed medications:
Yes No
66 54
55.0 45.0 Medication cost per month
Less than 25% of the monthly income, 25% -50% of the monthly income More than 50% of the monthly income
18 88 14
15.0 73.3 11.7
4.1 ± 1.5 (1 – 8)
Figure 1: Percentage distribution of diseases knowledge
11.7%
87.3%
Medication Knowledge
Satisfactory Unsatisfactory
Figure 2: Percentage distribution of medication knowledge
Figure 3: Percentage distribution of level of adherence Table 3: Total mean score of Beliefs about Medicine Questionnaire [BMQ]
Subscale Mean ± SD Range
Specific-necessity 10.74±2.1 9-18
Specific-concern 12.71±2.43 10-17
General -overuse 16.39±1.42 12-20
General -harm 14.01±1.8 9-18
Table 4:Correlation matrix of medication adherence scores and elderly's characteristics Scores
Spearman's rank correlation coefficient Knowledge Adherence BMQ[Specific
necessity]
BMQ[Specific concern]
BMQ[general -overuse]
BMQ[general- harm]
Knowledge
Adherence .564**
BMQ[Specific
necessity] .392** .426**
BMQ[Specific
concern] .232 -.455** -.340**
BMQ[general-
overuse] -.218 -.471** .059 .281*
BMQ[general-
overuse] -.389** -.316* -.304* -.168 .082
Age -.218 -.260* -.253 .074 .117 .110
Education
level .701** .446** .213 .034 -.230 -.227
Income .379** .259* .206 .020 -.008 -.216
Health
insurance -.543** -.298** -.144 .035 .305* .074
Number of
diseases -.160 -.140* -.059 .129 .116 .113
Number of
medications .324 -.287** -.408* -.168 .082 .173*
