Research Article - Biomedical Research (2018) Volume 29, Issue 12
The prevalence of drug-drug interactions and polypharmacy among elderly patients in Jordan
Walid Al-Qerem*, Yazun Bashir Jarrar, Iyad Al-Sheikh and Abdullah ElMaadani
Department of Pharmaceutical Sciences, College of Pharmacy, Al-Zaytoonah University, Amman, Jordan
- *Corresponding Author:
- Walid Al-Qerem
Department of Pharmaceutical Sciences
College of Pharmacy
Accepted date: May 07, 2018
Background: The number of people aged 60 or older is estimated to be 5.6% among Jordanian population, those elderly people need special medical care; since they have a greater prevalence of chronic diseases and therefore subjected to higher prevalence of polypharmacy and potential drug-drug interaction (pDDI). There is no data about polypharmacy and pDDI in elderly patients among the Jordanian population.
Methods: Prescriptions for patients aged 60 or older were examined and those patients were interviewed in several community pharmacies and hospitals’ outpatient pharmacies. The interviews covered factors that may affect the possibility of pDDI and polypharmacy including patient’s education level, number of doctors the patient see, number of drugs the patient take, does the patient live alone and does the patient take the medication by himself.
Results: 367 (51.5% male and 48.5% female) patients were interviewed and their prescriptions examined. The data showed that 334 (91%) had at least one pDDI of those 67 (18.3%) had a major pDDI and 281 (76.6%) had at least one moderate pDDI. Polypharmacy was found in 275 (74.9%) of the participants. Factors that were associated with incidence of major pDDI included polypharmacy, taking Alimentary tract and metabolism drugs or drugs acting on blood and blood forming organ, and patient taking medication by him/herself. Several factors were associated with moderate pDDI including seeing a general practitioner, while polypharmacy was associated with education level and number of diseases.
Conclusion: High incidence of major and moderate pDDI and polypharmacy was found. This study emphasizes the need for a better control over elderly prescription in Jordan.
Polypharmacy, Drug-drug interaction, Geriatrics, Jordan
Drug-Drug Interaction (DDI) means that one drug alters the response of the other . Depending on the effect of the DDI on patients, the DDI can be classified into beneficial, harmful or neutral . The mechanism of DDI includes inhibition or induction of drug-metabolizing enzyme, inhibition of drug transporters and competition on plasma albumin which can affect the pharmacokinetic parameters . In addition, some drugs may influence the pharmacodynamics of other drugs, such as warfarin and vitamin K interaction . It is reported that DDI accounted to cause 4.8% of total hospitalization cases, which increases the medical costs and mortality among patients [5,6].
Polypharmacy has been defined as concurrent consumption of several medications. However, the exact definition varies in literature. While some studies required the usage of 5 or more medications a day to be labelled “polypharmacy”, other defined it as the usage of two or more medications [7-9].
Polypharmacy is more common in aged people with chronic diseases . It is estimated that more than 40% of adults aged 65 or older are on polypharmacy . As number of drug medications increase, the potential of DDI may increase . In addition, polypharmacy was associated with several adverse outcomes including hospitalization, nursing home placement, death, hypoglycemia, fractures, impaired mobility, pneumonia, and malnutrition .
The number of people aged 60 or older is estimated to be 5.6% among Jordanian population, which is lower than the worldwide elderly population percentage (12%) . Those elderly people need special medical care; since they have a greater prevalence of chronic diseases and therefore exposed to a high number of drugs administration and higher risk of DDI . It is reported that the prevalence of DDI among elderly patients is 13-58%, leading to greater hospital admissions and mortality [15,16].
There is no data regarding polypharmacy and DDI in elderly patients among Jordanian population. Therefore, the aim of this study was to find the prevalence and type of potential drugdrug interaction and the prevalence of polypharmacy among Jordanian elderly patients. The study also examined the factors associated with pDDIs and polypharmacy.
Post graduate students in pharmaceutical science in AlZaytonah University examined prescriptions for patients aged 60 or older and interviewed these patients in several pharmacies and hospitals in Amman, Madaba and Zarqa in Jordan during the period from October 2017 to January 2018. The interviews covered factors that may affect the possibility of DDI and/or polypharmacy including patient’s education level, how many doctors does the patient see, how many drugs does the patient take, does the patient live alone and if the patient takes the medication by himself, does the patient suffer from any chronic disease. The severity of the potential drugdrug interaction (pDDI) was classified in accordance with drugs.com and Lexicomp Online® into 3 categories [17,18]:
1. Minor: Minimally clinically significant which are equivalent to lexicomp category B;
2. Moderate: Moderately clinically significant which are equivalent to lexicomp category C.
3. Major: Highly clinically significant, generally avoid or modify drug regimen; the risk of the interaction may outweigh the benefits which is equivalent to Lexicomp categories D and X.
In case conflicting results were found between drugs.com and Lexicomp we would classify the interaction according to the more severe category
All medications were classified according to the Anatomical Therapeutic Chemical Classification System (ATC) .
The ethical approval was obtained from AlZaytonah University Ethical Committee before beginning this study.
In addition, the present study examined the number of drugs used and the prevalence of polypharmacy among the studied sample. Polypharmacy in this study was defined as concurrent consumption of 5 medications or more per day.
All continuous variables were expressed as means (M) ± standard deviations (SD). For categorical variables, frequencies and percentages were reported.
Chi-square (χ2) test was performed between different categorical variables including polypharmacy and pDDI (All, moderate and major), with different classes of drugs, gender, visiting a general practitioner (GP), age group, education level, and taking the medicine by himself.
A univariate and forward stepwise multivariate binary logistic regression models were performed, the binary outcome variable in the models was (moderate pDDI, no pDDI), the independent variables considered include: age group, gender, education level, does the patient live alone, does the patient take the medicine by himself, polypharmacy, different types of medication, number of doctors seen by the patient, and does the patient see a GP. Other univariate and forward stepwise multivariate binary logistic regression models were performed to investigate the relation between several factors and polypharmacy, the multivariate regression model included all the previously stated predictors and the outcome was (polypharmacy, no polypharmacy). All binary logistic regressions assumptions were evaluated including multicollinearity and linearity of independent variables and log odds. The data were analyzed using SPSS software .
The demographics of the studied sample are shown in Table 1. The total sample studied was 367 (51.5% male and 48.5% female). Major pDDI’s were found in 18.3% of the participants. The average of number of drugs involved in a major pDDI in participants that had major pDDI was 2.98 ± 1.57 and the maximum reported number of drugs was 7. Polypharmacy was found in 74.9% of the participants and the average number of drugs per patient was 5.5 ± 2.1. Most of the patients (78.5%) were currently seeing more than one doctor (1.67 ± 0.81).
|Patient living alone||40||10.9|
|Types of doctor seen|
|General practitioner only||36||9.8|
|Number of drug per patient||5.5||2.13|
|Number of drugs involved in major pDDI in patients with major pDDI||2.98||1.57|
|Number of diseases per patient||2.45||1.15|
|How many physicians does the patient visit currently?||1.67||0.81|
Table 1. Demographic and clinical characteristics of participants (N=367).
Table 2 shows the number of drugs used by the participants and their ATC classes. The participants were on 2022 medications of those 1745 (86.3%) were involved in polypharmacy and 154 (7.6%) in major pDDI. The most commonly ATC class used was cardiovascular (783, 38.7%), 35.3% of those were agents acting on the renin-angiotensin system. Alimentary tract and metabolism drugs were 27.2% of the drugs used; most of those drugs were for diabetes and drugs for acid-related disorders. Drugs acting on blood and blood forming organs were 12.7%, the majority of which were antithrombotic agents. The majority of drugs involved in a major pDDI were cardiovascular drugs (61, 39.6%), followed by drugs acting on blood and blood forming organs (47, 30.5%) and alimentary tract and metabolism drugs (18, 11.7%). However, the most common subgroup involved in major pDDI were antithrombotic agents (45, 29.2%), followed by lipid modifying agents (22, 14.3%) and acid-related disorders (14, 91%).
|Polypharmacy (>5 drugs)||1745||86.3|
|Drugs involved major pDDI||154||7.6|
|Alimentary tract and metabolism (A)||594||27.2|
|Drugs used in diabetes (A10)||230||38.7|
|Drugs for acid related disorders (A03)||185||31.1|
|Mineral supplements (A12)||30||5|
|Blood and blood forming organs (B)||256||12.7|
|Antithrombotic agents (B01)||198||77.3|
|Anti-anemic preparations (B03)||32||12.5|
|Cardiovascular system (C)||783||38.7|
|Cardiac therapy (C01)||37||4.7|
|Beta blocking agents (C07)||109||13.9|
|Calcium channel blockers (C08)||78||9.9|
|Agents acting on the renin-angiotensin system (C09)||277||35.3|
|Lipid modifying agents (C10)||164||20.9|
|Genito urinary system and sex hormones (G)||33||1.6|
|Systemic hormonal preparations, XCL. Sex hormones and insulin’s (H)||24||1.2|
|Anti-infective for systemic use (J)||59||2.9|
|Antineoplastic and immunomodulating agents (L)||10||0.5|
|Musculo-skeletal system (M)||76||3.8|
|Nervous system (N)||154||7.6|
|Anti-parasitic products, insecticides and repellents (P)||2||0.1|
|Respiratory system (R)||52||2.6|
|Sensory organs (S)||6||0.3|
Table 2. The number of drugs used by the participants and their ATC classes and codes.
Table 3 shows the percentage of patients on different ATC drug classes. As the table shows most of the patients were taking cardiovascular drugs, followed by Alimentary tract and metabolism drugs and drugs acting on blood and blood forming organ.
|Drug type||All patients||Polypharmacy||Major drug interaction|
|Blood and blood forming organ (B)||195||53.1||172||62.6||40||65.5|
|Alimentary tract and metabolism (A)||292||79.6||236||85.8||43||70.5|
|Cardiovascular system (C)||312||85||238||86.5||54||88.5|
|Nervous system (N)||104||28.3||93||33.8||18||29.5|
|Musculo-skeletal system (M)||72||19.6||59||22.1||7||11.5|
|Anti-infective for systemic use (J)||46||12.5||44||16||9||14.8|
Table 3. Percentage of patients on different ATC drug classes.
Chi-square test (Table 4) showed statistically significant correlations between all pDDI and the following: polypharmacy, being on alimentary tract and metabolism, being on blood and blood forming organ and cardiovascular system medications, while major pDDI was significantly associated with alimentary tract and metabolism drugs, drugs acting on blood and blood forming organ and patient taking the medication by her/himself; polypharmacy was significantly correlated with alimentary tract and metabolism drugs, drugs acting on blood and blood forming organ, drugs acting on the nervous system, anti-infective drugs for systemic use, patient taking the medication by her/himself, education and age group.
|Frequency (%)||X2||P||Frequency (%)||X2||p||Frequency (%)||X2||P|
|Polypharmacy||N/A||268 (80.2)||55.7||p<0.01||51 (83.6)||2.93||0.08|
|Alimentary tract and metabolism||236 (80.8)||26.39||p<0.01*||247 (82)||13.9||p<0.01||43 (14.7)||3.7||0.04*|
|Blood and blood forming organ||172 (88.2)||39.02||p<0.01*||188 (56.3)||14.83||p<0.01||40 (20.5)||4.54||0.03*|
|Cardiovascular system medication||238 (76.3)||2.02||0.15||293 (87.7)||21.42||p<0.01||54 (17.3)||0.71||0.4|
|Nervous system||93 (89.4)||16.21||p<0.01*||96 (28.7)||0.3||0.58||18 (17.3)||0.05||0.8|
|Anti-infective for systemic use||44 (95.7)||12.02||p<0.01*||44 (13.2)||1.38||0.24||9 (19.6)||0.32||0.53|
|Patient taking the medication by himself||192 (71.6)||12.02||p<0.01*||240 (71.9)||2.57||0.11||38 (14.2)||4.23||0.04*|
|Illiterate||44 (80)||26.38||p<0.01*||52 (15.6)||5.87||0.21||10 (18.2)||1.8||0.76|
|Primary||90 (88.2)||97 (29)||19 (18.6)|
|Secondary||76 (76.8)||88 (26.3)||18 (18.2)|
|University||55 (58.5%)||83 (24.9)||12 (12.8)|
|Post-Graduate||10 (58.8)||14 (4.2)||2 (11.8)|
|60-69||152 (70.4)||6.683||0.03*||193 (57.8)||1.87||0.39||34 (15.7)||0.65||0.72|
|70-79||83 (83.8)||93 (27.8)||19 (19.2)|
|>80||40 (76.9)||48 (14.4)||8 (15.4)|
Table 4. The relation between pDDI, major pDDI and polypharmacy with covariates and ATC drug classes.
Stepwise logistic regression (Table 5) was performed to analyze factors associated with moderate pDDI. As mentioned previously the model included age group, gender, education level, does the patient live alone, does the patient take the medicine by himself, polypharmacy, different types of medication, number of doctors seen by the patient, and does the patient see a GP. The model showed good fit as Hosmer- Lemeshow test p value was above 0.05 (p=0.9) and Cox and Snell R square indicated that the model explained 14.5% of the variances while Nagelkerke R square indicated that 21.9% of the variances were explained. The results showed that the probability of having a moderate pDDI increases with cardiovascular and nervous system medications and polypharmacy and decreases with seeing a GP.
|Factors||Univariate logistic regression||Multivariate logistic regression|
|Crude OR||P||95% CI||Adjusted OR**||P||95% CI|
|*GP is an abbreviation of general precisionist.|
Table 5. Factors associated with moderate pDDI.
Factors associated with polypharmacy were also analyzed using logistic regression (Table 6). The model included the same predictors mentioned above excluding polypharmacy. The model showed good fit as Hosmer-Lemeshow test p value was above 0.05 (p=0.61) and Cox and Snell R square indicated that the model explained 27.4% of the variances while Nagelkerke R square indicated that 40.6% of the variances were explained that females had higher odds to have a polypharmacy when compared with males. The results also indicated that being on alimentary tract & metabolism drugs, blood and blood forming organs, and nervous system medications, increases the risk of having polypharmacy. The results also indicated that number of diseases increased the odds of polypharmacy, while education decreased it.
|Factors||Univariate logistic regression||Multivariate logistic regression|
|Crude OR||P||95% CI||Adjusted OR||P||95% CI|
|Alimentary tract and metabolism||0.39||<0.01||2.27-6.67||4.363||<0.01||2.120-8.982|
|Blood and blood forming organs||5.01||<0.01||2.95-8.5||8.963||<0.01||4.598-17.474|
|Number of diseases||0.63||<0.01||0.49-0.81||1.71||<0.01||1.27-2.29|
Table 6. Factors associated with polypharmacy.
This study examined the prescriptions of outpatient Jordanian geriatrics in community pharmacies and hospitals’ outpatient pharmacies. To the best of our knowledge, this study is the first report regarding the pDDIs and polypharmacy among geriatric Jordanian patients. We found a high prevalence of pDDIs and polypharmacy among Jordanian geriatric patients. Accordingly, further studies should be done to reduce the DDIs and DDI-induced mortality in Jordanians.
Prevalence of pDDI and polypharmacy
The study found that the overall prevalence of pDDI among the studied sample is 91%, of those 18.5% had at least one major pDDI. This is significantly lower than reported in other studies including a study conducted on hospitalized cardiac patients that reported that 86.3% had at least one major pDDI, but significantly higher than other studies, for example a study reported that the major DDI was only 3.4% [2,21]. This wide variation could be attributed differences in methodology including the age of the studied sample.
Most studies that examined the prevalence of polypharmacy were conducted in the inpatient setting [8,22-26]. However, in this study we investigated the prevalence of polypharmacy in the outpatient settings to capture a more comprehensive insight. We found that 74.9% of the participants used 5 drugs or more. The prevalence of polypharmacy, found in this study, is significantly higher than what was reported in a previous study conducted in Jordan in 2012, which reported that 44.8% of the studied geriatrics used 5 drugs or more . However, when compared to other studies in the region that used the same definition of polypharmacy, our findings were significantly lower. For example a study done in Saudi Arabia reported that 96% of the participants aged above 60 used 5 drugs or more . Another study conducted in Dubai reported that 89% of the participated patients were taking more than five medications . Our results were comparable to a study conducted in Oman on discharged geriatrics and reported polypharmacy in 76.3% of the participants .
As reported previously, our study found significant correlation between polypharmacy and major pDDI ; where 95.6% of participants who had at least one major pDDI where using more than 5 drugs. Therefore, the high prevalence of pDDIs, found in this study, is due mainly to the polypharmacy.
Association with gender
There are conflicting findings in the literature regarding the association between gender and pDDI and polypharmacy. For example it was reported that women had a lower probability of having potentially serious DDIs (type D), which should be avoided, than men, while another study found that female gender was positively associated with pDDI [2,30]. Other studies in accordance with this study, found no association between pDDI and gender [31,32]. These contradicting finding maybe attributed to differences in the methodologies of the studies. However in accordance with several previous studies, we have found an association between polypharmacy and female gender [9,33,34]. Although other studies have reported that gender influence diminished in elderly population, our results did not indicate [35,36].
Association with education
The regression results showed that level of education was negatively associated with polypharmacy which is in accordance with previous studies findings [37,38]. This might indicate the importance of awareness toward drug use.
Association with comorbidities and drug classification
The results indicated that polypharmacy was positively associated with number of comorbidities as reported previously .
The most common prescribed groups for all patients (with or without polypharmacy) was for the cardiovascular system, mainly agents acting on the renin-angiotensin system and lipid modifying agents. Although cardiovascular system drugs were not associated with polypharmacy, they were associated with pDDI and moderate pDDI. This is an expected finding due to high prevalence of cardiovascular diseases in Jordan as it is the major reason for mortality in Jordanians aged in-between 30-70 . In addition, the guidelines for treating several cardiovascular diseases including heart failure and hypertension emphasise the importance of using multiple medications .
Alimentary tract and metabolism drugs were associated with polypharmacy, major pDDI and pDDI. This could be due the high prevalence of diabetic elderly Jordanians, in addition to the inappropriate overuse of proton pump inhibitors in Jordan [41-43]. The proton pump inhibitors are cytochrome P450 inhibitors; therefore, these medications influence metabolism of other drugs and may cause DDI .
Drugs acting on blood and blood forming organ may be associated with polypharmacy, major pDDI, and pDDI due to recommendations of using antiplatelet or antithrombotic in patients with cardiovascular diseases. The antiplatelet clopidogrel is a prodrug which is activated through CYP2C19 and we found that the CYP450 inhibitors, such as proton pump inhibitors, were commonly co-administrated among the participants . Anti-infectious were also associated with polypharmacy due to the high prevalence of infectious diseases as reported previously . These findings are similar to findings reported by previous studies that reported a high prevalence of administration of cardiovascular system drugs, drugs acting on blood and blood forming organ, alimentary tract and metabolism drugs and anti-infectious drugs [23,25,34,46].
Role of GP
The regression results showed that visiting a GP decreased the odds of having moderate pDDI, which emphasizes the beneficial effect of GP and specialist collaboration; as the GP may act as an important link between the patient and different specialists consulting the patient. Literature has emphasized the importance of ‘collaborative care’ or ‘coordinated care’ where a teamwork with a defined member of the team taking responsibility for the coordination of care can provide the best medical outcome and may prevent adverse outcome including pDDI, these finding suggest the need to encourage more GP; as the majority (67.3%) of our participants did no see one .
High incidence of major and moderate pDDI and polypharmacy was found in the study participants. This study emphasizes the need for a better control over elderly prescription in Jordan and the need to increase the role of family doctors to form a link between different physicians seen by the patient
- Lehmann K. Drug interactions-principles, examples and clinical consequences. Additional important drug interactions. Dtsch Arztebl Int 2013; 110: 133.
- Cruciol-Souza JM, Thomson JC. Prevalence of potential drug-drug interactions and its associated factors in a Brazilian teaching hospital. J Pharm Pharm Sci 2006; 9: 427-433.
- Palleria C, Di Paolo A, Giofre C, Caglioti C, Leuzzi G, Siniscalchi A. Pharmacokinetic drug-drug interaction and their implication in clinical management. J Res Med Sci 2013; 18: 601-610.
- Lurie Y, Loebstein R, Kurnik D, Almog S, Halkin H. Warfarin and vitamin K intake in the era of pharmacogenetics. Br J Clin Pharmacol 2010; 70: 164-170.
- Pirmohamed M, James S, Meakin S, Green C, Scott AK, Walley TJ. Adverse drug reactions as cause of admission to hospital: prospective analysis of 18 820 patients. BMJ 2004; 3296: 15-19.
- Becker ML, Kallewaard M, Caspers PW, Visser LE, Leufkens HG, Stricker BH. Hospitalisations and emergency department visits due to drug-drug interactions: a literature review. Pharmacoepidemiol Drug Saf 2007; 16: 641-651.
- Gnjidic D, Le Couteur DG, Kouladjian L, Hilmer SN. Deprescribing trials: methods to reduce polypharmacy and the impact on prescribing and clinical outcomes. Clin Geriatr Med 2012; 28: 237-253.
- Onder G, Petrovic M, Tangiisuran B, Meinardi MC, Markito-Notenboom WP, Somers A. Development and validation of a score to assess risk of adverse drug reactions among in-hospital patients 65 years or older: the GerontoNet ADR risk score. Arch Intern Med 2010; 170: 1142-1148.
- Bjerrum L, Søgaard J, Hallas J, Kragstrup J. Polypharmacy: correlations with sex, age and drug regimen. A prescription database study. Eur J Clin Pharmacol 1998; 54: 197-202.
- Gurwitz JH, Field TS, Harrold LR, Rothschild J, Debellis K, Seger AC. Incidence and preventability of adverse drug events among older persons in the ambulatory setting. JAMA 2003; 289: 1107-1116.
- Fulton MM, Allen ER. Polypharmacy in the elderly: a literature review. J Am Acad Nurse Pr 2005; 17: 123-132.
- Frazier SC. Health outcomes and polypharmacy in elderly individuals: an integrated literature review. J Gerontol Nurs 2005; 31: 4-11.
- Christensen K, Doblhammer G, Rau R, Vaupel JW. Ageing populations: the challenges ahead. Lancet 2009; 374: 1196-1208.
- Boyd CM, Darer J, Boult C, Fried LP, Boult L, Wu AW. Clinical practice guidelines and quality of care for older patients with multiple comorbid diseases: implications for pay for performance. JAMA 2005; 294: 716-724.
- Secoli SR. Polypharmacy: interaction and adverse reactions in the use of drugs by elderly people. Rev Bras Enferm 2010; 63: 136-140.
- Salazar JA, Poon I, Nair M. Clinical consequences of polypharmacy in elderly: expect the unexpected, think the unthinkable. Expert Opin Drug Saf 2007; 6: 695-704.
- Drug. Drug interaction report. Drugs.com 2000.
- Lexi-Comp OnlineTM. Pediatric and neonatal lexi-drugs. Springer 2011.
- World Health Organisation. The anatomical therapeutic chemical classification system with defined daily doses (ATC/DDD). WHO 2017.
- IBM Corp. IBM SPSS statistics for windows. IBM Corp. Armonk, New York 2013.
- Murtaza G, Khan MYG, Azhar S, Khan SA, Khan TM. Assessment of potential drug-drug interactions and its associated factors in the hospitalized cardiac patients. Saudi Pharm J 2016; 24: 220-225.
- Wawruch M, Zikavska M, Wsolova L, Kuzelova M, Tisonova J, Gajdosik J. Polypharmacy in elderly hospitalised patients in Slovakia. Pharm World Sci 2008; 30: 235-242.
- Al-Hashar A, Al Sinawi H, Al Mahrizi A, Al-Hatrushi M. Prevalence and covariates of polypharmacy in elderly patients on discharge from a tertiary care hospital in Oman. Oman Med J 2016; 31: 421-425.
- Eurich D, Gamble J-M, Hall J, Marrie T, Sadowski C, Majumdar S. Medication transitions and polypharmacy in older adults following acute care. Ther Clin Risk Manag 2014; 10: 189.
- Hubbard RE, Peel NM, Scott IA, Martin JH, Smith A, Pillans PI. Polypharmacy among inpatients aged 70 years or older in Australia. Med J Aust 2015; 202: 373-377.
- Martínez-Arroyo JL, Gómez-García A, Sauceda-Martínez D. Polypharmacy prevalence and potentially inappropriate drug prescription in the elderly hospitalized for cardiovascular disease. Gac Med Mex 2014; 150: 29-38.
- Yasein N, Barghouti F, Irshaid Y, A. Suleiman A, Abu-Hassan D, Tawil R. Elderly patients in family practice: Polypharmacy and inappropriate prescribing-Jordan. Int Med J 2012; 19.
- Salih SB, Yousuf M, Durihim H, Almodaimegh H, Tamim H. Prevalence and associated factors of polypharmacy among adult Saudi medical outpatients at a tertiary care center. J Family Community Med 2013; 20: 162-167.
- Al Ameri MN. Prevalence of poly-pharmacy in the elderly: implications of age, gender, co-morbidities and drug interactions. SOJ Pharm Pharm Sci 2014.
- Johnell K, Klarin I. The relationship between number of drugs and potential drug-drug interactions in the elderly: a study of over 600,000 elderly patients from the Swedish Prescribed Drug Register. Drug Saf 2007; 30: 911-918.
- Lin C-F, Wang C-Y, Bai C-H. Polypharmacy, aging and potential drug-drug interactions in outpatients in Taiwan. Drugs Aging 2011; 28: 219-225.
- Dookeeram D, Bidaisee S, Paul JF, Nunes P, Robertson P, Maharaj VR, et al. Polypharmacy and potential drug-drug interactions in emergency department patients in the Caribbean. Int J Clin Pharm 2017; 39: 1119-1127.
- Maher RL, Hanlon J, Hajjar ER. Clinical consequences of polypharmacy in elderly. Expert Opin Drug Saf 2014; 13: 57-65.
- Linjakumpu T, Hartikainen S, Klaukka T, Veijola J, Kivelä S-L, Isoaho R. Use of medications and polypharmacy are increasing among the elderly. J Clin Epidemiol 2002; 55: 809-817.
- Rj T, Linja A, Pu K. Drug use among the home-dwelling elderly. Trends Polypharm Sedation 2003.
- Perry BA, Turner LW. A prediction model for polypharmacy: are older, educated women more susceptible to an adverse drug event? J Women Aging 2001; 13: 39-51.
- Haider SI, Johnell K, Weitoft GR, Thorslund M, Fastbom J. The Influence of educational level on polypharmacy and inappropriate drug use: a register-based study of more than 600,000 older people. J Am Geriatr Soc 2009; 57: 62-69.
- Walckiers D, Heyden J Van der, Tafforeau J. Factors associated with excessive polypharmacy in older people. Arch Public Heal 2015; 73: 50.
- WHO. Global status report on non-communicable diseases 2014. World Health 2014; 176.
- Volpe M, Chin D, Paneni F. The challenge of polypharmacy in cardiovascular medicine. Fundam Clin Pharmacol 2010; 24: 9-17.
- Al-Nsour M. Prevalence of selected chronic, non-communicable disease risk factors in Jordan: Results of the 2007 Jordan behavioral risk factor surveillance survey. Prev Chronic Dis 2012; 9: 1-9.
- Zalloum N, Farha RA, Awwad O, Samara N. Inappropriate prescribing of proton pump inhibitors among patients in two Jordanian tertiary health facilities. Trop J Pharm Res 2016; 15: 2489.
- Alqudah MAY, Al-Azzam S, Alzoubi K, Alkhatatbeh M, Rawashdeh N. Overuse of proton pump inhibitors for stress ulcer prophylaxis in Jordan. Int J Clin Pharmacol Ther 2016; 54: 597-602.
- Ogawa R, Echizen H. Drug-drug interaction profiles of proton pump inhibitors. Clin Pharmacokinet 2010; 49: 509-533.
- Sangkuhl K, Klein TE, Altman RB. Clopidogrel pathway. Pharmacogenet Genomics 2010; 20: 463-465.
- Ribeiro AQ, Rozenfeld S, Klein CH, César CC, Acurcio F de A. Survey on medicine use by elderly retirees in Belo Horizonte, South-eastern Brazil. Rev Saude Publica 2008; 42: 724-732.
- Piterman L, Koritsas S. Part I. General practitioner-specialist relationship. Intern Med J 2005; 35: 430-434.