Magnitude and associated factors of poor medication adherence among diabetic and hypertensive patients visiting public health facilities in Ethiopia during the COVID-19 pandemic.

OBJECTIVE: This study aims to assess the magnitude and associated factors of poor medication adherence among diabetic and hypertensive patients visiting public health facilities in Addis Ababa, Ethiopia during the COVID-19 pandemic.
METHODS: A multi-site cross-sectional design was conducted from 1st through 30th of August 2020 at public health facilities of the study area. Adult outpatients with T2DM and hypertension visiting hospitals and health centers were included in the study. A proportion to size allocation method was used to determine the required sample size per facility. Data was collected using the 8-item Morisky medication adherence scale. Descriptive statistics and binary logistic regression were used to analyze data. A 95% confidence interval and p≤0.05 statistical significance was considered to determine factors associated with poor medication adherence.
RESULTS: A total of 409 patients were included in the present study. About 57% of the patients reported that the COVID-19 pandemic has posed negative impacts on either of their follow-up visits, availability of medications, or affordability of prices. And, 21% have reported that they have been affected in all aspects. The overall magnitude of poor medication adherence was 72%. Patients with extreme poverty were more likely to have good medication adherence (AOR: 0.59; 95%C.I: 0.36-0.97), whereas attendance to a health center (AOR: 1.71; 95%C.I: 1.02-2.85), presence of comorbidity (AOR: 2.05; 95%C.I: 1.13-3.71), and current substance use history (AOR: 11.57; 95%C.I: 1.52-88.05) predicted high odds of poor adherence.
CONCLUSION: Over a three-fourth of the patients, in the study setting, have poor adherence to their anti-diabetic and antihypertensive medications. Health facility type, income level, comorbidity, and current substance use history showed a statistically significant association with poor adherence to medication. Stakeholders should set alternative strategies as perceived impacts of the COVID-19 pandemic on medication adherence are high in the study area.

Introduction

Adherence to anti-diabetic and antihypertensive medications is an area of interest with marked implications to affect patient management outcomes. The World Health Organization (WHO) defined adherence in 2001 as the extent to which a patient follows medical instructions [1]. Whereas this concept accounts for a broader aspect in the medical practice, its correlation with the management and control of chronic illnesses as diabetes and hypertension is well documented. This is likely because, adherence in this group encompasses multiple dimensions, such as lifestyle changes, medications, patient attitudes, and provider-patient relationships among others [2, 3] with potential interaction in the longer or lifetime frames.

Measuring adherence provides information on patients’ behavior to medication and lifestyle practices [4]. Studies have documented that the level of medication adherence in developed nations remained, only, close to 50% [5-7]. This figure is even lower in the developing and middle-income countries owed to the paucity of healthcare inputs and limited access to the services. Reports of adherence to antihypertensive medications from China (65.1%), Gambia (27%), and Seychelles (26%) showed the magnitude and relevance of the problem [8-10].

Medication adherence studies on antidiabetic and antihypertensive medications have been conducted across regions of Ethiopia. Even though the measurement tool and design of the study are similar for most of the studies, there is a considerable variation in terms of the level of adherence by study settings and type of chronic illness considered [11-14]. Reports from the present study setting also revealed that adherence levels to anti-diabetic medications ranged from 51.3% to 76% [15-17].

Currently, when the focus of pharmaceutical companies is on battling the COVID-19 pandemic across the globe, low and middle-income countries (LMICs) like Ethiopia, might be worst affected due to the rather vulnerable and inadequate pharmaceutical manufacturing capacities in these countries to meet their general pharmaceutical needs particularly those for chronic diseases. With limited supply to meet the increased demand created, the market values of medicines for chronic diseases have escalated, making them unaffordable for several patients in LMICs who require them [13]. Besides, adequate therapeutic outcomes of chronic illnesses require a linear adherence to medications [18]. This, in turn, could be linked to accessibility, affordability that can, negatively, be impacted during the outbreak [19].

Also, even though more studies have been conducted on the topic [11-17], potential variation in findings is inevitable due to time, study design, perception, context, the population considered, sample size, and quality of care delivered to patients among others. The purpose of this study is to assess the level of medication adherence, patients’ perception of the impact of the COVID-19 pandemic, and factors associated with poor adherence to anti-diabetic and antihypertensive medications among patients visiting public health facilities in Addis Ababa.

Methods

Study setting, design, and period

The study is conducted in Addis Ababa, the capital of Ethiopia. The 2021 estimated population of the city is over 4.8 Million [20]. There exist a total of 12 public hospitals [21] of which six are managed under the federal ministry of health (FMOH) whilst the rest five hospitals and 103 health centers are administered under the Addis Ababa health bureau (AAHB) [22]. The prevalence of diabetes mellitus and hypertension in public health facilities was reported to be 14.8% [23] and 32–34.7% [24, 25] respectively. A cross-sectional study design was conducted from 1st through 30th August 2020 at seven public health facilities to assess the adherence of patients to antidiabetic and antihypertensive medications during the COVID-19 pandemic. One of the facilities (Saint Paul’s hospital millennium medical college (SPHMMC)) was a teaching hospital under the ministry of health whereas, one general hospital (Ras Desta Damtew memorial hospital (RDDMH)), and five health centers namely; Arada, Lideta, Nifas Silk Lafto wereda 09, Akaki kality, and Bulbula are administered under the Addis Ababa regional health bureau.

Populations and inclusion criteria

The source population of this study was; all adult outpatients diagnosed with T2DM and hypertension in Addis Ababa, Ethiopia. All outpatients aged 18 years or above, those who have been on either anti-diabetic or antihypertensive medications for more than six months, visiting the selected public health facilities during the stated study period, and who provided informed consent were eligible in the study. Patients with known or suspected psychiatric problems and those attending to the emergency units were not included.

Sample size and sampling technique

The minimum sample size was estimated based on reports of adherence to antihypertensive [13] and anti-diabetic medications [15]. Of the two figures (66.7% and 51.3% respectively), the latter produced a higher required sample size. The single population proportion formula with a 95% confidence interval, and 5% tolerable error assumptions was employed in the calculation. Adding a 10% for non-response, a total of 422 participants was required for the study. Hospitals and health centers were selected purposively based on patient flow and socio-demographic diversity of catchment populations. A proportion to size allocation method was used to determine the required number of patients per health facility. Taking into account the COVID-19 risk, participants who consented to take part were recruited and included in the study using a consecutive sampling technique.

Data collection tool, procedures, and quality

Medication adherence was measured based on the 8-item Morisky medication adherence instrument [26]. Socio-demographic and clinical profiles were included with the questionnaire. After obtaining verbal informed consent, a face-to-face interview, using a pre-tested questionnaire, was done by trained data collectors. An Amharic (an official working language of Ethiopia) translated instrument was used during the data collection and back-translated to English for entry and analysis. Content validity of the tool was ensured by the study team. Supervision was undertaken throughout the data collection period.

Variables of the study

The dependent variables are adherence level and patients’ perception of the COVID-19 impact. On the other hand, the independent variables were socio-demographic variables, such as age, sex, health facility type, education, marital status, income level, current substance use history, presence of close people, number of close people, and Clinical variables, such as presence of comorbidity, disease duration, treatment duration, diagnosis type and presence of sleep disturbance.

Operational definitions

Good adherence

Refers to a patient’s overall score sum of 16 points from the 8-item Morisky’s medication adherence scale (MMAS). Items 1 through 7 were coded as 1 = yes, 2 = no except for item 5 in which no was rated as 1 and yes was rated as 2. For item 8, the Likert scaled scores of 1 to 5 were reverse coded as 2 = never and 1 = often to always.

Poor adherence

Refers to the MMAS-8 score summation of 8 through 15 where a patient missing at least one or more of the items of the scale was classified under poor adherence.

Current history of substance use

Patient reporting to have used either one or any combination of alcohol, Khat, or cigarettes in the past three months.

Close people

Refers to family members or relatives whom a patient can rely on or seek for any form of assistance during hard times.

Comorbidity

Was considered when a patient presents with one or more chronic conditions in addition to either diabetes or hypertension.

Ethical considerations

Ethical approval to conduct this study was obtained from Saint Paul’s Hospital Millennium Medical College (SPHMMC) institutional review board (IRB), and the Addis Ababa regional health bureau research ethics review committee. After ethical clearance was sought from the regional health bureau, a support letter was written to the respective health facilities before data collection. Verbal informed consent was obtained from each participant included in the study. Participation in the study was voluntary. Confidentiality of the data obtained was maintained throughout and after completion of the study. No personal identifiers were either included in the tool or were collected during the study.

Data analysis

After cleaning and coding manually, data was entered and checked for completeness and accuracy in statistical products for a social solution (SPSS) V.26.0. Both descriptive and inferential statistics were applied in the analysis. Tables and figures were used to present descriptive results. A Bi-variable analysis of all potential patient characteristics was done at p≤0.2 for potential association with poor adherence to anti-diabetic and antihypertensive medications. Variables that satisfied the first test were subsequently included in the multivariable logistic regression at a p≤0.05 level of significance. A 95% level of confidence was considered in both cases.

Results

Profile of patients

A total of 409 patients were included in the present study. Even though few patients declined to take part during the subsequent recruitment (n = 13), the number of respondents was beyond the minimum requirement. The age of patients ranged from 19 to 95 with a mean of 56.5 and a standard deviation (SD) of 13.4 Years. The majority were in the age group of 45 or above (321,78.5%), females (229,6%), visiting hospitals (224,54.8%), not attended formal education (174, 42.5%), married (259, 63.3%), live with moderate poverty or better (222, 54.3%), have comorbidity (250, 61.0%), with 7 years or less mean duration of disease (277, 67.7%) and 7 years or less mean duration of treatment (257, 62.8%). Most of the participants had no current history of any substance use (92.2%), diagnosed with hypertension only (35.0%), had no sleep disturbance (68.7%), have close people around (88.5%), and live with 3–5 family members (59.7%) (Table 1). Among the comorbidities reported, hypertension (204, 81.6%), diabetes mellitus (179, 71.6%), heart disease (66, 26.4%), hypercholesterolemia (36, 14.4%), chronic asthma (23, 9.2%), and stroke (12, 4.8%) accounted for the top frequencies. A Cronbach’s alpha test of the reliability of the scale among the samples also showed an acceptable range for both hospitals (α = 0.88) and health centers (α = 0.63).

Table 1

Profile of T2DM and hypertensive patients visiting chronic care units of public health facilities in Addis Ababa, August 2020.

Characteristic	Label	Frequency	%
Age (yrs.)
	≤45	88	21.5
	>45	321	78.5
Sex
	Male	180	44
	Female	229	56
Visiting site
	Health center	185	45.2
	Hospital	224	54.8
Education
	Not attended formal education	174	42.5
	Grades 1 to 12	165	40.4
	Diploma or above	70	17.1
Marital status
	Unmarried	53	13.0
	Married	259	63.3
	Divorced/separated/widowed	97	23.7
Income level (ETB) *
	Extreme poverty	187	45.7
	Moderate poverty or better	222	54.3
Presence of comorbidity
	No	159	38.9
	Yes	250	61.1
Disease duration**
	≤7 years	277	67.7
	>7 years	132	32.3
Treatment duration**
	≤7 years	257	62.8
	>7 years	152	37.2
Current substance use history
	Yes	32	7.8
	No	377	92.2
Diagnosis type
	Type 2 diabetes mellitus	132	32.2
	Hypertension	143	35.0
	Both T2DM and hypertension	134	32.8
Presence of sleep disturbance
	Yes	128	31.3
	No	281	68.7
Presence of close people
	No	47	11.5
	Yes	362	88.5
Number of family members
	≤2	79	19.3
	3–5	244	59.7
	≥6	86	21.0

*classified considered based on the World Bank’s definition of poverty [27].

** considered based on the mean duration (Yrs.) of diagnosis or initiation of treatment.

Patients’ perception of the impact of COVID-19 pandemic

About 163(40%) of the patients reported that the COVID-19 pandemic has posed negative impacts on the availability of medications and their follow-up visits, whereas 160(39%) believed that it caused an unaffordable or increased price of medications. Two hundred thirty-four (57%) reported that they have faced one or more of the problems whilst 87(21%) stated that they come across all the three (Fig 1).

Fig 1

Perception of T2DM and hypertensive patients on the impact of the COVID-19 pandemic visiting chronic care units of public facilities in Addis Ababa, August 2020.

Level of adherence to antidiabetic and antihypertensive medications

The level of adherence to antidiabetic and antihypertensive medications was measured using the 8-item Morisky medication adherence scale. Accordingly, the overall level of adherence was found to be 28% whilst 72% were poorly adherent missing at least one element from the scale (Fig 2).

Fig 2

Adherence level to antidiabetic and antihypertensive medications among patients visiting public health facilities during the COVID-19 pandemic in Addis Ababa, Ethiopia, August 2020.

Factors associated with poor medication adherence

Lastly, multiple characteristics of patients were tested against the presence of any potential association with poor medication adherence. Patients under extreme poverty were more likely to report a good adherence as compared to patients with moderate poverty or better average monthly income (AOR: 0.59; 95%C.I: 0.36–0.97). On the other hand, patients attending health centers (AOR: 1.71; 95%C.I: 1.02–2.85), having any comorbidity (AOR: 2.05; 95%C.I: 1.13–3.71), and current history of any substance use (AOR: 11.57; 95%C.I: 1.52–88.05) have shown a statistically significant positive association with poor medication adherence (Table 2).

Table 2

Factors associated with poor adherence to antidiabetic and antihypertensive medications among patients visiting public health facilities during the COVID-19 pandemic in Addis Ababa, Ethiopia, August 2020.

Variable	Label	Level of adherence		COR (95%CI)	AOR (95%CI)
		Good (n)	Poor (n)
Facility level
	Health centers	38	147	1.98(1.27–3.12)	1.71(1.02–2.85)*
	Hospitals	76	148	1	1
Education
	Not attended formal education	35	139	1.94(1.04–3.62)	1.85(0.94–3.63)
	Primary/secondary education	56	109	0.95(0.53–1.73)	0.96(0.50–1.84)
	College/University education	23	47	1	1
Average monthly income (ETB) d
	Extreme poverty	58	129	0.75(0.49–1.16)	0.50(0.27–0.89)*
	Moderate poverty or better	56	166	1	1
Comorbid condition
	No	56	103	1	1
	Yes	58	192	0.56(0.36–0.86)	2.05(1.13–3.71)*
Current history of substance use
	Yes	1	31	13.27(1.79–98.39)	11.44(1.50–87.11)*
	No	113	264	1	1
Diagnosis type
	T2DM	42	90	0.59(0.34–1.03)	1.06(0.52–2.16)
	Hypertension	43	100	0.64(0.37–1.11)	0.92(0.48–1.77)
	Both T2DM and hypertension	29	105	1	1
Presence of sleep disturbance
	Yes	28	100	1.58(0.97–2.57)	1.44(0.86–2.42)
	No	86	195	1	1
Presence of close people around
	No	7	40	2.40(1.04–5.52)	2.03(0.84–4.90)
	Yes	107	255	1	1

*indicates statistical significance at P≤0.05. COR: crude odds ratio; AOR: adjusted odds ratio.

Discussion

The COVID-19 pandemic has severely affected health systems in general and follow-up service to chronic illnesses in particular [28-30]. Its impact in Sub-Saharan Africa is more pronounced as this region is often characterized by low health system infrastructure coupled with a growing burden of non-communicable diseases [31]. In Ethiopia too, most healthcare services have been disrupted due to the alarming spread of the pandemic and daily loaded terrifying news [32]. Augmented with less attention of the public to regularly practice preventive measures, more patients are still at risk of either its direct or indirect impacts militating their adherence to therapy. It is apparent from the present study that the majority of patients experienced negative impacts on either of their follow-visits, availability, or affordability of medications at least once during the outbreak. It was also noted that about a fifth of the patients in the present sample reported having faced all of the problems.

Evaluation of adherence to medication level could be regarded as a potential indicator for patients’ commitment to reverse an affected state of health [33]. Poor adherence to long-term medications is multifactorial often comprising socio-demographic factors, individual patient-related, therapy-related factors, and the health system among others [34]. As a result, achieving proper adherence remains to be a challenge both in the developed [5, 6] and developing [7-10] countries even though pharmacotherapy remains to be the mainstay of treatment especially among the older population [35].

The present study shows that level of poor adherence, where a patient failed to meet all the recommended criteria, was found to be significantly high (72%). This figure is higher as compared to the level of adherence to antihypertensive medications reported from Southwest Ethiopia (61.8%) by Asgedom and his colleagues [11], in Hawassa (67%) documented by Getnet et al. [12], and in Addis Ababa (66.7%) reported by Tibebu and his colleagues [13]. The highest level of adherence (75%) to antihypertensive medications was reported from Northwest Ethiopia as well [14]. More precisely, the earlier studies have indicated that at least half a proportion of the patients in Addis Ababa had a good level of adherence to their antihypertensive [13] and antidiabetic medications [15-17]. Whereas multiple contributors would result in a poor outcome, the impact of the COVID-19 pandemic six months before the study period was undeniably notable [32, 36]. Most patients have also implied in their report of perceived negative influence the outbreak had posed in terms of meeting with follow-up appointments, accessing medicines, and affording for prices. These factors are mentioned to account for a remarkable role in patients’ poor adherence to therapy [37, 38].

Studies documented that various factors have a link with poor adherence to medications among patients with chronic illness. These may include; lack of involvement of family and friends [39], economic difficulties [40], poor relationship between professional and patients [41], and side effects as well as the complexity of regimens [41, 42]. Furthermore, while patients with asymptomatic diseases have less incentive to adhere to medications, the presence of multiple comorbid conditions that are treated with more drugs can also impair attaining proper adherence [34, 43, 44]. The earlier studies done in Ethiopia have indicated that such contributors, as comorbidity [11-13], age group [12-14], level of knowledge about disease and medication [12–14, 16], and level of education [15, 16] were reported to be among the factors associated with medication adherence.

In paradox with the popular belief [40, 45], lower-income was found to be associated with higher odds of good adherence to anti-diabetic and antihypertensive medications in the current setting. Though the connection of income and health is well established in terms of either direct effect on material fulfillment or indirectly through ensuring social participation [46], the present association could be confounded with non-income factors. In the current Ethiopian context, all patients under the poverty line (45.7% of the respondents) are waived insurance fees that may improve their service utilization rate and access to medicines. Yet, adherence is a behavior of composite factors [34] that can be altered even apart from gaining access to service and medications. Taking into account non-compliance consequences, poor patients might tend to apply medical advice or maintain good relations with providers.

On the other hand, attending a health center, having any comorbid condition and current history of any substance use have shown a statistically significant positive association with poor medication adherence. An increase in the odds of poor adherence among patients attending health centers would be related to patients’ health-seeking behavior, the severity of complications, patient loads, or perceived poor availability of COVID-19 preventive measures at these settings. That could be likely because, as primary healthcare units in the Ethiopian health system, health centers serve to catchment populations that do not need advanced diagnosis and treatment. This is in line with other studies that reported that having a comorbid condition [11] and substance use history [11, 47] were associated with high odds of poor medication adherence. This could also be attributed to the fact that patients may either not be able to comprehend the outcome of their disease and benefit of adherence to medications [48], experience side effects of polypharmacy [49] or fail to practice a healthy lifestyle.

This study has tried to present a city-wide comprehensive report on the medication adherence practice of patients visiting public health facilities in Addis Ababa, Ethiopia. Apart from being able to include various strata of facilities and patients, the findings can be easily compared to previous figures to evaluate the impact imposed by the COVID-19 pandemic on medication adherence. However, the observed association between dependent and independent variables may suffer from temporality. Inclusion of the only patients who were available during the study period could also pose a selection bias that might have affected the study results.

Conclusion

A significant proportion of patients with T2DM and hypertension in Addis Ababa have experienced negative impacts on either of their follow-visits, availability, or affordability of medications at least once during the COVID-19 outbreak. Over a three-fourth of the patients had poor adherence to their medications. Facility type, average monthly income, level of education, presence of comorbidity, and current histories of any substance use have shown a statistically significant association with poor adherence to antidiabetic and antihypertensive medications.

All concerned health authorities should take into account, and set multidisciplinary strategies to prevent impacts of the COVID-19 pandemic on medication adherence of patients with chronic illnesses.

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21 Jan 2021

PONE-D-20-34174

Magnitude and associated factors to medication poor adherence among diabetic and hypertensive patients visiting public health facilities in Ethiopia during the COVID-19 pandemic

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Reviewer #1: The authors present an original reasearch article entiteled: Magnitude and associated factors to medication poor adherence among diabetic and hypertensive patients visiting public health facilities in Ethiopia during the COVID-19 pandemic.

The manuscripts reads like a first version manuscript. It needs to be rewritten with clearer senteces. A native speaker should edit the manuscript.

Abstract: the abstract is well written but quite long. Please be consise.

Introduction: THe introduction reads as a textbook with little conffection between the paragrafs.

The first paragraph starts with defining the WHO criteria for adherence. What does adherence refer to. Such a paragfar is not appealing to read further. I suggest to start with why drug adherence for hyperntension and diabetes is of interenst to study.

The paragraphs discussing the literature may be more suitable for the discussion (paragraf 3 and 4). Could be in 2 or 3 sentecences in the introduction.

Methods:

"A cross sectional study design was conducted in August 2020 among seven public health facilities (two hospitals and five health centers) to assess adherence of patients to antidiabetic and antihypertensive medications during the COVID-19

pandemic. " Was it from the start of august till the end of august? Wat was the time window for the study? Who assessed the data?

Wat is there an approval from the Medical ethical commitee?

Where only chronic patients included or also patients with hypertension and DM de novo.

"Content validity was of the tool was ensured by study team. Cronbach’s

alpha test of reliability of the scale among pretested samples showed acceptable range for both

hospitals (α=0.88) and health centers [α=0.63]. " This is describtion of the results. I suggest to transfer it to the results section.

The descrioption of the adherence is unclear for readers who are not familiar with the morskey score. Perhaps a table would be more suitable.

Results:

Please put tables at the end of the paper.

The description of the results is not conssitent. For example: AOR: 0.58; 95%C.I: 0.35-0.97 and AOR: 0.50; 95% C.I:0.27-0.89

Discussion:

Can be extended with the literature discussion from the introduction.

Please start the discussion with a short discription of the results.

The conclusion is again a summary of the results, please make it a conclusion and add a clear recommendation paragraph.

Please add in the discussion a clear strenght and limitation paragraph.

Reviewer #2: This study investigated the adherence to medication in patients with diabetes and hypertension in Ethiopia during the COVID-pandemia. Only app. ¼ of the patients were fully adherent. COVID was mentioned in app. 40% of the patients as causing some reduction in adherence. Other factors could be identified to increase or reduce adherence.

Some comments:

Introduction:

good summary. However, the authors could highlight a bit more what the added value of their work is, in addition to investigating the situation during the COVID pandemia, as compared to the papers cited in the introduction (e.g. differences in the setting as I can imaging that the populations seen in different settings differ, or why numbers of other studies may be not representative, or that the population of this study is the same as that of one of the other studies, allowing to investigate the direct impact of COVID on adherence).

Methods:

Where all patients including during the time period or was it a selected group of patients? Did all patients consent to participate in the study? Probably not, To what extend did those not included differ from those that participated in this study? It may be helpful to have a figure explaining the patient flow.

The sample size calculation is unclear. What was the aim / target for the calculation? Please be more precise. I do not understand it at present.

It would be helpful to add the questionnaire, at least as supplementary file. This makes it also easier to understand exactly how good adherence was defined.

Is it correct that participating patients did not give written informed consent? If yes, was this an exemption specifically approved by the Ethical Committee a priori?

Were all variables included in multivariable analysis or were there any selection criteria? If no selection criteria applied, the power may be not sufficient for multivariable analysis given the number of independent variables. In this case, I would recommend to first perform a univariable analysis and only include those with a e.g. P<0.1 in the multivariable analysis. At present, it is not clear why some variables are mentioned in table 2 and others not.

Results:

How was the presence of close people defined? How was co-morbidity defined? Would it not be better to name the prevalence of co-morbidities (at least for the most prevalent ones)? In addition, it would be interesting with which medication patients were treated.

Figure 1. % instead of absolute numbers would be better.

As far as I understand, an OR of <1.0 indicates less non-adherence, i.e. better adherence. I think that it is easier to understand if you only better adherence (with an OR > 1) and worse adherence (with an OR <1). This is easier to understand. This obviously also applies to the according parts of the discussion (e.g. association with better adherence instead of association with lower odds of poor adherence).

Would it not be better to use the poverty line as cut-off instead of the median within the study, particularly as this is also related to the discussion?

Please define AOR and COR in table 2.

Discussion:

It is a bit confusing that you refer that 40% are negatively affected by the pandemia regarding non-adherence, but in fact, there were 57%. This applies also to the abstract. This is confusing. In addition, you do not need to repeat results in the discussion (use e.g. the majority instead).

Please discuss your findings in the light of previous findings in your country. You only do so regarding the overall adherence. It would be interesting to hear if factors associated with better adherence were similar in other studies and what potential explanations for the differences are.

The finding and discussion of low income being associated with better adherence is interesting. What do other studies say on this and what may be the differences with your findings? This is missing. The findings related to co-morbidites etc. are in line with your findings. This needs to be mention and is separate to the discussion about impact of low income.

Have a separate paragraph regarding limitations. You also need to add that the number of included patients is limited and other important factors may have been missed because of this limitation. In addition, the selection of patients may be a limitation (not only that inclusion was limited to one month), but this is difficult to judge as nothing is reported in this regard (see above).

Minor comments:

There are quite some spelling and grammatical mistakes (e.g. incorrect use of tenses). Please check and correct.

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Reviewer #1: No

Reviewer #2: No

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10 Feb 2021

Response attached.

Submitted filename: Response to reviewers.docx

Click here for additional data file.

25 Feb 2021

PONE-D-20-34174R1

Magnitude and associated factors of poor medication adherence among diabetic and hypertensive patients visiting public health facilities in Ethiopia during the COVID-19 pandemic

PLOS ONE

Dear Dr. Shimels,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

See comments by reviewer #2. These are not major issues, but you still should address them. In particular, please provide the adequate information about the power calculation and have your manuscript copy-edited by a native speaking person.

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Reviewers' comments:

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Comments to the Author

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Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: No

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Reviewer #1: The authors adressed all comments adequately.

The respons en manuscript can be improved to a more neat version, but probably with the editing phase this matter can be adressed.

Reviewer #2: I would like to thank the authors for the improvement in their manuscript. Most issues are resolved sufficiently, but there are still some remaining.

Thus, the authors still fail to provide sufficient information regarding the power calculation. The authors provide references from previous studies, but they fail to exactly mention their assumptions that led to the required sample size.

The use of the English language has improved, but the manuscript still contains mistakes. As there is no copy-editing for PLOS ONE, the manuscript must be provided in good English without mistakes. I understand that this may be difficult for the authors. Therefore, they need to have the manuscript corrected by a person that is (almost) native English speaking.

Please provide the information that written informed consent was not required.

According to the instruction to authors, tables should be placed directly after the paragraph in which they are cited (the recommendation by the other reviewer was not correct).

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Reviewer #1: No

Reviewer #2: No

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11 Mar 2021

Thank you for the email, and requesting us to make a second revision of the manuscript titled, “Magnitude and associated factors to medication poor adherence among diabetic and hypertensive patients visiting Public health facilities in Ethiopia during the Coronavirus pandemic” submitted for potential publication in your journal. We appreciate and thank the reviewers for the comments raised. The following changes were made to the document.

i) Explanation to the sample size calculation: two earlier reported figures on the level of adherence to anti-DM and antihypertensive medications were used for the calculation. Though the two reported figures were tested for, the sample size which was obtained based on adherence to anti-DM (i.e, adherence to anti-DM, p=51.3%) was higher (384) and considered as the minimum required sample size. As a single population observational [cross-sectional] study, the confidence interval method was considered to compute the minimum sample size. It is also apparent that 95% C.I [which means a 5% allowed type I error], 5% level of precision, and a Point estimate for level of adherence to anti-DM and anti-hypertensive medications (reported earlier) was included reasonably. This has been presented in the methods section as:

The minimum sample size was estimated based on reports of adherence to antihypertensive [13] and anti-diabetic medications [15]. Of the two figures (66.7% and 51.3% respectively), the latter produced a higher required sample size. The single population proportion formula with a 95% confidence interval, and 5% tolerable error assumption was employed in the calculation. Adding a 10% for non-response, a total of 422 participants was required for the study…………

ii) Regarding language issue, and editorial mistakes

The authors and an additional academician (out of the SPHMMC staff) have revised the grammar as well as typological errors thoroughly, and have fixed some issues. Unfortunately, we were unable to find one who will be both a native speaker and understands the subject area. We hope that the editorial quality is quite improved as it presents now, but still willing to receive further comments. All details are presented in a ‘red font’ highlight within the ‘manuscript with track change’ version.

We appreciate for the time and consideration to our work, and look forward to hearing from your end.

Tariku Shimels, corresponding author

15 Mar 2021

Magnitude and associated factors of poor medication adherence among diabetic and hypertensive patients visiting public health facilities in Ethiopia during the COVID-19 pandemic

PONE-D-20-34174R2

Dear Dr. Shimels,

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Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

29 Mar 2021

PONE-D-20-34174R2

Magnitude and associated factors of poor medication adherence among diabetic and hypertensive patients visiting public health facilities in Ethiopia during the COVID-19 pandemic

Dear Dr. Shimels:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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on behalf of

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PLOS ONE