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. 2021 Jul 30;16(7):e0255327. doi: 10.1371/journal.pone.0255327

Patient delay and associated factors among tuberculosis patients in Gamo zone public health facilities, Southern Ethiopia: An institution-based cross-sectional study

Asrat Arja 1,*, Wanzahun Godana 2, Hadiya Hassen 2, Biruk Bogale 3
Editor: Marian Loveday4
PMCID: PMC8323940  PMID: 34329333

Abstract

Background

Delayed tuberculosis diagnosis and treatment increase morbidity, mortality, expenditure, and transmission in the community. Early diagnosis and initiation of treatment are essential for effective TB control. Therefore, the main objective of this study was to assess the magnitude and factors associated with patient delay among tuberculosis patients in Gamo Zone, Southern Ethiopia.

Methods

A cross-sectional study was conducted in Gamo Zone, Southern Ethiopia from February to April 2019. Fifteen health facilities of the study area were selected randomly and 255 TB patients who were ≥18 years of age were included. Data were collected using a questionnaire through face-to-face interviews and analyzed using SPSS version 20.0. Patient delay was analyzed using the median as the cut-off value. Multivariable logistic regression analysis was fitted to identify factors associated with patient delay. A p-value of ≤ 0.05 with 95% CI was considered to declare a statistically significant association.

Results

The median (inter-quartile range) of the patient delay was 30 (15–60) days. About 56.9% of patients had prolonged patients’ delay. Patient whose first contact were informal provider (adjusted odds ratio [AOR]: 2.24; 95% confidence interval [CI] 1.29, 3.86), presenting with weight loss (AOR: 2.53; 95%CI: 1.35, 4.74) and fatigue (AOR: 2.38; 95%CI: 1.36, 4.17) and body mass index (BMI) categories of underweight (AOR: 1.74; 95%CI: 1.01, 3.00) were independently associated with increased odds of patient delay. However, having good knowledge about TB (AOR: 0.44; 95% CI: 0.26, 0.76) significantly reduce patients’ delay.

Conclusion

In this study, a significant proportion of patients experienced more than the acceptable level for the patient delay. Knowledge about TB, the first action to illness, presenting symptoms, and BMI status were identified factors associated with patient delay. Hence, raising public awareness, regular training, and re-training of private and public healthcare providers, involving informal providers, and maintenance of a high index of suspicion for tuberculosis in the vulnerable population could reduce long delays in the management of TB.

Introduction

Effective TB control globally depends on substantial changes in TB prevention and care strategies in countries with a high burden, including Ethiopia. However, the cornerstones of global TB control programs are the early identification and timely management of infectious TB cases successfully. Therefore, peoples who have had a cough for two weeks or more are encouraged to see health facilities for a diagnosis and early treatment [1, 2]. As a result, any delay in diagnosing and treating tuberculosis patients not only increases community spread but could also lead to a more advanced disease state, which can lead to more symptoms and a higher risk of death [3].

Tuberculosis has been recognized as a major global public health issue since 1993, and numerous global TB control measures have been developed and implemented, including Directly Observed Short-Course Treatment (DOTS), Stop TB, and End TB strategies [46]. Thus, successful diagnosis and treatment of TB saved an estimated 54 million lives between 2000 and 2017, and TB mortality has dropped by 33 percent since 1990. Given such progress and the fact that almost all cases can be treated, TB has remained one of the world’s major public health concerns [7].

According to a recent WHO report, an estimated 10 million new cases of TB have occurred, of which only 6.4 million new cases of TB have been reported to national authorities and reported to the WHO, and most missing persons with TB are presumed to be receiving some form of treatment from public or private healthcare providers. This reflects a 3.6 million gap between the incident and notified cases. Ten countries accounted for 80 percent of this difference; India, Indonesia, and Nigeria were the top three, accounting for nearly half the gap (46%) [7].

In Ethiopia, tuberculosis has also been identified as a major public health problem and efforts to control it have begun since the early 1960s. However, TB has remained one of the country’s major public health concerns, accounting for the third cause of hospital admission and the second cause of death [2]. With an estimated 219,186 new cases and 48,910 TB deaths, Ethiopia has been ranked among the 30 TB-HIV High Burden Countries (HBC) [8]. Moreover, according to a recent global report about 32% of TB cases from estimated new cases may not have been diagnosed and properly treated in Ethiopia [7]. These cases contribute to an increase in transmission, mortality, and morbidity and most transmissions occur from the onset of a cough to the initiation of treatment [9]. In addition, late diagnosing and treatment of TB patients has proven to be a major challenge to the TB control program, especially in countries with low incomes, including Ethiopia.

The government of Ethiopia has granted TB control due consideration, and prevention and control of TB and Leprosy are among the country’s priority health programs in the country’s Health Sector Transformation Plan (HSTP) [10]. In Ethiopia, like most TB control programs, TB case finding were mainly relying on passive and community-based enhanced TB case finding as to the main strategy with focusing on diagnosing TB among people who actively seek medical care with TB symptoms or identified from the community through health extension workers. With this strategy, the program achieved to detect not greater than two-thirds of its annual estimated TB cases requiring an additional but efficient strategy to be implemented to achieve the ambitious targets set by END TB for 2035 [2, 10].

Factors contributing to patient delay (PD) include family size, occupation, the income of the family, stigma, knowledge about TB, first visit informal provider, distance to the health facility, and self-medication [1114]. There are growing numbers of studies on diagnostic and treatment delays. However, little is known about the food insecurity status of the patient and its association with patient side delay [12, 1517]. As a result, the identification and assessment of factors for patient delays has been set as one of the national priority research agenda [18]. There are growing pieces of evidence on the patient side of TB patients in Ethiopia. However, there have been no studies specifically in our research area, and recent information on treatment delay is highly needed. Furthermore, Diagnosis of TB and delay in treatment time and contributing factors to this delay differ across communities, types of health facilities visited, and geographical areas, including within population groups of the same local settings and disease category. This necessitates the conduct of localized studies to identify population-specific contributing factors to TB diagnosis and treatment delays. Therefore, this study aims to assess the magnitude and factors associated with patient delay among tuberculosis patients in Gamo Zone public health facilities.

Materials and methods

Study setting and design

An institution-based cross-sectional study was conducted from February 1 to April 1, 2019, in the Gamo Zone of the Southern Nations Nationalities and Peoples Region. The Zone is also located 500 km from Addis Ababa and 275km from Hawassa, the capital city of Southern Ethiopia. In this study area, there are 55 public health facilities (one general hospital, three primary hospitals, and fifty-one health centers), and forty-eight private clinics during the study period.

Diagnosis and treatment of all forms of TB across the country are based on the adopted national TB control guideline [2] that specific case definitions, diagnostic, and treatment standards. Public health institutions are the main sources of health care for most people: health services access, as defined by a residence within 10 kilometers of any health institution, is about 80% in the study area. Patients have free access to TB diagnostic services and treatment in public health facilities. Hence, all the districts are giving tuberculosis diagnosis and treatment services, including DOTS, at the patient’s nearest potential health facilities, including health posts. The lowest level of a health facility is a health post, employed by two health extension workers (HEWs). In detecting and referring TB suspects to the next level of health care, which is the health center for diagnosis and initiation of treatment, HEWs play an important role.

Sample size determination and sampling technique

The sample size was determined by using the formula required for the determination of sample size for estimating single population proportions considering the following assumptions: a proportion of patient delay (41.1%) taken from a previous study conducted in Northern Central Ethiopia [15], confidence interval of 95%, a margin of error of 5% and an expected non-response rate of 10%. Accordingly, the calculated sample size was 410. However, since the total number of all forms of TB cases in the study area is less than 10,000, we have considered a finite population correction for sample size. This made the final sample size of study 234. Considering a non-response of 10% a total of 258 cases of TB was required.

To obtain a representative sample for this study, we selected six districts and two towns administrative randomly out of 13 districts and four towns administrative of the study areas. The total sample size was proportionately allocated for the 15 randomly selected health facilities based on the expected cases of TB patients who seek care at each health facility was undertaken after reviewing previous years’ TB reports.

Data collection tool and data collection procedure

A structured questionnaire suited from tools used in Tuberculosis prevalence surveillance, Addis Ababa, Ethiopia, and An in-depth analysis of TB patients pathway in the Eastern Mediterranean Region [19, 20] was used to gather the data. In addition, to draw clinical profiles of the patients from the TB registry, a data abstraction checklist was prepared. The questionnaire was initially prepared in English and then translated to the Amharic language, and translated back to English to check for any inconsistencies.

The questionnaire consisted of socio-demographic characteristics, clinical and health-seeking behavior, and knowledge about TB and related stigma. TB registration books were reviewed for tuberculosis diagnostic information, such as date of diagnosis, type of PTB, type of diagnostic investigation used to diagnose TB, nutritional status, HIV serostatus, patient category, and date of treatment initiation.

Data quality assurance

To assure the data quality, the data collection tool was prepared after a review of relevant works of literature and similar studies. The training was given for one day both for data collectors and supervisors on briefing the general objective of the study, and discussing the contents of the questionnaire. Pre-testing of the tool was carried out on the 13(5%) of sample size outside my study area (Sodo Zuriya, Humbo Tabala HC) before starting the actual data collection and necessary corrections were made.

Data management and analysis

The collected data were entered into Epi-data version 4.4.1 and exported to SPSS software version 20.0 for analysis. Data were summarized using frequency, proportions, mean, median, standard deviation, and inter-quartile range.

Patient delay days were further explored for skewness’, kurtosis, normality plots (Q-Q plots and/or histograms), or Kolmogorov-Smirnov test to check for normality. Hence, the distribution of the number of days elapsed across different time points was not normal and median days were used as a cutoff point to define delays. Thus, the patient delay was defined based on median days elapsed between onset of illness to the first visit to the health facility. As the data were skewed, non-parametric tests (Mann–Whitney/Kruskal-Wallis) were employed to compare group differences in patients’ delays. Mann–Whitney test was used to compare two groups and the Kruskal-Wallis test was used for comparing three or more groups.

Associations between the dependent variable (patient delay) and the independent variables were analyzed by calculating the Odds Ratios and 95% confidence interval. Independent variables with marginal associations (P ≤ 0.25) in the bivariate analysis were entered in multivariate logistic regression analysis. The significant association of independent variables with the dependent variable was assessed by using a 95% confidence interval and a respective adjusted odds ratio (AOR). The logistic model’s fitness was checked using Hosmer-Lemeshow GOF-test at p-value >0.05. A two-tailed-sided p-value of ≤0.05 was taken as statistically significant.

Operational definition and definition of terms

Patient delay periods were defined similarly to previous studies, and the median value was used as a cut-off value to make a simple comparison with previous similar studies.

Patient delay

The time interval (in days) between the initial onsets of the first symptoms of TB until the first visit to a formal health care provider. TB patients who consulted a formal health care provider longer than the median value after the onset of the initial constitutional signs and symptoms of TB were considered delayed [14, 15].

The onset of tuberculosis symptom

The time at which the first symptom (i.e. Cough and other constitutional symptoms like fever, weakness, and weight loss or chest pain) of the illness for which a patient’s health care seeking began [21].

Formal-health care providers: modern government or private health care facilities such as clinics, health centers, and hospitals [15].

Non-formal health providers: These include traditional health providers, local injectors, and drug retail outlets [15].

Knowledge about TB: was assessed using eight items with “yes” or “no” questions including the cause of TB (microbe, bacteria, germ), TB is hereditary, TB is contagious, mode of TB transmission (breathing, sneezing, coughing, raw milk intake), symptoms of TB, TB is curable, length of treatment (6 month = yes, otherwise no) and TB treatment modalities as free = yes or for charge = no. Patients who scored more than the set average (50%) were considered knowledgeable and those who scored less than average were considered not knowledgeable [19].

Food insecurity experience scale

FIES is comprised of eight questions ranging in the severity of FI (Food insecurity) they measure, from low FI (question 1) to Severe Food insecurity (question 8). Respondents answer yes/no to the 8 questions and the responses are aggregated to give raw scores ranging from 0 to 8. FI was classified into 3 categories: 1) food secure (FS) with raw scores = 0–3; 2) moderate FI (MFI), with raw scores = 4–6; and 3) Sever FI, with raw scores = 7–8 [22].

Ethical consideration

Ethical clearance was obtained from the Ethical review committee of Arba Minch University, College of Medicine and Health Science. Following the approval, an official letter of co-operation was written to concerned bodies by the Department of Public Health of Arba Minch University. Permission was also obtained from the Gamo Zone health department, district health office, and the respective health facilities. Informed verbal consent was obtained from each participant, after the necessary explanation about the purpose, procedures of the study, the importance of their participation, and their right to the decision of participating in the study. Participants were informed of their right to refuse to answer some or any of the questions, as well as the importance of maintaining the confidentiality of the information collected throughout the study by remaining anonymous, keeping their privacy by interviewing them in a separate room during the interview and locking records.

Results

Socio-demographic characteristics of the study participants

From two hundred fifty-eight TB patients invited, data of 255 TB patients were analyzed, excluding three patients for incompleteness of data giving the response rate of 99%. Accordingly, 161(63.1%) of the respondents were registered at health centers and 106(41.6%) were females. The median (IQR) age of the study participant was 25(21–28) years and the majority of the 112(43%) were among the age range of 18–24 years. One hundred forty (54.9%) of the cases were followers of protestant Christian and 149(58.4%) of the enrolled participant resided in rural. Concerning occupation and income, around 69 (27.1%) participants were students and 159(62.4%) belong to the income level of ≤ $13.91 respectively. The median time taken by patients from their home to initially visit the health facility was 30 minutes in one direction. (IQR 20–60). (Table 1)

Table 1. Socio-demographic characteristics of TB patients in Gamo zone public health facilities, Southern Ethiopia, 2019 (n = 255).

Variables Frequency Percent (%)
Treatment center Hospital 94 36.9
Health center 161 63.1
Sex Male 149 58.4
Female 106 41.6
Age 18–24 112 43.9
25–44 97 38.0
≥45 46 18.1
Residence Urban 106 41.6
Rural 149 58.4
Educational status Illiterate 68 26.7
Primary school 89 34.9
Secondary and above 98 38.4
Marital status Single 98 38.4
Married 145 56.9
Widowed/Divorced 12 4.7
Family size 1 to 3 63 24.7
>3 192 75.3
Income status(US Dollar) ≤ $13.91 159 62.4
$13.92–25.29 47 18.4
>$25.29 49 19.2
Occupational status Employed 58 22.7
Farmer 60 23.5
Student 69 27.1
Unskilled workera 16 6.3
Unemployed/Housewife 52 20.4
Religion Orthodox 106 41.6
Protestant 140 54.9
Othersb 9 3.5
One way walking time ≤30 min 144 56.5
30–60 min 59 23.1
≥60 min 52 20.4

a Housemaid, daily laborer

b Muslim(6), Catholic(2), traditional(1)

Health-care seeking behavior of tuberculosis patients

After the symptoms, 115 took action including self-treatment and use traditional medicine before the HCF visit. About the severity of the diseases at presentation, 144(56.5%) of the patients were ambulatory in functional status before contacting a formal health facility. Of all the respondents, 193(75.7%) perceived their first visit was delayed for which 170(66.7%) and 50 (19.6%) reasoned expecting the illness to limit by itself and lack of money respectively (Fig 1).

Fig 1. Perceived reasons for delay health care seeking among TB patients in Gamo zone public health facilities, Southern Ethiopia, 2019.

Fig 1

More than half 171 (67%) of patients first contacted public health facility and 214 (83.9%) were encountered more than one health care contacts before a diagnosis of TB made, and 17 (6.7%) patients were diagnosed at private facilities. Related to community-based health insurance (CBHI) status 44 (17.3%) were a member before seeking care among respondents (Table 2).

Table 2. Healthcare seeking behavior among TB patients in Gamo zone public health facilities, Southern Ethiopia, 2019 (n = 255).

Variables Frequency Percent (%)
First action to illness Visit HCFa 126 49.4
Self-treatment 92 36.1
Use traditional medicine 22 8.6
Consult HEWb 15 5.9
Severity of disease at the 1st contact Working 88 34.5
Ambulatory 144 56.5
Bedridden 23 9.0
Facility first visited Private facilities 64 25.1
Public hospital 59 23.1
Health center 112 43.9
Health post 20 7.9
Health care contacts Single 41 16.1
Multiple 214 83.9
Place of TB diagnosis Public 238 93.3
Private 17 6.7
CBHI statusc Yes 44 17.3
No 211 82.7
Knowledge towards TB Poor 131 51.4
Good 124 48.6
TB associated Stigma Low stigma 42 16.5
High stigma 213 83.5
TB category SPPTBd 173 67.8
SNPTBe 35 13.7
EPTBf 47 18.5
HIV status Positive 21 8.2
Negative 234 91.8
Contact history in the last 1 year Yes 65 25.5
No 190 22.5
BMI Normal 132 51.8
Underweight 123 48.2
FIES statusg Food secure 124 48.6
Moderate food insecurity 80 31.4
Sever food insecurity 51 20.0

a health care facility

bHealth Extension worker(trained females those provide a household package of health care to household)

c Community-based health insurance

dsmear-positive pulmonary tuberculosis

e smear-negative pulmonary tuberculosis

fextrapulmonary tuberculosis

g Food insecurity experience scale

Knowledge, behavioural and clinical characteristics of tuberculosis patient

Regarding knowledge about TB, 124 (48.6%) had relatively good knowledge about TB illness and its treatment. The majority of the TB patients knew that TB is curable 232(91%) and the duration of anti-TB treatment 155 (60.8%). Nearly 225(88.2%) of the patients knew that TB was a contagious disease. Regarding the level of stigma associated with TB, most 213(83.5%) of the respondents practiced High stigma on tuberculosis.

Of the total respondents who were assessed during diagnosis to check their nutritional status, 132 (51.8%) had a normal BMI of 18.5 to 24.99 kg/m2, while the rest were underweight. The majority of the respondents were in the food secure categories with respect to food insecurity experience (Table 2).

Clinical characteristics of the participants at the presentation

At the onset of illness, the majority of patients came with a combination of symptoms. The most frequently reported symptom was cough in 209(82%) patients; followed by night sweating in 12(49.8%) patients, fatigue/weakness in 108(42.4%) patients, weight loss in 73 (28.6), chest pain in 74 (29.0) and loss of appetite in 70 (27.5) patients respectively (Fig 2).

Fig 2. Complaints, which made patients, seek medical care in Gamo zone public health facilities, Southern Ethiopia, 2019.

Fig 2

More than half of the respondents 173 (67.8%) were smear-positive in classification and before the commencement of treatment, all of the cases were offered HIV screening tests of whom 21(8.2%) tested positive. Regarding contact history, in the last year with TB patients only 65(25.5%) had contact with TB patients.

Delay period and associated factors

Patient delay

The median (IQR) days elapsed between onset of illness to first health facility visit (patient delay) was 30 (15–60). Of all recruited study participants, 145 (56.9%) did seek medical advice after 30 days of the onset of their illness. The median patient delay is significantly different with residence (p<0.001), TB patients from rural (median 30 days) longer patient delay than those from urban (median 21 days), educational status (p<0.001): Illiterate (median 45 days) and primary school (median 30 days) had longer patient delays than those secondary and above (median 21 days). Furthermore, type of TB (P = 0.03), occupational status (p = 0.002), one way walking time (p = 0.002), among type of symptom patients presenting with lose weight and appetite(p = 0.011 and p = 0.021 respectively), severity of disease at first contact (p = 0.006), first action (p = 0.001), facility first visited (0.024), number of health care contact (p = 0.043) knowledge towards TB (p = 0.004) were significantly associated with median patient delay (Tables 3 & 4).

Table 3. Distribution of patient delay by socio-demographic, clinical variables and health-seeking trajectories, non-parametric (Mann–Whitney and Kruskal-Wallis) test.
Characteristics Patient delay
Median(IQR) p-value
Total 30(15,60)
Delayed, n (%) 145(56.9)
Sex Male 30(15,60) 0.672
Female 30(15,60)
Residence Urban 21(15,30) <0.001
Rural 30(21,60)
Age 18–24 30(15,41.25) 0.237
25–44 30(15,60)
≥45 30(15,60)
Education status Illiterate 45 (21,90) <0.001
Primary school 30(17.5,60)
Secondary and above 21(15,30)
Marital status Single 30 (15,30) 0.244
Married 30(15,60)
Widowed/Divorced 30(15,52.5)
Family size 1 to 3 30(15, 30) 0.166
>3 30(15,60)
Occupational status Employed 30(15,30) 0.002
Farmer 45(21,90)
Student 21(15,30)
Unskilled worker 30(20,52.50)
Unemployed 25.5(15,60)
Income status ≤ $13.91 30(15,60) 0.094
$13.92–25.29 45(21,60)
>$25.29 30(15.37.5)
CBHIb status Members 30(20,60) 0.160
Not member 30(15,60)
One way walking time <30min 30(15,30) 0.002
30-60min 30(15,45)
>60min 30(21,90)

a Housemaid, daily laborer

b Community-based health insurance

Table 4. Distribution of patient delay by socio-demographic, clinical variables and health-seeking trajectories, nonparametric (Mann–Whitney and Kruskal-Wallis) test (Continued).
Characteristics Patient delay
Median(IQRa) p-value
TB category SPPTBb 30 (15,60) 0.552
SNPTBc 21(15,45)
EPTBd 30(21,60)
Types of symptom Cough 30(15,60) 0.698
Fever 30(21,60) 0.288
Loss weight 30(21,60) 0.011
Hemoptysis 30(15,50) 0.748
Chest pain 30(20,60) 0.136
Breathlessness 30(21,60) 0.072
Night sweating 30(15,45) 0.468
Fatigue 30(21,60) 0.072
Loss of appetite 30(21,60) 0.021
Severity of disease at the 1st contact Working 21 (15,45) 0.006
Ambulatory 30(20,60)
Bedridden 60(21,90)
Contact history in the last 1 year Yes 30(21,60) 0.662
No 30(15,60)
HIVe status Positive 21 (15,60) 0.672
Negative 30(15,60)
First action Informal provider 30 (21,60) 0.001
Formal provider 21(15,30)
Facility first visited Government 30 (15,45) 0.024
Private 30(21,60)
Health care contacts Single 21(15,30) 0.043
Multiple 30(18.75,60)
BMIf Normal 30(15,41.25) 0.090
Underweight 30(15,60)
FIESg Food secure 30 (15,30) 0.083
Moderate food insecurity 30(15,60)
Sever food insecurity 30(21,60)
Knowledge towards TB Poor 30(21,60) 0.004
Good 21(15,45)
TB associated stigma Low stigma 21(15,54) 0.084
High stigma 30(15,60)

Note: Using non-parametric Kruskal-Wallis test to compare three or more groups and Mann–Whitney test to compare two groups. Statistically significant values are in bold.

a interquartile range

b smear-positive pulmonary tuberculosis

c smear-negative pulmonary tuberculosis

d extrapulmonary tuberculosis

e human immunodeficiency virus

f Body Mass Index

g food insecurity experience scale.

On bivariate logistic regression, prolonged patients delay was significantly associated with rural residence, older age (≥45 years), having large family members, occupation, educational status, walking for more than 60 min to arrive at the health facility, not being a member of CBHI, smear-negative status, and EPTB, the severity of disease at the first contact, having symptoms of fever, loss of weight, chest pain, fatigue, loss of appetite and breathlessness, the first action of informal provider, the private facility first visited, having multiple health care contact, nutritional status of underweight, FIES of moderately and severe food insecurity and having high stigma. Nevertheless, having good knowledge of TB was significantly associated with reduced patients delay.

In multiple logistic regression, among types of symptoms: patient presetting with loss of weight (AOR: 2.53; 95%CI: 1.35,4.74) and fatigue (AOR: 2.38; 95%CI: 1.36,4.17), first action informal provider (AOR: 2.24; 95%CI: 1.29,3.86) and body mass index(BMI) categories of underweight (AOR: 1.74; 95%CI: 1.01,3.00) were independently associated with higher odds of patient delay beyond the median of 30 days. On the other hand having good knowledge about TB (AOR: 0.44; 95% CI; 0.26, 0.76) was independently associated with lower odds of patient delay beyond the median of 30 days (Table 5).

Table 5. Factors associated with patient delay among TB patients in Gamo zone public health facilities, Southern Ethiopia, bivariate and multivariate analysis, 2019.
Variables Patient delay(days) Crude and adjusted OR
≥30 <30 COR(95%CI) AOR(95%CI)
Residence Urban 50(47.2) 56(52.8) 1 1
Rural 95(63.8) 54(36.2) 1.97(1.19,3.27) 1.64(0.94,2.86)
Age 18–24 58(51.8) 54(48.2) 1 1
25–44 58(59.8) 39(40.2) 1.38(0.80,2.40) 1.25(0.56,2.81)
≥45 29(63.0) 17(37.0) 1.59(0.78,3.21) 0.75(0.26,2.21)
Educational status Illiterate 46(67.6) 22(32.4) 2.27(1.19,4.32) 1.55(0.56,4.27)
Primary school 52(58.4) 37(41.6) 1.52(0.85,2.72) 0.90(0.43,1.95)
Secondary and above 47(48.0) 51(52.0) 1 1
Occupation Employed 32(55.2) 26(44.8) 1 1
Farmer 43(71.7) 17(28.3) 2.05(0.96,4.41) 1.69(0.60,4.71)
Student 34(49.3) 35(50.7) 0.79(0.39,1.59) 0.82(0.35,1.95)
Unskilled worker 10(62.5) 6(37.5) 1.35(0.43,0.42) 0.80(0.21,3.12)
Unemployed/Housewife 26(50.0) 26(50.0) 0.81(0,38,1.72) 0.74(0.29,1.93)
One way walking time ≤30 min 77(53.5) 67(46.5) 1 1
30–60 min 32(54.2) 27(45.8) 1.03(0.56,1.89) 0.62(0.29,1.34)
≥60 min 36(69.2) 16(30.8) 1.96(0.99,3.84) 0.97(0.40,2.37)
CBHIa Status Member 30(68.2) 14(31.8) 1 1
Not member 115(54.5) 96(45.5) 0.56(0.28,1.11) 0.62(0.27,1.38)
TB category SPPTBb 102(59.0) 71(41.0) 1
SNPTBc 15(42.9) 20(57.1) 0.52(0.25,1.90) 0.49(0.22,1.12)
EPTBd 28(59.6) 19(40.4) 1.03(0.53,1.98) 1.41(0.65,3.06)
Severity of disease at the 1st contact Working 42(47.7) 46(52.3) 1 1
Ambulatory 86(59.7) 58(40.3) 1.62(0.95,2.77) 1.18(0.59,2.37)
Bedridden 17(73.9) 6(26.1) 3.10(1.12,8.61) 1.71(0.45,6.56)
Types of symptoms
Fever Yes 40(64.5) 22(35.5) 1.52(0.84,2.75) 1.46(0.74,2.88)
No 105(54.4) 88(45.6) 1 1
Loss of weight Yes 53(72.6) 20(27.4) 2.59(1.44,4.68) 2.53(1.35,4.74)*
No 92(50.5) 90(49.5) 1
Chest pain Yes 47(63.5) 27(36.5) 1.47(0.84,2.57) 1.44(0.73,2.82)
No 98(54.1) 83(45.9) 1 1
Breathlessness Yes 35(64.8) 19(35.2) 1.52(0.82,2.84) 1.34(0.67,2.68)
No 110(54.7) 91(45.3) 1 1
Fatigue Yes 73(67.6) 35(32.4) 2.17(1.30,3.64) 2.38(1.36,4.17)*
No 72(49.0) 75(51.0) 1
Loss of appetite Yes 48(68.6) 22(31.4) 1.98(1.10,3.54) 1.60(0.80,3.21)
No 97(52.4) 88(47.6) 1 1
First action Informal provider 78(68.4) 36(31.6) 2.39(1.43,4.00) 2.24(1.29,3.86)*
Formal provider 67(47.5) 74(52.5) 1 1
Facility first visited Government 102(53.4) 89(46.6) 1 1
Private 43(67.2) 21(32.8) 1.78(0.99,3.24) 1.52(0.75,3.04)
Health care contacts Single 18(43.9) 23(56.1) 1 1
Multiple 127(59.3) 87(40.7) 1.86(0.95,3.66) 113(0.46,2.80)
BMIe Normal 68(51.5) 64(48.5) 1
Underweight 77(62.6) 46(37.4) 1.57(0.96,2.60) 1.74(1.01,3.00)*
FIESf status Food secure 64(51.6) 60(48.4) 1 1
Moderate insecurity 48(60.0) 32(40.0) 1.41(0.80,2.48) 0.68(0.31,1.50)
Sever food insecurity 33(64.7) 18(35.3) 1.72(0.87,3.37) 1.00(0.41,2.45)
Knowledge toward TB Poor 86(65.6) 46(34.4) 1 1
Good 59(47.6) 65(52.4) 0.47(0.29,0.79) 0.44(0.26,0.76)*
TB associated stigma Low stigma 19(45.2) 23(54.8) 1 1
High stigma 126(59.2) 87(40.8) 1.75(0.90,3.41) 1.35(0.61,2.95)

a Community based health insurance

b smear-positive pulmonary tuberculosis

c smear-negative pulmonary tuberculosis

d extrapulmonary tuberculosis

e Body Mass Index, food insecurity experience scale.

*P-value < 0.05; COR: Crude odds ratio; AOR: Adjusted odds ratio; CI: Confidence Interval; 1: Reference category

Discussion

This study set out with the aim of assessing the magnitude and factors associated with patient delay among tuberculosis patients in Gamo Zone, Southern Ethiopia. The result of this study demonstrated that the median (IQR) of the patient delay was 30(15–60) days and the observed patient delay was agreed with previous studies in Ethiopia [15, 16, 23] and other low-and-middle-income countries (28–30 days) [24, 25]. The current study finding is lower than studies carried out in different areas of Ethiopia (36–63 days) [13, 26] and Nepal (50 days), and Ghana (59 days) [17, 27]. However, tuberculosis patients in China (median, 10 days) and Iran (median, 13 days) were substantially less delayed than those in this study [14, 28]. The cultural issue, low socioeconomic standing, and low level of knowledge and understanding of the disease are all potential explanations for disparities in delay. Besides that, the patients’ prolonged delay in our study may be linked to their inability to recognize symptoms at the first onset of the disease. This result was supplemented by a recent national tuberculosis prevalence survey, which showed that less than half of TB patients meet the "TB suspect" criteria and of them have solely imprecise symptoms [29].

The proportion of patients who delayed beyond the median value of patients delay (30 days) was 56.9% in the current study, with a 95% CI (50.7%, 63.0%). Previous studies in Ethiopia [13, 30], other African countries [17, 25], and Pakistan [31] also reported consistent proportions.

However, the findings of this study were relatively higher than those of studies conducted in Ethiopia (31.3–46.3%) [13, 30], and other African countries Zimbabwe and Uganda [24, 32], and lower than studies conducted in Bale Zone of Ethiopia’s, where 89.9% of TB patients visited a health care provider after the median time had elapsed (30 days) [33]. Variations among these studies may be due to differences in countries’ health systems, strategies and policies, and infrastructure, as well as differences in the sample population’s socio-demographic features, such as rural versus urban settings, and pure agricultural versus pastoralist populations [34].

It is necessary to have adequate knowledge of tuberculosis in order to seek medical help as soon as possible. In this study, the extent of knowledge regarding TB was found to be significantly associated with patient delay. The study discovered that patients who have a good knowledge of TB disease and treatment are less likely to put off seeking care. Similarly, other studies have found that a lack of knowledge about tuberculosis and its treatment program as an explanation for the delay in seeking care [13, 26, 34, 35], and can endorse that lack of knowledge may additionally result in patients’ reluctance in search of appropriate health care.

Using an informal care provider was found to be a strong predictor of patient delay during this study. Patients who went to non-formal health care providers first had longer patient delays than patients who went to formal health care providers first. Previous studies in Ethiopia [13, 26] and other African countries [35, 36] have reported consistent findings. This finding could be attributed to the fact that patients have taken several actions before visits to a formal health care facility that affect the timing of care-seeking. This could be ascribed to the use of such home remedies or over-the-counter antibiotics or analgesics, which could, for the time being, minimize the manifestation of the disease. Another potential reason for this result is that the relative abundance of drug stores provides an advantage of proximity as compared to diagnostic health facilities, as well as cost savings as drug stores do not charge for cards or laboratory services [13].

Following previous studies [37, 38], the most frequent symptoms in our patients were cough, night time sweating, fatigue, and chest pain. From the mentioned symptoms, weight reduction and fatigue have been found as a factor associated with prolonged patient delay. Accordingly, weight reduction was shown to be positively associated with a longer patient delay in multiple studies in Brazil, Melbourne, and Montenegro [27, 39, 40]. These findings may be clarified by the fact that patients perceive these symptoms as temporary signs of a general disease, leading to self-treatment that lasts until deterioration and the appearance of more specific symptoms. Furthermore, timely referral to healthcare services for debilitating symptoms could also be difficult owing to financial constraints, low health awareness, and stigma [38]. However, this finding was contrary to the finding from Brazil [41]. A possible explanation for these differences may be the majority of the patient in Brazil might know that weight loss is one of TB symptoms.

Another finding from this study suggests that people with a BMI’s in the underweight category are more presumably to delay than those with a normal BMI. These results further support the above finding that patient presenting with weight loss was more likely to delay than their counterpart. We also checked for Multicollinearity between weight loss and BMI’s status, but there was no Multicollinearity [38]. However, this result has not previously been described. Those underweight patients possibly come from low socio-economic status, given that poverty commonly influences the health-seeking behavior of individuals.

Conclusions

Our results demonstrated that a significant proportion of patients had delays that exceeded the suitable range. The median patient delay, according to our findings, was 30 days. About 56.9% of patients had prolonged patients’ delay. The first action provided by an informal provider, a lack of knowledge about TB, underweight BMI status, and a patient presenting with symptoms of weight loss and fatigue were studied to be factors associated with prolonged patient delay.

The findings from this study suggest that the community should be sensitized to seeking appropriate health care as early as possible. The sensitization programs should take into consideration of different groups in a society such as women, elders, illiterate, and economically poor by using culturally convenient media of communication to ensure that the whole community is reached. Greater efforts are needed to ensure intensify TB case finding involving the community, formal and informal providers by decentralizing diagnostic and therapeutic services to lower-level public and private healthcare facilities. Health education sessions should be designed and provided to enhance accurate awareness dissemination on symptoms, medication options, and the curability of TB in the community, as well as patients attending primary health care facilities. There is no doubt that the maintenance of a high suspected tuberculosis index in the older population is justifiable. Given that different factors may delay the diagnosis of TB in elderly individuals, efforts should be made to reduce these delays in order to stop or control the spread of TB. Further research should be undertaken to investigate the in-depth understanding of reasons for a patient using qualitative designs and a community-based study can be done to capture symptomatic individuals who are not attending health facilities.

Supporting information

S1 Fig. Schematic representation of sampling procedure.

(TIF)

S1 Text. Additional definition and measurements.

(DOCX)

S1 File. Questionnaire.

(PDF)

S1 Data. The raw data supporting the finding of this article.

(CSV)

Acknowledgments

We are grateful to Arba Minch University, College of Health Sciences and Medicine for providing us with ethical clearance for this study. We also extend our appreciation to study participants, data collectors, Supervisors, and Health facility leaders.

Abbreviations

TB

Tuberculosis

DOTS

Directly observed treatment short-course

HSTP

Health sectors transformation plan

PD

Patient delay

CBHI

Community-based health insurance

HCF

Health care facility

FIES

Food insecurity experience scale

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

The author(s) received no specific funding for this work.

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Decision Letter 0

Claudia Marotta

19 Jan 2021

PONE-D-20-27080

PATIENT DELAY AND ASSOCIATED FACTORS AMONG TUBERCULOSIS PATIENTS IN GAMO ZONE PUBLIC HEALTH FACILITIES, SOUTHERN ETHIOPIA; 2019:AN  INSTITUTION-BASED CROSS-SECTIONAL STUDY

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Reviewer #1: Acceptable findings for a common serious disease in an endemic country. Both Introduction and Methods are narrated in a scientific way. Results flowed smoothly and conclusions met the study objectives.

Reviewer #2: The manuscript is very interesting but it is too long: all the sections must be summarized. The main section are the RESULTS. There are tables with frequencies and other with the results related with these frecuencies and the text related.

Reviewer #3: In general, although not unprecedented, the article makes relevant contributions to the understanding of access to TB diagnosis and treatment in an important region of Ethiopia.

In the section “Introduction”: in the fourth paragraph that reads “Thus, Ethiopia has been listed among the 14 TB, TB / HIV (Human Immunodeficiency Virus) and Multi-Drug Resistant TB (MDR TB) high burden Countries (HBC) that accounted for 80% of all estimated TB cases Worldwide (7) ”. The reference (7) cites 30 high burden countries: 20 by absolute number of TB cases plus 10 based on severity of disease burden - incidence per capita. In the last paragraph of the same section where it reads “Therefore, the aim of this study is to assess the magnitude and factors associated with patient and health system delays among tuberculosis patients in Gamo Zone public health facilities”, the results and discussion do not explore the factors associated with the delay associated to the health system. Therefore, I suggest removing the delay related to the health system from the aim of the study.

Material and methods: it is not clear how the patients were selected and recruited, if there was sampling for smear positive and smear negative patients. Since smear negative at diagnosis may be related to the early search for care, I suggest having a separate analysis for smear negative patients; the same applies to extrapulmonary TB, in which the search for diagnosis can take longer because the symptoms are often more insidious. In cases of smear negative patients, how was TB diagnosis confirmed?

In the item “Study setting and design” the first paragraph describes the health network of Gamo Zone and there is no mention of the “health posts” that appear in the second paragraph. I suggest clarifying what "health posts" are and make up the health network.

In the presentation of the “Results”, Table 1 describes that 9 people had other religions and the note in the same Table referring to the letter “b” describes “b Muslim (6), Catholic (10), traditional (17)”. What are the numbers in parentheses? In this section I suggest dollarizing the value of "income status" to give an idea of the degree of poverty in relation to international parameters. For example, in 2015 the United Nations Organization classified the income of USD 1.90 / day / person as extreme poverty. It is also not clear whether the income was per family or per capita.

At the end of the fourth paragraph of the “Discussion” the authors state: “Another possible explanation for this finding is that the relative abundance of drug store offers an advantage of proximity compared to diagnostic health facilities and the drug store also have added advantages of cost minimization, as they do not charge for cards and laboratory services (17)"

however, in the“ Study setting and design” section we can read “Patients have free access to TB diagnosis and treatment in public health facilities ”. The sentences seem contradictory. I suggest that the authors clarify.

In the “Conclusion” section there is text in red. At the end of the text it reads “(review it)”. What does that mean? In addition, one of the conclusions is that there is a need for “regular refresher trainings”, but there are no data related to “health system delays” in the results or in the discussion section that can suspport this statement. I suggest removing from the last paragraph of the “introduction” section the “factors associated .... health system delays”, as already pointed out above.

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Reviewer #1: Yes: Layth Al-Salihi

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PLoS One. 2021 Jul 30;16(7):e0255327. doi: 10.1371/journal.pone.0255327.r002

Author response to Decision Letter 0


17 Apr 2021

Dear Editors and Reviewers,

Thank you for giving us the opportunity to submit a revised draft of our manuscript titled “Patient delay and associated factors among tuberculosis patients in Gamo zone public health facilities, Southern Ethiopia: An institution-based cross-sectional study” to PLOSE ONE. We appreciate the time and effort that you and the reviewers have dedicated to providing your valuable feedback on our manuscript. We are grateful to the reviewers for their insightful comments on our paper. We have been able to incorporate changes to reflect most of the suggestions provided by the reviewers.

Attachment

Submitted filename: Response to Editor Comments.docx

Decision Letter 1

Marian Loveday

15 Jul 2021

Patient delay and associated factors among tuberculosis patients in Gamo zone public health facilities, Southern Ethiopia: An institution-based cross-sectional study

PONE-D-20-27080R1

Dear Dr. Arja,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. 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.

Kind regards,

Marian Loveday, Ph.D.

Academic Editor

PLOS ONE

Reviewers' comments:

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: N/A

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors used a scientific language in expressing their study. The article context is kept in line the aim of the study.

Reviewer #2: The revision has been well adapted to the reviewers comments. The Delay in diagnostic of Tuberculosis is an important issue in all TB programmes.

Reviewer #3: (No Response)

**********

Acceptance letter

Marian Loveday

22 Jul 2021

PONE-D-20-27080R1

Patient delay and associated factors among tuberculosis patients in Gamo zone public health facilities, Southern Ethiopia: An institution-based cross-sectional study

Dear Dr. Arja:

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.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Marian Loveday

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Fig. Schematic representation of sampling procedure.

    (TIF)

    S1 Text. Additional definition and measurements.

    (DOCX)

    S1 File. Questionnaire.

    (PDF)

    S1 Data. The raw data supporting the finding of this article.

    (CSV)

    Attachment

    Submitted filename: Response to Editor Comments.docx

    Data Availability Statement

    All relevant data are within the paper and its Supporting Information files.


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