Willingness and yield of screening for hepatitis B among outpatients of a tertiary care centre,Puducherry,South India

Abstract

India’s National Viral Hepatitis Control Programme recommends screening outpatients for hepatitis B at tertiary care centres. We aimed to assess the yield of screening and reasons for refusal for testing. We included adult outpatients at a tertiary care centre, South India during September and October 2019. Participants’ willingness to be tested and the reasons for refusal were noted. Fingerstick blood sample was tested for HBsAg using rapid kit. Of a total of 700 participants, 157 (22%, 95% CI: 19.4–25.7%) were unwilling to be tested. Men were more unwilling (26%) compared to women (19%) (aPR 1.90 95% CI: 1.22–2.94; p = 0.004). ‘Lack of time’ was the most common reason reported for refusal (10%). Of 543 participants tested, 15 (2.8%, 95% CI: 1.6–4.5%) were positive for HBsAg. Similar studies from other regions in India are required for the estimation of yield of opportunistic approach.

Keywords

HBV HBsAg willingness yield prevalence risk factors

Introduction

In 2015, the global prevalence of chronic hepatitis B virus (HBV) infection was estimated to be 257 million, of which 11% of the burden was contributed by India.¹ Although the average prevalence of hepatitis B (HBsAg) in India ranges from 3 to 4%,² it has been declared a public health problem owing to its fatal consequences.¹ In 2015, an estimated 1.34 million deaths had occurred globally due to viral hepatitis.¹ This number is comparable to deaths caused by tuberculosis (TB) and higher than that caused by human immunodeficiency virus (HIV). In recent years, as the mortality caused by TB and HIV kept declining, the number of deaths due to viral hepatitis continued to rise. The Global Burden of Diseases in 2016 suggested that the mortality attributable to viral hepatitis in India could be 1.18% of all deaths, and the national estimates suggested that it contributed to 3% of all deaths related to communicable diseases.³

Hepatitis B, being a vaccine-preventable disease, provides an opportunity for screening to estimate the disease burden, identify risk factors and strategise adequate public health measures.⁴ The goals set by WHO for the elimination of hepatitis B by 2030 include achieving the target of 90% reduction in incidence and a 65% reduction in the number of related deaths from a 2015 basline.¹ Working towards elimination and control of viral hepatitis, a National Viral Hepatitis Control Programme was launched.³ This recommends opportunistic screening (i.e. offering a test for an unsuspected disorder at a time when a person presents to a doctor for another reason⁵) among patients visiting health care facilities. However, this strategy is yet to be implemented all over the country.

It has been practised for non-communicable diseases such as diabetes⁶ and hypertension,⁷ and this has helped in achieving higher rates of case detection. Though recommended by the national programme, evidence is limited on the yield of screening among outpatients. It is also important to know the willingness of patients to be tested and the reasons why others refuse.

Materials and methods

A hospital-based cross-sectional analytical study was conducted among patients aged >18 years, seeking outpatient care in the Department of Medicine of a tertiary care centre in Puducherry, South India during September and October 2019. Known cases of hepatitis B infection were excluded. Screening for hepatitis B is not offered routinely to all patients except for blood donors, pregnant women and patients undergoing surgery.

We calculated the sample size of 1024 based on expected prevalence of hepatitis B infection among outpatients as 4%,² absolute precision of 1.2% and an α error of 5%. However, owing to logistic reasons (time and testing kits), we included only 700 outpatients. Every 10th patient registering in the outpatient clinic was included.

We used a structured questionnaire to collect information on socio-demographic details and behavioural characteristics such as age, gender, residence, education, occupation, contact number, marital status, tobacco and alcohol use. Medical history of jaundice, family history of jaundice, presence of any self-reported chronic illnesses (diabetes, hypertension, respiratory disorders, kidney diseases, TB or HIV), history of dialysis for acute or chronic kidney disease, history of dental procedures, hepatitis B vaccination status and number of injections received in the previous year were collected. High-risk behaviour was assessed by asking questions about the history of injectable drug use, high-risk sexual behaviour (premarital and extramarital) and history of tattooing.

The reasons for refusal were recorded from those who were unwilling. The presence of HBsAg in whole blood (collected using a fingerstick) was tested with the help of Alere Determine™ HBsAg rapid testing kit (Manufactured by Abbott, Chiba, Japan). The sensitivity of the testing kit was 95.16%, and specificity was 99.95%.⁸

Our study protocol was reviewed and approved by the Institute Ethics Committee (reference number – JIP/IEC/2019/301) of Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry. The patients who tested positive were counselled and referred to the Department of Medical Gastroenterology for further management.

Data were entered in EpiData Manager v4.3.3.1 (Odense, Denmark) and analysed using Stata version 14 (Statacorp., TX, USA). Unwillingness to be screened and seroprevalence of HBsAg were expressed as proportions with 95% confidence interval (CI). Reasons for refusal were summarised as percentages. Association of socio-demographic, behavioural and other characteristics with unwillingness and seroprevalence of HBsAg was assessed using χ² test, and unadjusted prevalence ratios (aPR) with 95% CI were calculated. Log binomial regression was performed by including the variables that had a p-value of <0.2 in unadjusted analysis, and aPR with 95% CI was calculated. A p-value < 0.05 was considered statistically significant.

Results

A total of 706 participants were approached for the study, of whom 6 (0.8%) were known cases of hepatitis B and hence excluded. The flow of study participants in the screening cascade is described in Figure 1. The mean (standard deviation) age of the study participants was 42 (14) years and 330 (47%) were males. The socio-demographic characteristics of the study participants are given in Table 1.

Figure 1.

Flowchart depicting the number and proportion of the study participants in the screening cascade.

Table 1.

Socio-demographic characteristics of the outpatients of a tertiary care centre, Puducherry, 2019 (N = 700).

Characteristics	n	%
Age groups (years)
18–29	145	20.7
30–44	245	35.0
45–59	239	34.1
≥60	71	10.1
Gender
Male	330	47.1
Female	370	52.9
Education
No formal education	146	20.9
Primary and middle school (1–8)	199	28.4
Secondary school (9–12)	205	29.3
Graduate and above	150	21.4
Occupation
Unemployed	110	15.7
Employed	315	45.0
Business	35	5.0
Student	39	5.8
Homemaker	186	26.6
Retired	15	2.1
Marital status
Unmarried	106	15.1
Married	522	74.6
Separated/widowed	72	10.3
Patient type
New	262	37.4
Old	265	37.9
Attendant	173	24.7

Of total, 85 (12%) had a history of blood transfusion, 327 (47%) had dental treatment and 109 (16%) had tattooing. The behavioural and health-related characteristics are described in Table 2. Of the 157 (22%, 95% CI: 19.4–25.7%) who refused, ‘lack of time’ was the most common reason (10%). Other reasons given were ‘no necessity to get tested’, ‘scared’, ‘tested already’, ‘not interested’, ‘anaemic/weak/not well’ and ‘family consent required’. Males showed higher unwillingness (26%) when compared to females (19%), and this difference was statistically significant (aPR 1.90 95% CI: 1.22–2.94; p = 0.004) (Table 3).

Table 2.

Behavioural and health-related characteristics of outpatients of a tertiary care centre, Puducherry, 2019 (N = 700).

Characteristics	n	%
Tobacco use in last one month	118	16.9
Alcohol use ever	211	30.1
Alcohol use in last 12 months	166	23.7
Self-reported chronic illness^a	262	37.4
Family history of hepatitis B infection	11	1.6
History of jaundice	158	22.6
Family history of jaundice	189	27.0
History of blood transfusion	85	12.1
History of dialysis	3	0.4
History of dental procedures	327	46.7
History of injecting drug use	0	0
History of tattooing	109	15.6
High-risk sexual behaviour	81	11.6
Number of injections received in past one year
<5	354	50.6
5–25	289	41.3
>25	56	8.0
Received at least one dose of hepatitis B vaccination
Yes	128	18.3
No	287	41.0
Don’t know	285	40.7

Self-reported chronic illness – diabetes, hypertension, kidney disease, espiratory diseases, liver diseases, cardiac diseases, TB and HIV.

Table 3.

Association of socio-demographic characteristics with unwillingness for hepatitis B screening among outpatients of a tertiary care centre, Puducherry, 2019 (N = 700).

Categories	N	Unwillingness	CPR (95% CI)	APR (95% CI)	p-Value^a
Categories	N	n (%)	CPR (95% CI)	APR (95% CI)	p-Value^a
Total	700	157 (22.4)	–
Age groups (years)
18–29	145	26 (17.9)	1	1	–
30–44	245	44 (18.0)	1.00 (0.65–1.55)	1.05 (0.61–1.79)	0.867
45–59	239	55 (23.0)	1.28 (0.84–1.95)	1.19 (0.69–2.04)	0.535
≥60	71	32 (45.1)	2.51 (1.63–3.87)	1.60 (0.86–2.95)	0.137
Gender
Female	370	72 (19.5)	1	1	–
Male	330	85 (25.8)	1.32 (1.00–1.75)	1.90 (1.22–2.94)	0.004
Education
Graduate and above	150	32 (23.3)	1	1	–
Secondary school (9–12)	205	36 (17.6)	0.82 (0.54–1.26)	0.77 (0.51–1.19)	0.241
Primary and middle school (1–8)	199	47 (23.6)	1.11 (0.75–1.65)	1.10 (0.71–1.70)	0.667
No formal education	146	42 (28.8)	1.35 (0.90–2.01)	1.43 (0.90–2.28)	0.135
Marital status
Unmarried	106	19 (17.9)	1	1	–
Married	522	118 (22.6)	1.26 (0.81–1.95)	1.07 (0.59–1.92)	0.830
Separated/widowed	72	20 (27.8)	1.55 (0.89–2.69)	1.42 (0.72–2.83)	0.312

CPR: crude prevalence ratio; APR: adjusted prevalence ratio; CI: confidence interval.

p-Value is for adjusted analysis. The variables included in log-binomial model are as follows: age groups, gender, residence, education, occupation, marital status, patient type, family history of jaundice, number of injections received in past one year, history of blood transfusion, history of dental procedures and history of tattooing and high-risk sexual behaviour.

The participants with no tattoo were 1.7 times more unwilling than those who had (aPR 1.72 95% CI: 1.12–2.65; p = 0.013). Unwillingness was significantly higher in patients who had no history of high-risk sexual behaviour (aPR 1.81 95% CI: 1.09–3.02; p = 0.023) (Table 4).

Table 4.

Association of behavioural and health-related characteristics with unwillingness for hepatitis B screening among outpatients of a tertiary care centre, Puducherry, 2019 (N = 700).

Categories	N	Unwillingness	CPR (95% CI)	APR (95% CI)	p-Value
Categories	N	n (%)	CPR (95% CI)	APR (95% CI)	p-Value
Total	700	157 (22.4)
Family history of hepatitis B
Yes	11	0	–	–	–
No	689	157 (22.8)	–	–	–
History of jaundice
Yes	158	36 (22.8)	1	–	–
No	542	121 (22.3)	0.98 (0.71–1.36)	–	–
Family history of jaundice
Yes	189	36 (19.1)	1	–
No	511	121 (23.7)	1.24 (0.89–1.73)	1.16 (0.84–1.60)	0.377
Number of injections received in past one year
<5	354	76 (21.5)	1	–
5–25	289	74 (25.6)	1.19 (0.90–1.58)	1.09 (0.83–1.45)	0.526
>25	57	7 (12.5)	0.58 (0.28–1.18)	0.48 (0.25–0.93)	0.029
History of blood transfusion
Yes	85	11 (12.9)	1	1
No	615	146 (23.7)	1.83 (1.04–3.24)	1.72 (0.98–3.01)	0.058
History of dental procedures
Yes	327	65 (19.9)	1	1
No	373	92 (24.7)	1.24 (0.94–1.64)	1.17 (0.88–1.55)	0.288
History of tattooing
Yes	109	17 (15.6)	1	1
No	591	140 (23.7)	1.52 (0.96–2.41)	1.72 (1.12–2.65)	0.013
High-risk sexual behaviour
Yes	81	12 (14.8)	1	1
No	619	145 (23.4)	1.58 (0.92–2.72)	1.81 (1.09–3.02)	0.023

CPR: crude prevalence ratio; APR: adjusted prevalence ratio; CI: confidence interval.

p-Value is for adjusted analysis. The variables included in log binomial model are as follows: age groups, gender, residence, education, occupation, marital status, patient type, family history of jaundice, number of injections received in past one year, history of blood transfusion, history of dental procedures and history of tattooing and high-risk sexual behaviour.

Among those who expressed willingness for screening (543 participants), 15 (2.8%, 95% CI: 1.5–4.5%) were positive for HBsAg, and hence the number needed to screen was 36. True prevalence calculated after adjusting for sensitivity and specificity of the test kits was 2.9%. Hepatitis B positivity was significantly higher among males (5.3%) than females (0.7%), and this difference was statistically significant (p = 0.001). Seroprevalence of HBsAg was higher among those who reported alcohol use (4.6%) compared to non-users (2.2%) (p = 0.044). The validity of the test was good. Sensitivity of the test kit was 95.16%, and specificity was 99.95%,⁸ which was high enough to ensure accuracy of the test results by reducing false positivity.

Discussion

Fear of a positive result may be an important reason for the refusal of testing but could have been underreported owing to social desirability. Evidence from men’s reluctance for HIV testing in South Africa due to fear of stigmatisation and discrimination supports this speculation.⁹ Our yield of hepatitis B positivity at 2.8% was similar to the national prevalence estimates of 3–4%.² The yield was higher among men and is concordant with the other studies across the world.^10–12 Higher prevalence of risk factors such as chronic alcohol consumption and high-risk sexual behaviour among Indian men will partially explain higher estimates in men. Expanding this opportunistic screening approach to multiple tertiary care centres will help the national programme to identify a good proportion of undiagnosed cases in the community and link them to anti-viral therapy if required. Integrating hepatitis B testing for all clients attending HIV testing centres may yet improve the yield and coverage of testing.

Seroprevalence of hepatitis B was higher among those who reported alcohol use (p = 0.044). Both alcohol consumption and hepatitis B are known to deleteriously affect the liver. Individuals reporting alcohol use and seropositivty for hepatitis B need to be cautious as the disease progression is severe. There is an increased risk of developing liver cancer earlier than expected.¹³

Despite a good response rate (100%) related to information on socio-demographic and behavioural characteristics, our sample size did not allow us to study the association of socio-demographic and behavioural factors with HBsAg positivity. The generalisation of study findings to other settings is limited. We did not have information on confirmatory testing for HBsAg (ELISA) and the eligibility for antiviral therapy.

Conclusion

We believe, from the data in our study, that an opportunistic screening approach will help identify undiagnosed cases and link them to care. Introducing opportunistic screening in health care settings will help achieve WHO goals for the elimination of hepatitis B by 2030.

Footnotes

Acknowledgements

We extend our gratitude to the clinical and non-clinical staff of Department of Medicine, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), for providing assistance for conducting the study.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The first author (SSK) received funding from Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER Intramural Funds) as part of Masters Dissertation for buying the rapid test kits and other consumables.

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