Seroprevalence and risk factors for hepatitis B and hepatitis C in three large regions of Kazakhstan.

BACKGROUND & AIMS: Kazakhstan has implemented comprehensive programs to reduce the incidence of Hepatitis B and Hepatitis C. This study aims to assess seroprevalence and risk factors for HBsAg and anti-HCV positivity in three large regions of Kazakhstan.
METHODS: A cross-sectional study was conducted in three regions geographically remote from each other. Participants were randomly selected using a two-stage stratified cluster sampling and were surveyed by a questionnaire based on the WHO STEP survey instrument. Blood samples were collected for HBsAg and anti-HCV testing.
RESULTS: A total of 4,620 participants were enrolled. The seroprevalence was 5.5% (95%CI: 3.6%-8.4%) for HBsAg and 5.1% (95%CI: 3.5%-7.5%) for anti-HCV antibodies. Both were more prevalent in the western and northern regions than in the southern. A history of blood transfusion was significantly associated with anti-HCV presence, with odds ratios (ORs) of 2.10 (95%CI: 1.37-3.21) and was borderline associated with HBsAg 1.39 (95%CI: 0.92-2.10), respectively. Having a family member with viral hepatitis was also borderline associated (2.09 (95%CI: 0.97-4.50)) with anti-HCV positivity.
CONCLUSIONS: This study found a high-intermediate level of endemicity for HBsAg and a high level of endemicity for anti-HCV antibodies in three large regions of Kazakhstan. We found that history of surgery was not associated with HbsAg neither with anti-HCV seropositivity rates. Blood transfusion was associated with anti-HCV seropositivity, however, to investigate effectiveness of the introduced comprehensive preventive measures in health care settings, there is a need to conduct further epidemiological studies.

Introduction

Viral hepatitis is a major public health threat and one of the leading causes of mortality and disability worldwide, with a number of related deaths similar to HIV, malaria and tuberculosis. [1] Chronic hepatitis B virus (HBV) and hepatitis C virus (HCV) infections constitute over 90% of the overall burden of viral hepatitis. In 2015, approximately 257 million and 71 million people worldwide had chronic hepatitis B and hepatitis C infections respectively, predominantly in developing countries, and were responsible for an estimated 1.3 million deaths. [2] HBV and HCV infections also decrease the quality of life and pose significant financial burdens on patients and their families, including health-related expenses and adverse impacts on employment. [3, 4]

Kazakhstan, an upper-middle income country, is the largest country in Central Asia, and has a population of around 18 million, sparsely distributed throughout the vast country. Slightly less than half of the population lives in rural areas, lacks access to adequate healthcare and has poorer health indicators than people living in urban areas. [5] Studies evaluating the epidemiology of HBV and HCV in Kazakhstan have included only populations-at-risk, and/or were conducted in a single city or region. [6-13] In the last decade, hepatological services have been improved, and policies and interventions to prevent viral hepatitis implemented, including a vaccination campaign against HBV, screening of blood donors and populations-at-risk for HBV and HCV, and establishment of national clinical treatment guidelines. [14] However, the impact of these actions on HBV and HCV–associated risk factors remains unclear. Understanding the epidemiology of HBV and HCV can inform more effective policies to decrease the burden of viral hepatitis in Kazakhstan that may be applicable to other developing countries as well.

Our study is the first geographical-diverse, randomized study investigating the prevalence of HBsAg and anti-HCV antibodies in three large regions of Kazakhstan.

Materials and methods

Study design

This study is an extension of a national cross-sectional study on the monitoring of non-communicable diseases (NCD) supported by the Ministry of Health, which utilized the standardized WHO STEPwise approach to NCD surveillance (STEPS). [15]

A two-stage stratified cluster sampling was utilized. Given that Kazakhstan consists of 14 oblasts (administrative districts), three oblasts with larger populations–Almaty (size ~ 4 mln) in the South, Pavlodar (size ~ 0.8 mln) in the North, and Aktobe (size ~ 0.9 mln) in the West–were selected. In the first stage, each oblast was stratified into large cities, small towns and villages, according to population size, as primary sampling units (PSU). 35 PSUs were randomly selected across all strata. In the second stage, within each randomly selected stratum, 100 households were selected using systemic random sampling technique from a list of households in each selected PSU. Trained nurse interviewers collected data by face-to-face interviews from randomly selected households between January 2015 and December 2017.

Data collection

In the first step of data collection, participants were surveyed about their socio-demographic, behavioral risk factors and history of NCD using the WHO STEPS survey instrument. [16] The WHO STEPS survey instrument was developed by leading experts in their respective fields and used for national risk factor surveillance in many countries worldwide. [17] The instrument was translated by bilingual experienced researchers to Russian language. After experts fluent in both languages assessed appropriateness of the translation, the instrument was back translated to English by an independent translator to check for appropriateness of the translation to the original version. Later, the instrument was pre-tested among 50 participants and was revised for clarity and wording.

In the second step, physical measurements such as height, weight, blood pressure and other anthropometric measurements were collected by trained nurse interviewers. In the last step, after completing the survey and collecting anthropometric measurements, participants were invited to their local outpatient clinics for venous blood sample collection. An experienced phlebotomist collected venous blood specimen into Vacutainer serum separator tubes. The serum was separated from cells within 2 hours of collection and stored at 4°C temperature (not more than 48 hours) until assayed. Serum samples were tested for hepatitis B surface antigen (HBsAg), and anti-HCV antibody (anti-HCV) using Elecysys HBsAg II and Elecsys Anti-HCV (Roche Diagnostics GmbH, Germany) enzyme-linked immunosorbent assays (ELISA) according to the manufacturer’s instructions on the cobas e 601 platform. All results were reported as positive or negative. The instruments were calibrated daily based on standardized procedures.

A total of 4,620 participants responded to the survey. Out of these participants, 3,694 for HBsAg and 3,697 for anti-HCV were included in the study. Participants were excluded because of indeterminate serological test results (due to hemolysis or borderline results) or incomplete data (S1 Appendix).

The study was conducted in accordance with the Declaration of Helsinki and received ethical approval from the Ethics Board of the National Institute of Cardiology and Internal Diseases (Protocol #18 dated 28.01.2015) and the Institutional Research Ethics Committee of Nazarbayev University (NUSOM-IREC-NOV-2019-#20). Eligible participants provided written consent.

Data variables

Using the WHO STEPS survey instrument, data on socio-demographic characteristics and behavioral risk factors were collected. Socio-demographic variables included age categories (18–29, 30–39, 40–59, and 60–88 years of age), educational status (none/high school level, vocational level and university level), ethnicity (Kazakh; Russian; and others (Uzbek, which comprises 1% of the population; Ukrainian, 4.2%; other Asians, 4.5%; other European ethnicities, 1.8%), type of residence (urban or rural) and region (South, North and West). Any settlement with more than 50,000 people was considered an urban area, while any settlement with at least 50 residents and not exceeding 50,000 people was defined as a rural area. [18] Participants were asked questions concerning potential risk factors for infection, including history of any surgery, blood transfusion, hemodialysis, having a family member with viral hepatitis, injecting drug usage and tattooing.

Statistical analysis

After conducting basic descriptive statistics for all participants (means, medians, standard deviations, frequencies), bivariate analysis was performed to compare differences between independent variables and HBsAg or anti-HCV status. In bivariate analysis between socio-demographic and outcome variables, the prevalence of viral hepatitis with 95% confidence intervals and p-values were reported. Chi-square or Fisher’s exact tests for categorical variables and the Student’s T-test or Mann-Whitney U test for continuous independent variables were conducted, as appropriate. Existence of spatial autocorrelations in HBsAg and anti-HCV seropositivity by the region were tested using the Global Moran’s I test. Given spatial autocorrelations were identified (Moran’s I = 0.006 with p<0.001 for HBsAg and Moran’s I = 0.005 with p<0.001 for anti-HCV), multivariable mixed effects logistic regression was used to account for clustering of cases within the region and potential non-independence of the outcomes. In these models, associations between risk factors and the prevalence of outcomes as determined by HBsAg and anti-HCV results were presented as adjusted odds ratios while controlling for age and sex. Final models were built through inclusion of: first, demographic variables (age, sex and ethnicity), then additionally two potential risk factors (history of having surgery and history of blood transfusion), and later, all other risk factors (family member with viral hepatitis, hemodialysis and having tattoo or piercing). Given that we used two-stage cluster sampling, all descriptive, bivariate and multivariable statistics were weighted using inverse probability weighting to adjust for sampling design and non-response rate. All analyses were conducted using STATA 15 statistical software. [19]

Results

Seroprevalence and risk factors for HBV

Among the 3,694 respondents, 218 individuals, which corresponded to 5.5% (95%CI: 3.6%-8.4%) weighted prevalence, were identified as HBsAg-seropositive. The highest prevalence of HBsAg was observed among the young age group 30–39 years old (Fig 1). In bivariate analysis, the weighted prevalence of HBsAg among males at 6.5% (95%CI: 4.7–8.9), was borderline statistically significantly higher than females, who had a weighted prevalence of 5.1% (95%CI: 3.1%-8.3%) (Table 1). HBsAg seropositivity of 7.3% (95%CI: 6.1%-8.6%) and 7.0% (95%CI: 3.7%-13.0%) in West and North Kazakhstan respectively, were statistically significantly higher than the 2.7% (95% CI: 1.4%-5.1%) in the South. No difference in the seroprevalence was observed between urban and rural areas (Fig 2A).

Fig 1

Age-specific distributions of HBsAg and anti-HCV seroprevalence.

Table 1

Bivariate analysis for associations of socio-demographics characteristics with prevalence of HBsAg seropositivity.

Characteristics	Number of tested individuals	Unweighted prevalence of HBsAg % (95% CI)	Weighted prevalence of HBsAg % (95% CI)	p-value†
All participants	3,694	5.9 (5.2–6.7)	5.5 (3.6–8.4)	-
Age categorical				0.12
18–29	555	4.5 (2.9–6.6)	3.9 (2.0–7.6)
30–39	513	7.8 (5.6–10.5)	7.3 (4.2–12.4)
40–59	1,762	6.1 (5.0–7.3)	6.1 (3.9–9.3)
60–88	864	5.3 (3.9–7.0)	4.0 (2.0–7.7)
Gender				0.07
Females	2,827	5.5 (4.7–6.4)	5.1 (3.1–8.3)
Males	867	7.3 (5.6–9.2)	6.5 (4.7–8.9)
Ethnicity				0.08
Kazakh	2,482	6.3 (5.4–7.3)	5.9 (0.4–8.8)
Russian	767	4.6 (3.2–6.3)	2.8 (1.1–7.1)
Other ethnicities	417	5.5 (3.5–8.2)	5.4 (3.5–8.2)
Education level				0.75
None/school level	827	5.3 (3.9–7.1)	5.9 (2.7–12.4)
Vocational level	1,754	5.9 (4.9–7.1)	5.4 (3.8–7.6)
University level	1,104	6.2 (4.8–7.7)	5.1 (3.2–8.2)
Residence				0.35
Urban	2,106	5.9 (4.8–7.2)	4.0 (1.4–10.3)
Rural	1,588	5.9 (4.9–7.0)	6.3 (4.6–8.5)
Region				0.02
South	749	2.4 (1.4–3.8)	2.7 (1.4–5.1)
West	1,491	6.8 (5.6–8.2)	7.3 (6.1–8.6)
North	1,454	6.7 (5.5–8.1)	7.0 (3.7–13.0)

†Estimated by Chi-square test or Fisher’s exact test.

Number (percent) of participants missing answer for ethnicity– 28 (0.8%); missing answer for education– 9 (0.2%).

Fig 2

Regional and residential differences in the seroprevalence of HBsAg (a) and anti-HCV antibodies (b).

In Table 2, a weighted multivariable mixed effects logistic regression analysis adjusting for age and sex, showed that having a reported history of blood transfusion increased the odds of having a HBsAg positive result by 34% as compared to those not reporting any blood transfusion (p-value = 0.02). Those reporting to have tattoo or piercing had lower odds of having HBsAg when compared to those without (adjOR = 0.44, 95%CI: 0.27–0.72, p-value = 0.001).

Table 2

Risk factors for hepatitis B: Bivariate analysis and multivariable mixed effects logistic regression analysis adjusting for age and sex.

Variables	Number tested	Weighted prevalence of HBsAg % (95% CI)	p-value†	Adjusted OR‡ (95%CI)	p-value for adjusted OR
Family member having viral hepatitis			0.93		0.57
No	3,383	5.5 (3.6–8.3)		1.0
Yes	275	5.3 (2.3–11.9)		0.90 (0.63–1.29)
History of surgery			0.84		0.93
No	1,963	5.4 (3.5–8.2)		1.0
Yes	1,696	5.6 (3.3–9.4)		1.02 (0.64–1.62)
Having tattoo or piercing			0.29		0.001
No	3,299	5.7 (3.6–9.0)		1.0
Yes	352	3.2 (1.2–8.5)		0.44 (0.27–0.72)
Having hemodialysis			0.25		0.32
No	3,634	5.5 (3.6–8.4)		1.0
Yes	18	1.6 (0.1–16.4)		0.39 (0.06–2.46)
History of blood transfusion			0.34		0.02
No	3,154	5.3 (3.2–8.4)		1.0
Yes	506	6.8 (4.1–11.3)		1.34 (1.04–1.74)

†Chi-square test or Fisher’s exact test as appropriate.

‡Models were adjusted for age and sex.

In the final weighted multivariable mixed effects logistic regression analysis (Table 3) with HBsAg status as the outcome, three variables were found to be statistically significant: age, sex, and having tattoo or piercing. Those who were males (adjOR = 1.5; 95%CI: 1.31–1.72), in 30–39 age group, in 30–39 age group (adjOR = 1.98; 95%CI: 1.21–3.25) or 40–59 age group (adjOR = 1.64; 95%CI: 1.19–2.26), were more likely to be HBsAg-positive. However, those who had tattoo or piercing were less likely to have HBsAg positive result (adjOR = 0.45; 95%CI: 0.29–0.7). Also, in the Model 2, those reporting a history of blood transfusion were more likely to have HBsAg seropositivity with borderline significance (adjOR = 1.38; 95%CI: 0.97–1.95; p = 0.07).

Table 3

Final multivariable mixed effects logistic regression models for HbsAg seropositivity.

Variables	HBsAg seropositivity		HBsAg seropositivity		HBsAg seropositivity
	OR (95% CI)	p-value	OR (95% CI)	p-value	OR (95% CI)	p-value
	Model 1		Model 2		Model 3
Categorical age		0.03		0.03		0.03
18–29	Ref.		Ref.		Ref.
30–39	1.94 (1.20–3.14)		1.92 (1.20–3.08)		1.98 (1.21–3.25)
40–59	1.62 (1.09–2.41)		1.58 (1.12–2.24)		1.64 (1.19–2.26)
60–88	1.00 (0.47–2.11)		0.99 (0.51–1.91)		1.02 (0.54–1.92)
Sex		<0.001		<0.001		<0.001
Female	Ref.		Ref.		Ref.
Male	1.39 (1.19–1.62)		1.41 (1.21–1.64)		1.50 (1.31–1.72)
Ethnicity		0.21		0.23		0.26
Kazakh	Ref.		Ref.		Ref.
Russian	0.48 (0.16–1.42)		0.46 (0.16–1.32)		0.50 (0.16–1.53)
Other ethnicities	1.25 (0.77–2.05)		1.26 (0.74–2.15)		1.28 (0.76–2.14)
History of having surgery	-	-		0.92		0.99
No			Ref		Ref.
Yes			0.98 (0.60–1.59)		0.99 (0.62–1.61)
History of blood transfusion	-	-		0.07		0.11
No			Ref.		Ref.
Yes			1.38 (0.97–1.95)		1.39 (0.92–2.10)
Family member having viral hepatitis	-	-	-	-		0.71
No					Ref.
Yes					0.91 (0.56–1.48)
Having hemodialysis	-	-	-	-		0.18
No					Ref.
Yes					0.38 (0.09–1.59)
Having tattoo or piercing	-	-	-	-		<0.001
No					Ref.
Yes					0.45 (0.29–0.70)

Model 1 included age, sex and ethnicity. Model 2 = Model 1+ history of having surgery and history of blood transfusion. Model 3 = Model 2 + family member having viral hepatitis, history of hemodialysis and having tattoo or piercing.

Seroprevalence and risk factors for HCV

A total of 222 out of 3,697 participants, which accounted for weighted prevalence of 5.1% (95%CI: 3.5%-7.5%), were found to be seropositive for anti-HCV (Table 4). Anti-HCV seropositivity had a tendency to increase with older ages (Fig 1). The 3.1% prevalence of anti-HCV in South Kazakhstan (95%CI: 1.8%-5.3%) was lower than the prevalence in West and North Kazakhstan at 5.7% (95%CI: 3.2%-9.9%) and 7.5% (95%CI: 5.2%-10.7%), respectively, with a p-value = 0.07. No difference in the seroprevalence was observed between urban and rural areas (Fig 2B).

Table 4

Socio-demographics: Prevalence of anti-HCV seropositivity, bivariate analysis.

Characteristics	Number tested	Unweighted prevalence of HCV % (95% CI)	Weighted prevalence of anti-HCV % (95% CI)	p-value†
All participants	3,697	6.0 (5.3–6.8)	5.1 (3.5–7.5)	-
Age categorical				0.55
18–29	553	5.4 (3.7–7.6)	4.3 (1.1–14.9)
30–39	510	6.1 (4.2–8.5)	3.7 (1.6–8.4)
40–59	1,762	5.8 (4.7–7.0)	5.1 (3.8–6.7)
60–88	872	6.8 (5.2–8.6)	6.6 (4.0–10.8)
Gender				0.78
Females	2,827	5.5 (4.7–6.5)	5.2 (3.5–7.6)
Males	870	7.5 (5.8–9.4)	4.9 (2.9–8.3)
Ethnicity				0.52
Kazakh	2,480	6.9 (5.0–6.9)	4.9 (3.4–7.2)
Russian	771	5.8 (4.3–7.7)	4.9 (2.6–8.9)
Other ethnicities	418	6.9 (4.7–9.8)	6.3 (3.4–11.4)
Education level				0.49
None/school level	828	6.2 (4.6–8.0)	5.8 (4.2–8.1)
Vocational level	1,754	5.5 (4.5–6.7)	4.7 (2.9–7.7)
University level	1,106	6.6 (5.2–8.2)	5.1 (3.3–7.9)
Residence				0.49
Urban	2,102	6.0 (5.0–7.1)	5.6 (3.8–8.2)
Rural	1,595	6.0 (5.0–7.3)	4.2 (1.8–9.1)
Region				0.07
South	750	2.9 (1.8–4.4)	3.1 (1.8–5.3)
West	1,488	6.0 (4.8–7.3)	5.7 (3.2–9.9)
North	1,459	7.6 (6.3–9.1)	7.5 (5.2–10.7)

†Chi-square test or Fisher’s exact test as appropriate.

Number (percent) of participants missing answer for ethnicity– 28 (0.8%); missing answer for education– 9 (0.2%).

As shown in Table 5, a weighted multivariable mixed effects logistic regression analysis adjusting for age and sex showed an 114% increase in odds of having anti-HCV positive results for participants who reportedly had family members who were infected with viral hepatitis as compared to those who had not (p-value = 0.03). Having had a blood transfusion also increased the odds of having anti-HCV antibodies by 117% (p-value<0.001).

Table 5

Risk factors for anti-HCV antibodies: Bivariate analysis and multivariable logistic regression analysis adjusting for age and sex.

Variables	Number tested	Weighted prevalence of HCV % (95% CI)	p-value†	Adjusted OR‡ (95% CI)	p-value for adjusted OR
Injection drug use			0.85		0.74
No	3,639	5.1 (3.5–7.4)		1.0
Yes	22	5.9 (0.7–34.7)		1.49 (0.14–16.04)
Family member having viral hepatitis			<0.01		0.03
No	3,388	4.7 (3.2–6.9)		1.0
Yes	274	10.2 (5.4–18.4)		2.14 (1.09–4.21)
History of surgery			0.25		0.43
No	1,963	4.6 (2.8–7.4)		1.0
Yes	1,700	5.7 (3.9–8.4)		1.22 (0.75–1.98)
Having tattoo or piercing			0.22		0.17
No	3,301	4.8 (3.1–7.5)		1.0
Yes	354	7.8 (4.0–14.4)		1.73 (0.79–3.78)
Having hemodialysis			0.28		0.48
No	3,638	5.1 (3.5–7.5)		1.0
Yes	18	1.6 (0.1–16.9)		0.36 (0.20–6.30)
History of blood transfusion			<0.001		0.001
No	3,158	4.4 (2.9–6.8)		1.0
Yes	506	9.0 (5.7–14.0)		2.17 (1.40–3.35)

†Chi-square test or Fisher’s exact test as appropriate.

‡Models were adjusted for age and sex.

In the final weighted multivariable mixed effects logistic regression analysis (Model 6, Table 6), blood transfusion was statistically significantly associated with HCV seropositivity, while having family member with hepatitis showed borderline significance. Those who had a family member infected with viral hepatitis (adjOR = 2.09; 95%CI: 0.97–4.5), who had a history of blood transfusion (adjOR = 2.1; 95%CI: 1.37–3.21) were more likely to be anti-HCV positive.

Table 6

Final multivariable mixed-effects logistic regression models for anti-HCV seropositivity.

Variables	Anti-HCV seropositivity		Anti-HCV seropositivity		Anti-HCV seropositivity
	OR (95% CI)	p-value	OR (95% CI)	p-value	OR (95% CI)	p-value
	Model 4		Model 5		Model 6
Categorical age		0.70		0.88		0.92
18–29	Ref.		Ref.		Ref.
30–39	0.80 (0.15–4.14)		0.72 (0.13–4.06)		0.71 (0.13–4.00)
40–59	1.10 (0.60–2.02)		0.96 (0.50–1.82)		0.91 (0.49–1.70)
60–88	1.52 (0.69–3.32)		1.35 (0.55–3.32)		1.38 (0.54–3.53)
Gender		0.64		0.76		0.55
Female	Ref.		Ref.		Ref.
Male	1.11 (0.85–1.46)		1.05 (0.77–1.43)		1.13 (0.75–1.70)
Ethnicity		0.56		0.46		0.47
Kazakh	Ref.		Ref.		Ref.
Russian	0.85 (0.35–2.08)		0.82 (0.30–2.24)		0.80 (0.28–2.28)
Other ethnicities	1.39 (0.91–2.13)		1.50 (0.95–2.36)		1.48 (0.95–2.31)
History of blood transfusion		-		<0.001		0.001
No			Ref		Ref.
Yes			2.21 (1.60–3.05)		2.10 (1.37–3.21)
History of surgery	-	-		0.83		0.94
No			Ref.		Ref.
Yes			1.06 (0.64–1.75)		1.02 (0.65–1.60)
Injection drug use	-	-	-	-		0.99
No					Ref.
Yes					1.01 (0.05–21.27)
Family member having viral hepatitis	-	-	-	-		0.06
No					Ref.
Yes					2.09 (0.97–4.50)
Having tattoo or piercing	-	-	-	-		0.24
No					Ref.
Yes					1.70 (0.71–4.10)
Having hemodialysis	-	-	-	-		0.20
No					Ref.
Yes					0.23 (0.02–2.17)

Model 4 included age, sex and ethnicity. Model 5 = Model 4+ history of having surgery and history of blood transfusion. Model 6 = Model 5 + family member having viral hepatitis, history of hemodialysis and having tattoo or piercing.

Models differed in that age and sex were significantly associated only in the model with HBsAg, and history of previous blood transfusion only in the model with anti-HCV.

Discussion

We have investigated the seroprevalence and associated risk factors of HBsAg and anti-HCV antibodies in the three large regions of Kazakhstan utilizing randomized data. The prevalence of HBsAg and anti-HCV antibodies among the study population was found to be 5.5% and 5.1%, respectively, both much higher than the prevalence for the WHO European Region (0.9% for HBV and 1.1% for HCV infections). [20]

Previously, studies showed lower prevalence of HCV in Kazakhstan. [21, 22] A recent systematic review estimated a prevalence of anti-HCV antibodies at 0.7% for the general population of Kazakhstan; however the studies included in the review were largely sampling non-randomly among blood donors and were limited to single locations, potentially introducing important bias. [22] The meta-analyses conducted by Gower et al. throughout different countries in Central Asia estimated a 3.3% population had anti-HCV antibodies in Kazakhstan, [21] excluding studies in blood donors. Though their computed prevalence estimate for Kazakhstan was lower that the prevalence found in our study, the country was still found to have the second highest HCV seroprevalence in Central Asia. [21] In different studies, the prevalence of HBsAg seropositivity in Kazakhstan was found to be similar to other countries in the Central Asia region, falling into the range of high-intermediate level of endemicity. [23]

Numerous studies have established the effectiveness of vaccination in reducing HBV infection. [23, 24] In our study, the seroprevalence of HBsAg was low in the young age group, then sharply increased among 30–39 years old, and decreased in older ages. We can speculate that the low prevalence of HBsAg among the young age group might be attributed to the introduction of universal HBV vaccination in 1998; [14] the vaccination covered more than 97% of children born after 1995. However, perinatal transmission studies and early childhood HBV prevalence studies are needed to confirm the effectiveness of the vaccination campaign. The presence of the highest number of infections in the 30–39 years of age group suggests that HBV transmission happened in a recent past (10–30 years) [25] and might have been due to sexual, horizontal or vertical transmission, before the universal vaccination was introduced.

The incidence of HBV and HCV infections in Western countries has been declining since screening of donated blood for blood borne infections, safer injection practices and universal HBV vaccination in infants were introduced. [26] Currently, in those countries, horizontal transmission among adult at-risk populations, such as IVDUs and people with high-risk sexual contacts, has become the most common. In low and middle-income countries, there is growing evidence that health-related procedures are the main route of transmission of HBV and HCV. [26, 27] Inconsistent screening of blood donors and unsafe injection practices both by professionals and nonprofessionals are common means of transmission.

Surgical procedures are recognized as an important route of transmission for HBV infection worldwide. [28] Our findings could not find associations of a history of surgery with HBV nor with HCV infection. The introduction of compulsory vaccination of all medical workers and routine surveillance for HCV and HBV infections among most of them, especially those working in surgical departments, may have played a role in reducing the risk of transmission from medical workers to patients. [29] However, failure to comply with infection safety measures could contribute to iatrogenic transmission in the future. Thus, there is a need to conduct further studies and strengthen the hospital-associated infections surveillance system in Kazakhstan, as data is limited. [30]

A blood transfusion history was associated with increases in the anti-HCV seropositivity rate while it was a borderline significant with HBsAg positivity. In low and middle income countries, the transmission of viral hepatitis through blood transfusion remains a critical problem. [2] Fifteen years ago it was estimated that 31 out 142 developing countries did not screen donated blood for blood-borne infections, and additional 37 did not screen regularly. [27] In Kazakhstan, blood donors at high-risk for having HBV and HCV are screened through the use of a questionnaire before donation and serological testing. In 2009, health authorities mandated testing of all donated blood for anti-HCV antibodies, anti-HIV antibodies and HBsAg. Thus, to reduce risk of window period infection transmission, a four-month storage of plasma was also introduced in 2009, for which at the end of the four months the donor is tested again before the usage of donated plasma. [31] During the years 2012–2015, a second stage of testing, i.e. Polymerase Chain Reaction (PCR) for donated blood was added to increase the sensitivity and reduce the risk of transmission of infections. [32] Even though we did not collect data on dates of blood transfusion, we can speculate that infected participants who received donated blood may have had transfusions before the more rigorous blood bank screening programs were put in place. In any case, the high prevalence of anti-HCV antibodies in all age groups and their increase with age (Fig 1) suggests higher exposure to the infection in a recent (10–30 years) and distant past (30–50 years). [25]

We also found an association between having a family member with any viral hepatitis and the presence of anti-HCV antibodies. A systematic review conducted by Waure et al. indicates that household members are at risk of HCV infection if someone in that household is infected. [33] There are no definitive explanations for this association. However, some studies have suggested that transmission could occur through using the same razors, scissors or toothbrushes among family members. [34]

We found no differences in the prevalence of HBsAg and anti-HCV antibodies between urban and rural areas. The highest prevalence of both was observed in West and North Kazakhstan; this finding may be associated with regional inequities in healthcare, health financing and health outcomes, [5] given that the highest quality health services are provided in the South.

Strengths and limitations

This study has several strengths. The large sample size allowed for higher statistical power to measure prevalence and risk factors with greater precision. The survey was conducted in three large regions, remotely located from each other, increasing potential national representativeness of the findings. In addition, a randomized multistage cluster sampling method was utilized, which could increase generalizability of the findings. Finally, HBsAg and anti-HCV antibodies were determined using serological tests rather than self-reporting.

However, several limitations of the study must be considered. Independent risk factors were obtained using self-reported information, including having tattoo or piercing, which could be biased. Also, important potential risk factors, such as occupation (e.g. healthcare worker), sexual behaviors and more in-depth questions for other risk factors were not included in the survey. Additionally, anti-HCV antibodies can simply indicate past rather than current infection, and HCV-RNA should have been tested to determine the number of current HCV-infected individuals. Lastly, the study respondents from three regions may not completely represent the general population of Kazakhstan since sex (overrepresented by female participants) and age (the majority were in age group of 40–88 years old) distributions were not comparable to the national demographical statistics.

Conclusions

In conclusion, the study estimates the seroprevalence of HBsAg and anti-HCV antibodies in the three large regions of Kazakhstan, highlighting the high-intermediate and high levels of endemicity, respectively. We found that history of surgery was not associated with HBsAg, neither with anti-HCV seropositivity rates. Blood transfusion was associated with anti-HCV seropositivity, however, to investigate effectiveness of the introduced comprehensive preventive measures in health care settings, there is a need to conduct further epidemiological studies.

Flowchart of inclusion and exclusion of participants.

(PDF)

Click here for additional data file.

Global Moran’s I test for spatial autocorrelation of HBsAg and anti-HCV seropositivity by region.

(PDF)

Click here for additional data file.

Russian translated the WHO STEPS instrument.

(PDF)

Click here for additional data file.

The study dataset in excel format.

(XLS)

Click here for additional data file.

STROBE checklist.

(PDF)

Click here for additional data file.

18 Feb 2021

PONE-D-20-31835

Seroprevalence and risk factors for hepatitis B and hepatitis C in the general population of Kazakhstan

PLOS ONE

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2)  Please include additional information regarding the survey or questionnaire used in the study and ensure that you have provided sufficient details that others could replicate the analyses. For instance, if you developed a questionnaire as part of this study and it is not under a copyright more restrictive than CC-BY, please include a copy, in both the original language and English, as Supporting Information, or include a citation if it has been published previously.

3) In the Methods, please discuss whether and how the questionnaire was validated and/or pre-tested. If these did not occur, please provide the rationale for not doing so.

4) In the discussions about your research, please take care to avoid statements implying causality from correlational research, e.g. “iatrogenic factors seem to continue to play a significant role as a route of transmission”. A cross-sectional study can be used to explore associations and not causality due to a number of limitations such a failure to determine temporal precedence.

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7) As part of your revision, please complete and submit a copy of the STROBE checklist, a document that aims to improve reporting and reproducibility of observational studies for purposes of post-publication data analysis and reproducibility: (http://www.strobe-statement.org). Please include your completed checklist as a Supporting Information file. Note that if your paper is accepted for publication, this checklist will be published as part of your article.

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Reviewer #1: Partly

**********

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

Reviewer #1: No

**********

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Reviewer #1: No

**********

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5. 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: Overall this is an interesting paper that describes an important disease globally and in Kazakhstan. The paper estimated hepatitis B and hepatitis C for a representative sample of the Kazakhstan population for three large oblasts (provinces). The goal was to relate seroprevalence estimates to several demographic or sociological factors. While important work, there are several major methodological issues that need to be addressed before consideration for publication.

ABSTRACT: there are abbreviations for the viruses used in the abstract that need to be spelled out like the authors did in the first paragraph of the introduction.

INTRODUCTION: I'm concerned about calling this a national study when only three oblasts were used to represent a landscape as largest as Kazakhstan. Having been there and worked there for several years, I appreciate that these three areas represent a large proportion of the population. However, I do not think the authors have done enough to describe the distribution of people or describe the proportion of people outside of these three areas and how they may or may not differ from those inside of the study area. I'm not sure it is fair to call this national as designed or at least described.

METHODS: there are several issues that must be addressed prior to consideration for publication.

First, as a serological surveillance study I would expect to read a much more clear methodology of how samples were collected, processed, and the serological tests performed. Overall, the methods section lacks appropriate citations and detailed enough methodology to repeat this work. Without expanding on both citations in detail this work should not be considered reproducible.

In the discussion of the data variables for this study, the authors provide very little information on how urban and rural were defined. These terms are specifically defined in a variety of studies using different cutoffs for population density. Likewise, across these three regions of Kazakhstan, there is a growing periurban environment where rural migrants are moving closer to the city and the city suburbs are expanding into the rural area. This study at a minimum needs to define urban and rural.

The larger issue with this study is the use of backward stepwise variable selection for the regression modeling. It has been well known for many years now that stepwise selection techniques are losing favor and there is a large body of statistical literature describing why. It has become a best practice to use a multi-model approach, for example, looking at all possible variable combinations with something like a dredge approach. Those models would then be evaluated with something like an AIC. Equally concerning is the use of the spatial location, at least defined by region, as a covariate without first testing for spatial autocorrelation. Each of these three regions was selected because they represent a large proportion of the human population in Kazakhstan. Human populations by their nature are typically clustered in space meaning their covariates are likely autocorrelated. The authors here did nothing to test for spatial autocorrelation either in the input data or in the residuals of the models. Without such tests is difficult to assess whether or not the data for this study meet the assumptions of independence for the regression model selected. Likewise, it has become more usual to see a mixed model approach where a random effect would be used for region. These issues should be addressed and should not simply be addressed by adding one or two sentences to the methodology, but rather performing additional model evaluation, selection, and spatial autocorrelation testing.

Building on concerns about the regression model, the authors also used the T-test for the variables without first testing for normality. It may be more likely that a nonparametric test touches the Mann-Whitney U test may be more appropriate to analyze the same question.

Later in the results the authors state there were some adjustments for the models and those were not provided.

DISCUSSION: the discussion of the paper is well written. However the discussion highlights the results of the study, which do not address the concerns raised above about the methodology performed. It is important to ensure that the statistical analysis was appropriate before pacing and discussion that supports those results.

I think this is an interesting paper and addresses a very serious disease concern. The methodological comments I raise here can be addressed and should strengthen the paper.

**********

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Reviewer #1: No

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2 May 2021

Comments and Suggestions for Authors

1) 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.Indded, there are several issues that must be addressed prior to consideration for publication, first of all, the notion of "Nationwide" is elusive in this case, methotological aspects may be improved and therefore the discussion section.

Response:

We thank the Editor for this comment. We agree that the study respondents from three regions may not completely represent the general population of Kazakhstan since sex (overrepresented by female participants) and age (the majority were in age group of 40-88 years old) distributions were not comparable to the national demographical statistics. Thus, we modified accordingly the text and the title of the manuscript. We also included more details to the methodology, recalculated estimates using a different statistical approach and improved the discussion section based on the changes in the results.

2) Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming.

Response: The manuscript was adjusted according to PLOS One style and formatting requirements, including file naming.

3) Please include additional information regarding the survey or questionnaire used in the study and ensure that you have provided sufficient details that others could replicate the analyses. For instance, if you developed a questionnaire as part of this study and it is not under a copyright more restrictive than CC-BY, please include a copy, in both the original language and English, as Supporting Information, or include a citation if it has been published previously.

Response: We thank the Editor for the comment. We used the standardized WHO STEPs survey instrument which extensively utilized for the risk factor surveillance worldwide (reference was added). This instrument was translated and then back-translated. The full information about the questionnaire was added in lines 95-103 in the methods section. We also attached a Russian translated version of the questionnaire to the supplementary materials.

4) In the Methods, please discuss whether and how the questionnaire was validated and/or pre-tested. If these did not occur, please provide the rationale for not doing so.

Response: We acknowledge that information about the questionnaire was not complete. Thus, we added information about the questionnaire in lines 95-103. Please see changes in the main text.

5) In the discussions about your research, please take care to avoid statements implying causality from correlational research, e.g. “iatrogenic factors seem to continue to play a significant role as a route of transmission”. A cross-sectional study can be used to explore associations and not causality due to a number of limitations such a failure to determine temporal precedence.

Response: We appreciate the comment and agree with the suggestion. We rewrote the conclusions. Please see changes in the text.

6) In statistical methods, please clarify whether you corrected for multiple comparisons.

Response: We did not perform multiple pairwise testing among comparison groups. In calculating odds ratios for a categorical variable with three or more groups, we calculated a global p-value for the categorical variable. Thus, there was no need to perform a correction for multiple pairwise testing.

7) In your statistical analyses, please state whether you accounted for survey weights and clustering by region.

Response: We thank the Editor for the valuable suggestion. We recalculated estimates based on the complexity of the study sampling approach. Also, we included the following sentence in the Methods part: “Given that we used two-stage cluster sampling, all descriptive, bivariate and multivariable statistics were weighted using inverse probability weighting to adjust for sample design and non-response rate.” And used multivariable mixed effects logistic regression analysis to account for clustering by region in the study. More details could be found in the statistical analysis part.

8) As part of your revision, please complete and submit a copy of the STROBE checklist, a document that aims to improve reporting and reproducibility of observational studies for purposes of post-publication data analysis and reproducibility: (http://www.strobe-statement.org). Please include your completed checklist as a Supporting Information file. Note that if your paper is accepted for publication, this checklist will be published as part of your article.

Response: The STROBE checklist was completed and attached as Supporting information.

9) We note that the grant information you provided in the ‘Funding Information’ and ‘Financial Disclosure’ sections do not match.

When you resubmit, please ensure that you provide the correct grant numbers for the awards you received for your study in the ‘Funding Information’ section.

Response: We made corrections in the system so the grant information in the “Funding Information” and “Financial Disclosure” sections match.

10) We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions.

In your revised cover letter, please address the following prompts:

a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially identifying or sensitive patient information) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent.

b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings as either Supporting Information files or to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. Please see http://www.bmj.com/content/340/bmj.c181.long for guidelines on how to de-identify and prepare clinical data for publication. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories.

We will update your Data Availability statement on your behalf to reflect the information you provide.

Response: The anonymized dataset was provided as Supplementary Information.

Reviewer #1: Overall this is an interesting paper that describes an important disease globally and in Kazakhstan. The paper estimated hepatitis B and hepatitis C for a representative sample of the Kazakhstan population for three large oblasts (provinces). The goal was to relate seroprevalence estimates to several demographic or sociological factors. While important work, there are several major methodological issues that need to be addressed before consideration for publication.

11) ABSTRACT: there are abbreviations for the viruses used in the abstract that need to be spelled out like the authors did in the first paragraph of the introduction.

Response: The abbreviations were spelled out.

12) INTRODUCTION: I'm concerned about calling this a national study when only three oblasts were used to represent a landscape as largest as Kazakhstan. Having been there and worked there for several years, I appreciate that these three areas represent a large proportion of the population. However, I do not think the authors have done enough to describe the distribution of people or describe the proportion of people outside of these three areas and how they may or may not differ from those inside of the study area. I'm not sure it is fair to call this national as designed or at least described.

Response: We thank the Reviewer for this comment. We agree that the study respondents from three regions may not completely represent the general population of Kazakhstan since sex (overrepresented by female participants) and age (the majority were in age group of 40-88 years old) distributions were not comparable to the national demographical statistics. Thus, we modified accordingly the text and the title of the manuscript. This limitation was also mentioned in the discussion part.

13) METHODS: there are several issues that must be addressed prior to consideration for publication. First, as a serological surveillance study I would expect to read a much more clear methodology of how samples were collected, processed, and the serological tests performed. Overall, the methods section lacks appropriate citations and detailed enough methodology to repeat this work. Without expanding on both citations in detail this work should not be considered reproducible.

Response: We thank the reviewer for the comment. We added more details in the methodology on sample collection process and serological testing. Please refer to changes in the study design subsection.

14) In the discussion of the data variables for this study, the authors provide very little information on how urban and rural were defined. These terms are specifically defined in a variety of studies using different cutoffs for population density. Likewise, across these three regions of Kazakhstan, there is a growing periurban environment where rural migrants are moving closer to the city and the city suburbs are expanding into the rural area. This study at a minimum needs to define urban and rural.

Response: We thank the Reviewer for this comment. The threshold for diving into urban and rural areas was 50,000 people in a settlement according to “Law of Administrative-Territorial Structure of Republic of Kazakhstan” (https://online.zakon.kz/m/document/?doc_id=1007265). So, the following definition was added in the methods section: “Any settlement with more than 50,000 people was considered an urban area, while any settlement with at least 50 residents and not exceeding 50,000 people was defined as rural area.”

15) The larger issue with this study is the use of backward stepwise variable selection for the regression modeling. It has been well known for many years now that stepwise selection techniques are losing favor and there is a large body of statistical literature describing why. It has become a best practice to use a multi-model approach, for example, looking at all possible variable combinations with something like a dredge approach. Those models would then be evaluated with something like an AIC. Equally concerning is the use of the spatial location, at least defined by region, as a covariate without first testing for spatial autocorrelation. Each of these three regions was selected because they represent a large proportion of the human population in Kazakhstan. Human populations by their nature are typically clustered in space meaning their covariates are likely autocorrelated. The authors here did nothing to test for spatial autocorrelation either in the input data or in the residuals of the models. Without such tests is difficult to assess whether or not the data for this study meet the assumptions of independence for the regression model selected. Likewise, it has become more usual to see a mixed model approach where a random effect would be used for region. These issues should be addressed and should not simply be addressed by adding one or two sentences to the methodology, but rather performing additional model evaluation, selection, and spatial autocorrelation testing.

Response: We highly appreciate thoughtful comments provided by the Reviewer. We tested for spatial autocorrelation using the Moran’s I test and found dependence of outcomes. Thus, we decided to apply logistic mixed effects regression in statistical analysis. Accordingly, changes were made in the statistical analysis subsection in the methods section. Also, we included the Moran’s I test results in the Supplementary Materials section.

Regression models were built through three stages by including only demographic variables, then additionally adding two risk factors (history of surgery and blood transfusion), and later all other risk factors. This way a reader could compare the models and observe interrelationships of covariates in the models. We felt that building a model based only statistical significance or higher predictive power would lead to not epidemiologically interesting model. That is why, we decided to include epidemiologically important exposure variables (risk factors) despite their statistical non-significance.

16) Building on concerns about the regression model, the authors also used the T-test for the variables without first testing for normality. It may be more likely that a nonparametric test touches the Mann-Whitney U test may be more appropriate to analyze the same question.

Response: We appreciate the comment. Yes, we checked for normality of continuous variables before performing the T-test. Based on the shape distribution of a continuous variable or sufficiently large sample sizes in comparison groups, we selected either the T-test or the Mann-Whitney U test. See changes in the statistical analysis subsection.

17) Later in the results the authors state there were some adjustments for the models and those were not provided.

Response: We added footnotes of description of included variables in the models under each table which presented results from multivariable regression analysis.

18) DISCUSSION: the discussion of the paper is well written. However the discussion highlights the results of the study, which do not address the concerns raised above about the methodology performed. It is important to ensure that the statistical analysis was appropriate before pacing and discussion that supports those results.

Response: After using weighted logistic mixed effects regression analysis, some findings did change. Based on changes in the results, we modified text in the discussion part. Specifically, a history of surgery was not anymore statistically significantly associated with HBsAg seropositivity. Please see the changes in lines 299-314.

19) I think this is an interesting paper and addresses a very serious disease concern. The methodological comments I raise here can be addressed and should strengthen the paper.

Response: We thank the Reviewer for the valuable comments in improving and strengthening the manuscript. Hope the Reviewer will be satisfied with the provided responses and corresponding changes in the text.

20) While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Response: We updated the figures, so they met the PLOS requirements.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

26 Nov 2021

Seroprevalence and risk factors for hepatitis B and hepatitis C in three large regions of Kazakhstan.

PONE-D-20-31835R1

Dear Dr. Issanov,

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.

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Academic Editor

PLOS ONE

Additional Editor Comments (optional):

The answers and improvment after the first round of review were convincing and the paper was improved to reach the desired quality to be published in PlosOne.

Reviewers' comments:

7 Dec 2021

PONE-D-20-31835R1

Seroprevalence and risk factors for hepatitis B and hepatitis C in three large regions of Kazakhstan.

Dear Dr. Issanov:

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.

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