Materials and methods
Study design
This cross-sectional study was carried out at the National Centre of Cervical and Breast Cancer Screening and Training of the Bangabandhu Sheikh Mujib Medical University (BSMMU) from July 2021 to June 2022. Ethical clearance for this research was obtained from the Institutional Review Board of BSMMU (IRB no. BSMMU/2021/474, 12.04.21).
Study areas and selection of women
A multistage sampling method was used to select the study areas. Initially, eight districts were selected by simple random sampling from eight administrative divisions of Bangladesh. The residents within a 5-kilometer radius of the district hospitals were considered the urban population. Women residing within the sub-districts were considered the rural population. All eight district hospital CC screening centers were purposively selected to recruit urban population. Then, one sub-district hospital screening center from each of the eight districts was selected by simple random sampling to recruit rural population. Figure 1 shows the geographical locations of the study areas in eight divisions of Bangladesh. Ever-married women aged 30–49 years attending selected screening centers were recruited purposively for data collection after counselling (N = 3,856). Pregnant women and those with a previous history of treatment for cervical disease were excluded.
Cervical sample collection
HPV DNA specimens were collected prior to the VIA test using a cervical sampler by trained nurses/doctors and suspended in a vial of preservative (Cobas PCR collection media) for transport to the laboratory. Specimens were transported as soon as possible to BSMMU or stored in a freezer (4°C) at hospitals or at room temperature (<30°C) until transfer.
HPV DNA detection and genotyping
HPV DNA detection and genotyping was performed using the Cobas 4800 HPV test (Roche Diagnostics, GmbH, and Mannheim, Germany), a qualitative testing device for the detection of HPV DNA. This test amplifies target DNA in cervical epithelial cells by PCR and nucleic acid hybridization to detect 14 HR-HPV types. This assay allows specific identification of HPV types 16 and 18 and pooled detection of HPV types 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, and 68.12 The human beta-globulin-oriented fluorescent probe provided quality control for the whole reaction.
Data analysis plan
The data were assessed for completeness, accuracy and consistency before analysis. Continuous variables were summarized using means and standard deviations. Categorical variables were summarized using frequency distributions. Associations between categorical variables were assessed by Chi-square test or Fisher’s exact test. A P value of <0.05 was considered to indicate a statistically significant difference. The data analysis was performed using SPSS version 23.0.
Results
Socio-demographic and reproductive characteristics
Among the 3,856 women screened, 1,748 (45.3%) were from urban areas, and 2,108 (54.7%) were from rural areas. The mean age at marriage was 15.8 (±2.3) years, and the mean age at the 1st delivery was 17.9 (±2.8) years for the total population. A significant variation in monthly family income was observed among urban and rural participants. A significantly higher number of women (P value = 0.007) and husbands (P value = 0.001) in rural areas were married more than once compared to those in urban areas (Table 1).
Table 1Distribution of the study population by socio-demographic characteristics (n = 3,856)
| Characteristics | Rural | Urban | P valuea |
|---|
| Age of Women | No. (%) | No. (%) | <0.001 |
| 30–34 years | 561 (26.6) | 486 (27.8) | |
| 35–39 years | 782 (37.1) | 542 (31.0) | |
| 40–44 years | 432 (20.5) | 441 (25.2) | |
| 45–49 years | 333 (15.8) | 279 (16.0) | |
| Education of women | | | |
| Not educated | 881 (41.8) | 799 (45.7) | 0.141 |
| Up Primary | 890 (42.2) | 696 (39.8) | |
| SSC | 198 (9.4) | 140 (8.0) | |
| HSC | 120 (5.7) | 96 (5.5) | |
| Graduate & above | 19 (0.9) | 17 (1.0) | |
| Occupation of the Women | | | |
| Housewife | 2,101 (99.7) | 1,742 (99.7) | 0.952 |
| Service Holder | 7 (0.3) | 6 (0.3) | |
| Occupation of the Husband | | | |
| Farming | 1,417 (67.2) | 1,107 (63.3) | 0.041 |
| Service Holder | 170 (8.1) | 180 (10.3) | |
| Business | 314 (14.9) | 295 (16.9) | |
| Living abroad | 114 (5.4) | 74 (4.2) | |
| Driver | 44 (2.1) | 42 (2.4) | |
| Others | 21 (1.0) | 25 (1.4) | |
| Not alive | 28 (1.3) | 25 (1.4) | |
| Religion of the women | | | |
| Muslim | 1,936 (91.8) | 1,632 (93.4) | 0.158 |
| Hindu | 169 (8.0) | 116 (6.6) | |
| Buddhist | 3 (0.1) | 0 (0.0) | |
| Monthly family income | | | |
| Up to 5,000 | 1,036 (49.1) | 756 (43.2) | 0.003 |
| Taka 5,001–10,000 | 750 (35.6) | 710 (40.6) | |
| Taka 10,001–20,000 | 172 (8.2) | 135 (7.7) | |
| Taka 20,001–50,000 | 147 (7.0) | 144 (8.2) | |
| Taka 50,001 and above | 3 (0.1) | 3 (0.2) | |
| Number of Marriages of Women | | | |
| One | 2,085 (98.9) | 1,742 (99.7) | 0.007 |
| More than one | 23 (1.1) | 6 (0.3) | |
| Number of Marriages of Husband | | | |
| One | 2,090 (99.1) | 1,746 (99.9) | 0.001 |
| More than one | 18 (0.9) | 2 (0.1) | |
HR-HPV genotyping among women
Among the 3,856 asymptomatic women tested for HR-HPV, 138 (3.6%) women were HR-HPV positive. When considering single infections, among the 138 HR-HPV positive women, HPV 16 (49, 35.5%) was the most prevalent genotype, followed by HPV 18 (12, 8.7%). Another 10 (7.2%) women had HPV 16 infection as co-infection with HPV 18 or ‘Other HR-HPV’. Other HR-HPV infections (65, 47.1%) were also quite common (Fig. 2).
Distribution of HR-HPV positivity and genotypes among different divisions
Table 2 and Figure 3 show the division-wise distribution of overall HR-HPV infection. Almost an equal number of women were from urban and rural areas in different districts. The highest percentage of women with HR-HPV infection was in the Sylhet division (6.4%), and the lowest was in the Rajshahi division (1.7%). The HR-HPV infection rate was also high in the Barishal (5.0%) and Chittagong (4.6%) divisions. This study showed significant regional variation in overall HR-HPV prevalence among the divisions (P < 0.001).
Table 2Distribution of HR-HPV DNA Results by Division (n = 3,856)
| Divisions | Districts | Sub-districts | N (%) | HPV DNA
| P value |
|---|
| Negative (%) | Positive (%) |
|---|
| Dhaka | Narshingdi | Monohardi | 516 (13.4) | 496 (96.1%) | 20 (3.9) | <0.001a |
| Mymensingh | Mymensingh | Bhaluka | 395 (10.2) | 384 (92.7) | 11 (2.8) | |
| Rangpur | Lalmonirhat | Kaliganj | 499 (12.9) | 488 (97.8) | 11 (2.2) | |
| Chittagong | Cumilla | Titas | 501 (13.0) | 478 (95.4) | 23 (4.6) | |
| Barishal | Jhalokathi | Rajapur | 400 (10.4) | 380 (95.0) | 20 (5.0) | |
| Rajshahi | Sirajganj | Kazipur | 521 (13.5) | 512 (98.3) | 9 (1.7) | |
| Khulna | Chuadanga | Alamdanga | 570 (14.8) | 555 (97.4) | 15 (2.6) | |
| Sylhet | Maulvibazar | Sreemangal | 454 (11.8) | 425 (93.6) | 29 (6.4) | |
| | Total | 3,856 (100.0) | 3,718 (96.4) | 138 (3.6) | |
Figure 4 shows the division-wise distribution of overall HR-HPV infection in both urban and rural areas. Among women who had undergone HR-HPV DNA testing, 7.1% of women in rural Sylhet had the highest incidence of HR-HPV infection. In urban areas, women in the Chittagong (5.9%) division had the highest incidence of HR-HPV infection, followed by those in the Barishal (5.5%) and Sylhet (5.3%) divisions. Overall, no significant difference in HR-HPV infection distribution was found between urban and rural women (P = 0.9).
However, when considering urban and rural areas within each division separately, a significant difference in HR-HPV infection (P = 0.007) was found among women in the Mymensingh district (Table 3).
Table 3Distribution of HR-HPV infection in urban and rural areas of different divisions (n = 3,856)
| Name of Division | HR-HPV
| Total | P value |
|---|
| Positive N (%) | Negative N (%) |
|---|
| Dhaka | Urban | 6 (3.0) | 195 (97.0) | 201 | 0.402 |
| Rural | 14 (4.4) | 301 (95.6) | 315 | |
| Total | 20 (3.9) | 496 (96.1) | 516 | |
| Mymensingh | Urban | 10 (5.0) | 190 (95.0) | 200 | 0.007 |
| Rural | 1 (0.5) | 194 (99.5) | 195 | |
| Total | 11 (2.8) | 384 (97.2) | 395 | |
| Rangpur | Urban | 2 (1.0) | 198 (99.0) | 200 | 0.213a |
| Rural | 9 (3.0) | 290 (97.0) | 299 | |
| Total | 11 (2.2) | 488 (97.8) | 499 | |
| Chittagong | Urban | 12 (5.9) | 193 (94.1) | 205 | 0.261 |
| Rural | 11 (3.7) | 285 (96.3) | 296 | |
| Total | 23 (4.6) | 478 (95.4) | 501 | |
| Barishal | Urban | 11 (5.5) | 189 (94.5) | 200 | 0.646 |
| Rural | 9 (4.5) | 191 (95.5) | 200 | |
| Total | 20 (5.0) | 380 (95.0) | 400 | |
| Rajshahi | Urban | 5 (2.5) | 194 (97.5) | 199 | 0.313a |
| Rural | 4 (1.2) | 318 (98.8) | 322 | |
| Total | 9 (1.7) | 512 (98.3) | 521 | |
| Khulna | Urban | 9 (2.4) | 363 (97.6) | 372 | 0.664 |
| Rural | 6 (3.0) | 192 (97.0) | 198 | |
| Total | 15 (2.6) | 555 (97.4) | 570 | |
| Sylhet | Urban | 9 (5.3) | 162 (94.7) | 171 | 0.446 |
| Rural | 20 (7.1) | 263 (92.9) | 283 | |
| Total | 29 (6.4) | 425 (93.6) | 454 | |
| Total | Urban | 64 (3.7) | 1,684 (96.3) | 1,748 | 0.802 |
| Rural | 74 (3.5) | 2,034 (96.5) | 2,108 | |
| Total | 138 (3.6) | 3,718 (96.4) | 3,856 | |
Table 4 shows the division-wise distribution of HR-HPV genotypes. Among the 138 women positive for HR-HPV DNA test, the prevalence of HPV16 infection was highest in Sylhet division (2.6%), followed by the Barishal (1.8%) and Dhaka (1.7%) divisions. The prevalence of other HR-HPV infections was highest in Sylhet (13, 2.9%), followed by the Chittagong division (14, 2.8%).
Table 4Distribution of HR-HPV genotypes among 8 divisions
| Name of Divisions | Negative N (%) | HPV 16 N (%) | HPV 18 N (%) | Other HR-HPV N (%) | HPV 16/18 and Other HR-HPV N (%) | HPV 16 and Other HR-HPV N (%) | HPV 18 and Other HR-HPV N (%) | Total |
|---|
| Dhaka | 496 (96.1) | 9 (1.7) | – | 10 (1.9) | – | – | 1 (0.2) | 516 |
| Mymensingh | 384 (97.2) | 4 (1.0) | – | 7 (1.8) | – | – | – | 395 |
| Rangpur | 488 (97.8) | 4 (0.8) | 2 (0.4) | 5 (1.0) | – | – | – | 499 |
| Chittagong | 478 (95.4) | 3 (0.6) | 3 (0.6) | 14 (2.8) | 1 (0.2) | 2 (0.4) | – | 501 |
| Barishal | 380 (95.0) | 7 (1.8) | 2 (0.5) | 7 (1.8) | 1 (0.2) | 2 (0.5) | 1 (0.2) | 400 |
| Rajshahi | 512 (98.3) | 2 (0.4) | 1 (0.2) | 4 (0.8) | 2 (0.4) | – | – | 521 |
| Khulna | 555 (97.4) | 8 (1.4) | 2 (0.4) | 5 (0.9) | – | – | – | 570 |
| Sylhet | 425 (93.6) | 12 (2.6) | 2 (0.4) | 13 (2.9) | 1 (0.2) | 1 (0.2) | – | 454 |
| Total | 3,718 (96.4) | 49 (1.3) | 12 (0.3) | 65 (1.7) | 5 (0.1) | 5 (0.1) | 2 (0.1) | 3,856 |
Association of viral infections with risk factors
Figure 5 shows that the proportion of patients with HR-HPV infection was higher among the 35–39 years age group in comparison to other age groups, and this gradually decreased with age in both urban and rural areas. In rural areas, there was a continuous 2nd rise of HR-HPV infection from 40 years onwards.
Table 5 shows that age group, education level, occupation, monthly family income, parity, age of marriage, and age of the first delivery did not show significant effect on HR-HPV infection among women.
Table 5Association of different socioeconomic and reproductive factors with HR-HPV prevalence (n = 3,856)
| HR-HPV
| Total | P value |
|---|
| Negative (n = 3,718) | Positive (n = 138) |
|---|
| Age of Woman (years) | 30–34 | 1,015 (27.3) | 32 (23.2) | 1,047 (27.2) | 0.59a |
| 35–39 | 1,272 (34.2) | 52 (37.7) | 1,324 (34.3) | |
| 40–44 | 844 (22.7) | 29 (21.0) | 873 (22.6) | |
| 45–49 | 587 (15.8) | 25 (18.1) | 612 (15.9) | |
| Residence | Urban | 1,684 (45.3) | 64 (46.4) | 1,748 (45.3) | 0.802a |
| Rural | 2,034 (54.7) | 74 (53.6) | 2,108 (54.7) | |
| Education | No schooling | 1,622 (43.6) | 58 (42.0) | 1,680 (43.6) | 0.895a |
| Up Primary | 1,524 (41.0) | 62 (44.9) | 1,586 (41.1) | |
| SSC | 328 (8.8) | 10 (7.2) | 338 (8.8) | |
| HSC | 209 (5.6) | 7 (5.1) | 216 (5.6) | |
| Graduate & above | 35 (0.9) | 1 (0.7) | 36 (0.9) | |
| Occupation | Housewife | 3,705 (99.7) | 138 (100.0) | 3,843 (99.7) | >0.99a |
| Service Holder | 13 (0.3) | 0 (0.0) | 13 (0.3) | |
| Monthly family income (Taka) | Up 5,000 | 1,737 (46.7) | 55 (39.9) | 1,792 (46.5) | 0.389a |
| 5,001–10,000 | 1,399 (37.6) | 61 (44.2) | 1,460 (37.9) | |
| 10,001–20,000 | 298 (8.0) | 9 (6.5) | 307 (8.0) | |
| 20,001–50,000 | 278 (7.5) | 13 (9.4) | 291 (7.5) | |
| 50,001 and above | 6 (0.2) | 0 (0.0) | 6 (0.2) | |
| Parity | Nulliparous | 71 (1.9) | 4 (2.9) | 75 (1.9%) | 0.858a |
| Primipara | 551 (14.8) | 20 (14.5) | 571 (14.8%) | |
| Multi para | 2,795 (75.2) | 102 (73.9) | 2,897 (75.1) | |
| Grand multipara | 301 (8.1) | 12 (8.7) | 313 (8.1) | |
| Age of marriage | <18 years | 2,774 (74.6) | 109 (79.0) | 2,883 (74.8) | 0.245a |
| 18 years and above | 944 (25.4) | 29 (21.0) | 973 (25.2) | |
| Age of first delivery | Less than <18 years | 1,648 (44.3) | 71 (51.4) | 1,719 (44.6) | 0.098a |
| 18 years and above | 2,070 (55.7) | (48.6) | 2,137 (0.4) | |
Discussion
This cross-sectional study demonstrated the prevalence and distribution of HR-HPV genotypes among urban and rural Bangladeshi populations in selected eight districts of eight divisions. The overall HR-HPV infection rate (3.6%) among women aged 30–49 years was relatively low, and a similar finding (4.2%) was observed in a population-based study in the Dhaka division.13 The HR-HPV prevalence in Punjab (1.5%) and Karachi (0. 7%) of Pakistan showed an even lower prevalence.14,15 Suburban areas of Thailand (5.6%), Vietnam (9.5%), North India (8.2%), Andhra Pradesh of India (10.3%), Southern India (12.5%), and China (12.1%) had relatively higher prevalence of HR-HPV.16–21 The prevalence of HR-HPV in Kolkata, India (5.8%) was comparatively lower than in other parts of India and close to the prevalence observed in the present research.22 This may be related to the geographical, cultural and behavioral similarities between Kolkata and Bangladesh. Therefore, the prevalence of HR-HPV infection may vary from country to country, and in the majority of Asian countries, including Bangladesh, the HR-HPV prevalence is relatively lower than that in Western countries (13.7%–28.3%).23–25
Even though Bangladesh is a small country, significant regional variation of HR-HPV prevalence was observed among different divisions (P < 0.001). Sylhet (6.4%), Barishal (5.0%), and Chittagong (4.6%) divisions had higher prevalence of HR-HPV and Rajshahi (1.7%) had the lowest infection rate. Sylhet, Barishal, and Chittagong divisions need more attention during the formulation of larger population-based implementation research. Regional variation of HR-HPV prevalence within the country was observed in Thailand between Lampang (9.1%) and Songkla (3.9%),26 in India between North India (8.2%) and Andhra Pradesh (10.3%),18,19 in China between Xinjiang (9.7%),27 Han (11.5%) and Mongolia (32.6%).28
In this study, HPV 16 (35.5%) was the most prevalent single infection among HR-HPV positive cases, followed by HPV 18 (8.7%). Another study in Bangladesh revealed a similar prevalence of HPV 16 (28.7%).13 In Vietnam, the prevalence of HPV 16 (31.6%) and HPV 18 (8. 2%) was similar to that in Bangladesh.17 In Pakistan, HPV 16 (18%) and HPV 18 (6%) were less prevalent.29 In a Chinese population, HPV 16 was the major genotype observed.30 Therefore, the prevalence of HPV 16 and HPV 18 varies in different geographical regions. HPV genotyping is presently being mentioned for better risk assessment, and currently, only types 16 and 18 are commonly described for direct clinical management.31 The prevalence of HPV 16 infection was high in Sylhet (2.6%), Barishal (1.8%) and Dhaka (1.7%) divisions, and these divisions need particular attention during implementation policy.
Among the 138 HR-HPV positive cases, other HR-HPV infection (65, 1.7%) was more prevalent than HPV 16 infection (49, 1.3%). This indicates the necessity of a larger population-based longitudinal study to determine the fate of this high proportion of ‘other HR-HPV types’.
The major strengths of this study lie in the inclusion of samples from all divisions of the country, the use of a well-validated HPV test, and the collection of samples from both urban and rural areas. However, no significant variation in HR-HPV prevalence between rural and urban women was found, except in Mymensingh. Nahar et al. also found no significant variation between rural and urban women in the Dhaka division,13 indicating the necessity of equal attention to both rural and urban populations during the implementation of the CC screening program. This study included women aged 30 to 49 years only; the sample size was relatively small, and these were important limitations of this study.
The proportion of HR-HPV infection was highest among the 35–39 years age group, with a second rise after 40–44 years onwards in rural areas. Studies from CostaRica and Colombia also revealed a second peak,32–34 which may be a cohort effect, due to exposure of older women to HPV or reactivation of latent HPV infection for women infected with human immunodeficiency virus. However, the prevalence of human immunodeficiency virus infection is very low in Bangladesh,35 and further research is necessary to explore the cause of the second rise in the older population of rural women, including factors related to immune suppression and other unknown carcinogenic potential. The second increase in HR-HPV infection indicates the usefulness of screening among older women. A population-based survey identified that in the rural population of Bangladesh, the prevalence of HR-HPV infection was 5.0% among the 45–64 years age group.13 Other studies in Bangladesh reported that 19.23% of HR-HPV positive women were between 45–60 years of age,36 and 26.7% of HR-HPV positive women were between 40–70 years of age.37 It was also revealed that among CC patients, the highest number were older than 50 years (43.4%).38 Based on these findings, the age for CC screening can be extended to more than 60 years of age.
In this study, age, education level, occupation, monthly family income, parity, age of marriage, and age of first delivery did not show any significant influence on HR-HPV infection. However, a significant association of HR-HPV infection with education levels and early age of sex initiation was observed in other studies.30,39 A small sample size and the inclusion of women aged 30 to 49 years only may be related to the low influence of all these known risk factors. However, further investigations with larger sample sizes and wider age groups are needed.