Prevalence and genotype distribution of high-risk human papillomavirus infections among women in selected communities in the Philippines: Results of the defeat HPV study

Abstract

Persistent infection with high-risk human papillomavirus (HR HPV) is the necessary cause of cervical cancer. In the Philippines, available data on the prevalence and genotype distribution of HPV infections are limited and largely derived from earlier hospital-based studies. The present study determined the overall and type-specific prevalence of HR HPV infection among women in selected communities in the Philippines, along with the associated sociodemographic and behavioral factors. A total of 1,194 women from two communities were examined. Cervical swabs were collected, and the extracted DNA were analyzed for HPV genotyping through a commercial multiplex real-time PCR assay kit. Sociodemographic information, clinical history, and sexual and reproductive behavior were obtained through an interviewer-administered semi-structured questionnaire. The overall prevalence of HR HPV infection was 11.22 % (95 % CI: 9.56–13.14 %). Women residing in urban areas had 1.62 times higher odds (95 % CI: 1.08–2.42) of HR HPV infection than those in rural areas. Moreover, for every year of delaying vaginal sexual debut, there was a 7 % decrease in the odds of HR HPV infection. HPV 52 was the most prevalent genotype (2.59 %), followed by HPV 16 (1.84 %) and HPV 68 (1.09 %). Multiple HR HPV genotypes were recorded in 23 % of HR HPV-infected women. The most frequent co-infections are HPV 16 + HPV 18, HPV 16 + HPV 52, and HPV 39 + HPV 52. These findings highlight the need for updated surveillance and consideration of local genotype distribution in cervical cancer prevention strategies, such as in HPV DNA testing and HPV vaccination programs.

1. Introduction

Cervical cancer is widely prevalent worldwide with high morbidity and mortality rates.¹ It is ranked as the fourth most common cancer in women globally, with around 660,000 estimated new cases and 350,000 deaths in 2022. About 94 % of these deaths occurred in low- and middle-income countries, with the highest rates recorded in sub-Saharan Africa, Central America, and Southeast Asia.¹ In the Philippines, 39.6 million women are at risk of developing cervical cancer, with a reported 7897 new cases and 4052 deaths annually. It is the second most common cancer among women in the country after breast cancer.²

Persistent infection with high-risk human papillomavirus (HR HPV) is the necessary cause of cervical cancer and is the most common viral infection of the lower genital tract.³ Over 200 HPV genotypes have been identified, of which high-risk types such as HPV 16 and 18 are capable of establishing persistent infections that increase the risk for cervical cancer.⁴ The global prevalence is estimated at 31 % for any HPV type and 21 % for high-risk types. HPV 16 and 18 account for most cervical cancer cases, although other HR HPV genotypes such as HPV 31, 33, 45, 52, and 58 also significantly contribute to disease development.⁵ In the Philippines, surveillance data on HPV prevalence and genotype distribution are limited. A cross-sectional study by Ngelangel (1998) investigated the HPV infections among women with normal cytology and women with cervical squamous cell carcinoma and adenocarcinoma. Types 16 and 18 were most common among all groups, with a 9 % positivity among those with a normal cervix.⁶ In another hospital-based study, types 16 and 18 also ranked as the top genotypes among 87 patients with invasive cervical carcinoma.⁷ Similar findings were also seen in a more recent study among 28 patients with cervical squamous cell carcinoma in a tertiary hospital in the Philippines.⁸ A different pattern, however, was seen in a study among Filipino sex workers with or without abnormal cervical cytology, where HPV type 52 had the highest prevalence.⁹ In a more recent study that tested anogenital swabs from healthy, non-pregnant women who participated in a vaccine trial, types 52 and 51 were among the most frequently detected.¹⁰ It is essential to note that most of these studies are hospital-based or conducted among specific populations, and there is limited data on the viral types circulating in Philippine communities.

Aside from HPV genotype prevalence and distribution, it is equally important to understand how sociodemographic and behavioral factors contribute to HR HPV infection. Globally, the consistently associated factors include younger age, lower educational attainment, low socioeconomic status, and unmarried or cohabiting status. Behavioral risks such as early sexual debut, multiple sexual partners, smoking, alcohol consumption, and contraceptive use have also been commonly reported from various studies.11, 12, 13, 14, 15, 16, 17 Furthermore, region-specific findings provide additional insights into the factors that are more prominent in their regions associated with HR HPV infection. In the United States, socioeconomic disparity plays a critical role, where women living below the poverty line are significantly associated with HR HPV infections.¹⁷ Then, lifestyle behaviors in other regions, such as alcohol consumption history in China,¹² smoking habits in Europe^11,16 as well as in Mexico¹⁵ have also been reported. Meanwhile, in Africa, being unmarried or unemployed were the more prominent social determinants of HR HPV infection.¹³ Despite the well-established global and regional determinants of HR HPV infection, community-level data on how these factors interact with genotype distribution in the Philippines remain scarce.

In this study, we determined the prevalence and genotype distribution of HPV infections among women in two communities, one urban and one rural, in the Philippines. By identifying circulating genotypes and risk factors, our findings can inform national HPV vaccination strategies, guide cervical cancer screening programs, and contribute to the global landscape of HPV surveillance.

2. Materials and methods

2.1. Study and sampling design

This study, which forms part of the DEFEAT HPV study, employed a community-based cross-sectional design with convenience sampling and enrolled women through the Likhaan Center for Women's Health Clinic in Tondo, Manila, as the urban center, and in Naic, Cavite province, as the rural center, both in the Philippines.¹⁸ The protocol was approved by the University of the Philippines Manila Research Ethics Board (UPMREB 2021-0645-01). The study was performed following the relevant ethical guidelines, and written informed consents were obtained from all participants.

2.2. Sample size

Based on an estimated HR HPV prevalence of 9.3 %, a precision of 5 %, and an additional 10 % adjustment for nonparticipation and poor quality of biospecimen, a minimum sample size of 1186 women was required for the prevalence survey (calculated using [http://sampsize.sourceforge.net/iface/index.html], accessed August 1, 2022). This was equally divided between the two recruitment sites.

2.3. Inclusion and exclusion criteria

The inclusion criteria of this study were the following: women age 21 years or older will be eligible to participate if they are currently sexually active or seeking birth control, are not currently pregnant, have an intact uterus, have no current referral for hysterectomy, and have no history of treatment for cervical intraepithelial neoplasia (CIN) within the previous 18 months. The exclusion criteria were the following: currently menstruating; currently taking antibiotics, antifungals, or antivirals, or within the last three months; had a hysterectomy for any indication; use of douching substances, vaginal applied medications and suppositories, feminine deodorant sprays, vaginal lubricants within 48 h prior the visit; any skin condition in the genital area interfering with the study; sexual intercourse less than 48 h prior the visit; type I or type II diabetes; hepatitis; being positive for human immunodeficiency virus.

2.4. Patient data collection

The data collection tool was pre-tested for content and face validity, and field interviewers received training prior to deployment in the field. Information was obtained through an interviewer-administered questionnaire. The following data were collected: (1) sociodemographic characteristics (age, place of residence, educational attainment, monthly family income, marital status, alcohol drinking, and smoking); (2) medical history (use of oral contraceptives and previous Pap test or visual inspection with acetic acid); (3) sexual and reproductive health behavior (use of contraceptives, number of children, age at first oral intercourse, lifetime oral sexual partners, age at first vaginal intercourse, and lifetime vaginal sexual partners). A licensed physician conducted a standard gynecological examination. These were performed in a private room with the assistance of trained personnel.

2.5. Sample collection and preparation

A licensed physician collected cervical swabs using an ENAT PM 2 mL L–shape Applicator (Cat. No. 608CS01L; Seegene Inc., Seoul, South Korea) following a standard gynecological technique. All collected specimens were suspended in universal transport medium, stored in zip-lock bags, and transported to the Virology Laboratory, College of Public Health, University of the Philippines Manila, Philippines. Samples were aliquoted into cryotubes and stored at −80 °C until laboratory processing.

2.6. DNA extraction

DNA was extracted from cervical swabs using the Qiagen DNeasy Blood and Tissue Kit following the manufacturer's protocol. Samples were lysed, purified via spin columns, and the DNA was eluted in AE buffer. DNA was characterized using UV spectrophotometry and stored at −80 °C until further analysis.

2.7. HPV genotyping

HPV detection and genotyping were performed using the Allplex™ HPV28 assay, which simultaneously detects 28 HPV genotypes, including 19 high-risk (HR), 9 low-risk (LR) types, and an internal control (Cat. No. HP7S00X; Seegene Inc.).¹⁹ The real-time PCR assay was carried out on the CFX96™ Real-Time PCR Detection System (Bio-Rad Laboratories, Hercules, CA, USA) using Seegene's AIOS system for automated workflow (Seegene Inc., Seoul, South Korea).

2.8. Data interpretation

Amplification data were analyzed using Seegene Viewer software, which automatically interprets results by identifying specific HPV genotypes and distinguishing HR from LR types. Samples with failed internal control amplification and PCR runs with failed positive and negative controls were deemed invalid and subjected to repeat testing.

2.9. Statistical analysis

Descriptive statistics were calculated for all variables, stratified by HPV infection status. Participants were classified as HR HPV positive if at least one oncogenic genotype was detected, regardless of co-infection with low-risk types. For analytic purposes, women positive for low-risk HPV types were grouped with HPV-negative women as a single ‘HR HPV negative’ reference category, consistent with the biological and clinical distinction between low-risk and oncogenic high-risk HPV types, and to allow evaluation of factors explicitly associated with high-risk HPV infection. The Shapiro–Wilk test was used to assess the normality of continuous variables. Variables not meeting the normality assumption were summarized as median and interquartile range (IQR) and compared between groups using the Mann–Whitney U test. Categorical variables were summarized as counts and percentages and compared between groups using the chi-square test without continuity correction.

Univariate logistic regression analyses were performed to estimate crude odds ratios (OR) and 95 % confidence intervals (CI) for the association between each predictor and HR HPV positivity. Continuous predictors were modeled as numeric variables unless a Box–Tidwell test indicated a violation of the linearity-in-the-logit assumption, in which case they were categorized.

Multivariable logistic regression was used to identify factors independently associated with high-risk HPV infection. Candidate variables were selected based on biological plausibility and having a p-value of ≤0.20 in the univariate logistic regression. Multicollinearity was assessed using the variance inflation factor, with a threshold of 5 indicating potentially problematic collinearity. Model coefficients were exponentiated to provide adjusted ORs and corresponding 95 % Wald CIs. Model calibration was assessed using the Hosmer–Lemeshow goodness-of-fit test. A two-sided p-value <0.05 was considered statistically significant for all analyses.

HR HPV infection status was classified as single or multiple genotype infections based on the PCR test result. Binary indicator variables were created for genotypes 16–82. The proportions of single- and multiple-genotype infections were visualized using a pie chart (ggplot 2). For multiple genotype infections, the top 10 exact genotype combinations were identified and plotted as horizontal bar charts.

To provide a descriptive assessment of potential vaccine coverage, high-risk HPV genotypes detected in the study were compared with the high-risk types included in currently available HPV vaccines. For each participant with high-risk HPV infection, we determined whether the infection included at least one genotype targeted by the bivalent or quadrivalent vaccines (HPV16 and/or HPV18) and whether it included any high-risk genotype covered by the 9-valent vaccine (HPV16, 18, 31, 33, 45, 52, or 58). We then calculated the proportion of women who tested positive for high-risk HPV infections that contained vaccine-targeted types and estimated the additional proportion potentially covered by the 9-valent vaccine compared with bivalent or quadrivalent vaccines. This analysis was descriptive and was not intended to evaluate the effectiveness or clinical impact of the vaccine. Analyses were conducted in RStudio v2025.05.1 + 513.

3. Results

3.1. Sociodemographic characteristics and reproductive behavior

Among 1,194 women aged 20–68 years who were recruited and examined in this study, 11.22 % (95 % CI: 9.56–13.14 %) tested positive for HR HPV (Table 1). The median age of the study participants was 35 (IQR: 29, 42). Most identified as Roman Catholic (87.50 %). Over half (55.29 %) had completed secondary education. At the time of participation, 78.00 % were unemployed, and 82.63 % reported a monthly income of below PHP 10,000 (approximately USD 179). Most participants were either cohabitating (55.16 %) or married (39.73 %). Half currently consume alcohol (51.13 %), whereas only 15.87 % reported as current smokers. More HR HPV-positive women were living in urban areas (59.70 %) than in rural areas (40.30 %). The median age of first vaginal and oral sexual debut was at 18 years old (Table 2). HR HPV-positive women had a significantly earlier age of vaginal sexual debut (17 years old) compared to HR HPV-negative women (18 years old). The median number of vaginal and oral sexual partners was 1 (IQR: 1, 2). HR HPV-positive women had a higher number of sexual partners than HR HPV-negative women (p < 0.001). The median number of children was 3 (IQR: 2, 4). The majority of women (68.86 %) were using contraceptives.

Table 1.

Sociodemographic characteristics of the study participants.

Characteristic	Overall	Negative	Positive	p-valueb
	N = 1,194a	N = 1,060a	N = 134a
Age	35 (29, 42)	35 (29, 42)	34 (29, 41)	0.75
Residence
Rural	600 (50.25 %)	546 (51.51 %)	54 (40.30 %)	0.024
Urban	594 (49.75 %)	514 (48.49 %)	80 (59.70 %)
Religion
Born Again	85 (7.13 %)	76 (7.18 %)	9 (6.77 %)	0.97
Iglesia ni Cristo	42 (3.52 %)	37 (3.49 %)	5 (3.76 %)
Islam	7 (0.59 %)	7 (0.66 %)	0 (0.00 %)
Roman Catholic	1043 (87.50 %)	926 (87.44 %)	117 (87.97 %)
Others	15 (1.26 %)	13 (1.23 %)	2 (1.50 %)
Educational attainment
None	46 (3.86 %)	41 (3.88 %)	5 (3.73 %)	0.47
Elementary	353 (29.61 %)	311 (29.40 %)	42 (31.34 %)
High school	659 (55.29 %)	592 (55.95 %)	67 (50.00 %)
College	128 (10.74 %)	109 (10.30 %)	19 (14.18 %)
Postgraduate	6 (0.50 %)	5 (0.47 %)	1 (0.75 %)
Employment status
Full-time work	154 (12.93 %)	132 (12.48 %)	22 (16.54 %)	0.42
Part-time work	108 (9.07 %)	96 (9.07 %)	12 (9.02 %)
No work	929 (78.00 %)	830 (78.45 %)	99 (74.44 %)
Monthly income (in Philippine Peso)
0–9999	985 (82.63 %)	878 (82.99 %)	107 (79.85 %)	0.39
10000–19999	181 (15.18 %)	158 (14.93 %)	23 (17.16 %)
20000–29999	23 (1.93 %)	20 (1.89 %)	3 (2.24 %)
30000–39999	3 (0.25 %)	2 (0.19 %)	1 (0.75 %)
Alcohol drinking
Never drinker	332 (27.83 %)	298 (28.14 %)	34 (25.37 %)	0.075
Former drinker	251 (21.04 %)	231 (21.81 %)	20 (14.93 %)
Current drinker	610 (51.13 %)	530 (50.05 %)	80 (59.70 %)
Smoking
Never smoker	933 (78.34 %)	833 (78.81 %)	100 (74.63 %)	0.35
Former smoker	69 (5.79 %)	62 (5.87 %)	7 (5.22 %)
Current smoker	189 (15.87 %)	162 (15.33 %)	27 (20.15 %)
Marital status
Never married	34 (2.85 %)	29 (2.74 %)	5 (3.76 %)	0.084
Married	474 (39.73 %)	434 (40.94 %)	40 (30.08 %)
Living together	658 (55.16 %)	572 (53.96 %)	86 (64.66 %)
Widowed	11 (0.92 %)	11 (1.04 %)	0 (0.00 %)
Separated	16 (1.34 %)	14 (1.32 %)	2 (1.50 %)

^an (%).

^bWilcoxon rank sum test for continuous variables; Pearson's Chi-squared test (if all expected count >5) or Fisher's exact test (if expected count >5) for categorical variables.

Table 2.

Sexual and reproductive history and practices of the study participants related to HPV infection and cervical cancer.

Characteristic	Overall	Negative	Positive	p-valueb
	N = 1,194a	N = 1,060a	N = 134a
Age at first vaginal sex	18 (16, 20)	18 (17, 20)	17 (16, 20)	0.024
Age at first oral sex	18 (17, 20)	18 (17, 20)	18 (16, 20)	0.15
Number of oral sex partners	1 (1, 2)	1 (1, 2)	2 (1, 3)	<0.001
Number of vaginal sex partners	1 (1, 2)	1 (1, 2)	2 (1, 3)	<0.001
Number of children	3 (2, 4)	3 (2, 4)	3 (2, 4)	0.33
Heard about cervical cancer screening
No	161 (13.50 %)	148 (13.98 %)	13 (9.70 %)	0.17
Yes	1032 (86.50 %)	911 (86.02 %)	121 (90.30 %)
Had cervical cancer screening
No	827 (69.32 %)	738 (69.69 %)	89 (66.42 %)	0.44
Yes	366 (30.68 %)	321 (30.31 %)	45 (33.58 %)
Willingness to undergo cervical cancer screening
No	5 (0.42 %)	4 (0.38 %)	1 (0.75 %)	0.45
Yes	1180 (99.58 %)	1048 (99.62 %)	132 (99.25 %)
Heard about HPV vaccine
No	844 (70.69 %)	759 (71.60 %)	85 (63.43 %)	0.05
Yes	350 (29.31 %)	301 (28.40 %)	49 (36.57 %)
Received any HPV vaccine
No	1165 (97.65 %)	1034 (97.64 %)	131 (97.76 %)	>0.99
Yes	28 (2.35 %)	25 (2.36 %)	3 (2.24 %)
Know someone with cervical cancer
No	1126 (94.30 %)	999 (94.25 %)	127 (94.78 %)	0.8
Yes	68 (5.70 %)	61 (5.75 %)	7 (5.22 %)
Contraceptive use
No	369 (31.14 %)	333 (31.62 %)	36 (27.27 %)	0.31
Yes	816 (68.86 %)	720 (68.38 %)	96 (72.73 %)

^an (%).

^bWilcoxon rank sum test for continuous variables; Pearson's Chi-squared test (if all expected count >5) or Fisher's exact test (if expected count >5) for categorical variables.

3.2. Awareness and practices regarding HPV infection and cervical cancer

Awareness of cervical cancer screening, such as Pap test and visual inspection with acetic acid, was high (86.50 %), but only 30.68 % had ever undergone cervical cancer screening. Willingness to undergo cervical cancer screening was nearly universal (96.87 %). There was a low HPV vaccine awareness (29.31 %) and extremely low uptake (2.35 %). Most participants (94.30 %) did not know of anyone diagnosed with cervical cancer (Table 2).

3.3. HR HPV genotype distribution

We detected 19 HR HPV genotypes, and the top 10 most prevalent genotypes are presented in Fig. 1. HPV 52 had the highest prevalence at 2.59 %, followed by HPV 16 at 1.84 %, HPV 68 and HPV 51 at 1.09 %, HPV 82 at 1.00 %, and HPV 59 and HPV 18 at 0.92 %. The rest of the genotypes had lower prevalence, ranging from 0.08 % to 0.75 % HPV 26 and HPV 31 had the lowest prevalence at 0.17 % and 0.08 %, respectively.

Fig. 1.

Prevalence of different HR HPV genotype infections among the study participants.

3.4. Factors associated with HR HPV infection

To explore the factors associated with HR HPV infection, univariate and multivariable logistic regression were both performed to control for possible confounding variables. The Hosmer–Lemeshow goodness-of-fit test indicated no evidence of lack of fit for the multivariable logistic regression model (χ² = 4.335, df = 8, p = 0.826), suggesting that the model fit the data well.

For sociodemographic factors, only the place of residence had a significant association with high-risk HPV infection. Women living in urban areas had 1.62 times higher odds of HR HPV infection compared to those living in rural areas (95 % CI: 1.04–2.43; p = 0.019). Age, religion, educational attainment, employment status, monthly income, alcohol drinking, smoking status, and marital status had no significant associations with HR HPV infection (Table 3).

Table 3.

Sociodemographic factors associated with HR HPV infection.

Characteristic	Crude OR (95 % CI)	p-value	Adjusted OR (95 % CI)	p-value
Age	1.00 (0.98–1.02)	0.711	–	–
Residence
Rural	Ref	Ref	–	–
Urban	1.57 (1.09–2.27)	0.015	1.62 (1.08–2.42)	0.0191
Religion
Born Again	Ref	Ref	–	–
Iglesia ni Cristo	1.14 (0.36–3.65)	0.824	–	–
Islam	0.00 (0.00 - Inf)	0.981	–	–
Roman Catholic	1.07 (0.52–2.19)	0.859	–	–
Others	1.30 (0.25–6.71)	0.755	–	–
Educational attainment
None	Ref	Ref	–	–
Elementary	1.11 (0.41–2.96)	0.839	–	–
High school	0.93 (0.36–2.43)	0.879	–	–
College	1.43 (0.50–4.08)	0.504	–	–
Postgraduate	1.64 (0.16–17.01)	0.679	–	–
Employment status
Full-time work	Ref	Ref	Ref	Ref
Part-time work	0.75 (0.35–1.59)	0.453	0.72 (0.42–1.22)	0.219
No work	0.72 (0.44–1.18)	0.187	0.66 (0.29–1.50)	0.321
Monthly income (in Philippine Peso)
0–9999	Ref	Ref	–	–
10000–19999	1.19 (0.74–1.93)	0.469	–	–
20000–29999	1.23 (0.36–4.21)	0.741	–	–
30000–39999	4.10 (0.37–45.63)	0.251	–	–
Alcohol drinking
Never drinker	Ref	Ref	Ref	Ref
Former drinker	0.76 (0.43–1.35)	0.350	1.33 (0.83–2.14)	0.24
Current drinker	1.32 (0.86–2.03)	0.197	0.78 (0.42–1.47)	0.442
Smoking
Never smoker	Ref	Ref	Ref	Ref
Former smoker	0.94 (0.42–2.11)	0.882	1.22 (0.73–2.03)	0.442
Current smoker	1.39 (0.88–2.19)	0.160	0.94 (0.40–2.20)	0.89
Marital status
Never married	Ref	Ref	–	–
Married	0.54 (0.20–1.46)	0.221	–	–
Living together	0.87 (0.33–2.31)	0.783	–	–
Widowed	0.00 (0.00 - Inf)	0.975	–	–
Separated	0.83 (0.14–4.81)	0.834	–	–

In terms of sexual and reproductive history and practices, several factors showed a significant association with high-risk HPV infection (Table 4). Each additional year in age at first vaginal sexual intercourse was associated with a 7 % decrease in the odds of HR HPV infection (OR 0.93, 95 % CI: 0.88–0.99). In univariate analysis, each additional vaginal and oral sex partner was associated with an 11 % (OR 1.11) and 10 % (OR 1.10) increase in the odds of HR HPV infection, respectively. However, after adjusting for potential confounders, these associations were no longer statistically significant. Women who had heard about cervical cancer screening had 1.81 times higher odds of HR HPV infection compared to those who had not, although this association did not reach statistical significance (OR 1.81, 95 % CI: 0.91–3.61; p = 0.089). Women who had heard about the HPV vaccine had higher odds of HR HPV infection (OR 1.45, 95 % CI: 1.00–2.12; p = 0.051), but this association was not statistically significant after adjusting for potential confounders.

Table 4.

Sexual and reproductive history and practices associated with HR HPV infection.

Characteristic	Crude OR (95 % CI)	p-value	Adjusted OR (95 % CI)	p-value
Age at first vaginal sex	0.95 (0.90–1.00)	0.045	0.93 (0.88–0.99)	0.031
Age at first oral sex	1.01 (1.00–1.03)	0.185	1.03 (1.00–1.06)	0.098
Number of vaginal sex partners	1.11 (1.01–1.22)	0.035	1.04 (0.94–1.16)	0.454
Number of oral sex partners	1.10 (1.02–1.20)	0.0193	–	–
Number of children	1.03 (0.93–1.12)	0.604	–	–
Heard about cervical cancer screening
No	Ref	Ref	Ref	Ref
Yes	1.51 (0.83–2.75)	0.175	1.81 (0.91–3.61)	0.089
Had cervical cancer screening
No	Ref	Ref	–	–
Yes	1.16 (0.79–1.70)	0.440	–	–
Willingness to undergo cervical cancer screening
No	Ref	Ref	–	–
Yes	0.50 (0.06–4.54)	0.541	–	–
Heard about the HPV vaccine
No	Ref	Ref	Ref	Ref
Yes	1.45 (1.00–2.12)	0.051	1.26 (0.83–1.92)	0.278
Received any HPV vaccine
No	Ref	Ref	–	–
Yes	0.95 (0.28–3.18)	0.930	–	–
Know someone with cervical cancer
No	Ref	Ref	–	–
Yes	0.90 (0.40–2.02)	0.803	–	–
Contraceptive use
No	Ref	Ref	–	–
Yes	1.23 (0.82–1.85)	0.309	–	–

3.5. Patterns of high-risk HPV genotype infections and co-occurrence

Our study showed that 23 % of HR HPV-positive participants demonstrated multiple HR HPV genotype infections (Fig. 2A). Fig. 2B showed the 10 most frequent genotype combinations of multiple genotype infections. The predominant co-infection genotype combinations were HPV 39 + HPV 42 + HPV 52, HPV 16 + HPV 52, and HPV 16 + HPV 18, which were present in three cases each.

Fig. 2.

Patterns of high-risk HPV genotype infections and co-infection in the study population. (A) Distribution of infection patterns showing the proportion of participants with single versus multiple high-risk (HR) HPV genotype infections. (B) Top 10 most frequent exact genotype combinations among multiple infections.

3.6. Vaccine-type coverage analysis

Among women with high-risk HPV infection, 23.9 % were infected with types 16 or 18 covered by bivalent (2vHPV) or quadrivalent HPV (4vHPV) vaccines. In contrast, the additional high-risk types included in the nonavalent HPV (9vHPV) vaccine increased theoretical coverage to 53.7 %, representing a 29.9 % increase.

4. Discussion

Most of the epidemiological studies available focused on risk factors for cervical cancer, which were presumed to be the same for HR HPV infection. While genetic susceptibility²⁰ and other biological factors such as the cervicovaginal microbiome and host immune system²¹ determine progression of HR HPV infection to development of malignant lesions, sociobehavioral determinants affect the timeliness of detection and intervention. In terms of sociodemographic characteristics, only the area of residence was identified as a risk factor, with women from urban areas at higher odds of acquiring HR HPV (aOR 1.62). The link between living in urban areas and HR HPV remained significant after adjusting for socioeconomic factors, such as age, education, employment, and monthly income (aOR 1.57, 95 % CI 1.07–2.31, p = 0.022), indicating that factors related to residence (such as population density, sexual network structures, or healthcare access) may independently influence HR HPV risk. Evidence on urban-rural differences is conflicting: in a multi-center cross-sectional study of 3856 women in Bangladesh, there is no statistically significant difference in HR HPV positivity between women from urban and rural areas in various divisions, except in the Mymensingh district, where significantly more women from the urban area were positive for HR HPV.²² In contrast, in a cross-sectional study of 414 women in Mali, the prevalence of HR HPV infection in women from rural areas was twice that in women from urban areas.²³ Meanwhile, a cross-sectional study of 99 women from Mexico showed no statistically significant difference between women from urban and rural areas.²⁴ This heterogeneity is explained by urban-rural classification acting as a proxy variable not only for social and economic contexts, but also other domains that comprise the social determinants of health (e.g., health care access and quality, education access and quality, neighborhood and built environment).²⁵

Interestingly, while smoking and low socioeconomic status have both been previously identified as independent risk factors for cervical cancer,²⁶ it was not observed in this study. The results of our study agreed with previous studies that showed that engaging in early sexually intercourse increased the risk of HPV infection,^27,28 high-grade squamous intraepithelial lesions,²⁹ and cervical cancer.³⁰ This association was mediated by number of sexual partners, history of sexually transmitted infection, alcohol and drug use, and partner's number of sexual partners.²⁸ Univariate analysis showed that having multiple sexual partners was associated with increased odds of HR HPV infection, but this did not reach statistical significance after adjusting for potential confounders. A study in Thailand showed that having multiple sexual partners were found to be at a significantly higher risk for HPV 18 (OR 4.58; 95 % CI 1.44–14.58).³¹ Another study in the United States showed that HPV infection was 5.77 times more likely for women who had >11 sexual partners compared to women with 0–1 partner.³² Moreover, our data show that for every year of delaying vaginal sexual debut, there was a 7 % decrease in the odds of HR HPV infection. These results emphasize the role of sexual and reproductive health education as a possible intervention to address HR HPV infection and, by extension, cervical cancer.

This study is the largest community-based research on HPV genotyping conducted in the Philippines involving 1194 women from urban and rural centers. The overall prevalence of HR HPV infection was 11.22 %. Of the 19 HR HPV genotypes detected, HPV 52 was the most common HR HPV genotype, with a prevalence of 2.59 %, which was higher than HPV 16 (1.84 %) and HPV 18 (0.92 %). This finding contrasts with previous reports, which showed that HPV 16 and 18 were the most common HR HPV genotypes seen in Filipino women with normal cervical cytology.^5,6 However, our findings are consistent with a more recent study among Filipino commercial sex workers, which reported a 7.46 % prevalence of HPV 52, compared with 7.12 % for HPV 16 and 3.39 % for HPV 18.⁹ The high prevalence of HPV 52 infection is unlikely due to vaccine pressure, as most of the study participants were not vaccinated against HPV, but rather additional evidence supporting the underestimation of HPV 52 infection in previous studies. While HPV 52 is less oncogenic than the classical HR HPV 16 and 18,³³ it has been shown to have one of the lowest clearance rates among HPV genotypes. In a cohort of women in northwest Ethiopia, HPV 52 has a 12-month clearance rate of 25 %, which is only a bit higher than HPV 16 at 23.08 %.³⁴ Similarly, in a cohort of women in Guangdong, China, HPV-52 has a 24-month clearance rate of 57.67 %, the lowest among HR HPV genotypes evaluated.³⁵ Overall, the higher than reported prevalence of HPV-52 infection and its low clearance rate should inform clinical management as well as public health strategies.

It is alarming that 23 % of HR HPV-positive women in our study were infected with multiple HR HPV genotypes, with the most common co-infections observed with HPV 16 + HPV 18, HPV 16 + HPV 52, and HPV 39 + HPV 52. These patients with co-infection may be at higher risk of persistent HPV infection and poorer prognosis if they develop cervical cancer.³⁶ A previous study observed that cervical cancer patients with tumors containing multiple HPV genotypes had a significantly higher rate of distant tumor recurrences and a worse cancer-specific survival rate.³⁷,³⁸ Our study also revealed that co-infections with HPV 16-HPV 18 and HPV 16-HPV 52 were common. Previous studies conducted in China and France showed that co-infection with HPV 16 and HPV 52 was the most common combination of HPV genotypes. In the study in France, all patients with this co-infection were classified as having high-grade cervical lesions. Another study found that HPV 16-HPV 52 and HPV 16-HPV 18 co-infections were both associated with higher odds of 3.6 to 3.8 of high-grade cervical lesions, compared to HPV 16 alone.³⁹

The overall high positivity rate of HR HPV infection reinforces the necessity for organized, population-based cervical cancer screening programs (HPV testing, Pap test, or co-testing), as opportunistic screening may miss a large proportion of at-risk women. However, HPV 16 and 18 testing underestimates risk in population in populations where HPV 52 is highly prevalent, thus genotyping beyond HPV 16 and 18 should be considered to identify women at risk for high-grade CIN. With regards to patient counseling, a high prevalence underscores the importance of educating patients that HPV infection is common, often transient, but some types, like HPV 52, carry higher oncogenic potential. Counseling patients on the role of persistence, not just positivity, in driving progression to cancer should also highlight the value of regular follow-ups.

The results of this study on genotype distribution provide valuable background information that can inform considerations of HPV vaccination strategies in the Philippines. However, further work is needed to evaluate the potential impact of specific vaccine products. Although our study was not designed to assess vaccine effectiveness, the observed genotype distribution suggests that the 9vHPV vaccines may offer significantly wider coverage of circulating high-risk HPV types in this population compared to the 2vHPV and 4vHPV) vaccines. Vaccination remains an essential tenet in cervical cancer prevention, with Denmark being able to reduce the prevalence of HPV 16 and 18 to less than 1 percent by 2021 after introducing HPV vaccination as part of the national cervical screening program in 2008.⁴⁰ Currently, the Philippine government, through its Department of Health (DOH), provides free quadrivalent HPV vaccination to girls aged 9–14 years in public schools as part of its school-based immunization program. While 2vHPV and 4vHPV vaccines cover HPV 16 and 18, they do not cover all genotypes included in 9vHPV vaccine.^41,42 A recent study showed that 4vHPV vaccine had no effect against non-vaccine types.⁴³ Cross-protection of 2vHPV and 4vHPV vaccines against other HPV genotypes was reported, but their cross-protective effects did not reach the observed efficacy of 9vHPV vaccine, which was ≥95 % efficacious to prevent 6-month persistent infection, 12-month persistent infection, and cervical disease related to each of the five HPV types (31, 33, 45, 52, and 58).⁴⁴ Moreover, cross-protection efficacy significantly wanes through the years.⁴²

In addition to efficacy, cost-effectiveness studies support the adoption of 9vHPV vaccine. A study in China showed that switching from 2vHPV to 9vHPV vaccine is potentially cost-saving and associated with a significant reduction of cervical cancer burden. Adopting this new strategy would result in more than $1,852 million in cost savings and 237,000 QALYs gained.⁴⁵ Another study in Taiwan showed that the 9vHPV vaccination program for 13- to 14-year-old girls would be highly cost-effective compared with the bivalent HPV vaccine. It would prevent an additional 15,951 cervical cancer cases and 6600 cervical cancer-related deaths compared with the bivalent vaccine.⁴⁶ Another study in the Netherlands showed that 9vHPV vaccine prevents an additional 1320 high-grade cervical lesions, 70 cancers, 34,000 anogenital wart episodes, and 30 recurrent respiratory papillomatosis and generates €4.1 million discounted savings from fewer treatments.⁴⁷ Thus, adopting broader coverage vaccines, such as the 9vHPV vaccine, would be more advantageous in settings where HPV 52 has a high prevalence, such as the Philippines.

Furthermore, public health surveillance should include continuous HPV genotype monitoring, as this is crucial for detecting shifts in circulating strains, especially since vaccine-driven genotype replacement is possible. Such data would drive national immunization policy, particularly for tailoring vaccine selection. Finally, the current high HPV positivity rate signals persistent gaps in sexual health education, condom use, and access to screening and vaccination, emphasizing the importance of strengthening school-based and community-based vaccination programs, alongside awareness campaigns for long-term cervical cancer prevention.

This study has several limitations. Despite a sample size of 1,194 women, the study only included two communities in the Philippines and used convenience sampling. Hence, the prevalence obtained in this study may not be generalizable to all Filipino women. Certain sociodemographic and behavioral data collected for this study were self-reported and may have been affected by potential recall bias. This bias could have affected the accuracy of the responses and introduced confounding factors. Lastly, some variables in our dataset had missing information for several patients. We did not perform imputations, and the missing values were treated as blanks and excluded from the analysis for the affected variables only. These missing values may have reduced the sample size available for those specific analyses and limited the generalizability of the results.

5. Conclusion

This large community-based study provides the most comprehensive and up-to-date data on the prevalence and genotype distribution of HR HPV among women without cervical cancer in specific communities in Cavite and Manila, Philippines. We found that urban residence and earlier age at sexual debut were associated with an increased risk of HR HPV infection, highlighting the role of sociodemographic and behavioral factors in shaping infection risk. HPV 52 appeared as the most common high-risk genotype, surpassing HPV 16 and 18, with a considerable proportion of women harboring multiple HR HPV infections, particularly combinations involving HPV 16, 18, and 52. These findings underscore the importance of continued surveillance of genotype distribution to inform screening and vaccination strategies in the Philippines. We recommend strengthening health education and promotion on factors associated with HR HPV infection to address modifiable risk factors and improve cervical cancer prevention efforts in the Philippines. We suggest reinforcement of community-based screening programs and ensuring broad access to HPV vaccination. There is a need to highly consider vaccines covering HPV 52, and other non-HPV 16/18 HR HPV genotypes, since these other genotypes are common among Filipino women and may also increase the risk of cervical cancer.

CRediT authorship contribution statement

Ourlad Alzeus G. Tantengco: Writing – review & editing, Writing – original draft, Visualization, Validation, Software, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Ian Kim B. Tabios: Writing – review & editing, Writing – original draft, Validation, Supervision, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Conceptualization. Abialbon G. Francisco: Visualization, Software, Methodology, Investigation, Formal analysis, Data curation. Clarissa L. Velayo: Writing – review & editing, Writing – original draft, Validation, Supervision, Methodology, Investigation, Conceptualization. Ryan C.V. Lintao: Writing – review & editing, Writing – original draft, Validation, Methodology, Conceptualization. Fresthel Monica M. Climacosa: Writing – review & editing, Validation, Methodology, Funding acquisition, Conceptualization. Leslie Michelle M. Dalmacio: Writing – review & editing, Supervision, Project administration, Methodology, Funding acquisition, Conceptualization. Leslie Faye T. Cando: Writing – review & editing, Writing – original draft, Methodology, Conceptualization. Glenmarie Angelica S. Perias: Writing – review & editing, Writing – original draft, Methodology, Conceptualization. Ronniel Alfred N. Acebes: Writing – original draft, Software, Methodology, Investigation, Data curation. Sheriah Laine M. de Paz-Silava: Writing – review & editing, Writing – original draft, Validation, Supervision, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Conceptualization.

Funding

This study was funded by the Department of Science and Technology Grants-in-Aid of the Republic of the Philippines awarded to SLMdPS. OAGT, IKBT, FMMC, RCVL, LFTC, GASP, and SLMdPS are past and current trainees of the MD-PhD in Molecular Medicine Program, supported by the Department of Science and Technology – Philippine Council for Health Research and Development (DOST-PCHRD), and administered through the University of the Philippines Manila.

Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: OAGT and IKBT have presented research findings as independent scientists at events organized by MSD Philippines without receiving honoraria. MSD Philippines was not involved in the study. All other authors declare no conflicts of interest.

Data availability

Data will be made available on request.