Skip directly to search Skip directly to A to Z list Skip directly to page options Skip directly to site content

Establishing Baseline Cervical Cancer Screening Coverage — India, 2015–2016


Article Metrics

Altmetric:

Citations:

Views: Views equals page views plus PDF downloads

Metric Details
MMWR Email Subscription Button

 

Elizabeth A. Van Dyne, MD1,2; Benjamin D. Hallowell, PhD2; Mona Saraiya, MD2; Virginia Senkomago, PhD2; Shivani A. Patel, PhD3; Sutapa Agrawal, PhD4; Arpita Ghosh, PhD4; Deepika Saraf, PhD5; Ravi Mehrotra, MD5; Preet K. Dhillon, PhD4 (View author affiliations)

View suggested citation

Summary

What is already known about this topic?

Cervical cancer is the second leading cause of cancer mortality among women in India; in 2016 the Ministry of Health and Family Welfare of India recommended population-based cervical cancer screening in women aged ≥30 years.

What is added by this report?

Among women in India aged 30–49 years, less than one third (29.8%) reported ever having been screened for cervical cancer. There was substantial geographic variation, and screening prevalence was associated with education of women and their partners, wealth, and marriage.

What are the implications for public health practice?

These estimates can be used as baseline data to plan cervical cancer screening targeted interventions, programmatic rollouts, and evaluation to help India meet the goal of universal cervical cancer screening.

Cervical cancer is the second leading cause of new cancer cases and cancer-related deaths among women in India, with an estimated 96,922 new cases and 60,078 deaths each year.* Despite the availability of effective low-cost screening options in India, limited access to screening and treatment services, diagnosis at a later stage, and low investment in health care infrastructure all contribute to the high number of deaths (1). In 2016 the Ministry of Health and Family Welfare of India recommended cervical cancer screening using visual inspection with acetic acid every 5 years for women aged 30–65 years (per World Health Organization [WHO] guidelines) (2,3). To establish a baseline for cervical cancer screening coverage, survey data were analyzed to estimate the percentage of women aged 30–49 years who had ever been screened for cervical cancer (defined as ever having had a cervix examination). Cervical cancer screening was estimated using data from the Fourth National Family Health Survey (NFHS-4), a nationally representative survey conducted at the district level during 2015–2016, which included 699,686 Indian women aged 15–49 years. Lifetime cervical cancer screening prevalence was low (29.8%) and varied by geographic region, ranging from 10.0% in the Northeast Region to 45.2% in the Western Region. Prevalence of screening was higher among women with higher levels of education and household wealth, those who had ever been married, and urban residents. This screening prevalence can be used as a baseline indicator for cervical cancer screening in India in accordance with the WHO Noncommunicable Diseases Global Monitoring Framework during state-based programmatic rollout and program evaluation (4).

The 2015–2016 NFHS-4, a cross-sectional, nationally representative survey, was conducted in all 29 states and seven union territories in India; it included a sample of 699,686 women aged 15–49 years in both urban and rural areas, with a 97.6% response rate. The survey questionnaire underwent pretesting and was translated into 18 regional languages and back-translated to ensure consistency. To ascertain cervical cancer screening, women aged 30–49 years were asked “Have you ever undergone a cervix examination?” Weighted prevalence estimates of women who reported screening and 95% confidence intervals (CIs) were calculated. Chi-squared tests were used to assess statistical significance of differences, defined as a p-value <0.05. Data were stratified by age, rural/urban residence, level of education, marital status, household wealth index,§ religion, work status, caste/tribe status, partner’s education, and geographic region.** Maps were created to display weighted prevalence estimates.

Overall, among 336,777 women aged 30–49 years, 29.8% (95% CI = 29.4%–30.2%) reported ever having been screened for cervical cancer (Table). Screening prevalence increased with women’s educational level and that of their partners, ranging from 24.7% among women with no formal education to 37.1% among women who had completed grade 12 or higher, and from 26.3% among those whose partners had no formal education to 36.9% among those whose partners had at least a grade 12 level education.

Cervical cancer screening prevalence varied by women’s marital status, from a low of 6.2% among those who were never married to 30.5% among those who were currently married. When assessed by household wealth, prevalence was lowest among women from the poorest households (17.1%) and highest among those from the wealthiest households (40.4%). Screening prevalences were lower among Hindu (29.4%) and Muslim (26.8%) women than among Sikh (50.2%), Buddhist (48.2%), and Christian (39.1%) women, and lower among women who belonged to a Scheduled Tribe (25.1%) or Scheduled Caste (28.2%) than among women in “Other Backward Classes” (30.8%) or the general category.

Geographically, screening prevalence was higher among women in urban (34.0%) than among those in rural (27.5%) areas, and higher in the Western Region (45.2%), union territories (41.2%), South Region (38.1%), and North Region (37.0%) than in the Northeast (10.0%), East (15.7%), and Central (22.7%) regions (Figure). Across states, screening prevalence ranged from 5.2% (West Bengal) to 78.1% (Kerala) (Table).

Discussion

Nationally, fewer than one in three Indian women reported having been screened for cervical cancer, although screening prevalence was highly variable across states and within districts, and was higher in urban areas. Higher screening prevalence was associated with education of women and their partners, wealth, and marriage.

The operational framework in India recommends a screen-and-treat approach using visual inspection with acetic acid, consistent with WHO guidelines for countries that do not have cervical cancer screening programs in place or resources for Papanicolaou (Pap) or human papillomavirus testing†† (2,3). Visual inspection with acetic acid screening programs in India have been found through randomized controlled trials to effectively reduce cervical cancer mortality by approximately 30% (5,6).

The historical focus of the health system in India has been on maternal and child health and communicable diseases. However, it is also important to take into account the epidemiologic transition and demographic shift in the Indian population to more disability-adjusted life years from noncommunicable, chronic diseases than from communicable, maternal, neonatal, and nutritional diseases (7). The decision of India’s Ministry of Health and Family Welfare to provide guidance in 2016 on universal population-based cervical cancer screening among women aged 30–65 years is a response to this epidemiologic transition. Screening of women in the target population will be recommended every 5 years; surveillance during the initial rollout and each 5-year interval will be evaluated, and strategies will be modified to improve screening rates (2).

The national and state cervical cancer screening baseline estimates in this study can be used for programmatic rollout, implementation benchmarks, and program evaluation in accordance with the WHO cervical cancer indicator§§ for women aged 30–49 years screened for cervical cancer (4). Cervical cancer screening can also be monitored in age groups outside the recommended guidelines to evaluate effective implementation of screening recommendations.

The findings of this study are subject to at least three limitations. First, despite the intention that the survey question serve as an indicator for cervical cancer screening, women might have reported cervical examinations that were not related to cervical cancer screening. This could lead to an overestimation of screening prevalence. There is a concern that women might have confused a pelvic exam with a cervical cancer screening test; however, as in the United States, self-reported questions have proved to be a consistent way of measuring screening prevalence in countries with no organized screening program or screening registries (8,9). Second, it is possible that women might have responded in a manner they viewed as more socially acceptable. Finally, with dialect differences, survey questions might not have been fully understood. The next version of the survey (NFHS-5) will specifically ask women whether they have undergone a screening test for cervical cancer. A study to determine accuracy of self-reported screening of the survey question compared with that of clinical records might be beneficial.

The main strength of this study is the large sample size of the nationally representative survey. These are the first reported data on cervical cancer screening in India that allow examination across all states and union territories down to the district level. Previous national estimates were based on smaller sample sizes in older data sources; for example, the 2003 World Health Survey, a household survey of 3,954 women found that 5.3% of Indian women aged 25–64 years reported having been screened with a Pap test in the past 3 years (10).

Moving forward with the state-level screening program rollouts in India, it is important to consider how socioeconomic factors might be associated with acceptance of screening at the district, state, and national levels. In the future, these baseline data can be used to plan and evaluate cervical cancer screening programs, perform cost-effectiveness analyses, and evaluate facility readiness. Prioritizing geographic areas and groups with lower screening prevalences might be needed to progress to India’s national goal of universal cervical cancer screening (3).¶¶

At the May 2018 World Health Assembly, the WHO Director-General issued a call to action to eliminate cervical cancer globally as a public health problem, including comprehensive strategies such as vaccination, screening, and treatment.*** Strong surveillance systems that include cancer registries, national surveys, or registries that can measure screening or vaccination coupled with modeling will all play an important role in ensuring that cervical cancer can be eliminated as a public health problem in women.

Corresponding author: Mona Saraiya, msaraiya@cdc.gov, 770-488-4293.


1Epidemic Intelligence Service, CDC; 2Division of Cancer Prevention and Control, National Center for Chronic Disease Prevention and Health Promotion, CDC; 3Emory University, Atlanta, Georgia; 4Public Health Foundation of India, New Delhi, India; 5National Institute for Cancer Prevention and Research, Noida, India.

All authors have completed and submitted the ICMJE form for disclosure of potential conflicts of interest. No potential conflicts of interest were disclosed.


* International Agency for Research on Cancer Global Cancer Observatory. http://gco.iarc.fr/today/data/factsheets/populations/356-india-fact-sheets.pdf.

National Family Health Survey-4, India, 2015–2016, data version 73. http://rchiips.org/NFHS/nfhs4.shtml and https://dhsprogram.com/.

§ The household wealth index is a composite measure of a household’s cumulative living standard. The wealth index is calculated using data on a household’s ownership of selected assets, such as televisions and bicycles, materials used for housing construction, and types of water access and sanitation facilities.

Scheduled Classes, Scheduled Tribes, and “Other Backward Classes” are constitutionally recognized categories describing historically, socially, educationally, and/or economically disadvantaged groups that are officially recognized in India. “General” is a group that has a higher status in the caste hierarchy. Scheduled Castes are castes that the Government of India identifies as in need of special protection from social injustice and exploitation. They are explicitly recognized by the Constitution of India, were previously called the “depressed classes” by the British; other past names were untouchables or dalits. Scheduled Tribes consist of approximately 700 tribes that tend to be geographically isolated and have limited economic and social interaction with the rest of the population. Although there is a substantial degree of heterogeneity within each category, these categories are routinely used for population-based monitoring in India.

** North: Haryana, Himachal Pradesh, Jammu and Kashmir, Punjab, and Rajasthan. Central: Chhattisgarh, Madhya Pradesh, Uttarakhand, and Uttar Pradesh. East: Bihar, Jharkhand, Odisha, and West Bengal. Northeast: Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim, and Tripura. Western: Goa, Gujarat, and Maharashtra. South: Andhra Pradesh, Karnataka, Kerala, Tamil Nadu, and Telangana. Union territories: Andaman and Nicobar Islands, Chandigarh, Dadra and Nagar Haveli, Daman and Diu, Delhi, Lakshadweep, and Puducherry.

†† http://nicpr.res.in/images/PDF/guidelines_for_population_level_screening_of_common_NCDs.pdf.

§§ Proportion of women aged 30–49 years screened for cervical cancer at least once, or more often, and for lower or higher age groups according to national programs or policies.

¶¶ https://www.bmj.com/content/bmj/355/bmj.i5574.full.pdf.

*** https://www.who.int/reproductivehealth/call-to-action-elimination-cervical-cancer/en.

References

  1. Ginsburg O, Bray F, Coleman MP, et al. The global burden of women’s cancers: a grand challenge in global health. Lancet 2017;389:847–60. CrossRef PubMed
  2. World Health Organization. WHO guidelines for screening and treatment of precancerous lesions for cervical cancer prevention. Geneva, Switzerland: World Health Organization; 2013. https://apps.who.int/iris/bitstream/10665/94830/1/9789241548694_eng.pdf
  3. Government of India Ministry of Health and Family Welfare. Operational framework: management of common cancers. New Delhi, India: Government of India Ministry of Health and Family Welfare; 2016. http://cancerindia.org.in/wp-content/uploads/2017/11/Operational_Framework_Management_of_Common_Cancers.pdf
  4. World Health Organization. 25 indicators of noncommunicable diseases global monitoring framework. Geneva, Switzerland: World Health Organization; 2014. https://www.who.int/nmh/global_monitoring_framework/2013-11-06-who-dc-c268-whp-gap-ncds-techdoc-def3.pdf?ua=1
  5. Shastri SS, Mittra I, Mishra GA, et al. Effect of VIA screening by primary health workers: randomized controlled study in Mumbai, India. J Natl Cancer Inst 2014;106:. CrossRef PubMed
  6. Sankaranarayanan R, Esmy PO, Rajkumar R, et al. Effect of visual screening on cervical cancer incidence and mortality in Tamil Nadu, India: a cluster-randomised trial. Lancet 2007;370:398–406. CrossRef PubMed
  7. India State-Level Disease Burden Initiative Collaborators. Nations within a nation: variations in epidemiological transition across the states of India, 1990–2016 in the Global Burden of Disease Study. Lancet 2017;390:2437–60. CrossRef PubMed
  8. Rauscher GH, Johnson TP, Cho YI, Walk JA. Accuracy of self-reported cancer-screening histories: a meta-analysis. Cancer Epidemiol Biomarkers Prev 2008;17:748–57. CrossRef PubMed
  9. Viens L, Perin D, Senkomago V, Neri A, Saraiya M. Questions about cervical and breast cancer screening knowledge, practice, and outcomes: a review of demographic and health surveys. J Womens Health (Larchmt) 2017;26:403–12. CrossRef PubMed
  10. Gakidou E, Nordhagen S, Obermeyer Z. Coverage of cervical cancer screening in 57 countries: low average levels and large inequalities. PLoS Med 2008;5:. CrossRef PubMed
TABLE. Prevalence of cervical cancer screening among women aged 30–49 years, by demographic and socioeconomic characteristics — Fourth National Family Health Survey, India, 2015–2016Return to your place in the text
Characteristic No. in sample Weighted screening prevalence, % (95% CI) p-value (chi-squared)*
Overall 336,777 29.8 (29.4–30.2)
Age group (yrs)
30–34 97,048 29.0 (28.4–29.6) <0.0001
35–39 90,433 29.5 (29.0–30.0)
40–44 76,627 30.4 (29.9–31.0)
45–49 72,669 30.7 (30.1–31.3)
Education
No education 143,607 24.7 (24.2–25.2) <0.0001
Grades 1–8 96,582 29.9 (29.4–30.4)
Grades 9–11 51,753 36.9 (36.1–37.8)
Grades ≥12 44,835 37.1 (36.1–38.1)
Partners’ education
No education 13,470 26.3 (25.1–27.5) <0.0001
Grades 1–8 18,214 31.4 (30.3–32.6)
Grades 9–11 13,735 35.9 (34.4–37.3)
Grades ≥12 12,524 36.9 (35.2–38.5)
Marital status
Never married 7,165 6.2 (5.0–7.3) <0.0001
Currently married 305,662 30.5 (30.1–30.9)
Widowed 18,838 25.9 (24.9–27.0)
Divorced/Separated/Deserted 5,112 24.9 (23.0–26.9)
No. of children
0 17,562 27.6 (26.4–28.8) <0.0001
1 31,029 33.0 (32.0–34.0)
2 98,185 34.0 (33.4–34.6)
≥3 190,001 26.8 (26.5–27.2)
Household wealth index§
Poorest 63,723 17.1 (16.6–17.5) <0.0001
Poor 69,441 23.1 (22.5–23.6)
Middle 68,525 30.2 (29.5–30.8)
Rich 67,191 34.7 (33.9–35.4)
Richest 67,897 40.4 (39.5–41.3)
Working status
Currently working 17,732 31.9 (30.7–33.1) 0.6000
Not currently working 41,489 32.1 (31.3–33.0)
Religion
Hindu 252,410 29.4 (29.0–29.9) <0.0001
Muslim 40,686 26.8 (25.9–27.8)
Christian 26,378 39.1 (37.0–41.1)
Sikh 7,953 50.2 (47.3–53.0)
Buddhist 4,587 48.2 (43.4–52.9)
Jain 597 38.6 (32.3–44.8)
Other 4,166 9.1 (7.3–11.0)
Caste/Tribe status**
Scheduled Caste 57,860 28.2 (27.3–29.1) <0.0001
Scheduled Tribe 61,013 25.1 (24.2–26.1)
“Other Backward Class” 130,332 30.8 (30.3–31.4)
General 85,963 31.2 (30.5–31.9)
Do not know 1,609 17.3 (14.4–20.2)
Place of residence
Urban 102,300 34.0 (33.2–34.8) <0.0001
Rural 234,477 27.5 (27.1–27.9)
Geographic regions††
North 56,018 37.0 (36.2–37.9) <0.0001
Central 91,087 22.7 (22.1–23.3)
East 59,048 15.7 (15.2–16.2)
Northeast 49,292 10.0 (9.5–10.5)
Western 27,537 45.2 (43.8–46.6)
South 45,070 38.1 (37.2–39.0)
Union Territories 8,725 41.2 (35.3–47.0)
State/Union territory by region
North <0.0001
Haryana 10,097 42.0 (39.8–44.1)
Himachal Pradesh 5,604 30.8 (28.5–33.0)
Jammu and Kashmir 11,107 50.7 (48.7–52.8)
Punjab 10,210 51.3 (48.3–54.2)
Rajasthan 19,000 26.0 (24.7–27.3)
Central
Chhattisgarh 11,551 23.7 (21.9–25.4)
Madhya Pradesh 29,475 30.1 (29.0–31.1)
Uttarakhand 8,103 23.0 (21.2–24.8)
Uttar Pradesh 41,958 19.2 (18.4–19.9)
East
Bihar 20,215 18.1 (17.2–19.0)
Jharkhand 13,282 15.3 (14.3–16.4)
Odisha 16,837 34.4 (32.8–36.0)
West Bengal 8,714 5.2 (4.6–5.9)
Northeast
Arunachal Pradesh 7,291 10.5 (9.3–11.6)
Assam 13,942 6.3 (5.6–7.0)
Manipur 7,156 25.5 (24.1–27.0)
Meghalaya 4,087 27.0 (24.6–29.5)
Mizoram 6,314 30.9 (28.6–33.2)
Nagaland 5,518 20.9 (19.3–22.5)
Sikkim 2,559 15.9 (13.7–18.2)
Tripura 2,425 7.6 (6.0–9.2)
Western
Goa 989 64.6 (59.3–69.8)
Gujarat 11,788 33.2 (31.2–35.2)
Maharashtra 14,760 51.0 (49.2–52.8)
South
Andhra Pradesh 5,618 42.6 (40.4–44.8)
Karnataka 13,567 18.4 (16.9–20.0)
Kerala 6,399 78.1 (76.3–80.0)
Tamil Nadu 15,724 31.0 (29.7–32.4)
Telangana 3,762 41.2 (38.2–44.3)
Union territories
Andaman and Nicobar Islands 1,563 28.8 (23.4–34.3)
Chandigarh 385 73.6 (66.1–81.0)
Dadra and Nagar Haveli 361 23.4 (16.8–30.1)
Daman and Diu 677 52.6 (44.3–60.9)
Delhi 2,899 40.7 (33.7–47.8)
Lakshadweep 596 71.8 (66.7–76.8)
Puducherry 2,244 28.9 (22.2–35.6)

* Chi-square test, significantly different if p<0.05 among groups; p-values were calculated using prevalence to the hundredth decimal place.
Partners’ education and work status were collected in only a random subset of households selected for state-modules and limited to married women so do not sum to total.
§ The household wealth index is a composite measure of a household’s cumulative living standard. The wealth index is calculated using data on a household’s ownership of selected assets such as televisions and bicycles, materials used for housing construction, and types of water access and sanitation facilities.
Other included Jewish, Parsi/Zoroastrian, no religion, and other religion.
** Scheduled Caste, Scheduled Tribe, and “Other Backward Class” are constitutionally recognized categories describing historically, socially, educationally, and/or economically disadvantaged groups that are officially recognized in India. “General” is a category that does not belong to any of the prior three categories. Although there is a substantial degree of heterogeneity within each category, these categories are routinely used for population-based monitoring in India.
†† North: Haryana, Himachal Pradesh, Jammu and Kashmir, Punjab, and Rajasthan. Central: Chhattisgarh, Madhya Pradesh, Uttarakhand, and Uttar Pradesh. East: Bihar, Jharkhand, Odisha, and West Bengal. Northeast: Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim, and Tripura. Western: Goa, Gujarat, and Maharashtra. South: Andhra Pradesh, Karnataka, Kerala, Tamil Nadu, and Telangana. Union territories: Andaman and Nicobar Islands, Chandigarh, Dadra and Nagar Haveli, Daman and Diu, Delhi, Lakshadweep, and Puducherry.

Return to your place in the textFIGURE. Prevalence of cervical cancer screening among women aged 30–49 years, by district — National Family Health Survey-4, India, 2015–2016
The figure is a map showing the prevalence of cervical cancer screening among women aged 30–49 years, by district in India during 2015–2016, according to the National Family Health Survey-4.

Suggested citation for this article: Van Dyne EA, Hallowell BD, Saraiya M, et al. Establishing Baseline Cervical Cancer Screening Coverage — India, 2015–2016. MMWR Morb Mortal Wkly Rep 2019;68:14–19. DOI: http://dx.doi.org/10.15585/mmwr.mm6801a4.

MMWR and Morbidity and Mortality Weekly Report are service marks of the U.S. Department of Health and Human Services.
Use of trade names and commercial sources is for identification only and does not imply endorsement by the U.S. Department of Health and Human Services.
References to non-CDC sites on the Internet are provided as a service to MMWR readers and do not constitute or imply endorsement of these organizations or their programs by CDC or the U.S. Department of Health and Human Services. CDC is not responsible for the content of pages found at these sites. URL addresses listed in MMWR were current as of the date of publication.

All HTML versions of MMWR articles are generated from final proofs through an automated process. This conversion might result in character translation or format errors in the HTML version. Users are referred to the electronic PDF version (https://www.cdc.gov/mmwr) and/or the original MMWR paper copy for printable versions of official text, figures, and tables.

Questions or messages regarding errors in formatting should be addressed to mmwrq@cdc.gov.

TOP