The determinants of cervical cancer screening uptake in women with obesity: application of the Andersen’s behavioral model to the CONSTANCES survey

  • Jeanna-eve FranckEmail author
  • Virginie Ringa
  • Mireille Cœuret-Pellicer
  • Pierre Chauvin
  • Gwenn Menvielle
Original Paper



Despite their higher risk for and mortality from cervical cancer, evidence indicates low rates of cervical cancer screening (CCS) among women with obesity. The literature on the specific factors related to CCS nonadherence in this population is limited.


We examined the data on 2,934 women with obesity included in the CONSTANCES survey from 2012 to 2015. Using the Andersen’s behavioral model, we studied the relationships between the socioeconomic, sociodemographic, health, health personal behaviors, and healthcare use-related factors with CCS nonadherence. The analysis was performed using structural equation models.


Regular follow-up by a gynecologist, good quality of primary care follow-up, and comorbidities were negatively associated with CCS nonadherence. Limited literacy, older age, being single, living without children, and financial strain were positively associated with CCS nonadherence. Our results do not point to competitive care, since women with comorbidities had better CCS behaviors, which were explained by a good quality of primary care follow-up.


Our study identified the factors that explain CCS nonadherence among women with obesity and clarified the effects of health status and healthcare use on screening. Further efforts should be undertaken to reduce the obstacles to CCS by improving care among women with obesity.


Cervical cancer screening Obesity Healthcare use Health status Competitive care Andersen’s model 



We thank the Inserm-Versailles Saint Quentin en Yvelines University “Epidemiological Population-Based Cohorts Unit” (UMS 11) who designed and is in charge of the CONSTANCES Cohort Study. They also thank the “Caisse nationale d’assurance maladie des travailleurs salaries” (CNAMTS) and the “Centres d’examens de santé” of the French Social Security which are collecting a large part of the data, as well as the “Caisse nationale d’assurance vieillesse”, ClinSearch, Asqualab and Eurocell in charge of the data quality control.

Author contributions

GM and JF designed the study. JF ran the analyses and wrote the paper. JF and MP prepared the dataset. All authors discussed the results and their interpretation, participated to the writing of the paper and approved the final version of the manuscript.


This work was supported by a Grant from the French Agency on Cancer (INCa, Grant Number 2014-1-PL SHS-05); the CONSTANCES cohort benefits from a Grant from ANR (Grant Number ANR-11-INBS-0002); CONSTANCES is also partly funded by MSD, AstraZeneca and Lundbeck.

Compliance with ethical standards

Conflict of interest

The authors do not have competing interests to declare.


  1. 1.
    INCa (2016) Les cancers en France en 2015 (French)Google Scholar
  2. 2.
    Barré S, Massetti M, Leleu H, Catajar N, de Bels F (2017) Characteristics of French women who fail to undergo regular Pap smears for cervical cancer screening. BEH 2–3:39–47 (French)Google Scholar
  3. 3.
    ObEpi (2012) Enquête épidémiologique nationale sur le surpoids et l’obésité (French)Google Scholar
  4. 4.
    Aldrich T, Hackley B (2010) The impact of obesity on gynecologic cancer screening: an integrative literature review. J Midwifery Womens Health 55:344–356CrossRefGoogle Scholar
  5. 5.
    Maruthur NM, Bolen SD, Brancati FL, Clark JM (2009) The association of obesity and cervical cancer screening: a systematic review and meta-analysis. Obesity (Silver Spring) 17:375–381CrossRefGoogle Scholar
  6. 6.
    Friedman AM, Hemler JR, Rossetti E, Clemow LP, Ferrante JM (2012) Obese women’s barriers to mammography and Pap smear: the possible role of personality. Obesity (Silver Spring) 20:1611–1617CrossRefGoogle Scholar
  7. 7.
    Joy D, Amanda F, Heather H, Suzanne L (2018) Provider weight-bias and how it contributes to healthcare disparities of obese patients. Interv Obes Diabetes.
  8. 8.
    Seymour J, Barnes JL, Schumacher J, Vollmer RL (2018) A qualitative exploration of weight bias and quality of health care among health care professionals using hypothetical patient scenarios. Inquiry 55:46958018774171PubMedGoogle Scholar
  9. 9.
    Bertakis KD, Azari R (2005) The impact of obesity on primary care visits. Obes Res 13:1615–1623CrossRefGoogle Scholar
  10. 10.
    Pearson WS, Bhat-Schelbert K, Ford ES, Mokdad AH (2009) The impact of obesity on time spent with the provider and number of medications managed during office-based physician visits using a cross-sectional, national health survey. BMC Public Health 9:436CrossRefGoogle Scholar
  11. 11.
    Ferrante JM, Chen PH, Crabtree BF, Wartenberg D (2007) Cancer screening in women: body mass index and adherence to physician recommendations. Am J Prev Med 32:525–531CrossRefGoogle Scholar
  12. 12.
    Diaz A, Kang J, Moore SP, Baade P, Langbecker D, Condon JR et al (2017) Association between comorbidity and participation in breast and cervical cancer screening: a systematic review and meta-analysis. Cancer Epidemiol 47:7–19CrossRefGoogle Scholar
  13. 13.
    Hernandez-Boussard T, Ahmed SM, Morton JM (2012) Obesity disparities in preventive care: findings from the National Ambulatory Medical Care Survey, 2005–2007. Obesity (Silver Spring) 20:1639–1644CrossRefGoogle Scholar
  14. 14.
    Peytremann-Bridevaux I, Santos-Eggimann B (2007) Healthcare utilization of overweight and obese Europeans aged 50–79 years. J Public Health 15:377–384CrossRefGoogle Scholar
  15. 15.
    Labeit AM, Peinemann F (2017) Determinants of a GP visit and cervical cancer screening examination in Great Britain. PLoS ONE 12:e0174363CrossRefGoogle Scholar
  16. 16.
    Sicsic J, Franc C (2014) Obstacles to the uptake of breast, cervical, and colorectal cancer screenings: what remains to be achieved by French national programmes? BMC Health Serv Res 14:465CrossRefGoogle Scholar
  17. 17.
    Andersen RM (1995) Revisiting the behavioral model and access to medical care: does it matter? J Health Soc Behav 36:1–10CrossRefGoogle Scholar
  18. 18.
    Zins M, Goldberg M, CONSTANCES Team (2015) The French CONSTANCES population-based cohort: design, inclusion and follow-up. Eur J Epidemiol 30:1317–1328CrossRefGoogle Scholar
  19. 19.
    Haute Autorité de Santé (2010) Dépistage du cancer du col de l’utérus (French). https://www.has-santefr/portail/jcms/r_1501380/fr/depistage-du-cancer-du-col-de-l-uterus. Accessed 26 Sep 2018
  20. 20.
    Beran TN, Violato C (2010) Structural equation modeling in medical research: a primer. BMC Res Notes 3:267CrossRefGoogle Scholar
  21. 21.
    van Buuren S (2007) Multiple imputation of discrete and continuous data by fully conditional specification. Stat Methods Med Res 16:219–242CrossRefGoogle Scholar
  22. 22.
    Duport N, Serra D, Goulard H, Bloch J (2008) Which factors influence screening practices for female cancer in France? Rev Epidemiol Sante Publique 56:303–313CrossRefGoogle Scholar
  23. 23.
    Damiani G, Basso D, Acampora A, Bianchi CB, Silvestrini G, Frisicale EM et al (2015) The impact of level of education on adherence to breast and cervical cancer screening: evidence from a systematic review and meta-analysis. Prev Med 81:281–289CrossRefGoogle Scholar
  24. 24.
    Kilfoyle KA, Vitko M, O’Conor R, Bailey SC (2016) Health literacy and women’s reproductive health: a systematic review. J Womens Health (Larchmt) 25:1237–1255CrossRefGoogle Scholar
  25. 25.
    Kim K, Han HR (2016) Potential links between health literacy and cervical cancer screening behaviors: a systematic review. Psychooncology 25:122–130CrossRefGoogle Scholar
  26. 26.
    Nutbeam D (2000) Health literacy as a public health goal: a challenge for contemporary health education and communication strategies into the 21st century. Health Promot Int 15:259–267CrossRefGoogle Scholar
  27. 27.
    Amy NK, Aalborg A, Lyons P, Keranen L (2006) Barriers to routine gynecological cancer screening for White and African-American obese women. Int J Obes (Lond) 30:147–155CrossRefGoogle Scholar
  28. 28.
    Phelan SM, Burgess DJ, Yeazel MW, Hellerstedt WL, Griffin JM, van Ryn M (2015) Impact of weight bias and stigma on quality of care and outcomes for patients with obesity. Obes Rev 16:319–326CrossRefGoogle Scholar
  29. 29.
    Fjaer EL, Balaj M, Stornes P, Todd A, McNamara CL, Eikemo TA (2017) Exploring the differences in general practitioner and health care specialist utilization according to education, occupation, income and social networks across Europe: findings from the European social survey (2014) special module on the social determinants of health. Eur J Public Health 27:73–81CrossRefGoogle Scholar
  30. 30.
    Droomers M, Westert GP (2004) Do lower socioeconomic groups use more health services, because they suffer from more illnesses? Eur J Public Health 14:311–313CrossRefGoogle Scholar
  31. 31.
    Damiani G, Federico B, Basso D, Ronconi A, Bianchi CB, Anzellotti GM et al (2012) Socioeconomic disparities in the uptake of breast and cervical cancer screening in Italy: a cross sectional study. BMC Public Health 12:99CrossRefGoogle Scholar
  32. 32.
    Mitchell RS, Padwal RS, Chuck AW, Klarenbach SW (2008) Cancer screening among the overweight and obese in Canada. Am J Prev Med 35:127–132CrossRefGoogle Scholar
  33. 33.
    Lee JA, Pause CJ (2016) Stigma in practice: barriers to health for fat women. Front Psychol 7:2063PubMedPubMedCentralGoogle Scholar
  34. 34.
    Ferrante JM, Ohman-Strickland P, Hudson SV, Hahn KA, Scott JG, Crabtree BF (2006) Colorectal cancer screening among obese versus non-obese patients in primary care practices. Cancer Detect Prev 30:459–465CrossRefGoogle Scholar
  35. 35.
    Ornstein SM, Jenkins RG, Litvin CB, Wessell AM, Nietert PJ (2013) Preventive services delivery in patients with chronic illnesses: parallel opportunities rather than competing obligations. Ann Fam Med 11:344–349CrossRefGoogle Scholar
  36. 36.
    Richard A, Rohrmann S, Schmid SM, Tirri BF, Huang DJ, Guth U et al (2015) Lifestyle and health-related predictors of cervical cancer screening attendance in a Swiss population-based study. Cancer Epidemiol 39:870–876CrossRefGoogle Scholar
  37. 37.
    Fedewa SA, Sauer AG, Siegel RL, Jemal A (2015) Prevalence of major risk factors and use of screening tests for cancer in the United States. Cancer Epidemiol Biomark Prev 24:637–652CrossRefGoogle Scholar
  38. 38.
    Cleron E (2015) Femme et sport. Bull stat d’études n°15Google Scholar
  39. 39.
    Clarke MA, Fetterman B, Cheung LC, Wentzensen N, Gage JC, Katki HA et al (2018) Epidemiologic evidence that excess body weight increases risk of cervical cancer by decreased detection of precancer. J Clin Oncol 36:1184–1191CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Social Epidemiology, Institut Pierre Louis D’Epidémiologie Et de Santé Publique IPLESPSorbonne Université, INSERMParisFrance
  2. 2.INSERM, Univ Paris-Saclay, Univ Paris-Sud, UVSQ, CESPVillejuifFrance
  3. 3.Population-Based Epidemiologic Cohorts UnitINSERM, UMS 011VillejuifFrance
  4. 4.INSERM IPLESP – ERESParisFrance

Personalised recommendations