Cancer morbidity trends and regional differences in England-A Bayesian analysis

PLoS One. 2020 May 20;15(5):e0232844. doi: 10.1371/journal.pone.0232844. eCollection 2020.

Abstract

Reliable modelling of the dynamics of cancer morbidity risk is important, not least due to its significant impact on healthcare and related policies. We identify morbidity trends and regional differences in England for all-cancer and type-specific incidence between 1981 and 2016. We use Bayesian modelling to estimate cancer morbidity incidence at various age, year, gender, and region levels. Our analysis shows increasing trends in most rates and marked regional variations that also appear to intensify through time in most cases. All-cancer rates have increased significantly, with the highest increase in East, North West and North East. The absolute difference between the rates in the highest- and lowest-incidence region, per 100,000 people, has widened from 39 (95% CI 33-45) to 86 (78-94) for females, and from 94 (85-104) to 116 (105-127) for males. Lung cancer incidence for females has shown the highest increase in Yorkshire and the Humber, while for males it has declined in all regions with the highest decrease in London. The gap between the highest- and lowest-incidence region for females has widened from 47 (42-51) to 94 (88-100). Temporal change in in bowel cancer risk is less manifested, with regional heterogeneity also declining. Prostate cancer incidence has increased with the highest increase in London, and the regional gap has expanded from 33 (30-36) to 76 (69-83). For breast cancer incidence the highest increase has occurred in North East, while the regional variation shows a less discernible increase. The analysis reveals that there are important regional differences in the incidence of all-type and type-specific cancers, and that most of these regional differences become more pronounced over time. A significant increase in regional variation has been demonstrated for most types of cancer examined here, except for bowel cancer where differences have narrowed.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Age Distribution
  • Aged
  • Aged, 80 and over
  • Bayes Theorem
  • Breast Neoplasms / epidemiology
  • Child
  • Child, Preschool
  • England / epidemiology
  • Female
  • Geography, Medical
  • Humans
  • Incidence
  • Infant
  • Infant, Newborn
  • Intestinal Neoplasms / epidemiology
  • Lung Neoplasms / epidemiology
  • Male
  • Middle Aged
  • Morbidity / trends
  • Neoplasms / epidemiology*
  • Prostatic Neoplasms / epidemiology
  • Sex Distribution
  • Young Adult

Grants and funding

This work was funded by the Institute and Faculty of Actuaries, under a research project on "Modelling measurement and management of longevity and morbidity risk" (project ID: ARC001). GS also received financial support by the Society of Actuaries, under a research project on "Predictive modelling for medical morbidity trends related to insurance.” The funders did not play any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. All the views presented in this paper are of the authors only.