Secular trends, race, and geographic disparity of early-stage breast cancer incidence: 25 years of surveillance in Connecticut

Am J Public Health. 2015 Jul;105 Suppl 3(Suppl 3):e64-70. doi: 10.2105/AJPH.2015.302640. Epub 2015 Apr 23.

Abstract

Objectives: We considered changes in the geographic distribution of early stage breast cancer among White and non-White women while secular trends in lifestyle and health care were under way.

Methods: We aggregated tumor registry and census data by age, race, place of residence, and year of diagnosis to evaluate rate variation across Connecticut census tracts between 1985 and 2009. Global and local cluster detection tests were completed.

Results: Age-adjusted incidence rates increased by 2.71% and 0.44% per year for White and non-White women, respectively. Significant global clustering was identified during surveillance of these populations, but the elements of clustering differed between groups. Among White women, fewer local clusters were detected after 1985 to 1989, whereas clustering increased over time among non-White women.

Conclusions: Small-area variation of breast cancer incidence rates across time periods proved to be dynamic and race-specific. Incidence rates might have been affected by secular trends in lifestyle or health care. Single cross-sectional analyses might have confused our understanding of disease occurrence by not accounting for the social context in which patient preferences or provider capacity influence the numbers and locations of diagnosed cases. Serial analyses are recommended to identify "hot spots" where persistent geographic disparities in incidence occur.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Breast Neoplasms / diagnostic imaging
  • Breast Neoplasms / epidemiology*
  • Breast Neoplasms / ethnology*
  • Connecticut / epidemiology
  • Female
  • Geography
  • Humans
  • Incidence
  • Mammography / statistics & numerical data
  • Middle Aged
  • Population Surveillance
  • Prognosis
  • Racial Groups
  • Registries
  • Small-Area Analysis
  • Survival Analysis