Disparities in Female Breast Cancer Stage at Diagnosis in New Jersey: A Spatial-Temporal Analysis
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Disparities in Female Breast Cancer Stage at Diagnosis in New Jersey: A Spatial-Temporal Analysis

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  • Alternative Title:
    J Public Health Manag Pract
  • Description:

    We used the space-time scan statistic in SaTScan to identify geographic areas and time periods with significantly elevated proportions of female breast cancer diagnosed at the in situ or distant stage in New Jersey. The analyses were conducted with census tracts as the geographic unit of analysis, elliptical spatial windows, 3-year temporal windows, and Poisson models. Statistical significance was determined by 999 Monte Carlo simulations (P < .05); significant clusters were mapped in ArcMap. Breast cancer cases within the clusters were compared with breast cancer cases outside the clusters on demographic, socioeconomic, and clinical factors using the Pearson chi-square test (P < .05). In addition, populations within the clusters were compared with the population outside the clusters on demographic and socioeconomic factors.


    After exclusions, 126 756 cases of primary female breast cancer diagnosed in 1997 to 2011 from the New Jersey State Cancer Registry were included in the analysis. One distant stage breast cancer cluster was identified in northeastern New Jersey from 1997 through 2011 (n = 26 244, relative risk [RR] = 1.42, P < .001). Two in situ breast cancer clusters were found in northeastern New Jersey from 2004 through 2011 (n = 12 496, RR = 1.35, P < .001) and in central New Jersey from 2006 through 2011 (n = 29 319, RR = 1.24, P < .001). The distant stage cluster contained relatively high percentages of minority and lower socioeconomic status (SES) breast cancer cases and populations, whereas the in situ clusters had relatively low percentages of minority and lower SES breast cancer cases and populations.


    Although there have been improvements since an earlier study of distant stage breast cancer diagnosed in 1995 to 1997, disparities in stage at diagnosis continue. These findings can be used by our local cancer control partners to target specific populations for interventions such as breast cancer education and mammography screening, as well as by state legislative and public health authorities for resource allocation.

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