The geographic distribution of breast cancer incidence in Massachusetts 1988 to 1997, adjusted for covariates
<p>Abstract</p> <p>Background</p> <p>The aims of this study were to determine whether observed geographic variations in breast cancer incidence are random or statistically significant, whether statistically significant excesses are temporary or time-persistent, and whet...
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doaj-c0725a0bbd8e493b87cdc664b42c3f712020-11-24T21:44:20ZengBMCInternational Journal of Health Geographics1476-072X2004-08-01311710.1186/1476-072X-3-17The geographic distribution of breast cancer incidence in Massachusetts 1988 to 1997, adjusted for covariatesGershman SusanGregorio David IKulldorff MartinDeChello Laurie MJoseph Sheehan TMroszczyk Mary<p>Abstract</p> <p>Background</p> <p>The aims of this study were to determine whether observed geographic variations in breast cancer incidence are random or statistically significant, whether statistically significant excesses are temporary or time-persistent, and whether they can be explained by covariates such as socioeconomic status (SES) or urban/rural status?</p> <p>Results</p> <p>A purely spatial analysis found fourteen geographic areas that deviated significantly from randomness: ten with higher incidence rates than expected, four lower than expected. After covariate adjustment, three of the ten high areas remained statistically significant and one new high area emerged. The space-time analysis identified eleven geographic areas as statistically significant, seven high and four low. After covariate adjustment, four of the seven high areas remained statistically significant and a fifth high area also identified in the purely spatial analysis emerged.</p> <p>Conclusions</p> <p>These analyses identify geographic areas with invasive breast cancer incidence higher or lower than expected, the times of their excess, and whether or not their status is affected when the model is adjusted for risk factors. These surveillance findings can be a sound starting point for the epidemiologist and has the potential of monitoring time trends for cancer control activities.</p> http://www.ij-healthgeographics.com/content/3/1/17 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Gershman Susan Gregorio David I Kulldorff Martin DeChello Laurie M Joseph Sheehan T Mroszczyk Mary |
spellingShingle |
Gershman Susan Gregorio David I Kulldorff Martin DeChello Laurie M Joseph Sheehan T Mroszczyk Mary The geographic distribution of breast cancer incidence in Massachusetts 1988 to 1997, adjusted for covariates International Journal of Health Geographics |
author_facet |
Gershman Susan Gregorio David I Kulldorff Martin DeChello Laurie M Joseph Sheehan T Mroszczyk Mary |
author_sort |
Gershman Susan |
title |
The geographic distribution of breast cancer incidence in Massachusetts 1988 to 1997, adjusted for covariates |
title_short |
The geographic distribution of breast cancer incidence in Massachusetts 1988 to 1997, adjusted for covariates |
title_full |
The geographic distribution of breast cancer incidence in Massachusetts 1988 to 1997, adjusted for covariates |
title_fullStr |
The geographic distribution of breast cancer incidence in Massachusetts 1988 to 1997, adjusted for covariates |
title_full_unstemmed |
The geographic distribution of breast cancer incidence in Massachusetts 1988 to 1997, adjusted for covariates |
title_sort |
geographic distribution of breast cancer incidence in massachusetts 1988 to 1997, adjusted for covariates |
publisher |
BMC |
series |
International Journal of Health Geographics |
issn |
1476-072X |
publishDate |
2004-08-01 |
description |
<p>Abstract</p> <p>Background</p> <p>The aims of this study were to determine whether observed geographic variations in breast cancer incidence are random or statistically significant, whether statistically significant excesses are temporary or time-persistent, and whether they can be explained by covariates such as socioeconomic status (SES) or urban/rural status?</p> <p>Results</p> <p>A purely spatial analysis found fourteen geographic areas that deviated significantly from randomness: ten with higher incidence rates than expected, four lower than expected. After covariate adjustment, three of the ten high areas remained statistically significant and one new high area emerged. The space-time analysis identified eleven geographic areas as statistically significant, seven high and four low. After covariate adjustment, four of the seven high areas remained statistically significant and a fifth high area also identified in the purely spatial analysis emerged.</p> <p>Conclusions</p> <p>These analyses identify geographic areas with invasive breast cancer incidence higher or lower than expected, the times of their excess, and whether or not their status is affected when the model is adjusted for risk factors. These surveillance findings can be a sound starting point for the epidemiologist and has the potential of monitoring time trends for cancer control activities.</p> |
url |
http://www.ij-healthgeographics.com/content/3/1/17 |
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