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Residential mobility and breast cancer in Marin County, California, USA.

Jacquez GM, Barlow J, Rommel R, Kaufmann A, Rienti M, AvRuskin G, Rasul J - Int J Environ Res Public Health (2013)

Bottom Line: Analysis found significant global clustering of cases localized to specific residential histories and times.However, persistent case-clustering of greater than fifteen years duration was also detected.A biologically plausible exposure or risk factor has yet to be identified.

View Article: PubMed Central - PubMed

Affiliation: BioMedware, Inc., 3526 West Liberty, Suite 100, Ann Arbor, MI 48103, USA. gjacquez@buffalo.edu.

ABSTRACT
Marin County (California, USA) has among the highest incidences of breast cancer in the U.S. A previously conducted case-control study found eight significant risk factors in participants enrolled from 1997-1999. These included being premenopausal, never using birth control pills, lower highest lifetime body mass index, having four or more mammograms from 1990-1994, beginning drinking alcohol after age 21, drinking an average two or more alcoholic drinks per day, being in the highest quartile of pack-years of cigarette smoking, and being raised in an organized religion. Previously conducted surveys provided residential histories; while statistic accounted for participants' residential mobility, and assessed clustering of breast cancer cases relative to controls based on the known risk factors. These identified specific cases, places, and times of excess breast cancer risk. Analysis found significant global clustering of cases localized to specific residential histories and times. Much of the observed clustering occurred among participants who immigrated to Marin County. However, persistent case-clustering of greater than fifteen years duration was also detected. Significant case-clustering among long-term residents may indicate geographically localized risk factors not accounted for in the study design, as well as uncertainty and incompleteness in the acquired addresses. Other plausible explanations include environmental risk factors and cases tending to settle in specific areas. A biologically plausible exposure or risk factor has yet to be identified.

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Related in: MedlinePlus

Residential histories as space-time step functions. The axes x and y define a geographic domain (i.e., longitude and latitude decimal degrees), the t axes represents time (i.e., date). The study extends from time t0 to time tT. The residential histories for persons i and j are shown as step functions through space-time. For example, person i begins the study residing at location xi, yi, t0. They remain at that geographic coordinate until the instant before time t1, when they move to xi, yi, t1. The duration of time they reside at this first place of residence is ω0.
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ijerph-11-00271-f001: Residential histories as space-time step functions. The axes x and y define a geographic domain (i.e., longitude and latitude decimal degrees), the t axes represents time (i.e., date). The study extends from time t0 to time tT. The residential histories for persons i and j are shown as step functions through space-time. For example, person i begins the study residing at location xi, yi, t0. They remain at that geographic coordinate until the instant before time t1, when they move to xi, yi, t1. The duration of time they reside at this first place of residence is ω0.

Mentions: The data were loaded into BioMedware’s SpaceStat software, which represents residential histories as a space-time step function (Figure 1). This is a fundamentally different representation than that typically used with geographic data from case control studies as it represents places of residence as space-time threads (those locations where people lived throughout the study period—their residential history) rather than as spatial point distributions that are a disconnected set of points in space-time. The duration of place of residence is part of the data representation in Figure 1—how long a person resides at a given location clearly may impact their exposure [6], and therefore is incorporated into the underlying data model. Linked cartographic and statistical brushing of time-dynamic data on maps, histograms and time plots [7], was then used to quantify different aspects of residential mobility.


Residential mobility and breast cancer in Marin County, California, USA.

Jacquez GM, Barlow J, Rommel R, Kaufmann A, Rienti M, AvRuskin G, Rasul J - Int J Environ Res Public Health (2013)

Residential histories as space-time step functions. The axes x and y define a geographic domain (i.e., longitude and latitude decimal degrees), the t axes represents time (i.e., date). The study extends from time t0 to time tT. The residential histories for persons i and j are shown as step functions through space-time. For example, person i begins the study residing at location xi, yi, t0. They remain at that geographic coordinate until the instant before time t1, when they move to xi, yi, t1. The duration of time they reside at this first place of residence is ω0.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3924444&req=5

ijerph-11-00271-f001: Residential histories as space-time step functions. The axes x and y define a geographic domain (i.e., longitude and latitude decimal degrees), the t axes represents time (i.e., date). The study extends from time t0 to time tT. The residential histories for persons i and j are shown as step functions through space-time. For example, person i begins the study residing at location xi, yi, t0. They remain at that geographic coordinate until the instant before time t1, when they move to xi, yi, t1. The duration of time they reside at this first place of residence is ω0.
Mentions: The data were loaded into BioMedware’s SpaceStat software, which represents residential histories as a space-time step function (Figure 1). This is a fundamentally different representation than that typically used with geographic data from case control studies as it represents places of residence as space-time threads (those locations where people lived throughout the study period—their residential history) rather than as spatial point distributions that are a disconnected set of points in space-time. The duration of place of residence is part of the data representation in Figure 1—how long a person resides at a given location clearly may impact their exposure [6], and therefore is incorporated into the underlying data model. Linked cartographic and statistical brushing of time-dynamic data on maps, histograms and time plots [7], was then used to quantify different aspects of residential mobility.

Bottom Line: Analysis found significant global clustering of cases localized to specific residential histories and times.However, persistent case-clustering of greater than fifteen years duration was also detected.A biologically plausible exposure or risk factor has yet to be identified.

View Article: PubMed Central - PubMed

Affiliation: BioMedware, Inc., 3526 West Liberty, Suite 100, Ann Arbor, MI 48103, USA. gjacquez@buffalo.edu.

ABSTRACT
Marin County (California, USA) has among the highest incidences of breast cancer in the U.S. A previously conducted case-control study found eight significant risk factors in participants enrolled from 1997-1999. These included being premenopausal, never using birth control pills, lower highest lifetime body mass index, having four or more mammograms from 1990-1994, beginning drinking alcohol after age 21, drinking an average two or more alcoholic drinks per day, being in the highest quartile of pack-years of cigarette smoking, and being raised in an organized religion. Previously conducted surveys provided residential histories; while statistic accounted for participants' residential mobility, and assessed clustering of breast cancer cases relative to controls based on the known risk factors. These identified specific cases, places, and times of excess breast cancer risk. Analysis found significant global clustering of cases localized to specific residential histories and times. Much of the observed clustering occurred among participants who immigrated to Marin County. However, persistent case-clustering of greater than fifteen years duration was also detected. Significant case-clustering among long-term residents may indicate geographically localized risk factors not accounted for in the study design, as well as uncertainty and incompleteness in the acquired addresses. Other plausible explanations include environmental risk factors and cases tending to settle in specific areas. A biologically plausible exposure or risk factor has yet to be identified.

Show MeSH
Related in: MedlinePlus