California Breast Cancer Mapping Project Final Report November 2012

7/30/2019 California Breast Cancer Mapping Project Final Report November 2012

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California Breast CancerMapping Project:

Identifying Areas ofConcern in California

November 2012


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California Breast CancerMapping Project:

Identifying Areas ofConcern in California

November 2012


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California Breast Cancer Mapping Project

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The ndings and opinions expressed in this report are those o the CBCMP, or which they are solely responsible. The State o Caliornia and theCaliornia Department o Public Health bear no responsibility or the contents o this report.


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Contents

Acknowledgments v

Preface vii

Executive Summary ix

Introduction 1

A Note on the Term Cancer Cluster 4

Overview of CBCMP Analytic Protocol 5

Overall Results 7

Cancer Surveillance in Rural Areas 9

Implications 11

Breast Cancer, Race, and Ethnicity 13

Results

Results: North San Francisco Bay Area of Concern 15

Results: South San Francisco Bay Area of Concern 27

Results: West Los Angeles/East Ventura Area of Concern 39

Results: South Orange Area of Concern 51

Methods 63

Bibliography 67

Resources 69

Glossary 73


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Preface

As advocates committed to breast cancer prevention, detection,treatment and survivorship, we are well aware o the devastatingimpact o breast cancer on women, men, amilies and commu-nities. We are also aware o the increased lietime risk o gettingbreast cancer, a risk that has grown rom 1 in 20 in the 1960s to 1in 8 today. Progress to reduce the overall burden o breast cancerrequires increasingly-sophisticated health tracking tools that addressgeographic variability, particularly given Caliornias robustly diversepopulations. We are proud to present this report, which uses sophis-ticated statistical methods to produce important geographic mapso elevated invasive breast cancer in Caliornia. We urge advocatesand researchers to ocus attention and resources on these areas to

better understand the population, prevention, early detection, treat-ment and survivorship needs in the state o Caliornia. Such eortswill require that stakeholders work across city or county lines in aspirit o true interdisciplinary collaboration to address yet-unknownand unmet needs. We also hope that public health departments inthese areas and beyond remain highly responsive to communitiesthat have continuing questions and needs or more granular andtimely data on cancer rates among specic populations.

Beyond the ndings presented in this report, we also want to un-derscore the importance o community-based participatory research

(CBPR) to ensure that health mapping and tracking inorms breast

cancer control policy and practice. The Caliornia Breast Cancer Map-ping Project Advisory Group involved a broad cross-section o advo-cates rom breast cancer and community advocacy organizations,environmental health breast cancer organizations, clinical and publichealth practitioners, and researchers. Together, we inormed everystep o this study, including identiying the most inormative statisticalapproach (using the Scan Statistic described in the report), identiy-ing criteria or minimizing alse positive areas, and guiding the devel-opment o this report. Such a process showed great respect or thediversity o advocacy opinions. We are proud to have modeled a pro-cess that values such substantive input on the study, and are commit-

ted to continuing to serve as bridges to our respective communitiesto ensure the translation o this science to practice. We urge breastcancer researchers everywhere to use such CBPR protocols and pro-cesses to maximize the responsiveness and relevance o research tocommunities needs around breast cancer. Indeed, given the impor-tance o health tracking and disease mapping, we hope the processesand protocols described in this report become models or preventingand/or addressing health disparities throughout Caliornia.

The CBCMP Advisory Group


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Executive Summary

Breast cancer is the most common cancer among women in Calior-nia, with an average o 26,300 new cases diagnosed every year and4,175 deaths rom breast cancer occurring annually.1 Data about whois aected by breast cancer is essential to the eorts o the broadarray o stakeholders working to identiy, treat, and support wom-en with breast cancer and to understand and prevent the disease.

These stakeholders include breast cancer and community advocacyorganizations, clinical and public health practitioners, researchers,and other concerned citizens.

The Need for Breast Cancer Maps

Disease mapping, or the display o disease data on maps, is one othe most commonly requested services among local and state publichealth agencies.2,3,4 Although state agencies such as cancer registriesoten produce cancer maps or the public, such maps generally showonly the cancer rate or each county. This can be limiting or stake-holders who are interested in cancer as it relates to towns and neigh-borhoods. Fortunately, advances in the elds o epidemiology and sta-tistics now enable the creation o statistically reliable maps that are notlimited by county boundaries and still maintain patient condentiality.

The Caliornia Breast Cancer Mapping Project (CBCMP) was unded

by the Caliornia Breast Cancer Research Program rom 2009 through2011 to explore the technical easibility o mapping areas in the statewith elevated cancer rates in a manner that is determined to be use-

ul by the breast cancer stakeholder community. An advisory group(AG) o breast cancer advocates, clinicians, and public health practi-tioners engaged in a process to develop a protocol or creating suchmaps. In addition to the statistical method used to identiy areaswith elevated rates o breast cancer, the CBCMP protocol includessteps to remove misleading results arising rom limitations in thedata themselves, to characterize the women diagnosed with cancer,and to describe the population living in areas with elevated rates.

Project sta used the CBCMP protocol to analyze and map invasivebreast cancer among women in Caliornia rom 2000 through 2008.

Areas of Concern Identified forCalifornia

For the rst time in Caliornia, the CBCMP has produced maps identiy-ing areasno longer restricted by county boundarieswith elevat-ed rates o invasive breast cancer or the entire state. These maps, alongwith the protocol used to create them, are presented in this report.

The maps show our areas, two in the San Francisco Bay region andtwo in the Los Angeles-Orange County region, or which the age-ad-

justed incidence o invasive breast cancer appears to be 1020%

higher than or the rest o the state. Further analyses were conduct-ed to characterize the women diagnosed with breast cancer and thegeneral population in these areas o concern. With a ew exceptions,

1 Caliornia Cancer Registry (2009). Trends in Cancer Incidence, Mortality, Risk Factors, and Health B ehaviors in Caliornia.

2 Bell B, Hoskins R, Pickle L, Wartenberg D. Current practices in spatial analysis o cancer data: Mapping health statistics to inorm policy makers and the public. International Journal o HealthGeographics. 2006;5.

3 Roberts E, English P, Wong M, Wol C, Falade M. Continuous Local Rate Modeling or Communication in Public Health: A Practical Approach. Journal o Public Health Management and Prac-tice. 2008;14(6):562-568.

4 Roberts EM, English P, Wong M, et al. Progress in Pediatric Asthma Surveillance II: Geospatial Patterns of Asthma in Alameda County, California. Preventing Chronic Disease. 2006;3(3).


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the ndings reect known sociodemographic patterns in breast can-cer risk or the state.

Because the statistical method used in the CBCMP protocol diers romthose used conventionally, individual counties that may have beenpreviously identied as having signicantly elevated rates through oth-

er statistical methods may not show up in these maps. Previously doc-umented inormation about rates or specic counties is still valid andshould not be considered undermined by the CBCMP maps.

Conclusions

The CBCMP successully demonstrated the ability to identiy areaswith elevated breast cancer risk in Caliornia irrespective o countyboundaries, while maintaining condentiality, eliminating alse pos-itives, and accounting or the age distribution within the population

as well as large increases in population size. Because the maps arebased on census tracts, additional inormation rom the U.S. Censusabout the sociodemographics o the areas o concern can also bepresented and compared to that or the state.

The project also identied limitations o the CBCMP protocol, mostnotably the size o the detectable area. For a group o 50 censustracts, an invasive breast cancer rate that is 50% greater than that

o the overall state can be reliably detected. An area composed oewer tracts will require a larger increase or detection, while anarea composed o more tracts will require less o an increase. In ourndings, the areas that came to attention had rate increases smallerthan 50% but were detectable because they included a much largernumbers o tracts.

Where Do We Go from Here?

Implications for Statewide Mapping

Details o the process and deliberations o the CBCMP AG have beenpublished in a peer-reviewed manuscript.5 The AG concluded thatpublic agencies should augment their surveillance activities to in-clude the CBCMP protocol (or an adapted orm thereo ) to detectand characterize regions o the state with elevated breast cancer risk

on a routine basis. While in general very little is known about whatcauses the rates o invasive breast cancer in one population to behigher than another, mapping variations in breast cancer risk canenable communities, breast cancer advocates, public health prac-titioners, and other breast cancer stakeholders to identiy commu-nities most impacted by breast cancer, explore resource needs andopportunities, and dene concerns.

5 Roberts EM, et al (in press). Guidelines or the Mapping o Cancer Registry Data: Results rom a Breast Cancer Expert Panel Study. Journal o Public Health Management and Practice. Avail-

able at www.caliorniabreastcancermapping.org.
http://www.californiabreastcancermapping.org/http://www.californiabreastcancermapping.org/


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Introduction

Breast Cancer Data for the

General Public

Breast cancer is the most common cancer among women in Cali-ornia, with an average o 26,300 new cases diagnosed every yearand 4,175 deaths rom breast cancer occurring annually.6 Accordingto the American Cancer Society, the chance o a woman having in-vasive breast cancer some time during her lie is about 1 in 8.7

The need or breast cancer data by communities, advocates, and otherbreast cancer stakeholders is oten motivated by the desire to ensuresufcient breast cancer services are available, to understand behavior-

al and environmental risk actors or breast cancer, and to understandwhy breast cancer aects so many women. Not surprisingly, one othe most common requests made to local and state public healthagencies is or data in the orm o maps.8,9,10 When eective, diseasemaps present critical inormation in a manner useul to a broad arrayo stakeholders, and they can be valuable or any community seekingto understand its collective vulnerability and access to resources.11,12,13

In Caliornia, local public health departments and the Caliornia Can-cer Registry (CCR) requently receive such requests or breast cancerdata and inormation. Although these agencies oten produce maps

or public dissemination, these maps generally only show the breastcancer rate or each county. This county-level only restriction can

be rustrating, since there is oten a need to understand risk, explore

resources, or take action at the town or neighborhood level.

Challenges in Mapping Breast Cancer

There are numerous challenges to mapping cancer rates by areassmaller than counties (such as census tracts). The smaller the area inquestion or the rarer the disease, the greater the ollowing problemsbecome: (1) rates becoming less reliable and less inormative and (2)the possibility o disclosing patient identity which is both unethi-cal and restricted by law increases.

With the methods most oten used by public agencies, it is virtu-ally impossible to calculate rates and create maps or areas smallerthan a county without running into the above problems, even or a

disease as common as breast cancer. Using these methods, the onlyoption is to combine several years o breast cancer data, which limitsones ability to know how patterns may change over time.

Fortunately, since the 1990s, statisticians have developed methodsor calculating and mapping rates or small areas that both protectcondentiality and avoid unreliable rates. With so many statisticalmethods to choose rom, it is important to engage stakeholders

who use breast cancer data to determine which methods best meettheir needs and priorities.

6 Seenote 1.

7 American Cancer Society (2011). Breast Cancer Overview: How many women get breast cancer?Retrieved rom www.cancer.org/cancer/breastcancer/overviewguide/breast-cancer-over-view-key-statistics, July 18, 2011.6.

8 See note 2.

9 Seenote 3.

10 See note 4.

11 Beyer K, Rushton G. Mapping Cancer or Community Engagement. Preventing Chronic Disease. 2009;6(1):1-8.

12 Driedger S, Kothari A, Morrison J, Sawada M, Crighton E, Graham I. Using Participatory Design to Develop (Public) Health Decision Support Systems through GIS. International Journal oHealth Geographics. 2007;6.

13 Heitgerd J, Dent A, Holt J, et al. Community Health Status Indicators: Adding a Geospatial Component. Preventing Chronic Disease. 2008;5(3):1-5.
http://www.cancer.org/cancer/breastcancer/overviewguide/breast-cancer-overview-key-statisticshttp://www.cancer.org/cancer/breastcancer/overviewguide/breast-cancer-overview-key-statisticshttp://www.cancer.org/cancer/breastcancer/overviewguide/breast-cancer-overview-key-statisticshttp://www.cancer.org/cancer/breastcancer/overviewguide/breast-cancer-overview-key-statistics


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The California Breast CancerMapping Project

The Caliornia Breast Cancer Mapping Project (CBCMP) was created inresponse to these challenges in mapping breast cancer. The CBCMP,

unded by the Caliornia Breast Cancer Research Program rom 2009through 2011, consisted o project sta and an Advisory Group (AG)o advocates, clinicians, and public health proessionals in Caliornias

breast cancer community, all working together to develop a proto-col or statewide breast cancer mapping.

Beore initiating the protocol development process, the AG engagedin discussions exploring whether sub-county maps would be useulin their work. The AG determined that sub-county maps could beused or identiying vulnerable communities, targeting services, andincreasing knowledge about the social and environmental actors

contributing to breast cancer in aected communities. The AG alsoacknowledged that while mapped data can be useul or generatingresearch questions, the maps themselves cannot provide inormationabout what causes breast cancer in a community. Details o the AGdeliberations have been published in a peer-reviewed manuscript.14

For the development o the protocol, the AG reviewed the charac-teristics o several statistical methods and articulated priorities toguide how they could be used. Among their decisions was that thestatistical method known as the Scan Statistic, when combined withsteps to correct or data limitations, should be used to detect andcharacterize sub-county regions o the state with elevated breastcancer risk.

The CBCMP Protocol

The CBCMP protocol is centered on the Scan Statistic, which isamong the most reviewed and analyzed approaches to disease map-

ping in the epidemiological literature. In addition to this method, theprotocol includes steps to (1) remove misleading results arising romlimitations inherent in the data and (2) dene the boundaries o ar-eas o concern so that they can be examined consistently over time.

The CBCMP protocol identies areas o concern, which we dene as

collections o census tracts in Caliornia with elevated age-adjustedrates o invasive breast cancer that cannot be attributed to popu-lation growth, limitations inherent in the data, or random chance.Within an area o concern, the specic groups o census tracts iden-tied by Scan Statistic as having elevated rates can dier rom year-to-year.

An overview (page 5) and a more detailed discussion (page 63) othe analysis using the CBCMP protocol are included in this report.

About this ReportTo demonstrate and explore the implications o the CBCMP protocol,project sta used the protocol to analyze and map nine years o dataon women diagnosed with invasive breast cancer in Caliornia.

Included in this report are:

Statewide maps o areas o concern or invasive breast cancer

Time-series maps showing changes in census tracts identied bythe Scan Statistic over time within each area o concern

Demographic analysis o the women diagnosed with breast can-

cer or each area o concern Demographic analysis o the general population living in each

area o concern

Overview and detailed description o the analytic process

Breast cancer risk does not aect all communities in Caliornia thesame way. The more that is known about how dierent people are

14 See note 5.


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Introduction

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aected, the better our collective ability will be to identiy commu-nities at risk, provide services, and increase knowledge about poten-tial causes o breast cancer. In the uture, public agencies and oth-ers may consider adapting this protocol on a routine basis to betterunderstand the burden o cancer in Caliornia. The CBCMP hopes toassist in that process by sharing eective methods to map breastcancer data at the sub-county level.

Companion Piece to This Report

A complete description o the CBCMP AGs deliberation process in-cluding a brieer, more technical discussion o the analytic ndings

is available in the a manuscript titled Guidelines or the Mapping oCancer Registry Data: Results rom an Expert Panel Study, available at

www.caliorniabreastcancermapping.org .


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A Note on the Term Cancer Cluster

The term cancer cluster is commonly used to reer to a dis-tinct geographic area, such as a school, neighborhood, or

workplace, with a higher number o cancer cases than wouldbe expected. The clustering o cancer cases in a small geo-graphic area, time period, and/or among a dened group opeople can raise concerns that the cancer may be caused by aspecic environmental contaminant or pollution source.

The CBCMP results are related to the idea o clusters since theanalysis identied localized areas with increased rates o dis-

ease unrelated to random chance. Thereore, the CBCMP AGand sta held many discussions on whether or not to use theterm cluster to describe project ndings. There is no com-

mon or agreed upon defnition o cluster, and reservationsabout using the term stemmed rom two connotations that

would be misleading i used in the context o this report:

The term may imply specifc environmental or indus-

trial pollution is causing the elevated number o cases:

Scientists believe that it may take decades between expo-sure to environmental contaminants and the subsequentdevelopment o breast cancer, during which time peoplewho have been exposed requently move out o the area

and unexposed people move in. Thereore, although theCBCMP is very concerned about the possibility that expo-

sure to environmental chemicals may lead to breast can-cer, it is very unlikely that our project would identiy such aphenomenon.

The term may imply government negligence or mal-

easance:The second connotation is that a public agency

has willully ignored or hidden the existence o the cluster,with phrases like alleged cluster and cluster allegation com-monly used. In contrast, agencies such as the CaliorniaCancer Registry (CCR) have been consistently transparentand orthcoming with providing data to the CBCMP ater

legal provisions were made to maintain patient condenti-ality. As the CBCMP is composed o independent research-ers, CCR is not responsible or the ndings, but they haveexpressed interest in them and have not acted to preventtheir dissemination.

Because these connotations do not apply to the project re-sults, the group decided to use the term area of concern to

describe the collection o census tracts that had elevated breastcancer rates and to avoid the term clusterwhen at all possible.


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15 An exception to this rule occurred or the 2008 data. For this year, Scan Statistic identied elevated risk in a collection o tracts that overlapped both the North San Francisco Bay andSouth San Francisco Bay areas o concern (plus tracts in between). Sta calculated rates or subsets o these data (e.g., by county within each area) and determined that the ndings were

more honestly represented by treating these as two separate areas o concern (based on 20002007 data) rather than as a single large area o concern (as implied by the 2008 data only).

Overview of CBCMP Analytic Protocol

Below is a brie overview o the CBCMP protocol only. A complete,technical description and list o citations are available in the Meth-ods section (page 63). For details on how the AG guided the methodselection and protocol development, see Guidelines or the Mappingo Cancer Registry Data: Results rom an Expert Panel Study, available atwww.caliorniabreastcancermapping.org.

Summary of Analysis

The steps involved in conducting the analysis and developing mapsare summarized below. All work was conducted under the supervi-sion o the Committee or the Protection o Human Subjects o the

Caliornia Department o Public Health and the Institutional ReviewBoard o the Public Health Institute.

Obtain data: Data were obtained rom the Caliornia CancerRegistry describing the numbers o cases o invasive breast can-cer among women by age, year o diagnosis, and census tract oresidence at the time o diagnosis or the years 20002008. Popu-lation data, or denominators, and inormation about the popula-tions in the areas o concern were taken rom the 2000 and 2010U.S. Census. For years between 2000 and 2010, the populationdata were estimated mathematically.

Apply statistical method: O the statistical methods reviewed, theAG collectively determined that the Scan Statistic was the most e-ective or mapping breast cancer data at the sub-county level (i.e.,using census tracts as the unit o mapping) and was preerred overother methods due to its ability to accurately identiy a true breastcancer elevation at this level. Breast cancer data were processed

using SatScanTM, a computer program developed specically orthe Scan Statistic method. SatScanTM allows the user to choose set-tings in order to customize the analysis. Settings were selected toreect the AG priorities as closely as possible (page 63). For exam-ple, the sotware was set to calculate age-adjusted rates, allowingor comparisons o dierent areas across the state that may havedierent proportions o elderly residents.

Review results and make corrections: SatScanTM identiedgroups o contiguous census tracts in Caliornia with elevatedbreast cancer rates. The raw results were then systematically re-viewed to identiy and remove those groups whose elevatedrates were very likely attributable to the rapid population growth

in that area during that time period. Once these misleadinggroups o census tracts were removed rom the analysis, a reviewo the remaining groups showed that they were concentrated ina small number o specic geographic areas over time. These ar-eas were designated as areas o concern. To be considered parto an area o concern, each census tract had to show up in a

group identied by SatScanTM at least once during the nine yearsanalyzed (20002008).15

Characterize areas o concern: Ater the maps were created, theage-adjusted invasive breast cancer rates or each area o concernor all nine years were calculated, along with rates or the stateas a whole or purposes o comparison. The demographic com-position o the women diagnosed in each area was compiled,along with the proportion o women or whom their cancer hadspread at the time o diagnosis (late-stage) and the proportiono women who received government-assisted insurance or who


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were uninsured at the time o diagnosis. Finally, demographic in-ormation about the general population living in each o the ar-eas o concern was compiled.

Capabilities and Limitations

Notable capabilities and limitations o the CBCMP protocol include:

Detectable size and rate:The ability or the Scan Statistic (or anyother statistical method) to detect a rate elevation is a unction o(1) the size o the area in question in this case, the number ocensus tracts, (2) the degree to which the rate has increased, and(3) the overall rate o the disease in question. For a group o 50tracts, Scan Statistic appears to reliably detect an invasive breastcancer rate elevation i it is 50% above that o the state overall.As detailed in the results sections, all o the areas o concern hadmuch smaller rate increases (generally 1020%) but they were de-

tectable because they included much larger numbers o tracts.

Eliminating alse positives: Scan Statistic has the ability to ig-nore elevations in cancer rates that may have occurred due torandom chance (i.e., alse positive ndings). This is particularlycrucial when examining all census tracts in a state as large as Cal-iornia on a yearly basis. For example, with the traditional methodused in public health agencies, one would expect that between150 and 200 o the census tracts identied would have elevatedcancer rates due solely to random chance or every year o data

analyzed. In contrast, the SatScanTM settings or this protocol wereselected to reduce this alse positive rate to once for every 1,000

years of data analyzed.Thereore, with Scan Statistic, there is veryhigh condence that the areas identied actually have elevatedrates o breast cancer and are not due to random chance.

Uncertainty about boundaries: The boundaries o each area oconcern are highly imprecise. The time-series maps in this reportdemonstrate how the census tracts identied by SatScanTM as hav-ing elevated breast cancer rates uctuate rom year to year, illustrat-ing how difcult it is to know actual boundaries with certainty.

Urban versus rural areas: The Scan Statistic unctions equallywell in both urban and rural areas. However, the SatScanTM set-tings selected or this protocol restricted raw results to areas lessthan 30 kilometers (about 19 miles) in radius. This may have dis-proportionately limited detections in rural areas because ruralcensus tracts are much larger. SatScanTM provides workarounds

or this limitation, the exploration o which is recommended oruture work.

Because the Scan Statistic diers rom statistical methods used con-ventionally, some counties that have been identied in previousanalyses as having signicantly elevated rates may not show up inthe CBCMP ndings. This is because the Scan Statistic uses higher

standards or statistical signicance. Previously documented inorma-tion about breast cancer rates in individual counties is still valid andshould not be considered undermined by the CBCMP results.


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Overall Results

The CBCMP protocol was applied to data describing invasive breastcancer among women in Caliornia or each year rom 2000 through2008. See Overview o CBCMP Analytic Protocol (page 5) or details, ca-pabilities, and limitations o protocol.

Areas with Elevated Invasive Breast

Cancer Rates in California

Our analysis identied our distinct areas in Caliornia with invasivebreast cancer rates that were between 10% and 20% higher than thestatewide rate (Figure 1).

The areas are located in North San Francisco Bay (360 tracts); SouthSan Francisco Bay (264 tracts); western Los Angeles and eastern Ven-tura counties (699 tracts); and southern Orange County, with a smallportion o western Riverside County (177 tracts).

Characteristics of Areas of Concern

In general, trends or women diagnosed with invasive breast cancer

were similar across the our areas o concern.

For all our areas o concern: Invasive breast cancer incidence rates have declined slightly, mir-

roring the decline o the statewide rate

White women are over-represented among cases compared to

the overall state population, which is consistent with the act thatWhite women ace an increased risk o breast cancer

Hispanic women are under-represented among cases comparedto the overall population, which is consistent with the act thatHispanic women ace a decreased risk o breast cancer

Figure 1. Areas of concern in California for invasive breast canceramong women

North San Francisco Bay

South San Francisco Bay

West Los Angeles/East Ventura

South Orange

County boundaries

Data Source: Caliornia Cancer Registr y, 2000-2008, prepared by the Caliornia Breast Cancer Mapping Project


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Arican-American women are diagnosed at a rate proportional totheir representation in the state overall

Asian women are generally under-represented among casescompared to the overall population, which is consistent withthe act that some groups o Asian women ace a decreased risko breast cancer (but note that risk or Asian women difers bysub-group)

For all areas o concern except West Los Angeles/East Ventura:

Women were slightly more likely to be diagnosed at an earlierstage (i.e., beore their cancer had spread) compared to womendiagnosed statewide

Women were more likely to have private insurance at the time odiagnosis than women in the state overall

For West Los Angeles/East Ventura, women were slightly more likelyto rely on government-assisted insurance or to be uninsured com-pared to women diagnosed statewide.

More detail about each area o concern is provided in the resultssections ollowing this section. Each section ocuses on a single area

o concern and includes the ollowing data and inormation: A description and map o the area o concern

Time-series maps and data or annual breast cancer rates rom20002008 or the area o concern and the state as a comparison

Sociodemographic data describing the women diagnosed withbreast cancer

Sociodemographic data describing the general population livingin the area o concern and the state as a comparison or the years2000 and 2010


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Overall Results

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Cancer Surveillance in Rural Areas

To calculate a reliable rate or any disease, epidemiologists re-quire a certain number o cases to occur (scientists call this

statistical power). For this reason, it is more difcult to calcu-late a rate or rare diseases than it is or common ones, and itis more difcult to calculate rates or places where ew peoplelive than it is or places where many live. For this reason, thereis a long-standing problem that inormation about cancerrates in rural areas is difcult to come by.

Most commonly, scientists studying rural areas combine (ag-

gregate) data rom multiple years together to obtain enoughcases. Since we are relying on annual estimates when check-ing the validity o our data (or example, ruling out population

shits as a cause o rate elevations), we do not have this op-tion. We notice, urthermore, that none o the areas o concerninclude particularly rural areas. Is this because the Scan Statis-tic is unable to detect rate elevations in rural areas or becausethere are no rate elevations in these areas?

While we cannot answer this question with certainty, we sus-pect that the latter possibility is the case. This conclusion issupported by the ollowing observations:

CBCMP sta studied the ability o the Scan Statistic to de-tect invasive breast cancer rate elevations in rural areas o

Caliornia using simulated data. They ound that areas oconcern with pronounced increases in rates (say 50% high-er than elsewhere), particularly when o sufcient size (say,

50-100 census tracts), could be detected quite reliably.

In Caliornia, rural counties themselves tend not to be thosewith the highest invasive breast cancer rates over the longterm. As seen in Figure 2 (page 12), only one o the tencounties with the highest rates in the state (Tuolumne) islocated ar rom an urban center, and the majority o suchcounties have rates lower than the state overall.

It may be that changing the Scan Statistic parameters will en-able us to dene areas o concern in rural areas i there areany to be ound but we are leaving that to uture work. It isalso important to keep in mind that although elevated rates oinvasive breast cancer tend to occur in urban areas, the samemay not be true or other types o cancer.

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Implications

In general, very little is known about what causes the rates o inva-sive breast cancer or one population to be higher those or another.

However, mapping variations in breast cancer risk can enable com-munities, breast cancer advocates, public health practitioners, andother breast cancer stakeholders to identiy communities most im-pacted by breast cancer, explore resource needs and opportunities,and raise other community concerns.

The sub-county maps produced by the CBCMP protocol are valuablenot as a replacement to other modes o presenting breast cancersurveillance data, but rather as a supplement to them. For example,unding and interventions are oten conceived as county-level ini-tiatives, so there will always be a need or county level gures de-

scribing incidence and prevalence. In contrast, sub-county mappingprovides communities with inormation on breast cancer rates bothwithin and across county boundaries.

Breast Cancer in California:

New Information

The ability to search or and identiy areas o concern that crosscounty boundaries represents a substantial improvement over meth-ods traditionally used by public agencies and provides new inorma-tion that can inorm local breast cancer eorts within that area oconcern. For example:

Because o its relatively small population, Ventura County hasnever been noted to have consistently elevated rates o invasivebreast cancer on an annual basis relative to the state overall. LosAngeles County is much larger, but taken as a whole has a lowerrate o invasive breast cancer than the state overall. We now seethat an area partially overlapping each o these counties possess-

es a consistently elevated rate (page 41), providing communitiesin both counties a ocus or outreach and education, problem

solving, resource management, and undraising.

Similarly, Orange County on the whole has previously only beenseen to have a slightly elevated invasive breast cancer rate (withintermittent statistical signicance), while Riverside County hashad, in general, a lower rate than the state. We now see that wom-en living in the southern portion o Orange County and a smallportion o western Riverside County ace a signicantly higher risko disease in nearly every year examined (pages 53 and 56).

The elevated rate o invasive breast cancer among women living in

Marin County has been well documented. The ndings in this re-

port, however, raise the possibility that communities elsewhere inthe northern San Francisco Bay may be similarly aected (page 17).

In the South San Francisco Bay, only women in San Mateo Countyhave been previously noted to have consistently elevated risk orinvasive breast cancer. We now see that it is relevant to discusscommunities throughout the South Bay, including those in north-ern Santa Clara and southern Alameda counties (page 29).

In summary, as demonstrated in Figure 2 (page 12), the consider-ation o areas o concern in addition to counties provides a morecomprehensive picture o breast cancer risk in Caliornia than the

consideration o counties alone.

Implications for Cancer Surveillance

and Public Communication

In the uture, public agencies and others may consider conducting thistype o analysis on a routine basis in Caliornia to better understandthe burden o cancer in the state. The CBCMP hopes to assist in that

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process by sharing eective methods to map breast cancer data at thesub-county level. The augmentation o surveillance activities to includeroutine analyses o this type would have the ollowing benets:

Improved understanding by state and county ofcials o the pop-ulations most susceptible to invasive breast cancer

Guidance or both communities and research scientists seekingto rene their understandings o breast cancer risk

Reassurance o the public that geographic surveillance o canceris being conducted with both the highest possible geograph-ic resolution and the exclusion o ndings arising rom randomchance (alse positive ndings)

Topics for Future Inquiry

As much as the protocol developed by the CBCMP provides us with

inormation, it also presents us with questions that we should strive toanswer in the uture. Possibly the most immediate o these arise romthe many decisions we have made in how we implement the ScanStatistic or analysis. Available sotware allows us to choose rom a va-riety o maximum sizes or the raw results, adjustments or populationcharacteristics, and algorithms or choosing between overlapping ar-eas with elevated rates. All o these decisions aect both the resultsthemselves and how they might be described and communicated tothe public. We strove to design our implementation o the Scan Statis-tic to maximize both reliability and utility o the results, but we recog-nize that our approach is only one among many possibilities.

Particularly because this is the rst time inormation o this kind hasbeen made generally available, the CBCMP sta and Advisory Groupare intensely interested in how these ndings might be utilized andcommunicated among dierent groups in Caliornia and elsewhere.

While the present ndings demonstrate geographic variations in therisk o invasive breast cancer, most discussions up to this point haveocused on how demographic characteristics are related to cancer

risk. Because o the details about how various data are generated, it

Figure 2. Invasive breast cancer rates in areas of concern (AOCs,orange) and counties (blue) using nine-year aggregations ofsurveillance data

0 20 40 60 80 100 120 140

Rate per 100,000

ModocMono

Lassen

San BenitoMerced

TulareMonterey

MaderaMendocino

SiskiyouMariposaCalaveras

ImperialLake

ColusaPlumas

RiversideSutter

FresnoShasta

Del NorteInyo

GlennYubaKern

San BernardinoAmadorTehama

ButteNevada

Santa BarbaraSanta Clara

San Luis ObispoSan Francisco

statewide

Los AngelesEl DoradoKings

Santa CruzSan Joaquin

StanislausHumboldt

San MateoWest LA/Ventura AOC

PlacerNapa

TuolumneSacramento

VenturaSonoma

YoloSolano

AlamedaSan Diego

Orange

Orange AOCMarin

South Bay AOCNorth Bay AOC

Contra Costa

statewide rate

Data Source: Caliornia Cancer Registr y, 2000-2008, prepared by the Caliornia Breast Cancer Mapping Project

Implications


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Implications

13

can be difcult to tell whether the CBCMP results are telling a similarstory in a dierent way, or i new inormation is being added (seeinset box: Breast Cancer, Race, and Ethnicity).

Finally, we wonder how much the CBCMP protocol could be appliedto the analysis o cancers besides breast cancer. We note that this in-

volves more than just swapping out one set o data or another. Forexample, the questions people have about breast cancer may bedierent rom those people have about cancers o the lung, brain,

or immune system. The role o environmental actors is a persistentquestion or any cancer, but concerns about how these may occurare unique to each type. Also, the number o invasive breast cancercases diagnosed each year in Caliornia is quite high relative to othercancers, which mathematically results in dierent trade-os betweensensitivity and specicity. Considering both o these dierences,

would similar analyses or dierent cancers still be useul? This is a rel-evant question, and we encourage urther discussion on this matter.

Breast Cancer, Race, and Ethnicity

Since both ones genes and ones history o expoure to envi-ronmental hazards are believed to determine cancer risk, it isnot surprising that women with dierent racial/ethnic back-

grounds have dierent rates o invasive breast cancer. Speak-ing generally or US populations, White women have the high-est rates, ollowed by Arican-Americans, Hispanics,* Asiansand Pacic Islanders, and Native Americans. These are big gen-eralizations, however, because sub-groups o women in eachcategory may have cancer rates that are higher or lower thanthe category as a whole.

Because o the complicated history o Caliornia (and else-where), people o one racial/ethnic group are oten over-rep-resented in one area and under-represented in another. For

example, all o the areas o concern described here have rel-atively greater numbers o White women than the state over-all. Thereore, relative elevations in breast cancer in these areasmay simply be a reection o higher rates among White wom-

en. On the other hand, it would be equally valid to argue thatthe geographic patterns in breast cancer are the underlyingcause and the racial/ethnic patterns are simply a reection o

this geography; this is a chicken-or-egg question that scien-tists currently have no way to address.

We are requently asked i women in the areas o concern areacing the usual risk o breast cancer or their race and eth-nicity, or whether their risk is even higher than one would ex-pect based on their race and ethnicity. Because the CaliorniaCancer Registry and the US Bureau o the Census use dierentcategories or race and ethnicity, answering this question iscomplex and unortunately beyond the scope o our project.All we can say is that the areas o concern that we ound are

consistent with what we know about cancer rates among ra-cial/ethnic groups in the United States overall and hope thatmore resources will be available in the uture to address thisimportant question.

* Although many people nd it counter-intuitive, demographers consider Hispanic to be an ethnic rather than a racial category; this means it reers more to the

geographic area rom which ones ancestors came than it does to ones physical characteristics such as skin color (either type o category can be very complicated,

o course). Thereore, Hispanic women may be any race (e.g., White, Arican-American, etc.), and women in the other groups are assumed to be non-Hispanic.



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Results: North San FranciscoBay Area of ConcernMaps o North San Francisco Bay Area o Concern

Figure 3. Regional view o the North and South San Francisco Bay areas o concern

Figure 4. Census tracts in the North San Francisco Bay area o concern, 20002008

Figure 5. Time-series maps o census tracts with elevated rates o invasive breast cancerwithin the North San Francisco Bay area o concern

Invasive Breast Cancer Data or North San Francisco Bay Area o Concern

Figure 6. Age-adjusted invasive breast cancer rates (per 100,000 women) or the North SanFrancisco and Caliornia, 20002008

Table 1. Invasive breast cancer cases and age-adjusted rates (per 100,000 women) or theNorth San Francisco Bay and Caliornia, 20002008

Figure 7. Percent o women diagnosed with invasive breast cancer at a late-stage in the

North San Francisco Bay and Caliornia, 20002008Table 2. Women diagnosed with invasive breast cancer at a late-stage in the North San

Francisco Bay and Caliornia, 20002008

Sociodemographic Data or Invasive Female Breast Cancer Cases in North SanFrancisco Bay Area o Concern

Figure 8. Race/ethnicity o women diagnosed with invasive breast cancer in the North SanFrancisco Bay and Caliornia, 20002008

Table 3. Race/ethnicity o women diagnosed with invasive breast cancer in the North SanFrancisco Bay and Caliornia, 20002008

Figure 9. Percent o women diagnosed with invasive breast cancer who receive government-assisted insurance or are uninsured, North San Francisco Bay and Caliornia, 20002008

Table 4. Percent o women diagnosed with invasive breast cancer who receive government-assisted insurance or are uninsured, North San Francisco Bay and Caliornia, 20002008

U.S. Census 2000 and 2010 Population Data or North San Francisco Bay Area oConcern and Caliornia

Table 5. Population demographics o North San Francisco Bay and Caliornia, years 2000 and 2010

Figure 10. Female residents by race/ethnicity or North San Francisco Bay and Caliornia, 2000and 2010

Figure 11. Female residents by age or North San Francisco Bay and Caliornia, 2000 and 2010

Results



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16

Results: North San Francisco Area of Concern


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17

Figure 3. Regional view o North and South San Francisco Bay areas o concern

Marin

SonomaNapa

Solano

ContraCosta

Alameda

SantaClara

San Mateo

20 Miles



County boundaries

Data Source: Caliornia Cancer Registry, 20002008, prepared by the Caliornia Breast Cancer Mapping Project

Maps of North SanFrancisco Bay Area ofConcern

Description

The North San Francisco Bay area o concernis shown in Figure 3 in green. The South SanFrancisco Bay area o concern, shown in purple,is discussed in the next chapter o results. Eacharea overlaps small portions o Alameda County.

Counties overlapping North San Francisco

Bay area o concern include: Alameda, Con-tra Costa, Solano, Napa, Sonoma, Marin, andSan Francisco

Population size: 1,723,658 in 2010, a 7% in-

crease rom the year 2000 census population



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A detailed census tract view o the North SanFrancisco Bay area o concern is shown in Figure 4.

Figure 4. Census tracts in the North San Francisco Bay area o concern, 20002008

5 Miles

Oakland

SanFrancisco

Mill Valley

Petaluma

Napa

Concord

Richmond

Faireld

MarinCounty

Alameda County

Solano County

Conta CostaCounty

Napa CountySonoma County




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19

Figure 5. Time-series maps o census tracts with elevated rates o invasive breast cancerwithin the North San Francisco Bay area o concern

MillValley

Concord

Faireld

Oakland

Napa

MillValley

Concord

Faireld

Oakland

Napa

MillValley

Concord

Faireld

Oakland

Napa

MillValley

Concord

Faireld

Oakland

Napa

MillValley

Concord

Faireld

Oakland

Napa

MillValley

Concord

Faireld

Oakland

Napa

MillValley

Concord

Faireld

Oakland

Napa

MillValley

Concord

Faireld

Oakland

Napa

MillValley

Concord

Faireld

Oakland

Napa

2000 2001 2002

2003 2004 2005

2006 2007 2008

North San Francisco Bay, census tracts with elevated rate

North San Francisco Bay, other census tracts in area of concern

County boundaries


In the time-series maps (Figure 5), the area oconcern is shown in gray, while the green areasindicate groups o census tracts with elevatedrates o invasive breast cancer or the given year.

The area o concern is composed o all groupso census together that had an elevated rate

o invasive breast cancer at any time during20002008.



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Invasive Breast CancerData for North SanFrancisco Bay Area ofConcern

Breast Cancer Rates over Time

Age-adjusted rates o emale invasive breastcancer generally declined rom 2000 to 2008,but were steadily higher in the North San Fran-cisco Bay area o concern compared to state-wide (Figure 6 and Table 1).

Figure 6. Age-adjusted invasive breast cancer rates (per 100,000 women) or the NorthSan Francisco and Caliornia, 20002008

2000 2002 2004 2006 20080

50

100

150

200

Year

Age-adjustedrateper100,0

00women

Statewide

North SF Bay


Table 1. Invasive breast cancer cases and age-adjusted rates (per 100,000 women) or theNorth San Francisco Bay and Caliornia, 20002008

North San Francisco Bay Caliornia

YearNumbero cases

Age-adjustedrate

95% confdenceinterval

Numbero cases

Age-adjustedrate


2000 1,330 142.1 134.5150.0 20,545 120.9 119.2122.5

2001 1,373 144.7 137.2152.6 20,902 120.3 118.7122.0

2002 1,310 135.9 128.6143.5 21,106 118.9 117.3120.5

2003 1,188 121.7 114.8128.8 19,817 109.4 107.9111.0

2004 1,155 116.3 109.7123.3 19,722 106.7 105.2108.2

2005 1,200 119.4 112.7126.4 20,381 108.2 106.7109.7

2006 1,287 127.1 120.2134.4 20,436 106.5 105.0108.0

2007 1,303 126.2 119.3133.4 21,094 107.6 106.1109.0

2008 1,174 111.8 105.4118.6 19,005 95.3 93.996.6




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Figure 7. Percent o women diagnosed with invasive breast cancer at a late-stage in theNorth San Francisco Bay and Caliornia, 20002008

PercentofCases

North SF Bay

Statewide

2000 2002 2004 2006 2008

Year

0

10

20

30

40

50


Table 2. Women diagnosed with invasive breast cancer at a late-stage in the North SanFrancisco Bay and Caliornia, 20002008


YearCases diagnosed at

a late-stagePercent oall cases

Cases diagnosed ata late-stage

Percent oall cases

2000 475 36% 7,407 37%

2001 461 34% 7,630 37%

2002 450 35% 7,701 37%

2003 415 35% 7,236 37%

2004 388 34% 7,268 37%

2005 408 34% 7,442 37%

2006 436 34% 7,379 36%

2007 431 33% 7,668 37%

2008 404 35% 6,845 36%

All Years 3,868 34% 66,576 37%


Stage at diagnosis

A slightly lower percent o women were diag-nosed at a late-stage in the North San FranciscoBay compared to statewide (Figure 7 and Table2). Overall, the percent o women diagnosed ata late-stage was relatively stable in both Calior-nia and the North San Francisco Bay.



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22

Figure 8. Race/ethnicity o women diagnosed with invasive breast cancer in the North SanFrancisco Bay and Caliornia, 20002008

White African-American Hispanic/Latino Asian Other0

20

40

60

80

Race/Ethnicity

Percent

Statewide

North SF Bay

Data Source: Caliornia Cancer Registry, 2000-2008, prepared by the Caliornia Breast Cancer Mapping Project

Table 3. Race/ethnicity o women diagnosed with invasive breast cancer in the North SanFrancisco Bay and Caliornia, 20002008


Race/Ethnicity Cases Percent Cases Percent

White 8,037 71% 124,541 68%

Arican-American 1,228 11% 11,161 6%

Hispanic/Latino 759 7% 27,318 15%Asian 1,166 10% 18,383 10%

Other 130 1% 1,605 1%

All Cases 11,320 100% 183,008 100%

Data Source: Caliornia Cancer Registry, 2000-2008, prepared by the Caliornia Breast Cancer Mapping Project

Sociodemographic Datafor Invasive Female BreastCancer Cases in NorthSan Francisco Bay Area of

ConcernRace/ethnicity

In the North San Francisco Bay, White womenaccounted or 71% o invasive breast cancer cas-es diagnosed rom 20002008 (Figure 8 and Ta-ble 3), though according to census data Whiteemales represent about hal o the 2010 emale

population (Table 5 and Figure 10). Hispanicwomen, on the other hand, accounted or lessthan 7% o invasive breast cancer cases diag-

nosed rom 20002008, though they representalmost 20% o the population. Arican-Americanwomen accounted or 11% o breast cancercases rom 20002008 while representing 11%o the emale population, while Asian womenaccounted or 10% o breast cancer cases diag-nosed rom 20002008 while representing 17%o the population.



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Figure 9. Percent o women diagnosed with invasive breast cancer who receive government-assisted insurance or are uninsured, North San Francisco Bay and Caliornia, 20002008

PercentofCases

Statewide

North SF Bay

2000 2002 2004 2006 2008

Year

0

5

10

15

20

25


Table 4. Percent o women diagnosed with invasive breast cancer who receive government-assisted insurance or are uninsured, North San Francisco Bay and Caliornia, 20002008


YearGovernment-assisted

insurance or uninsuredPercent oall cases

Government-assistedinsurance or uninsured

Percent oall cases

2000 191 14% 3,678 18%

2001 190 14% 3,884 19%

2002 208 16% 4,063 19%

2003 162 14% 3,555 18%

2004 166 14% 3,537 18%

2005 144 12% 3,529 17%

2006 159 12% 3,509 17%

2007 182 14% 3,574 17%

2008 142 12% 3,317 17%

All Years 1,544 14% 32,646 18%


Insurance Status

A smaller proportion o women diagnosedwith invasive breast cancer in the North SanFrancisco Bay were uninsured or receivedgovernment-assisted insurance at the timeo diagnosis in comparison to patients acrossCaliornia (Figure 9 and Table 4). On average, 14%o women with breast cancer in the North SanFrancisco Bay were uninsured or received gov-ernment-assisted insurance.



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Population Data: U.S. Census2000 and 2010 for NorthSan Francisco Bay Area ofConcern and California

We analyzed data rom the 2000 and 2010 U.S.Census to better understand who lives in areaso concern, how these communities compare tothe state as a whole, and how the demographicshave or have not changed in the past decade.

Overall, the North San Francisco Bay experi-enced a decrease in the proportion o youngemales, and an increase in the proportion oemales aged 4564 years, similar to statewidetrends (Table 5 and Figure 11). In addition,

there was a decline in the proportion o Whiteand Arican-American emales and increases inthe proportion o Asian and Hispanic emales(Table 5 and Figure 10).

Table 5. Population demographics o North San Francisco Bay and Caliornia, years 2000and 2010


Population 2000 2010 2000 2010

Total population 1,607,322 1,723,658 33,871,648 37,253,956

Female 823,008 51% 882,247 51% 16,996,756 50% 18,736,126 50%

Male 784,314 49% 841,411 49% 16,874,892 50% 18,517,830 50%

Age (emale)

024 years 252,598 31% 260,295 30% 6,112,204 36% 6,422,590 34%

2544 years 253,704 31% 239,189 27% 5,248,109 31% 5,182,849 28%

4564 years 203,431 25% 253,708 29% 3,554,659 21% 4,731,190 25%

65+ years 113,870 14% 129,055 15% 2,081,784 12% 2,399,497 13%

Race (emale)

White 445,031 54% 425,037 48% 8,008,532 47% 7,510,531 40%

Arican-American 110,031 13% 97,144 11% 1,111,726 7% 1,094,910 6%Asian 116,927 14% 149,576 17% 1,946,293 12% 2,580,855 14%

Hispanic or Latino 117,050 14% 170,468 19% 5,351,525 31% 6,933,591 37%

Other 34,564 4% 40,022 5% 578,680 3% 616,239 3%

Housing tenure

Owner-occupied 366,312 59% 384,779 58% 6,546,334 57% 7,035,371 56%

Renter-occupied 252,378 41% 277,791 42% 4,956,536 43% 5,542,127 44%

Data source: U.S. Census, 2000 and 2010, prepared by the Caliornia Breast Cancer Mapping Project



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However, the North San Francisco Bay continuesto encompass a higher proportion o White andArican-American emales, and a markedly lowerproportion o Hispanic emales, compared toCaliornia as a whole. The North San FranciscoBay emale population also tends to be older

compared to the Caliornia population.

Figure 10. Female residents by race/ethnicity or North San Francisco Bay and Caliornia,2000 and 2010

0

50

40

30

20

10

60

70

Percent

Statewide

2000

2000

2010

2010

North SF Bay

White African-American Asian Hispanic/Latino Other

Race/EthnicityData source: U.S. Census, 2000 and 2010, prepared by the Caliornia Breast Cancer Mapping Project

Figure 11. Female residents by age for North San Francisco Bay and California, 2000 and 2010

024 2544 4564 65+

Age Category

Percent

Statewide

North SF Bay

0

10

20

30

40

50

2000

20002010

2010


Interpreting the line charts(Figures 10 and 11)

These gures show comparisons be-tween statewide population (blue lines)and the North San Francisco Bay areao concern (green lines), and between2000 and 2010.

Comparing 2000 to 2010:

The lines slope indicates the amounto change rom 2000 to 2010. Down-ward-slanted lines indicate a decreasein the percentage o women rom2000 to 2010. Upward-slanted linesindicate an increase in the percent-age o women rom 2000 to 2010.Relatively at lines indicate little or nochange between 2000 and 2010.

Comparing the area o concern tostatewide:

Where the blue line is above thegreen line, the percentage o womenstatewide is higher than in the areao concern. Where the green line isabove the blue line, the percentageo women in the area o concern ishigher than the statewide population.



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Results: South San FranciscoBay Area of ConcernMaps o South San Francisco Bay Area o Concern

Figure 12. Regional view o the North and South San Francisco Bay areas o concern

Figure 13. Census tracts in the South San Francisco Bay area o concern, 20002008

Figure 14. Time-series maps o census tracts with elevated rates o invasive breast cancerwithin the South San Francisco Bay area o concern

Invasive Breast Cancer Data or South San Francisco Bay Area o Concern

Figure 15. Age-adjusted invasive breast cancer rates (per 100,000 women) or the South SanFrancisco Bay and Caliornia, 20002008

Table 6. Invasive breast cancer cases and age-adjusted rates (per 100,000 women) or theSouth San Francisco Bay and Caliornia, 20002008

Figure 16. Percent o women diagnosed with invasive breast cancer at a late-stage in the

South San Francisco Bay and Caliornia, 20002008Table 7. Women diagnosed with invasive breast cancer at a late-stage in the South San

Francisco Bay and Caliornia, 20002008

Sociodemographic Data or Invasive Breast Cancer Cases in South San FranciscoBay Area o Concern

Figure 17. Race/ethnicity o women diagnosed with invasive breast cancer in the South SanFrancisco Bay and Caliornia, 20002008

Table 8. Race/ethnicity o women diagnosed with invasive breast cancer in the South SanFrancisco Bay and Caliornia, 20002008

Figure 18. Percent o women diagnosed with invasive breast cancer who receive government-assisted insurance or are uninsured, South San Francisco Bay and Caliornia, 20002008

Table 9. Percent o women diagnosed with invasive breast cancer who receive government-assisted insurance or are uninsured, South San Francisco Bay and Caliornia, 20002008

U.S. Census 2000 and 2010 Population Data or South San Francisco Bay Area oConcern and Caliornia

Table 10. Population demographics o South San Francisco Bay and Caliornia, years 2000 and 2010

Figure 19. Female residents by race/ethnicity or South San Francisco Bay and Caliornia, 2000

and 2010

Figure 20. Female residents by age or South San Francisco Bay and Caliornia, 2000 and 2010



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Results: South San Francisco Area of Concern


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Figure 12. Regional view o the North San Francisco Bay and South San Francisco Bayareas o concern

Marin

SonomaNapa

Solano

ContraCosta

Alameda

SantaClara

San Mateo

20 Miles



County boundaries


Maps of South SanFrancisco Bay Area ofConcern

Description

The South San Francisco Bay is designated inpurple and sits just south o the North San Fran-cisco Bay area o concern, shown in green anddescribed in the preceding chapter (Figure 12).Each area overlaps portions o Alameda County.

Counties overlapping South San Francisco

Bay area o concern: Alameda, Santa Clara,and San Mateo


crease rom the year 2000 census



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A detailed census tract view o the South San Fran-

cisco Bay area o concern is shown in Figure 13.

Figure 13. Census tracts in the South San Francisco Bay area o concern, 20002008

Fremont

San Mateo

Santa Clara

Palo Alto

Hayward

Half Moon Bay

AlamedaCounty

Santa CruzCounty

San MateoCounty

Santa ClaraCounty

5 Miles




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Figure 14. Time-series maps o census tracts with elevated rates o invasive breast cancerwithin the South San Francisco Bay area o concern

Hayward

Fremont

San Mateo

SantaClara

Half Moon Bay

Hayward

Fremont

San Mateo

SantaClara

Half Moon Bay

Hayward

Fremont

San Mateo

SantaClara

Half Moon Bay

Hayward

Fremont

San Mateo

SantaClara

Half Moon Bay

Hayward

Fremont

San Mateo

SantaClara

Half Moon Bay

Hayward

Fremont

San Mateo

SantaClara

Half Moon Bay

Hayward

Fremont

San Mateo

SantaClara

Half Moon Bay

Hayward

Fremont

San Mateo

SantaClara

Half Moon Bay

Hayward

Fremont

San Mateo

SantaClara

Half Moon Bay

2000 2001 2002

2003 2004 2005

2006 2007 2008

South San Francisco Bay, census tracts with elevated rate

South San Francisco Bay, other census tracts in area of concern

County boundaries


In the time-series maps (Figure 14), the area oconcern is shown in gray, while the purple areasindicate groups o census tracts with elevatedrates o invasive breast cancer or the given year.





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Invasive Breast CancerData for South SanFrancisco Bay Area ofConcern

Breast Cancer Rates over Time

Age-adjusted rates o emale invasive breastcancer declined slightly rom 2000 to 2008, butwere steadily higher in the South San FranciscoBay when compared to Caliornia (Figure 15 and

Table 6).

Figure 15. Age-adjusted invasive breast cancer rates (per 100,000 women) or the SouthSan Francisco Bay and Caliornia, 20002008

2000 2002 2004 2006 20080

50

100

150

200

Year

Age-adjustedrateper100,0

00women

Statewide

South SF Bay


Table 6. Invasive breast cancer cases and age-adjusted rates (per 100,000 women) or theSouth San Francisco Bay and Caliornia, 20002008

South San Francisco Bay Caliornia

YearNumbero cases

Age-adjustedrate


Numbero cases

Age-adjustedrate


2000 955 141.2 132.4150.1 20,545 120.9 119.2122.5

2001 905 132.0 123.5140.9 20,902 120.3 118.7122.0

2002 992 142.9 134.1152.1 21,106 118.9 117.3120.5

2003 881 124.8 116.7133.4 19,817 109.4 107.9111.0

2004 890 124.8 116.7133.3 19,722 106.7 105.2108.2

2005 863 119.1 111.3127.4 20,381 108.2 106.7109.7

2006 878 119.8 112.0128.1 20,436 106.5 105.0108.0

2007 923 123.9 116.0132.3 21,094 107.6 106.1109.0

2008 926 123.1 115.2131.4 19,005 95.3 93.9 96.6




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Figure 16. Percent o women diagnosed with invasive breast cancer at a late-stage in theSouth San Francisco Bay and Caliornia, 20002008

PercentofCases

South SF Bay

Statewide

2000 2002 2004 2006 2008

Year

0

10

20

30

40

50


Table 7. Women diagnosed with invasive breast cancer at a late-stage in the South SanFrancisco Bay and Caliornia, 20002008


YearCases diagnosed at

a late-stagePercent oall cases

Cases diagnosed ata late-stage

Percent oall cases

2000 330 35% 7,407 37%

2001 308 34% 7,630 37%

2002 346 35% 7,701 37%

2003 290 33% 7,236 37%

2004 290 33% 7,268 37%

2005 290 34% 7,442 37%

2006 262 30% 7,379 36%

2007 321 35% 7,668 37%

2008 299 32% 6,845 36%

All Years 2,736 33% 66,576 37%


Stage at diagnosis

A slightly lower percent o women were diag-nosed at a late-stage in the South San FranciscoBay area o concern compared to statewide(Figure 16 and Table 7). Overall, the percent owomen diagnosed at a late-stage was relatively

stable in Caliornia, with small uctuations in theSouth San Francisco Bay area o concern.



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Figure 17. Race/ethnicity o women diagnosed with invasive breast cancer in the SouthSan Francisco Bay and Caliornia, 20002008

White African-American Hispanic/Latino Asian Other0

20

40

60

80

Race/Ethnicity

Percent

South SF Bay

Statewide


Table 8. Race/ethnicity o women diagnosed with invasive breast cancer in the South SanFrancisco Bay and Caliornia, 20002008


Race/Ethnicity Cases Percent Cases Percent

White 6,067 74% 124,541 68%

Arican-American 146 2% 11,161 6%

Hispanic/Latino 606 7% 27,318 15%Asian 1337 16% 18,383 10%

Other 57 1% 1,605 1%

All Cases 8,213 100% 183,008 100%


Sociodemographic Datafor Invasive Female BreastCancer Cases in SouthSan Francisco Bay Area of

ConcernRace/ethnicity

In the South San Francisco Bay, White emalesaccounted or 74% o invasive breast cancercases diagnosed rom 2000-2008 (Figure 17and Table 8), though according to census dataWhite emales represent 44% o the 2010 emale

population (Table 10 and Figure 19). Hispanicemales accounted or just 7% o invasive breastcancer rom 20002008, but they represent

18% o the population in the South San Fran-cisco Bay. Arican-American women accountedor 2% o breast cancer cases rom 20002008while representing 2% o the emale population,and Asian women accounted or 16% o breastcancer cases diagnosed rom 20002008 whilerepresenting 31% o the population.



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Figure 18. Percent of women diagnosed with invasive breast cancer who receive government-assisted insurance or are uninsured, South San Francisco Bay and California, 20002008

PercentofCases

Statewide

South SF Bay

2000 2002 2004 2006 2008

Year

0

5

10

15

20

25


Table 9. Percent o women diagnosed with invasive breast cancer who receive government-assisted insurance or are uninsured, South San Francisco Bay and Caliornia, 20002008


YearGovernment-assisted

insurance or uninsuredPercent oall cases

Government-assistedinsurance or uninsured

Percent oall cases

2000 121 13% 3,678 18%

2001 119 13% 3,884 19%

2002 146 15% 4,063 19%

2003 120 14% 3,555 18%

2004 138 16% 3,537 18%

2005 127 15% 3,529 17%

2006 103 12% 3,509 17%

2007 168 18% 3,574 17%

2008 118 13% 3,317 17%

All Years 1,160 14% 32,646 18%


Insurance Status

A smaller proportion o women diagnosed withinvasive breast cancer in the South San Fran-cisco Bay were uninsured or received govern-ment-assisted insurance at the time o diagnosisin comparison to patients across Caliornia (Fig-

ure 18 and Table 9). On average, 14% o womenwith breast cancer in the South San FranciscoBay were uninsured or received government-as-sisted insurance. In 2007, this percentage rose tobe approximately the same as that o the stateoverall, but this increase did not persist and maynot be reliable.



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Table 10. Population demographics o South San Francisco Bay and Caliornia, years 2000and 2010


Population 2000 2010 2000 2010

Total population 1,226,313 1,285,291 33,871,648 37,253,956

Female 612,067 50% 647,790 50% 16,996,756 50% 18,736,126 50%

Male 614,246 50% 637,502 50% 16,874,892 50% 18,517,830 50%

Age (emale)

024 years 180,776 30% 190,553 29% 6,112,204 36% 6,422,590 34%

2544 years 207,470 34% 193,421 30% 5,248,109 31% 5,182,849 28%

4564 years 141,295 23% 171,580 26% 3,554,659 21% 4,731,190 25%

65+ years 82,526 13% 92,236 14% 2,081,784 12% 2,399,497 13%

Race (emale)

White 341,532 56% 287,853 44% 8,008,532 47% 7,510,531 40%

Arican-American 16,356 3% 15,284 2% 1,111,726 7% 1,094,910 6%

Asian 139,299 23% 200,612 31% 1,946,293 12% 2,580,855 14%

Hispanic or Latino 92,653 15% 118,022 18% 5,351,525 31% 6,933,591 37%

Other 22,227 4% 26,019 4% 578,680 3% 616,239 3%

Housing tenure

Owner-occupied 273,589 60% 275,354 58% 6,546,334 57% 7,035,371 56%

Renter-occupied 184,643 40% 198,841 42% 4,956,536 43% 5,542,127 44%


Population Data: U.S. Census2000 and 2010 for SouthSan Francisco Bay Area ofConcern and California

We analyzed data rom the 2000 and 2010U.S. Census to better understand who lives inthese areas o concern, how these communitiescompare to the state as a whole, and how thedemographics have or have not changed in thepast decade.

Overall, the South San Francisco Bay has expe-rienced a small increase in the proportion oemales aged 4564 years, similar to statewidetrends (Table 10 and Figure 20). In addition, therewas a decline in the proportion o White emales,

and increases in the proportion o Asian andHispanic populations (Table 10 and Figure 19).



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Figure 19. Female residents by race/ethnicity or South San Francisco Bay and Caliornia,2000 and 2010

0

50

40

30

20

10

60

70

Percent

Statewide

2000

2000

2010

2010

South SF Bay

White African-American Asian Hispanic/Latino Other

Race/EthnicityData source: U.S. Census, 2000 and 2010, prepared by the Caliornia Breast Cancer Mapping Project

Figure 20. Female residents by age for South San Francisco Bay and California, 2000 and 2010

024 2544 4564 65+

Age Category

Perc

ent

Statewide

South SF Bay

0

10

20

30

40

50

2000

20002010

2010


The South San Francisco Bay continues toencompass a higher proportion o White andAsian emales, and a markedly lower proportiono Hispanic emales, compared to Caliornia as awhole. The South San Francisco Bay emale pop-ulation also tends to be slightly older compared

to the Caliornia population.

Interpreting the line charts(Figures 19 and 20)

These gures show comparisons be-tween statewide population (blue lines)and the North San Francisco Bay areao concern (purple lines), and between2000 and 2010.

Comparing 2000 to 2010:

The lines slope indicates the amounto change rom 2000 to 2010. Down-ward-slanted lines indicate a decreasein the percentage o women rom2000 to 2010. Upward-slanted linesindicate an increase in the percent-age o women rom 2000 to 2010.Relatively at lines indicate little or nochange between 2000 and 2010.

Comparing the area o concern tostatewide:

Where the blue line is above thepurple line, the percentage o womenstatewide is higher than in the areao concern. Where the purple line isabove the blue line, the percentageo women in the area o concern ishigher than the statewide population.



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Results: West Los Angeles/East Ventura Area of ConcernMaps o West Los Angeles/East Ventura Area o Concern

Figure 21. Regional view o the West Los Angeles/East Ventura and South Orange areas o concernFigure 22. Census tracts in the West Los Angeles/East Ventura area o concern, 20002008

Figure 23. Time-series maps o census tracts with elevated rates o invasive breast cancerwithin West Los Angeles/East Ventura area o concern

Invasive Breast Cancer Data or West Los Angeles/East Ventura Area o Concern

Figure 24. Age-adjusted invasive breast cancer rates (per 100,000 women) or West LosAngeles/East Ventura and Caliornia, 20002008

Table 11. Invasive breast cancer and age-adjusted rates (per 100,000 women) or West LosAngeles/East Ventura and Caliornia, 20002008

Figure 25. Percent o women diagnosed with invasive breast cancer at a late-stage in WestLos Angeles/East Ventura and Caliornia, 20002008

Table 12. Women diagnosed with invasive breast cancer at a late-stage in West Los Angeles/East Ventura and Caliornia, 20002008

Sociodemographic Data or Invasive Female Breast Cancer Cases in West LosAngeles/ East Ventura Area o Concern

Figure 26. Race/ethnicity o women diagnosed with invasive breast cancer in the West LosAngeles/East Ventura and Caliornia, 20002008

Table 13. Race/ethnicity o women diagnosed with invasive breast cancer in West LosAngeles/East Ventura and Caliornia, 20002008

Figure 27. Percent o women diagnosed with invasive breast cancer who receive government-assisted insurance or are uninsured, West Los Angeles/East Ventura and Caliornia, 20002008

Table 14. Percent o women diagnosed with invasive breast cancer who receive government-assisted insurance or are uninsured, West Los Angeles/East Ventura and Caliornia, 20002008

U.S. Census 2000 and 2010 Population Data or West Los Angeles/East VenturaArea o Concern and Caliornia

Table 15. Population demographics o West Los Angeles/East Ventura and Caliornia, years2000 and 2010

Figure 28. Female residents by race/ethnicity or West Los Angeles/East Ventura and Caliornia,

2000 and 2010

Figure 29. Female residents by age or West Los Angeles/East Ventura and Caliornia, 2000 and 2010



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Results: West Los Angeles/East Ventura Area of Concern


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Maps of West LosAngeles/East VenturaArea of Concern

Description

The West Los Angeles (LA)/East Ventura area oconcern overlaps portions o western Los An-geles and eastern Ventura counties, as shown inthe red area (Figure 21). The South Orange areao concern (shown in aqua) is discussed in the

ollowing section.

Counties overlapping West Los Angeles/East

Ventura area of concern include: Los Angeles

and Ventura


crease rom the year 2000 census

Figure 21. Regional view of the West Los Angeles/East Ventura and South Orange areasof concern

West Los Angeles/East Ventura

South Orange

County boundaries

Ventura

LosAngeles

RiversideOrange

20 Miles




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A detailed census tract view o the West LosAngeles/East Ventura area o concern is shownin Figure 22.

Figure 22. Census tracts in the West Los Angeles/East Ventura area o concern, 20002008

Malibu

Moor Park

Santa Clarita

Beverly Hills

Ventura County Los Angeles County

5 Miles


Results: West Los Angeles/East Ventura Area of Concern


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In the time-series maps (Figure 23), the area oconcern is shown in gray, while the red areasindicate groups o census tracts with elevatedrates o invasive breast cancer or the given year.



Figure 23. Time-series maps o census tracts with elevated rates o invasive breast cancerwithin West Los Angeles/East Ventura area o concern

Malibu

Moor Park

Santa Clarita

Beverly HillsMalibu

Moor Park

Santa Clarita

Beverly HillsMalibu

Moor Park

Santa Clarita

Beverly Hills

Malibu

Moor Park

Santa Clarita

Beverly HillsMalibu

Moor Park

Santa Clarita

Beverly HillsMalibu

Moor Park

Santa Clarita

Beverly Hills

Malibu

Moor Park

Santa Clarita

Beverly HillsMalibu

Moor Park

Santa Clarita

Beverly HillsMalibu

Moor Park

Santa Clarita

Beverly Hills

2000 2001 2002

2003 2004 2005

2006 2007 2008

West Los Angeles/West Ventura, census tracts with elevated rate

South San Francisco Bay, other census tracts in area of concern

County boundaries




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Invasive Breast CancerData for West Los

Angeles/East VenturaArea of Concern

Breast Cancer Rates over TimeAge-adjusted rates o emale invasive breastcancer declined rom 2000 to 2008, but weresteadily higher in the West Los Angeles/EastVentura area o concern compared to statewide(Figure 24 and Table 11).

Figure 24. Age-adjusted invasive breast cancer rates (per 100,000 women) or West LosAngeles/East Ventura and Caliornia, 20002008

2000 2002 2004 2006 20080

50

100

150

200

Year

Age-adjustedrateper100,000women

Statewide

West LA/East Ventura


Table 11. Invasive breast cancer cases and age-adjusted rates (per 100,000 women) orWest Los Angeles/East Ventura and Caliornia, 20002008

West LA/East Ventura Caliornia

YearNumbero cases

Age-adjustedrate


Numbero cases

Age-adjustedrate


2000 2,184 132.4 126.9138.0 20,545 120.9 119.2122.5

2001 2,309 137.2 131.7142.9 20,902 120.3 118.7122.0

2002 2,303 134.5 129.1140.2 21,106 118.9 11

California Breast Cancer Mapping Project Final Report November 2012

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