Meeting the mammography screening needs of underserved women : the performance of the National Breast and Cervical Cancer Early Detection Program in 2002 -- 2003 -LRB- United States -RRB- Objective To examine the extent to which the National Breast and Cervical Cancer Early Detection Program -LRB- Program -RRB- has helped to meet the mammography screening needs of underserved women . Introduction Breast cancer is the leading cause of cancer-related death among Hispanic women in the United States and the second-leading cause of cancer-related death among non-Hispanic women , causing more than 41,000 deaths in 2002 -LSB- 1 -RSB- . Breast cancer mortality is higher in poorer areas of the country than in wealthier areas -LSB- 2 -RSB- . Although timely breast cancer screening with mammography reduces mortality -LSB- 3 -RSB- , in the United States , screening rates are low among low-income women who lack insurance coverage for mammography -LSB- 4 , 5 -RSB- . In 1992 , among women aged 40 years and older , 60 % of women with health insurance and 22 % of women without health insurance had received a mammogram within the previous 2 years . Among those women with family incomes greater than or equal to 200 % of the federal poverty level , 64 % had received a mammogram within the previous 2 years , but only 41 % of women from families with incomes less than 200 % of the poverty level had received this service -LRB- Robert Uhler , MS , Personal Communication , April 2006 -RRB- . The annual income level for a family of four at 200 % of poverty in 1992 was approximately $ 28,000 -LSB- 6 , 7 -RSB- . In this context , to help low-income , uninsured women gain access to mammography screening services , the U.S. Congress passed the Breast and Cervical Cancer Mortality Prevention Act of 1990 -LRB- Public Law 101-354 -RRB- , authorizing the Centers for Disease Control and Prevention -LRB- CDC -RRB- to establish the National Breast and Cervical Cancer Early Detection Program -LRB- NBCCEDP -RRB- -LSB- 8 -RSB- referred to henceforth as the Program . The Program provides services through cooperative agreements , which are in place in all 50 states , the District of Columbia -LRB- DC -RRB- , 4 U.S. territories , and 13 American Indian/Alaskan Native organizations ; for a total of 68 grantees . Services provided by an American Indian/Alaska Native organization were consolidated with services provided by the state-based program where the American Indian/Alaska Native organization participant resides . In this work , `` state -LRB- s -RRB- '' refers to the 51 geopolitical units -LRB- 50 states and the District of Columbia -LRB- DC -RRB- -RRB- . The Program provides both breast and cervical cancer screening services to low-income uninsured women aged 18 -- 64 . From 1991 through June 2005 , the Program screened 2.6 million women for breast and cervical cancer , provided 3 million mammograms to 1.7 million women and diagnosed 5,309 cases of in situ breast cancers and 15,493 cases of invasive breast cancers . The Program provides screening mammography to women ages 40 and older . In 1996 , Program policy prioritized mammography screening of older women to allow for best use of limited resources . Of women receiving their initial screening mammogram through the Program in 2000 -- 2004 , 2.4 % were under 40 years of age ; 28.0 % were 40 -- 49 years old ; 66.4 % were between the ages of 50 and 64 ; and 3.2 % were over 64 years of age . Fifty-two percent of the women were non-Hispanic Whites , 14 % were non-Hispanic Blacks , 6 % were non-Hispanic Asian/Pacific Islanders , 4 % were non-Hispanic American Indian/Alaska Natives , 31 % were Hispanics , and 3 % were of unknown race/ethnicity -LSB- 9 -RSB- . The Program grew from eight grantees funded at $ 30 million in Fiscal Year 1991 to 68 grantees that received $ 204 million in 2005 . Sixty percent of federal funds received by the grantees are spent on clinical services . The remaining 40 % are used to fund other Program components including program management , data collection , quality assurance and improvement , partnership development , professional education , recruitment and evaluation . Treatment is covered by state Medicaid funding and other non-Program sources . A detailed description of the history of the Program is provided elsewhere -LSB- 8 -RSB- . Earlier research -LSB- 10 -RSB- found that in 1994 -- 1996 the Program provided either breast or cervical cancer screening services to about 12 -- 15 % of eligible women aged 50 -- 64 , but that study did not estimate the proportion of women who were provided mammography screening specifically or provide estimates by race/ethnicity or for states . The objective of the current analysis was to examine the extent to which the Program has helped to meet the mammography screening needs of this underserved population . Specifically , we estimated the numbers and percentages of women aged 40 -- 64 who in 2002 -- 2003 were eligible for breast cancer screening through the Program at both the state and national levels and the percentage of these eligible women who received Program-funded mammography . Finally , because disparities by race and ethnicity in the provision of screening services have commonly been reported in the U.S. -LSB- 5 , 11 -- 13 -RSB- , we examined the extent to which the Program at the national level provided services to women of different racial and ethnic backgrounds . Materials and methods We examined eligibility using the Annual Social and Economic Supplement -LRB- ASEC -RRB- to the Current Population Survey -LRB- CPS -RRB- conducted by the U.S. Census Bureau , and screening service delivery using Program data . We used data from 2002 and 2003 because Program data were complete for those years -LSB- 8 -RSB- . Eligibility for NBCCEDP breast cancer screening services Women aged 40 and older who do not have health insurance or whose insurance does not cover mammography screening are eligible for free breast cancer screening through the Program if their family incomes are below 250 % of the federal poverty level . Twenty-two states and Washington , DC set eligibility criteria at lower poverty level . The annual income levels for a family of four at 200 % and 250 % of poverty in 2003 were approximately $ 37,000 and $ 46,000 , respectively -LSB- 7 , 14 -RSB- . Because 95.8 % of women age 65 and over were covered by Medicare -LSB- 15 -RSB- and were therefore not served by the Program , we included only women aged 40 -- 64 in this analysis . Data sources CPS ASEC Questions about age , family size , sex , race , and Hispanic origin were included in the basic CPS , which is a monthly national survey undertaken primarily to determine the characteristics of the labor force of the U.S. civilian non-institutional population . Respondents were asked to identify their race by selecting one or more options from a list . Hispanic origin was asked separately from race . About 78,000 interviewed households in the CPS were asked a set of supplementary questions -LRB- the ASEC -RRB- about health insurance coverage , income received , and place of residence during the previous year -LSB- 16 -RSB- . The methods used to collect and report CPS ASEC data have been described previously -LSB- 17 -RSB- . NBCCEDP Data for the number of women screened during 2002 -- 2003 were obtained from Program service records . Grantees routinely collect income , family size , and insurance information to determine eligibility and collect screening information on each woman in the Program . These data include screening location , demographic characteristics , service dates , and outcomes . Demographic data are self-reported . Reporting of race and Hispanic origin is optional . The structure of the Program and methods for collecting and reporting Program data have been described elsewhere -LSB- 8 -RSB- . Data analysis CPS ASEC We estimated the number of women eligible for the Program by race and ethnicity -LRB- Hispanic origin -RRB- at the national level by extrapolating the respondents ' answers to the general U.S. population using standard Census Bureau methods -LSB- 15 -- 19 -RSB- . Given the CPS sample size , it was impossible to produce meaningful estimates by race or ethnicity for individual states . We categorized women who reported they were of Hispanic origin as Hispanic regardless of race . We categorized the remaining women , who were non-Hispanic , into one of the following racial groups : White , Black , American Indian/Alaska Native , Asian/Native Hawaiian/other Pacific Islander , or multiracial -LRB- which is henceforth defined synonymously with Two or More Races -RRB- . In the CPS , if a respondent did not report his or her race , the respondent 's race was allocated using the race of another member of the household , or failing that , the previous record on the CPS file -LSB- 17 -RSB- . People were considered uninsured if they were not covered by any type of private or government health insurance for the entire previous year -LSB- 18 -RSB- . Poverty was computed by comparing total family income -LRB- or the person 's own income if she did not live with family members -RRB- with 1 of 48 dollar amounts called poverty thresholds -LSB- 18 , 19 -RSB- . Each person 's poverty threshold was based on family size and number of children younger than 18 years -LSB- 14 -RSB- . The method of computing confidence intervals -LRB- CI -RRB- for the estimates of the eligible population is provided in Appendices 1 and 2 . We use two-tailed 90-percent CI to be consistent with the Census Bureau 's practices for reporting poverty and health insurance data . NBCCEDP In counting the total number of women who received at least one Program-funded mammogram in 2002 and 2003 , women were classified into the race/ethnic categories used to estimate Program eligibility . About 2.4 % of women who were screened did not claim any race or Hispanic origin . These women -LRB- 12,653 -RRB- were counted in the total number of women screened , but not in the specific race/ethnicity categories . NBCCEDP screening rates Based on the number of women screened and estimates of the numbers of women aged 40 -- 64 in both the U.S. population and the Program-eligible population we estimated the percentage of all U.S. women aged 40 -- 64 and the percentage of Program-eligible women who received a Program-funded mammogram at least once in 2002 or 2003 . We estimated provision of mammography screening over a 2-year period because the U.S. Preventive Services Task Force recommends that women aged 40 and older be provided with screening mammography every 1 -- 2 years -LSB- 3 -RSB- . We further examined the distribution of mammography screening among women from different racial and ethnic backgrounds . The method of computing CI for the estimated screening rates is provided in Appendix 3 . Results During 2002 -- 2003 , approximately 47 million women aged 40 -- 64 resided in the United States -LRB- Table 1 -RRB- . Of those women , approximately 4.0 million -LRB- 90 % CI , 3.8 million -- 4.2 million -RRB- or 8.5 % -LRB- CI , 8.1 -- 9.0 % -RRB- were estimated to be eligible for a Program-funded mammogram . Non-Hispanic White women constituted the largest number of women eligible for the Program : 2.0 million -LRB- CI , 1.8 -- 2.1 million -RRB- . However , the percentage of non-Hispanic White women who were eligible for the Program -LRB- 5.7 % ; CI , 5.3 -- 6.1 % -RRB- was smaller than that of other racial groups except for multiracial women . The percentage of multiracial women who were eligible , 8.9 % , was lower than the percentage for Hispanic women and for non-Hispanic American Indian/Alaska Native women , but was not statistically distinguishable from that of the other groups . The percentage eligible among Hispanic women -LRB- 23.1 % -RRB- was not statistically distinguishable from non-Hispanic American Indian/Alaska Native women -LRB- 19.8 % -RRB- but was higher than the percentage eligible among the other racial and ethnic groups . Table 1Number and percentage of U.S. women aged 40 -- 64 years who were eligible for the National Breast and Cervical Cancer Early Detection Program -LRB- NBCCEDP -RRB- , 2002 -- 2003Race/ethnicityAll women age 40 -- 64Women eligiblea for NBCCEDP mammography screeningNumber -LRB- thousand -RRB- Percent distributionbNumber -LRB- thousand -RRB- 90 % CIPercentc90 % CITotal46 ,8991004,0073,806 -- 4,2088.58.1 -- 9.0Non-Hispanic42 ,50490.62,9912,817 -- 3,1667.06.6 -- 7.4 White34 ,40373.41,9721,835 -- 2,1095.75.3 -- 6.1 Black5 ,43911.6714629 -- 79913.111.6 -- 14.6 AI/AN2250 .54523 -- 6619.811.3 -- 28.4 A/NH/OPI1 ,9774.2221173 -- 26811.28.9 -- 13.4 Multiracial4601 .04120 -- 618.94.6 -- 13.2 Hispanic4 ,3959.41,016909 -- 1,12223.120.9 -- 25.3 AI/AN : American Indian and Alaska Native ; A/NH/OPI : Asian and/or Native Hawaiian and other Pacific Islanders ; Multiracial : two or more racesa Women eligible for NBBCCEDP-funded mammography screening include women aged 40 -- 64 with family incomes below 250 % of federal poverty level , who are uninsured for mammography . The number of eligible women could be an underestimate because it excludes women who have insurance but whose insurance does not cover mammography screening . See Sect . Methods for detailsb Percent of all U.S. women aged 40 -- 64c Percent of all U.S. women aged 40 -- 64 in a given racial or ethnic group who were eligible for NBCCEDP funded mammography servicesSource : Authors ' tabulations of data from the U.S. Census Bureau , Current Population Survey , 2003 -- 2004 Annual Social and Economic Supplements During 2002 -- 2003 , 528,622 women aged 40 -- 64 received at least one mammogram through the Program , among whom 12,653 -LRB- 2.4 % -RRB- were of unknown race/ethnicity -LRB- Table 2 -RRB- . Of all women in the United States aged 40 -- 64 , the Program provided mammography screening to approximately 1.1 % . The rates of screening with mammography in the past 2 years -LRB- 2002 -- 2003 -RRB- , referred to henceforth as the screening rates , varied substantially by race/ethnicity . Approximately 9.7 % of all American Indian/Alaska Native women were screened and approximately 0.3 % of all multiracial women were screened . Table 2Number and percentage of women eligible for the National Breast and Cervical Cancer Early Detection Program -LRB- NBCCEDP -RRB- and U.S. women provided with mammography screening services , at least once , through NBCCEDP , between 2002 and 2003Race/ethnicityNumber of women screenedPercentage of U.S. women screenedaPercentage of NBCCEDP-eligible women screenedb % 90 % CITotal528 ,6221.113.212.5 -- 13.9Non-Hispanic349 ,6550.811.711.0 -- 12.4 White221 ,4330.611.210.4 -- 12.0 Black74 ,2591.410.49.2 -- 11.6 AI/AN21 ,8829.749.225.5 -- 72.9 A/NH/OPI30 ,6871.613.910.9 -- 16.9 Multiracial1 ,3940.33.41.7 -- 5.2 Hispanic166 ,3143.816.414.7 -- 18.1 Unknown Race/ethnicity12 ,653 -- -- -- AI/AN : American Indian and Alaska Native ; A/NH/OPI : Asian and/or Native Hawaiian and other Pacific Islanders ; Multiracial : two or more racesNBCCEDP mammography eligible women include : uninsured women aged 40 -- 64 with family incomes below 250 % of federal poverty levela Percent of all U.S. women in a given racial and ethnic group who were provided mammograms funded by NBCCEDPb Percent of all U.S. women in a given racial and ethnic group who are eligible and who were provided with NBCCEDP funded mammogramsSource : Authors ' tabulations of data from the U.S. Census Bureau , Current Population Survey , 2003 -- 2004 Annual Social and Economic Supplements , and from NBCCEDP April 2005 data Among all women eligible for the Program , approximately 13.2 % -LRB- CI , 12.5 -- 13.9 % -RRB- were screened one or more times -LRB- Table 2 -RRB- . This estimate is based on the national Program eligibility limit of 250 % of poverty . Using state-specific poverty level criteria , we estimated the screening rate for all states combined to be 14.7 % -LRB- CI , 13.8 -- 15.6 % -RRB- , reflecting the lower eligibility limits used in many states -LRB- data not shown -RRB- . The percentage of all eligible women who were screened in the Program varied by race/ethnicity -LRB- Table 2 -RRB- . The screening rates for non-Hispanic White and non-Hispanic Black women were not statistically distinguishable . Hispanic women had a higher screening rate than other women except for non-Hispanic American Indian/Alaska Native women , who had the highest screening rate , with an estimated 49.2 % -LRB- CI , 25.5 -- 72.9 % -RRB- screened . The screening rate for non-Hispanic multiracial women was lowest -LRB- 3.4 % , CI , 1.7 -- 5.2 % -RRB- . The estimated number and percentage of women in each state who were eligible for the Program and state-specific poverty levels used as eligibility criteria are shown in Table 3 . The estimated numbers of eligible women were greater in heavily populated states such as California , Texas , New York and Florida than in the other states . The estimated percentage of women eligible for the Program was highest in New Mexico -LRB- 15.6 % ; CI 10.7 -- 20.5 % -RRB- , although that percentage was not statistically distinguishable from the percentage for Louisiana , Mississippi , and five other states . Similarly , while Minnesota 's estimated percent eligible appeared lowest -LRB- 2.8 % ; CI 1.2 -- 4.5 % -RRB- , it was not statistically distinguishable from Delaware , Massachusetts , and 11 other states . Table 3Number of women aged 40 -- 64 and estimated number of women eligible for the National Breast and Cervical Cancer Early Detection Program -LRB- NBCCEDP -RRB- , breast cancer screening , by state : 2-Year averages ; 2002 -- 2003U . S. populationEligible womenTotalPoverty criterionaNo . -LRB- thousands -RRB- 90 % CI -LRB- thousands -RRB- % Of totalb90 % CI -LRB- % -RRB- U.S. 46,899200 / 2503,5943,403 -- 3,7857.77.27 -- 8.06 Alabama7482005734 -- 807.64.6 -- 10.6 Alaska10325095 -- 128.55.5 -- 11.6 Arizona8072507241 -- 1028.95.3 -- 12.4 Arkansas4232003923 -- 559.25.7 -- 12.8 California5 ,506200476386 -- 5658.67.1 -- 10.2 Colorado7142505535 -- 757.75.0 -- 10.3 Connecticut5852002312 -- 344.02.0 -- 5.9 Delaware14325052 -- 83.71.7 -- 5.8 District of Columbia9225063 -- 96.63.5 -- 9.7 Florida2 ,805200262206 -- 3189.37.4 -- 11.2 Georgia1 ,4072009555 -- 1356.84.0 -- 9.5 Hawaii19625094 -- 144.52.1 -- 6.9 Idaho213200169 -- 237.24.1 -- 10.4 Illinois1 ,93620012385 -- 1606.34.5 -- 8.2 Indiana1 ,0112006036 -- 835.93.6 -- 8.2 Iowa4802502413 -- 355.02.7 -- 7.3 Kansas4292502413 -- 355.63.1 -- 8.0 Kentucky6692508054 -- 10612.08.4 -- 15.6 Louisiana71225010875 -- 14215.210.9 -- 19.5 Maine219250148 -- 196.23.9 -- 8.6 Maryland9332505431 -- 765.73.4 -- 8.0 Massachusetts1 ,0612504021 -- 603.82.0 -- 5.6 Michigan1 ,65525011076 -- 1436.64.7 -- 8.6 Minnesota8612502410 -- 392.81.2 -- 4.5 Mississippi4712506140 -- 8213.08.8 -- 17.1 Missouri8942005128 -- 735.73.3 -- 8.2 Montana159200159 -- 219.25.7 -- 12.8 Nebraska276225157 -- 225.32.8 -- 7.9 Nevada3412502817 -- 388.15.2 -- 11.0 New Hampshire225250116 -- 164.92.7 -- 7.0 New Jersey1 ,4582509666 -- 1266.64.6 -- 8.6 New Mexico2952504631 -- 6215.610.7 -- 20.5 New York3 ,212250262209 -- 3158.26.6 -- 9.7 North Carolina1 ,33020013797 -- 17610.37.5 -- 13.1 North Dakota10520074 -- 96.33.7 -- 9.0 Ohio1 ,96820011579 -- 1515.84.1 -- 7.6 Oklahoma5252004023 -- 577.64.5 -- 10.7 Oregon6152504527 -- 627.24.5 -- 10.0 Pennsylvania2 ,07025011177 -- 1455.43.8 -- 7.0 Rhode Island18125095 -- 134.92.9 -- 7.0 South Carolina6712004828 -- 687.24.3 -- 10.0 South Dakota11620085 -- 116.74.1 -- 9.4 Tennessee1 ,0252507040 -- 1006.84.0 -- 9.7 Texas3 ,205200396318 -- 47412.410.1 -- 14.7 Utah3022501910 -- 296.43.3 -- 9.4 Vermont11525052 -- 74.12.1 -- 6.1 Virginia1 ,2452006233 -- 915.02.7 -- 7.2 Washington1 ,0732007041 -- 996.53.9 -- 9.1 West Virginia3112003222 -- 4210.27.1 -- 13.4 Wisconsin9202504526 -- 654.92.8 -- 7.0 Wyoming8525096 -- 1210.57.1 -- 13.9 a 28 States and DC set income eligibility at 250 % of poverty , 21 states at 200 % of poverty and 1 state at 225 % of poverty . The estimated number of eligible women for the U.S. is based on the eligibility criteria used in each stateb Eligible women as percentage of all women aged 40 -- 64 years in that stateSource : Authors ' tabulations of data from the U.S. Census Bureau , Current Population Survey , 2003 -- 2004 . Annual Social and Economic Supplements . The percentages of eligible women who were screened through the Program varied greatly across states -LRB- Fig. 1 -RRB- . The percentage of eligible women screened by in individual state ranged from about 2.2 % -LRB- CI , 1.5 -- 2.8 % -RRB- to approximately 79 % -LRB- CI , 49.4 -- 108.9 % -RRB- . The median percentage screened among the states was 18.2 % -LRB- CI , 11.7 -- 24.7 % -RRB- . The tenth highest percentage estimate was 28.5 -LRB- CI , 23.2 -- 33.9 % -RRB- and the tenth lowest percentage estimate was 10.71 -LRB- CI , 7.4 -- 14.1 % -RRB- . Fig. 1Percentages of NBCCEDP eligible women screened for breast cancer , by State and District of Columbia , compared with the National Aggregate Percentage , 2002 -- 2003 . Note : The boxes show the percentage of eligible women screened by each state . The whiskers in each box , show the variation in the screening rate -LRB- the upper and lower CI -RRB- . NBCCEDP referes to National Breast and Cervical Cancer Early Detection Program . * States includes DC , sorted by percentage of eligible women screened . Source : Authors ' tabulations of data from the U.S. Census Bureau , Current Population Survey , 2003 -- 2004 . Annual Social and Economic Supplements , and from NBCCEDP April 2005 data Discussion We found that a large number of women -- 4 million women or 8.5 % of all U.S. women aged 40 to 64 -- were uninsured during 2002 -- 2003 and had incomes below 250 % of the federal poverty level , meeting Program eligibility requirements . Of these , only about 13.2 % received mammograms funded through the Program . Although many of the estimates for groups of women classified by race/ethnicity were imprecise , as indicated by wide CI , there was clearly wide variation in numbers and percentages of women eligible for the Program and in the percentages of eligible women who were screened . The percentage of eligible women screened was highest among American Indians and Alaska Natives . Although the estimates of eligible women in each state were also imprecise , the findings clearly showed wide variability . The percentage of eligible women screened in each state ranged from approximately 2 % to approximately 79 % . The Program is an important source of mammography screening services for low-income , uninsured women , but neither NBCCEDP nor other providers that serve this population are able to meet the current needs . The Program has grown since 1991/1992 when 38,476 women were screened in 12 states -LSB- 8 -RSB- to screen over 500,000 women during 2002/2003 in all states . A large number of federally funded community health centers , hospitals , clinics , and voluntary associations provide mammography screening services to underserved women . The numbers of women screened by these programs are not readily available . However , we know from the 2003 National Health Interview Survey -LRB- NHIS -RRB- that only 42.3 % of women with no health insurance and family incomes less than 250 % of the poverty level reported having had a mammogram during the previous two years -LRB- Robert Uhler , MS , Personal Communication , February 2006 -RRB- . Of the 4 million women we have identified in this study as eligible for the Program , the NHIS results indicate that about 1.7 million women were screened , meaning that approximately 1.2 million received screening outside of the Program . However , this leaves about 2.3 million low-income , uninsured women who did not obtain those services from either the Program or other sources . The largest numbers of women eligible for the Program were non-Hispanic White women . In contrast , the largest percentages of women eligible for the Program were from minority groups , except for women of Two or More Races . Hispanic and non-Hispanic American Indian/Alaska Native groups had the highest percentages of eligible women . We were limited in our ability to assess the extent to which the Program met the mammography screening needs of women by race/ethnicity because about 12,000 women screened in the Program were of unknown race/ethnicity . If we had been able to correctly allocate these women to their appropriate race/ethnic groups , the percentages of women screened would have differed from those shown , potentially by an important margin . However , the findings indicate that the Program was most successful in meeting the needs of American Indian/Alaska Native women , approximately 49 % of whom were screened . A possible reason for this success may be that these populations are the focus of health services through which the Program operates . In 1993 , Congress amended the Breast and Cervical Mortality Prevention Act , Public Law 108-183 , to authorize funding for American Indian/Alaska Native organizations and provided the opportunity to direct resources to these populations , specifically four grantees in Alaska and another nine geographically distributed across the contiguous United States . The number and percentage of women who were eligible for the Program varied greatly from state to state , because of differences in population size , age , and sex distributions , as well as differences in income and insurance coverage , including Medicaid -LSB- 18 -RSB- . In addition to the aforementioned factors , reasons for variations in the percentage of eligible women screened include differences in income eligibility criteria , presence of American Indian/Alaska Native grantee , CDC funding levels , other sources of funding , and organization and efficiency of the screening Programs . The upper and lower bounds of the CI indicate that some estimates were not precise , but were useful nevertheless . These estimates have been made available to each state for their use in Program planning to better understand the need for screening services in their states . Our study is subject to a number of limitations . As already noted , many of the estimates are imprecise because the numbers of women in the CPS ASEC sample who are eligible for the Program are relatively small . In addition , health insurance coverage could be underreported in the CPS ASEC given that the survey uses annual retrospective questions and respondents may have difficulty recalling the information -LSB- 18 -RSB- . Also , some women are eligible for the Program even if they have health insurance , but are underinsured , meaning the insurance does not cover mammography screening services , or there is a high copayment . Since CPS ASEC insurance questions do not measure covered services , these underinsured eligible women are not included in the denominators of our screening percentages . It is uncertain how many low-income women in the United States population are underinsured . Finally , our inability to define the race or ethnicity of some women in the study could result in an underestimate of the participation rate for any given race or ethnic group . We suggest two strategies to improve screening rates : increasing efficiencies of the Programs and improving their collaboration with other organizations . First , the Program must seek ways of increasing its efficiency to serve more women with existing resources . A study of Program costs found that the average cost of screening a woman through the Program was lower for grantees screening greater numbers of women because of economies of scale , that is , average cost decreased as number of women screened increased -LSB- 20 -RSB- . States with small populations in larger geographical areas may have limited opportunities to achieve such economies of scale . CDC has recently initiated a cost-effectiveness evaluation of the Program and is developing methods to better collect and analyze information on resources and how they might be used more efficiently . A variety of means to increase efficiency will need to be pursued . For example , many women in the Program are screened annually . The U.S. Preventive Services Task Force recommends screening every 1 -- 2 years because it has found little evidence that annual screening is more effective than biennial screening -LSB- 3 -RSB- . Many European programs provide screening every 2 -- 3 years -LSB- 21 -RSB- . The Program may need to evaluate the potential balance of health benefits from adopting a biennial schedule that could serve more women . Second , the Program needs to improve collaboration and coordination with other providers that serve a similar client population . The Program already coordinates substantially with private and nonprofit organizations , businesses , and other groups involved in breast cancer screening , but that coordination needs to be increased to recruit the women who are not currently being served . For example , in addition to providing screening services , the Program provides diagnostic services for eligible women screened by organizations outside of the Program . Alternative sources of diagnostic services may need to be pursued to free resources for increased screening of eligible women . Although greater efficiency and improved coordination with other screening providers could better meet the needs of underserved women , they are unlikely to be enough . Given that about 2.3 million low-income uninsured women did not obtain recommended breast cancer screening services in 2003 and that the Program provided those services to about 500,000 women ; increased efficiency and coordination alone will be insufficient to meet the needs of the eligible population . In 2000 , when Healthy People 2010 first set out its objectives of eliminating health disparities and increasing the proportion of women aged 40 and older who have received a mammogram within the previous two years to 70 % -LSB- 12 -RSB- , the greatest disparities in breast cancer screening were for women who had no health insurance , those who had no usual source of care , and recent immigrants -LSB- 5 -RSB- . Although progress has been made since 1987 in increasing mammography screening among low-income and uninsured women , the increases for low-income women are less than those for higher-income women , and screening among the uninsured lags far behind screening among women with private or public health insurance -LSB- 5 -RSB- . The Program contributes substantially to the effort to provide breast cancer screening services to those women by serving 13.2 % of those eligible . However , the Healthy People 2010 objectives are still far from being met .

O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O B I O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O

breast cancer
mammography screening
screening rates


Transient caloric restriction and cancer risk -LRB- The Netherlands -RRB- Over the past century , many animal experiments have shown that caloric restriction can reduce the risk of cancer , a finding that proved to be highly reproducible . Many papers have been published on its potential for human health , but until know little evidence is available on its actual effects in humans . In Utrecht , The Netherlands , we have been investigating the effects of the 1944 -- 1945 Dutch famine on breast cancer risk factors and breast cancer risk , and paradoxically the relatively short-term famine seemed to be related to increased breast cancer risk in later life . One of the differences between the famine situation and the large body of evidence from animal experiments is the duration of caloric restriction . Almost all animal experiments investigated sustained caloric restriction and information on the effects of short-term transient caloric restriction is very scarce . A search in the literature identified some animal experiments on short-term transient caloric restriction and these seemed to be at least supportive to the famine findings . Because caloric restriction in humans for preventive health measures would be mostly short-term , it is important to extend animal research on short-term caloric restriction . During the 20th century , a large body of experimental evidence has been accrued signifying that caloric restriction protects against cancer . Rodent data are abundant and consistently show -LRB- i -RRB- that caloric restriction lowers the incidence of a variety of spontaneous as well as induced or transplanted tumours ; -LRB- ii -RRB- that this effect is directly proportional to the amount of caloric restriction ; -LRB- iii -RRB- that the effects can largely be ascribed to caloric restriction per se , and not merely to the decrease in one or more dietary components ; -LRB- iv -RRB- that caloric restriction initiated in early life as well as in later life is effective in cancer prevention ; -LRB- v -RRB- that caloric restriction prolongs life -LSB- 1 -- 5 -RSB- . A pooled quantification of the inhibitory effects of caloric restriction on spontaneous mammary tumour incidence in mice showed that caloric restriction lowered the incidence with 55 % -LSB- 6 -RSB- . Preliminary reports on energy restriction in non-human primates appear to be consistent with findings in rodents -LSB- 7 , 8 -RSB- . What about humans ? Obviously , this is difficult to investigate , but can lead to important insights in cancer aetiology and to opportunities for prevention . The 1944 -- 1945 Dutch famine , a relatively short severe famine during World War II -LSB- 9 , 10 -RSB- , could shed some light on this issue , and has been used before as an `` experiment of history '' -LSB- 11 -- 13 -RSB- . During the past years , we have conducted several studies on the effects of the 1944 -- 1945 Dutch famine on breast cancer risk factors and breast cancer risk in Utrecht , The Netherlands . For these studies we used data on women who were between 2 and 33 years of age during the famine . Therefore we were not only able to investigate the long-term effects of caloric restriction , but could also relate those effects to specific time-windows in female development . Women were classified to their degree of famine experience on an individual basis , leading to a three-point famine score -LRB- ` absent ' , ` moderate ' , or ` severe ' exposure -RRB- that enabled dose-response evaluation -LSB- 14 -RSB- . In brief , we found that the famine is associated with subsequent reduced reproductive ability in women who were exposed during childhood . This is manifested by decreased chance of childbirth and an earlier mean age at menopause -LSB- 15 , 16 -RSB- . Strikingly , research on moderate early life diet restriction in Drosophila melanogaster by Tu and Tatar showed also a decrease in adult fecundity -LSB- 17 -RSB- . Furthermore , we found that hormone concentrations , measured postmenopausal , seem to be affected by the famine with increases in sex-steroid as well as insulin-like growth factor -LRB- IGF -RRB- - I and IGF binding protein -LRB- IGFBP -RRB- -3 levels -LRB- resulting in unaffected IGF-I to IGFBP-3 ratios -RRB- -LSB- 18 , 19 -RSB- . All our observations showed a dose-response to degree of famine exposure , with smaller but still observable associations in those moderately exposed . With regard to breast cancer risk , the associations between the famine and the reproductive system would suggest a protective effect of the famine -LSB- 20 -RSB- . However , the associations with hormone concentrations would suggest the contrary -LSB- 21 , 22 -RSB- , with the exception of increased IGFBP-3 that may relate to decreased breast cancer risk -LSB- 23 -RSB- . When we actually determined the effect of famine on breast cancer risk in this population , we found that the famine is related to increased risk , again in a dose response manner -- a finding that was stronger in women who were children during the 1944 -- 1945 winter -LSB- 24 -RSB- . Body mass index at later ages did not confound this relation nor modified it -LRB- last data unpublished -RRB- , suggesting that catch-up growth after the famine did not play an important role . Total cancer risk , exclusive of breast cancer , seemed not to be affected by the famine -LSB- 25 -RSB- , which does not preclude that famine may have affected risk of specific types of cancer , but the numbers in our study are presently too small for analysis with more detail . Another famine study by Dirx et al. on breast cancer risk could not detect a protection against breast cancer from the famine either , and if anything , showed a moderate increase in risk in women that were exposed at young ages -LSB- 11 -RSB- . In addition , Dirx et al. showed that the famine was , non-significantly , associated with increased prostate cancer and decreased colon cancer risk -LSB- 12 , 13 -RSB- . In these studies , Dirx et al. used place of residence as a measure of famine exposure whereas we used individual exposure data , based on recall . These findings are not in line with the animal experiments consistently showing caloric restriction to prevent cancer . Several differences between the usually adopted caloric deprivation strategy in animal experiments and the 1944 -- 1945 Dutch famine may explain these differences , such as the amount of restricted calories . The exact degree of caloric restriction during the 1944 -- 1945 Dutch famine is difficult to ascertain , but rations dropped to about 30 % of desired norms for adults and to about 50 % for young children . The relative amounts of carbohydrates , fats and proteins remained more or less balanced , and supplementations to the rations were sometimes clandestinely available . Young children were relatively protected within families and by charity organisations -LSB- 9 , 10 -RSB- . Although the amount of caloric restriction during this famine is larger than usually adopted in animal experiments , tumour incidence has been shown to decrease proportionally to degree of caloric restriction in animal experimental settings , amounting to an estimated 62 % tumour reduction with 53 % caloric restriction -LSB- 2 -RSB- . Therefore , it is unlikely that differences in the amount of caloric restriction explain the contradictory results of the famine studies and the animal experiments . More notably , during the Dutch famine people were transiently exposed for a relatively short duration of time -LRB- 6 months -RRB- -LSB- 9 , 10 -RSB- . Therefore , this `` experiment of history '' -- as most current famines due to crop disaster or war -- is only similar to experiments in rodents that studied short-term caloric restriction followed by ad libitum feeding , whereas the vast majority of these studies investigated dietary interventions that were sustained throughout the animals entire live . We were able to identify eight animal experiments that investigated transient and mostly short-term caloric restriction , where after animals were allowed to eat at will -LSB- 26 -- 33 -RSB- . Two of these experiments studied the effect of caloric restriction for different time periods during and after the chemically induction of breast cancer in female rats -LSB- 28 , 31 -RSB- . Sustained caloric restriction dramatically decreased tumour incidence : from 50 % in the ad libitum group to 20 % in the continuously restricted group -LSB- 31 -RSB- . It also seemed that caloric restriction during tumour initiation -- from 1 week before until 1 week after 7,12-dimethylbenz - -LSB- α -RSB- anthracene administration -- potently reduced mammary tumour development -LSB- 28 -RSB- . However , restriction for any period after tumour initiation followed by ad libitum feeding , if anything , showed no substantial effect , and could even lead to increased breast cancer risk -LSB- 28 -RSB- . Furthermore , Kritchevsky noticed that when rats were returned from restricted to ad libitum feeding this resulted in hyperphagia , accelerated weight gain , transient mammary hypertrophy , and enhanced tumour growth -LSB- 31 -RSB- . Four other experiments investigated the effect of caloric restriction for different periods on , amongst others , spontaneous overall tumour incidence in rats -LSB- 26 , 27 , 30 -RSB- , and mice -LSB- 29 -RSB- . Again , these studies showed that sustained caloric restriction throughout life lowered cancer risk substantially . However , caloric restriction confined to early life did either not affect cancer risk -LSB- 30 -RSB- , or actually seemed to increase it -LSB- 26 , 27 , 29 -RSB- . This feeding strategy did not materially increase lifespan , so this can not explain the observed increase in cancer risk . The study of Cheney et al. in female mice provides some evidence that caloric restriction confined to mid-life may also eventually lead to increased cancer burden -LSB- 29 -RSB- . Recently , interest was rekindled with two more studies on prolonged but transient caloric restriction and 1-methyl-1-nitrosaurea induced mammary carcinogenesis in rats -LSB- 32 , 33 -RSB- . These studies both show that upon refeeding tumour incidence increased . The disparity between our findings in humans after caloric restriction during a short and severe famine and the abundant literature on sustained caloric restriction and cancer risk in rodents may be ascribed to differences in exposure duration , as is corroborated by the abovementioned animal studies on transient caloric restriction that are in line with the famine observations . From a biological point of view , it may not be surprising that a short and transient period of caloric restriction in early life may increase human cancer risk . During caloric restriction , a range of responses can be seen , most of which could be directly beneficial to overall cancer risk but are unlikely to be of importance once the restriction is discontinued . Proliferation of cells is reduced with both increased rates of apoptosis together with decreased DNA synthesis and increased DNA repair , limiting the number of preneoplastic lesions . Oxidative stress is reduced , resulting in decreased reactive oxygen species that can damage DNA . Furthermore , of interest to hormone associated tumours , levels of a number of hormones and growth factors are altered during caloric restriction : glucocorticoids are increased whereas concentrations of IGF-I -LRB- and to a lesser extent IGFBP-3 resulting in decreased bioavailability of IGF-I -RRB- , insulin , prolactin , estrogens and leptin are decreased -LSB- 3 -- 5 , 34 -- 36 -RSB- . Changes in leptin levels can interfere with sexual maturation -LSB- 37 , 38 -RSB- , a period in development during which the Dutch famine showed the largest impact on breast cancer risk in our study . It could be that the hypothalamo-pituitary axis , which is not matured in girls until a few years after menarche when regular menses are established -LSB- 39 -RSB- , has erroneously adapted to the period of paucity , leading to inappropriate set-levels of hormones that could relate to hormone associated cancers -LSB- 18 , 19 -RSB- . Such erroneous adaptations , also described as a `` thrifty phenotype '' -LSB- 40 -RSB- , are the subject of the `` foetal and infant origins of adult disease '' hypothesis by Barker and colleagues -LSB- 41 -RSB- . Evidence is mounting that such long-lasting effects indeed exist and may contribute considerably to later health -LSB- 42 -RSB- . The potential involvement of the hypothalamo-pituitary axis herein has been recognised -LSB- 43 -RSB- . In conclusion , the general notion that caloric restriction prevents cancer needs some amendment , even for rodents . Evidence is strong that during caloric restriction , cancer risk is decreased proportionally to the amount of restriction , and such interventions can be effective whether started in early life or later . However , a short and transient period of restriction followed by a `` normal '' diet does not show such effects and could actually be detrimental . Thompson et al. made a similar plea . If humans are advised to eat less as a means to prevent cancer , this would probably result in repetitive periods of weight loss followed by periods of weight gain . He warned that such weight cycling may be associated with a modest acceleration of the carcinogenic response -LSB- 44 -RSB- . Animal experiments on short-term interventions or weight-cycling diets are scarce and their results yet inconclusive . Such animal experiments are nevertheless highly relevant and need further investigation before any preventive strategy is researched in experimental settings , or actually adopted , in humans , as short-term interventions are the most feasible for the human situation but may bring along considerable hazards . It would be of importance to see if our observations can be replicated in such animal experiments and in human studies making use of other famine episodes , e.g. the 1959 -- 1961 Chinese famine -LSB- 45 -RSB- . Other human studies may involve for instance children from countries with poor nutrition that are adopted by families in economically prosperous countries . These children have been exposed to adverse nutritional circumstances at young ages for a clearly demarcated period followed by nutritional abundance -LRB- in contrast to immigration studies of for example Japanese women to the United States who gradually adapt , often partly , to a Western lifestyle -RRB- . Indian girls adopted in Sweden have for example been shown to reach menarche at younger ages compared to Indian standards -LSB- 46 -RSB- . It would be intriguing to see whether other physiologic changes occur in these children , e.g. with regard to hormonal levels . Furthermore , studies on cancer risk in patients with anorexia nervosa are also of interest . Two studies have reported on the topic and found a decreased risk of breast cancer -LSB- 47 , 48 -RSB- . The generalisability of these observations is however troubled as factors underlying this disease may contribute to the decrease in breast cancer risk , so this may not merely be ascribed to a decreased caloric intake per se . Currently , the relation between famine exposure in early life and risk of other types of cancer than that of the breast is largely unknown . It would be valuable to further investigate these relations to see whether associations are different between cancer types , e.g. comparing hormone to non-hormone associated cancer types . This would give further insight into whether general mechanisms in human cancer aetiology are involved or whether adaptation of hormonal axes leading to harmful hormone concentrations is the potential culprit .

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O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O B O O O O O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O

caloric restriction
transient
cancer
risk
famine
human