***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: Background : A better underst and ing of factors that affect breast density , one of the strongest breast cancer risk indicators , may provide important clues about breast cancer etiology and prevention . This study evaluates the association of vitamin D and calcium , from food and /or supplements , to breast density in premenopausal and postmenopausal women separately . Methods : A total of 777 premenopausal and 783 post-menopausal women recruited at two radiology clinics in Quebec City , Canada , in 2001 to 2002 , completed a food frequency question naire to assess vitamin D and calcium .  Breast density from screening mammograms was assessed using a computer-assisted method . Associations between vitamin D or calcium and breast density were evaluated using linear regression models . Adjusted means in breast density were assessed according to the combined daily intakes of the two nutrients using generalized linear models . Results : In premenopausal women , total intakes of vitamin D and calcium were inversely related to breast density ( β = −1.4 ; P = 0.004 for vitamin D ; β = −0.8 ; P = 0.0004 for calcium ) . In multivariate linear regression , simultaneous increments in daily total intakes of 400 IU vitamin D and 1,000 mg calcium were associated with an 8.5 % ( 95 % confidence interval , 1.8 - 15.1 ) lower mean breast density . The negative association between  dietary vitamin D intake and breast density tended to be stronger at higher levels of calcium intake and vice versa . Among postmenopausal women , intakes of vitamin D and calcium were not associated with breast density . Conclusion : These findings show that higher intakes of vitamin D and calcium from food and supplements are related to lower levels of breast density among premenopausal women . They suggest that increasing intakes of vitamin D and calcium may represent a safe and inexpensive strategy for breast cancer prevention Background : Because of its nutrients and anabolic hormones , cow 's milk may promote height growth , which in turn has been related to breast cancer risk . We prospect ively investigated associations between dairy intakes and height growth . Methods : A cohort of 5,101 girls from throughout the United States completed annual surveys ( 1996 - 2001 , 2003 ) , providing height , weight , and past-year diet . At baseline , all were premenarchal , ages 9 years and above , with no serious medical conditions . We studied three outcomes : annual height growth , peak growth velocity , and adult height . Multivariate models estimated the effects of milk , cheese , yogurt , and energy on subsequent growth , adjusted for race/ethnicity , age , prior height , and body mass index . Other models studied fats and proteins . Results : Premenarchal girls who drank > 3 servings per day of milk  grew 0.11 in . ( P = 0.02 ) more the following year than girls consuming < 1 serving per day . Yogurt ( + 0.13 in./cup ; P = 0.02 ) , but not cheese or total calories , predicted height growth . In a separate model , dairy protein ( + 0.034 in./10 g ; P < 0.001 ) predicted height growth . Larger peak velocities were seen among girls reporting , at baseline , more milk ( > 3 glasses per day versus < 1 ; + 0.14 in . , P = 0.01 ) , more yogurt ( + 0.17 in./cup , P = 0.02 ) , and , in a separate model , more dairy protein ( + 0.039 in./10 g ; P = 0.003 ) . Baseline milk and dairy protein predicted taller adults .  Dairy protein was more important than dairy fat , for all outcomes . Nondairy animal protein and vegetable protein were never significant , nor were nondairy animal fat and vegetable fat . Conclusion : Of the foods/nutrients studied , dairy protein had the strongest association with height growth . These findings suggest that a factor in the nonlipid phase of milk , but not protein itself , has growth-promoting action in girls . ( Cancer Epidemiol Biomarkers Prev 2009;18(6):1881–7 Mammographic density is a strong risk factor for breast cancer ; however the mechanism that underlies this association is unclear . We hypothesized that measures of energy balance early in life and in adulthood may be associated with mammographic density . We conducted a cross-sectional analysis of 1,398 women in the Nurses ’ Health Study to examine associations between  physical activity , childhood and current body fatness , weight gain from age 18 years to present and mammographic density . Percent mammographic density was measured from digitized mammograms by a computer-assisted method . Demographic and lifestyle data were obtained from prospect ively collected question naires . For all analyses , subjects were stratified into three groups : premenopausal women , postmenopausal women not currently taking hormones  , and postmenopausal women currently taking hormones .  Childhood body fatness was inversely associated with mammographic density . The correlations ranged from −0.15 to −0.19 in the three strata of women ( P ≤ 0.001 ) . The difference in mean percent mammographic density between the leanest and heaviest body types ranged from 6.2 to 9.9 % . Similarly , adult body fatness was inversely associated with percent mammographic density . The correlations ranged from −0.41 to −0.48 in the three strata of women ( P < 0.0001 ) . The difference in mean percent mammographic density between the leanest and heaviest body types ranged from 22.3 to 35.1 % . Weight gain from age 18 was also inversely associated with mammographic density . There was no association between recent physical activity and mammographic density . These findings indicate that childhood and adult body fatness and weight change from age 18 are inversely associated with mammographic density Objective To examine the effects of various anthropometric determinants on mammographic patterns at postmenopausal ages , accounting for reproductive differences . Methods Mammograms from 900 post-menopausal women classified into high- ( P2/DY ) versus low-density ( N1/P1 ) groups using the Wolfe criteria were associated with changes in body figure , reported and measured height and weight , body mass index , hip , waist and chest circumferences , chest/hip ratio , waist/hip ratio ( WHR ) , breast size , and leg length . Reproductive factors included ages at menarche , first pregnancy and menopause , years since menopause , parity , and breast feeding duration . The study was nested within a large cross-sectional survey of a population -based breast cancer screening program in Northern Greece . Results Increasing chest circumference ( p = 0.002 ) , change in body build during adulthood to a heavier profile ( p = 0.04 ) , and heavy somatotype at age 18 ( p = 0.007 ) were the anthropometric determinants significantly associated with low-density mammographic patterns . Conclusions Chest circumference as a measure of upper body fat adiposity appears to be a stronger determinant of mammographic patterns than body fat distribution ( measured as WHR ) . A heavy body build in adulthood is associated with decreased mammographic density . Further studies are necessary to confirm our results , ideally prospect i ve cohorts , looking at the effect of anthropometric determinants on mammographic pattern changes over time and breast cancer risk Physical activity has been associated with a reduced risk of  breast cancer .  However , little is known about the association between recreational physical activity and mammographic density . We examined the association between recreational physical activity and mammographic density using mammograms from 375 white and African American women without breast cancer who served as controls in the Los Angeles component of the Women 's Contraceptive and Reproductive Experiences Study . We used data from 5 time periods of activity in the statistical analysis : from menarche to mammogram screening , the first 3 and 10 years after menarche , the most recent 10 years and the 3 years prior to mammogram screening . Lifetime history of recreational physical activity was obtained through interviews using a structured question naire . We used multiple linear regression to estimate least-squared mean values of absolute and percent mammographic density within categories of physical activity . Overall , we found no statistically significant evidence that physical activity reduced absolute or percent mammographic density . We observed a modest positive association between lifetime physical activity and percent mammographic density ( p for trend = 0.04 ) among younger women , and between recent physical activity and percent density among both younger ( < 50 years , p for trend = 0.09 ) and older ( > or = 50 years , p for trend = 0.06 ) women , but these associations diminished after additionally adjusting for body mass index ( BMI ) ( all p > or = 0.10 ) . However , among women younger than 50 years , we found some evidence for a protective effect of " strenuous " physical activity in the first 3 years after menarche , with a nonstatistically significant inverse association with both absolute ( p for trend = 0.07 ) and percent ( p for trend = 0.08 ) mammographic density after adjustment for BMI . Our results suggest that physical activity is not a strong predictor of mammographic density To examine the effects of dietary fat intake on breast cancer risk , we are conducting a r and omized trial of dietary intervention in women with extensive areas of radiologically dense breast tissue on mammography , a risk factor for breast cancer . Early results show that after 2 years on a low-fat , high-carbohydrate diet there is a significant reduction in area of density , particularly in women going through menopause . In women who went through menopause during the 2-year follow-up , the mean decreases in area of density and percentage of density in the intervention group were 11.0 cm2 and 11.0 % , respectively , whereas the control group decreased 4.5 cm2 and 5.2 % . The purpose of this analysis was to determine whether changes in intake of specific macronutrients could account for the observed reduction in breast density in these women . Differences between 2-year and baseline values of macronutrients ( averaged over 3 nonconsecutive days of food intake ) were calculated . We examined the effect of dietary variables , adjusted for changes in total calorie intake and weight and for family history of breast cancer , on changes in area of density and percentage of density using linear regression . Reduction in total or saturated fat intake or cholesterol intake was significantly associated with decreased dense area ( p < or = .004 ) . The most significant dietary variable associated with reduction in percentage of density was reduction in dietary cholesterol intake ( P = 0.001 ) , although reducing saturated fat intake was of borderline significance ( P = 0.05 ) . The effect of the membership in the intervention and control groups on change in area of density or percentage of density was reduced by models that included changes in intake of any fat , or cholesterol , or carbohydrates . The observation of an effect of diet at menopause on breast density , a marker of increased risk of breast cancer , may be an indication that exposures at this time have an enhanced effect on subsequent risk Background : The Alberta Physical Activity and Breast Cancer Prevention ( ALPHA ) Trial examined the influence of aerobic exercise on biological factors that are associated with breast cancer risk .  Mammographic density , a secondary outcome , is reported here . Methods : The ALPHA Trial was a parallel group r and omized controlled trial conducted between May 2003 and July 2007 . Postmenopausal , sedentary women ages 50 to 74 years ( n = 320 ) were evenly r and omized to aerobic exercise ( 45 minutes , 5 days per week ) or control ( usual life-style ) for 1 year . Dense fibrogl and ular tissue and nondense fatty tissue were measured from mammograms at baseline and 1 year using computer-assisted thresholding software for area measurements and a new technique that relies on the calibration of mammography units with a tissue-equivalent phantom for volumetric measurements . Results : Nondense volume decreased in the exercise group relative to the control group ( difference between groups = −38.5 cm3 ; 95 % confidence interval , −61.6 to 15.4 ; P = 0.001 ) . Changes in total body fat accounted for this decrease . Changes in dense area and dense volume , measures that have previously been associated with breast cancer risk , were not significantly different between the groups ( P ≥ 0.26 ) . Conclusions : Achieving changes in mammographic measures may require more exercise or a study population with higher baseline levels of sex hormones or a wider range of mammographic density . The data from this study , however , suggest that the protective effect of exercise on breast cancer risk may operate through a mechanism other than mammographic density . Cancer Epidemiol Biomarkers Prev ; 19(4 ) ; 1112–21 . © 2010 AACR Purpose Few studies have investigated the association between breast density and breast cancer by a family history of breast cancer , menopausal status , and postmenopausal hormone use ( PMH ) . We investigated if associations of breast density and breast cancer differ according to the status of these risk factors . Methods This study included 1,481 incident breast cancer cases diagnosed within the Nurses ’ Health Study I and II cohorts and 2,779 matched controls .  Breast density was measured from digitized film images with computerized techniques . Information on breast cancer risk factors was obtained prospect ively from the biennial question naires before the date of the cancer diagnosis for cancer cases and their matched controls . The data were analyzed with logistic regression . Results Breast cancer risk increased with increasing percent breast density in all strata ( p for trend in all subsets < 0.0001 ) . The density-related risk of breast cancer was similar in women with and without a family history ( OR = 4.00 [ 95 % CI 2.01–7.94 ] vs. 3. 
    Output:
    
There was no significant association between mammographic density and rate of dairy consumption , amount of sunlight exposure , and daily physical activity  .