Association between breast cancer risk and leisure physical activity in a rural cohort population.

BACKGROUND: Physical activity has been identified as a modifiable risk factor for breast cancer. Varying definitions of physical activity have made the evaluation difficult to analyze. In a state with high prevalence of obesity and elevated rates of breast cancer incidence and mortality, physical activity may be an important element for risk reduction. Women's participation in physical activity and the relation to breast cancer incidence has rarely been determined in the southern states where obesity are prevalent.
METHODS: Associations between various levels of physical activity and incident breast cancer cases among 21,665 subjects residing in Arkansas from 2007-2018 were completed. Multivariate logistic regression was used to estimate the odds ratios (OR) and 95% confidence intervals (95% CI), adjusting for various risk factors such as age, alcohol use, education, region, ethnicity, age at menarche, ever had children, and history of breastfeeding and family history of breast cancer. Stratification on menopausal status was performed to observe any breast cancer differences within the different biological pathways.
RESULTS: Among premenopausal subjects, inverse associations were observed among increase time in walking (OR =0.63, 95% CI: 0.36-1.11 and OR =0.47, 95% CI: 0.26-0.83) and overall weekly physical activity (OR =0.89, 95% CI: 0.50-1.57 and OR =0.52, 95% CI: 0.30-0.90) and breast cancer. No association was evident between the risk for breast cancer and physical activity among postmenopausal subjects. The relationship between physical activity and risk for breast cancer differed between menopausal statuses. The most apparent association was seen among premenopausal subjects with an increase in walking (P=0.01).
CONCLUSIONS: Although physical activity has been demonstrated to have a beneficial effect on breast cancer prevention among postmenopausal women, results from this study do not sufficiently support the hypothesis in this population. Results varied among menopausal status as well as among different definitions of physical activity. Further investigation is needed to identify factors contributing to de-attenuating the relationships. 2019 Translational Cancer Research. All rights reserved.

Introduction

Breast cancer is the most common cancer for women and encompasses 15% of all new cancer cases in the United States (1). It is the second leading cause of cancer death among women accounting for approximately 41,760 deaths annually (2). Numerous risk factors, both modifiable and nonmodifiable, have been identified for breast cancer risk. Nonmodifiable factors include age, race, menarche, reproductive history, personal breast cancer history, family history/genetic inheritance, and various medical treatments (3-9). A large part of breast cancer risk comes from modifiable risk factors such as reproductive history, sedentary lifestyle, hormone replacements, smoking, stress/anxiety, body weight, alcohol use, and physical activity (3-12). Of these modifiable risk factors, physical activity has been associated with a 20–80% reduction in the risk of breast cancer (3,7,13,14). The American Cancer Society recommends adults participate in a minimum of 150 minutes of moderate or 75 minutes of vigorous physical activity each week (15). Numerous studies have identified inverse associations between physical activity and breast cancer risk (3-8,10,11,13,14,16-33), as well as positive associations between sedentary behaviors and breast cancer risk (10,20,34). Physical activity is also known to have an inverse dose-response relationship with obesity (35). Despite knowing that being physically active and maintaining a healthy lifestyle decreases one’s risk for breast cancer, a substantial proportion of American adults remain physically inactive (36) and nearly 30% of adults 18 years and older in the U.S. have been classified as being obese (37) and the trend continues to increase (38). Particularly in the state of Arkansas, the current adult obesity rate as of 2017 was 35%, ranking the state 7th in the nation for obesity (39). Since 1997, the adult obesity rate has increased over the past 27 years (17% vs. 35%) (39). With the alarmingly high rate of obesity among Arkansan women, further investigation into the health effects resulting from lack of physical activity is necessary. By identifying preventative strategies such as physical activity, cases of breast cancer as well as obesity rates can be reduced.

Different mechanistic pathways for breast cancer have been proposed for pre- and post-menopausal women. After menopause, estrogen is largely produced in adipose tissue (40). These sex hormones have been identified to stimulate cellular proliferation in the breast; therefore an increase in adipose tissue in postmenopausal women has been identified as an increased risk for breast cancer (6,11,26,29,32,40). An association between lowering various circulating hormones and growth factors in the body and breast cancer development and progression has been identified (41). By preventing obesity and its adverse health outcomes, particularly relating to body’s responses to insulin, reduced inflammation and enhanced immune function are anticipated (42). Among premenopausal women, sex hormones are stored in the ovaries, therefore are less influenced by fat deposition, resulting in an inverse association between obesity and breast cancer (40). Given these known differences in breast cancer pathways between pre- and post-menopausal women, this study utilized data obtained from the Arkansas Rural Community Health (ARCH) Study, a largely rural cohort population in the mid-south region of the United States, to evaluate the association between leisure physical activities and breast cancer among pre- and post-menopausal women in Arkansas.

Methods

The present study used data collected from the Arkansas Rural Community Health (ARCH) Study cohort, formerly known as Spit for the Cure (43,44). Representation from all 75 counties in Arkansas is included in the cohort, as well as an overrepresentation among the African Americans. Although the cohort is racially diverse, education attainment is higher than the state average. The ARCH population was not intended to be representative of the entire female population. Baseline data including socioeconomic status, family and medical history, reproductive health, and physical activity were collected from 26,347 women between the ages of 18 and 100 through various community events. Among these women, 2,333 women were excluded due to reporting having a breast cancer diagnoses at baseline and 339 women were excluded due to missing or error in baseline information regarding breast cancer status. Those who participated at baseline and consented to be re-contacted were mailed a follow-up survey pertaining to their cancer status. Further linkage to the Arkansas Central Cancer Registry was performed annually through December 2018. A total of 193 women were excluded due to follow-up or Arkansas Central Cancer Registry information indicating having a positive breast cancer diagnosis at baseline. Overall, 23,482 women were eligible for the current study based on breast cancer status. 728 individuals were further excluded due to BMI or weight errors in data entry. A total of 823 women were also excluded due to missing or unsure menopausal status. The final dataset consists of 266 incident breast cancer cases and 21,665 non-cases. Among the cases, 77 reported being premenopausal and 189 reported being postmenopausal. Non-cases consisted of 12,128 premenopausal and 9,537 postmenopausal women. Study protocols are approved by the University of Arkansas for Medical Sciences Institutional Review Board.

Breast cancer case definitions

Baseline and follow-up survey data were self-reported, whereas cancer registry linkage results are based on medical record abstraction and have been adjudicated (45). Subjects were classified as free of breast cancer at baseline if they reported never having a breast cancer diagnosis at baseline and follow-up and do not to appear on the cancer registry linkage. Breast cancer cases were defined as any individual free of breast cancer diagnoses at enrollment and reported breast cancer diagnosis at least one year after they enrolled in the cohort either through cancer registry linkage or self-reported follow-up surveys (n=266). Any subject diagnosed within a year of their baseline survey were excluded (n=78) from the analysis to avoid potential bias due to underdiagnosed breast cancer at enrollment. Only subjects who had a diagnosis date and/or year at least one year after enrollment were included in the analysis. Subjects stating they were free of breast cancer at baseline and at the follow-up survey, responded “no” to ever having breast cancer in the follow-up, and were not identified in the cancer registry linkage were defined as non-cases in the study (n=21,665).

Physical activity assessment

Physical activity information was based on self-report measures at enrollment (21). Three different measurement and quantification tools were utilized to accurately assess physical activity. First, levels of physical activity were categorized within the self-report questionnaire as, “Vigorous Activity”, “Moderate Activity”, “Walking”, and “Sitting”, including examples of activities respective to each category. Examples of self-reported activities are provided in . As commonly reported in the literature, walking was separated from moderate activity due to, depending on how brisk, it generally falls into the lower end of the intensity spectrum for most people. It is thus used to investigate the potential health effects separately (46,47). Frequency of each activity level, as well as the duration of activities, was reported. Analyses were performed on each level of physical activity based on a calculation of total weekly minutes performed. The second assessment of physical activity was the overall amount performed calculated by cumulative weekly minutes of activity. This assessment excluded intensity level previously analyzed and utilized total summation of weekly minutes spent engaging in physical activity. The last assessment was defined as a metabolic equivalent of task (MET) score. The MET score was calculated for each individual based on existing literature (13,48-50). A MET is defined as the resting metabolic rate, the amount of oxygen consumed at rest (49,50). Each level of physical activity was categorized based on the amount of energy expended; more intense activities are given a higher numeric value. The calculation for an individual’s weekly MET score is as follows:

Table 1

Examples of physical actives by level

Physical activity level	Example of activity
Vigorous activity	Activities such as heavy lifting, digging, aerobics, or fast bicycling
Moderate activity	Activities such as carrying light loads, bicycling at a regular pace, or doubles tennis. Does not include walking
Walking	This includes at work and at home, walking to travel from place to place, and any other walking that you might do solely for recreation, sport, exercise, or leisure
Sitting	This includes time spent at work, at home, while doing course work, and during leisure time. This may include time spent sitting at a desk, visiting friends, reading, or sitting, or lying down to watch television

Weekly MET score = (weekly minutes spent sitting ×1) + (weekly minutes spent walking ×3.3) + (weekly minutes participating in moderate physical activity ×4) (weekly minutes participating in vigorous physical activity ×8).

Any subject who reported “None” for the past seven days of any level of physical activity was recorded as “0” for amount of time spent participating in the corresponding level of physical activity. This was applied for all three assessments of physical activity.

Other covariates

Body mass index (BMI) was calculated as: BMI = [weight (kg) ÷ height (m2)]. Subjects with unreliable or outlier data (less than 15 or greater than 50) were removed from the analyses (n=728). Sociodemographic information provided at baseline such as age (continuous), race (categorical), BMI (continuous), alcohol consumption (categorical), education level (categorical), and region (categorical) were included in the examination for potential confounding or effect modification. Race was analyzed as a categorical variable, white/European American (EA), black/African American (AA) and other. In the final stratified models, other racial groups were excluded from the analysis due to insufficient sample size (cases, n=3) and race was analyzed as a dichotomous variable, EA and AA. Region was analyzed as a dichotomous variable as Rural and Urban, classified by the subjects’ zip code at baseline using the rural-urban commuting area (RUCA) codes (51). Endogenous and exogenous hormonal factors potentially affecting the risk of breast cancer such as menarche (continuous), menopausal status (yes/no), ever given birth (yes/no), breastfeeding (yes/no), and family history of breast cancer (yes/no/unsure). Family history of breast cancer included the participants’ mother, sister, or daughters’ breast cancer history. Any recorded family history resulted in a family history of ‘yes’. Collection of breast cancer history among male relatives was not collected at baseline, due to the rareness of the disease (52). In the final stratified models, unsure of any family history groups were excluded from the analysis due to insufficient sample size (cases, n=1) and family history was analyzed as a dichotomous variable, yes or no. A composite variable was created to capture parity and breastfeeding history (never gave birth and never breastfed, at least one child and never breastfed, and had at least one child and had breastfed).

Statistical analyses

Differences in patient characteristics between cases and non-cases were evaluated using χ2 tests for categorical variables, and t-tests for continuous variables. Vigorous and moderate physical activity, as well as time spent walking, were categorized into three classes based on the distributions among cases; the first class being those who participated in the activity for less than one hour per week, the midpoint of the remaining values was identified to separate the lower and upper values into two classes. Time spent sitting, overall weekly physical activity, and the metabolic equivalent of task score were categorized based on tertiles, dividing the variables into three equal parts based on their distributions among cases.

Unconditional logistic regression was used to estimate crude and multivariable-adjusted odds ratios (ORs) and 95% confidence intervals (95% CI) to observe associations between increased breast cancer risk and physical activity. Tests for trend were performed by assessing physical activity tertiles as ordinal variables in the logistic regression model to observe their associations with breast cancer. Potential confounding variables for the association between physical activity and breast cancer were included in the multivariable logistic regression models. The most parsimonious model was used to estimate associations with breast cancer and physical activities, with covariates including age, BMI, parity/breastfeeding history, region, family history of breast cancer, and race. Each analysis performed was two-sided with P values of α less than 0.05. All analyses were performed using SAS version 9.3.

Results

Demographic information consisting of 266 incident breast cancer cases and 21,665 non-cases are summarized in by menopausal status. The majority of subjects self-identified as EA in both premenopausal (case =75.3%; non-case =73.2%) and postmenopausal (case =82.5%; non-case =77.2%) groups. Among premenopausal subjects, approximately 88% of cases completed either some college/technical degree or completion of college or postgraduate degree, while non-case slightly less non-cases (84.5%) received the same level of education. Education level was lower for postmenopausal subjects. Among cases, approximately 80% complete either some college/technical degree or completion of college or postgraduate degree versus 71% non-cases. Among both pre- and postmenopausal subjects, regardless of case status, there were more subjects who were classified as above a normal weight (overweight to severely obese) than at a normal weight (premenopausal: cases =62.4% vs. 33.8%, non-cases =58.9% vs. 38.2%; postmenopausal: cases =70.9% vs. 25.9%, non-case =69.7% vs. 27.2%, respectively). For both pre- and post-menopausal women, cases were more likely to have a family history of breast cancer when compared to non-cases (premenopausal: 32.5% vs. 12.5%; postmenopausal 29.1% vs. 20.6%). Only one case in the dataset was unsure of any family history of breast cancer. The cohort consisted primarily of subjects who had given birth (premenopausal: case =74.0%; non-cases =60.5%) (postmenopausal: case =89.4%; non-cases =86.4%); of those subjects, 49.1% of premenopausal cancer cases breastfeed, compared to 63.7% of premenopausal non-cases, whereas for postmenopausal cases, 48.5% breastfed and 47.4% of non-cases breastfed. Among premenopausal subjects who breastfed, non-cases were more likely to breastfeed at less than 6 months (51.2%) or 6 months to a year (31.1%) compared to cases (50.0% and 25.0% respectively), whereas cases were more likely to breastfeed more than non-cases for greater than one year (25.0% vs. 17.0%). Among postmenopausal subjects, non-cases were more likely to breastfeed for less than 6 months (51.7%) and greater than one year (17.2%) compared to cases (45.2% and 16.7% respectively), and cases were more likely to breastfeed 6 months to one year (35.7%) compared to non-cases (30.2%). Regardless of case or menopausal status, the majority of subjects drank alcohol never to once a year, and the least amount of subjects drank every day. Cases in both pre- and postmenopausal groups are more likely to reside in urban areas (54.6% and 57.1%), and non-cases are more likely to reside in rural areas (57.4% and 58.3%). Premenopausal non-cases are more likely to not have children and not breastfeed (38.8% vs. 26.0%) and have at least one child and breastfeed (38.5% vs. 36.4%) when compared to non-cases. Premenopausal cases are however more likely to have at least one child and not breastfeed when compared to non-cases (37.7% vs. 21.8%). Different patterns are seen among postmenopausal subjects; non-cases are more likely to not have children and not breastfeed than cases (12.1% vs. 9.5%), and cases are more likely to have at least one child and not breastfeed (46.0% vs. 45.1%) as well as have at least one child and breastfeed (43.4% vs. 41.0%) compared to non-cases. Mean age of cases (42 yrs) was eight years older than non-cases (34 yrs) among premenopausal subjects. Among postmenopausal subjects; mean age for cases (59 yrs) was three years older than non-cases (56 yrs).

Table 2

Sociodemographic characteristics of the population by breast cancer status

Characteristics	Premenopausal women							Postmenopausal women
	Case			Non-case		P		Case			Non-case		P
	N=77	%		N=12,128	%			N=189	%		N=9,537	%
Race						0.20							0.19
CA/White	58	75.3		8,876	73.2			156	82.5		7,360	77.2
AA/African American	19	24.7		2,776	22.9			30	15.9		1,901	19.9
Other	0	0.0		476	3.9			3	1.6		276	2.9
Missing	0	0.0		0	0.0			0	0.0		0	0.0
Education						0.21							0.05
Less than high school	0	0.0		243	2.0			8	4.2		428	4.5
High school graduate or GED	8	10.4		1,623	13.4			30	15.9		2,327	24.4
Some college or technical school	20	26.0		3,914	32.3			73	38.6		3,134	32.9
College or post graduate	48	62.3		6,335	52.2			78	41.3		3,638	38.1
Missing	1	1.3		13	0.1			0	0.0		10	0.1
BMI						0.56							0.47
Normal weight (18.5–24.9)	26	33.8		4,633	38.2			49	25.9		2,597	27.2
Overweight (25–29.9)	25	32.4		3,112	25.7			51	27.0		2,948	30.9
Obese (30–39.9)	18	23.4		3,202	26.4			70	37.0		3,052	32.0
Severely obese (≥40)	5	6.5		824	6.8			13	6.9		644	6.8
Missing	3	3.9		357	2.9			6	3.2		296	3.1
Given birth						0.02							0.27
No	20	26.0		4,704	38.8			18	9.5		1,155	12.1
Yes	57	74.0		7,337	60.5			169	89.4		8,244	86.4
Missing	0	0.0		87	0.7			2	1.1		138	1.5
Ever breastfeed§						0.02							0.82
No	29	50.9		2,640	36.0			87	51.5		4,300	52.2
Yes	28	49.1		4,674	63.7			82	48.5		3,909	47.4
Missing	0	0.0		23	0.3			0	0.0		35	0.4
Length of breastfeeding¶						0.50							0.47
Less than 6 months	14	50.0		2,419	51.2			38	45.2		2,055	51.7
6 months to 1 year	7	25.0		1,471	31.1			30	35.7		1,202	30.2
Greater than 1 year	7	25.0		802	17.0			14	16.7		683	17.2
Missing	0	0.0		34	0.7			2	2.4		37	0.9
Alcohol use						0.28							<0.01
Never to once a year	37	48.0		5,105	42.1			108	57.1		5,535	58.0
Once a month	16	20.8		3,518	29.0			27	14.3		1,801	18.9
Once a week to several times a week	23	29.9		3,257	26.9			35	18.5		1,850	19.4
Every day	0	0.0		171	1.4			14	7.4		291	3.1
Missing	1	1.3		77	0.6			5	2.7		60	0.6
Region						0.02							<0.01
Urban	42	54.5		4,904	40.4			108	57.1		3,844	40.3
Rural	35	45.5		6,961	57.4			81	42.9		5,557	58.3
Missing	0	0.0		263	2.2			0	0.0		136	1.4
Breastfeeding and children						<0.01							0.52
No children and do not breastfeed	20	26.0		4,704	38.8			18	9.5		1,155	12.1
Have children and do not breastfeed	29	37.7		2,640	21.8			87	46.0		4,300	45.1
Have children and breastfeed	28	36.3		4,674	38.5			82	43.4		3,909	41.0
Missing	0	0.0		110	0.9			2	1.1		173	1.8
Family history of breast cancer						<0.01							<0.01
No	52	67.5		10,358	85.4			133	70.4		7,391	77.5
Yes	25	32.5		1,515	12.5			55	29.1		1,964	20.6
Unsure	0	0.0		255	2.1			1	0.5		182	1.9
Missing	0	0.0		0	0.0			0	0.0		0	0.0
Age (yrs) (mean, SD)	42	7.6		34	9.7	<0.01		59	10.1		56	10.6	<0.01
Missing	1			61				0			32
BMI (mean, SD)	28.4	6.3		28.3	6.8	0.90		29.5	6.2		29.3	6.4	0.69
Missing	0			156				3			114
Menarche (yrs) (mean, SD)	12.9	1.7		12.4	1.7	0.05		12.3	1.6		12.5	1.7	0.07
Missing	0			162				1			157
Number of Children§ (mean, SD)	2	1.1		2	1.2	0.42		2	1.2		3	1.4	0.81
Missing	2			145				2			145

†, Chi-square test for categorical variables (including ‘missing’); ‡, t-test for continuous variables; §, when ever given birth = ‘yes’; ¶, when breastfeeding = ‘yes’. lbs, pounds; yrs, years; SD, standard deviation.

The results of the logistic regression models assessing the association between various forms of physical activity and breast cancer risk are summarized in . For the models analyzing vigorous and moderate physical activity, as well as time spend walking a referent of “less than 1 hour/week” was used. Models analyzing time spend sitting, overall weekly physical activity and metabolic equivalent of task score, a referent of the first tertile (lowest frequency of activity) was used.

Table 3

Odds ratios and 95% confidence intervals for association between different measurements of physical activity and breast cancer among premenopausal women

Physical activity type	Unadjusted						Adjusteda
	Case	Non-case	OR	95% CI	P		Case	Non-case	OR	95% CI	P
Vigorous physical activity	N=75	N=11,404			0.05		N=74	N=10,673			0.18
<1 hour/week	44	4,855	1.00	Ref.			43	4,536	1.00	Ref.
≥1 to 3.5 hours/week	16	4,115	0.43	0.24–0.76			16	3,876	0.51	0.29–0.92
>3.5 hours/week	15	2,434	0.68	0.38–1.22			15	2,261	0.79	0.43–1.44
Moderate physical activity	N=71	N=11,195			0.60		N=71	N=10,494			0.84
<1 hour/week	23	3,795	1.00	Ref.			23	3,525	1.00	Ref.
≥1 to 2.1 hours/week	24	2,833	1.40	0.79–2.48			24	2,674	1.55	0.86–2.77
>2.1 hours/week	24	4,567	0.87	0.49–1.54			24	4,295	0.96	0.54–1.71
Time spent walking	N=72	N=11,226			<0.01		N=72	N=10,510			0.01
<1 hour/week	26	2,291	1.00	Ref.			26	2,128	1.00	Ref.
≥1 to 3 hours/week	24	3,787	0.56	0.32–0.98			24	3,572	0.63	0.36–1.11
>3 hours/week	22	5,148	0.38	0.21–0.67			22	4,810	0.47	0.26–0.83
Time spent sitting	N=76	N=11,581			0.80		N=75	N=10,841			0.65
≤28 hours/week	29	4,694	1.00	Ref.			29	4,353	1.00	Ref.
>28 to 49 hours/week	25	3,536	1.14	0.67–1.96			25	3,347	1.23	0.72–2.12
>49 hours/week	22	3,351	1.06	0.61–1.85			21	3,141	1.13	0.64–2.01
Overall weekly physical activity	N=76	N=11,573			<0.01		N=75	N=10,828			0.02
≤3 hours/week	29	2,862	1.00	Ref.			28	2,674	1.00	Ref.
>3 to 7.1 hours/week	22	2,909	0.75	0.43–1.30			22	2,712	0.89	0.50–1.57
>7.1 hours/week	25	5,802	0.43	0.25–0.73			25	5,442	0.52	0.30–0.90
Metabolic equivalent of task score	N=76	N=11,646			0.04		N=75	N=10,897			0.19
≤3,486 METs	26	3,375	1.00	Ref.			26	3,138	1.00	Ref.
>3,486 to 4,878 METs	25	2,708	1.20	0.69–2.08			24	2,528	1.29	0.73–2.26
>4,878 METs	25	5,563	0.58	0.34–1.01			25	5,231	0.69	0.40–1.23

a, adjusted for age, BMI, family history, parity, breastfeeding history, region, and ethnicity. OR, odds ratio; CI, confidence interval; MET, metabolic equivalent of task; BMI, body mass index.

Table 4

Odds ratios and 95% confidence intervals for association between different measurements of physical activity and breast cancer among postmenopausal women

Physical activity type	Unadjusted						Adjusteda
	Case	Non-case	OR	95% CI	P		Case	Non-case	OR	95% CI	P
Vigorous physical activity	N=182	N=8,964			0.63		N=176	N=8,416			0.53
<1 hour/week	92	4,886	1.00	Ref.			89	4,591	1.00	Ref.
≥1 to 2.5 hours/week	46	1,830	1.34	0.93–1.91			44	1,719	1.34	0.92–1.94
>2.5 hours/week	44	2,248	1.04	0.72–1.49			43	2,106	1.08	0.74–1.57
Moderate physical activity	N=174	N=8,710			0.55		N=168	N=8,189			0.46
<1 hour/week	57	3,066	1.00	Ref.			55	2,860	1.00	Ref.
≥1 to 4 hours/week	63	3,050	1.11	0.77–1.60			61	2,887	1.10	0.76–1.58
>4 hours/week	54	2,594	1.12	0.77–1.63			52	2,442	1.16	0.79–1.70
Time spent walking	N=177	N=8,870			0.56		N=172	N=8,328			0.52
<1 hour/week	50	2,453	1.00	Ref.			49	2,294	1.00	Ref.
≥1 to 3 hours/week	65	3,045	1.05	0.72–1.52			64	2,874	1.05	0.72–1.53
>3 hours/week	62	3,372	0.90	0.62–1.31			59	3,160	0.89	0.60–1.31
Time spent sitting	N=185	N=9,183			0.96		N=179	N=8,606			0.59
≤28 hours/week	82	4,121	1.00	Ref.			80	3,863	1.00	Ref.
>28 to 42 hours/week	45	2,163	1.05	0.72–1.51			42	2,021	1.02	0.70–1.49
>42 hours/week	58	2,899	1.01	0.72–1.41			57	2,722	1.11	0.78–1.57
Overall weekly physical activity	N=186	N=9,191			0.56		N=180	N=8,613			0.72
≤3.4 hours/week	63	2,934	1.00	Ref.			62	2,736	1.00	Ref.
>3.4 to 11.2 hours/week	62	2,099	0.93	0.65–1.33			60	2,931	0.92	0.64–1.32
>11.2 hours/week	61	3,158	0.90	0.63–1.28			58	2,946	0.93	0.65–1.35
Metabolic equivalent of task score	N=186	N=9,255			0.55		N=180	N=8,670			0.98
≤3,297 METs	62	2,919	1.00	Ref.			59	2,733	1.00	Ref.
>3,297 to 5,430 METs	63	3,137	0.95	0.66–1.35			63	2,946	1.06	0.74–1.53
>5,430 METs	61	3,199	0.90	0.63–1.28			58	2,991	1.01	0.70–1.45

a, adjusted for age, BMI, family history, parity, breastfeeding history, region, and ethnicity. OR, odds ratio; CI, confidence interval; MET, metabolic equivalent of task; BMI, body mass index.

Limited associations between physical activity and breast cancer risk were observed among premenopausal subjects (). Breast cancer risk was significantly decreased for the second category of vigorous physical activity (OR =0.51, 95% CI: 0.29–0.92) and insignificantly decreased for the third category (OR =0.79, 95% CI: 0.43–1.44) with an insignificant trend (P=0.18). There was no association observed between moderate physical activity and breast cancer. A significant trend was seen in time spent walking (OR =0.63, 95% CI: 0.36–1.11 and OR =0.47, 95% CI: 0.26–0.83) among the second and third category (P=0.01). Breast cancer risk was insignificantly elevated in the second and third tertiles of time spent sitting (OR =1.23, 95% CI: 0.72–2.12 and OR =1.13, 95% CI: 0.64–2.01). Overall weekly physical activity was shown with an insignificant decrease in breast cancer risk for the second tertile (OR =0.89, 95% CI: 0.50–1.57) and a significant decrease in breast cancer risk in the third tertile (OR =0.52, 95% CI: 0.30–0.90), with an overall significant trend (P=0.02). A marginally significant decrease in breast cancer risk can be seen in those in the third tertile (OR =0.69, 95% CI: 0.40–1.23) for the MET scores, however the estimates did not decrease monotonically.

Association between breast cancer and physical activity for post-menopausal subjects is summarized in . An insignificant increase in breast cancer risk was seen in vigorous physical activity among the second category (OR =1.34, 95% CI: 0.92–1.94), while minimal difference was seen in the third (OR =1.08, 95% CI: 0.74–1.57). Similarly, minimal difference in risk was seen for the second category (OR =1.10, 95% CI: 0.76–1.58) and an insignificant increase in risk was seen for the third category (OR =1.16, 95% CI: 0.79–1.70) among moderate physical activity. Minimal change in risk in time spent walking was seen between the second or third category (OR =1.05, 95% CI: 0.72–1.53 and OR =0.89, 95% CI: 0.60–1.31, respectively). An insignificant increase in breast cancer risk among the third tertile (OR =1.11, 95% CI: 0.78–1.57) was seen for time spent sitting, although the test for trend was not significant (P=0.59), minimal difference was seen among the second tertile (OR =1.02, 95% CI: 0.70–1.49). Minimal decrease in risk for overall weekly physical activity was seen among the second and third tertiles (OR =0.92, 95% CI: 0.64–1.32 and OR =0.93, 95% CI: 0.65–1.35, respectively) with no apparent trend (P=0.72). Similarly, minimal increase in risk is seen for MET scores among the second and third tertiles (OR =1.06, 95% CI: 0.74–1.53 and OR =1.01, 95% CI: 0.70–1.45, respectively) with no evidence of a trend (P=0.98).

Discussion

Data from the ARCH study were utilized to examine associations between physical activity and breast cancer risk among EA and AA participants. Associations between physical activity and breast cancer among premenopausal subjects were evident, while the association was less apparent in postmenopausal subjects. Premenopausal subjects were observed to have more congruent associations among assessments that did not require the subject to define their intensity levels of physical activity, such as walking and overall hours of weekly physical activity. These differences observed within premenopausal subjects could be attributed to inaccurate self-reported physical activity. Although self-report questionnaires are one of the most common tools for measuring physical activity, their ability to produce valid and precise measurements is lacking (20,21). These self-reports may vary due to factors such as obesity and level of intensity (21). By asking participants to classify their intensity levels of each category, recall bias may occur as well as overlap between levels of activity intensity. Without requesting subjects to define their physical activities into different intensity levels, we see more significant associations in analyses examining overall amount of physical activity.

While not statistically significant, we observed a reduced risk for breast cancer among premenopausal subjects who participated in more vigorous physical activity. These results may be in part due to an excess amount of strenuous exercise in premenopausal subjects. This high-intensity athletic performance can cause various health abnormalities such as amenorrhea, and delayed menarche (22,29). This has been hypothesized to decrease a premenopausal woman’s risk for breast cancer due to the low levels of estrogen circulating in the body (22,29). In most of the previous studies examining breast cancer risk, the populations are largely comprised of postmenopausal subjects; fewer studies examine this relationship exclusively in premenopausal subjects. There is no scientific consensus regarding the intensity of physical activity level, as well as the period of exposure for a reduced risk of breast cancer among premenopausal subjects (29,32). Although the current study does not produce many significant findings on higher intense physical activities, different directions in breast cancer risk can be seen between premenopausal and postmenopausal subjects. These differences may indicate that the previously described pathways of breast cancer differ depending upon menopausal status. In agreement to previous literature, our data, although the majority not statistically significant, suggests physical activity produces a protective effect towards breast cancer among premenopausal subjects.

The present study was unable to establish an association between risk for breast cancer among postmenopausal subjects and physical activity. One hypothesis that may explain the null findings is obesity (7). It is evident in the literature that physical activity is needed to sufficiently reduce adiposity, thus reducing circulating estrogen levels in women postmenopausal (30,32,40). Despite knowing that a decrease in obesity is related to a decreased breast cancer risk, the optimal intensity level to decrease breast cancer risk in postmenopausal women is still under-defined (30). Previous studies have established that obesity has an association with breast cancer risk among postmenopausal subjects (4-8,10,11,23-32,53), particularly a dose-response relationship (30,37). While the current study adjusted for BMI as a confounding factor, given majority of this study cohort are overweight or obese (>60% and 70% among pre- and post-menopausal women, respectively), residual confounding may still occur due to inaccurate self-report measures. A subsequent analysis was carried out among postmenopausal subject, while stratifying among obesity status. However no significant differences were observed (results not shown).

Upon further investigation regarding the relationship between individuals BMI level and their overall amount of physical activity, we observed significant correlation among both premenopausal and postmenopausal subjects (data not shown). Within premenopausal subjects, we observed that as BMI increases, the overall amount of weekly physical activity decreases. A similar relationship was found among postmenopausal subjects, however the association was not as strong. We hypothesize that these differences regarding obesity may partially explain the findings presented in this study that physical activity was inversely associated with breast cancer among premenopausal subjects but not postmenopausal subjects. This may also be in part due to uncontrolled residual confounding (9).

Other explanations may account for the null associations found among breast cancer risk and physical activity observed among postmenopausal subjects. Information on other cancer type besides breast is not a variable at this point. Data collected at baseline as well as follow-up data were recorded using self-reported questionnaires. These responses are at an increased risk for recall bias due to social desirability and cognitive demands of recall (17). This may be particularly true for weight and waist and hip circumferences (20,21,54). These issues can be higher among cases undergoing treatment as well as having treatment-related or disease-related symptoms. Although cases were identified and surveys were collected a minimum of one year before diagnosis, undiagnosed cases may still have disease-related symptoms prior to diagnosis. As a result, individuals may have reflected modified behavior. Questions regarding self-reported physical activity at baseline were asked in regards to days participated and duration of participation. Several participants reported over six hours of vigorous physical activity seven days out of the week. This suggests that these questions are subject to possible misreporting bias (10). This bias could be due to social desirability or different interpretations of the different levels of physical activity among participants. Even though there was no distinction made regarding leisure time vs. occupational physical activity in the questionnaire, the literature indicates that there is a distinction between the two (27). Individuals may over or under report based on their occupational status, including or excluding physical activity that is carried out while at place of employment. Results of this study could be biased due to this distinction.

In general, when making comparisons among premenopausal and postmenopausal results, variation can be observed regarding the direction of associations. Overall, the relationship between physical activity and breast cancer among premenopausal subjects produced an inverse association. As the amount of any physical activity increases, the breast cancer risk generally decreases. Among postmenopausal subjects, non-significant direct associations can be seen for nearly all classifications of physical activity. However, among postmenopausal women, these relationships are minuscule. By observing the dissimilar directionality between women of differing menopausal statuses, we hypothesize that there are other unknown factors, particularly among postmenopausal women, that play a role in the risk for breast cancer.

Conclusions

This study identified that various levels of physical activity are likely to be associated with breast cancer risk among Arkansan women. While results were not established among postmenopausal subjects, more substantial results were found among premenopausal subjects. This study has highlighted that breast cancer risk is not equivalent between women of different menopausal status, and should be investigated individually, particularly regarding the covariate of obesity. While all findings did not provide significant associations, they cannot be ruled out. The lack of concordance in associations between menopausal statuses entails caution for the interpretation of these results. For all women, participation in moderate physical activity is encouraged. With substantial breast cancer incidence in the state of Arkansas, and few established modifiable risk factors are known, further investigation into physical activity is needed to accurately determine the relationship with breast cancer risk among both pre- and postmenopausal women.