Sedentary Behavior and Prostate Cancer Risk in the NIH–AARP Diet and Health Study

The etiology of prostate cancer remains poorly understood, and few modifiable risk factors have been identified (1). Sedentary behavior (sitting time) is now considered an important chronic disease risk factor, independent of moderate- to vigorous-intensity physical activity (2, 3). Sedentary behavior has been adversely associated with obesity, metabolic dysfunction, and chronic inflammation, processes that may be operative in carcinogenesis (4). Whether sedentary behavior is associated with prostate cancer risk has not yet been established. A small number of studies have examined prostate cancer risk across categories of occupations, comparing sedentary jobs with physically active jobs, but they produced conflicting results. Orsini and colleagues reported that men whose lifetime occupation has involved mostly sitting had a 27% increased risk of prostate cancer (5), whereas Thune and Lund reported a nonsignificant 30% increased risk among men reporting “mostly sedentary” occupations (6). In contrast, Lacey and colleagues found that men whose occupation entailed mainly sitting had a nonsignificant 40% lower risk of prostate cancer than men whose work involved light labor (7). To date, time spent in sedentary behaviors outside of occupation has not been examined in the context of prostate cancer risk. We examined whether self-reported daily sitting or television/video viewing time were associated with prostate cancer, independent of moderate- to vigorous-intensity physical activity.

The NIH–AARP Diet and Health Study was established in 1995–1996 with the mailing of a self-administered questionnaire that elicited information on diet, family history of cancer, anthropometry, and other lifestyle factors to 3.5 million members of the AARP. Members selected for the cohort were ages 50 to 71 years and resided in one of the six states (California, Florida, Louisiana, New Jersey, North Carolina, or Pennsylvania) or two metropolitan areas (Atlanta, Georgia and Detroit, or Michigan; ref. 8). Individuals who responded initially (n = 566,401) were sent a second questionnaire within 6 months of receipt of the baseline assessment. The second questionnaire collected more detailed information on cancer risk factors, including physical activity and sedentary behavior. The NIH–AARP Diet and Health Study received ethical approval from the Special Studies Institutional Review Board of the U.S. National Cancer Institute (Bethesda, MD). All participants provided written, informed consent.

The second questionnaire was completed by 334,906 participants between 1996 and 1997. We excluded participants who had had their baseline (n = 6,959) or second questionnaire (n = 3,424) completed by proxy respondents, females (n = 136,407) and participants with a previous diagnosis of cancer (n = 10,607). We further excluded 1,300 men due to missing data on sedentary behavior variables and 5,728 men with missing or extreme values of body mass index (BMI) or caloric intake. Extreme values were defined as log-transformed values two or more interquartile ranges below the 25th percentile, or two or more interquartile ranges above the 75th percentile. The analytic cohort comprised 170,481 men.

Histologically confirmed incident prostate cancer cases, diagnosed through December 31, 2006, were identified through linkage to 11 state cancer registry databases. These state cancer registries met the certification requirements defined by the North American Association of Central Cancer Registries, and were estimated to achieve close to 90% case ascertainment within 24 months (9). Advanced prostate cancer cases had clinical or pathologic tumor classifications of T3 or T4, N1 status, or M1 status, or were incident cases first identified by state cancer registry who subsequently died of prostate cancer between 1995 and 2006. Prostate cancer mortality cases were extracted from the National Death Index through December 31, 2008; mortality cases were not linked to incidence data derived from state cancer registries. Prostate cancer mortality was defined as cases where the underlying or contributing cause of death was prostate cancer.

The main exposure variables, total daily sitting and television/video viewing time, were assessed by the second questionnaire. Participants were asked “during a typical 24-hour period over the past 12 months, how many hours did you spend?”: sitting (less than 3 hours; 3–4 hours, 5–6 hours, 7–8 hours, 9 or more hours per day) or watching television or videos (none, less than 1 hour, 1–2 hours, 3–4 hours, 5–6 hours, 7–8 hours, and 9 or more hours per day). We combined the first two response options for television into less than 1 hour per day, due to the very small proportion (0.6%) of respondents who reported watching no television/videos. Similarly, we combined the final two response options for television into 7 or more hours per day (only 1.9% of respondents had reported watching 9 or more hours per day). To ensure an adequate number of cases across categories for analyses examining risk of advanced prostate cancer or prostate cancer mortality, we collapsed the exposure categories for sitting (less than 3 hours, 3–4 hours, 5–6 hours, 7 or more hours per day) and television/video viewing (less than 3 hours, 3–4 hours, 5 or more hours per day).

We examined the bivariate associations of potentially confounding variables with total prostate cancer risk and sedentary behavior variables to help guide the selection of covariates to be included in multivariate models. All covariates were assessed by self-administered questionnaire. Sociodemographic factors were reported at baseline: age (years), race (White, Black, other); marital status (married/de facto, widowed, divorced/separated, never married), and educational attainment (less than 12 years, finished high school, some college, college graduate). Also assessed at baseline were family history of prostate cancer (yes, no), personal history of diabetes (yes, no), BMI (kg/m²), smoking status (never, former, current), caloric intake (kcal, quartiles), and alcohol intake (ethanol g/day, quartiles). Moderate- to vigorous-intensity physical activity in the past 10 years was assessed by the second questionnaire (less than weekly, weekly but less than 1 hour per week, 1–3 hours per week, 4–7 hours per week, more than 7 hours per week). History of prostate-specific antigen testing and digital rectal examination (in past 3 years, yes; no) was also recorded by the second questionnaire.

Cox proportional hazards regression was used to estimate multivariate HRs and 95% confidence intervals (CI) of prostate cancer, using the time of follow-up as the underlying time metric. Person-time was calculated starting with the date at second questionnaire return and ending at the date at event (diagnosis of prostate cancer, death, move out of cancer registry catchment area, end of study follow-up). We considered potential interactions of sedentary behavior variables with family history of prostate cancer, race, BMI, moderate- to vigorous-intensity physical activity, history of digital rectal examination, and history of prostate-specific antigen testing. We also examined the risk separately for disease onset before the age of 65 years, and after the age of 65.

The cohort was followed for an average period of 8.5 years, during which 13,751 incident prostate cancer cases were ascertained. The median age at diagnosis was 69.5 years. We also examined associations of sedentary behavior with risk of advanced prostate cancer (n = 1,365) and with prostate cancer mortality (n = 669).

The characteristics of the study population at baseline are presented in Table 1. Greater amounts of sitting time were associated with receiving a college education, a higher BMI, personal history of diabetes, more television viewing, and less recreational physical activity.

Neither self-reported daily sitting time nor television/video viewing time was associated with risk of total or advanced prostate cancer, nor with prostate cancer mortality (Tables 2 and 3). There were no meaningful differences in HRs or 95% CIs between age-adjusted and multivariate models; hence only multivariate results are presented.

There were no interaction effects between sitting time or television/video viewing time and family history of disease, race, moderate- to vigorous-intensity physical activity, history of digital rectal examination, or history of prostate-specific antigen testing (results not shown). However, a statistically significant interaction effect was found for television/video viewing time and BMI (P = 0.02). We therefore stratified our analyses by BMI, and saw some suggestion that sedentary behavior may be associated with an increased risk of prostate cancer amongst obese men, and with a reduced risk of prostate cancer amongst men in the healthy weight range (Tables 2 and 3).

For men ages less than 65 years, no significant association was seen for daily sitting time (HR ≥7 vs. <3 h/day = 0.92; 95% CI, 0.74–1.15) or for television/video viewing time (HR ≥5 vs. <3 h/day = 1.01; 95% CI, 0.81–1.26). Similarly, amongst men ages 65 years or older, there was no association for either daily sitting time (HR = 0.92; 95% CI, 0.75–1.12) or for television/video viewing time (HR = 0.90; 95% CI, 0.75–1.09).

In this large, prospective investigation, we found scant evidence for associations between self-reported measures of sedentary behavior and risk of prostate cancer. The data were suggestive of some effect modification by BMI category for television/video viewing time and total prostate cancer risk, and for both daily sitting and television/video viewing time and advanced prostate cancer risk/prostate cancer mortality.

Previous studies that examined prostate cancer risk across occupational activity categories found conflicting results (5–7). These studies used an estimate of usual occupational activity to examine the association with sitting in the workplace, whereas we were able to examine prostate cancer risk in relation to estimated daily sitting and television/video viewing time (a highly prevalent leisure-time sedentary behavior). It is unlikely, however, that the different behavior setting in which sitting occurs would significantly affect the biologic response to the exposure. Hence, our mostly null results provide further conflicting evidence pertaining to sedentary behavior and prostate cancer risk.

The etiology of prostate cancer remains poorly understood, and few modifiable risk factors have been identified, although there is evidence to suggest that the interrelations of energy intake, body composition, and physical activity play some role in prostate cancer etiology (10). Studies that have examined the associations between physical activity and prostate cancer risk stratified by BMI have demonstrated no associations amongst healthy weight and overweight men, but an inverse association amongst obese men (1).

The reasons for the observed risk variation across BMI categories in this study are not clear. The apparent elevation in risk amongst obese men could reflect the compounded biologic exposures resulting from obesity and sedentary behavior. For example, both obesity and sedentary behavior have been independently associated with metabolic dysfunction (4), a factor that may facilitate prostate cancer development and progression (1, 11). The favorable muscle:fat ratio of lean men may help to counteract some of the deleterious biologic consequences of sedentary behavior that may be operative in prostate cancer risk (12). Obesity has been hypothesized to mediate many of the pathways by which sedentary behavior affects cancer risk (4). The associations between sedentary behavior, body composition, and prostate cancer are clearly complex, and further research is necessary to elucidate these pathways.

A previous report from the NIH–AARP Diet and Health Study did not find a significant association between vigorous-intensity physical activity and total, advanced, or fatal prostate cancer (13). However, another report from the same cohort examined the associations of physical activity with prostate cancer risk separately for White and Black men, and found that 4 or more hours of moderate/vigorous intensity physical activity, compared to with infrequent activity, during early adulthood provided a 35% lower risk of prostate cancer (14). No significant interaction effect was noted in our study; hence, we did not stratify our analyses by race.

In this study, advanced prostate cancer was defined primarily by tumor—node—metastasis criteria. The Gleason scoring system offers a prostate cancer-specific method for defining advanced disease, and this method would likely have enlarged the number of cases defined as “advanced.” For the purpose of our analyses, however, it is unlikely that the use of the Gleason scoring system would have altered the study results, given the consistently null associations demonstrated across the different prostate cancer outcomes.

Our findings imply that sedentary behavior does not make a significant, independent contribution toward prostate cancer risk. However, some pertinent methodologic issues should be considered when interpreting the results. It is possible that use of self-report measures led to measurement error, biasing results toward the null. Although the psychometric properties of the sedentary behavior items used in this study have not been established, they have previously been associated with an increased risk of all-cause and cancer mortality (15), colon cancer (16), and endometrial cancer (17), and are similar to items that have demonstrated reasonable reliability and validity (18–21). However, the validation of these similar items was limited by the lack of adequate gold-standard for sedentary behavior. Studies have estimated convergent validity by comparing sedentary behavior items against activity logs (19, 20) or accelerometer data (19, 21), which can be imprecise.

Screening bias has also been suggested as a possible problem in studies such as ours. Health-conscious men may spend less time sitting and also may be more likely to be screened for, and therefore diagnosed with, prostate cancer (22). We adjusted our multivariate models for participants' prostate-specific antigen and digital rectal examination screening before baseline, but were unable to adjust for subsequent screening, and therefore our adjustment may be incomplete. Study strengths include the prospective design, large sample, and ability to control for many important confounding factors. We were also able to isolate advanced cases of prostate cancer to examine these separately.

This is the first study to consider whether self-reported daily sitting or television/video viewing time was associated with prostate cancer risk. We did not demonstrate an association, but there is sufficient biologic plausibility to warrant further investigation that may confirm or refute our findings. Future studies would benefit from the use of more accurate and comprehensive assessment of sedentary behavior, such as previous day recalls or objective measures of sedentary time (23, 24).

A.R. Hollenbeck is a consultant/advisory board member of Society of Psychologists in Management and Love/Avon Army of Women Scientific Advisory Council. No potential conflicts of interest were disclosed by the other authors.

The views expressed herein are solely those of the authors and do not necessarily reflect those of the FCDC or FDOH. The Pennsylvania Department of Health specifically disclaims responsibility for any analyses, interpretations, or conclusions.

Conception and design: B.M. Lynch, C.M. Friedenreich, A.R. Hollenbeck, C.E. Matthews

Development of methodology: C.M. Friedenreich, S.C. Moore

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): A.R. Hollenbeck

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): B.M. Lynch, C.M. Friedenreich, K.A. Kopciuk, S.C. Moore

Writing, review, and/or revision of the manuscript: B.M. Lynch, C.M. Friedenreich, K.A. Kopciuk, A.R. Hollenbeck, S.C. Moore, C.E. Matthews

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): C.E. Matthews

Study supervision: C.M. Friedenreich, C.E. Matthews

The authors thank participants in the NIH–AARP Diet and Health Study for their outstanding cooperation, Sigurd Hermansen and Kerry Grace Morrissey from Westat for study outcomes ascertainment and management, Leslie Carroll at Information Management Services for data support and analysis, and Farah Khandwala (Alberta Health Services—CancerControl) for her assistance with data management. Cancer incidence data from the Atlanta metropolitan area were collected by the Georgia Center for Cancer Statistics, Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia. Cancer incidence data from California were collected by the California Cancer Registry, California Department of Public Health's Cancer Surveillance and Research Branch, Sacramento, California. Cancer incidence data from the Detroit metropolitan area were collected by the Michigan Cancer Surveillance Program, Community Health Administration, Lansing, Michigan. The Florida cancer incidence data used in this report were collected by the Florida Cancer Data System (Miami, Florida) under contract with the Florida Department of Health, Tallahassee, Florida. Cancer incidence data from Louisiana were collected by the Louisiana Tumor Registry, Louisiana State University Health Sciences Center School of Public Health, New Orleans, Louisiana. Cancer incidence data from New Jersey were collected by the New Jersey State Cancer Registry, Cancer Epidemiology Services, New Jersey State Department of Health, Trenton, New Jersey. Cancer incidence data from North Carolina were collected by the North Carolina Central Cancer Registry, Raleigh, North Carolina. Cancer incidence data from Pennsylvania were supplied by the Division of Health Statistics and Research, Pennsylvania Department of Health, Harrisburg, Pennsylvania. Cancer incidence data from Arizona were collected by the Arizona Cancer Registry, Division of Public Health Services, Arizona Department of Health Services, Phoenix, Arizona. Cancer incidence data from Texas were collected by the Texas Cancer Registry, Cancer Epidemiology and Surveillance Branch, Texas Department of State Health Services, Austin, Texas. Cancer incidence data from Nevada were collected by the Nevada Central Cancer Registry, State Health Division, State of Nevada Department of Health and Human Services, Las Vegas, Nevada.

This work was supported by the AARP and the Intramural Research Program of the NIH, National Cancer Institute. Brigid M. Lynch is funded by a Public Health Training Fellowship from the National Health and Medical Research Council (586727) and the Victorian Government's Operational Infrastructure Support Program. Christine M. Friedenreich is funded by an Alberta Innovates-Health Solutions Health Senior Scholar Award, and is the Alberta Cancer Foundation Weekend to End Women's Cancers Breast Cancer Chair.