Background:

Adolescence is a period of rapid prostatic growth, yet is understudied for susceptibility for future risk of prostate cancer. We examined cardiorespiratory fitness (CRF) in late adolescence in relation to long-term prostate cancer risk.

Methods:

A population-based cohort study was conducted of all 699,125 Swedish military conscripts during 1972–1985 (97%–98% of 18-year-old men) in relation to risk of prostate cancer overall, aggressive prostate cancer, and prostate cancer mortality during 1998–2017 (ages 50–65 years). CRF was measured by maximal aerobic workload, and prostate cancer was ascertained using the National Prostate Cancer Register. Muscle strength was examined as a secondary predictor.

Results:

In 38.8 million person-years of follow-up, 10,782 (1.5%) men were diagnosed with prostate cancer. Adjusting for sociodemographic factors, height, weight, and family history of prostate cancer, high CRF was associated with a slightly increased risk of any prostate cancer [highest vs. lowest quintile: incidence rate ratio (IRR), 1.10; 95% CI, 1.03–1.19; P = 0.008], but was neither significantly associated with aggressive prostate cancer (1.01; 0.85–1.21; P = 0.90) nor prostate cancer mortality (1.24; 0.73–2.13; P = 0.42). High muscle strength also was associated with a modestly increased risk of any prostate cancer (highest vs. lowest quintile: IRR, 1.14; 95% CI, 1.07–1.23; P < 0.001), but neither with aggressive prostate cancer (0.88; 0.74–1.04; P = 0.14) nor prostate cancer mortality (0.81; 0.48–1.37; P = 0.43).

Conclusions:

High CRF or muscle strength in late adolescence was associated with slightly increased future risk of prostate cancer, possibly related to increased screening, but neither with risk of aggressive prostate cancer nor prostate cancer mortality.

Impact:

These findings illustrate the importance of distinguishing aggressive from indolent prostate cancer and assessing for potential detection bias.

Prostate cancer is the second most common cancer in men and a leading cause of cancer mortality worldwide (1, 2). Early-life exposures may increase risk of prostate cancer later in life. Autopsy studies have reported that 10%–30% of men in their 30s have histologic foci of prostate cancer (3–5). Adolescence is a period of rapid prostatic growth (6), during which the prostate may be more susceptible to carcinogenic exposures (7), as previously demonstrated for the breast and other maturing organs (8). Carcinogenesis models have suggested that the initiating genomic alteration for prostate cancer often occurs in adolescence (9) and develops into prostate cancer precursor lesions observed in >50% of men in the next decade of life (10). Most studies of potential prostate cancer risk factors have focused on mid- or late-life exposures, long after the prostate has developed. Identification of modifiable early-life risk factors could enable men to reduce their lifetime risk for prostate cancer, and particularly aggressive prostate cancer which has high mortality.

Cardiorespiratory fitness (CRF) is a modifiable factor that may be associated with reduced prostate cancer risk through its associations with altered immune function, inflammatory cytokines, and insulin-like growth factors (IGF; refs. 11–16). High CRF may enhance immune function by increasing the number and activity of natural killer cells, neutrophils, and macrophages, which are tumor suppressive, and by reducing circulating cytokines (e.g., IL6 and TNFα), which have proliferative and antiapoptotic effects (14, 15). Men with high CRF also have been reported to have lower levels of IGF-1, which promotes cell growth, and higher levels of IGF-binding proteins, which have tumor suppressor effects (11, 12). Prostate biopsy studies have reported increased numbers of apoptotic prostate cancer cells in young men with high exercise levels (11–14).

Despite this evidence, CRF has seldom been examined in relation to prostate cancer risk because of the difficulty of measuring CRF in large cohorts of men and the decades of follow-up required. A few studies have examined CRF in mid-adulthood in relation to overall prostate cancer, but have yielded inconsistent findings that are difficult to interpret because of limited sample sizes and inability to distinguish aggressive from indolent prostate cancer (17–22). Other studies have examined self-reported physical activity in relation to overall prostate cancer risk, with inconclusive results (23–25). However, self-reported physical activity is a poor proxy for CRF (26, 27), the underlying physiologic factor affected by physical activity that may influence cancer risks, and is difficult to recall decades later. In contrast, CRF is objectively measured as VO2 max (maximal oxygen uptake), which measures the ability of the cardiovascular and respiratory systems to supply oxygen to skeletal muscles during sustained physical activity (28). To our knowledge, no prior studies have examined early-life CRF in relation to future risk of prostate cancer, which may help elucidate modifiable areas for prostate cancer prevention. We conducted a national cohort study of nearly 700,000 men in Sweden with objective measurement of CRF at age 18 years. Our aim was to examine early-life CRF in relation to the long-term risk of prostate cancer overall, aggressive disease, and mortality.

Study population

We identified 733,602 young men (mean age, 18.3 ± 0.8 years) who underwent a military conscription examination in Sweden during 1972–1985. These years were chosen to coincide with the initiation of CRF testing in 1972 and to have at least 32 years of follow-up to age 50 years or older. The military conscription examination was compulsory for all 18-year-old men nationally each year except for 2%–3% who either were incarcerated or had severe chronic medical conditions or disabilities documented by a physician. We excluded 34,477 (4.7%) men who had missing information for CRF during this period, leaving 699,125 men (95.3% of the original cohort) for analysis. This study was conducted in accordance with the Declaration of Helsinki and was approved by the Regional Ethics Review Board in Lund, Sweden (no. 2013/736). Participant consent was not required as this study used only deidentified registry-based secondary data.

Exposure measurement

CRF, muscle strength, height, and weight measurements at age 18 years were obtained from the Swedish Military Conscription Registry (29–36). CRF was measured as the maximal aerobic workload in Watts using a well-validated electrically braked stationary bicycle ergometer test, as described previously (29–37). Maximal aerobic workload is highly correlated with maximal oxygen uptake (VO2 max; correlation ∼0.9; ref. 38), and measurement using this bicycle ergometer test is highly reproducible, with a test–retest correlation of 0.95 (39). CRF measured in this manner was examined alternatively as a continuous variable and categorical variable in quintiles (<219, 219–239, 240–260, 261–290, and ≥291 Watts).

In addition to CRF, we examined muscle strength as a secondary predictor of interest because it represents a different aspect of physical fitness (29–36). Muscle strength was measured in Newtons using well-validated isometric dynamometer tests and calculated as the weighted sum of maximal knee extension, elbow flexion, and hand grip, as described previously (29–36, 40). Muscle strength was examined alternatively as a continuous variable and categorical variable in quintiles (<1,810, 1,810–1,982, 1,983–2,139, 2,140–2,324, and ≥2,325 Newtons).

Height and weight at age 18 years were measured using standard protocols and modeled alternatively as continuous variables and categorical variables in quintiles (29–36). Body mass index (BMI) also was examined as an alternative to height and weight. BMI was calculated as body weight in kilograms divided by the square of height in meters, and examined alternatively as a continuous and categorical variable using Centers for Disease Control and Prevention (CDC) definitions for adolescents up to age 19 years to facilitate comparability with U.S. studies. “Overweight” was defined as ≥85th and <95th percentile and “obesity” as ≥95th percentile on the CDC's 2000 sex-specific BMI-for-age growth charts, which correspond to BMI ≥25.6 and <29.0, and ≥29.0, respectively, for 18-year-old males (41). In this study, “normal BMI” refers to <85th percentile, which corresponds to BMI <25.6 for 18-year-old males.

Prostate cancer ascertainment

The study cohort was followed up for the earliest diagnosis of prostate cancer from January 1, 1998, through December 31, 2017, as identified using the National Prostate Cancer Register (NPCR) of Sweden. This register contains 98% of all incident prostate cancer cases since 1998 compared with the National Cancer Registry, to which reporting is mandated by law (42). NPCR also contains data on cancer characteristics including tumor grade according to Gleason score, disease stage according to the tumor–nodes–metastasis classification, and PSA level at diagnosis.

Aggressive prostate cancer was defined by clinical stage T3 or T4, Gleason score ≥8, and/or PSA ≥20 ng/mL at the time of diagnosis, based on criteria from the National Comprehensive Cancer Network Practice Guidelines (42, 43). Low-risk prostate cancer was defined as clinical stage T1–T2 with Gleason score 2–6 and PSA <10 ng/mL, and intermediate-risk prostate cancer as T1–T2 with Gleason score 7 and/or PSA 10–<20 ng/mL (42, 43). All deaths attributed to prostate cancer as the primary cause were identified from the Swedish Cause of Death Registry using International Classification of Diseases (ICD) codes (ICD-7: 177, ICD-8/9: 185, and ICD-10: C61). This registry includes deaths among all persons registered in Sweden since 1960, with compulsory reporting nationwide.

Covariates

Other variables that may be associated with CRF and prostate cancer were obtained from the Swedish Military Conscription Registry and national census data, which were linked using an anonymous personal identification number. The following were used as adjustment variables: birth date (modeled simultaneously as a continuous variable and categorical variable by decade), year of military conscription examination (continuous and categorical by decade), country of birth (Sweden/other), highest attained education level during the study period (≤9, 9–12, and >12 years), first-degree family history of prostate cancer (yes or no, ascertained at age 50 years using NPCR and Swedish Cancer Registry data), and average neighborhood socioeconomic status (SES) during the study period [composed of an index that includes low education level, low income, unemployment, and social welfare receipt, as described previously; ref. 44, and categorized as low (>1 SD below the mean), medium (within 1 SD from the mean), or high (>1 SD above the mean)]. Neighborhood SES was included because neighborhood deprivation has been associated with reduced CRF (45) as well as increased risk of prostate cancer diagnosis or mortality (46, 47). Data were >99% complete for each variable. Missing data for each variable were coded as a separate category, but had a negligible effect on the analyses because of their rarity.

Statistical analysis

Poisson regression with robust SEs was used to compute incidence rate ratios (IRR) and 95% confidence intervals (CI) for associations between CRF and subsequent risk of any prostate cancer, low- or intermediate-risk prostate cancer, aggressive prostate cancer, or prostate cancer mortality, examined in separate models. Two different adjustment models were used. The reduced model was adjusted only for birth date and year of the military conscription examination. The full model additionally included muscle strength, height, weight, country of birth, education level, neighborhood SES, and family history of prostate cancer. Poisson model goodness-of-fit was assessed using deviance and Pearson χ2 tests, which showed a good fit in all models. Potential interactions between CRF and covariates were explored in relation to prostate cancer risk on both the multiplicative and additive scale. All statistical tests were two-sided and used an α-level of 0.05. All analyses were conducted using Stata version 15.1.

In an exploratory subanalysis, we explored for evidence of detection bias (i.e., the possibility that men with high CRF were more likely to be diagnosed with prostate cancer because of increased screening) by assessing all ICD codes for cancer screening (ICD-9: V76 and ICD-10: Z12; reported in 3,336 men) and specifically prostate cancer screening (ICD-10: Z12.5; 780 men) during the study period in the Swedish Outpatient and Primary Care Registries. The Outpatient Registry started in 2001 and contains outpatient diagnoses from all specialty clinics nationwide. The Primary Care Registry initially included all primary care diagnoses from two populous counties covering 20% of the national population starting in 1998, then was gradually expanded to cover >75% of the national population by 2008 and onward.

In 38.8 million person-years of follow-up, 10,782 (1.5%) men were diagnosed with prostate cancer, including 1,817 (0.3%) with aggressive prostate cancer and 217 (0.03%) who died from prostate cancer (mean follow-up time, 39.5 years). The median age at the end of follow-up was 57.0 years (mean, 57.5 ± 4.2; range, 50.0–75.0). The median age at any prostate cancer diagnosis was 56.8 years (mean, 56.3 ± 4.3; range, 37.2–66.7), at aggressive prostate cancer diagnosis was 57.4 years (mean, 56.7 ± 4.4; range, 39.9–65.6), and at prostate cancer–related death was 55.5 years (mean, 54.7 ± 4.5; range, 41.4–64.3). Participant characteristics by CRF level are shown in Table 1 and by subsequent prostate cancer diagnosis or mortality in Supplementary Table S1.

Table 1.

Characteristics of study participants by CRF quintile, 1972–1985, Sweden.

CRF, Watts
<219219–239240–260261–290≥291
(n = 138,814)(n = 130,843)(n = 147,699)(n = 141,382)(n = 140,387)
%%%%%
Age at baseline, years (mean ± SD) 18.5 ± 1.0 18.3 ± 0.9 18.3 ± 0.8 18.2 ± 0.7 18.2 ± 0.6 
Muscle strength, Newtons (mean ± SD) 1,893 ± 289 2,014 ± 288 2,085 ± 294 2,148 ± 299 2,220 ± 304 
 <1,810 38.1 22.6 16.2 11.5 7.5 
 1,810–1,982 25.9 24.9 21.4 18.4 14.3 
 1,983–2,139 17.1 20.9 21.4 20.9 19.2 
 2,140–2,324 12.2 18.3 21.5 23.4 24.7 
 ≥2,325 6.7 13.2 19.5 5.8 34.2 
 Missing <0.1 <0.1 <0.1 <0.1 0.1 
Height, cm (mean ± SD) 176.5 ± 6.9 178.1 ± 6.6 179.0 ± 6.4 179.9 ± 6.4 181.3 ± 6.3 
 <174.0 32.0 23.3 19.1 14.9 10.1 
 174.0–176.9 18.0 17.3 15.9 14.6 12.1 
 177.0–180.9 23.1 24.9 25.0 24.8 23.4 
 181.0–183.9 12.7 15.1 16.5 17.8 19.0 
 ≥184.0 14.2 19.4 23.5 27.9 35.4 
 Missing <0.1 <0.1 <0.1 <0.1 <0.1 
Weight, kg (mean ± SD) 63.4 ± 9.7 67.4 ± 9.8 69.7 ± 9.9 71.5 ± 9.7 73.7 ± 9.0 
 <61.0 41.9 21.8 13.4 7.9 3.7 
 61.0–65.9 25.4 26.5 22.4 18.4 12.3 
 66.0–69.9 13.5 18.8 20.1 20.0 17.6 
 70.0–75.9 10.4 17.6 22.7 26.8 30.5 
 ≥76.0 8.8 15.3 21.4 26.9 35.8 
 Missing <0.1 <0.1 <0.1 <0.1 0.1 
BMI, kg/m2 (mean ± SD) 20.3 ± 2.8 21.2 ± 2.8 21.8 ± 2.8 22.1 ± 2.6 22.4 ± 2.4 
 Normal (<25.6) 95.4 93.3 91.7 91.2 91.5 
 Overweight (25.6–28.9) 3.0 4.6 5.9 6.5 6.6 
 Obesity (≥29.0) 1.6 2.1 2.4 2.2 1.8 
 Missing <0.1 <0.1 <0.1 0.1 0.1 
Born in Sweden 
 Yes 96.0 96.7 96.9 97.3 97.6 
 No 3.9 3.2 3.0 2.6 2.3 
 Missing 0.1 0.1 0.1 0.1 0.1 
Education (years) 
 ≤9 26.6 21.5 17.6 12.8 7.8 
 10–12 53.5 53.7 53.3 51.7 46.5 
 >12 19.9 24.8 29.0 35.5 45.7 
 Missing <0.1 <0.1 <0.1 <0.1 <0.1 
Neighborhood SES 
 Low 11.4 9.4 8.2 6.8 4.9 
 Medium 71.9 71.9 71.8 70.5 68.6 
 High 15.5 17.6 19.2 22.0 26.1 
 Missing 1.2 1.0 0.8 0.7 0.4 
Family history of PC 15.0 15.0 14.8 14.7 14.8 
CRF, Watts
<219219–239240–260261–290≥291
(n = 138,814)(n = 130,843)(n = 147,699)(n = 141,382)(n = 140,387)
%%%%%
Age at baseline, years (mean ± SD) 18.5 ± 1.0 18.3 ± 0.9 18.3 ± 0.8 18.2 ± 0.7 18.2 ± 0.6 
Muscle strength, Newtons (mean ± SD) 1,893 ± 289 2,014 ± 288 2,085 ± 294 2,148 ± 299 2,220 ± 304 
 <1,810 38.1 22.6 16.2 11.5 7.5 
 1,810–1,982 25.9 24.9 21.4 18.4 14.3 
 1,983–2,139 17.1 20.9 21.4 20.9 19.2 
 2,140–2,324 12.2 18.3 21.5 23.4 24.7 
 ≥2,325 6.7 13.2 19.5 5.8 34.2 
 Missing <0.1 <0.1 <0.1 <0.1 0.1 
Height, cm (mean ± SD) 176.5 ± 6.9 178.1 ± 6.6 179.0 ± 6.4 179.9 ± 6.4 181.3 ± 6.3 
 <174.0 32.0 23.3 19.1 14.9 10.1 
 174.0–176.9 18.0 17.3 15.9 14.6 12.1 
 177.0–180.9 23.1 24.9 25.0 24.8 23.4 
 181.0–183.9 12.7 15.1 16.5 17.8 19.0 
 ≥184.0 14.2 19.4 23.5 27.9 35.4 
 Missing <0.1 <0.1 <0.1 <0.1 <0.1 
Weight, kg (mean ± SD) 63.4 ± 9.7 67.4 ± 9.8 69.7 ± 9.9 71.5 ± 9.7 73.7 ± 9.0 
 <61.0 41.9 21.8 13.4 7.9 3.7 
 61.0–65.9 25.4 26.5 22.4 18.4 12.3 
 66.0–69.9 13.5 18.8 20.1 20.0 17.6 
 70.0–75.9 10.4 17.6 22.7 26.8 30.5 
 ≥76.0 8.8 15.3 21.4 26.9 35.8 
 Missing <0.1 <0.1 <0.1 <0.1 0.1 
BMI, kg/m2 (mean ± SD) 20.3 ± 2.8 21.2 ± 2.8 21.8 ± 2.8 22.1 ± 2.6 22.4 ± 2.4 
 Normal (<25.6) 95.4 93.3 91.7 91.2 91.5 
 Overweight (25.6–28.9) 3.0 4.6 5.9 6.5 6.6 
 Obesity (≥29.0) 1.6 2.1 2.4 2.2 1.8 
 Missing <0.1 <0.1 <0.1 0.1 0.1 
Born in Sweden 
 Yes 96.0 96.7 96.9 97.3 97.6 
 No 3.9 3.2 3.0 2.6 2.3 
 Missing 0.1 0.1 0.1 0.1 0.1 
Education (years) 
 ≤9 26.6 21.5 17.6 12.8 7.8 
 10–12 53.5 53.7 53.3 51.7 46.5 
 >12 19.9 24.8 29.0 35.5 45.7 
 Missing <0.1 <0.1 <0.1 <0.1 <0.1 
Neighborhood SES 
 Low 11.4 9.4 8.2 6.8 4.9 
 Medium 71.9 71.9 71.8 70.5 68.6 
 High 15.5 17.6 19.2 22.0 26.1 
 Missing 1.2 1.0 0.8 0.7 0.4 
Family history of PC 15.0 15.0 14.8 14.7 14.8 

Abbreviation: PC, prostate cancer.

CRF results

After adjusting for sociodemographic factors, height, weight, and family history, high CRF at age 18 years was associated with a slightly increased risk of any prostate cancer (e.g., highest vs. lowest quintile: IRR, 1.10; 95% CI, 1.03–1.19; P = 0.008; Table 2). This increased risk was driven by an association with low- or intermediate-risk prostate cancer, which comprised 83% of prostate cancer cases (highest vs. lowest quintile: IRR, 1.12; 95% CI, 1.04–1.22; P = 0.004; Table 2). However, CRF was neither significantly associated with risk of aggressive prostate cancer (highest vs. lowest quintile: IRR, 1.01; 95% CI, 0.85–1.21; P = 0.90) nor prostate cancer mortality (IRR, 1.24; 95% CI, 0.73–2.13; P = 0.42). The prostate cancer mortality risk estimates had low precision due to the small number of prostate cancer–related deaths (n = 217). When low-risk and intermediate-risk prostate cancer were examined separately, similar associations with CRF were found (Supplementary Table S2).

Table 2.

Associations between CRF or other factors at age 18 years (1972–1985) and subsequent prostate cancer diagnosis or mortality (1998–2017), Sweden.

Any PC (n = 10,782)Low- or intermediate-risk PC (n = 8,965)aAggressive PC (n = 1,817)bPC mortality (n = 217)
Reduced modelcFull modeldFull modeldFull modeldFull modeld
IRR95% CIIRR95% CIPIRR95% CIPIRR95% CIPIRR95% CIP
CRF (Watts, quintiles) 
 <219 1.00  1.00   1.00   1.00   1.00   
 219–239 1.06 1.00–1.12 1.03 0.97–1.09 0.31 1.05 0.98–1.12 0.15 0.96 0.83–1.09 0.51 0.85 0.55–1.32 0.48 
 240–260 1.13 1.07–1.19 1.07 1.01–1.13 0.02 1.09 1.02–1.17 0.007 0.97 0.84–1.11 0.64 1.31 0.88–1.93 0.18 
 261–290 1.15 1.08–1.22 1.07 1.00–1.14 0.04 1.08 1.01–1.16 0.03 1.00 0.86–1.16 0.99 1.28 0.82–1.99 0.27 
 ≥291 1.23 1.15–1.31 1.10 1.03–1.19 0.008 1.12 1.04–1.22 0.004 1.01 0.85–1.21 0.90 1.24 0.73–2.13 0.42 
 Per 50 Watts (trend) 1.08 1.05–1.11 1.03 1.01–1.06 0.02 1.04 1.01–1.07 0.008 1.00 0.93–1.07 0.99 1.15 0.94–1.40 0.19 
Muscle strength (Newtons, quintiles) 
 <1,810 1.00  1.00   1.00   1.00   1.00   
 1,810–1,982 1.06 1.00–1.12 1.04 0.98–1.11 0.17 1.06 1.00–1.14 0.06 0.94 0.82–1.09 0.41 0.87 0.57–1.32 0.52 
 1,983–2,139 1.07 1.01–1.14 1.05 0.99–1.12 0.12 1.07 1.00–1.15 0.05 0.95 0.82–1.11 0.51 0.94 0.61–1.46 0.79 
 2,140–2,324 1.12 1.06–1.19 1.11 1.04–1.18 0.002 1.13 1.05–1.21 0.001 1.01 0.86–1.17 0.95 0.90 0.57–1.41 0.64 
 ≥2,325 1.14 1.07–1.21 1.14 1.07–1.23 <0.001 1.21 1.12–1.30 <0.001 0.88 0.74–1.04 0.14 0.81 0.48–1.37 0.43 
 Per 300 Newtons (trend) 1.05 1.03–1.07 1.06 1.04–1.09 <0.001 1.08 1.06–1.11 <0.001 0.97 0.92–1.03 0.32 0.99 0.84–1.18 0.92 
Height (cm, quintiles) 
 <174.0 1.00  1.00   1.00   1.00   1.00   
 174.0–176.9 1.09 1.02–1.16 1.05 0.99–1.12 0.11 1.03 0.96–1.11 0.42 1.18 1.01–1.38 0.04 1.29 0.79–2.10 0.30 
 177.0–180.9 1.12 1.05–1.18 1.07 1.01–1.13 0.03 1.07 1.00–1.14 0.05 1.08 0.93–1.25 0.33 1.62 1.05–2.51 0.03 
 181.0–183.9 1.12 1.06–1.20 1.07 1.00–1.14 0.06 1.07 0.99–1.15 0.07 1.05 0.89–1.24 0.56 1.42 0.87–2.33 0.16 
 ≥184.0 1.15 1.09–1.22 1.09 1.02–1.16 0.009 1.06 0.98–1.13 0.13 1.26 1.09–1.49 0.003 1.75 1.10–2.79 0.02 
 Per 5 cm (trend) 1.03 1.02–1.05 1.02 1.01–1.04 0.002 1.02 1.01–1.04 0.006 1.03 0.99–1.07 0.13 1.08 1.04–1.12 <0.001 
Weight (kg, quintiles) 
 <61.0 1.00  1.00   1.00   1.00   1.00   
 61.0–65.9 1.06 1.00–1.12 0.98 0.92–1.04 0.53 0.98 0.91–1.05 0.49 1.00 0.86–1.17 0.99 1.19 0.76–1.87 0.44 
 66.0–69.9 1.12 1.05–1.19 0.99 0.92–1.06 0.71 0.97 0.90–1.05 0.48 1.05 0.89–1.24 0.54 1.06 0.65–1.75 0.81 
 70.0–75.9 1.12 1.05–1.19 0.96 0.89–1.03 0.24 0.96 0.88–1.03 0.25 0.97 0.81–1.15 0.72 0.88 0.53–1.46 0.62 
 ≥76.0 1.02 0.95–1.08 0.86 0.80–0.93 <0.001 0.83 0.76–0.91 <0.001 1.03 0.86–1.25 0.72 0.95 0.55–1.63 0.84 
 Per 5 kg (trend) 0.99 0.99–1.00 0.96 0.95–0.98 <0.001 0.95 0.94–0.97 <0.001 1.01 0.99–1.04 0.41 0.95 0.86–1.05 0.34 
BMI (kg/m2)e 
 Normal (<25.6) 1.00  1.00   1.00   1.00   1.00   
 Overweight (25.6–28.9) 0.86 0.78–0.94 0.87 0.79–0.95 0.003 0.83 0.75–0.92 <0.001 1.07 0.86–1.31 0.56 0.96 0.51–1.78 0.89 
 Obesity (≥29.0) 0.62 0.52–0.74 0.64 0.54–0.77 <0.001 0.57 0.46–0.70 <0.001 1.04 0.74–1.47 0.82 0.49 0.12–1.96 0.31 
 Per 5 BMI units (trend) 0.93 0.90–0.96 0.89 0.85–0.92 <0.001 0.86 0.83–0.90 <0.001 1.01 0.92–1.11 0.81 0.87 0.65–1.17 0.37 
Any PC (n = 10,782)Low- or intermediate-risk PC (n = 8,965)aAggressive PC (n = 1,817)bPC mortality (n = 217)
Reduced modelcFull modeldFull modeldFull modeldFull modeld
IRR95% CIIRR95% CIPIRR95% CIPIRR95% CIPIRR95% CIP
CRF (Watts, quintiles) 
 <219 1.00  1.00   1.00   1.00   1.00   
 219–239 1.06 1.00–1.12 1.03 0.97–1.09 0.31 1.05 0.98–1.12 0.15 0.96 0.83–1.09 0.51 0.85 0.55–1.32 0.48 
 240–260 1.13 1.07–1.19 1.07 1.01–1.13 0.02 1.09 1.02–1.17 0.007 0.97 0.84–1.11 0.64 1.31 0.88–1.93 0.18 
 261–290 1.15 1.08–1.22 1.07 1.00–1.14 0.04 1.08 1.01–1.16 0.03 1.00 0.86–1.16 0.99 1.28 0.82–1.99 0.27 
 ≥291 1.23 1.15–1.31 1.10 1.03–1.19 0.008 1.12 1.04–1.22 0.004 1.01 0.85–1.21 0.90 1.24 0.73–2.13 0.42 
 Per 50 Watts (trend) 1.08 1.05–1.11 1.03 1.01–1.06 0.02 1.04 1.01–1.07 0.008 1.00 0.93–1.07 0.99 1.15 0.94–1.40 0.19 
Muscle strength (Newtons, quintiles) 
 <1,810 1.00  1.00   1.00   1.00   1.00   
 1,810–1,982 1.06 1.00–1.12 1.04 0.98–1.11 0.17 1.06 1.00–1.14 0.06 0.94 0.82–1.09 0.41 0.87 0.57–1.32 0.52 
 1,983–2,139 1.07 1.01–1.14 1.05 0.99–1.12 0.12 1.07 1.00–1.15 0.05 0.95 0.82–1.11 0.51 0.94 0.61–1.46 0.79 
 2,140–2,324 1.12 1.06–1.19 1.11 1.04–1.18 0.002 1.13 1.05–1.21 0.001 1.01 0.86–1.17 0.95 0.90 0.57–1.41 0.64 
 ≥2,325 1.14 1.07–1.21 1.14 1.07–1.23 <0.001 1.21 1.12–1.30 <0.001 0.88 0.74–1.04 0.14 0.81 0.48–1.37 0.43 
 Per 300 Newtons (trend) 1.05 1.03–1.07 1.06 1.04–1.09 <0.001 1.08 1.06–1.11 <0.001 0.97 0.92–1.03 0.32 0.99 0.84–1.18 0.92 
Height (cm, quintiles) 
 <174.0 1.00  1.00   1.00   1.00   1.00   
 174.0–176.9 1.09 1.02–1.16 1.05 0.99–1.12 0.11 1.03 0.96–1.11 0.42 1.18 1.01–1.38 0.04 1.29 0.79–2.10 0.30 
 177.0–180.9 1.12 1.05–1.18 1.07 1.01–1.13 0.03 1.07 1.00–1.14 0.05 1.08 0.93–1.25 0.33 1.62 1.05–2.51 0.03 
 181.0–183.9 1.12 1.06–1.20 1.07 1.00–1.14 0.06 1.07 0.99–1.15 0.07 1.05 0.89–1.24 0.56 1.42 0.87–2.33 0.16 
 ≥184.0 1.15 1.09–1.22 1.09 1.02–1.16 0.009 1.06 0.98–1.13 0.13 1.26 1.09–1.49 0.003 1.75 1.10–2.79 0.02 
 Per 5 cm (trend) 1.03 1.02–1.05 1.02 1.01–1.04 0.002 1.02 1.01–1.04 0.006 1.03 0.99–1.07 0.13 1.08 1.04–1.12 <0.001 
Weight (kg, quintiles) 
 <61.0 1.00  1.00   1.00   1.00   1.00   
 61.0–65.9 1.06 1.00–1.12 0.98 0.92–1.04 0.53 0.98 0.91–1.05 0.49 1.00 0.86–1.17 0.99 1.19 0.76–1.87 0.44 
 66.0–69.9 1.12 1.05–1.19 0.99 0.92–1.06 0.71 0.97 0.90–1.05 0.48 1.05 0.89–1.24 0.54 1.06 0.65–1.75 0.81 
 70.0–75.9 1.12 1.05–1.19 0.96 0.89–1.03 0.24 0.96 0.88–1.03 0.25 0.97 0.81–1.15 0.72 0.88 0.53–1.46 0.62 
 ≥76.0 1.02 0.95–1.08 0.86 0.80–0.93 <0.001 0.83 0.76–0.91 <0.001 1.03 0.86–1.25 0.72 0.95 0.55–1.63 0.84 
 Per 5 kg (trend) 0.99 0.99–1.00 0.96 0.95–0.98 <0.001 0.95 0.94–0.97 <0.001 1.01 0.99–1.04 0.41 0.95 0.86–1.05 0.34 
BMI (kg/m2)e 
 Normal (<25.6) 1.00  1.00   1.00   1.00   1.00   
 Overweight (25.6–28.9) 0.86 0.78–0.94 0.87 0.79–0.95 0.003 0.83 0.75–0.92 <0.001 1.07 0.86–1.31 0.56 0.96 0.51–1.78 0.89 
 Obesity (≥29.0) 0.62 0.52–0.74 0.64 0.54–0.77 <0.001 0.57 0.46–0.70 <0.001 1.04 0.74–1.47 0.82 0.49 0.12–1.96 0.31 
 Per 5 BMI units (trend) 0.93 0.90–0.96 0.89 0.85–0.92 <0.001 0.86 0.83–0.90 <0.001 1.01 0.92–1.11 0.81 0.87 0.65–1.17 0.37 

Abbreviation: PC, prostate cancer.

aLow-risk PC was defined as clinical stage T1–T2 with Gleason score 2–6 and PSA <10 ng/mL, and intermediate-risk PC as T1–T2 with Gleason score 7 and/or PSA 10–<20 ng/mL.

bAggressive PC was defined as clinical stage T3–T4, Gleason score ≥8, and/or PSA ≥20 ng/mL.

cAdjusted for birth date and year of military conscription examination.

dAdjusted for birth date, year of military conscription examination, CRF, muscle strength, height, weight, country of birth, education, neighborhood SES, and family history of PC (except BMI was included as an alternative to height and weight in a separate model). The reference category for each variable is indicated by an IRR of 1.00.

eDefined on the basis of CDC criteria for males aged <20 years.

Compared with IRRs in the reduced model, adjustment for covariates in the full model (as above) resulted in substantially lower IRRs for any prostate cancer (Table 2), but negligible change for aggressive prostate cancer and slightly higher IRRs for prostate cancer mortality (Supplementary Table S3 compared with Table 2). Education level was the strongest confounder that accounted for these changes. Figure 1 shows the probability of diagnosis with prostate cancer by CRF level, adjusted for covariates.

Figure 1.

Probability of diagnosis with prostate cancer (PC, 1998–2017) by CRF at age 18 years (1972–1985), adjusted for covariates.

Figure 1.

Probability of diagnosis with prostate cancer (PC, 1998–2017) by CRF at age 18 years (1972–1985), adjusted for covariates.

Close modal

Secondary results

Similar to the results for CRF, high muscle strength was associated with a modestly increased risk of any prostate cancer (e.g., highest vs. lowest quintile: IRR, 1.14; 95% CI, 1.07–1.23; P < 0.001), which was driven by its association with low- or intermediate-risk prostate cancer (IRR, 1.21; 95% CI, 1.12–1.30; P < 0.001). However, muscle strength was neither associated with aggressive prostate cancer (highest vs. lowest quintile: IRR, 0.88; 95% CI, 0.74–1.04; P = 0.14) nor prostate cancer mortality (IRR, 0.81; 95% CI, 0.48–1.37; P = 0.43).

Height was positively associated with risk of any prostate cancer, aggressive prostate cancer, and prostate cancer mortality. Compared with men in the lowest quintile for height, those in the highest quintile had a 9% increased risk of any prostate cancer (IRR, 1.09; 95% CI, 1.02–1.16; P = 0.009), 26% increased risk of aggressive prostate cancer (IRR, 1.26; 95% CI, 1.09–1.49; P = 0.003), and 75% increased risk of prostate cancer mortality (IRR, 1.75; 95% CI, 1.10–2.79; P = 0.02) in the fully adjusted model.

In contrast, men in the highest quintile for weight at age 18 years had a slightly reduced subsequent risk of any prostate cancer compared with those in the lowest quintile (IRR, 0.86; 95% CI, 0.80–0.93; P < 0.001), but no significant difference in risk of aggressive prostate cancer (IRR, 1.03; 95% CI, 0.86–1.25; P = 0.72) and prostate cancer mortality (IRR, 0.95; 95%CI, 0.55–1.63; P = 0.84). Similarly, obesity at age 18 years was associated with a 36% lower risk of any prostate cancer (IRR, 0.64; 95% CI, 0.54–0.77; P < 0.001), but was neither significantly associated with risk of aggressive prostate cancer (IRR, 1.04; 95%CI, 0.74–1.47; P = 0.82) nor prostate cancer mortality (IRR, 0.49; 95%CI, 0.12–1.96; P = 0.31), compared with men who had a normal BMI at baseline.

Men with high education level or neighborhood SES had a significantly increased risk of low- or intermediate-risk prostate cancer, but neither aggressive prostate cancer nor prostate cancer mortality. No interactions between CRF or muscle strength and any other variables were found in relation to prostate cancer risk or mortality. When stratifying by height (above vs. below the median), only modest differences in risk estimates were seen (Supplementary Table S4). No significant additive or multiplicative interactions were found between CRF and height (Supplementary Table S5) or between muscle strength and height (Supplementary Table S6) in relation to risk of any prostate cancer, aggressive prostate cancer, or prostate cancer mortality.

Exploratory subanalysis

The association between CRF and the reported prevalence of any cancer screening or prostate cancer screening was examined to explore for potential detection bias because of increased screening in men with high CRF. ICD codes for cancer screening and prostate cancer screening were reported for 3,336 and 780 men, respectively. Using these available data, men in the highest CRF quintile were significantly more likely to have cancer screening (IRR, 1.34; 95% CI, 1.20–1.49; P < 0.001) or prostate cancer screening (IRR, 1.37; 95% CI, 1.10–1.72; P = 0.006), compared with those in the lowest quintile. These findings are consistent with the possibility of detection bias (i.e., the positive association observed between CRF and diagnosis with any prostate cancer may be because of increased screening among men with high CRF). Further adjustment for cancer screening or prostate cancer screening in the main analyses had a negligible effect on the risk estimates, possibly due to the scarcity of this information.

In this large population-based cohort, high CRF at age 18 years was associated with a modestly increased risk of any prostate cancer, and specifically low- or intermediate-risk disease. However, we found no significant association between CRF and risk of aggressive prostate cancer or prostate cancer mortality. The observed association with low- or intermediate-risk prostate cancer may be related to increased screening among men with high CRF, as suggested by our exploratory analysis of cancer screening. Also consistent with such an effect, we found that high education and neighborhood SES levels, which likely are associated with increased prostate cancer screening, were also associated with low- or intermediate-risk prostate cancer, but not with aggressive prostate cancer. These findings demonstrate the importance of distinguishing aggressive from indolent prostate cancer and assessing the possibility of detection bias in studies of prostate cancer risk factors.

Objectively measured CRF has seldom been examined in relation to overall prostate cancer risk (17–22), and to our knowledge never in relation to risk of aggressive prostate cancer. Prior studies of CRF in mid-adulthood in relation to overall prostate cancer have yielded conflicting results, possibly due to relatively small sample sizes and combining aggressive and indolent prostate cancer cases. A U.S. study with 337 prostate cancer cases in 4,920 men (mean age, 59 years) reported no significant association between CRF and overall prostate cancer risk, although there was a nonsignificant trend toward an inverse association (22). Another U.S. study with 634 self-reported prostate cancer cases in 19,042 men (mean age, 46 years), with an average follow-up of 9 years, reported a positive association between CRF and overall prostate cancer risk only before 1995 (i.e., during the first few years after introduction of PSA screening in 1987; ref. 18). This finding suggested the possibility of detection bias, wherein men with high CRF were more likely to be early adopters of PSA screening, leading to a spurious positive association with overall prostate cancer risk (18). A later study from the same cohort examined 1,310 prostate cancer cases at ages ≥65 years from Medicare records and reported similar findings, but also may have been susceptible to detection bias (19). A Finnish study with 127 prostate cancer cases in 2,268 men (mean age, 53 years; ref. 20) and a Norwegian study with 213 prostate cancer cases in 1,997 men (mean age, 50 years; ref. 21) reported no association between CRF and overall prostate cancer risk. All of these studies were based on sampling from selected clinics rather than national populations, and none examined the association between CRF and aggressive prostate cancer.

Other studies have suggested that self-reported high physical activity may be related to decreased risk of any prostate cancer. A meta-analysis that included 88,294 prostate cancer cases from 19 cohort studies and 24 case–control studies reported that high physical activity (variably defined and ascertained) was associated with a modestly reduced risk of any prostate cancer (pooled RR for highest vs. lowest category, 0.90; 95% CI, 0.84–0.95; ref. 24). However, a review of meta-analyses also concluded that the existing epidemiologic data are inconsistent and do not provide strong evidence to support an association between physical activity and risk of prostate cancer (25).

Because aggressive prostate cancer is common and lethal (1, 2), the identification of modifiable factors early in life is a public health priority. However, no modifiable behavioral risk factors have yet been identified, with the possible exception of BMI, for which evidence is inconsistent. Some (48, 49), but not all (50–52), studies have suggested a modest association between high BMI and risk of advanced prostate cancer (variably defined). A meta-analysis of 12 studies reported conflicting findings for BMI in relation to localized versus advanced prostate cancer risk: an inverse association with localized prostate cancer (RR per 5-unit increase in BMI, 0.94; 95% CI, 0.91–0.97), but a modest positive association with advanced prostate cancer (RR, 1.09; 95% CI, 1.02–1.16), with weak evidence for study heterogeneity (52). In contrast, we found that high BMI at age 18 years was associated with a reduced risk of any prostate cancer later in life, and was not significantly associated with aggressive prostate cancer or prostate cancer mortality. These conflicting findings need further elucidation in studies with longitudinal BMI measurements and the ability to distinguish aggressive from indolent prostate cancer.

To our knowledge, this study is the first to examine objectively measured muscle strength in relation to future risk of prostate cancer. Similar to the results for CRF, muscle strength was associated with a modestly increased risk of any prostate cancer, but neither with aggressive prostate cancer nor prostate cancer mortality. Our findings also suggested that tall men have a significantly increased risk for these outcomes. Men in the highest compared with lowest quintile for height had an estimated 26% (95% CI, 9%–49%) and 75% (10%–179%) higher risk of aggressive prostate cancer and prostate cancer mortality, respectively. These findings are consistent with prior studies that have linked tall height with increased risk of prostate cancer (49, 53) as well as other site-specific cancers (54). The underlying mechanisms are not established but may involve early exposure to growth factors such as IGF-I, which has been associated with prostate cancer risk (55).

Strengths of this study include objective measurement of CRF and prospective ascertainment of prostate cancer and cancer characteristics in a large population-based cohort. This study design helped minimize potential selection bias. The use of registry data with prospectively measured CRF, height, weight, family history, and socioeconomic factors also avoided recall bias.

This study also had several limitations. CRF and muscle strength were measured only once at age 18 years, and hence we were unable to examine changes in these factors over time. Although these characteristics often persist into adulthood, longitudinal measurements are needed to further assess cumulative lifetime exposures. Misclassification of CRF or muscle strength through submaximal effort by military conscripts during the testing could have influenced results toward the null hypothesis. Information on timing of puberty or testosterone levels was unavailable. Earlier puberty has been hypothesized to increase the risk of prostate cancer because of increased length of time that the prostate is exposed to high levels of androgens (56), and may also be associated with higher CRF or muscle strength in adolescence by leading to greater lean muscle mass (57). Despite an average follow-up of nearly four decades, this was still a relatively young cohort. The mean age at end of follow-up was 57 years, more than 10 years younger than the median age at prostate cancer diagnosis in Sweden (58) or worldwide (2). These men also were substantially leaner at age 18 years compared with current young men, and thus generalizability to later cohorts is uncertain.

In summary, in this large population-based cohort, men with high CRF or muscle strength at age 18 years had a slightly increased risk of prostate cancer later in life, likely related to increased screening among men with these characteristics. However, neither CRF nor muscle strength was significantly associated with risk of aggressive prostate cancer or prostate cancer mortality. Future studies with information on other early-life environmental exposures are needed to explore other modifiable factors that potentially could enable men to reduce their lifetime prostate cancer risk. Such studies should distinguish aggressive from indolent prostate cancer and assess for potential detection bias.

No potential conflicts of interest were disclosed.

The funding agencies had no role in the design and conduct of the study; in the collection, analysis, and interpretation of the data; or in the preparation, review, or approval of the article.

C. Crump: Conceptualization, formal analysis, validation, investigation, visualization, methodology, writing–original draft, writing–review and editing. P. Stattin: Conceptualization, resources, investigation, visualization, methodology, writing–review and editing. J.D. Brooks: Conceptualization, investigation, visualization, methodology, writing–review and editing. T. Stocks: Investigation, visualization, methodology, writing–review and editing. J. Sundquist: Conceptualization, resources, data curation, software, formal analysis, funding acquisition, validation, investigation, visualization, methodology, writing–review and editing. W. Sieh: Conceptualization, investigation, visualization, methodology, writing–review and editing. K. Sundquist: Conceptualization, resources, data curation, software, funding acquisition, investigation, visualization, methodology, writing–review and editing.

This work was supported by the Swedish Research Council and ALF project grant, Region Skåne/Lund University, Sweden. The collection and access to data in the National Prostate Cancer Register (NPCR) of Sweden was made possible by the continuous work of the NPCR steering group: P. Stattin (chairman), Ingela Franck Lissbrant (deputy chair), Camilla Thellenberg, Eva Johansson, Lennart Åström, Magnus Törnblom, Stefan Carlsson, Marie Hjälm Eriksson, David Robinson, Mats Andén, Ola Bratt, Jonas Hugosson, Maria Nyberg, Per Fransson, Fredrik Sandin, and Karin Hellström.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1.
Bray
F
,
Ferlay
J
,
Soerjomataram
I
,
Siegel
RL
,
Torre
LA
,
Jemal
A
. 
Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries
.
CA Cancer J Clin
2018
;
68
:
394
424
.
2.
Rawla
P
. 
Epidemiology of prostate cancer
.
World J Oncol
2019
;
10
:
63
89
.
3.
Sakr
WA
,
Grignon
DJ
,
Crissman
JD
,
Heilbrun
LK
,
Cassin
BJ
,
Pontes
JJ
, et al
High grade prostatic intraepithelial neoplasia (HGPIN) and prostatic adenocarcinoma between the ages of 20–69: an autopsy study of 249 cases
.
In Vivo
1994
;
8
:
439
43
.
4.
Sakr
WA
,
Haas
GP
,
Cassin
BF
,
Pontes
JE
,
Crissman
JD
. 
The frequency of carcinoma and intraepithelial neoplasia of the prostate in young male patients
.
J Urol
1993
;
150
:
379
85
.
5.
Bell
KJ
,
Del Mar
C
,
Wright
G
,
Dickinson
J
,
Glasziou
P
. 
Prevalence of incidental prostate cancer: a systematic review of autopsy studies
.
Int J Cancer
2015
;
137
:
1749
57
.
6.
Humphrey
PA
. 
Prostate gland development and anatomic structure
.
In
:
Prostate pathology
.
Chicago
:
American Society for Clinical Pathology
; 
2003
. p.
2
29
.
7.
Sutcliffe
S
,
Colditz
GA
. 
Prostate cancer: is it time to expand the research focus to early-life exposures?
Nat Rev Cancer
2013
;
13
:
208
518
.
8.
Chodosh
LA
,
D'Cruz
CM
,
Gardner
HP
,
Ha
SI
,
Marquis
ST
,
Rajan
JV
, et al
Mammary gland development, reproductive history, and breast cancer risk
.
Cancer Res
1999
;
59
:
1765
71s
.
9.
Diamandis
EP
,
Yu
H
. 
Does prostate cancer start at puberty?
J Clin Lab Anal
1996
;
10
:
468
9
.
10.
Gardner
WA
 Jr
,
Culberson
DE
. 
Atrophy and proliferation in the young adult prostate
.
J Urol
1987
;
137
:
53
6
.
11.
Soliman
S
,
Aronson
WJ
,
Barnard
RJ
. 
Analyzing serum-stimulated prostate cancer cell lines after low-fat, high-fiber diet and exercise intervention
.
Evid Based Complement Alternat Med
2011
;
2011
:
529053
.
12.
Rundqvist
H
,
Augsten
M
,
Stromberg
A
,
Rullman
E
,
Mijwel
S
,
Kharaziha
P
, et al
Effect of acute exercise on prostate cancer cell growth
.
PLoS One
2013
;
8
:
e67579
.
13.
Leung
PS
,
Aronson
WJ
,
Ngo
TH
,
Golding
LA
,
Barnard
RJ
. 
Exercise alters the IGF axis in vivo and increases p53 protein in prostate tumor cells in vitro
.
J Appl Physiol
2004
;
96
:
450
4
.
14.
Barnard
RJ
,
Leung
PS
,
Aronson
WJ
,
Cohen
P
,
Golding
LA
. 
A mechanism to explain how regular exercise might reduce the risk for clinical prostate cancer
.
Eur J Cancer Prev
2007
;
16
:
415
21
.
15.
Lehrer
S
,
Diamond
EJ
,
Mamkine
B
,
Droller
MJ
,
Stone
NN
,
Stock
RG
. 
C-reactive protein is significantly associated with prostate-specific antigen and metastatic disease in prostate cancer
.
BJU Int
2005
;
95
:
961
2
.
16.
Wekesa
A
,
Harrison
M
,
Watson
RW
. 
Physical activity and its mechanistic effects on prostate cancer
.
Prostate Cancer Prostatic Dis
2015
;
18
:
197
207
.
17.
Oliveria
SA
,
Kohl
HW
 III
,
Trichopoulos
D
,
Blair
SN
. 
The association between cardiorespiratory fitness and prostate cancer
.
Med Sci Sports Exerc
1996
;
28
:
97
104
.
18.
Byun
W
,
Sui
X
,
Hebert
JR
,
Church
TS
,
Lee
IM
,
Matthews
CE
, et al
Cardiorespiratory fitness and risk of prostate cancer: findings from the Aerobics Center Longitudinal Study
.
Cancer Epidemiol
2011
;
35
:
59
65
.
19.
Lakoski
SG
,
Willis
BL
,
Barlow
CE
,
Leonard
D
,
Gao
A
,
Radford
NB
, et al
Midlife cardiorespiratory fitness, incident cancer, and survival after cancer in men: the Cooper Center Longitudinal Study
.
JAMA Oncol
2015
;
1
:
231
7
.
20.
Laukkanen
JA
,
Pukkala
E
,
Rauramaa
R
,
Makikallio
TH
,
Toriola
AT
,
Kurl
S
. 
Cardiorespiratory fitness, lifestyle factors and cancer risk and mortality in Finnish men
.
Eur J Cancer
2010
;
46
:
355
63
.
21.
Robsahm
TE
,
Falk
RS
,
Heir
T
,
Sandvik
L
,
Vos
L
,
Erikssen
J
, et al
Cardiorespiratory fitness and risk of site-specific cancers: a long-term prospective cohort study
.
Cancer Med
2017
;
6
:
865
73
.
22.
Vainshelboim
B
,
Muller
J
,
Lima
RM
,
Nead
KT
,
Chester
C
,
Chan
K
, et al
Cardiorespiratory fitness and cancer incidence in men
.
Ann Epidemiol
2017
;
27
:
442
7
.
23.
Benke
IN
,
Leitzmann
MF
,
Behrens
G
,
Schmid
D
. 
Physical activity in relation to risk of prostate cancer: a systematic review and meta-analysis
.
Ann Oncol
2018
;
29
:
1154
79
.
24.
Liu
Y
,
Hu
F
,
Li
D
,
Wang
F
,
Zhu
L
,
Chen
W
, et al
Does physical activity reduce the risk of prostate cancer? A systematic review and meta-analysis
.
Eur Urol
2011
;
60
:
1029
44
.
25.
Markozannes
G
,
Tzoulaki
I
,
Karli
D
,
Evangelou
E
,
Ntzani
E
,
Gunter
MJ
, et al
Diet, body size, physical activity and risk of prostate cancer: an umbrella review of the evidence
.
Eur J Cancer
2016
;
69
:
61
9
.
26.
Lee
DC
,
Sui
X
,
Ortega
FB
,
Kim
YS
,
Church
TS
,
Winett
RA
, et al
Comparisons of leisure-time physical activity and cardiorespiratory fitness as predictors of all-cause mortality in men and women
.
Br J Sports Med
2011
;
45
:
504
10
.
27.
Myers
J
,
Kaykha
A
,
George
S
,
Abella
J
,
Zaheer
N
,
Lear
S
, et al
Fitness versus physical activity patterns in predicting mortality in men
.
Am J Med
2004
;
117
:
912
8
.
28.
Zeiher
J
,
Ombrellaro
KJ
,
Perumal
N
,
Keil
T
,
Mensink
GBM
,
Finger
JD
. 
Correlates and determinants of cardiorespiratory fitness in adults: a systematic review
.
Sports Med Open
2019
;
5
:
39
.
29.
Crump
C
,
Sundquist
J
,
Winkleby
MA
,
Sundquist
K
. 
Cardiorespiratory fitness and long-term risk of sleep apnea: a national cohort study
.
J Sleep Res
2019
;
28
:
e12851
.
30.
Crump
C
,
Sundquist
J
,
Winkleby
MA
,
Sundquist
K
. 
Height, weight, and aerobic fitness level in relation to the risk of atrial fibrillation
.
Am J Epidemiol
2018
;
187
:
417
26
.
31.
Crump
C
,
Sundquist
J
,
Winkleby
MA
,
Sundquist
K
. 
Aerobic fitness, muscular strength and obesity in relation to risk of heart failure
.
Heart
2017
;
103
:
1780
7
.
32.
Crump
C
,
Sundquist
J
,
Winkleby
MA
,
Sundquist
K
. 
Interactive effects of obesity and physical fitness on risk of ischemic heart disease
.
Int J Obes
2017
;
41
:
255
61
.
33.
Crump
C
,
Sundquist
J
,
Winkleby
MA
,
Sundquist
K
. 
Interactive effects of aerobic fitness, strength, and obesity on mortality in men
.
Am J Prev Med
2017
;
52
:
353
61
.
34.
Crump
C
,
Sundquist
J
,
Winkleby
MA
,
Sundquist
K
. 
Interactive effects of physical fitness and body mass index on risk of stroke: a national cohort study
.
Int J Stroke
2016
;
11
:
683
94
.
35.
Crump
C
,
Sundquist
J
,
Winkleby
MA
,
Sieh
W
,
Sundquist
K
. 
Physical fitness among Swedish military conscripts and long-term risk for type 2 diabetes mellitus: a cohort study
.
Ann Intern Med
2016
;
164
:
577
84
.
36.
Crump
C
,
Sundquist
J
,
Winkleby
MA
,
Sundquist
K
. 
Interactive effects of physical fitness and body mass index on the risk of hypertension
.
JAMA Intern Med
2016
;
176
:
210
6
.
37.
Nordesjo
L
,
Schele
R
. 
Validity of an ergometer cycle test and measures of isometric muscle strength when predicting some aspects of military performance
.
Swedish J Defence Med
1974
;
10
:
11
23
.
38.
Patton
JF
,
Vogel
JA
,
Mello
RP
. 
Evaluation of a maximal predictive cycle ergometer test of aerobic power
.
Eur J Appl Physiol Occup Physiol
1982
;
49
:
131
40
.
39.
Andersen
LB
. 
A maximal cycle exercise protocol to predict maximal oxygen uptake
.
Scand J Med Sci Sports
1995
;
5
:
143
6
.
40.
Hook
O
,
Tornvall
G
. 
Apparatus and method for determination of isometric muscle strength in man
.
Scand J Rehabil Med
1969
;
1
:
139
42
.
41.
Ogden
CL
,
Flegal
KM
. 
Changes in terminology for childhood overweight and obesity
.
Natl Health Stat Report
2010
;
25
:
1
5
.
42.
Van Hemelrijck
M
,
Wigertz
A
,
Sandin
F
,
Garmo
H
,
Hellstrom
K
,
Fransson
P
, et al
Cohort profile: the National Prostate Cancer Register of Sweden and Prostate Cancer data Base Sweden 2.0
.
Int J Epidemiol
2013
;
42
:
956
67
.
43.
Mohler
J
,
Bahnson
RR
,
Boston
B
,
Busby
JE
,
D'Amico
A
,
Eastham
JA
, et al
NCCN Clinical Practice Guidelines in Oncology: prostate cancer
.
J Natl Compr Canc Netw
2010
;
8
:
162
200
.
44.
Crump
C
,
Sundquist
K
,
Sundquist
J
,
Winkleby
MA
. 
Neighborhood deprivation and psychiatric medication prescription: a Swedish national multilevel study
.
Ann Epidemiol
2011
;
21
:
231
7
.
45.
Clennin
MN
,
Dowda
M
,
Sui
X
,
Pate
RR
. 
Area-level socioeconomic environment and cardiorespiratory fitness in youth
.
Med Sci Sports Exerc
2019
;
51
:
2474
81
.
46.
Li
X
,
Sundquist
K
,
Sundquist
J
. 
Neighborhood deprivation and prostate cancer mortality: a multilevel analysis from Sweden
.
Prostate Cancer Prostatic Dis
2012
;
15
:
128
34
.
47.
Zeigler-Johnson
CM
,
Tierney
A
,
Rebbeck
TR
,
Rundle
A
. 
Prostate cancer severity associations with neighborhood deprivation
.
Prostate Cancer
2011
;
2011
:
846263
.
48.
Rodriguez
C
,
Freedland
SJ
,
Deka
A
,
Jacobs
EJ
,
McCullough
ML
,
Patel
AV
, et al
Body mass index, weight change, and risk of prostate cancer in the Cancer Prevention Study II Nutrition Cohort
.
Cancer Epidemiol Biomarkers Prev
2007
;
16
:
63
9
.
49.
Perez-Cornago
A
,
Appleby
PN
,
Pischon
T
,
Tsilidis
KK
,
Tjonneland
A
,
Olsen
A
, et al
Tall height and obesity are associated with an increased risk of aggressive prostate cancer: results from the EPIC cohort study
.
BMC Med
2017
;
15
:
115
.
50.
Pischon
T
,
Boeing
H
,
Weikert
S
,
Allen
N
,
Key
T
,
Johnsen
NF
, et al
Body size and risk of prostate cancer in the European Prospective Investigation into Cancer and Nutrition
.
Cancer Epidemiol Biomarkers Prev
2008
;
17
:
3252
61
.
51.
Wright
ME
,
Chang
SC
,
Schatzkin
A
,
Albanes
D
,
Kipnis
V
,
Mouw
T
, et al
Prospective study of adiposity and weight change in relation to prostate cancer incidence and mortality
.
Cancer
2007
;
109
:
675
84
.
52.
Discacciati
A
,
Orsini
N
,
Wolk
A
. 
Body mass index and incidence of localized and advanced prostate cancer–a dose-response meta-analysis of prospective studies
.
Ann Oncol
2012
;
23
:
1665
71
.
53.
Genkinger
JM
,
Wu
K
,
Wang
M
,
Albanes
D
,
Black
A
,
van den Brandt
PA
, et al
Measures of body fatness and height in early and mid-to-late adulthood and prostate cancer: risk and mortality in The Pooling Project of Prospective Studies of Diet and Cancer
.
Ann Oncol
2020
;
31
:
103
14
.
54.
Aarestrup
J
,
Bjerregaard
LG
,
Meyle
KD
,
Pedersen
DC
,
Gjaerde
LK
,
Jensen
BW
, et al
Birthweight, childhood overweight, height and growth and adult cancer risks: a review of studies using the Copenhagen School Health Records Register
.
Int J Obes
2020
;
44
:
1546
60
.
55.
Travis
RC
,
Appleby
PN
,
Martin
RM
,
Holly
JMP
,
Albanes
D
,
Black
A
, et al
A meta-analysis of individual participant data reveals an association between circulating levels of IGF-I and prostate cancer risk
.
Cancer Res
2016
;
76
:
2288
300
.
56.
Giles
GG
,
Severi
G
,
English
DR
,
McCredie
MR
,
MacInnis
R
,
Boyle
P
, et al
Early growth, adult body size and prostate cancer risk
.
Int J Cancer
2003
;
103
:
241
5
.
57.
Herbst
KL
,
Bhasin
S
. 
Testosterone action on skeletal muscle
.
Curr Opin Clin Nutr Metab Care
2004
;
7
:
271
7
.
58.
Pettersson
A
,
Robinson
D
,
Garmo
H
,
Holmberg
L
,
Stattin
P
. 
Age at diagnosis and prostate cancer treatment and prognosis: a population-based cohort study
.
Ann Oncol
2018
;
29
:
377
85
.