Body mass index trajectories and prostate cancer risk: Results from the EPICAP study

Predicted body fat percentage, fat mass and lean body mass in relation to risk of prostate cancer: Results from the NHANES 1999 to 2010

The purpose of this study is to examine the relationship between fat mass (FM), body fat percentage (BF%), lean body mass (LM), and prostate cancer (PCa), and evaluate their potential impact on the risk of PCa. Data from the National Health and Nutrition Examination Survey (NHANES) of the United States were utilized. Adult male participants from 6 survey cycles between 1999 and 2010 were selected as the study sample. Multivariable logistic regression analysis was conducted to explore the association between BF%, LM, and PCa, while controlling for potential confounding variables. Among the 8440 participants, 359 cases of PCa were diagnosed. The relationship between BF%, LM, and PCa was nonlinear. In the multivariable logistic regression analysis, there was an independent association between BF% and PCa risk (OR: 1.04, 95% CI: 1.02-1.06), suggesting that higher BF% levels are associated with an increased risk of PCa. Conversely, higher LM levels were associated with a decreased risk of PCa (OR: 0.96, 95% CI: 0.95-0.98). The findings of this study demonstrate a correlation between BF% and LM with PCa, but do not provide direct evidence of a causal relationship. Higher BF% levels are associated with an increased risk of PCa, while higher LM levels are associated with a decreased risk. These results provide valuable insights for understanding and potentially preventing PCa, although further research is needed to fully comprehend the underlying mechanisms.

A body shape index (ABSI) but not body mass index (BMI) is associated with prostate cancer-specific mortality: Evidence from the US NHANES database

BACKGROUND

Prostate cancer (PCa) is a common malignancy in males and obesity may play a role in its development and progression. Associations between visceral obesity measured by a body shape index (ABSI) and PCa mortality have not been thoroughly investigated. This study assessed the associations between ABSI, body mass index (BMI), and long-term PCa-specific mortality using a nationally representative US database.

METHODS

This population-based longitudinal study collected data of males aged ≥40 years diagnosed with PCa and who underwent surgery and/or radiation from the National Health and Nutrition Examination Survey database 2001-2010. All included participants were followed through the end of 2019 using the National Center for Health Statistics Linked Mortality File. Associations between PCa-specific mortality, BMI, and ABSI were determined using Cox proportional hazards regression and receiver operating characteristic (ROC) curve analysis.

RESULTS

Data of 294 men (representing 1,393,857 US nationals) were analyzed. After adjusting for confounders, no significant associations were found between BMI (adjusted hazard ratio [aHR] = 1.06, 95% confidence interval [CI]: 0.97-1.16, p = 0.222), continuous ABSI (aHR = 1.29, 95% CI: 0.83-2.02, p = 0.253), or ABSI in category (Q4 vs. Q1-Q3: aHR = 1.52, 95% CI: 0.72-3.24, p = 0.265), and greater risk of PCa-specific mortality. However, among participants who had been diagnosed within 4 years, the highest ABSI quartile but not in BMI was significantly associated with greater risk for PCa-specific mortality (Q4 vs. Q1-Q3: aHR = 5.34, 95% CI: 2.26-12.62, p = 0.001). In ROC analysis for this subgroup, the area under the curve of ABSI alone for predicting PCa-specific mortality was 0.638 (95% CI: 0.448-0.828), reaching 0.729 (95% CI: 0.490-0.968 when combined with other covariates.

CONCLUSIONS

In US males with PCa diagnosed within 4 years, high ABSI but not BMI is independently associated with increased PCa-specific mortality.

Clustering and trajectories of key noncommunicable disease risk factors in Norway: the NCDNOR project

Noncommunicable diseases (NCDs) are a leading cause of premature death globally and have common preventable risk factors. In Norway, the NCDNOR-project aims at establishing new knowledge in the prevention of NCDs by combining information from national registries with data from population-based health studies. In the present study, we aimed to harmonize data on key NCD risk factors from the health studies, describe clustering of risk factors using intersection diagrams and latent class analysis, and identify long-term risk factor trajectories using latent class mixed models. The harmonized study sample consisted of 808,732 individuals (1,197,158 participations). Two-thirds were exposed to ≥ 1 NCD risk factor (daily smoking, physical inactivity, obesity, hypertension, hypercholesterolaemia or hypertriglyceridaemia). In individuals exposed to ≥ 2 risk factors (24%), we identified five distinct clusters, all characterized by fewer years of education and lower income compared to individuals exposed to < 2 risk factors. We identified distinct long-term trajectories of smoking intensity, leisure-time physical activity, body mass index, blood pressure, and blood lipids. Individuals in the trajectories tended to differ across sex, education, and body mass index. This provides important insights into the mechanisms by which NCD risk factors can occur and may help the development of interventions aimed at preventing NCDs.

Associations between Body Mass Index and Prostate Cancer: The Impact on Progression-Free Survival

Background and objectives: This study aimed to evaluate the impact of body mass index on PCa outcomes in our institution and also to find if there are statistically significant differences between the variables. Materials and Methods: A retrospective chart review was performed to extract information about all male patients with prostate cancer between 1 February 2015, and 25 October 2022, and with information about age, weight, height, follow-up, and PSA. We identified a group of 728 patients, of which a total of 219 patients resulted after the inclusion and exclusion criteria were applied. The primary endpoint was progression-free survival, which was defined as the length of time that the patient lives with the disease, but no relapses occur, and this group included 105 patients. In this case, 114 patients had a biological, local or metastatic relapse and were included in the progression group. Results: Our study suggests that prostate cancer incidence rises with age (72 ± 7.81 years) in men with a normal BMI, but the diagnostic age tends to drop in those with higher BMIs, i.e., overweight, and obese in the age range of 69.47 ± 6.31 years, respectively, 69.1 ± 7.51 years. A statistically significant difference was observed in the progression group of de novo metastases versus the absent metastases group at diagnostic (p = 0.04). The progression group with metastases present (n = 70) at diagnostic had a shorter time to progression, compared to the absent metastases group (n = 44), 18.04 ± 11.37 months, respectively, 23.95 ± 16.39 months. Also, PSA levels tend to diminish with increasing BMI classification, but no statistically significant difference was observed. Conclusions: The median diagnostic age decreases with increasing BMI category. Overweight and obese patients are more likely to have an advanced or metastatic prostate cancer at diagnosis. The progression group with metastatic disease at diagnostic had a shorter time to progression, compared to the absent metastases group. Regarding prostate serum antigen, the levels tend to become lower in the higher BMI groups, possibly leading to a late diagnosis.

Association between genetically proxied PCSK9 inhibition and prostate cancer risk: A Mendelian randomisation study

BACKGROUND

Prostate cancer (PrCa) is the second most prevalent malignancy in men worldwide. Observational studies have linked the use of low-density lipoprotein cholesterol (LDL-c) lowering therapies with reduced risk of PrCa, which may potentially be attributable to confounding factors. In this study, we performed a drug target Mendelian randomisation (MR) analysis to evaluate the association of genetically proxied inhibition of LDL-c-lowering drug targets on risk of PrCa.

METHODS AND FINDINGS

Single-nucleotide polymorphisms (SNPs) associated with LDL-c (P < 5 × 10-8) from the Global Lipids Genetics Consortium genome-wide association study (GWAS) (N = 1,320,016) and located in and around the HMGCR, NPC1L1, and PCSK9 genes were used to proxy the therapeutic inhibition of these targets. Summary-level data regarding the risk of total, advanced, and early-onset PrCa were obtained from the PRACTICAL consortium. Validation analyses were performed using genetic instruments from an LDL-c GWAS conducted on male UK Biobank participants of European ancestry (N = 201,678), as well as instruments selected based on liver-derived gene expression and circulation plasma levels of targets. We also investigated whether putative mediators may play a role in findings for traits previously implicated in PrCa risk (i.e., lipoprotein a (Lp(a)), body mass index (BMI), and testosterone). Applying two-sample MR using the inverse-variance weighted approach provided strong evidence supporting an effect of genetically proxied inhibition of PCSK9 (equivalent to a standard deviation (SD) reduction in LDL-c) on lower risk of total PrCa (odds ratio (OR) = 0.85, 95% confidence interval (CI) = 0.76 to 0.96, P = 9.15 × 10-3) and early-onset PrCa (OR = 0.70, 95% CI = 0.52 to 0.95, P = 0.023). Genetically proxied HMGCR inhibition provided a similar central effect estimate on PrCa risk, although with a wider 95% CI (OR = 0.83, 95% CI = 0.62 to 1.13, P = 0.244), whereas genetically proxied NPC1L1 inhibition had an effect on higher PrCa risk with a 95% CI that likewise included the null (OR = 1.34, 95% CI = 0.87 to 2.04, P = 0.180). Analyses using male-stratified instruments provided consistent results. Secondary MR analyses supported a genetically proxied effect of liver-specific PCSK9 expression (OR = 0.90 per SD reduction in PCSK9 expression, 95% CI = 0.86 to 0.95, P = 5.50 × 10-5) and circulating plasma levels of PCSK9 (OR = 0.93 per SD reduction in PCSK9 protein levels, 95% CI = 0.87 to 0.997, P = 0.04) on PrCa risk. Colocalization analyses identified strong evidence (posterior probability (PPA) = 81.3%) of a shared genetic variant (rs553741) between liver-derived PCSK9 expression and PrCa risk, whereas weak evidence was found for HMGCR (PPA = 0.33%) and NPC1L1 expression (PPA = 0.38%). Moreover, genetically proxied PCSK9 inhibition was strongly associated with Lp(a) levels (Beta = -0.08, 95% CI = -0.12 to -0.05, P = 1.00 × 10-5), but not BMI or testosterone, indicating a possible role for Lp(a) in the biological mechanism underlying the association between PCSK9 and PrCa. Notably, we emphasise that our estimates are based on a lifelong exposure that makes direct comparisons with trial results challenging.

CONCLUSIONS

Our study supports a strong association between genetically proxied inhibition of PCSK9 and a lower risk of total and early-onset PrCa, potentially through an alternative mechanism other than the on-target effect on LDL-c. Further evidence from clinical studies is needed to confirm this finding as well as the putative mediatory role of Lp(a).

Early prediction of prostate cancer risk in younger men using polygenic risk scores and electronic health records

BACKGROUND

Prostate cancer (PCa) screening is not routinely conducted in men aged 55 and younger, although this age group accounts for more than 10% of cases. Polygenic risk scores (PRSs) and patient data applied toward early prediction of PCa may lead to earlier interventions and increased survival. We have developed machine learning (ML) models to predict PCa risk in men 55 and under using PRSs combined with patient data.

METHODS

We conducted a retrospective study on 91,106 male patients aged 35-55 using the UK Biobank database. Five gradient boosting models were developed and validated utilizing routine screening data, PRSs, additional clinical data, or combinations of the three.

RESULTS

Combinations of PRSs and patient data outperformed models that utilized PRS or patient data only, and the highest performing models achieved an area under the receiver operating characteristic curve of 0.788. Our models demonstrated a substantially lower false positive rate (35.4%) in comparison to standard screening using prostate-specific antigen (60%-67%).

CONCLUSION

This study provides the first preliminary evidence for the use of PRSs with patient data in a ML algorithm for PCa risk prediction in men aged 55 and under for whom screening is not standard practice.

Diabetes, metabolic syndrome and prostate cancer risk: Results from the EPICAP case-control study

BACKGROUND

Diabetes may be associated with decreased prostate cancer (PCa) risk. However, previous studies have not always accounted for time since diabetes diagnosis or antidiabetic drug use. Futhermore, the role of metabolic syndrome (MetS) in PCa risk is still debated. We investigated the role of diabetes and MetS in PCa risk based on data from the Epidemiological study of PCa (EPICAP).

METHODS

EPICAP is a population-based case-control study that included 819 incident PCa cases in 2012-2013 and 879 controls frequency matched by age. MetS was characterized according to National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III). Logistic regression models adjusted for age, family history of PCa and ethnicity, were used to assess odds ratios (ORs) and their 95%conficence intervals (CIs) for the associations between diabetes, MetS and PCa risk.

RESULTS

Whereas we did not observed an association between diabetes and PCa, a decreased risk of PCa has been highlighted with an increasing treated diabetes duration (p-trend=0.008). No association has been observed between MetS, the number of MetS criteria and the risk of PCa. However, we suggested that NSAIDs use could modify the association between MetS and PCa risk.

CONCLUSION

Our results suggest an inverse association between the duration of diabetes and PCa risk. The role of metabolic factors, such as MetS and its components, in PCa risk remains unclear and requires further investigations.

Clinical Predictors of Grade Group Upgrading for Radical Prostatectomy Specimens Compared to Those of Preoperative Needle Biopsy Specimens

BACKGROUND

Decision-making and selection of treatment modalities for newly diagnosed prostate cancer (PCa) are often determined by risk stratification using grade group (GG), prostate-specific antigen (PSA), and clinical stage. The discrepancies between needle biopsy (NB) and radical prostatectomy (RP) specimens often occur because of the sampling errors in NB or multifocal features of PCa. Thus, we aimed to estimate the preoperative clinical factors for predicting GG upgrading after robot-assisted RP (RARP).

METHODS

In this retrospective study, we reviewed the clinical and pathological records of patients who underwent RARP at Gifu University Hospital. We focused on patients with organ-confined PCa who had not received neoadjuvant therapy prior to RARP. The primary endpoint was identified as the predictive factor of GG upgrading for RARP specimens compared to those of NB specimens.

RESULTS

Eighty-one patients were included in this study. The enrolled patients were divided into two groups: those who had GG upgrading for RARP specimens (the NB upgrade group) or those who did not have GG upgrading (the no upgrade group). The median age of all patients was 70 years, and the median body mass index (BMI) was 22.9 kg/m². The median neutrophil count was 3720/μL, lymphocyte count was 1543/μL, and neutrophil-to-lymphocyte ratio (NLR) was 2.24. In univariate analysis, BMI, PSA, neutrophil count, and NLR were significantly associated with GG upgrading in RARP specimens compared to NB specimens. BMI and NLR were identified as strong predictive factors for GG upgrading in RARP specimens in the multivariate analysis.

CONCLUSIONS

Although this study's small number of enrolled patients was a vital weakness, BMI and NLR might have been significantly correlated with GG upgrading for RP specimens compared with NB specimens. Therefore, BMI and NLR may have potential benefits for newly diagnosed patients with PCa in terms of decision-making and the selection of treatment modalities.

Caregiver perceptions of neighbourhood green space quality, heavy traffic conditions, and asthma symptoms: Group-based trajectory modelling and multilevel longitudinal analysis of 9,589 Australian children

BACKGROUND

This study assessed the associations between changes in exposure to green space quality, heavy traffic conditions, and asthma symptoms among children.

METHODS

10-year cohort data of 9589 children, retrieved from the Longitudinal Study of Australian Children, were analysed. Caregiver-reported neighbourhood green space quality, heavy traffic conditions, and asthma symptoms were measured biennially. Group-based trajectory mixture models were used to develop trajectory groups, denoting different patterns of, or changes in, exposure to green space quality, heavy traffic conditions, and asthma symptoms across childhood. Multilevel multinomial logistic regression was used to identify factors associated with trajectory group membership and examine the confounders-adjusted associations between trajectory groups of green space quality, heavy traffic conditions, and asthma symptoms.

RESULTS

Four trajectory groups for each green space quality and heavy traffic conditions, and five trajectory groups for asthma symptoms were developed. Children in less disadvantaged areas were more likely to be in trajectory groups with exposure to quality green space, but less likely to be exposed to heavy neighbourhood traffic. Living in more remote areas was associated with the decreased likelihood to be in groups with exposure to both quality green space and heavy traffic conditions over time. Accumulation of exposure to quality green space across childhood was not found to be protective against asthma symptoms. However, children whose caregiver perceptions of heavy traffic conditions trended from low to moderate levels; or were consistently in high levels across childhood had a higher likelihood to be in trajectory groups with a higher risk of asthma symptoms.

CONCLUSION

Exposure to quality green space was not associated with the reduced risk of asthma symptoms. The accumulation of exposure to heavy traffic conditions increased the likelihood of asthma symptoms among children. Reducing the presence of heavy traffic in neighbourhoods might reduce the risk of childhood asthma.

Weight-change trajectory in relation to cancer risk: findings from a nationwide cohort study in South Korea

OBJECTIVE

This study examined relationships between weight-change trajectories and all cancers and obesity-related cancer risks.

METHODS

A total of 1,882,304 men and 899,912 women from the 2002 to 2017 National Health Insurance Service cohort were included. Weight-change trajectories in 2002 to 2009, according to BMI, were determined using group-based trajectory modeling. Cox proportional hazards regression assessed associations between trajectories and cancer incidence.

RESULTS

Overall, >50% of individuals maintained stable weight, as did two-thirds of those in the overweight and obesity groups. A total of 64,725 men and 37,608 women developed incident cancer. Weight stability in overweight or obesity groups was associated with greater cancer risk. In both sexes, higher weight across BMI groups increased risks of all cancers, obesity-related cancers and thyroid, colorectal, stomach, liver, prostate, and postmenopausal breast cancer. Stratified by BMI, weight gain increased risks of all cancers and obesity-related cancers in men with obesity class I and women with overweight. Weight loss decreased risks of obesity-related cancers, thyroid cancer, and kidney cancer among men with overweight, premenopausal breast, endometrial, and ovarian cancer in women with overweight, and obesity-related cancers and thyroid cancer in women with class I obesity.

CONCLUSIONS

Maintaining weight and avoiding weight gain are crucial for reducing cancer risk, but achieving a stable, normal BMI optimizes cancer prevention.

Association between obesity and frequency of high‑grade prostate cancer on biopsy in men: A single‑center retrospective study

The present study aimed to investigate the relationship between BMI and the prostate cancer (PCa) risk at biopsy in Italian men. Retrospective analyses of the clinical data of 2,372 consecutive men undergoing ultrasound-guided multicore (≥10) prostate biopsy transrectally between May 2010 and December 2018 were performed. BMIs were categorized, according to Western countries' classification of obesity, as follows: <18.5 kg/m² (underweight), 18.5-24.99 kg/m² (normal weight), 25-30 kg/m² (overweight) and >30 kg/m² (obese). The distribution of patients undergoing biopsy was compared with a model population from the official survey data. Patient characteristics and the relationships between characteristics were investigated using correlation analysis, ANOVA, Kruskal-Wallis and Dunn's tests. The present study estimated the influence on cancer incidence not only of BMI but also of other patient characteristics using multi-variable logistic modelling and compared, using the models, the expected outcomes for patients who differed only in BMI. From a sample of 2,372 men, the present study enrolled 1,079 men due to a lack of clinical data [such as prostate specific antigen (PSA) and BMI data] in the other patients undergoing prostate biopsy. Their distribution was significantly different from the model distribution with the probability of undergoing biopsy increasing with increasing BMI. The median age was 69.4 years. The median BMI was 26.4 kg/m², while the median PSA level was 7.60 ng/ml. In total, the biopsies detected PCa in 320 men (29.7%) and high-grade PCa (HGPCa) in 218 men (20.2%). Upon applying the aforementioned Western countries' criteria for BMI categories, there were 4 (0.4%) underweight, 318 (29.5%) of normal weight, 546 (50.6%) overweight, and 211 (19.6%) obese patients. ANOVA/Kruskal-Wallis tests revealed that overweight and obese men were younger than the normal-weight men, while there was no statistical difference in their PSA values. Furthermore, 29.3% of normal-weight men, 29.5% of overweight men and 29.9% of obese men were diagnosed with PCa, while 19.5% of normal-weight men, 20.1% of overweight men and 21.8% of obese men were affected by severe cancer. BMI was found to be positively correlated with PCa risk and negatively correlated with both age and PSA level. Age and PSA level were both positively correlated with PCa risk, while digital rectal examination (DRE) outcome was strongly indicative of PCa discovery if the test outcome was positive. Logistics models attributed a positive coefficient to BMI when evaluated against both PCa risk and HGPCa risk. In patients having a negative DRE outcome who differed only in BMI, logistic regression showed a 60% increased risk of PCa diagnosis in obese patients compared with in normal-weight patients. This risk difference increased when other characteristics were less indicative of PCa (younger age/lower PSA), while it decreased when patient characteristics were more indicative (older age/higher PSA, positive DRE). In conclusion, the present study demonstrated that, in men with higher BMIs, the risk of PCa is higher. The relative difference in risk between low and high BMI is most pronounced in younger patients having a lower PSA level and a negative DRE outcome.

Perceived green space quality, child biomarkers and health-related outcomes: A longitudinal study

Accumulating exposure to quality green space over time is posited to influence child health, yet longitudinal studies are scarce. This study aimed to examine the associations between trajectories of perceived green space quality and child health-related outcomes. We used data from 1874 childrenin the B-cohort of the Longitudinal Study of Australian Children who participated in the Child Health Checkpoint module at 11-12 years. Data on caregiver perceived green space quality measured biennially was assessed using discrete trajectory mixture models to group children by contrasting distributions in green space quality over time. Examination of associations between trajectory groups of perceived green space quality and child biomarkers (i.e., albumin-to-creatinine ratio, total, cholesterol, total triglycerides, and glucose), physical health and behavioural assessments (i.e., anthropometric measurements, blood pressure, sedentary behaviour, physical activity, sleep, aerobic work capacity, and general wellbeing), and health care use were assessed using multilevel models, adjusted for sociodemographic variables. Four perceived green space quality trajectories were identified: "decreasing quality from high to moderate"; "increasing quality from low to high"; "consistently high quality"; "consistently low quality". Compared with consistently low levels of quality green space, adjusted models indicated consistently high-quality green space was associated with lower total triglycerides (β -0.13; 95%CI -0.25, -0.01). Lower odds of hospital admission was observed among children who accumulated quality green space over time (OR 0.45; 95%CI 0.23, 0.87). These associations were observed in boys only in sex-stratified analyses. Moreover, boys accumulating quality green space through time tended to have lower diastolic blood pressure (β -2.76; 95%CI -5.17, -0.35) and girls who experienced loss in quality green space tended to have a higher percentage of body fat (β 2.81; 95%CI 0.43, 5.20). Accumulating quality green space over time is important for various aspects of child health, with contrasting benefits by sex.

Longitudinal trajectories of lifetime body shape and prostate cancer angiogenesis

Angiogenesis potentially underlies the pathway between excess adiposity and prostate carcinogenesis. This study examined the association between lifetime body shape trajectories and prostate cancer angiogenesis. 521 prostate cancer patients who underwent prostatectomy or transurethral resection between 1986 and 2000 were enrolled from the Health Professionals Follow-up Study. Cancers were immunostained and quantitated for cancer vessel regularity, diameter, area, and density, and composite angiogenesis (factor analysis). To identify distinct groups of body shape change, we conducted group-based trajectory modeling. We used multivariable linear regression to estimate the percentage difference in angiogenesis score and 95% confidence interval (CI) between body shape change trajectories during lifetime (age 5-60 years), early life (age 5-30 years), or later life (age 30-60 years). Compared to men with lifetime lean or medium body shape, higher angiogenesis scores were observed in men with moderate increase [percentage difference of 35% (95% CI 5-64)], marked increase [24% (95% CI - 2 to 51)], and constantly heavy with mild increase body shape [38% (95% CI 8-69)]. However, a lower angiogenesis score was noted in men with early-life marked increase (- 22%, 95% CI - 44 to 0) and stable medium body shape (- 14%, 95% CI - 40 to 12), compared to moderate increase body shape. Increased angiogenesis was also found for absolute weight gain from age 21-60 years. Lifetime body fatness accumulation, especially after age 21, was associated with increased prostate cancer angiogenesis, while weight gain in early-life adulthood was associated with lower cancer angiogenesis.

Personalized 5-Year Prostate Cancer Risk Prediction Model in Korea Based on Nationwide Representative Data

Prostate cancer is the fourth most common cause of cancer in men in Korea, and there has been a rapid increase in cases. In the present study, we constructed a risk prediction model for prostate cancer using representative data from Korea. Participants who completed health examinations in 2009, based on the Korean National Health Insurance database, were eligible for the present study. The crude and adjusted risks were explored with backward selection using the Cox proportional hazards model to identify possible risk variables. Risk scores were assigned based on the adjusted hazard ratios, and the standardized points for each risk factor were proportional to the β-coefficient. Model discrimination was assessed using the concordance statistic (c-statistic), and calibration ability was assessed by plotting the mean predicted probability against the mean observed probability of prostate cancer. Among the candidate predictors, age, smoking intensity, body mass index, regular exercise, presence of type 2 diabetes mellitus, and hypertension were included. Our risk prediction model showed good discrimination (c-statistic: 0.826, 95% confidence interval: 0.821-0.832). The relationship between model predictions and actual prostate cancer development showed good correlation in the calibration plot. Our prediction model for individualized prostate cancer risk in Korean men showed good performance. Using easily accessible and modifiable risk factors, this model can help individuals make decisions regarding prostate cancer screening.

General and abdominal obesity trajectories across adulthood, and risk of prostate cancer: results from the PROtEuS study, Montreal, Canada

PURPOSE

Greater body fatness is a probable cause of advanced prostate cancer (PCa). Body fat distribution and timing of exposure may be relevant. We investigated associations between body size trajectories and PCa incidence in a population-based case-control study in Montreal, Canada.

METHODS

Cases (n = 1,931), aged ≤ 75 years, were diagnosed with PCa in 2005-2009; 1,994 controls were selected from the electoral list. Interviews were conducted to assess body mass index (BMI) and Stunkard's silhouette at ages 20, 40, 50, 60 years, and before interview. Current waist and hip circumferences were measured, and a predictive model estimated waist circumference in the past. BMI and waist circumference trajectories were determined to identify subgroups. Logistic regression estimated odds ratios (OR) and 95% confidence intervals (CI) for the association between anthropometric indicators and PCa.

RESULTS

Subjects with a current BMI ≥ 30 kg/m² had a lower risk of overall PCa (OR 0.71, 95% CI 0.59-0.85). Associations with adult BMI followed similar trends for less and more aggressive tumors, with stronger inverse relationships in early adulthood. Contrastingly, current waist circumference ≥ 102 cm was associated with elevated risk of high-grade PCa (OR 1.33, 95% CI 1.03-1.71). Men with increasing BMI or waist circumference adult trajectories had a lower risk of PCa, especially low-grade, than those in the normal-stable range. This was especially evident among men in the obese-increase group for BMI and waist circumference.

CONCLUSION

Abdominal obesity increased the risk of aggressive PCa. The inverse relationship between body size trajectories and PCa may reflect PSA hemodilution, lower detection, and/or a true etiological effect.

Group‐based trajectory modeling of body mass index and body size over the life course: A scoping review

Background

Group‐based trajectory modeling has been applied to identify distinct trajectories of growth across the life course. Objectives of this study were to describe the methodological approaches for group‐based modeling of growth across the life course and to summarize outcomes across studies.

Methods

A scoping review with a systematic search of Medline, EMBASE, CINAL, and Web of Science was conducted. Studies that used a group‐based procedure to identify trajectories on any statistical software were included. Data were extracted on trajectory methodology, measures of growth, and association with outcomes.

Results

A total of 59 studies were included, and most were published from 2013 to 2020. Body mass index was the most common measure of growth (n = 43). The median number of identified trajectories was 4 (range: 2–9). PROC TRAJ in SAS was used by 33 studies, other procedures used include TRAJ in STATA, lcmm in R, and Mplus. Most studies evaluated associations between growth trajectories and chronic disease outcomes (n = 22).

Conclusions

Group‐based trajectory modeling of growth in adults is emerging in epidemiologic research, with four distinct trajectories observed somewhat consistently from all studies. Understanding life course growth trajectories may provide further insight for population health interventions.

Body mass index trajectories and prostate cancer risk: Results from the EPICAP study

Elevated body mass index (BMI) has been inconsistently associated with prostate cancer occurrence but it has been suggested that life course adulthood obesity may be associated with an increased risk of prostate cancer. However, few studies have investigated lifetime BMI and prostate cancer risk. We analyzed life course BMI trajectories on prostate cancer risk based on data from the Epidemiological study of Prostate Cancer (EPICAP). We included in our analyses 781 incident prostate cancer cases and 829 controls frequency matched by age. Participants were asked about their weight every decade from age 20 to two years before reference date. BMI trajectories were determined using group-based trajectory modeling to identify groups of men with similar patterns of BMI changes. We identified five BMI trajectories groups. Men with a normal BMI at age 20 developing overweight or obesity during adulthood were at increased risk of aggressive prostate cancer compared to men who maintained a normal BMI. Our results suggest that BMI trajectories resulting in overweight or obesity during adulthood are associated with an increased risk of aggressive prostate cancer, particularly in never smokers, emphasizing the importance of maintaining a healthy BMI throughout adulthood.