Experimental evidence indicates that exercise performed at different times of the day may affect circadian rhythms and circadian disruption has been linked to breast and prostate cancer. We examined ...in a population‐based case‐control study (MCC‐Spain) if the time‐of‐day when physical activity is done affects prostate and breast cancer risk. Lifetime recreational and household physical activity was assessed by in‐person interviews. Information on time‐of‐day of activity (assessed approximately 3 years after the assessment of lifetime physical activity and confounders) was available for 781 breast cancer cases, 865 population female controls, 504 prostate cases and 645 population male controls from 10 Spanish regions, 2008‐2013. We estimated odds ratios (ORs) and 95% confidence intervals (95% CI) for different activity timings compared to inactive subjects using unconditional logistic regression adjusting for confounders. Early morning (8‐10 am) activity was associated with a protective effect compared to no physical activity for both breast (OR = 0.74, 95% CI = 0.48‐1.15) and prostate cancer (OR = 0.73, 95% CI = 0.44‐1.20); meta‐OR for the two cancers combined 0.74 (95%CI = 0.53‐1.02). There was no effect observed for breast or prostate cancer for late morning to afternoon activity while a protective effect was also observed for evening activity only for prostate cancer (OR = 0.75, 95% CI = 0.45‐1.24). Protective effects of early morning activity were more pronounced for intermediate/evening chronotypes for both cancers. This is the first population‐based investigation identifying a differential effect of timing of physical activity on cancer risk with more pronounced effects for morning hour activity. Our results, if confirmed, may improve current physical activity recommendations for cancer prevention.
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Exercise protects against a variety of cancers, but does time of day matter? Disrupting the body's circadian rhythm can boost cancer risk. Here, the authors compared breast and prostate cancer risk among people who exercised in the early morning, late morning, afternoon, and evening. They conducted a population‐based case‐control study, in which participants filled out a questionnaire about their patterns of sleeping, eating, and exercising. Exercising in the early morning appeared to be more strongly protective against breast and prostate cancer than exercising later in the day. Evening exercise appeared to have a moderate protective effect on prostate cancer.
This cross-sectional study aims to analyse the relationship between sedentary behaviour and breast cancer (BC) risk from a social perspective.
Women aged 45-70 who participated in the Valencia Region ...Breast Cancer Screening Programme (2018-2019) were included, with a total of 121,359 women analysed, including 506 with cancer and 120,853 without cancer. The response variable was BC (screen-detected) and the main explanatory variable was sedentary behaviour (≤2 / >2-≤3 / >3-≤5 / >5 hours/day, h/d). Nested logistic regression models (M) were estimated: M1: sedentary behaviour adjusted for age and family history of BC; M2: M1 + hormonal/reproductive variables (menopausal status, number of pregnancies, hormone replacement therapy; in addition, months of breastfeeding was added for a subsample of women with one or more live births); M3: M2 + lifestyle variables (body mass index, smoking habits); M4: M3 + socioeconomic variables (educational level, occupation); Final model: M4 + gender variables (childcare responsibilities, family size). Interaction between sedentary behaviour and educational level was analysed in the Final model. Moreover, for the whole sample, postmenopausal women and HR+ BC, the Final model was stratified by educational level.
Sedentary behaviour was associated with an increased risk of BC with a nearly statistically significant effect in the Final model (>2-≤3 h/d: OR = 1.22 (0.93-1.61); >3-≤5 h/d: OR = 1.14 (0.86-1.52); >5: OR = 1.19 (0.89-1.60)). For women with a low educational level, sitting more than 2 h/d was associated with an increased risk of BC in the whole sample (>2-≤3 h/d OR = 1.93 (1.19-3.21); in postmenopausal women (>2-≤3 h/d, OR = 2.12 (1.18-2.96), >5h/d OR = 1.75 (1.01-3.11)) and in HR+ BC (>2-≤3h/d, OR = 2.15 (1.22-3.99)). Similar results were observed for women with one or more live births. Conclusions Sitting >2 h/d is associated with BC risk in women with low educational level, especially in postmenopausal women and those with live births.
In the fecal immunological test, a suitable cut-off value may be selected to classify results as either positive or negative. Our aim is to estimate the optimal cut-off value for detecting colorectal ...cancer in different age and sex groups. This is a multicentric retrospective cohort study of participants in CRC screening programs with FIT between 2006 and 2012. A total of 545,505 participations were analyzed. Cancers diagnosed outside of the program were identified after a negative test result (IC_test) up until 2014. The Wilcoxon test was used to compare fecal hemoglobin levels. ROC curves were used to identify the optimal cut-off value for each age and sex group. Screening program results were estimated for different cut-off values. The results show that the Hb concentration was higher in colorectal cancer (average = 179.6μg/g) vs. false positives (average = 55.2μg/g), in IC_test (average = 3.1μg/g) vs. true negatives (average = 0μg/g), and in men (average = 166.2μg/g) vs. women (average = 140.2μg/g) with colorectal cancer. The optimal cut-off values for women were 18.3μg/g (50-59y) and 14.6μg/g (60-69y), and 16.8μg/g (50-59y) and 19.9μg/g (60-69y) for men. Using different cut-off values for each age and sex group lead to a decrease in the IC_test rate compared to the 20μg/g cut-off value (from 0.40‰ to 0.37‰) and an increase in the false positive rate (from 6.45% to 6.99%). Moreover, test sensitivity improved (90.7%), especially in men and women aged 50-59y (89.4%; 90%) and women aged 60-69y (90.2%). In conclusion, the optimal cut-off value varies for different sex and age groups and the use of an optimal cut-off value for each group improves sensitivity and leads to a small decrease in IC_tests, but also to a larger increase in false positives.
To construct an individual socioeconomic status index (ISESI) with information available in the Population Information System of the Region of Valencia, Spain, and use it to analyse inequalities in a ...colorectal cancer screening programme (CRCSP).
Cross-sectional study of men and women aged between 50 and 75 at the time of the study (2020) that were selected from the target population of the Region of Valencia CRCSP. (study sample 1,150,684). First, a multiple correspondence analysis was performed to aggregate information from the Population Information System of the Region of Valencia into an ISESI. Second, data from the 2016 Region of Valencia Health Survey were used for validation, and finally the relationship between CRCSP participation and the ISESI was analysed by logistic regression models.
The variables included in the index were nationality, employment status, disability, healthcare coverage, risk of vulnerability and family size. The most important categories for determining the highest socioeconomic status were being employed and not being at risk of social vulnerability, and being unemployed and at risk of social vulnerability for determining the lowest socioeconomic status. Index validation demonstrated internal and external coherence for measuring socioeconomic status. The relationship between CRCSP participation and the ISESI categorised by quartile (Q) showed that Q4 (the lowest socioeconomic status) was less likely to participate OR = 0.769 (0.757-0.782) than Q1 (the highest socioeconomic status), and the opposite was found for Q2 OR = 1.368 (1.347-1.390) and Q3 OR = 1.156 (1.137-1.175).
An ISESI was constructed and validated using Population Information System data and made it possible to evaluate inequalities in colorectal cancer screening.
Heat exposure and heat stress/strain is a concern for many workers. There is increasing interest in potential chronic health effects of occupational heat exposure, including cancer risk. We examined ...potential associations of occupational heat exposure and colorectal cancer (CRC) risk in a large Spanish multi-case--control study.
We analyzed data on 1198 histologically confirmed CRC cases and 2690 frequency-matched controls. The Spanish job-exposure matrix, MatEmEsp, was used to assign heat exposure estimates to the lifetime occupations of participants. Three exposure indices were assessed: ever versus never exposed, cumulative exposure and duration (years). We estimated odds ratios (OR) and 95% confidence intervals (CI) using unconditional logistic regression adjusting for potential confounders.
Overall, there was no association of ever, compared with never, occupational heat exposure and CRC (OR 1.09, 95% CI 0.92-1.29). There were also no associations observed according to categories of cumulative exposure or duration, and there was no evidence for a trend. There was no clear association of ever occupational heat exposure and CRC in analysis conducted among either men or women when analyzed separately. Positive associations were observed among women in the highest categories of cumulative exposure (OR 1.81, 95% CI 1.09-3.03) and duration (OR 2.89, 95% CI 1.50-5.59) as well as some evidence for a trend (P<0.05).
Overall, this study provides no clear evidence for an association between occupational heat exposure and CRC.
Breast and prostate cancers have been associated with circadian disruption. Some previous studies examined associations of sleep duration and breast or prostate cancer risk though findings remain ...inconsistent. This study examines associations of a range of detailed sleep characteristics and breast and prostate cancer risk in a large-scale population-based case-control study, MCC-Spain. A total of 1738 incident breast cancer cases, 1112 prostate cancer cases and frequency matched controls (n = 1910, and 1493 respectively) were recruited. Detailed data on habitual sleep duration, quality, timing, and daytime napping ("siesta") were collected at recruitment. Additional data on sleep habits during both the previous year and at age 40 years were also subsequently captured. Adjusted odds ratios (ORs) and 95% confidence intervals (CI) were estimated. There were no associations of habitual sleep duration (h), timing of sleep, or any or specific sleep problems, and either breast and prostate cancer risk. There was a significant positive association of ever taking habitual siestas at recruitment and breast cancer risk (OR = 1.22, 95% CI 1.06-1.42), which strengthened with increased frequency or duration. There were also significant positive associations observed for both breast and prostate cancer, among those reporting recent sleep problems, but not sleep problems at age 40 years, in a subsequent circadian questionnaire. Adverse associations with siesta and disturbed sleep during the previous year likely reflect symptoms of developing/diagnosed cancer and comorbidities. Overall, there was no clear association between various sleep characteristics and breast or prostate cancer risk observed.
Purpose To build models combining circulating microRNAs (miRNAs) able to identify women with breast cancer as well as different types of breast cancer, when comparing with controls without breast ...cancer. Method miRNAs analysis was performed in two phases: screening phase, with a total n = 40 (10 controls and 30 BC cases) analyzed by Next Generation Sequencing, and validation phase, which included 131 controls and 269 cases. For this second phase, the miRNAs were selected combining the screening phase results and a revision of the literature. They were quantified using RT-PCR. Models were built using logistic regression with LASSO penalization. Results The model for all cases included seven miRNAs (miR-423-3p, miR-139-5p, miR-324-5p, miR-1299, miR-101-3p, miR-186-5p and miR-29a-3p); which had an area under the ROC curve of 0.73. The model for cases diagnosed via screening only took in one miRNA (miR-101-3p); the area under the ROC curve was 0.63. The model for disease-free cases in the follow-up had five miRNAs (miR-101-3p, miR-186-5p, miR-423-3p, miR-142-3p and miR-1299) and the area under the ROC curve was 0.73. Finally, the model for cases with active disease in the follow-up contained six miRNAs (miR-101-3p, miR-423-3p, miR-139-5p, miR-1307-3p, miR-331-3p and miR-21-3p) and its area under the ROC curve was 0.82. Conclusion We present four models involving eleven miRNAs to differentiate healthy controls from different types of BC cases. Our models scarcely overlap with those previously reported. Keywords: Breast cancer, Screening, miRNA, Diagnosis, Prognosis
Use of artificial sweeteners (AS) such as aspartame, cyclamate, saccharin and sucralose is widespread. We evaluated the association of use of aspartame and other AS with cancer. In total 1881 ...colorectal, 1510 breast, 972 prostate and 351 stomach cancer and 109 chronic lymphocytic leukaemia (CLL) cases and 3629 population controls from the Spanish Multicase-Control (MCC-Spain) study were recruited (2008-2013). The consumption of AS, from table-top sweeteners and artificially sweetened beverages, was assessed through a self-administered and validated food frequency questionnaire (FFQ). Sex-specific quartiles among controls were determined to compare moderate consumers (<third quartile) and high consumers (≥ third quartile) vs non consumers (reference category), distinguishing aspartame-containing products and other AS. Unconditional logistic regression models were used to estimate adjusted OR and 95%CI, and results were stratified by diabetes status. Overall, we found no associations between the consumption of aspartame or other AS and cancer. Among participants with diabetes, high consumption of other AS was associated with colorectal cancer (OR = 1.58, 95% CI 1.05-2.41, P trend = .03) and stomach cancer (OR = 2.27 0.99-5.44, P trend = .06). High consumption of aspartame, was associated with stomach cancer (OR = 2.04 0.7-5.4, P trend = .05), while a lower risk was observed for breast cancer (OR = 0.28 0.08-0.83, P trend = .03). In some cancers, the number of cases in participants with diabetes were small and results should be interpreted cautiously. We did not find associations between use of AS and cancer, but found associations between high consumption of aspartame and other AS and different cancer types among participants with diabetes.
Prostate cancer (PC) is the second most frequent tumor in men worldwide; however, its etiology remains largely unknown, with the exception of age and family history. The wide variability in ...incidence/mortality across countries suggests a certain role for environmental exposures that has not yet been clarified.
To evaluate the association between risk of PC (by clinical profile) and residential proximity to pollutant industrial installations (by industrial groups, groups of carcinogens, and specific pollutants released), within the context of a Spanish population-based multicase-control study of incident cancer (MCC-Spain).
This study included 1186 controls and 234 PC cases, frequency matched by age and province of residence. Distances from participants' residences to the 58 industries located in the study area were calculated and categorized into “near” (considering different limits between ≤1 km and ≤ 3 km) or “far” (>3 km). Odds ratios (ORs) and 95 % confidence intervals (95%CIs) were estimated using mixed and multinomial logistic regression models, adjusted for potential confounders and matching variables.
No excess risk was detected near the overall industries, with ORs ranging from 0.66 (≤2 km) to 1.11 (≤1 km). However, positive associations (OR; 95%CI) were found, by industrial group, near (≤3 km) industries of ceramic (2.54; 1.28–5.07), food/beverage (2.18; 1.32–3.62), and disposal/recycling of animal waste (2.67; 1.12–6.37); and, by specific pollutant, near plants releasing fluorine (4.65; 1.45–14.91 at ≤1.5 km) and chlorine (5.21; 1.56–17.35 at ≤1 km). In contrast, inverse associations were detected near industries releasing ammonia, methane, dioxins+furans, polycyclic aromatic hydrocarbons, trichloroethylene, and vanadium to air.
The results suggest no association between risk of PC and proximity to the overall industrial installations. However, some both positive and inverse associations were detected near certain industrial groups and industries emitting specific pollutants.
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•1st paper about prostate cancer risk and industrial pollution with individual data.•Overall, no association was found with proximity to industries as a whole.•Isolated positive associations found near ceramic and food/beverage industries.•Isolated inverse associations found near industries releasing ammonia and methane.
While previous reviews found a positive association between pre-existing cancer diagnosis and COVID-19-related death, most early studies did not distinguish long-term cancer survivors from those ...recently diagnosed/treated, nor adjust for important confounders including age. We aimed to consolidate higher-quality evidence on risk of COVID-19-related death for people with recent/active cancer (compared to people without) in the pre-COVID-19-vaccination period. We searched the WHO COVID-19 Global Research Database (20 December 2021), and Medline and Embase (10 May 2023). We included studies adjusting for age and sex, and providing details of cancer status. Risk-of-bias assessment was based on the Newcastle-Ottawa Scale. Pooled adjusted odds or risk ratios (aORs, aRRs) or hazard ratios (aHRs) and 95% confidence intervals (95% CIs) were calculated using generic inverse-variance random-effects models. Random-effects meta-regressions were used to assess associations between effect estimates and time since cancer diagnosis/treatment. Of 23 773 unique title/abstract records, 39 studies were eligible for inclusion (2 low, 17 moderate, 20 high risk of bias). Risk of COVID-19-related death was higher for people with active or recently diagnosed/treated cancer (general population: aOR = 1.48, 95% CI: 1.36-1.61, I
= 0; people with COVID-19: aOR = 1.58, 95% CI: 1.41-1.77, I
= 0.58; inpatients with COVID-19: aOR = 1.66, 95% CI: 1.34-2.06, I
= 0.98). Risks were more elevated for lung (general population: aOR = 3.4, 95% CI: 2.4-4.7) and hematological cancers (general population: aOR = 2.13, 95% CI: 1.68-2.68, I
= 0.43), and for metastatic cancers. Meta-regression suggested risk of COVID-19-related death decreased with time since diagnosis/treatment, for example, for any/solid cancers, fitted aOR = 1.55 (95% CI: 1.37-1.75) at 1 year and aOR = 0.98 (95% CI: 0.80-1.20) at 5 years post-cancer diagnosis/treatment. In conclusion, before COVID-19-vaccination, risk of COVID-19-related death was higher for people with recent cancer, with risk depending on cancer type and time since diagnosis/treatment.
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