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Background:
Communication

Dietary Intake of Anthocyanidins and Renal Cancer Risk: A Prospective Study

by
Xin Xu
*,
Yi Zhu
,
Shiqi Li
and
Dan Xia
*
Department of Urology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China
*
Authors to whom correspondence should be addressed.
Cancers 2023, 15(5), 1406; https://doi.org/10.3390/cancers15051406
Submission received: 16 January 2023 / Revised: 12 February 2023 / Accepted: 17 February 2023 / Published: 23 February 2023
(This article belongs to the Special Issue Urological Cancer: Epidemiology, Prevention and Quality of Life)
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Abstract

:

Simple Summary

In this large prospective study based on the PLCO trial, both categorical analysis and continuous analysis indicated that higher dietary anthocyanidin consumption was associated with a lower risk of renal cancer. To the best of our knowledge, this is the first prospective study that aimed to explore a potential association between dietary anthocyanidin intake and renal cancer risk.

Abstract

Evidence on the association between anthocyanidin intake and renal cancer risk is limited. The aim of this study was to assess the association of anthocyanidin intake with renal cancer risk in the large prospective Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. The cohort for this analysis consisted of 101,156 participants. A Cox proportional hazards regression model was used to estimate the hazard ratios (HRs) and the 95% confidence intervals (CIs). A restricted cubic spline model with three knots (i.e., 10th, 50th, and 90th percentiles) was used to model a smooth curve. A total of 409 renal cancer cases were identified over a median follow-up of 12.2 years. In the categorical analysis with a fully adjusted model, a higher dietary anthocyanidin consumption was associated with a lower risk of renal cancer (HRQ4vsQ1: 0.68; 95% CI: 0.51–0.92; p for trend < 0.010). A similar pattern was obtained when anthocyanidin intake was analyzed as a continuous variable. The HR of one-SD increment in the anthocyanidin intake for renal cancer risk was 0.88 (95% CI: 0.77–1.00, p = 0.043). The restricted cubic spline model revealed a reduced risk of renal cancer with a higher intake of anthocyanidins and there was no statistical evidence for nonlinearity (p for nonlinearity = 0.207). In conclusion, in this large American population, a higher dietary anthocyanidin consumption was associated with a lower risk of renal cancer. Future cohort studies are warranted to verify our preliminary findings and to explore the underlying mechanisms in this regard.

1. Introduction

The incidence of and costs related to renal cancer have increased during the last two decades. As the population ages, the prevalence of established risk factors such as obesity, hypertension and chronic kidney disease increases, and the expansion of routine imaging for many disorders means that the renal cancer burden will increase significantly [1,2]. The management of renal cancer has evolved rapidly in recent years with several immunotherapy-based combinations of strategies approved as first-line therapies for the metastatic disease. However, renal cancer remains one of the most lethal urological malignancies. According to the updated data reported by the World Health Organization, there were more than 140,000 renal cancer related deaths worldwide in 2012 [3]. With rising rates of recurrence, aside from developing a personalized therapeutic treatment plan with minimal adverse events [4], it is fundamentally important to improve cancer prevention by identifying the potential factors associated with its risk.
Recent evidence has suggested that dietary flavonoid intake may be associated with decreased risk of chronic and degenerative diseases [5]. Flavonoids are classified into 12 major subclasses based on chemical structures and different subclasses may have different effects on human diseases. Anthocyanins are colored water-soluble pigments belonging to flavonoids, which provide red, blue and purple colors to fruits and vegetables. Anthocyanin pigments have been widely used as natural food colorants [6]. Recently, these colored pigments were found to have potent antioxidant properties, which give various beneficial health effects on cardiovascular [7] and neurodegenerative diseases, as reported by scientific studies from cell culture, animal models and clinical trials [8]. Similarly, dietary anthocyanidin intake has been found to be associated with a lower risk of several cancers, including lung cancer [9], head and neck cancer [10], and esophageal cancer [11]. To the best of our knowledge, evidence on the association between anthocyanidin intake and renal cancer risk is limited. An early hospital-based case-control study from Italy was undertaken on this topic and found no significant association between anthocyanidin consumption and renal cell carcinoma [12] based on 767 RCC cases and 1534 hospital controls. Therefore, the aim of this study was to assess the association of anthocyanidin intake with renal cancer risk in the large prospective Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial.

2. Materials and Methods

2.1. Study Design and Population

The PLCO Cancer Screening Trial was a multicenter randomized controlled trial designed to assess whether screening exams could reduce the mortality from prostate, lung, colorectal, and ovarian cancers, and its study design and implementation were described previously [13]. There were two arms in the PLCO trial: the intervention arm and the control arm. A total of 76,682 men and 78,215 women aged between 55 to 74 years were enrolled in the PLCO study between November 1993 and September 2001 in ten screening centers across the United States of America (Washington, Pittsburgh, Honolulu, Denver, Marshfield, Minneapolis, Birmingham, Salt Lake City, Detroit, and St Louis). The principal recruitment strategy targeted individuals from the general population residing in the nearby areas of the screening centers. Participants in the intervention arm were screened during the first 3–4 years and participants in both arms of the study were subsequently followed for up to 10 more years to determine the potential benefits or harms of the screening exams. From its inception, the PLCO was designed not only as a RCT for the screening for four cancers but also more broadly as a research enterprise consisting of the trial, being a large, well-characterized cohort with all-cancer outcomes [14].
The current analysis is a secondary analysis of a primary database from the PLCO study. In total, 4918 participants were excluded because of a lack of baseline questionnaire data. Participants who did not complete a valid questionnaire or had been diagnosed with any cancer were also excluded (n = 48,237). We further excluded individuals with an implausible energy intake (i.e., lowest or highest 1%) (n = 546), with renal pelvis cancer (n = 34), and without follow-up time (n = 6). Overall, the cohort for this analysis consisted of 101,156 participants. Written informed consent was obtained from all the study participants, and the study protocol was approved by the Institutional Review Board of the NCI. The data used in this study were applied from the PLCO website with the permission of the NIH PLCO study group (CDAS project “PLCO-1020”).

2.2. Data Collection

Participants were arranged to complete a self-administered questionnaire containing personal baseline information. From the PLCO study, we collected information regarding age, gender, body mass index (BMI), race/ethnicity, education level, smoking status, and history of hypertension.
The Diet History Questionnaire (DHQ) version 1.0 (National Cancer Institute, 2007) was used to collect the dietary information, including the total daily energy intake and the daily intake of anthocyanidins. The DHQ recorded the frequency and quantity of 124 food items and supplements used over the past 12 months [15]. The daily frequency of food consumption was then multiplied by the representative sex-specific portion size of the food item using food composition data, which was based on the United States Department of Agriculture 1994–1996 Continuing Survey of Food Intakes by Individuals (CSFII) and the University of Minnesota’s Nutrition Data Systems for Research [16]. The DHQ was found to fare as well as or better than two widely used food frequency questionnaires (FFQs) when the PLCO trial was conducted [15]. Cyanidin, delphinidin, malvidin, peonidin, petunidin, and pelargonidin are the six common types of anthocyanidins [6,8]. In this study, the daily intake of these subclasses was collected through the DHQ. The amounts for processed foods were assumed to be 50% of the raw foods to account for the losses during processing [9]. The total daily intake of anthocyanidins was the sum of all six classes.

2.3. Renal Cancer Ascertainment

In this study, the outcome was the incidence of renal cancer. In the PLCO trial, the confirmation of the diagnosis of renal cancer was obtained from the study update forms which were mailed to participants annually asking about cancer diagnosis in the prior year. The follow-up time was based on reports from physicians and the results were confirmed by periodic linkage to the state cancer registries and the death certificates. In this study, a renal cancer case was defined as a malignant neoplasm of unspecified kidney, except for the renal pelvis (2022 ICD-10-CM Diagnosis Code C64.9). Follow-up started one year after completion of the DHQ and continued until the participants were diagnosed with cancer, withdrew from the trial, died from any cause, or completed the 10-year follow-up, whichever came first.

2.4. Statistical Analysis

A Cox proportional hazards regression model was used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs). The models were adjusted for potential confounders including age (continuous), sex, race (white versus non-white), BMI (<25.0 kg/m2 versus ≥25.0 kg/m2), education level (≤high school versus ≥some college), smoking status (ever versus current versus never), hypertension status (yes versus no), and total energy intake (continuous). The proportional hazards (PH) assumption was examined using the Schoenfeld residual test [17]. To assess the statistical significance of the potential differences across subgroups, Wald tests were performed on the interaction terms between anthocyanidin intake and the stratifying covariates. A restricted cubic spline model [18] with three knots (i.e., 10th, 50th, and 90th percentiles) was used to evaluate the non-linearity of the associations. In a sensitivity analysis, we excluded cases diagnosed within the first two years of follow-up and then repeated the analysis. All statistical analyses were performed using the software STATA version 15 (Stata Corp, College Station, TX, USA). All tests were two-sided.

3. Results

3.1. Study Characteristics

A total of 409 renal cancer cases were identified over a median follow-up of 12.2 years. Anthocyanidins from the diet ranged from 0 to 237.36 mg/day (median value: 12.17 mg/day). Table 1 shows the characteristics of participants by quartiles of anthocyanidin consumption. Overall, compared to participants with a lower intake of anthocyanidins, those with a higher consumption tended to be older, and were more likely to be female, non-Hispanic white, and never smokers at baseline. They also had a lower BMI but a higher rate of hypertension (all p < 0.001).

3.2. Dietary Anthocyanidin Intakes and Renal Cancer Risk

As shown in Table 2, in categorical analyses with a fully adjusted model, a higher dietary anthocyanidin consumption was associated with a lower risk of renal cancer (HRQ4vsQ1: 0.68; 95% CI: 0.51–0.92; p for trend <0.010). A similar pattern was obtained when anthocyanidin intake was analyzed as a continuous variable. The HR of one-SD increment in the anthocyanidin intake for renal cancer risk was 0.88 (95% CI: 0.77–1.00, p = 0.043). The proportional hazards assumption was verified using Schoenfeld residuals.
Table 3 shows the effects of the subclasses of anthocyanidin intake on renal cancer risk. The intake of delphinidin, peonidin, and petunidin was statistically significantly associated with at least a 30% reduction in the risk of renal cancer, with comparison of the highest vs. lowest quartiles (HRQ4vsQ1 for delphinidin: 0.59; 95% CI: 0.43–0.79; HRQ4vsQ1 for peonidin: 0.68; 95% CI: 0.50–0.93; HRQ4vsQ1 for petunidin: 0.69; 95% CI: 0.50–0.94). However, there was no significant association between the consumption of cyanidin, malvidin or pelargonidin and renal cancer risk.

3.3. Additional Analyses

The restricted cubic spline model revealed a reduced risk of renal cancer with a higher anthocyanidin intake (Figure 1). There was no statistical evidence for nonlinearity (p for nonlinearity = 0.207). In the subgroup analyses as shown in Table 4, a significant interaction was observed between anthocyanidin consumption and hypertension status (p = 0.002). Specifically, the favorable association between anthocyanidin intake and renal cancer risk was more pronounced in the participants with a history of hypertension than in those without. No significant interaction was observed for other stratification factors including sex, BMI and smoking status (all p > 0.05). In a sensitivity analysis, there was little change in the findings by excluding individuals with a follow-up of less than two years (HRQ4vsQ1: 0.68; 95% CI: 0.51–0.92).

4. Discussion

In this post hoc analysis of the PLCO trial, we found that the dietary intake of total anthocyanidins was inversely associated with renal cancer risk, and this association was also true for the subclasses including delphinidin, peonidin and petunidin. Importantly, the association was evident in the dose-response analysis and the sensitivity analysis.
In the subgroup analyses, a significant interaction was observed between anthocyanidin consumption and hypertension status. A more favorable association between anthocyanidin intake and renal cancer risk was observed in participants with hypertension. The reason for these findings was not clear. Participants with a history of hypertension may be more likely to have a healthy lifestyle and dietary pattern, which can promote the intake of anthocyanidin-rich foods. No significant interaction was observed for other important renal cancer risk factors including high BMI and smoking behavior. In the subgroup analysis according to the subclasses of anthocyanidins, a significant association was only observed for half of the types of anthocyanidins, including delphinidin, peonidin, and petunidin, which indicated that only part of the subclasses of anthocyanidins have health benefits.
According to the literature reviewed, the evidence has accumulated worldwide on the beneficial effects of anthocyanidins on chronic diseases [19,20], including cardiovascular disease [21], diabetes [22], nonalcoholic fatty liver disease [23], and neurological disease [24], as well as various types of cancer. Zhang et al. [9] recently reported that dietary intake of total anthocyanidins and of all six subclasses including cyanidin, delphinidin, malvidin, peonidin, petunidin, and pelargonidin were related to a reduced risk of lung cancer in the PLCO cohort. A large meta-analysis of observational studies suggested an inverse association between anthocyanidin consumption and the risk of esophageal cancer [11]. Higher intake of dietary anthocyanidins may also reduce the risk of colorectal cancer [25]. However, the relationship between anthocyanidin intake and renal cancer risk remains unclear, especially given the lack of evidence from prospective studies.
Our study, firstly, provided important data on the association between dietary anthocyanidin intake and renal cancer risk from a large-scale prospective American cohort. We also examined the association visually in a dose-response manner and according to gender and subclasses of anthocyanins, with adjustment for potential confounders. Previously, there were only two small case-control studies performed on this topic with no significant association observed [12,26]. The reasons for the inconsistency in the findings between our study and the previous two are unknown. It could be due to the unknown residual confounding, insufficient statistical power, in addition to the selection bias and recall bias imposed by case-control studies.
Several mechanisms have been proposed to explain a potential inverse association between dietary anthocyanin intake and cancer incidence. Anthocyanins may influence the composition of the gut microbiome, which may mediate the metabolic benefits of anthocyanins [27]. In a mouse model, Khandelwal et al. [28] found that the intake of the anthocyanidins pelargonidin and cyanidin reduced the genotoxic stress induced by environmental toxicants, such as diepoxybutane, urethane and endogenous nitrozation. Li et al. [29] suggested that anthocyanins exhibited anticarcinogenic properties by suppressing the proinflammatory, STAT3, and NF-kB signaling pathways and promoting the activity of essential detoxification enzymes. Farhan et al. [30] proposed that anthocyanidins could suppress human cancers by trigger copper mediated and ROS-dependent selective cell death of cancer cells. A recent umbrella review summarized that anthocyanin improved plasmatic lipids, glucose metabolism, and endothelial function [31], which all may help in cancer prevention.
As with any study of this type, our study had several limitations. Firstly, anthocyanidin consumption was only assessed once at baseline in the PLCO study and dietary information may have changed over time. In addition, anthocyanidin consumption was assessed by a self-administrated FFQ in our study, which was typically prone to response bias. Secondly, although we had adjusted for a wide range of potential confounders, our results could be susceptible to residual confounding as the present study was performed with an observational design. Thirdly, the potential co-linearity between anthocyanidins and other nutrients could mediate the observed associations, which was not determined in this study. Finally, physical activity has been inversely associated with the renal cancer risk [32,33]. Long-term dialysis [34] was a potential risk factor for renal cancer. However, these data were not available in the PLCO study and thus we could not adjust for these potential confounders.

5. Conclusions

In conclusion, in this large American population, a higher dietary consumption of total anthocyanidins, as well as three subclasses including delphinidin, peonidin and petunidin, was associated with a lower risk of renal cancer. Future cohort studies are warranted to verify our preliminary findings and to explore the underlying mechanisms in this regard.

Author Contributions

Conceptualization, X.X. and D.X.; Methodology, all authors; Data curation, X.X.; Formal analysis, X.X.; Visualization, X.X.; Writing-Original Draft Preparation, X.X. and Y.Z.; Writing-Review and Editing, D.X. and S.L.; Supervision, X.X. and D.X. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by grants from the National Natural Science Foundation of China (82172597) and Zhejiang Provincial Natural Science Foundation (LY22H160027).

Institutional Review Board Statement

The PLCO study was approved by the institutional review boards of the National Cancer Institute. The approved number of our study is PLCO-1020.

Informed Consent Statement

Patient consent was waived due to using the publicly available anonymized dataset.

Data Availability Statement

The data used in this study can be applied from PLCO website (https://cdas.cancer.gov/datasets/plco/, accessed on 15 August 2022).

Acknowledgments

The authors thank the National Cancer Institute for access to NCI’s data collected by the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. The statements contained herein are solely those of the authors and do not represent or imply concurrence or endorsement by NCI.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Wallen, E.M.; Pruthi, R.S.; Joyce, G.F.; Wise, M. Kidney cancer. J. Urol. 2007, 177, 2006–2018; discussion 2018–2009. [Google Scholar] [CrossRef] [PubMed]
  2. Capitanio, U.; Bensalah, K.; Bex, A.; Boorjian, S.A.; Bray, F.; Coleman, J.; Gore, J.L.; Sun, M.; Wood, C.; Russo, P. Epidemiology of Renal Cell Carcinoma. Eur. Urol. 2019, 75, 74–84. [Google Scholar] [CrossRef] [PubMed]
  3. Ferlay, J.; Soerjomataram, I.; Dikshit, R.; Eser, S.; Mathers, C.; Rebelo, M.; Parkin, D.M.; Forman, D.; Bray, F. Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012. Int. J. Cancer 2015, 136, E359–E386. [Google Scholar] [CrossRef] [PubMed]
  4. Chowdhury, N.; Drake, C.G. Kidney Cancer: An Overview of Current Therapeutic Approaches. Urol. Clin. N. Am. 2020, 47, 419–431. [Google Scholar] [CrossRef]
  5. Grosso, G.; Micek, A.; Godos, J.; Pajak, A.; Sciacca, S.; Galvano, F.; Giovannucci, E.L. Dietary Flavonoid and Lignan Intake and Mortality in Prospective Cohort Studies: Systematic Review and Dose-Response Meta-Analysis. Am. J. Epidemiol. 2017, 185, 1304–1316. [Google Scholar] [CrossRef]
  6. Mattioli, R.; Francioso, A.; Mosca, L.; Silva, P. Anthocyanins: A Comprehensive Review of Their Chemical Properties and Health Effects on Cardiovascular and Neurodegenerative Diseases. Molecules 2020, 25, 3809. [Google Scholar] [CrossRef]
  7. Goetz, M.E.; Judd, S.E.; Safford, M.M.; Hartman, T.J.; McClellan, W.M.; Vaccarino, V. Dietary flavonoid intake and incident coronary heart disease: The REasons for Geographic and Racial Differences in Stroke (REGARDS) study. Am. J. Clin. Nutr. 2016, 104, 1236–1244. [Google Scholar] [CrossRef] [Green Version]
  8. Khoo, H.E.; Azlan, A.; Tang, S.T.; Lim, S.M. Anthocyanidins and anthocyanins: Colored pigments as food, pharmaceutical ingredients, and the potential health benefits. Food Nutr. Res. 2017, 61, 1361779. [Google Scholar] [CrossRef] [Green Version]
  9. Zhang, Y.; Zhu, M.; Wan, H.; Chen, L.; Luo, F. Association between Dietary Anthocyanidins and Risk of Lung Cancer. Nutrients 2022, 14, 2643. [Google Scholar] [CrossRef]
  10. Sun, L.; Subar, A.F.; Bosire, C.; Dawsey, S.M.; Kahle, L.L.; Zimmerman, T.P.; Abnet, C.C.; Heller, R.; Graubard, B.I.; Cook, M.B.; et al. Dietary Flavonoid Intake Reduces the Risk of Head and Neck but Not Esophageal or Gastric Cancer in US Men and Women. J. Nutr. 2017, 147, 1729–1738. [Google Scholar] [CrossRef]
  11. Cui, L.; Liu, X.; Tian, Y.; Xie, C.; Li, Q.; Cui, H.; Sun, C. Flavonoids, Flavonoid Subclasses, and Esophageal Cancer Risk: A Meta-Analysis of Epidemiologic Studies. Nutrients 2016, 8, 350. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Bosetti, C.; Rossi, M.; McLaughlin, J.K.; Negri, E.; Talamini, R.; Lagiou, P.; Montella, M.; Ramazzotti, V.; Franceschi, S.; LaVecchia, C. Flavonoids and the risk of renal cell carcinoma. Cancer Epidemiol. Biomark. Prev. 2007, 16, 98–101. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Prorok, P.C.; Andriole, G.L.; Bresalier, R.S.; Buys, S.S.; Chia, D.; Crawford, E.D.; Fogel, R.; Gelmann, E.P.; Gilbert, F.; Hasson, M.A.; et al. Design of the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. Control Clin. Trials 2000, 21, 273S–309S. [Google Scholar] [CrossRef] [PubMed]
  14. Zhu, C.S.; Pinsky, P.F.; Kramer, B.S.; Prorok, P.C.; Purdue, M.P.; Berg, C.D.; Gohagan, J.K. The prostate, lung, colorectal, and ovarian cancer screening trial and its associated research resource. J. Natl. Cancer Inst. 2013, 105, 1684–1693. [Google Scholar] [CrossRef] [Green Version]
  15. Subar, A.F.; Thompson, F.E.; Kipnis, V.; Midthune, D.; Hurwitz, P.; McNutt, S.; McIntosh, A.; Rosenfeld, S. Comparative validation of the Block, Willett, and National Cancer Institute food frequency questionnaires: The Eating at America’s Table Study. Am. J. Epidemiol. 2001, 154, 1089–1099. [Google Scholar] [CrossRef] [Green Version]
  16. Subar, A.F.; Midthune, D.; Kulldorff, M.; Brown, C.C.; Thompson, F.E.; Kipnis, V.; Schatzkin, A. Evaluation of alternative approaches to assign nutrient values to food groups in food frequency questionnaires. Am. J. Epidemiol. 2000, 152, 279–286. [Google Scholar] [CrossRef]
  17. Schoenfeld, D. Chi-squared goodness-of-fit tests for the proportional hazards regression model. Biometrika 1980, 67, 145–153. [Google Scholar] [CrossRef]
  18. Marrie, R.A.; Dawson, N.V.; Garland, A. Quantile regression and restricted cubic splines are useful for exploring relationships between continuous variables. J. Clin. Epidemiol. 2009, 62, 511–517.e511. [Google Scholar] [CrossRef]
  19. Panchal, S.K.; John, O.D.; Mathai, M.L.; Brown, L. Anthocyanins in Chronic Diseases: The Power of Purple. Nutrients 2022, 14, 2161. [Google Scholar] [CrossRef]
  20. Gonçalves, A.C.; Nunes, A.R.; Falcão, A.; Alves, G.; Silva, L.R. Dietary Effects of Anthocyanins in Human Health: A Comprehensive Review. Pharmaceuticals 2021, 14, 690. [Google Scholar] [CrossRef]
  21. Krga, I.; Milenkovic, D. Anthocyanins: From Sources and Bioavailability to Cardiovascular-Health Benefits and Molecular Mechanisms of Action. J. Agric. Food Chem. 2019, 67, 1771–1783. [Google Scholar] [CrossRef]
  22. Blahova, J.; Martiniakova, M.; Babikova, M.; Kovacova, V.; Mondockova, V.; Omelka, R. Pharmaceutical Drugs and Natural Therapeutic Products for the Treatment of Type 2 Diabetes Mellitus. Pharmaceuticals 2021, 14, 806. [Google Scholar] [CrossRef]
  23. Mehmood, A.; Zhao, L.; Wang, Y.; Pan, F.; Hao, S.; Zhang, H.; Iftikhar, A.; Usman, M. Dietary anthocyanins as potential natural modulators for the prevention and treatment of non-alcoholic fatty liver disease: A comprehensive review. Food Res. Int. 2021, 142, 110180. [Google Scholar] [CrossRef]
  24. Suresh, S.; Begum, R.F.; Singh, S.A.; Chitra, V. Anthocyanin as a therapeutic in Alzheimer’s disease: A systematic review of preclinical evidences. Ageing Res. Rev. 2022, 76, 101595. [Google Scholar] [CrossRef]
  25. Chang, H.; Lei, L.; Zhou, Y.; Ye, F.; Zhao, G. Dietary Flavonoids and the Risk of Colorectal Cancer: An Updated Meta-Analysis of Epidemiological Studies. Nutrients 2018, 10, 950. [Google Scholar] [CrossRef] [Green Version]
  26. Rossi, M.; Bosetti, C.; Negri, E.; Lagiou, P.; La Vecchia, C. Flavonoids, proanthocyanidins, and cancer risk: A network of case-control studies from Italy. Nutr. Cancer 2010, 62, 871–877. [Google Scholar] [CrossRef] [PubMed]
  27. Dong, Y.; Wu, X.; Han, L.; Bian, J.; He, C.; El-Omar, E.; Gong, L.; Wang, M. The Potential Roles of Dietary Anthocyanins in Inhibiting Vascular Endothelial Cell Senescence and Preventing Cardiovascular Diseases. Nutrients 2022, 14, 2836. [Google Scholar] [CrossRef]
  28. Khandelwal, N.; Abraham, S.K. Intake of anthocyanidins pelargonidin and cyanidin reduces genotoxic stress in mice induced by diepoxybutane, urethane and endogenous nitrosation. Environ. Toxicol. Pharmacol. 2014, 37, 837–843. [Google Scholar] [CrossRef] [PubMed]
  29. Li, W.; Peng, C.; Zhaojie, L.; Wei, W. Chemopreventive and therapeutic properties of anthocyanins in breast cancer: A comprehensive review. Nutr. Res. 2022, 107, 48–64. [Google Scholar] [CrossRef]
  30. Farhan, M.; Rizvi, A.; Ali, F.; Ahmad, A.; Aatif, M.; Malik, A.; Alam, M.W.; Muteeb, G.; Ahmad, S.; Noor, A.; et al. Pomegranate juice anthocyanidins induce cell death in human cancer cells by mobilizing intracellular copper ions and producing reactive oxygen species. Front. Oncol. 2022, 12, 998346. [Google Scholar] [CrossRef] [PubMed]
  31. Sandoval-Ramírez, B.A.; Catalán, Ú.; Llauradó, E.; Valls, R.M.; Salamanca, P.; Rubió, L.; Yuste, S.; Solà, R. The health benefits of anthocyanins: An umbrella review of systematic reviews and meta-analyses of observational studies and controlled clinical trials. Nutr. Rev. 2022, 80, 1515–1530. [Google Scholar] [CrossRef] [PubMed]
  32. Behrens, G.; Leitzmann, M.F. The association between physical activity and renal cancer: Systematic review and meta-analysis. Br. J. Cancer 2013, 108, 798–811. [Google Scholar] [CrossRef] [PubMed]
  33. Moore, S.C.; Lee, I.M.; Weiderpass, E.; Campbell, P.T.; Sampson, J.N.; Kitahara, C.M.; Keadle, S.K.; Arem, H.; Berrington de Gonzalez, A.; Hartge, P.; et al. Association of Leisure-Time Physical Activity with Risk of 26 Types of Cancer in 1.44 Million Adults. JAMA Intern. Med. 2016, 176, 816–825. [Google Scholar] [CrossRef] [PubMed]
  34. Taborelli, M.; Toffolutti, F.; Del Zotto, S.; Clagnan, E.; Furian, L.; Piselli, P.; Citterio, F.; Zanier, L.; Boscutti, G.; Serraino, D. Increased cancer risk in patients undergoing dialysis: A population-based cohort study in North-Eastern Italy. BMC Nephrol. 2019, 20, 107. [Google Scholar] [CrossRef]
Cancers 15 01406 g001 550
Figure 1. Dose-response relationship between dietary anthocyanidin intake and renal cancer risk, based on a restricted cubic spline, which adjusted for age, sex, race, body mass index, education level, smoking status, hypertension status, and total energy intake (p for nonlinearity = 0.207).
Figure 1. Dose-response relationship between dietary anthocyanidin intake and renal cancer risk, based on a restricted cubic spline, which adjusted for age, sex, race, body mass index, education level, smoking status, hypertension status, and total energy intake (p for nonlinearity = 0.207).
Cancers 15 01406 g001
Table
Table 1. Main characteristics of participants included in this study by dietary anthocyanidin intakes.
Table 1. Main characteristics of participants included in this study by dietary anthocyanidin intakes.
VariablesQ1 (n = 25,340)Q2 (n = 25,258)Q3 (n = 25,269)Q4 (n = 25,289)p
Age (years), mean (SD)61.9 (5.2)62.5 (5.3)62.6 (5.3)62.6 (5.3)<0.001
Sex (n, %) <0.001
    Male 14,499 (57.2%)12,854 (50.9%)11,712 (46.3%)9996 (39.5%)
    Female10,841 (42.8%)12,404 (49.1%)13,557 (53.7%)15,293 (60.5%)
Smoking (n, %) <0.001
    Never10,072 (39.7%)12,067 (47.8%)12,868 (50.9%)13,348 (52.8%)
    Current4101 (16.2%)2218 (8.8%)1688 (6.7%)1309 (5.2%)
    Former11,166 (44.1%)10,969 (43.4%)10,709 (42.4%)10,628 (42.0%)
Education (n, %) <0.001
    ≤High school12,229 (48.3%)10,844 (42.9%)9944 (39.4%)9597 (37.9%)
    ≥Some college13,064 (51.6%)14,366 (56.9%)15,273 (60.4%)15,643 (61.9%)
BMI (n, %) <0.001
    <25.0 kg/m27543 (29.8%)8055 (31.9%)8814 (34.9%)9879 (39.1%)
    ≥25.0 kg/m217,442 (68.8%)16,875 (66.8%)16,123 (63.8%)15,093 (59.7%)
Race (n, %) <0.001
    White, Non-Hispanic22,592 (89.2%)23,174 (91.7%)23,305 (92.2%)22,949 (90.7%)
    Other2737 (10.8%)2075 (8.2%)1956 (7.7%)2331 (9.2%)
Hypertension (n, %) <0.001
    Yes16,734 (66.4%)16,839 (67.0%)17,065 (67.9%)17,188 (68.3%)
    No8471 (33.6%)8307 (33.0%)8077 (32.1%)7977 (31.7%)
    Total energy intake (kcal/d), mean ± SD1510.0 (678.3)1644.9 (663.5)1767.4 (673.4)1984.6 (712.0)<0.001
y, year; SD, Standard deviation; BMI, body mass index.
Table
Table 2. Association between dietary anthocyanidin intakes and renal cancer risk.
Table 2. Association between dietary anthocyanidin intakes and renal cancer risk.
Variables
(mg/day)		Median
(mg/day)		Cohort (n)Cases (n)Crude HR (95% CI), p-ValueAdjusted HR * (95% CI), p-Value
Q1 (<6.95)4.4525,340 133ReferenceReference
Q2 (≥ 6.95 to <12.18)9.4325,2581090.80 (0.62–1.03), p = 0.0830.85 (0.66–1.10), p = 0.213
Q3 (≥ 12.18 to <20.21)15.5325,269850.62 (0.47–0.81), p = 0.0010.68 (0.51–0.90), p = 0.007
Q4 (≥20.21)28.5525,289820.59 (0.45–0.78), p < 0.0010.68 (0.51–0.92), p = 0.012
p for trend < 0.001p for trend = 0.010
* Adjusted for age (continuous), sex (male vs. female), race (non-Hispanic White vs. Other), body mass index (BMI, <25.0 kg/m2 vs. ≥25.0 kg/m2), education (≤high school vs. ≥some college), smoking status (never vs. former vs. current), hypertension (yes vs. no), and total energy intake (continuous).
Table
Table 3. Associations between the subclasses of anthocyanidin intakes and renal cancer risk.
Table 3. Associations between the subclasses of anthocyanidin intakes and renal cancer risk.
VariablesCyanidinDelphinidinMalvidinPelargonidinPeonidinPetunidin
Q1ReferenceReferenceReferenceReferenceReferenceReference
Q20.83 (0.63–1.10), p = 0.1920.78 (0.59–1.03), p = 0.0751.02 (0.78–1.34), p = 0.8740.90 (0.69–1.18), p = 0.4450.97 (0.74–1.28), p = 0.8520.99 (0.76–1.29), p = 0.916
Q3 0.80 (0.60–1.07), p = 0.1280.85 (0.65–1.11), p = 0.2250.98 (0.75–1.30), p = 0.9060.93 (0.70–1.23), p = 0.6061.06 (0.81–1.38), p = 0.6860.92 (0.70–1.22), p = 0.556
Q40.86 (0.65–1.15), p = 0.3230.59 (0.43–0.79), p < 0.0010.75 (0.55–1.02), p = 0.0690.79 (0.58–1.06), p = 0.1200.68 (0.50–0.93), p = 0.0160.69 (0.50–0.94), p = 0.020
Adjusted for age (continuous), sex (male vs. female), race (non-Hispanic White vs. Other), body mass index (BMI, <25.0 kg/m2 vs. ≥25.0 kg/m2), education (≤high school vs. ≥some college), smoking status (never vs. former vs. current), hypertension (yes vs. no), and total energy intake (continuous).
Table
Table 4. Subgroup analyses between dietary anthocyanidin intakes and renal cancer risk.
Table 4. Subgroup analyses between dietary anthocyanidin intakes and renal cancer risk.
VariablesQ1 Q2Q3 Q4 p for Interaction
Sex > 0.05
    Male Reference0.95 (0.70–1.29), p = 0.7380.70 (0.49–0.99), p = 0.0440.73 (0.50–1.06), p = 0.094
    FemaleReference0.66 (0.41–1.06), p = 0.0820.62 (0.39–1.00), p = 0.0510.58 (0.35–0.95), p = 0.031
Smoking > 0.05
    NeverReference0.95 (0.62–1.46), p = 0.8100.80 (0.51–1.25), p = 0.3280.70 (0.43–1.13), p = 0.147
    CurrentReference0.38 (0.17–0.88), p = 0.0230.22 (0.07–0.74), p = 0.0140.38 (0.13–1.11), p = 0.077
    FormerReference0.97 (0.67–1.41), p = 0.8860.75 (0.50–1.12), p = 0.1590.82 (0.54–1.24), p = 0.339
BMI (n, %) > 0.05
    <25.0 kg/m2Reference0.72 (0.41–1.28), p = 0.2660.76 (0.43–1.35), p = 0.3530.70 (0.38–1.29), p = 0.253
    ≥25.0 kg/m2Reference0.89 (0.66–1.19), p = 0.4200.66 (0.48–0.92), p = 0.0130.69 (0.49–0.97), p = 0.032
Hypertension 0.002
    YesReference0.55 (0.38–0.81), p = 0.0030.66 (0.46–0.96), p = 0.0310.61 (0.41–0.92), p = 0.017
    NoReference1.27 (0.88–1.82), p = 0.1960.70 (0.46–1.08), p = 0.1110.79 (0.51–1.24), p = 0.306
BMI, body mass index.
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Xu, X.; Zhu, Y.; Li, S.; Xia, D. Dietary Intake of Anthocyanidins and Renal Cancer Risk: A Prospective Study. Cancers 2023, 15, 1406. https://doi.org/10.3390/cancers15051406

AMA Style

Xu X, Zhu Y, Li S, Xia D. Dietary Intake of Anthocyanidins and Renal Cancer Risk: A Prospective Study. Cancers. 2023; 15(5):1406. https://doi.org/10.3390/cancers15051406

Chicago/Turabian Style

Xu, Xin, Yi Zhu, Shiqi Li, and Dan Xia. 2023. "Dietary Intake of Anthocyanidins and Renal Cancer Risk: A Prospective Study" Cancers 15, no. 5: 1406. https://doi.org/10.3390/cancers15051406

APA Style

Xu, X., Zhu, Y., Li, S., & Xia, D. (2023). Dietary Intake of Anthocyanidins and Renal Cancer Risk: A Prospective Study. Cancers, 15(5), 1406. https://doi.org/10.3390/cancers15051406

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