Skip to main content
Download PDF
Download ePub

The association between dietary acid load and odds of prostate cancer: a case-control study

Journal of Health, Population and Nutrition volume 44, Article number: 72 (2025) Cite this article

Abstract

Background and objective

Conflicting results exist regarding the associations between dietary acid load (DAL) and cancer risk. This study aimed to investigate the association between DAL and the odds of prostate cancer (PC) in the Iranian population.

Methods

One hundred and twenty participants (60 controls and 60 newly diagnosed PC patients) engaged in a hospital-based case-control study conducted from April to September 2015. A validated, 160-item semi-quantitative food frequency questionnaire (FFQ) was used to assess usual dietary intakes. DAL was calculated using potential renal acid load (PRAL) and net endogenous acid production (NEAP). Multivariate logistic regression was performed to estimate odds ratios (ORs).

Results

Both PRAL (OR = 5.44; 95% CI = 2.09–14.17) and NEAP (OR = 4.88; 95% CI = 2.22–13.41) were associated with increased odds of PC in the crude model. After adjusting for potential confounders (energy intake, smoking, physical activity, ethnicity, job, education, and medication use), being in the third category of PRAL (OR = 3.42; 95% CI = 1.11–8.65) and NEAP (OR = 3.88; 95% CI = 1.26–9.55) were significantly associated with increased odds of PC.

Conclusion

Our findings suggest that dietary acid load may be linked to an increased risk of PC; however, further prospective studies with larger sample sizes and longer durations are necessary to validate these findings.

Introduction

Prostate cancer (PC) is a major health concern among the global male population [1]. It is the second most frequently diagnosed cancer and the sixth most common cause of cancer death among males worldwide [2,3,4,5]. In Iranian males, PC is the third most common cancer and the sixth leading cause of cancer-related deaths [6, 7]. Current data indicate that the incidence rate of PC in Iran is 7.1 cases per 100,000 individuals and it has also show that the rate of disease incidence has increased from 1996 to 2012 [8]. An individual’s age, ethnicity, and family history are well-known risk factors for PC; however, the pathogenesis of the disease might also be affected by other odds factors such as ultraviolet radiation, chronic inflammation, diet, alcohol consumption, and occupational exposure [9].

The association between dietary patterns and the risk of PC has been investigated in several studies, but has yielded inconsistent results [10]. Indeed, some studies showed that adherence to a Western dietary pattern could increase the odds of PC [11,12,13], but others did not find any associations [14, 15]. Additionally, research on the Mediterranean diet and the healthy eating index has produced mixed findings regarding their relationship with PC risk [11, 13, 15,16,17,18,19]. Recently, the importance of dietary acid load (DAL) has gained attention, with evidence suggesting that diet plays a significant role in maintaining acid-base balance in the body [20, 21]. Accordingly, it seems that adherence to western diets (with higher meat consumption) and healthy diets (with higher fruits and vegetables consumption and lower meat and processed grain intake), are associated with the acidic and alkali status of the diets, respectively [22]. In order to estimate dietary acid load, the potential renal acid load (PRAL) and the net endogenous acid production (NEAP) can be calculated from dietary intake [23]. The association between the DAL and risk of some cancers have been investigated in few case-control studies with inconsistent findings [24,25,26,27]. Accordingly, most of those studies showed no association between dietary acid load and odds of glioma [24], colorectal cancer [27], and breast cancer [25]. However, in a study, while the PRAL was not associated with lung cancer, the NEAP was associated with increased odds of lung cancer [26]. Regarding PC, result from a case-control study showed that a high dietary acid load (both high PRAL and NEAP) may link with increased odds of PC [28].

In summary, while some studies have explored the relationship between DAL and various cancers, there is a lack of focused research on prostate cancer. Also, there is a need for more localized research that considers cultural dietary habits. Iranian diets may differ significantly from those studied in Western contexts, and understanding how these dietary patterns affect cancer risk in this population is crucial. Moreover, by focusing on newly diagnosed PC patients we aimed to provide more reliable data on the association between diet-dependent acid load and odds of PC in an Iranian population.

Methods and materials

Subjects

The methodological framework for this secondary analysis is adapted from our prior original publication study [29]. Briefly, this hospital-based case-control study included 125 participants (62 cases and 63 controls) who were referred to hospital centers in Shiraz city from April to September 2015. The study sample size calculated based on the study by Askari et al. using α error = 0.05, β error = 0.3, and anticipated odds ratio (OR) of 0.4 [13]. Accordingly, a total of 125 individuals (62 cases and 63 controls) were included in this study. During the data collection, five participants (two cases and three controls) failed to respond to the FFQ, so they were excluded from the analyses. So, 120 participants (60 cases and 60 controls) were included in the final analysis. To collect required information such as general characteristics and dietary intakes, the patients were interviewed by trained nutritionists. We enrolled PC patients who were candidates for radical or open prostatectomy during their hospital stay according to the following inclusion criteria: Their disease was diagnosed within one month of diagnosis, and they were free from chronic diseases, diabetes, and any other type of cancer. Meanwhile, control patients from the same hospitals who had non-neoplastic, non-diabetic conditions, such as eye, gastrointestinal, ear, nose, and throat (ENT), kidney, and nerve diseases, were selected. Also, the controls did not follow any chronic disease-specific diets. The two groups were matched for body mass index (< 19, 19–25, 25–30, 30 < kg/m2) and age (within strata of 5-year age groups). Total energy intakes of < 800 or > 4200 kcal/day and poor/inadequate response to the food frequency questionnaire were considered as exclusion criteria. All participants provided informed consent and the study was approved by the ethics committee at Shiraz University of Medical Sciences (93-01-21-9059). The Helsinki declaration was followed for all methods.

Demographic and anthropometric assessment

Participant demographic data, including smoking habit (smokers/nonsmokers), physical activity level (little or never /moderate/high), ethnicity (fars/non-fars), employment status (unemployed/employed), education status (illiterate & primary/diploma & academic), and medication use (anti-hyperlipidemic, antihypertensive pharmaceuticals, and aspirin) were collected via a face-to-face interview. Weight was measured by a digital scale, with a precision of 0.1 kg (Glamor BS-801, Hitachi, China), while individuals wore light clothing and unshod. Height was measured at 0.1 cm precision, with participants in a standing position and unshod, using a non-stretchable tape. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared.

Dietary intake assessment and estimation of the DAL

An assessment of dietary intake was performed by using a semi-quantitative food frequency questionnaire (FFQ) [30,31,32]. In this questionnaire, we asked about 160 common food items common to Iranians. We categorized the frequency of consumption of each food item into nine categories: never or less than once a month, once a month, once a week, 2–4 times a week, 5–6 times a week, once a day, 2–3 times a day, 4–5 times a day, and ≥ 6 times a day. The portion sizes were categorized as follows: small portions (equal to half of the average serving size or less), medium portions (equal to the average serving size), and large portions (one and a half times the average serving size or more). The FFQs were analyzed using a specific multifunction software which developed by Borland Delphi 7 (https://borland-delphi.software.informer.com/7.0/) and Visual Basic 2008 (VB 9.0) (https://download.cnet.com/visual-basic-2008-express-edition/3000-windows-visual-basic-2008-express-edition.html). Daily intakes of energy, macronutrients, and micronutrients were derived using the Nutritionist 4 (https://nutritionist-pro.software.informer.com/4.3/#google_vignette) software. We used the PRAL and NEAP (indicators of the DAL) for estimation of the DAL. These indexes were calculated based on the previous published equation: NEAP (mEq/day) = 54.5 × protein (g/day)/potassium (mEq/ day) − 10.2 [10]. PRAL (mEq/day) = 0.4888 × protein intake (g/day) + 0.0366 × phosphorus (mg/day) − 0.0205 × potassium (mg/day) − 0.0125 × calcium (mg/day) − 0.0263 × magnesium (mg/day) [33].

Statistical analysis

The normality of the data was assessed using Kolmogorov-Smirnov test. Categorical variables were presented as percent, and continuous variables presented as mean ± SD. For comparing quantitative and qualitative variables across tertiles of PRAL and NEAP scores, one-way analysis of variance (ANOVA) and Chi-square or Fischer exact tests were used, respectively. Dietary intakes of participants across tertiles of PRAL and NEAP scores were compared using analysis of covariance (ANCOVA) test and presented as mean ± SE. Using multivariate logistic regression, we evaluated prostate cancer odds using PRAL and NEAP. A number of potential confounders were controlled in adjusted models, including age, body mass index, energy intake, smoking, physical activity, ethnicity, job, education, and drug use. Literature review of previously published articles, including PC as an outcome, led to the selection of these confounders. Statistical analyses were performed using SPSS software (version 23, SPSS Inc., Chicago, IL, USA), whilst P < 0.05 was, a priori, considered statistically significant.

Results

Sociodemographic characteristics, anthropometric measures, and energy intakes of participants are shown in Table 1. The results showed that controls were more physically active than cases (P = 0.02) and had lower PRAL (P = 0.01) and NEAP (P = 0.01) scores. Other characteristics didn’t differ between the cases and controls (P > 0.05).

Table 1 Socio-demographic characteristics, anthropometric measures, and energy intakes among 60 prostatic cancer cases and 60 hospital-based controls
Full size table

Major dietary intakes of study participants are shown in Table 2. As seen, there is differences between the cases and the controls in terms of dietary intakes of some food groups. Accordingly, the cases had lower intakes of fruits (P = 0.001) and vegetables (P = 0.01) and greater intakes of red/processed meats (P < 0.001) and sweets (P = 0.01) compared to the controls.

Table 2 Major dietary intakes among 60 prostatic cancer cases and 60 hospital-based controls
Full size table

The participant characteristics across the tertiles of PRAL and NEAP in cases and controls are shown in Table 3. It was observed that with increment of PRAL score, BMI of individuals in control group decreased (P = 0.04). Moreover, through tertiles of NEAP, the number of antihypertensive drug users were significantly increased in cases (P = 0.02). The results for other variables were not significant in both cases and controls (P > 0.05).

Table 3 General characteristics of participants across tertiles of PRAL and NEAP scores among 60 prostatic cancer cases and 60 hospital-based controls
Full size table

Table 4 presents the mean intakes of macronutrients and micronutrients across the tertiles of PRAL and NEAP in cases and controls. In cases, it shows that higher PRAL was significantly associated with higher dietary protein intake (P < 0.001). However, the results showed that dietary fiber (P < 0.001), Vitamin E (P = 0.05), Vitamin C (P = 0.03), Vitamin B6 (P = 0.04), potassium (P < 0.001), calcium (P = 0.04) and magnesium (P < 0.001), decreased across tertiles of PRAL. In controls, higher PRAL score were significantly associated with greater protein (P = 0.01), total fat (P = 0.01), Vitamin B12 (P = 0.01). In contrast, increased PRAL was significantly associated with lower dietary fiber (P < 0.001), Vitamin A (P < 0.001), Vitamin E (P < 0.001), Vitamin K (P < 0.001), Vitamin C (P < 0.001), Vitamin B5 (P = 0.05), Vitamin B6 (P < 0.001), Vitamin B9 (P < 0.001), potassium (P < 0.001), phosphorous (P = 0.05), calcium (P = 0.02), magnesium (P < 0.001), and zinc (P = 0.05).

Table 4 Dietary intakes of participants across tertiles of PRAL and NEAP scores among 60 prostatic cancer cases and 60 hospital-based controlsa
Full size table

Regarding the NEAP score, the higher score was significantly related with greater protein (P < 0.001) and zinc (P = 0.05) while lower intake of dietary fiber (P < 0.001), Vitamin E (P = 0.02), Vitamin C (P = 0.04), Vitamin B6 (P = 0.05), potassium (P < 0.001), calcium (P = 0.02), and magnesium (P = 0.01) in cases. Such assessments in controls showed that higher NEAP scores were linked with less dietary fiber (P < 0.001), Vitamin A (P = 0.01), Vitamin E (P < 0.001), Vitamin K (P = 0.01), Vitamin C (P < 0.001), Vitamin B6 (P < 0.001), Vitamin B9 (P < 0.001), potassium (P < 0.001), calcium (P = 0.03), magnesium (P < 0.001) and higher Vitamin B12 (P = 0.02).

The odds ratios (OR) of PC according to tertiles of PRAL and NEAP are presented in Table 5. Our crude results suggested that being in the third, compared to the first, tertiles of PRAL (OR = 5.44; 95% CI= (2.09–14.17)) or NEAP (OR = 4.88; 95% CI= (2.22–13.41)) increased the odds of PC. Moreover, after adjusting for potential confounders (energy intake, smoking, physical activity, ethnicity, job, education, anti-hyperlipidemic drugs, antihypertensive drugs, and aspirin), being in the third, compared to the first, tertiles of PRAL (OR = 3.42; 95% CI= (1.11–8.65)) or NEAP (OR = 3.88; 95% CI= (1.26–9.55)) remained significantly associated with an increased odd of PC.

Table 5 Odds of prostate cancer in relation to PRAL and NEAP among 60 prostatic cancer cases and 60 hospital-based controlsa
Full size table

Discussion

The results of this case-control study showed that DAL, as assessed by both PRAL and NEAP, was significantly associated with a higher odd of PC. The association between some nutrients and risk of PC have been investigated previously [34,35,36,37,38,39,40,41,42,43,44]; clearly, diet is the primary external or environmental epigenetic factor determining cancer development or maintenance [45]. This study showed a positive association between the DAL and odds of PC. In line with our results, a case-control study showed that dietary acid load (both high PRAL and NEAP) may link with increased odds of PC [26]. Also, few studies have suggested that acidic environments and the DALs might contribute to cancer development [46,47,48]; however, other studies have not substantiated these observations [47]. Regarding some specific types of cancer, previous research showed direct association between net acid excretion and odds of bladder cancer [25]. Also, in another study, higher acid load in diet was associated with higher odds of breast cancer [49]. Moreover, a lower serum bicarbonate level has also been associated with higher cancer mortality [50].

It appears that carcinogenesis may occur via intermediary effects associated with metabolic acidosis, as demonstrated in some studies [45]. As a result of dietary acid overload, metabolic acidosis can promote metastasis due to reduced buffering capacity of cancer patients [51,52,53]. Some studies on patients with cancer also showed changes in pH in the cancerous cells and their microenvironment, such that intracellular pH (pHi) increased compared to normal cells while extracellular pH (pHe) decreased [54]. Other studies have shown that shift towards higher consumption of acid-forming foods (like meats and processed foods), lower consumption of alkaline-forming foods (like fruits and vegetables), or supplementing with bicarbonate or phosphate salt, could affect the pH of urine, but not the pH of blood. It is generally believed that diet can cause metabolic acidosis through disruption of acid-base balance and the production of acid or alkaline precursors, and consuming acidogenic diets could promote higher urinary acid excretion in comparison to alkalizing foods [55,56,57,58]. In our study, the amounts of daily fruits and vegetables intakes seems to be high. Our finding is somewhat similar to a study by another study conducted in Iranian population [59]. In contrast, other Iranian studies reported lower fruits and vegetables intakes [60, 61]. Nevertheless, it cannot affect the overall findings because the indices (the PRAL and the NEAP) were estimated using different nutrients such as protein, phosphorus, potassium, calcium, and magnesium. These nutrients of course derives from different food items. For example, plant-based foods like fruits, vegetables, and grains are rich sources for potassium and magnesium and animal-based foods like dairies and meats are rich in protein, calcium, and phosphorus. So, an acid-base imbalance in a diet is under the influence of different nutrients not only one or two ones.

As a consequence, comprehensive mechanistic and clinical trials would be needed to determine the specific associations between the DAL and cancer pathogenesis.

This study had some strengths that should be noted. First, as far as we know this study is among few research investigating the association between the DAL and odds of PC. Second, as a result of using newly diagnosed cases, we were able to lower cancer odds associated with dietary changes in the subjects. Third, the statistical models were adjusted for several confounders, allowing more certainty of the results. However, despite the strengths and novelty of our study, there are some limitations that should be acknowledged. First, although we used a validated semi-quantitative FFQ, response errors, recall bias, and social desirability are inevitable in gathering data using FFQ. Second, it is impossible to avoid selection bias in case-control studies, and the same as all case-control studies, it was impossible to make a causal association between the DAL and PC. Third, while we matched controls and cases by age and body mass index and adjusted for several confounders, there will always be some residual confounders, which may affect our findings. Forth, we included hospital controls that cannot be representative of the population living in Shiraz province. Fifth, while the analysis provides valuable insights, the findings should be interpreted with caution due to the limited sample size. Sixth, further studies with larger sample sizes are needed to validate the associations observed in this study and reduce the risk of erroneous conclusions.

Conclusion

The results of this study suggest that the DAL could increase the odds of PC. Furthermore, the study revealed higher consumption of animal-based nutrients and lower consumption of plant-based nutrients after DAL scores were increased. The study’s findings suggest a significant association between dietary acid load and increased odds of PC, indicating that dietary modifications could play a crucial role in cancer prevention and management. Integrating these dietary considerations into clinical practice and healthcare providers can enhance patient care and potentially improve outcomes for individuals. These findings, however, need to be verified in further prospective studies with larger sample sizes and lengthier follow-up times.

Data availability

No datasets were generated or analysed during the current study.

References

  1. Agalliu I, Adebiyi AO, Lounsbury DW, Popoola O, Jinadu K, Amodu O, Paul S, Adedimeji A, Asuzu C, Asuzu M. The feasibility of epidemiological research on prostate cancer in African men in Ibadan, Nigeria. BMC Public Health. 2015;15(1):425.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Shafi H, Mooudi E, Abolfazli M, Zarghami A, Mohamadpoumr M, Firoozjai AR, Rahimi M. Screening of prostate cancer in individuals older than 40 years of age with positive heredity. J Mazandaran Univ Med Sci. 2013;22(97):159–64.

    Google Scholar 

  3. Torres-Roman JS, Ruiz EF, Martinez‐Herrera JF, Mendes Braga SF, Taxa L, Saldaña‐Gallo J, Pow‐Sang MR, Pow‐Sang JM, La Vecchia C. Prostate cancer mortality rates in Peru and its geographical regions. BJU Int. 2019;123(4):595–601.

    Article  PubMed  Google Scholar 

  4. Ferlay J, Ervik M, Lam F, Colombet M, Mery L, Piñeros M, Znaor A, Soerjomataram I, Bray F. Global cancer observatory: cancer today. Lyon, France: international agency for research on cancer. Cancer Today 2018.

  5. Gathirua-Mwangi WG, Zhang J. Dietary factors and risk of advanced prostate cancer. Eur J cancer Prevention: Official J Eur Cancer Prev Organisation (ECP). 2014;23(2):96.

    Article  CAS  Google Scholar 

  6. KOLAH DS, SAJADI A, Radmard AR, KHADEMI H. Five common cancers in Iran. 2010.

  7. Pakzad R, Rafiemanesh H, Ghoncheh M, Sarmad A, Salehiniya H, Hosseini S, Sepehri Z, Afshari-Moghadam A. Prostate cancer in Iran: trends in incidence and morphological and epidemiological characteristics. Asian Pac J Cancer Prev. 2016;17(2):839–43.

    Article  PubMed  Google Scholar 

  8. Moradi A, Zamani M, Moudi E. A systematic review and meta-analysis on incidence of prostate cancer in Iran. Health Promotion Perspect. 2019;9(2):92.

    Article  Google Scholar 

  9. Heidenreich A, Bastian PJ, Bellmunt J, Bolla M, Joniau S, van der Kwast T, Mason M, Matveev V, Wiegel T, Zattoni F. EAU guidelines on prostate cancer. Part 1: screening, diagnosis, and local treatment with curative intent—update 2013. Eur Urol. 2014;65(1):124–37.

    Article  PubMed  Google Scholar 

  10. Steck SE, Murphy EA. Dietary patterns and cancer risk. Nat Rev Cancer. 2020;20(2):125–38.

    Article  CAS  PubMed  Google Scholar 

  11. Rosato V, Edefonti V, Bravi F, Bosetti C, Bertuccio P, Talamini R, Dal Maso L, Montella M, Ferraroni M, La Vecchia C. Nutrient-based dietary patterns and prostate cancer risk: a case–control study from Italy. Cancer Causes Control. 2014;25(4):525–32.

    Article  PubMed  Google Scholar 

  12. Jalilpiran Y, Dianatinasab M, Zeighami S, Bahmanpour S, Ghiasvand R, Mohajeri SAR, Faghih S. Western dietary pattern, but not mediterranean dietary pattern, increases the risk of prostate cancer. Nutr Cancer. 2018;70(6):851–9.

    Article  PubMed  Google Scholar 

  13. Askari F, Parizi MK, Jessri M, Rashidkhani B. Dietary patterns in relation to prostate cancer in Iranian men: a case-control study. Asian Pac J Cancer Prev. 2014;15(5):2159–63.

    Article  PubMed  Google Scholar 

  14. Jackson M, Tulloch-Reid M, Walker S, McFarlane-Anderson N, Bennett F, Francis D, Coard K. Dietary patterns as predictors of prostate cancer in Jamaican men. Nutr Cancer. 2013;65(3):367–74.

    Article  CAS  PubMed  Google Scholar 

  15. Castelló A, Boldo E, Amiano P, Castaño-Vinyals G, Aragonés N, Gómez-Acebo I, Peiró R, Jimenez-Moleón JJ, Alguacil J, Tardón A. Mediterranean dietary pattern is associated with low risk of aggressive prostate cancer: MCC-Spain study. J Urol. 2018;199(2):430–7.

    Article  PubMed  Google Scholar 

  16. Yang M, Kenfield SA, Van Blarigan EL, Batista JL, Sesso HD, Ma J, Stampfer MJ, Chavarro JE. Dietary patterns after prostate cancer diagnosis in relation to disease-specific and total mortality. Cancer Prev Res. 2015;8(6):545–51.

    Article  CAS  Google Scholar 

  17. Möller E, Galeone C, Andersson TM-L, Bellocco R, Adami H-O, Andrén O, Grönberg H, La Vecchia C, Mucci LA, Bälter K. Mediterranean diet score and prostate cancer risk in a Swedish population-based case–control study. J Nutritional Sci 2013, 2.

  18. Hashemian M, Poustchi H, Abnet CC, Boffetta P, Dawsey SM, Brennan PJ, Pharoah P, Etemadi A, Kamangar F, Sharafkhah M. Dietary intake of minerals and risk of esophageal squamous cell carcinoma: results from the Golestan cohort study. Am J Clin Nutr. 2015;102(1):102–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Eslamparast T, Sharafkhah M, Poustchi H, Hashemian M, Dawsey SM, Freedman ND, Boffetta P, Abnet CC, Etemadi A, Pourshams A. Nut consumption and total and cause-specific mortality: results from the Golestan cohort study. Int J Epidemiol. 2017;46(1):75–85.

    PubMed  Google Scholar 

  20. Osuna-Padilla I, Leal-Escobar G, Garza-García C, Rodríguez-Castellanos F. Dietary acid load: mechanisms and evidence of its health repercussions. Nefrología (English Edition). 2019;39(4):343–54.

    Article  CAS  Google Scholar 

  21. Hietavala E, Stout J, Hulmi J, Suominen H, Pitkänen H, Puurtinen R, Selänne H, Kainulainen H, Mero A. Effect of diet composition on acid–base balance in adolescents, young adults and elderly at rest and during exercise. Eur J Clin Nutr. 2015;69(3):399–404.

    Article  CAS  PubMed  Google Scholar 

  22. Della Guardia L, Roggi C, Cena H. Diet-induced acidosis and alkali supplementation. Int J Food Sci Nutr. 2016;67(7):754–61.

    Article  CAS  PubMed  Google Scholar 

  23. Abbasalizad Farhangi M, Nikniaz L, Nikniaz Z. Higher dietary acid load potentially increases serum triglyceride and obesity prevalence in adults: an updated systematic review and meta-analysis. PLoS ONE. 2019;14(5):e0216547.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Milajerdi A, Shayanfar M, Benisi-Kohansal S, Mohammad-Shirazi M, Sharifi G, Tabibi H, Esmaillzadeh A. A case-control study on dietary acid load in relation to glioma. Nutr Cancer. 2022;74(5):1644–51.

    Article  CAS  PubMed  Google Scholar 

  25. Safabakhsh M, Imani H, Yaseri M, Omranipour R, Shab-Bidar S. Higher dietary acid load is not associated with risk of breast cancer in Iranian women. Cancer Rep. 2020;3(2):e1212.

    Article  CAS  Google Scholar 

  26. Ronco AL, Martínez-López W, Calderón JM, Golomar W. Dietary acid load and lung cancer risk: a case-control study in men. Cancer Treat Res Commun. 2021;28:100382.

    Article  PubMed  Google Scholar 

  27. Nasab SJ, Rafiee P, Bahrami A, Rezaeimanesh N, Rashidkhani B, Sohrab G, Naja F, Hejazi E, Sadeghi A. Diet-dependent acid load and the risk of colorectal cancer and adenoma: a case–control study. Public Health Nutr. 2021;24(14):4474–81.

    Article  Google Scholar 

  28. Ronco AL, Storz MA, Martinez-Lopez W, Calderon JM, Golomar W. High dietary acid load is associated with prostate cancer risk: an epidemiological study. World cancer Res J. 2021;8:e2119.

    Google Scholar 

  29. Jalilpiran Y, Hezaveh E, Bahmanpour S, Faghih S. Healthy plant foods intake could protect against prostate cancer risk: a case-control study. Asian Pac J Cancer Prevention: APJCP. 2017;18(7):1905.

    Google Scholar 

  30. Nematy MNM. Validity and reproducibility of Iranian food frequency questionnaire. Switz Res Park J. 2013;102:2137–46.

    Google Scholar 

  31. Tafazoli M, Fazeli E, Nematy M, Bahri N, Dadgar S. The relationship between functional ovarian cysts and vitamin A, vitamin E, and folate intake. J Obstet Gynaecology: J Inst Obstet Gynecol. 2017;37(2):205–9.

    Article  CAS  Google Scholar 

  32. Mosallaei ZMM, Safariyan M, Norouzy A. Mohajeri SAR Ea: dietary intake and its relationship with non-alcoholic fatty liver disease (NAFLD).

  33. Aslani Z, Bahreynian M, Namazi N, Shivappa N, Hébert JR, Asayesh H, Motlagh ME, Pourmirzaei MA, Kasaeian A, Mahdavi-Gorabi A. Association of dietary acid load with anthropometric indices in children and adolescents. Eating and Weight Disorders-Studies on Anorexia, Bulimia and Obesity 2021, 26(2):555–567.

  34. Xu X, Cheng Y, Li S, Zhu Y, Xu X, Zheng X, Mao Q, Xie L. Dietary Carrot consumption and the risk of prostate cancer. Eur J Nutr. 2014;53(8):1615–23.

    Article  CAS  PubMed  Google Scholar 

  35. Lu Y, Zhai L, Zeng J, Peng Q, Wang J, Deng Y, Xie L, Mo C, Yang S, Li S. Coffee consumption and prostate cancer risk: an updated meta-analysis. Cancer Causes Control. 2014;25(5):591–604.

    Article  PubMed  Google Scholar 

  36. Zhou X-F, Ding Z-S, Liu N-B. Allium vegetables and risk of prostate cancer: evidence from 132,192 subjects. Asian Pac J Cancer Prev. 2013;14(7):4131–4.

    Article  PubMed  Google Scholar 

  37. Lin Y-w, Hu Z-h, Wang X, Mao Q-q, Qin J. Zheng X-y, Xie L-p: tea consumption and prostate cancer: an updated meta-analysis. World J Surg Oncol. 2014;12(1):38.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Sheng T, Shen R-l, Shao H, Ma T-h. No association between fiber intake and prostate cancer risk: a meta-analysis of epidemiological studies. World J Surg Oncol. 2015;13(1):264.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Chen P, Zhang W, Wang X, Zhao K, Negi DS, Zhuo L, Qi M, Wang X, Zhang X. Lycopene and risk of prostate cancer: a systematic review and meta-analysis. Medicine 2015, 94(33).

  40. Chen JSY, Zhang LJ, Nutr Sci, Vitaminol. 59, 213–223, 2013.:: Lycopene/Tomato consumption and the risk of prostate cancer: a systematic review and meta-analysis of prospective studies. 2013., 59, 213–223.

  41. Xu C, Han F-F, Zeng X-T, Liu T-Z, Li S, Gao Z-Y. Fat intake is not linked to prostate cancer: a systematic review and dose-response meta-analysis. PLoS ONE 2015, 10(7).

  42. Meng H, Hu W, Chen Z, Shen Y. Fruit and vegetable intake and prostate cancer risk: A meta-analysis. Asia‐Pacific J Clin Oncol. 2014;10(2):133–40.

    Article  Google Scholar 

  43. Wu K, Spiegelman D, Hou T, Albanes D, Allen NE, Berndt SI, Van Den Brandt PA, Giles GG, Giovannucci E, Alexandra Goldbohm R. Associations between unprocessed red and processed meat, poultry, seafood and egg intake and the risk of prostate cancer: a pooled analysis of 15 prospective cohort studies. Int J Cancer. 2016;138(10):2368–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Aune D, Navarro Rosenblatt DA, Chan DS, Vieira AR, Vieira R, Greenwood DC, Vatten LJ, Norat T. Dairy products, calcium, and prostate cancer risk: a systematic review and meta-analysis of cohort studies. Am J Clin Nutr. 2015;101(1):87–117.

    Article  CAS  PubMed  Google Scholar 

  45. Robey IF. Examining the relationship between diet-induced acidosis and cancer. Nutr Metabolism. 2012;9(1):72.

    Article  CAS  Google Scholar 

  46. Wang R, Wen Z-Y, Liu F-H, Wei Y-F, Xu H-L, Sun M-L, Zhao Y-H, Gong T-T, Wang H-H, Wu Q-J. Association between dietary acid load and cancer risk and prognosis: an updated systematic review and meta-analysis of observational studies. Front Nutr 2022, 9.

  47. Fenton TR, Huang T. Systematic review of the association between dietary acid load, alkaline water and cancer. BMJ Open. 2016;6(6):e010438.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Armstrong H, Bording-Jorgensen M, Wine E. The multifaceted roles of diet, microbes, and metabolites in Cancer. Cancers. 2021;13(4):767.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Park YMM, Steck SE, Fung TT, Merchant AT, Elizabeth Hodgson M, Keller JA, Sandler DP. Higher diet-dependent acid load is associated with risk of breast cancer: findings from the sister study. Int J Cancer. 2019;144(8):1834–43.

    Article  CAS  PubMed  Google Scholar 

  50. Park M, Jung SJ, Yoon S, Yun JM, Yoon H-J. Association between the markers of metabolic acid load and higher all-cause and cardiovascular mortality in a general population with preserved renal function. Hypertens Res. 2015;38(6):433–8.

    Article  CAS  PubMed  Google Scholar 

  51. Kato Y, Ozawa S, Miyamoto C, Maehata Y, Suzuki A, Maeda T, Baba Y. Acidic extracellular microenvironment and cancer. Cancer Cell Int. 2013;13(1):1–8.

    Article  Google Scholar 

  52. Justus CR, Dong L, Yang LV. Acidic tumor microenvironment and pH-sensing G protein-coupled receptors. Front Physiol. 2013;4:354.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Huang S, Tang Y, Peng X, Cai X, Wa Q, Ren D, Li Q, Luo J, Li L, Zou X. Acidic extracellular pH promotes prostate cancer bone metastasis by enhancing PC-3 stem cell characteristics, cell invasiveness and VEGF-induced vasculogenesis of BM-EPCs. Oncol Rep. 2016;36(4):2025–32.

    Article  CAS  PubMed  Google Scholar 

  54. Boedtkjer E, Pedersen SF. The acidic tumor microenvironment as a driver of cancer. Annu Rev Physiol. 2020;82:103–26.

    Article  CAS  PubMed  Google Scholar 

  55. Miki A, Hashimoto Y, Tanaka M, Kobayashi Y, Wada S, Kuwahata M, Kido Y, Yamazaki M, Fukui M. Urinary pH reflects dietary acid load in patients with type 2 diabetes. J Clin Biochem Nutr. 2017;61(1):74–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Kanbara A, Miura Y, Hyogo H, Chayama K, Seyama I. Effect of urine pH changed by dietary intervention on uric acid clearance mechanism of pH-dependent excretion of urinary uric acid. Nutr J. 2012;11(1):1–7.

    Article  Google Scholar 

  57. Iwase H, Tanaka M, Kobayashi Y, Wada S, Kuwahata M, Kido Y, Hamaguchi M, Asano M, Yamazaki M, Hasegawa G. Lower vegetable protein intake and higher dietary acid load associated with lower carbohydrate intake are risk factors for metabolic syndrome in patients with type 2 diabetes: Post-hoc analysis of a cross‐sectional study. J Diabetes Invest. 2015;6(4):465–72.

    Article  CAS  Google Scholar 

  58. Adeva MM, Souto G. Diet-induced metabolic acidosis. Clin Nutr. 2011;30(4):416–21.

    Article  CAS  PubMed  Google Scholar 

  59. Tabibian SR, Hajhashemy Z, Shaabani P, Saneei P, Keshteli AH, Esmaillzadeh A, Adibi P. The relationship between fruit and vegetable intake with functional dyspepsia in adults. Neurogastroenterology Motil. 2021;33(9):e14129.

    Article  Google Scholar 

  60. Esmaillzadeh A, Kimiagar M, Mehrabi Y, Azadbakht L, Hu FB, Willett WC. Fruit and vegetable intakes, C-reactive protein, and the metabolic syndrome. Am J Clin Nutr. 2006;84(6):1489–97.

    Article  CAS  PubMed  Google Scholar 

  61. Ghasemian Gorji F, Ghadimi R, Hosseini SR, Bijani A, Shirzad A, Sayadi F, Baladi F, Mahmoodi E, Jenabian N, Naghibi M. Frequency of fruit and vegetable consumption and oral health-related quality of life among the elderly in Amirkola (Babol, Iran). Casp J Dent Res. 2023;12(1):8–19.

    Google Scholar 

Download references

Acknowledgements

Authors would like to thank the participants for their kind cooperation.

Funding

This study was financially supported by the Students Research Committee, Shiraz University of Medical Sciences (grant number: 93-01-21-9059).

Author information

Authors and Affiliations

  1. Department of community Nutrition, School of Nutritional Science and Dietetics, Tehran University of Medical Sciences, Tehran, Iran

    Sanaz Mehranfar, Yahya Jalilpiran, Alireza Jafari & Leila Setayesh

  2. Students’ Scientific Research Center (SSRC), Tehran University of Medical Sciences (TUMS), Tehran, Iran

    Yahya Jalilpiran

  3. School of Kinesiology and Health sciences, Faculty of Health, York University-Keele Campus, Toronto, Canada

    Haleh Rahimi

  4. Centre for Intelligent Healthcare, Coventry University, Coventry, CV1 5FB, UK

    Cain C. T. Clark

  5. Department of Community Nutrition, School of Nutrition and Food Sciences, Shiraz University of Medical Sciences, Shiraz, Iran

    Shiva Faghih

Authors
  1. Sanaz Mehranfar
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Yahya Jalilpiran
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Haleh Rahimi
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Alireza Jafari
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Leila Setayesh
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Cain C. T. Clark
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Shiva Faghih
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

S.M. wrote the manuscript; Y.J. collected the data; A.J. contributed to data analysis; H.R, L.S., and C. C. revised and edited the manuscript; S.F. designed the study and managed and supervised the final manuscript.

Corresponding author

Correspondence to Shiva Faghih.

Ethics declarations

Ethics approval and consent to participate

This study was ethically approved by ethics committee of Shiraz University of medical sciences (approval number: IR.SUMS.REC.1394. S 438). Then, written informed consent was obtained from all patients. All methods were performed in accordance with the declaration of Helsinki.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mehranfar, S., Jalilpiran, Y., Rahimi, H. et al. The association between dietary acid load and odds of prostate cancer: a case-control study. J Health Popul Nutr 44, 72 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s41043-025-00811-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s41043-025-00811-8

Keywords

Journal of Health, Population and Nutrition

ISSN: 2072-1315

Contact us