Skip to main content

Main menu

  • Home
  • Content
    • Published Ahead of Print
    • Current Issue
    • Podcasts
    • Subject Collections
    • Archives
    • ASN Meeting Abstracts
    • Saved Searches
  • Authors
    • Submit a Manuscript
    • Author Resources
    • Reprint Information
  • Trainees
    • Peer Review Program
    • Prize Competition
  • About CJASN
    • About CJASN
    • Editorial Team
    • CJASN Impact
    • CJASN Recognitions
  • More
    • Alerts
    • Advertising
    • Reprint Information
    • Subscriptions
    • Feedback
  • ASN Kidney News
  • Other
    • JASN
    • Kidney360
    • Kidney News Online
    • American Society of Nephrology

User menu

  • Subscribe
  • My alerts
  • Log in
  • My Cart

Search

  • Advanced search
American Society of Nephrology
  • Other
    • JASN
    • Kidney360
    • Kidney News Online
    • American Society of Nephrology
  • Subscribe
  • My alerts
  • Log in
  • My Cart
Advertisement
American Society of Nephrology

Advanced Search

  • Home
  • Content
    • Published Ahead of Print
    • Current Issue
    • Podcasts
    • Subject Collections
    • Archives
    • ASN Meeting Abstracts
    • Saved Searches
  • Authors
    • Submit a Manuscript
    • Author Resources
    • Reprint Information
  • Trainees
    • Peer Review Program
    • Prize Competition
  • About CJASN
    • About CJASN
    • Editorial Team
    • CJASN Impact
    • CJASN Recognitions
  • More
    • Alerts
    • Advertising
    • Reprint Information
    • Subscriptions
    • Feedback
  • ASN Kidney News
  • Visit ASN on Facebook
  • Follow CJASN on Twitter
  • CJASN RSS
  • Community Forum
Original ArticlesEpidemiology and Outcomes
You have accessRestricted Access

Dietary Fiber, Kidney Function, Inflammation, and Mortality Risk

Hong Xu, Xiaoyan Huang, Ulf Risérus, Vidya M. Krishnamurthy, Tommy Cederholm, Johan Ärnlöv, Bengt Lindholm, Per Sjögren and Juan Jesús Carrero
CJASN December 2014, 9 (12) 2104-2110; DOI: https://doi.org/10.2215/CJN.02260314
Hong Xu
*Divisions of Renal Medicine and Baxter Novum, Department of Clinical Science, Intervention, and Technology, and
†Department of Nephrology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Xiaoyan Huang
*Divisions of Renal Medicine and Baxter Novum, Department of Clinical Science, Intervention, and Technology, and
‡Division of Nephrology, Peking University Shenzhen Hospital, Peking University, Shenzhen, China;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ulf Risérus
Sections of §Clinical Nutrition and Metabolism and
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Vidya M. Krishnamurthy
*Divisions of Renal Medicine and Baxter Novum, Department of Clinical Science, Intervention, and Technology, and
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Tommy Cederholm
Sections of §Clinical Nutrition and Metabolism and
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Johan Ärnlöv
‖Geriatrics, Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden; and
¶School of Health and Social Studies, Dalarna University, Falun, Sweden
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Bengt Lindholm
*Divisions of Renal Medicine and Baxter Novum, Department of Clinical Science, Intervention, and Technology, and
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Per Sjögren
Sections of §Clinical Nutrition and Metabolism and
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Juan Jesús Carrero
*Divisions of Renal Medicine and Baxter Novum, Department of Clinical Science, Intervention, and Technology, and
**Center for Molecular Medicine, Karolinska Institute, Stockholm, Sweden;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data Supps
  • Info & Metrics
  • View PDF
Loading

Abstract

Background and objectives In the United States population, high dietary fiber intake has been associated with a lower risk of inflammation and mortality in individuals with kidney dysfunction. This study aimed to expand such findings to a Northern European population.

Design, setting, participants, & measurements Dietary fiber intake was calculated from 7-day dietary records in 1110 participants aged 70–71 years from the Uppsala Longitudinal Study of Adult Men (examinations performed during 1991–1995). Dietary fiber was adjusted for total energy intake by the residual method. Renal function was estimated from the concentration of serum cystatin C, and deaths were registered prospectively during a median follow-up of 10.0 years.

Results Dietary fiber independently and directly associated with eGFR (adjusted difference, 2.6 ml/min per 1.73 m2 per 10 g/d higher; 95% confidence interval [95% CI], 0.3 to 4.9). The odds of C-reactive protein >3 mg/L were lower (linear trend, P=0.002) with higher fiber quartiles. During follow-up, 300 participants died (incidence rate of 2.87 per 100 person-years at risk). Multiplicative interactions were observed between dietary fiber intake and kidney dysfunction in the prediction of mortality. Higher dietary fiber was associated with lower mortality in unadjusted analysis. These associations were stronger in participants with kidney dysfunction (eGFR<60 ml/min per 1.73 m2) (hazard ratio [HR], 0.58; 95% CI, 0.35 to 0.98) than in those without (HR, 1.30; 95% CI, 0.76 to 2.22; P value for interaction, P=0.04), and were mainly explained by a lower incidence of cancer-related deaths (0.25; 95% CI, 0.10 to 0.65) in individuals with kidney dysfunction versus individuals with an eGFR≥60 ml/min per 1.73 m2 (1.61; 95% CI, 0.69 to 3.74; P value for interaction, P=0.01).

Conclusions High dietary fiber was associated with better kidney function and lower inflammation in community-dwelling elderly men from Sweden. High dietary fiber was also associated with lower (cancer) mortality risk, especially in individuals with kidney dysfunction.

  • CKD
  • chronic inflammation
  • GFR
  • mortality risk
  • nutrition

Introduction

CKD is increasingly recognized as a public health burden, affecting >10% of the general population and with a much larger prevalence among elderly persons (1,2). Patients with CKD have a substantially increased risk of malnutrition, persistent inflammation, and cardiovascular disease (CVD), which collectively leads to high mortality risk (3,4). Identification of modifiable risk factors that could reduce the risk of complications in this vulnerable population is of great importance.

The role of dietary fiber in the prevention of CVD and cancer has received increasing attention in the community, prompting health care organizations to recommend increased dietary fiber intake (5,6). Although the biologic mechanisms explaining how fiber may protect against these outcomes have yet to be fully elucidated, epidemiologic evidence suggests that the beneficial effect of high-fiber diets is coupled with their effect on inflammation (7). A recent study from the Third National Health and Nutrition Examination Survey (NHANES III) showed that the inverse association of dietary fiber intake with inflammation and mortality risk was stronger in individuals with kidney dysfunction than in those without (8). The authors suggest that both inflammation and kidney function may be important mediators in the association between dietary fiber and mortality outcomes. Validation of this finding in other societies with different dietary habits is needed in order to substantiate and motivate preventive dietary recommendations. Therefore, this study aimed to evaluate the association between fiber intake, kidney function, inflammation, and death in Swedish community-dwelling elderly men of similar age. Within this aim, we additionally assessed possible effect modification by underlying kidney function.

Materials and Methods

Study Population

This study was performed in the Uppsala Longitudinal Study of Adult Men (ULSAM) (http://www2.pubcare.uu.se/ULSAM/). The present analyses are based on the third examination cycle of the ULSAM cohort (examinations performed during 1991–1995; n=1221), when dietary records were collected for the first time and participants were aged approximately 70–71 years (mean 70.9 ±0.5 years; range, 69.5–71.9). Exclusion criteria were unavailable data on 7-day dietary records and/or serum cystatin C (n=116), and extreme values of reported energy intake (<765 or >4300 kcal/d; n=5). This study therefore comprises 1110 participants. All participants gave written consent, and the Ethics Committee of Uppsala University approved the study.

Demographics and Comorbidities

Body mass index (BMI) was calculated as body weight in kilograms divided by the square of height in meters. Smoking was defined as current smoking versus nonsmoking. Exercise habits were self-reported according to four categories (sedentary, moderate, regular, and athletic) (9). Education level was recorded as low (elementary school), medium (secondary school), and high (university studies). Previous CVD was established from the Swedish Hospital Discharge Registry (International Classification of Diseases, Ninth Revision [ICD-9] codes 390–459 or International Classification of Diseases, Tenth Revision [ICD-10] codes I00–I99). Previous cancer diagnosis was defined as ICD-9 codes 150–250 or ICD-10 codes C00–D48. BP was measured by the Accutracker II ambulatory BP monitoring device (Suntech Medical Instruments, Raleigh, NC). Hypertension was defined as either average daytime BP from ambulatory BP monitoring ≥135/85 mmHg (10,11) or intake of antihypertensive drugs. Hyperlipidemia was defined as serum cholesterol >250 mg/dl (6.5 mmol/L), serum triglycerides >200 mg/dl (2.3 mmol/L), or treatment with lipid-lowering medications. Diabetes was defined as fasting plasma glucose ≥126 mg/dl (7.0 mmol/L), a 2-hour postload glucose level ≥200 mg/dl (11.1 mmol/L), or the use of oral hypoglycemic agents or insulin (12).

Laboratory Measurements

Serum cystatin C was measured by a latex-enhanced reagent (N Latex Cystatin C; Dade Behring, Deerfield, IL) with a Behring BN ProSpec analyzer (Dade Behring). The total analytical imprecision of the method was 4.8% at 0.56 mg/L and 3.7% at 2.85 mg/L. The eGFR was calculated from serum cystatin C concentrations (in milligrams per liter) by the following formula: eGFR = 77.24 × cystatin C−1.2623, which has been shown to be closely correlated with iohexol clearance (13). This equation was used in our primary analysis. We also used the CKD Epidemiology Collaboration (CKD-EPI) cystatin C equation to calculate the eGFR (14,15) and aimed to confirm our findings. Kidney dysfunction was defined as an eGFR<60 ml/min per 1.73 m2 according to the current Kidney Disease Outcomes Quality Initiative definition (1). C-reactive protein (CRP) measurements were performed by a latex-enhanced reagent (Dade Behring) using a Behring BN ProSpec analyzer (Dade Behring). The intra-assay coefficient of variation of the CRP method was 1.4% at both 1.23 mg/L and 5.49 mg/L. Serum CRP >3 mg/L was defined as elevated CRP according to a consensus statement of the US Centers for Disease Control and Prevention and the American Heart Association (16). IL-6 was analyzed by an ELISA kit (IL-6HS; R&D Systems, Minneapolis, MN). The interassay coefficient of variation was 5%. The urinary albumin excretion rate (UAER) was measured in one overnight urine collection (expressed in micrograms per minute). The assay utilized a commercially available RIA kit (Albumin RIA 100; Pharmacia, Uppsala, Sweden).

Dietary Assessment

Dietary habits were evaluated by a 7-day dietary record based on a validated precoded menu book, which was prepared and previously used by the Swedish National Food Administration (NFA) (17). The participants were given oral instructions by a dietitian on how to perform the dietary registration, and the amounts consumed were reported in household measurements or specified as portion sizes. The daily intakes of energy as well as macronutrients and micronutrients were calculated by using a database from the NFA. To reduce extraneous variation and predict the effect of dietary interventions, the daily intakes of macronutrients and micronutrients in this study were corrected for total energy intake by regression analysis of the residual method (18).

Follow-Up and Mortality

Follow-up for mortality was conducted, with no loss to follow-up, from the examination date until death or December 31, 2003. The Swedish National Registry recording for date and cause of death was used to define end points. During a median of 10 years (range, 0.1–12.4 years), 300 participants died. There were 138 deaths from CVD (ICD-9 codes 390–459 or ICD-10 codes I00–I99), 111 from cancer (ICD-9 codes 150–250 or ICD-10 codes C00–D48), 19 from infections (ICD-10 codes J180–K578), and 33 from other causes.

Statistical Analyses

Values are expressed as the mean±SD for normally distributed continuous variables, the median (interquartile range [IQR]) for skewed variables, or the percentage of the total for categorical variables. Study participants were divided into four groups according to quartiles of energy-adjusted dietary fiber. The Jonckheere–Terpstra test was used to assess linear trends across these groups, and the P value for trend was reported.

For comparison purposes with the NHANES III study (8), we use the same cut point of per 10 g/d higher in fiber intake. Selection of covariates was done on the basis of consideration as confounders in the association of interest. In a final step, we considered CRP adjustment as a plausible mediator. In cross-sectional analyses, multivariable linear regressions were calculated to evaluate the association of dietary fiber and kidney function (eGFR). We also performed prespecified multicategory (fiber intake quartiles) models. Three hierarchical models were investigated (an unadjusted model and two adjusted models). Model 1 considered adjustment for lifestyle factors (protein intake, age, BMI, smoking status, physical activity, and education). Model 2 further adjusted for the presence of comorbidities (CVD, hypertension, hyperlipidemia, and diabetes) and UAER. Data are expressed as regression coefficients (difference) and 95% confidence interval (95% CIs). Unadjusted and multiple adjusted logistic regressions were fitted to evaluate the association of dietary fiber with the presence of elevated serum CRP. Covariates in the adjusted models included protein intake, age, BMI, physical activity, smoking status, education, comorbidities, UAER, and eGFR. Data are presented as odds ratios and 95% CIs.

In longitudinal analysis, the association of dietary fiber with mortality was investigated with Cox proportional hazards analyses. Proportional hazard assumptions were confirmed by the Schoenfeld test. The relations between dietary fiber and mortality were investigated in unadjusted analyses and in analyses adjusted for protein intake, age, BMI, smoking status, physical activity, education, comorbidities, eGFR, and UAER (all considered confounders) as well as CRP (possible mediator). Adding CRP as a final separate step was also tested, but the intermediate model is not presented herein because the results were similar. Data are presented as hazard ratios and 95% CIs. Due to the cause of death distribution, we addressed the association between dietary fiber and both CVD- and cancer-specific deaths. Given the potential for changes in dietary habits soon after a diagnosis, we performed a sensitivity analysis that excluded deaths that occurred within 2 years of baseline (n=20).

We examined multivariable adjusted models that included interaction terms for dietary fiber (as a continuous variable) and kidney dysfunction (as a binominal variable: eGFR≥60 or <60 ml/min per 1.73 m2), and performed the analyses after stratification of individuals according to the presence/absence of kidney dysfunction. P values for interaction were reported. A P value <0.05 was regarded as significant. All statistical analyses were performed using STATA software (version 12.0; StataCorp, College Station, TX).

Results

General Characteristics

The median absolute intake of fiber was 16.3 g/d (IQR, 13.4–20.2; range, 4.9–40.8) and the energy-adjusted fiber intake was 16.8 g/d (IQR, 14.5–19.3; range, 4.8–34.7). We used energy-adjusted values as the exposure for the analyses. Clinical and biochemical characteristics are shown in Table 1 as stratified by quartiles of dietary fiber. Across increasing quartiles, participants had higher physical activity and education levels, but there was a lower proportion of smokers. eGFR was higher across increasing dietary fiber quartiles, whereas CRP and IL-6 were lower. Dietary protein, carbohydrate, sodium, and potassium intake were higher, whereas dietary fat was lower. Sodium intake was correlated with dietary fiber intake (Spearman’s ρ=0.16; P=0.001).

View this table:
  • View inline
  • View popup
Table 1.

Baseline characteristics according to quartile of dietary fiber intake (N=1110)

Dietary Fiber, eGFR, and Elevated Serum CRP

In unadjusted and adjusted linear regression models, dietary fiber positively associated with eGFR regardless of confounders (Table 2). Similar associations were observed when applying the CKD-EPI equation (Supplemental Table 1).

View this table:
  • View inline
  • View popup
Table 2.

Association of fiber intake with eGFR (N=1110)

In unadjusted logistic models, dietary fiber significantly associated with lower odds of having a state of higher CRP, which was progressively reduced after adjustment for confounders and became nonsignificant in the final model (Table 3). We also observed linear trends associating fiber quartiles with lower CRP odds. Similar associations were observed in individuals with and without kidney dysfunction. Comparable results were observed when using IL-6 as the exposure (per Log2 higher) (Supplemental Table 2). Results were confirmed when applying the CKD-EPI equation (Supplemental Table 3).

View this table:
  • View inline
  • View popup
Table 3.

Associations of fiber intake with elevated serum CRP (>3 mg/L) in the entire survey (N=1110) and after stratification for kidney dysfunction

Dietary Fiber and Mortality

Fiber intake was associated with lower all-cause and cancer-related mortality risk in unadjusted analyses, but full multivariate adjustment abrogated statistical significance (Table 4). A significant interaction product term in both all-cause and cancer mortality prediction was observed between dietary fiber and kidney dysfunction (Figure 1). After stratification, dietary fiber intake was an independent predictor of all-cause and cancer mortality in individuals with kidney dysfunction, but not in those without. Sensitivity analysis excluding deaths that occurred within 2 years from baseline (Supplemental Table 4), as well as analyses applying the CKD-EPI equation (Supplemental Table 5), showed similar results.

View this table:
  • View inline
  • View popup
Table 4.

Associations of dietary fiber with the risk of mortality (N=1110)

Figure 1.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 1.

Associations of dietary fiber (per 10 g/d higher) with all-cause, CVD, and cancer-related mortality, stratified by the presence/absence of kidney dysfunction. Data are presented are HRs and 95% CIs (error bars). Units for eGFR are ml/min per 1.73 m2. Covariates in the adjusted model include protein intake (energy adjusted), age, body mass index, smoking, physical activity, education, CVD, diabetes, hyperlipidemia, hypertension, eGFR, urinary albumin excretion rate, and C-reactive protein (cancer history was additionally included in the cancer mortality analysis). 95% CI, 95% confidence interval; CVD, cardiovascular disease; HR, hazard ratio.

Discussion

This cross-sectional study with prospective mortality follow-up in Swedish community-dwelling elderly men has three main findings. First, higher dietary fiber was associated with better kidney function. Second, higher dietary fiber was associated with markers of inflammation in minimally adjusted models. Third, higher dietary fiber was more strongly associated with survival in individuals with kidney dysfunction than in those without. The association between dietary fiber and death risk was mainly attributed to cancer.

In our study, dietary fiber was positively associated with kidney function. Supporting this concept, several studies with small sample sizes have described an association between dietary fiber intervention and reductions of BUN and an increase in fecal nitrogen excretion in patients with CKD (19–23). Serum creatinine concentration decreased and eGFR increased after 4 weeks of 16.5 g/d added fiber in 13 patients with stages 3–5 CKD (23). This study therefore expands this knowledge into the general population including elderly individuals, of which a large proportion (nearly 50%) presented kidney dysfunction. However, it should be noted that intake of protein can increase serum creatinine directly as well as indirectly, thereby increasing creatinine-based measures of GFR. Therefore, a strength in our analysis is the use of cystatin C eGFR estimations, which are presumably less influenced by this bias. Unfortunately, our cohort does not have data on urinary nitrogen excretion and serum urea nitrogen. Several potential mechanisms have been proposed for linking dietary fiber and kidney function. Dietary fiber can increase fecal bacteria mass and nitrogen excretion (24). Consumption of fiber, which increases the energy substrate available to fecal bacteria and stimulates their proliferation, could reduce serum urea by providing a fecal route of excretion for accumulated nitrogenous wastes. Both animal (25,26) and human studies (19–23) have shown that fiber supplementation increases nitrogen excretion in feces and decreases serum nitrogen. Another hypothesis is that foods with fiber are also rich in antioxidants and vitamins (27), which could also relate to or influence the associations reported here. In fact, vegetarian diets associate with decreased production of uremic toxins such as p-cresyl sulfate and indoxyl sulfate, which have been implicated in CKD progression (28). Moreover, a diet high in vegetable sources of protein might lead to lower endogenous production of acid, and a higher intake of fruits and vegetables in patients with stages 1–4 CKD yielded similar acidosis control as oral bicarbonate (29). Our observational design also allows the possibility of reverse causality (e.g., that lower fiber intake is a consequence of dietary adaptations in the context of kidney dysfunction).

The recent NHANES III study (8) reported that lower fiber intake associated with higher serum CRP levels in individuals with CKD. In our study, although dietary fiber (per 10 g/d higher) was not strongly associated with CRP in the whole survey, both CRP and IL-6 levels decreased across higher dietary fiber quartiles, but associations were similar in magnitude in both kidney function strata. We report that lower fiber intake was more strongly associated with mortality in individuals with kidney dysfunction than in those without; this association was independent of lifestyle factors, comorbidities, as well as calorie and protein intake. These data confirm the original observations from the NHANES III in an independent Northern European population and in individuals with a different dietary pattern (8), and thus may incite considerations toward dietary recommendation strategies. Our study design also offers the opportunity to analyze cause-specific deaths. Against our initial hypothesis, and in agreement with recent community studies (30), we do not observe an association with CVD-related mortality. Instead, the association between fiber and survival was mainly attributed to a lower incidence of cancer-related deaths. Although this interaction with kidney dysfunction is certainly a novel finding, the “protective” association with cancer death is in line with previous large population-based prospective community analyses (31). Several potential mechanisms have been proposed for explaining these links. Dietary fiber may increase the bulk and shorten the bowel transit, diluting the effect of potential carcinogens (32). Previous studies seem to suggest that short-chain fatty acids converted from dietary fiber by bacterial fermentation may inhibit the growth of cancer cell lines (32). In addition, lower dietary fiber may also alter the gut flora, causing dysbiosis and a state of chronic low-grade inflammation (33). Both of these aspects may be relevant in a CKD population with low fiber intake, in which dysbiosis may lead to alteration of the intestinal mucosal barrier and low-grade endotoxemia (34). Gut-derived uremic toxins such as indoxyl sulfate and inflammation are associated with higher mortality and further progression of CKD (35). Upcoming research in the field of the gut-renal axis may help elucidate the above-proposed mechanisms.

Additional strengths of our study include the relatively large, community-based sample, the prospective follow-up collection, and the use of 7-day dietary records. However, we are not exempt from limitations. Although the homogeneity of participants in this survey (same age, sex, ethnicity, and geographical distribution) may be a strength toward the study of unbiased associations, it renders a selective population that is not necessarily representative of women or individuals in other age groups. Ours is a cohort of relatively healthy individuals, attributed in part to the lower prevalence of CVD risk factors in Nordic countries and to the nature of the recruiting screening program. We did not directly measure the creatinine clearance rate but instead based our eGFR on serum cystatin C concentrations. Finally, we do not have detailed data on smoking (e.g., cigarettes per day or previous smoking history) or physical activity (other than self-reports).

High fiber intake was associated with better kidney function in community-dwelling elderly men from Sweden. Moreover, high fiber intake was more strongly associated with survival in individuals with kidney dysfunction than in those without. Further interventional studies are warranted to evaluate the effects of increasing fiber intake on kidney function and its consequences.

Disclosures

B.L. is affiliated with Baxter Healthcare Corporation.

Acknowledgments

This work was supported by grants from the Swedish Research Council. The doctoral education of H.X. is partially supported by Karolinska Institute faculty for funding of postgraduates. Baxter Novum is the result of a grant from Baxter Healthcare Corporation to Karolinska Institute.

Footnotes

  • Published online ahead of print. Publication date available at www.cjasn.org.

  • This article contains supplemental material online at http://cjasn.asnjournals.org/lookup/suppl/doi:10.2215/CJN.02260314/-/DCSupplemental.

  • Received March 3, 2014.
  • Accepted September 2, 2014.
  • Copyright © 2014 by the American Society of Nephrology

References

  1. ↵
    1. National Kidney Foundation
    : K/DOQI clinical practice guidelines for chronic kidney disease: Evaluation, classification, and stratification. Am J Kidney Dis 39[Suppl 1]: S1–S266, 2002pmid:11904577
    OpenUrlCrossRefPubMed
  2. ↵
    1. Wen CP,
    2. Cheng TY,
    3. Tsai MK,
    4. Chang YC,
    5. Chan HT,
    6. Tsai SP,
    7. Chiang PH,
    8. Hsu CC,
    9. Sung PK,
    10. Hsu YH,
    11. Wen SF
    : All-cause mortality attributable to chronic kidney disease: A prospective cohort study based on 462 293 adults in Taiwan. Lancet 371: 2173–2182, 2008pmid:18586172
    OpenUrlCrossRefPubMed
  3. ↵
    1. Meuwese CL,
    2. Snaedal S,
    3. Halbesma N,
    4. Stenvinkel P,
    5. Dekker FW,
    6. Qureshi AR,
    7. Barany P,
    8. Heimburger O,
    9. Lindholm B,
    10. Krediet RT,
    11. Boeschoten EW,
    12. Carrero JJ
    : Trimestral variations of C-reactive protein, interleukin-6 and tumour necrosis factor-α are similarly associated with survival in haemodialysis patients. Nephrol Dial Transplant 26: 1313–1318, 2011pmid:20846939
    OpenUrlCrossRefPubMed
  4. ↵
    1. Miyamoto T,
    2. Carrero JJ,
    3. Stenvinkel P
    : Inflammation as a risk factor and target for therapy in chronic kidney disease. Curr Opin Nephrol Hypertens 20: 662–668, 2011pmid:21825982
    OpenUrlCrossRefPubMed
  5. ↵
    1. King DE
    : Dietary fiber, inflammation, and cardiovascular disease. Mol Nutr Food Res 49: 594–600, 2005pmid:15884088
    OpenUrlCrossRefPubMed
  6. ↵
    1. Lattimer JM,
    2. Haub MD
    : Effects of dietary fiber and its components on metabolic health. Nutrients 2: 1266–1289, 2010pmid:22254008
    OpenUrlCrossRefPubMed
  7. ↵
    1. King DE,
    2. Egan BM,
    3. Geesey ME
    : Relation of dietary fat and fiber to elevation of C-reactive protein. Am J Cardiol 92: 1335–1339, 2003pmid:14636916
    OpenUrlCrossRefPubMed
  8. ↵
    1. Krishnamurthy VM,
    2. Wei G,
    3. Baird BC,
    4. Murtaugh M,
    5. Chonchol MB,
    6. Raphael KL,
    7. Greene T,
    8. Beddhu S
    : High dietary fiber intake is associated with decreased inflammation and all-cause mortality in patients with chronic kidney disease. Kidney Int 81: 300–306, 2012pmid:22012132
    OpenUrlCrossRefPubMed
  9. ↵
    1. Byberg L,
    2. Zethelius B,
    3. McKeigue PM,
    4. Lithell HO
    : Changes in physical activity are associated with changes in metabolic cardiovascular risk factors. Diabetologia 44: 2134–2139, 2001pmid:11793014
    OpenUrlCrossRefPubMed
  10. ↵
    1. National Clinical Guideline Centre (UK)
    : Hypertension: The Clinical Management of Primary Hypertension in Adults: Update of Clinical Guidelines 18 and 34, London, Royal College of Physicians, 2011
  11. ↵
    1. Mancia G,
    2. Fagard R,
    3. Narkiewicz K,
    4. Redon J,
    5. Zanchetti A,
    6. Böhm M,
    7. Christiaens T,
    8. Cifkova R,
    9. De Backer G,
    10. Dominiczak A,
    11. Galderisi M,
    12. Grobbee DE,
    13. Jaarsma T,
    14. Kirchhof P,
    15. Kjeldsen SE,
    16. Laurent S,
    17. Manolis AJ,
    18. Nilsson PM,
    19. Ruilope LM,
    20. Schmieder RE,
    21. Sirnes PA,
    22. Sleight P,
    23. Viigimaa M,
    24. Waeber B,
    25. Zannad F,
    26. Redon J,
    27. Dominiczak A,
    28. Narkiewicz K,
    29. Nilsson PM,
    30. Burnier M,
    31. Viigimaa M,
    32. Ambrosioni E,
    33. Caufield M,
    34. Coca A,
    35. Olsen MH,
    36. Schmieder RE,
    37. Tsioufis C,
    38. van de Borne P,
    39. Zamorano JL,
    40. Achenbach S,
    41. Baumgartner H,
    42. Bax JJ,
    43. Bueno H,
    44. Dean V,
    45. Deaton C,
    46. Erol C,
    47. Fagard R,
    48. Ferrari R,
    49. Hasdai D,
    50. Hoes AW,
    51. Kirchhof P,
    52. Knuuti J,
    53. Kolh P,
    54. Lancellotti P,
    55. Linhart A,
    56. Nihoyannopoulos P,
    57. Piepoli MF,
    58. Ponikowski P,
    59. Sirnes PA,
    60. Tamargo JL,
    61. Tendera M,
    62. Torbicki A,
    63. Wijns W,
    64. Windecker S,
    65. Clement DL,
    66. Coca A,
    67. Gillebert TC,
    68. Tendera M,
    69. Rosei EA,
    70. Ambrosioni E,
    71. Anker SD,
    72. Bauersachs J,
    73. Hitij JB,
    74. Caulfield M,
    75. De Buyzere M,
    76. De Geest S,
    77. Derumeaux GA,
    78. Erdine S,
    79. Farsang C,
    80. Funck-Brentano C,
    81. Gerc V,
    82. Germano G,
    83. Gielen S,
    84. Haller H,
    85. Hoes AW,
    86. Jordan J,
    87. Kahan T,
    88. Komajda M,
    89. Lovic D,
    90. Mahrholdt H,
    91. Olsen MH,
    92. Ostergren J,
    93. Parati G,
    94. Perk J,
    95. Polonia J,
    96. Popescu BA,
    97. Reiner Z,
    98. Rydén L,
    99. Sirenko Y,
    100. Stanton A,
    101. Struijker-Boudier H,
    102. Tsioufis C,
    103. van de Borne P,
    104. Vlachopoulos C,
    105. Volpe M,
    106. Wood DA,
    107. Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC)
    : 2013 ESH/ESC Guidelines for the management of arterial hypertension. Eur Heart J 34: 2159–2219, 2013pmid:23771844
    OpenUrlCrossRefPubMed
  12. ↵
    1. Resnick HE,
    2. Harris MI,
    3. Brock DB,
    4. Harris TB
    : American Diabetes Association diabetes diagnostic criteria, advancing age, and cardiovascular disease risk profiles: Results from the Third National Health and Nutrition Examination Survey. Diabetes Care 23: 176–180, 2000pmid:10868827
    OpenUrlAbstract
  13. ↵
    1. Larsson A,
    2. Malm J,
    3. Grubb A,
    4. Hansson LO
    : Calculation of glomerular filtration rate expressed in mL/min from plasma cystatin C values in mg/L. Scand J Clin Lab Invest 64: 25–30, 2004pmid:15025426
    OpenUrlCrossRefPubMed
  14. ↵
    1. Stevens LA,
    2. Coresh J,
    3. Schmid CH,
    4. Feldman HI,
    5. Froissart M,
    6. Kusek J,
    7. Rossert J,
    8. Van Lente F,
    9. Bruce RD 3rd.,
    10. Zhang YL,
    11. Greene T,
    12. Levey AS
    : Estimating GFR using serum cystatin C alone and in combination with serum creatinine: A pooled analysis of 3,418 individuals with CKD. Am J Kidney Dis 51: 395–406, 2008pmid:18295055
    OpenUrlCrossRefPubMed
  15. ↵
    1. Stevens PE,
    2. Levin AG,
    3. Kidney Disease: Improving Global Outcomes Chronic Kidney Disease Guideline Development Work Group Members
    : Evaluation and management of chronic kidney disease: Synopsis of the kidney disease: Improving global outcomes 2012 clinical practice guideline. Ann Intern Med 158: 825–830, 2013pmid:23732715
    OpenUrlCrossRefPubMed
  16. ↵
    1. Pearson TA,
    2. Mensah GA,
    3. Alexander RW,
    4. Anderson JL,
    5. Cannon RO 3rd.,
    6. Criqui M,
    7. Fadl YY,
    8. Fortmann SP,
    9. Hong Y,
    10. Myers GL,
    11. Rifai N,
    12. Smith SC Jr.,
    13. Taubert K,
    14. Tracy RP,
    15. Vinicor F,
    16. Centers for Disease Control and Prevention,
    17. American Heart Association
    : Markers of inflammation and cardiovascular disease: Application to clinical and public health practice: A statement for healthcare professionals from the Centers for Disease Control and Prevention and the American Heart Association. Circulation 107: 499–511, 2003pmid:12551878
    OpenUrlFREE Full Text
  17. ↵
    1. Becker W
    : Food Habits and Intake in Sweden 1989, Uppsala, Sweden, Swedish National Food Administration, 1994
  18. ↵
    1. Willett WC,
    2. Howe GR,
    3. Kushi LH
    : Adjustment for total energy intake in epidemiologic studies. Am J Clin Nutr 65[Suppl]: 1220S–1228S, discussion 1229S–1231S, 1997pmid:9094926
    OpenUrlAbstract/FREE Full Text
  19. ↵
    1. Younes H,
    2. Egret N,
    3. Hadj-Abdelkader M,
    4. Rémésy C,
    5. Demigné C,
    6. Gueret C,
    7. Deteix P,
    8. Alphonse JC
    : Fermentable carbohydrate supplementation alters nitrogen excretion in chronic renal failure. J Ren Nutr 16: 67–74, 2006pmid:16414445
    OpenUrlCrossRefPubMed
    1. Rivellese A,
    2. Parillo M,
    3. Giacco A,
    4. De Marco F,
    5. Riccardi G
    : A fiber-rich diet for the treatment of diabetic patients with chronic renal failure. Diabetes Care 8: 620–621, 1985pmid:3000714
    OpenUrlFREE Full Text
    1. Parillo M,
    2. Riccardi G,
    3. Pacioni D,
    4. Iovine C,
    5. Contaldo F,
    6. Isernia C,
    7. De Marco F,
    8. Perrotti N,
    9. Rivellese A
    : Metabolic consequences of feeding a high-carbohydrate, high-fiber diet to diabetic patients with chronic kidney failure. Am J Clin Nutr 48: 255–259, 1988pmid:2841839
    OpenUrlAbstract/FREE Full Text
    1. Bliss DZ,
    2. Stein TP,
    3. Schleifer CR,
    4. Settle RG
    : Supplementation with gum arabic fiber increases fecal nitrogen excretion and lowers serum urea nitrogen concentration in chronic renal failure patients consuming a low-protein diet. Am J Clin Nutr 63: 392–398, 1996pmid:8602598
    OpenUrlAbstract/FREE Full Text
  20. ↵
    1. Salmean YA,
    2. Segal MS,
    3. Langkamp-Henken B,
    4. Canales MT,
    5. Zello GA,
    6. Dahl WJ
    : Foods with added fiber lower serum creatinine levels in patients with chronic kidney disease. J Ren Nutr 23: e29–e32, 2013pmid:22739658
    OpenUrlCrossRefPubMed
  21. ↵
    1. Stephen AM,
    2. Cummings JH
    : Mechanism of action of dietary fibre in the human colon. Nature 284: 283–284, 1980pmid:7360261
    OpenUrlCrossRefPubMed
  22. ↵
    1. Younes H,
    2. Alphonse JC,
    3. Hadj-Abdelkader M,
    4. Remesy C
    : Fermentable carbohydrate and digestive nitrogen excretion. J Ren Nutr 11: 139–148, 2001
    OpenUrlCrossRefPubMed
  23. ↵
    1. Zervas S,
    2. Zijlstra RT
    : Effects of dietary protein and fermentable fiber on nitrogen excretion patterns and plasma urea in grower pigs. J Anim Sci 80: 3247–3256, 2002pmid:12542166
    OpenUrlPubMed
  24. ↵
    1. Pérez-Jiménez J,
    2. Serrano J,
    3. Tabernero M,
    4. Arranz S,
    5. Díaz-Rubio ME,
    6. García-Diz L,
    7. Goñi I,
    8. Saura-Calixto F
    : Bioavailability of phenolic antioxidants associated with dietary fiber: Plasma antioxidant capacity after acute and long-term intake in humans. Plant Foods Hum Nutr 64: 102–107, 2009pmid:19444613
    OpenUrlCrossRefPubMed
  25. ↵
    1. Goraya N,
    2. Simoni J,
    3. Jo C,
    4. Wesson DE
    : Dietary acid reduction with fruits and vegetables or bicarbonate attenuates kidney injury in patients with a moderately reduced glomerular filtration rate due to hypertensive nephropathy. Kidney Int 81: 86–93, 2012pmid:21881553
    OpenUrlCrossRefPubMed
  26. ↵
    1. Goraya N,
    2. Simoni J,
    3. Jo CH,
    4. Wesson DE
    : A comparison of treating metabolic acidosis in CKD stage 4 hypertensive kidney disease with fruits and vegetables or sodium bicarbonate. Clin J Am Soc Nephrol 8: 371–381, 2013pmid:23393104
    OpenUrlAbstract/FREE Full Text
  27. ↵
    1. Threapleton DE,
    2. Greenwood DC,
    3. Burley VJ,
    4. Aldwairji M,
    5. Cade JE
    : Dietary fibre and cardiovascular disease mortality in the UK Women’s Cohort Study. Eur J Epidemiol 28: 335–346, 2013pmid:23543118
    OpenUrlCrossRefPubMed
  28. ↵
    1. Chuang SC,
    2. Norat T,
    3. Murphy N,
    4. Olsen A,
    5. Tjønneland A,
    6. Overvad K,
    7. Boutron-Ruault MC,
    8. Perquier F,
    9. Dartois L,
    10. Kaaks R,
    11. Teucher B,
    12. Bergmann MM,
    13. Boeing H,
    14. Trichopoulou A,
    15. Lagiou P,
    16. Trichopoulos D,
    17. Grioni S,
    18. Sacerdote C,
    19. Panico S,
    20. Palli D,
    21. Tumino R,
    22. Peeters PH,
    23. Bueno-de-Mesquita B,
    24. Ros MM,
    25. Brustad M,
    26. Åsli LA,
    27. Skeie G,
    28. Quirós JR,
    29. González CA,
    30. Sánchez MJ,
    31. Navarro C,
    32. Ardanaz Aicua E,
    33. Dorronsoro M,
    34. Drake I,
    35. Sonestedt E,
    36. Johansson I,
    37. Hallmans G,
    38. Key T,
    39. Crowe F,
    40. Khaw KT,
    41. Wareham N,
    42. Ferrari P,
    43. Slimani N,
    44. Romieu I,
    45. Gallo V,
    46. Riboli E,
    47. Vineis P
    : Fiber intake and total and cause-specific mortality in the European Prospective Investigation into Cancer and Nutrition cohort. Am J Clin Nutr 96: 164–174, 2012pmid:22648726
    OpenUrlAbstract/FREE Full Text
  29. ↵
    1. Obrador A
    : Fibre and colorectal cancer: A controversial question. Br J Nutr 96[Suppl 1]: S46–S48, 2006pmid:16923251
    OpenUrlCrossRefPubMed
  30. ↵
    1. Ramezani A,
    2. Raj DS
    : The gut microbiome, kidney disease, and targeted interventions. J Am Soc Nephrol 25: 657–670, 2014pmid:24231662
    OpenUrlAbstract/FREE Full Text
  31. ↵
    1. Vaziri ND,
    2. Wong J,
    3. Pahl M,
    4. Piceno YM,
    5. Yuan J,
    6. DeSantis TZ,
    7. Ni Z,
    8. Nguyen TH,
    9. Andersen GL
    : Chronic kidney disease alters intestinal microbial flora. Kidney Int 83: 308–315, 2013pmid:22992469
    OpenUrlCrossRefPubMed
  32. ↵
    1. Kaczmarczyk MM,
    2. Miller MJ,
    3. Freund GG
    : The health benefits of dietary fiber: Beyond the usual suspects of type 2 diabetes mellitus, cardiovascular disease and colon cancer. Metabolism 61: 1058–1066, 2012pmid:22401879
    OpenUrlCrossRefPubMed
View Abstract
PreviousNext
Back to top

In this issue

Clinical Journal of the American Society of Nephrology: 9 (12)
Clinical Journal of the American Society of Nephrology
Vol. 9, Issue 12
December 05, 2014
  • Table of Contents
  • Table of Contents (PDF)
  • Index by author
View Selected Citations (0)
Print
Download PDF
Sign up for Alerts
Email Article
Thank you for your help in sharing the high-quality science in CJASN.
Enter multiple addresses on separate lines or separate them with commas.
Dietary Fiber, Kidney Function, Inflammation, and Mortality Risk
(Your Name) has sent you a message from American Society of Nephrology
(Your Name) thought you would like to see the American Society of Nephrology web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Dietary Fiber, Kidney Function, Inflammation, and Mortality Risk
Hong Xu, Xiaoyan Huang, Ulf Risérus, Vidya M. Krishnamurthy, Tommy Cederholm, Johan Ärnlöv, Bengt Lindholm, Per Sjögren, Juan Jesús Carrero
CJASN Dec 2014, 9 (12) 2104-2110; DOI: 10.2215/CJN.02260314

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Request Permissions
Share
Dietary Fiber, Kidney Function, Inflammation, and Mortality Risk
Hong Xu, Xiaoyan Huang, Ulf Risérus, Vidya M. Krishnamurthy, Tommy Cederholm, Johan Ärnlöv, Bengt Lindholm, Per Sjögren, Juan Jesús Carrero
CJASN Dec 2014, 9 (12) 2104-2110; DOI: 10.2215/CJN.02260314
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like

Jump to section

  • Article
    • Abstract
    • Introduction
    • Materials and Methods
    • Results
    • Discussion
    • Disclosures
    • Acknowledgments
    • Footnotes
    • References
  • Figures & Data Supps
  • Info & Metrics
  • View PDF

More in this TOC Section

Original Articles

  • Trends in Discard of Kidneys from Hepatitis C Viremic Donors in the United States
  • Availability, Accessibility, and Quality of Conservative Kidney Management Worldwide
  • Zolpidem Versus Trazodone Initiation and the Risk of Fall-Related Fractures among Individuals Receiving Maintenance Hemodialysis
Show more Original Articles

Epidemiology and Outcomes

  • Urine Kidney Injury Biomarkers and Risks of Cardiovascular Disease Events and All-Cause Death: The CRIC Study
  • Temporal and Demographic Trends in Glomerular Disease Epidemiology in the Southeastern United States, 1986–2015
  • Association between Monocyte Count and Risk of Incident CKD and Progression to ESRD
Show more Epidemiology and Outcomes

Cited By...

  • A Proinflammatory Diet Is Associated with Systemic Inflammation and Reduced Kidney Function in Elderly Adults
  • Google Scholar

Similar Articles

Related Articles

  • PubMed
  • Google Scholar

Keywords

  • CKD
  • chronic inflammation
  • GFR
  • mortality risk
  • nutrition

Articles

  • Current Issue
  • Early Access
  • Subject Collections
  • Article Archive
  • ASN Meeting Abstracts

Information for Authors

  • Submit a Manuscript
  • Trainee of the Year
  • Author Resources
  • ASN Journal Policies
  • Reuse/Reprint Policy

About

  • CJASN
  • ASN
  • ASN Journals
  • ASN Kidney News

Journal Information

  • About CJASN
  • CJASN Email Alerts
  • CJASN Key Impact Information
  • CJASN Podcasts
  • CJASN RSS Feeds
  • Editorial Board

More Information

  • Advertise
  • ASN Podcasts
  • ASN Publications
  • Become an ASN Member
  • Feedback
  • Follow on Twitter
  • Password/Email Address Changes
  • Subscribe

© 2021 American Society of Nephrology

Print ISSN - 1555-9041 Online ISSN - 1555-905X

Powered by HighWire