Chronic kidney disease (CKD) is increasingly recognised as a major global public health problem( Reference Jha, Garcia-Garcia and Iseki 1 ). Patients with CKD are at an increased risk for CVD, end-stage renal disease and all-cause mortality. Primary prevention of CKD is therefore clearly an important public health priority.

One modifiable factor that could reduce the risk of CKD may be diet. Evidence suggests that diets low in animal protein, animal fat, cholesterol and Na and high in β-carotene may be protective against renal dysfunction( 2 ). However, as the examination of nutrients only is unlikely to completely reflect health effects of diet, studying food groups may be a useful complementary approach. We recently found that coffee consumption was associated with a slightly higher estimated glomerular filtration rate (eGFR; lower eGFR may be a marker of renal damage)( Reference Herber-Gast, van Essen and Verschuren 3 ). We also found a higher low-fat dairy product consumption to be associated with less annual decline in eGFR( Reference Herber-Gast, Biesbroek and Verschuren 4 ). A link between consumption of whole grains, fruit and vegetables, for instance, and renal function may be plausible too, as these food groups have earlier been associated with type 2 diabetes and CVD, which are related to renal dysfunction( Reference Chanson-Rolle, Meynier and Aubin 5 – Reference Mellen, Walsh and Herrington 9 ). Indeed, cross-sectional findings from the Multi-Ethnic Study of Atherosclerosis (MESA) showed that higher consumption of whole grains and fruit was associated with lower albumin:creatinine ratio (ACR; greater ACR may be a marker of renal damage)( Reference Nettleton, Steffen and Palmas 10 ). These associations may partly be attributable to major components of these food groups, such as fibre, Mg, antioxidants and several B vitamins( Reference Chen, Yang and Hsiao 11 – Reference Massy and Drueke 14 ).

Until now, only two longitudinal studies reported on the associations of these food groups with indices of renal function, and their findings are inconsistent. In the Northern Manhattan Study (NOMAS), a high consumption of vegetables was associated with decreased risk of incident low (<60 ml/min per 1·73 m2) eGFR( Reference Khatri, Moon and Scarmeas 15 ). The Framingham Heart Study (FHS), however, found no associations between consumption of whole grains, fruit and vegetables and microalbuminuria (moderate increase of albumin excretion in the urine, which is a predictor of poor renal outcomes), incident low eGFR or risk of rapid eGFR decline (loss of >3 ml/min per 1·73 m2/year)( Reference Foster, Hwang and Massaro 16 ). However, both study populations comprised relatively older men and women and mostly had a mildly impaired eGFR (<90 ml/min per 1·73 m2) at baseline. Furthermore, serum creatinine was available at only two time points 10 years apart, which did not allow for accurate assessment of annual rate of renal function decline.

In the present study, we therefore aim to investigate associations between consumption of whole grains, fruit and vegetables and decline of the eGFR, in a population-based cohort of adults, with 5-yearly repeated measurements of all variables, over 15 years of follow-up. We will also study associations between consumption of these food groups and ACR. Furthermore, we will examine whether possible associations are mediated through increased fibre, Mg, antioxidant and/or B vitamins intake.

Methods

Study setting The Doetinchem Cohort Study is a Dutch prospective population-based study on factors affecting the health and well-being of Dutch adults. The first examination round (1987–1991; R1) was carried out among 12 405 men and women aged 20–59 years from the town of Doetinchem. Because of the extension of the study protocol, with similar budget, not all 12 405 participants could be re-invited. Instead, of those, a random sample of 7768 was re-invited to be examined in 1993–1997 (R2, n 6113), 1998–2002 (R3, n 4916), 2003–2007 (R4, n 4520) and 2008–2012 (R5, n 4017). The study was approved by an ethical review board, and informed consent was received from all participants. Further details of the study design have been described elsewhere( Reference Verschuren, Blokstra and Picavet 17 ).

Study population For the analysis with changes in eGFR as the outcome, we included those who responded to R2 in 1993–1997 (n 6113), because data on diet and eGFR were not available before 1993. For the analysis with ACR as the outcome, we included those who responded to R4 in 2003–2007 (n 4520), and who had ACR measured in R5 in 2008–2011, giving a total of 1929 participants. ACR data were not available before 2008 and after 2012. Pregnant women were censored at the round in which they reported to be pregnant. Furthermore, for both analyses we excluded participants as indicated in Fig. 1.

Dietary assessment Diet was assessed at R2–R4, using a self-administered semi-quantitative validated FFQ, which was developed for the European Prospective Investigation into Cancer and Nutrition study. Participants reported their usual frequency of consumption of 178 food and beverage items over the past 12 months, partially supported by coloured photographs. Consumption of food and beverage items (in g/d) and nutrient intakes were calculated using an extended version of the Dutch Food Composition database of 1996( 18 ). Total vegetable consumption included intake of chicory, endive, lettuce, spinach, cucumbers, butter beans, bell peppers, tomatoes, carrots, red beets, cabbages, mushrooms, green beans, spring beans, onions, garlic, stalk vegetables, sprouts and green peas. We did not consider potatoes as vegetables, as their nutritional value differs significantly from that of vegetables. Consumption of fruit comprised intake of applesauce, apples, pears, bananas, cherries, citrus fruits, grapes, kiwis, melons, peaches and strawberries. Fruit and vegetable juices were not included as they differ from their source of origin in terms of added sugar and food matrix( Reference Cooper, Forouhi and Ye 19 ).Unfortunately, our FFQ could not distinguish 100 % fruit and vegetable juices from other juices. Whole grains were defined as wholemeal bread, rye bread and unrefined grains (e.g. brown rice)( Reference Tabak, Smit and Heederik 20 ). The Spearman correlation coefficients for reproducibility after 12 months were 0·76 in men and 0·65 in women for vegetable intake, 0·61 in men and 0·77 in women for fruit intake and 0·86 in men and 0·85 in women for bread intake (as a proxy for whole grains)( Reference Ocke, Bueno-de-Mesquita and Goddijn 21 ). Furthermore, the validity was tested against twelve repeated 24-h recalls. Pearson’s correlation coefficients were 0·31 in men and 0·38 in women for vegetables, 0·68 in men and 0·56 in women for fruit and 0·76 in men and 0·78 in women for bread. Furthermore, the tracking coefficients covering a 15-year period were found to be moderate for whole grains (0·47), fruit (0·61) and vegetable (0·51) consumption (all P<0·001)( Reference Twisk 22 ).

Assessment of renal function In all rounds, trained staff collected 30-ml non-fasting plasma blood samples. Cystatin C was measured by particle-enhanced turbidimetric immunoassay using reagents from Gentian (Gentian), with intra-assay and interassay CV of <4·1 and 3·3 %, respectively. Serum creatinine was measured by dry chemistry (Eastman Kodak), with intra-assay and interassay CV of 0·9 and 2·9 %, respectively. All available samples for each participant from successive rounds were measured in a single run in 2012, which optimally reduced the interassay variation( Reference Vart, Bakker and Schottker 23 ). We estimated GFR using the Chronic Kidney Disease-Epidemiology (CKD-EPI) creatinine–cystatin C equation (2012), as both serum creatinine and cystatin C more accurately estimated renal function compared with models that included creatinine and cystatin C alone( Reference Inker, Schmid and Tighiouart 24 ). Annual decline of eGFR was calculated by subtracting eGFR between successive examinations and dividing by five, as each round was approximately 5 years apart. Urinary albumin and creatinine were assessed from spot urine samples obtained at R5. Albumin was measured by nephelometry, with intra-assay and interassay CV of 2·2 and 2·6 %, respectively (Dade Behring Diagnostic). Urinary creatinine was assessed by Kodak Ektachem dry chemistry (Eastman Kodak). Intra-assay and interassay CV were 0·9 and 2·9 %, respectively. ACR was determined from urinary albumin and creatinine and expressed as mg/g.

Covariates Data on socio-demographic, lifestyle, medical history of chronic diseases and medication use were collected at each round. Education was assessed as the highest level attained over follow-up and classified into low (intermediate secondary education or less), intermediate (intermediate vocational or higher secondary education) or higher (higher vocational education or university) education. Smoking status was classified as never smoker, ex-smoker or current smoker, and alcohol consumption as non-drinker, light drinker (0–4·9 g/d for both women and men), moderate drinker (5·0–14·9 g/d for women; 5·0–29·9 g/d for men) or heavy drinker (≥15·0 g/d for women; ≥30·0 g/d for men)( 25 ). Physical activity was assessed by the Cambridge Physical Activity Index score, on the basis of the frequency and total duration of activity during leisure time and work, and classified as inactive, moderately inactive, moderately active or active( Reference Wareham, Jakes and Rennie 26 ). BMI was calculated as the ratio of measured weight to height squared (kg/m2). Diabetes was defined as self-reported diabetes or a random glucose level ≥11·1 mmol. Hypercholesterolaemia was defined as non-fasting total cholesterol ≥6·5 mmol/l and/or the use of cholesterol-lowering medication. Hypertension was defined as systolic blood pressure ≥140 mmHg, and/or diastolic blood pressure ≥90 mmHg, and/or the use of antihypertensive medication. Low-fat dairy products were defined as milk and milk products with a fat concentration <2 g/100 g. Coffee intake was measured in cups per day and intake of nuts was measured in g/d. Intake of antioxidants comprised vitamin C, vitamin E, β-carotene, lutein, flavonoids and lignans, and was computed as described previously( Reference Nooyens, Milder and van Gelder 27 ). A standardised z score for all antioxidants was constructed at each round, on the basis of the means and standard deviations of intakes at baseline. Standardised z scores were then summed to calculate daily total intake of antioxidants. The B vitamins included B 1 , B 2 , B 3 and B 6 , and a total vitamin B composite variable was constructed for each round (mg/d). Supplemental intakes of vitamin C, vitamin E, B complex and multi-vitamins were assessed based on questionnaire data (self-report).