Central obesity associates with renal hyperfiltration in the non-diabetic general population: a cross-sectional study

The prevalence of obesity, defined as a body mass index (BMI) ≥ 30 kg/m², has increased rapidly in high-income nations over the last few decades and is steadily growing in many lower-income countries as well [1]. Obesity is a well-known risk factor for cardiovascular disease, hypertension and diabetes [2, 3]. These diseases are, in turn, well-established risk factors for chronic kidney disease (CKD) and end-stage renal disease (ESRD) [4‐7]. However, there is also evidence of a direct causal connection between obesity and ESRD, independent of hypertension and diabetes [8, 9].

Renal hyperfiltration (RHF), or an abnormally high glomerular filtration rate (GFR), has been postulated to represent an early stage in the development of CKD [10], most clearly observed in diabetic nephropathy [11]. RHF is also associated with several established CKD risk factors, including hypertension [12, 13] and smoking [14, 15]. A large longitudinal study by Park et al. of 43,503 Korean health screening participants found that a RHF definition based on eGFR was associated with all-cause mortality, even when adjusted for age, sex, muscle mass, diabetes and hypertension [16]. Although several studies have been conducted on the relationship between obesity and RHF [17‐25], it remains unclear whether these two conditions are also associated in the general non-diabetic population. The most important reason has been that there is currently no consensus on the definition of the term “hyperfiltration”. Most investigators who defined RHF in their studies used a single GFR cut-off point and adjusted their definition for no other variable than body surface area (BSA) [26]. Although there is no generally accepted way of defining RHF, it has been suggested that the definition should use age and sex-specific cut-offs and also some measure of correction for body size [26, 27].

Another methodological problem has been that previous epidemiological studies used GFR estimates based on creatinine and cystatin C, rather than GFR measurements [21‐25]. Estimated GFR is inaccurate for high-range GFR [28‐30] and can be confounded by associations with non-GFR-related factors [31, 32]. Studies on obesity and RHF using measured GFR (mGFR) have been limited by small sample sizes [17‐19] and the lack of adjustment for confounding variables [20].

In the Renal Iohexol Clearance Survey in Tromsø 6 (RENIS-T6), we measured GFR with iohexol clearance in 1627 middle-aged subjects from the general population. The aim of the present study was to examine the relationship between obesity and two alternative definitions of RHF.

In this study of non-diabetic, middle-aged subjects from the general population, higher WHR, but not BMI or WC, was consistently associated with RHF, regardless of the RHF definition used. This finding suggests that excessive abdominal fat stores, as opposed to excess body weight distributed more evenly in the body, may potentially be more harmful to kidney function.

Most previous RHF studies with mGFR have found a positive relationship between BMI and RHF that disappears upon the adjustment of GFR to BSA [17‐20]. The indexing of GFR to 1.73 m² of BSA may be problematic in itself, particularly in the abnormal body sizes encountered when studying obese subjects [41]. Kwakernaak et al. found that the WHR predicted a lower BSA-adjusted mGFR when adjusted for BMI, age, sex and BP [18]. However, the sample size was small and consisted of kidney donors and volunteers, who may not be representative of the general population. Pinto-Sietsma et al. made a similar finding of higher WHR associated with lower GFR in a larger population, but the result was based on GFR estimated by creatinine clearance [22].

The hypothesis of hyperfiltration as a precursor to overt CKD, originally proposed by Brenner, is based on hyperfiltration in individual glomeruli [10]. Because it is not possible to measure single-nephron GFR directly in living humans, an indirect measure of hyperfiltration based on whole-kidney GFR must be used in epidemiological studies. Whole-kidney GFR is a function of single-nephron GFR and the total number of nephrons. Nephron numbers vary by gender and birth weight and decrease with age [42], and adult height has been shown to correlate with birth weight [43]. Thus, gender, height and age were included in both the RHF definitions (Table 1). RHF_Height used the age-, sex- and height-specific 90th percentile, and because an individual’s normal body weight is correlated with height, it provides an indirect adjustment for a theoretical “normal” body size. RHF_Height is thus defined as excessive GFR relative to the mean GFR for a person with “normal” body weight. Because GFR increases with increasing body weight and increasing metabolic needs [44], it follows that RHF_Height is associated with measures of obesity, as shown in Table 3. However, when body weight was added as an independent variable to the same RHF_Height logistic regression models as in Table 3, the results were attenuated but remained essentially similar (Additional file 1: Table S3), indicating that an obese figure is associated with hyperfiltration independently of the effect of weight itself.

Another way to correct for interindividual variation in weight is to include weight in the definition of hyperfiltration, as in RHF_{Weight/height}. RHF_{Weight/height} accordingly defines hyperfiltration as excessive GFR relative to the mean GFR for persons with a given height and weight, whether obese or not. This definition may underestimate hyperfiltration in obese subjects, and RHF_{Weight/height} can be viewed as more conservative than RHF_Height. The association of WHR with hyperfiltration even when using RHF_{Weight/height} is a strong indicator that central obesity also entails hyperfiltration at the glomerular level.

The merits of different body size measurement methods in the context of epidemiological research and risk estimates for disease have been debated, as have the merits of various cut-off points [38]. BMI has become the dominant measure of obesity, partly due to its well-established association with several obesity-related diseases and partly due to the near-universal availability of height and weight as variables in both large population studies and general clinical practice. WHR, which measures body fat distribution rather than absolute body size, has been shown to be at least equal to, and often better than, BMI as a predictor for obesity-related disease including CKD [22, 45‐47].

The mechanisms of the adverse renal effect of abdominal adiposity are not fully understood, but some effects are known. The most severe and well-established mediators are increased risks of diabetes mellitus, hypertension and dyslipidemia [48‐50]. The effects of metabolic risk factors can be observed in our results, with a gradual attenuation of the odds ratio for RHF when variables for an unhealthy lipid profile and insulin resistance were included in the regression analyses.

Additionally, some other mechanisms are known, including dysfunction in the renin-angiotensin-aldosterone system, increased tubular sodium reabsorption, and the effects of obesity-related hormones and cytokines such as leptin, adiponectin and Tumor Necrosis Factor-α [48‐50].

Weight loss interventions, especially bariatric surgery, have been shown to reduce GFR in hyperfiltrating obese subjects [51]. However, most studies of such interventions have been small, and few studies have been published on long-term effects beyond the first 2 years after the interventions. A recent study by Zingerman et al. suggested a possible reversal of RHF in obese patients using acetazolamide, although the study did not include a placebo arm [52].

The strength of the present study lies in the measurement of GFR with a gold-standard method in a large, representative, mostly healthy cohort in an age group susceptible to early stages of chronic diseases. To our knowledge, this is the largest cohort from the general population that has been studied using precise GFR measurements. The exclusion of subjects with diabetes, cardiovascular disease and renal disease from the study population allowed us to focus on the preliminary stages of potential future CKD with less confounding from these high-risk patient groups. These groups would have been more likely to have passed the transient stage of hyperfiltration into a state of normal-range GFR, perhaps accompanied by slight albuminuria.

There are several limitations to this study. First, it was a cross-sectional study and thus could not prove causation, only correlation. Second, the study population was exclusively Caucasian and middle-aged, which may limit the transferability of findings to other population groups. Furthermore, while GFR was measured with a gold standard method, obesity was measured indirectly with anthropometric data, and not directly with gold standard dual energy X-ray absorptiometry, computed tomography or magnetic resonance imaging methods. Glucose and HbA1c were only measured once to exclude diabetes, while regular clinical practice requires two measurements for the diagnosis.

We conclude that the WHR is associated with RHF, independently of other risk factors and even using RHF_{Weight/height,} a conservative, body size-adjusted RHF definition. Longitudinal studies are needed to explore whether RHF predicts future non-diabetic CKD. Further studies on whether the WHR predicts CKD better than other obesity measurements are also warranted.