Saudi Journal of Kidney Diseases and Transplantation

ORIGINAL ARTICLE
Year
: 2014  |  Volume : 25  |  Issue : 4  |  Page : 793--800

Variation of body fat percentage with special reference to diet modification in patients with chronic kidney disease: A longitudinal study


Neha Srivastava1, Rana Gopal Singh1, Kumar Alok2, Shivendra Singh1,  
1 Department of Nephrology, Department of Community Medicine, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India
2 Division of Biostatistics, Department of Community Medicine, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India

Correspondence Address:
Neha Srivastava
Department of Nephrology, Institute of Medical Sciences, Banaras Hindu University, Varanasi
India

Abstract

Visceral adiposity causes hypertension, hyperglycemia and dyslipidemia. This study was conducted to evaluate whether a correlation exists between body fat percentage (BFP) of chronic kidney disease (CKD) patients and their dietary intake. In this hospital-based, quasi-experimental study, 135 incident cases of CKD were included, of whom 76 completed the study. The patients included were aged 18 years and above and had a body mass index (BMI) between 18 and 25 kg/m [2] , had CKD of any etiology and serum creatinine of up to 5 mg/dL. Patients with acquired immunodeficiency syndrome, active hepatitis B or C, malignancy, previous kidney transplantation, current participation in any trial, diabetes mellitus and those who were on dia­lysis were excluded. The study patients were put on a diet of 25-30 kcal/kg/day, with 60% of the calories coming from carbohydrates and 20% each from protein and fat. Assessment was made at baseline (BL) and at 12 months (TM) for anthropometric parameters, skin-fold thickness, nutri­tional parameters, serum albumin and dietary intake (3-day dietary record) and clinical charac­teristics. No significant change was seen in BFP, waist circumference (WC) and BMI at BS and at TM. There was significant improvement in serum albumin (P <0.05) and e-GFR (P <0.01) while CRP was elevated both at BL and TM. The dietary intake was within the prescribed limit, with significant improvement in energy intake between BS and TM (P <0.05). The intake of delta dietary protein and fat positively correlated with delta e-GFR (P <0.001). There was a significant association between change in BFP and change in BMI (P <0.005). During follow-up, there was no significant change in biochemical parameters and BFP as well as stage of CKD of the study patients. This study supports the fact that dietary counseling is an important part of treatment in patients with CKD.



How to cite this article:
Srivastava N, Singh RG, Alok K, Singh S. Variation of body fat percentage with special reference to diet modification in patients with chronic kidney disease: A longitudinal study.Saudi J Kidney Dis Transpl 2014;25:793-800


How to cite this URL:
Srivastava N, Singh RG, Alok K, Singh S. Variation of body fat percentage with special reference to diet modification in patients with chronic kidney disease: A longitudinal study. Saudi J Kidney Dis Transpl [serial online] 2014 [cited 2022 Nov 28 ];25:793-800
Available from: https://www.sjkdt.org/text.asp?2014/25/4/793/135008


Full Text

 Introduction



Many non-communicable, lifestyle-related di­seases such as diabetes mellitus (DM), obesity, hypertension (HTN), cardiovascular disease (CVD) and chronic kidney disease (CKD) have shown an increasing prevalence recently, even in developing countries. It may be attri­buted to the changing demographics, increasing affluence and sedentary lifestyles. It is estimated that 80% of deaths due to chronic disease occur in low- and middle-income countries. [1]

CKD is an important disease in this group; apart from progression to end-stage renal di­sease (ESRD), it is also considered an impor­tant risk factor for CVD. [2],[3] The Seventh Report of the Joint National Committee on Preven­tion, Detection, Evaluation and Treatment of High Blood Pressure (JNC-7) guidelines re­commend that glomerular filtration rate (GFR) <60 mL/min/1.73 m [2] or the presence of micro-albuminuria (MAU) is considered as equiva­lent to having associated CVD. [4] In the absence of a proper registry and paucity of population-based studies, the exact prevalence of CKD in India is not known. Based on data from major tertiary care centers, the presumptive estimate of incidence of ESRD in India is 100 per million population (PMP). [5]

Protein energy malnutrition (PEM) is com­mon among patients with renal failure. Mal­nourished individuals develop certain physio­logical dysfunctions. Because health risks are associated with abnormal amounts of body fat on either end of the scale (thinness or obesity), assessment of total body composition and re­gional body fat distribution is of prime concern to health professionals. Assessment of body composition has several applications, such as identifying health risk associated with exces­sively low or high levels of total body fat. Monitoring changes in fat mass (FM) and fat-free mass (FFM) helps in understanding energy metabolism as well as various diseases that alter body composition. This can lead to the development of more effective nutritional intervention strategies to counteract loss of FFM associated with malnutrition, aging, injury and certain diseases like ESRD. [6],[7],[8],[9] The objective of this study is to find a correlation between body fat percentage (BFP) and dietary intake among patients with CKD.

 Subjects and Methods



Study design and population selection

This is a hospital-based, quasi-experimental study aimed at following clinically stable CKD patients in stages 3, 4 and 5 for one year, bet­ween July 2010 and June 2011. The study pa­tients were receiving treatment at the Nephro-logy Department of Sir Sundar Lal Hospital, Banaras Hindu University, Varanasi.

Inclusion criteria

The inclusion criteria were age 18 years and above, body mass index (BMI) between 18 and 25 kg/m [2] , CKD due to any cause other than diabetes and serum creatinine not above 5 mg/dL.

Exclusion criteria

Patients with acute inflammatory illnesses, acquired immunodeficiency syndrome, active hepatitis B or C, malignancy, previous kidney transplantation, current participation in any drug trial, age less than 18 years, patients with diabetic mellitus and those on dialysis were not included in the study.

Dietary protocol

All patients were advised to restrict their protein intake to 0.6 g/kg/day, with 50% pro­tein being of high biological value, i.e., protein from animal sources. The total calorie intake was fixed at 25-30 kcal/kg/day (KDOQI guide­lines, 2000). Twenty percent of the calories were derived from fat, of which visible fat was limited to 10-15 g, and should be unsaturated in nature, i.e., of vegetable origin. [10] About 60% of the total calorie intake was from car­bohydrates, comprising mostly complex carbo­hydrates.

Patients were followed-up for one year, and only those who completed a minimum of six months of follow-up were included in the study. Of 135 patients being followed-up at the CKD outpatient clinic and meeting the inclusion criteria, 76 completed the study.

Ethical clearance

The protocol of the study was approved by the Ethics Committee of the Institute of Medical Sciences, Banaras Hindu University, Varanasi, and all the patients gave written consent before participation in the study.

 Methods



Data collection

Patients were assessed at the beginning of the study and again after 12 ± 2 months, collecting clinical, anthropometric and nutritional data at both times (in between a regular 3-monthly follow-up was performed). Demographic data were collected only at baseline (BL). All anthropometric measurements and the 24 h food recall and 3-day diet diary were per­formed by a trained dietician.

Anthropometric data

Anthropometric parameters included the fol­lowing: Body weight, height, arm circumfe­rence, skin-fold thickness (SKF) of the triceps, biceps, sub-scapular and supra iliac areas and waist circumference (WC). Body weight was measured using a personal weighing machine (beam-balanced scale); before taking the mea­surement, the machine was placed on a leveled surface and set at zero. Subjects were asked to stand straight, relaxed and with minimum clo­thing. Height of the subjects was taken in the standing position, without footwear, and recor­ded to the nearest 0.5 cm.

The BMI was calculated as body weight (kilo-grams)/height [2] (meters). Standard ideal body weight was calculated using Broka's index (height in cm-100). SKF was measured on the right hand side, using Harpenden Skinfold calipers; all measurements were taken nearest to 0.50 mm. WC was measured at the umbi­lical level by using a flexible plastic tape with a graduated scale to the nearest 0.1 cm. Because SKF cannot be accurately measured in over-weight/obese patients, those with BMI ≥25 kg/m [2] had their body fat assessed accor­ding to the validated equation of Weltman et al, [11],[12] which uses WC, body weight and height in the following equation: in males: body fat % = [0.31457 × waist circumference (cm)] -[0.10969 × body weight (kg)] + 10.8336; in females: body fat % = [0.11077 × waist circumference (cm)] - [0.17666 × height (cm)] + [0.14354 × body weight (kg)] + 51.03301.

For patients with BMI <25 kg/m [2] , body fat was estimated by the sum of SKF according to Durning Wormersley [13] and then BFP was cal­culated using Siri's equation. [14]

Dietary assessment

Dietary assessment was performed using 24-h dietary recall and 3-day diet diary. Standard-sized measuring utensils (glass, bowl and dif­ferent circled sized paper board like chapatti) were used. Different types of fat and protein sources being included in the diet were assessed. The values of various nutrients were calculated according to the description of Gopalan, 1971 (revised edition, 1989). [15]

Laboratory parameters

Biochemical parameters such as serum crea-tinine (alkaline picrate method), cholesterol (enzymatic end-point method), triglyceride (GPO-PAP method), albumin (bromocresol-green end-point method) and hemoglobin (Draft king method) were tested by a fully automated analyzer (RFCL, Flexor - XL). The GFR based on age, weight and creatinine was calculated separately for males and females by using the Cockroft-Gault equation given be­low. GFR greater than or equal to 120 was considered as normal.

GFR for males = [(140 age) × weight)/(72 × creatinine (mg/dL)]; GFR for females = [(140-age) × weight)/(72 × creatinine (mg/dL)] × 0.85.

 Statistical Analysis



Data are shown as mean ± SD for the varia­bles studied. The changes in dietary protein, fat, carbohydrate intake, BFP, BMI, WC, cho­lesterol, triglyceride, albumin, CRP and e-GFR were calculated as the difference between the measurements at 12 months (TM) and at BL. In order to establish the degree of association between changes in dietary intake (protein, fat, carbohydrate and energy) and changes in BFP, cholesterol, triglyceride, albumin, e-GFR, C-reactive protein (CRP), WC and BMI, a univa-riate analysis was performed (Pearson's test). The normality of the data was checked using the P-P plot; in this, the data points will all fall close to the ideal diagonal line. Further, the Kolmogorov Smirnov test was conducted for checking the normality of the data, and the test result was found to be non-significant; this means that the distribution of the sample was not significantly different from the normal distribution. Finally, multiple regression ana­lysis was carried out to observe the effect of dietary modification along with other potential confounders on the BFP, taken as a dependant variable. Four models were fitted containing different variables of interest. In each of the four models, the potential confounders (age, BMI, WC, e-GFR and CRP) were nested with diffe­rent categories (protein, fat, carbohydrate and energy) of dietary intake. The statistical ana­lyses were performed using SPSS version 16.

 Results



Baseline characteristics

Patients were mostly in the age range of 40- 70 years; 37 males and 39 females were inclu­ded in the study. The mean BMI (21.42 ± 4.36 years), WC (males: 76.52 ± 12.02 cm and fe­males: 74.17 ± 18.23 cm) and BFP (males: 19.2 ± 6.53, females: 26.2 ± 5.8) was indi­cative of normal weight subjects. The mean e-GFR (23.09 ± 10.28) was indicative of patients at CKD stage-4, and the mean CRP level was 7.69 ± 8.77.

Follow-up characteristics

[Table 1] compares the clinical characteristics and the nutritional parameters at BL and at 12 months of follow-up in the study patients. Thirty-seven males and 39 females completed the 12 months of follow-up. The dietary intake was within the recommended range for the patients. [16] The mean BMI (21.7 ± 3.6) and WC (males: 77.52 ± 10.76, females: 74.54 ± 18.71) did not change significantly at 12 months.{Table 1}

The mean BFP changed significantly in males (17.06% ± 6.47; P <0.05), but was within the normal weight category according to WHO-2004; [17] in females, there was no significant change (23.41% ± 8.05). Serum albumin levels improved from BL (3.89 ± 0.683) to follow-up (4.02 ± 0.716), and the increase was statis­tically significant (P <0.05). The e-GFR im­proved significantly (29.07 ± 13.24; P <0.001), but remained in the range of stage-4 CKD. Serum cholesterol (166.33 ± 47.95) and CRP (7.79 ± 8.93) did not change significantly du­ring follow-up, while the serum triglyceride levels increased significantly (123.52 ± 56.92; P <0.05). The mean hemoglobin level improved from 9.9 ± 2.14 at the start of the study to 10.31 ± 2.51 at the end of the study, although the change was not statistically significant.

Univariate analysis and multivariate asso­ciations

Univariate analysis showed a significant positive change in delta energy and delta BMI (P <0.05). Delta dietary protein and fat intake positively correlated with change in e-GFR, and there was a significant positive change in energy intake and e-GFR (P <0.001) [Table 2]. Multiple regression analysis was carried out [Table 3]. In all the four models, which were adjusted for age, BMI, WC, e-GFR and CRP, there was a significant association between changes in BFP and change in BMI (P <0.05).{Table 2}{Table 3}

 Discussion



CKD is a state of micro-inflammation; [18] apart from the uremic milieu, visceral fat is also a contributor to inflammation, as shown in various studies. [19],[20] Many studies suggest that visceral fat loss is an important contributor to the re­duction of inflammatory biomarkers. [21] Deposi­tion of abdominal fat in CKD patients is linked to both inflammation and protein energy was­ting (PEW), resulting in an increase of morta­lity and morbidity. Additionally, the difference in regional fat deposition may have different implications on patients. [22] Micro-inflammation in CKD, along with uremic symptoms, leads to PEW and malnutrition; these two relatively common and concurrent conditions in CKD patients have been considered as the main cause of the worsening atherosclerotic CVD in the CKD population. [23] Studies support the concept that interventions aimed at reducing weight and/or abdominal adiposity in pre-dialysis CKD patients may also translate into reduced systemic inflammation. [24] Reports ad­dressing the longitudinal association between changes in inflammatory markers and changes in body fat markers are important to motivate a clinical role of strategies aimed at losing body fat and body weight as a way to diminish or ameliorate the overall state of chronic inflam­mation present in CKD patients. [25] Secondary analysis of data from the Modification of Diet in Renal Disease (MDRD) study showed that tight control of blood pressure and modifi­cation of protein in the diet (0.6 g/kg/day with a GFR <25) helped delay progression by as much as 41%. [26] The distribution of the remai­ning non-protein calories should embrace car­diovascular health principles. Cardiovascular disease is accelerated in CKD, and all patients are considered at high risk. More than 50% of stage-5 CKD patients die from cardiovascular events. Decreasing the intake of saturated fat and increasing the intake of "good" fats as well as supporting other dietary interventions in combination with lifestyle changes such as moderate physical activity should be encou­raged. Pharmacological treatment may become necessary to reduce risk. [27] Based on these observations, dietary intervention is required to avoid PEW and malnutrition without an increase in BFP and to reduce micro-inflam­mation in CKD patients. [21] A balanced diet comprising of adequate energy, low fat and very low carbohydrate is associated with a significant decrease in several biomarkers of inflammation. [21]

In this study, a protein intake of 0.6 g/kg/day was recommended to the subjects in a diet comprising 25-30 kcal/kg/day, and progres­sion of disease was assessed at 12 months. At 12 months, we observed that there was a statis­tically significant increase in albumin and e-GFR, markers of nutrition and kidney func­tion. Albumin and cholesterol remained within normal levels, indicating no PEW among the subjects. [28] The CRP was elevated both at BL as well as after 12 months, and no significant change in the levels was seen. All the study patients had normal BMI, WC and BFP at 12 months.

In this study, annual change in GFR posi­tively correlated with change in dietary protein and energy intake; such a relationship has been reported earlier in a cross-sectional study. [29] In patients with CKD, dietary protein and energy intake as well as serum and anthropometric measures of protein nutritional status pro­gressively decline as the GFR decreases. In the present study, on multiple regression analysis, after adjusting for age, BMI, WC, e-GFR and CRP, the difference in the BMI positively and significantly correlated with the difference noted in BFP. In another study, a significant association was found in non-diabetic stage 3- 4 CKD patients, between BMI and fat mass with insulin resistance; this aspect needs to be studied in greater detail. [30]

In other studies on healthy Asian subjects, it has been shown that the relationship between BMI and BFP is age- and sex-dependent, [31],[32] and the relationship may differ between ethnic groups. [33],[34],[35]

Thus, dietary counseling regarding the amount of calories required from carbohydrate, fat and protein, and the quality of carbohydrate, fat and protein do have a role in retarding the pro­gression of CKD. One strength of this study was the use of two indicators of adiposity: Total BFP and central adiposity, and the com­parison of these indicators with dietary intake of the subjects.

 Conclusion



This study supports the fact that dietary coun­seling is an important part of treatment of CKD patients to avoid PEW and increase in visceral fat, one of the important markers of inflammation. During the follow-up study of 12 months, there was no significant change in biochemical parameters, BFP and stage of the patients with CKD.

 Acknowledgment



The authors are thankful to the patients who cooperated in this study for their help and consent.

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