Introduction
The prevalence of treated end-stage renal disease (ESRD) has steadily increased from 2001 to 2014 in all countries, and become a burden to every nation and healthcare system [
1]. In 2014, the prevalence of ESRD patients undergoing dialysis in Taiwan was 3093 patients per million population, about 90% of them receiving in-center hemodialysis treatment [
1]. It was summarized that nutritional factor was implicated as a risk factor for the development of metabolic in chronic kidney disease, especially in ESRD patients [
2].
Nutritional therapy is recognized as an effective approach to prevent metabolic abnormalities and unfavorable outcomes in people with chronic conditions [
3‐
8]. Increased dietary energy intake is mentioned in the National Kidney Foundation-Kidney Disease Outcomes Quality Initiative (K/DOQI) guidelines [
9]. It is recommended that consuming enough energy daily guarantees the nitrogen balance and prevents protein catabolism and tissue destruction, which could optimize the nutritional status and hemodialysis outcomes [
9]. However, the daily intake of macro-nutrients and micro-nutrients are largely inadequate in hemodialysis patients [
10]. More than a half of hemodialysis patients had problems to follow the healthy diet guidelines (related to energy and nutrients intakes) which related behaviors, technical difficulties, physical conditions, time, and food preparation [
11]. Inadequate dietary intake is also a possible result of a significant lifestyle change while receiving dialysis treatment. On the other hand, adherence to a complicated and restrictive dietary intake further exacerbates nutrient deficits in this group of patients [
9,
12‐
14].
The prevalence of metabolic syndrome was high in the ESRD patients undergoing hemodialysis [
15]. The MetS has been implicated as a risk factor for the development of diabetes, cardiovascular disease, cancer, and all-cause mortality [
16‐
19]. The prevalence of metabolic syndrome varied by different assessment criteria, e.g. 51%, 66.3%, and 75.3% according to National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III), International Diabetes Federation (IDF), and Harmonizing the Metabolic Syndrome (HMetS) criteria, respectively [
20]. This indicated that there was not yet a single definition that could reflect the real spectrum of the epidemiology of MetS. Therefore, in the current study, two definitions were used with different focuses to assess the MetS: The American Association of Clinical Endocrinologists (AACE) definition, focused on hyperglycosemia, was glucocentric [
21]; and Harmonizing Metabolic Syndrome definition was agreed by Joint statement from the IDF, American Heart Association (AHA) and the National Heart, Lung, and Blood Institute (NHLBI), the World Heart Federation, the International Atherosclerosis Society, and the International Association for the Study of Obesity, which relayed on collection of abdominal obesity and related CVD risk factors [
22].
There were few studies investigated dietary intake among hemodialysis patients. One study compared the dietary intake status between 54 HD patients, and 47 non-HD patients, and between dialysis day and non-dialysis day among elderly people in Brazil [
23]. The other study in the United States only examined the association between dietary energy intake and body composition changes in 13 HD patients [
24]. In addition, the dietary approach was found as an effective therapy to decrease most of the risks for MetS in a randomized controlled trial [
25]. However, hemodialysis patients were with high metabolic syndrome prevalence, and generally have difficulties achieving recommended energy intakes. In our knowledge, the role of dietary energy intake on metabolic disorders among hemodialysis patients remains to be investigated.
This study was to examine the association of inadequate dietary energy intake with metabolic abnormalities and metabolic syndrome among patients who receiving hemodialysis treatment from seven hemodialysis centers. It was hypothesized that hemodialysis patients with reported inadequate dietary energy intake (IDEI) more likely had metabolic abnormalities or metabolic syndrome.
Results
The mean ± SD of age, hemodialysis vintage, physical activity, CCI, and interdialytic weight gains were 59.4 ± 11.3, 5.5 ± 5.0, 4831.3 ± 1893.1, 4.6 ± 1.5, and 3.0 ± 1.7, respectively. Of study sample, there were 64.9% men, 38.2% diabetes, 48.2% hypertension, and 29.8% cardiovascular diseases, 28.5% with an elevated level of hs-CRP, 54.5% elevated body fat mass. The REE was lower in patients with inadequate EI (1014.5 ± 280.4) than those with adequate EI (1100.9 ± 274.7), with
p = 0.023. Regarding metabolic abnormalities, the prevalence of IFG, overweight or obese, elevated WC, high BP, high TG, and low HDL-C were 64.9%, 36.4%, 26.3%, 81.6%, 39.0%, and 61.0%, respectively. The prevalence of metabolic syndrome was 63.2% as diagnosed by AACE criteria, and 53.9% as diagnosed by HMetS criteria. The prevalence of the metabolic abnormalities (not hypertension) and syndromes were statistically significantly higher in hemodialysis patients with inadequate EI than those who with adequate EI (Table
1). Out of patients, 60.5% reported less than the recommendation level of dietary energy intake. Patients with inadequate EI more likely consumed inadequate protein and fat, but consumed less mineral, water, and vitamin than those with adequate EI (Table
2).
Table 1
Characteristics, and metabolic parameters, and other biochemical values in hemodialysis patientsa
Characteristics |
Age, years | 59.4 ± 11.3 | 59.9 ± 10.8 | 59.1 ± 11.6 | 0.630 |
Gender, male | 148 (64.9) | 57 (63.3) | 91 (65.9) | 0.687 |
Hemodialysis vintage, years | 5.5 ± 5.0 | 6.9 ± 5.9 | 4.5 ± 4.0 | < 0.001 |
CCI | 4.6 ± 1.5 | 4.7 ± 1.5 | 4.5 ± 1.6 | 0.327 |
Diabetes mellitus | 87 (38.2) | 24 (26.7) | 63 (45.7) | 0.004 |
Hypertension | 110 (48.2) | 45 (50.0) | 65 (47.1) | 0.669 |
Cardiovascular diseases | 68 (29.8) | 26 (28.9) | 42 (30.4) | 0.803 |
Physical activity, MET score | 4831.3 ± 1893.1 | 4984.9 ± 2033.2 | 4732.6 ± 1798.1 | 0.330 |
Height, cm | 162.4 ± 8.3 | 161.4 ± 7.0 | 163.0 ± 9.0 | 0.149 |
Weight, kg | 61.4 ± 12.3 | 55.1 ± 8.9 | 65.4 ± 12.6 | 0.000 |
IDWG, % | 3.0 ± 1.7 | 2.9 ± 2.0 | 3.1 ± 1.5 | 0.227 |
FM, % | 27.2 ± 10.0 | 23.4 ± 9.1 | 29.7 ± 9.9 | < 0.001 |
Elevated FM | 122 (54.5) | 34 (38.2) | 88 (65.2) | < 0.001 |
REE, kcal/day | 1048.6 ± 280.8 | 1100.9 ± 274.7 | 1014.5 ± 280.4 | 0.023 |
Metabolic abnormalities |
FPG | 105.3 (90.5, 145.2) | 97.3 (90.3, 134.0) | 114.0 (93.6, 153.8) | 0.025 |
IFG | 148 (64.9) | 47 (52.2) | 101 (73.2) | 0.001 |
BMI, kg/m2 | 23.2 ± 3.8 | 21.1 ± 2.6 | 24.5 ± 3.9 | < 0.001 |
BMI ≥ 24 (kg/m2) | 83 (36.4) | 13 (14.4) | 70 (50.7) | < 0.001 |
WC, cm | 81.1 ± 10.4 | 75.7 ± 7.5 | 87.6 ± 36.4 | 0.002 |
Elevated WC | 60 (26.3) | 8 (8.9) | 52 (37.7) | < 0.001 |
TG, mg/dL | 115.0 (82.9, 202.6) | 99.1 (78.0, 155.4) | 136.8 (85.0, 250.5) | 0.004 |
High TG ≥ 150 (mg/dL) | 89 (39.0) | 27 (30.0) | 62 (44.9) | 0.024 |
HDL-C, mg/dL | 41.6 ± 22.1 | 45.8 ± 21.0 | 38.9 ± 22.4 | 0.021 |
Low HDL-C | 139 (61.0) | 47 (52.2) | 92 (66.7) | 0.029 |
SBP, mmHg | 146.5 ± 22.7 | 149.5 ± 24.0 | 144.3 ± 21.3 | 0.089 |
DBP, mmHg | 80.0 ± 18.2 | 79.8 ± 19.0 | 79.9 ± 17.6 | 0.959 |
High BP | 186 (81.6) | 73 (81.1) | 113 (81.9) | 0.883 |
AACE-MetS d | 144 (63.2) | 46 (51.1) | 98 (71.0) | 0.002 |
HMetSe | 123 (53.9) | 33 (36.7) | 90 (65.2) | < 0.001 |
Other biochemical values |
TC, mg/dL | 168.3 ± 37.9 | 163.8 ± 33.7 | 170.7 ± 40.0 | 0.178 |
TC ≥ 200 mg/dL | 39 (17.1) | 10 (11.1) | 29 (21.0) | 0.052 |
LDL-C, mg/dL | 102.1 ± 32.5 | 98.0 ± 31.0 | 104.6 ± 32.9 | 0.130 |
LDL-C ≥ 100 mg/dL | 41 (18.0) | 13 (14.4) | 28 (20.3) | 0.261 |
FPI, μU/mL | 15.2 (7.9, 31.9) | 12.7 (6.8, 26.5) | 18.6 (9.3, 35.7) | 0.004 |
FPI ≥ 12 μU/mL | 142 (62.3) | 47 (52.2) | 95 (68.8) | 0.011 |
hs-CRP, mg/dL | 0.3 (0.1, 0.6) | 0.2 (0.1, 0.5) | 0.3 (0.1, 0.6) | 0.277 |
hs-CRP ≥ 0.5 mg/dL | 65 (28.5) | 23 (25.6) | 42 (30.4) | 0.425 |
iPTH, pg/mL | 225.2 (80.6, 409.1) | 231.0 (68.5, 441.2) | 223.9 (94.4, 382.7) | 0.916 |
iPTH ≥300 pg/mL | 93 (40.8) | 38 (42.2) | 55 (39.9) | 0.722 |
Creatinine, mg/dL | 11.1 ± 1.9 | 10.8 ± 1.7 | 11.3 ± 2.1 | 0.077 |
Creatinine ≤7.5 mg/dL | 8 (3.5) | 6 (6.7) | 2 (1.4) | 0.036 |
Albumin, mg/dL | 4.0 ± 0.4 | 4.0 ± 0.4 | 4.0 ± 0.4 | 0.992 |
Albumin ≤3.5 mg/dL | 24 (10.5) | 8 (8.9) | 16 (11.6) | 0.515 |
Pre-BUN, mg/dL | 72.9 ± 20.9 | 76.7 ± 21.2 | 70.2 ± 20.7 | 0.023 |
Post-BUN, mg/dL | 19.9 ± 7.8 | 19.0 ± 7.6 | 20.7 ± 7.9 | 0.106 |
eKt/V | 1.6 ± 0.3 | 1.8 ± 0.4 | 1.5 ± 0.3 | < 0.001 |
nPNA, g/kg | 1.4 ± 0.4 | 1.4 ± 0.4 | 1.3 ± 0.4 | < 0.001 |
nPNA < 1.0 g/kg | 29 (12.7) | 7 (7.8) | 22 (15.9) | 0.071 |
Table 2
Dietary intake among hemodialysis patientsa
Macronutrients |
Energy intake, kcal | 1885.0 ± 477.2 | 2182.6 ± 448.9 | 1690.9 ± 387.7 | < 0.001 |
Energy intake, kcal/kg | 31.5 ± 8.8 | 39.8 ± 7.0 | 26.1 ± 4.6 | < 0.001 |
Protein, g/kg IBW | 1.2 ± 0.3 | 1.4 ± 0.3 | 1.1 ± 0.3 | < 0.001 |
Protein < 1.2 g/kg IBW | 132 (57.9) | 28 (31.1) | 104 (75.4) | < 0.001 |
Protein, (%EI) | 15.0 ± 3.0 | 14.6 ± 2.7 | 15.2 ± 3.2 | 0.090 |
Protein < 15% EI | 118 (51.8) | 52 (57.8) | 66 (47.8) | 0.142 |
Carbohydrate, g | 222.1 ± 68.8 | 252.9 ± 71.5 | 202.0 ± 59.1 | < 0.001 |
Carbohydrate, (%EI) | 47.6 ± 8.6 | 46.5 ± 8.2 | 48.3 ± 8.9 | 0.138 |
Carbohydrate < 45%EI | 80 (35.1) | 33 (36.7) | 47 (34.1) | 0.687 |
Total fat, g | 78.3 ± 27.0 | 92.5 ± 26.5 | 69.0 ± 23.0 | < 0.001 |
Total fat, (%EI) | 37.1 ± 7.8 | 38.2 ± 7.4 | 36.4 ± 8.1 | 0.100 |
SFA (%EI) | 13.4 (8.0, 69.4) | 10.6 (8.0, 62.9) | 37.9 (8.5, 73.7) | 0.083 |
SFA ≥10% EI | 143 (62.7) | 53 (58.9) | 90 (65.2) | 0.334 |
MUFA (%EI) | 18.0 (10.6, 76.0) | 13.4 (9.8, 73.4) | 41.8 (11.3, 80.2) | 0.024 |
MUFA ≥20% EI | 109 (47.8) | 34 (37.8) | 75 (54.3) | 0.014 |
PUFA (%EI) | 17.6 (8.7, 60.6) | 12.2 (7.6, 52.0) | 32.8 (9.6, 62.9) | 0.015 |
PUFA ≥10% EI | 155 (68.0) | 55 (61.1) | 100 (72.5) | 0.072 |
SFA/UFA ratio | 0.5 ± 0.2 | 0.5 ± 0.2 | 0.5 ± 0.2 | 0.869 |
UFA/SFA ratio | 2.3 ± 0.7 | 2.3 ± 0.6 | 2.3 ± 0.8 | 0.426 |
Micronutrients |
Mineral and Water |
Sodium, mg/d | 1254.8 ± 897.6 | 1576.9 ± 1108.9 | 1044.6 ± 650.7 | < 0.001 |
Sodium > 1800 mg/d | 43 (18.9) | 29 (32.2) | 14 (10.1) | < 0.001 |
Fluid, mL/d | 1382.6 ± 480.5 | 1493.7 ± 506.7 | 1310.2 ± 449.8 | 0.005 |
Fluid > 1500 mL/d | 78 (34.2) | 38 (42.2) | 40 (29.0) | 0.039 |
Potassium, mg/d | 1445.2 ± 582.6 | 1616.3 ± 575.7 | 1333.6 ± 561.5 | < 0.001 |
Phosphate, mg/d | 694.9 ± 257.9 | 799.7 ± 270.2 | 626.6 ± 225.6 | < 0.001 |
Calcium, mg/d | 291.3 ± 177.2 | 336.9 ± 190.7 | 261.6 ± 161.6 | 0.002 |
Iron, mg/d | 8.6 ± 4.6 | 9.7 ± 5.3 | 7.8 ± 4.0 | 0.003 |
Zinc, mg/d | 8.1 ± 3.8 | 9.3 ± 4.0 | 7.3 ± 3.5 | < 0.001 |
Vitamins |
Vitamin B1 (thiamin), mg/d | 0.8 ± 0.6 | 1.0 ± 0.6 | 0.8 ± 0.6 | 0.008 |
Vitamin B2 (riboflavin), mg/d | 0.9 ± 0.5 | 1.0 ± 0.6 | 0.8 ± 0.5 | 0.001 |
Niacin (B3), mg/d | 11.8 ± 6.3 | 13.9 ± 7.0 | 10.5 ± 5.5 | < 0.001 |
Vitamin B6 (pyridoxine), mg/d | 1.2 ± 0.9 | 1.4 ± 1.0 | 1.0 ± 0.7 | 0.015 |
Vitamin B12, μg/d | 3.8 ± 3.7 | 4.5 ± 4.1 | 3.4 ± 3.4 | 0.022 |
Vitamin C, mg/d | 90.6 ± 63.5 | 95.6 ± 59.7 | 87.3 ± 65.8 | 0.335 |
Vitamin E, mg/d † | 12.6 ± 10.3 | 12.9 ± 11.1 | 12.6 ± 10.3 | 0.717 |
The results of bivariate logistic regression analyses presented that higher age associated with higher prevalence of IFG and AACE-MetS with odd ratio, OR = 1.03, 95% confidence interval, 95%CI, 1.00–1.05,
p < 0.05, and OR = 1.03, 95%CI, 1.01–1.06,
p < 0.05, respectively. Men experienced higher prevalence of overweight or obesity (OR = 1.85, 95%CI, 1.03–3.33,
p < 0.05), but lower prevalence of elevated waist circumference (OR = 0.32, 95%CI, 0.17–0.59,
p < 0.001) than women. Hemodialysis vintage was negatively associated with IFG (OR = 0.91, 95%CI, 0.86–0.97,
p < 0.001), Overweight/obese (OR = 0.92, 95%CI, 0.86–0.98,
p < 0.05), high TG (OR = 0.94, 95%CI, 0.89–0.99,
p < 0.05), low HDL-C (OR = 0.95, 95%CI, 0.90–0.99,
p < 0.05), AACE-MetS (OR = 0.90, 95%CI, 0.85–0.96,
p < 0.001), and HMetS (OR = 0.94, 95%CI, 0.89–0.99,
p < 0.05), respectively. Charlson comorbidity index was positively associated with IFG (OR = 1.38, 95%CI, 1.14–1.67,
p < 0.001), Overweight/obese (OR = 1.21, 95%CI, 1.01–1.45,
p < 0.05), AACE-MetS (OR = 1.44, 95%CI, 1.19–1.74,
p < 0.001), and HMetS (OR = 1.28, 95%CI, 1.07–1.53,
p < 0.01), respectively. Interdialytic weight gains was positively linked with IFG (OR = 1.21, 95%CI, 1.03–1.43,
p < 0.05), AACE-MetS (OR = 1.22, 95%CI, 1.04–1.43,
p < 0.05), and HMetS (OR = 1.24, 95%CI, 1.06–1.46,
p < 0.01), respectively (Table
3).
Table 3
Bivariate analysis the effects of personal factors and dietary intake on metabolic abnormalities and metabolic syndrome
Age, years | 1.03 (1.00, 1.05)* | 1.01 (0.99, 1.04) | 1.00 (0.98, 1.03) | 1.00 (0.98, 1.03) | 1.01 (0.98, 1.03) | 1.00 (0.97, 1.03) | 1.03 (1.01, 1.06)* | 1.01 (0.98, 1.03) |
Male gender | 1.18 (0.67, 2.07) | 1.85 (1.03, 3.33)* | 0.32 (0.17, 0.59)*** | 1.20 (0.68, 2.10) | 1.25 (0.72, 2.18) | 1.69 (0.86, 3.34) | 1.13 (0.65, 1.99) | 1.18 (0.69, 2.04) |
Hemodialysis vintage, years | 0.91 (0.86, 0.97)*** | 0.92 (0.86, 0.98)* | 0.97 (0.91, 1.03) | 0.94 (0.89, 0.99)* | 0.95 (0.90, 0.99)* | 1.01 (0.95, 1.09) | 0.90 (0.85, 0.96)*** | 0.94 (0.89, 0.99)* |
CCI | 1.38 (1.14, 1.67)*** | 1.21 (1.01, 1.45)* | 1.07 (0.88, 1.29) | 1.11 (0.94, 1.33) | 1.14 (0.95, 1.36) | 1.12 (0.89, 1.39) | 1.44 (1.19, 1.74)*** | 1.28 (1.07, 1.53)** |
Physical activity, (10% MET increment) | 1.07 (0.97, 1.18) | 0.99 (0.90, 1.08) | 0.92 (0.83, 1.02) | 0.96 (0.87, 1.05) | 0.93 (0.85, 1.03) | 1.07 (0.95, 1.20) | 1.06 (0.97, 1.17) | 0.99 (0.91, 1.09) |
hs-CRP > 0.5 mg/dL | 1.45 (0.78, 2.70) | 1.63 (0.90, 2.93) | 1.37 (0.72, 2.58) | 1.16 (0.64, 2.08) | 1.36 (0.75, 2.49) | 0.66 (0.33, 1.35) | 1.20 (0.66, 2.19) | 1.41 (0.79, 2.53) |
IDWG, % | 1.21 (1.03, 1.43)* | 1.00 (0.85, 1.16) | 1.10 (0.93, 1.31) | 1.12 (0.96, 1.32) | 1.13 (0.97, 1.32) | 1.05 (0.87, 1.28) | 1.22 (1.04, 1.43)* | 1.24 (1.06, 1.46)** |
Dietary intake |
Inadequate EI | 2.50 (1.43, 4.37)*** | 6.10 (3.10, 11.99)*** | 6.20 (2.78, 13.84)*** | 1.90 (1.09, 3.34)* | 1.83 (1.06, 3.15)* | 1.05 (0.53, 2.08) | 2.34 (1.35, 4.08)** | 3.24 (1.86, 5.63)*** |
Protein < 1.2 g/kg IBW | 1.20 (0.69, 2.08) | 0.85 (0.50, 1.47) | 0.93 (0.52, 1.70) | 1.12 (0.65, 1.92) | 1.31 (0.76, 2.23) | 0.92 (0.47, 1.82) | 1.05 (0.61, 1.81) | 1.32 (0.78, 2.23) |
Carbohydrate < 45%EI | 1.42 (0.79, 2.54) | 1.08 (0.61, 1.89) | 1.95 (1.07, 3.57)* | 0.83 (0.48, 1.46) | 0.87 (0.50, 1.51) | 1.44 (0.69, 3.00) | 1.46 (0.82, 2.59) | 1.25 (0.72, 2.16) |
SFA ≥10% EI | 1.41 (0.81, 2.46) | 0.85 (0.49, 1.48) | 0.64 (0.35, 1.17) | 0.94 (0.54, 1.62) | 0.91 (0.53, 1.58) | 1.91 (0.97, 3.75) | 1.45 (0.84, 2.53) | 0.92 (0.54, 1.57) |
MUFA ≥20% EI | 2.25 (1.28, 3.94)** | 1.11 (0.64, 1.90) | 0.71 (0.39, 1.30) | 0.89 (0.52, 1.52) | 1.12 (0.66, 1.91) | 1.44 (0.73, 2.84) | 2.19 (1.26, 3.81)** | 1.17 (0.69, 1.97) |
PUFA ≥10% EI | 1.04 (0.58, 1.85) | 0.96 (0.54, 1.72) | 1.02 (0.54, 1.93) | 1.14 (0.64, 2.02) | 1.14 (0.64, 2.00) | 1.58 (0.79, 3.15) | 1.10 (0.62, 1.95) | 1.12 (0.64, 1.95) |
SFA/UFA ratio | 0.67 (0.13, 3.43) | 0.30 (0.05, 1.80) | 0.33 (0.05, 2.41) | 0.49 (0.09, 2.64) | 2.23 (0.41, 12.15) | 2.50 (0.27, 23.46) | 0.86 (0.17, 4.42) | 0.53 (0.11, 2.62) |
UFA/SFA ratio | 1.11 (0.75, 1.63) | 1.37 (0.93, 2.01) | 1.51 (1.00, 2.28) | 1.28 (0.88, 1.86) | 1.08 (0.74, 1.58) | 0.81 (0.51, 1.29) | 1.05 (0.72, 1.55) | 1.46 (0.99, 2.14) |
Sodium > 1800 mg | 0.62 (0.32, 1.22) | 1.04 (0.53, 2.08) | 0.82 (0.38, 1.78) | 1.16 (0.59, 2.27) | 1.61 (0.79, 3.29) | 0.99 (0.42, 2.31) | 0.68 (0.35, 1.34) | 0.98 (0.50, 1.90) |
Fluid > 1500 mL | 0.68 (0.38, 1.19) | 1.73 (0.99, 3.04) | 1.55 (0.84, 2.85) | 1.34 (0.76, 2.33) | 1.45 (0.82, 2.57) | 0.92 (0.46, 1.86) | 0.70 (0.40, 1.23) | 1.16 (0.67, 2.02) |
Reported inadequate dietary energy intake associated with 1.83–6.20 folds of metabolic abnormalities or metabolic syndrome. It was significantly linked to higher prevalence of IFG (OR = 2.50, 95%CI, 1.43–4.37,
p < 0.001), overweight/obese (OR = 6.10, 95%CI, 3.10–11.99,
p < 0.001), elevated waist circumference (OR = 6.20, 2.78–13.84,
p < 0.001), high triglyceride (OR = 1.90, 95%CI, 1.09–3.34,
p < 0.05), low HDL-C (OR = 1.83, 95%CI, 1.06–3.15,
p < 0.05), AACE -MetS (OR = 2.34, 95%CI, 1.35–4.06,
p < 0.01), and HMetS (OR = 3.24, 95%CI, 1.86–5.63,
p < 0.001), respectively. The sodium and fluid intake were not associated with metabolic abnormalities or MetS (Table
3).
The associations of inadequate energy intake with metabolic abnormalities, AACE-MetS, and HMetS were stronger by 2.26 to 8.17 folds after adjusted for gender, age, physical activity, hemodialysis vintage, Charlson comorbidity index (CCI), hs-CRP, and IDWG in multivariate analyses. Inadequate energy intake did not show the significant association with high TG, low HDL-C or high blood pressure (Table
4). On the other hand, the consumption of MUFA greater or equal to 20% of EI is associated with higher likelihood of having IFG (OR = 2.85, 95%CI, 1.39–5.87,
p < 0.01), and AACE-MetS (OR = 3.01, 95%CI, 1.45–6.26,
p < 0.01, Table
4).
Table 4
Associations of dietary intake and metabolic abnormalities and metabolic syndrome via multivariate logistic regression analyses a
| IFG | Overweight/Obese | Elevated WC | High TG | Low HDL-C | High BP | | |
OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) |
Inadequate EI | 2.42 (1.30, 4.51)** | 6.70 (3.25, 13.81)*** | 8.17 (3.33, 20.01)*** | 1.72 (0.95, 3.10) | 1.67 (0.94, 2.98) | 1.18 (0.57, 2.43) | 2.26 (1.21, 4.23)* | 3.52 (1.91, 6.50)** |
Protein < 1.2 g/kg IBW | 0.94 (0.51, 1.74) | 0.74 (0.41, 1.33) | 0.81 (0.42, 1.56) | 0.95 (0.54, 1.69) | 1.14 (0.64, 2.02) | 0.99 (0.48, 2.04) | 0.78 (0.42, 1.46) | 1.15 (0.64, 2.04) |
Carbohydrate < 45%EI | 1.30 (0.69, 2.46) | 1.12 (0.61, 2.05) | 1.88 (0.97, 3.66) | 0.86 (0.48, 1.56) | 0.90 (0.50, 1.62) | 1.57 (0.72, 3.43) | 1.30 (0.69, 2.45) | 1.33 (0.73, 2.41) |
SFA ≥10% EI | 1.70 (0.87, 3.31) | 0.94 (0.50, 1.77) | 0.90 (0.45, 1.80) | 1.22 (0.66, 2.28) | 1.22 (0.66, 2.29) | 2.01 (0.93, 4.32) | 1.88 (0.96, 3.70) | 1.25 (0.66, 2.34) |
MUFA ≥20% EI | 2.85 (1.39, 5.87)** | 1.20 (0.63, 2.30) | 1.09 (0.52, 2.26) | 1.07 (0.56, 2.03) | 1.59 (0.83, 3.04) | 1.40 (0.62, 3.16) | 3.01 (1.45, 6.26)** | 1.55 (0.81, 2.99) |
PUFA ≥10% EI | 0.99 (0.52, 1.90) | 1.07 (0.58, 1.98) | 1.27 (0.64, 2.51) | 1.30 (0.71, 2.38) | 1.33 (0.73, 2.44) | 1.60 (0.77, 3.32) | 1.09 (0.57, 2.09) | 1.32 (0.72, 2.45) |
SFA/UFA ratio | 1.03 (0.17, 6.15) | 0.47 (0.07, 3.05) | 0.46 (0.06, 3.46) | 0.82 (0.14, 4.71) | 5.13 (0.79, 33.43) | 3.07 (0.31, 30.62) | 1.54 (0.26, 9.37) | 1.12 (0.20, 6.24) |
UFA/SFA ratio | 0.98 (0.63, 1.52) | 1.24 (0.82, 1.88) | 1.34 (0.86, 2.10) | 1.11 (0.74, 1.66) | 0.89 (0.59, 1.35) | 0.80 (0.49, 1.31) | 0.90 (0.58, 1.39) | 1.24 (0.81, 1.89) |
Sodium > 1800 mg | 0.63 (0.30, 1.31) | 0.96 (0.47, 1.97) | 0.96 (0.42, 2.20) | 1.16 (0.57, 2.34) | 1.66 (0.79, 3.51) | 0.95 (0.39, 2.31) | 0.73 (0.35, 1.52) | 0.99 (0.49, 2.01) |
Fluid > 1500 mL | 0.60 (0.32, 1.15) | 1.68 (0.91, 3.10) | 1.76 (0.89, 3.46) | 1.22 (0.67, 2.23) | 1.30 (0.70, 2.40) | 0.79 (0.37, 1.66) | 0.61 (0.32, 1.17) | 0.97 (0.52, 1.78) |
In sub-group analyses, inadequate EI showed an significant association with higher prevalence of AACE-MetS in non-hypertension group (OR = 4.09, 95%CI, 1.55–10.77,
p = 0.004), and non-cardiovascular disease group (OR = 2.59, 95%CI, 1.23–5.42,
p = 0.012); and associated with HMetS in group of diabetes (OR = 8.33, 95%CI, 2.08–33.37,
p = 0.003), non-hypertension (OR = 5.33, 95%CI, 1.97–14.40,
p = 0.001), hypertension (OR = 2.59, 95%CI, 1.05–6.37,
p = 0.038), and non-CVD (OR = 3.79, 95%CI, 1.80–7.97,
p < 0.001, Table
5).
Table 5
Association between inadequate energy intake and metabolic syndrome in subgroups of medical historya
Non-DM (n = 141) | 75 | 35 | 1.15 (0.54, 2.47) | 0.718 | 35 | 1.91 (0.88, 4.15) | 0.101 |
DM (n = 87) | 63 | 63 | N/A | | 55 | 8.33 (2.08, 33.37) | 0.003 |
Non-HTN (n = 118) | 73 | 51 | 4.09 (1.55, 10.77) | 0.004 | 44 | 5.33 (1.97, 14.40) | 0.001 |
HTN (n = 110) | 65 | 47 | 1.33 (0.51, 3.51) | 0.560 | 46 | 2.59 (1.05, 6.37) | 0.038 |
Non-CVD (n = 160) | 96 | 68 | 2.59 (1.23, 5.42) | 0.012 | 62 | 3.79 (1.80, 7.97) | < 0.001 |
CVD (n = 68) | 42 | 30 | 1.48 (0.33, 6.75) | 0.612 | 28 | 3.64 (0.99, 13.36) | 0.052 |
Discussion
In the present study, results elucidated that reported inadequate dietary energy intake (IDEI) associated with more MetS abnormalities, and a higher proportion of MetS. The reported IDEI strongly determined 2.26 to 8.17 folds of metabolic abnormalities and MetS diagnosed either by AACE or HMetS criteria. In hemodialysis patients, IDEI disrupts the energy balance, and the nitrogen balance, increases the tissue destruction, and protein catabolism which cause the MetS and exacerbate the dialysis outcomes [
64]. On the other hand, the MetS was found to be a high-risk for many chronic health problems such as obesity, T2DM, cardiovascular diseases, cancer, and all-cause of death [
16‐
19]. Therefore, the early MetS identification and nutritional therapy were highly recommended to reduce above adverse health problems [
25,
65]. In addition, patients who consumed adequate energy-rich-protein can improve the balance of body protein, body composition which further improve hemodialysis outcomes [
66].
The current study showed that about 60% of hemodialysis patients consumed low dietary energy intake. This was in the line with a reliable previous publication in which patients had at most 75% of the energy and protein intake as recommended by K/DOQI guidelines [
9]. MetS prevalence was high in the present study (63.2% AACE-MetS, 53.9% HMetS), and in previous studies in Southern Taiwan was 61.0% measured by NCEP-ATP III criteria [
15]. In comparison with previous studies, the prevalence of MetS was lower in the current study than that in a study in Brazil (74.5%) using the HMetS criteria [
27], and in United States (69.3%) using the NCEP-ATP III criteria [
67].
The consumption of PUFA and SFA did not show the significant association with MetS and its abnormalities, while the consumption of MUFA equal or greater than 20% demonstrated the association with higher IFG and AACE-MetS in the current study. In a previous study, no association between PUFA, or SFA, and MetS was found [
68]. Inconsistently, a number of previous studies suggested that the consumption of dietary MUFA improves insulin sensitivity. In addition, MUFA intake as a substitution for SFA demonstrated the benefit for reducing the metabolic syndrome [
69,
70]. The discrepancy between the findings of this study and other studies could be explained by the cross-sectional design of the current study, the causal relationship is not generated. In addition, the 24-h dietary recall is subject to reporting bias from patients. In practical application, the MUFA was with high density in the Mediterranean dietary pattern (MDP). Strong evidence from several studies and trials proved that the MDP was inversely associated with the incidence of MetS, cardiovascular diseases [
71‐
74]. Therefore, this MDP can be still encouraged and adopted in various population and cultures, with cost-effective serve for preventing the MetS and its components [
75]. However, the application is with precaution and more studies are suggested to intensively investigate the MDP effect on the MetS in hemodialysis patients.
The current results illustrated that the inadequate dietary EI was associated with high prevalence of HMetS in different sub-groups. In a study conducted in Italy, the authors found that patients with MetS reported lower energy intake than those without MetS [
76]. This suggested that MetS diagnosed by Harmonizing Metabolic Syndrome criteria is more sensitive than AACE-MetS in relation to energy intake. In practice, in order to improve the hemodialysis outcomes, the adequate dietary EI is recommended by the K/DOQI guidelines which can reduce the risks of MetS [
9].
The present study demonstrated that the higher prevalence of IFG and AACE-MetS was observed in older patients. The association was also found in previous studies on the general population in Norway, which MetS was diagnosed by either NCEP- ATP III, or IDF criteria [
60], and in individuals in the United States [
61]. This emphasized that the old people are more likely to have metabolic abnormalities, risks for CVD, and type 2 diabetes. Therefore, the MetS definitions should be specifically classified for elderly people, as in need of comprehensive assessment for risk factors. On the other hand, men more likely experienced overweight/obesity, but less likely had elevated waist circumference in comparison with women. This could be explained that men have greater abdominal visceral adipose tissue (likely corresponding to BMI), but less abdominal subcutaneous adipose tissue (likely corresponding to waist circumference) than women [
77].
The study conducted on 153 hemodialysis patients in three dialysis centers in Tehran demonstrated that the prevalence of MetS among women was higher than that among men [
62]. However, in the current study, gender was significantly associated with metabolic abnormalities, but not with AACE MetS or HMetS. This suggests that gender should take into consideration when assessing or treating patients with MetS, the presence of metabolic disorders in men or women may depend on their specific lifestyles and behaviors.
The longer hemodialysis vintage has shown the protective impact on MetS among studied hemodialysis patients. This somehow expressed the quality of hemodialysis in dialysis centers in Taiwan which reflected the effectiveness of multi-disciplinary care program in hospitals since 2003 to combat chronic kidney disease and related comorbidities [
78]. In addition, the full reimbursement of dialysis costs by National Health Insurance in Taiwan medical system could further optimize the quality of care [
79], which in turn reduced the prevalence of metabolic disorders in this study.
Physical activity was not associated with metabolic abnormalities or MetS in the present study. However, a review of several randomized trials concluded that the physical activity decreased the likelihood of development of MetS; if there were no contraindications, more intensive physical exercise or resistance training should be considered to prevent and treat MetS [
63]. In addition, patients who performed regular exercise had better dialysis outcomes and health benefits as reported in an international study on hemodialysis patients [
80].
Finally, the elevated level of hs-CRP did not show the association with MetS and its components. Inconsistently, the association was existed in the previous study, that inflammatory biomarkers had a correlation with MetS in hemodialysis patients [
62]. An elevated level of hs-CRP may be a key independent predictor of adverse outcomes in hemodialysis patients with MetS. Therefore, reducing serum hs-CRP level should be considered for preventing MetS, CVD, and finally mortality among hemodialysis patients.
There was some limitations in the current study. Firstly, the causality cannot be proved between dietary EI and metabolic abnormalities and MetS in a cross-sectional design. In addition, the application of adequate EI but less MUFA intake was not clearly addressed because of the nature of the cross-sectional study design, and unavoidable reporting bias. More in-depth longitudinal studies and trials are required. The self-reported dietary assessment using food records and recalls had impacts on energy underreporting, appropriate interpretations of the results are recommended [
81]. In the current study, we excluded those patients underreported their energy intake in order to avoid the bias and improve the reliability of findings [
42]. However, the sample size is relatively small for subgroup analysis. Further investigation should be conducted on larger sample, to enhance the reliability of finding. The present study demonstrated a number of strengths that patients’ body composition was measured precisely and directly using the BIA, while biochemical data were assessed by using standard laboratory tests. Two MetS definitions reflecting the glucocentric, obesity, and CVD risk factors were used to assure the non-spuriousness of the relationships. Future longitudinal studies or trials were recommended to confirm the relationship between dietary intake and MetS and impacts of nutritional interventions on dialysis outcomes.