J Nutr Sci Vitaminol, 61, 138–146, 2015

Influence of Dietary Sodium and Potassium Intake on the Heart Rate Corrected-QT Interval in Elderly Subjects Ryoma Michishita1, Kazuko Ishikawa-Takata2, Eiichi Yoshimura3, Rikako Mihara1, Masahiro Ikenaga1, Kazuhiro Morimura1, Noriko Takeda4,5, Yosuke Yamada6, Yasuki Higaki1,7, Hiroaki Tanaka1,7, Akira Kiyonaga1,7; The Nakagawa Study Group 1 

Laboratory of Exercise Physiology, Faculty of Health and Sports Science, Fukuoka University, 8–19–1 Nanakuma, Jonan-ku, Fukuoka 814–0180, Japan 2  Program of Health Promotion and Exercise, National Institute of Health and Nutrition, 1–23–1 Toyama, Shinjuku-ku, Tokyo 162–8636, Japan 3  Department of Food and Health Science, Prefectural University of Kumamoto, 3–1–100 Tsukide, Higashi-ku, Kumamoto 862–8502, Japan 4  Japan Society for the Promotion of Science, 8 Ichibancho, Chiyoda-ku, Tokyo 102–8472, Japan 5  Faculty of Sport Sciences, Waseda University, 2–579–15 Mikajima, Tokorozawa, Saitama 359–1192, Japan 6  Department of Nutritional Science, National Institute of Health and Nutrition, 1–23–1 Toyama, Shinjuku-ku, Tokyo 162–8636, Japan 7  Fukuoka University Institute for Physical Activity, 8–19–1 Nanakuma, Jonan-ku, Fukuoka 814–0180, Japan (Received June 20, 2014)

Summary  It is well known that imbalances in the dietary electrolytes are associated with a significantly higher incidence of cardiovascular disease (CVD). On the other hand, a prolonged heart rate corrected-QT (QTc) interval is associated with an increased risk of cardiac autonomic nervous system dysfunction, the incidence of CVD and sudden cardiac death. This study was designed to clarify the association between the nutritional status and the QTc interval in elderly subjects. The subjects included 119 elderly subjects (46 males and 73 females, age; 72.964.8 y) without a history of CVD, who were taking cardioactive drugs. Resting 12-lead electrocardiography was performed, while the QTc interval was calculated according to Bazett’s formula. The nutritional status was assessed using a brief self-administered diet history questionnaire. The subjects were divided into three categories, which were defined as equally trisected distributions of the body mass index (BMI). The QTc interval was significantly longer in both the low and high BMI groups than in the moderate BMI group in both genders (p,0.05, respectively). A stepwise multiple regression analysis showed the QTc interval to be independently associated with the potassium intake in the low BMI group and the sodium intake in the high BMI group in both genders (p,0.05, respectively). These results suggest that the body mass, especially lean body mass and overweight, were associated with a prolonged QTc interval and dietary electrolytes in elderly subjects. Based on our results, we consider that it is necessary to perform dietary counseling, especially focusing on sodium and potassium intake, depending on the body mass. Key Words  QTc interval, sodium intake, potassium intake, elderly subjects

It is well known that dietary high sodium intake and low potassium intake are associated with a significantly higher incidence of cardiovascular disease (CVD) and mortality (1–3). Conversely, a reduction of dietary sodium intake and an increase in potassium intake can decrease the incidence of CVD and mortality (4, 5). On the other hand, a prolonged heart rate corrected-QT (QTc) interval, as measured with a standard electrocardiogram (ECG), is associated with an increased risk of arrhythmias, sudden cardiac death, coronary artery disease, left ventricular hypertrophy and cardiac autonomic nervous system dysfunction (6–10). The QTc interval is longer in females than in males and is influE-mail: [email protected]

enced by age, sex hormones and electrolyte imbalance (7, 11, 12). Previous studies have reported that morbid obesity is also correlated with a prolonged QTc interval, while weight loss could improve the QTc in obese subjects (13–16). On the other hand, it is well known that eating disorders are also related to a significantly higher incidence of CVD, several complications and mortality through a prolonged QTc interval (17, 18). These results suggest that both weight gain and extreme weight loss may be independent risk factors for the incidence of CVD and sudden cardiac death. However, the association between the nutritional status and the QTc interval is still unknown. This study was designed to clarify the association between the nutritional status and the QTc interval in

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QTc Interval and Dietary Electrolyte Table  1.  The differences in the subjects’ characteristics for the three BMI categories in elderly males. All (n546) QTc interval (ms) 417.0621.4 QT interval (ms) 400.2632.4 R-R interval (ms) 928.16156.4 Heart rate (beats/min) 65.0611.6 Age (y) 74.565.5 Diabetes mellitus (yes/no) 6/40 Hypertension (yes/no) 17/29 Dyslipidemia (yes/no) 4/42 Cigarette smoking habit (yes/no) 4/42 BMI (kg/m2) 23.362.7 Waist circumference (cm) 85.5610.5 Systolic blood pressure (mmHg) 141.3618.1 Diastolic blood pressure (mmHg) 82.369.7 Alcohol intake (% of energy) 5.966.5 Total energy intake (kcal/d) 2,060.56487.7 Total energy intake/body weight 33.267.1  (kcal/d/kg) Protein intake (% of energy) 16.062.6 Fat intake (% of energy) 25.865.6 Carbohydrate intake (% of energy) 51.267.8 Sodium intake (mg/1,000 kcal) 2,333.66355.1 Potassium intake (mg/1,000 kcal) 1,541.06318.7 Calcium intake (mg/1,000 kcal) 337.7680.3 Magnesium intake (mg/1,000 kcal) 152.1625.9

Low (n515) Moderate (n515) High (n516) p for trend (16.8–21.9 kg/m2) (22.0–24.4 kg/m2) (24.7–28.0 kg/m2) 421.5618.3b 426.7629.4b,c 1,030.66151.9c 57.169.9c 75.164.7 1/14 5/10 1/14 1/14 20.261.5b,c 76.5611.2b,c 136.2621.1 79.768.4 3.064.4 1,713.26426.4c 32.368.3

400.7617.0a 391.0628.3a 952.46107.0c 63.267.0c 73.365.8 3/12 5/10 1/14 2/13 23.260.6a,c 84.764.3a,c 147.1615.6 83.1610.1 7.066.6 2,155.76309.2 34.865.4

428.1619.3b N.S. 383.9623.0a N.S. 809.36122.3a,b N.S. 75.2611.1a,b N.S. 74.965.7 N.S. 2/14 N.S. 7/9 N.S. 2/14 N.S. 1/15 N.S. 26.261.2a,b p,0.0001 94.665.2a,b p,0.05 140.5615.1 N.S. 83.969.4 N.S. 7.467.6 N.S. 2,296.86515.3a p,0.05 32.567.4 N.S.

16.363.1 25.063.6 49.865.3 2,282.16300.6 1,409.76279.3 315.9691.9 153.9629.5

15.563.0 26.067.1 50.369.0 2,264.06355.4 1,574.06302.5 322.5671.5 143.6626.3

16.361.9 26.565.8 53.668.5 2,459.26392.9 1,633.26345.1 372.4668.7 158.5621.1

N.S. N.S. N.S. N.S. N.S. N.S. N.S.

Data are expressed as the means6SD. a  p,0.05, compared with the low group, b p,0.05, compared with the moderate group, c p,0.05, compared with the high group. BMI: body mass index.

elderly subjects. The hypothesis was that dietary electrolyte levels, such as high sodium and low potassium intake may be a sensitive factor for predicting the future incidence of sudden cardiac death and CVD associated with a prolonged QTc interval. Malnutrition in the elderly is now widely regarded as an important problem affecting the incidence of CVD, several complications and sudden cardiac death (19). As mentioned above, a prolonged QTc interval is a good predictor of CVD and cardiac sudden death in elderly subjects. Therefore, in this study, we focused on elderly subjects, because identifying the link between the nutritional status and the QTc interval may be useful for detecting early-stage CVD and preventing sudden cardiac death in elderly subjects. SUBJECTS AND METHODS Subjects.  This study enrolled 119 elderly subjects [46 males and 73 females; age, 72.964.8 y; body mass index (BMI), 23.163.1 kg/m2; waist circumference, 86.369.9 cm; resting systolic/diastolic blood pressure, 139.2617.6/81.668.7  mmHg; resting heart rate, 64.4610.0 beats/min; R-R interval, 943.96138.0 ms; QT interval, 406.0629.9 ms and QTc interval, 419.06 21.4 ms], who participated in our Sarcopenia and Dementia Prevention Program (The Nakagawa Study). Those taking cardioactive drugs such as b-blockers and

 -blockers or patients with a history of cerebrovascular disease, coronary artery disease, LVH, cardiac valve disease, signs of dementia or diabetic complication (diabetic neuropathy, diabetic nephropathy and diabetic retinopathy) or an electrolyte disturbance, bundle branch block, intraventricular conduction disturbance, abnormal Q wave and abnormal ST-T waves were excluded from the study. All patients gave informed consent for participation after agreeing with the purpose, methods and significance of the study for which the work was undertaken and its conformation to the Declaration of Helsinki. This study was approved by the Ethics Committee of Fukuoka University (No. 11-04-01). Resting ECG, blood pressure and anthropometric measurements.  An ECG was recorded with a standard resting 12-lead ECG (FCP-7401, Fukuda Denshi, Tokyo, Japan) at a paper speed of 25 mm per seconds after more than 5 min of rest. The QTc interval was automatically calculated according to Bazett’s formula (20) (QTc interval5QT interval/square root of R-R interval). In this ECG, the QTc interval measurement was 4 ms of the sampling interval, and was evaluated from the average wave of both extremity and chest leads using the differential threshold methods. The blood pressure was measured in the left arm with

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Table  2.  The differences in the subjects’ characteristics for the three BMI categories in elderly females. All (n573) QTc interval (ms) 420.3621.5 QT interval (ms) 409.6627.8 R-R interval (ms) 953.96125.1 Heart rate (beats/min) 63.468.7 Age (y) 72.064.1 Diabetes mellitus (yes/no) 6/67 Hypertension (yes/no) 20/63 Dyslipidemia (yes/no) 12/61 Cigarette smoking habit (yes/no) 2/71 BMI (kg/m2) 23.163.3 Waist circumference (cm) 86.869.5 Systolic blood pressure (mmHg) 137.8617.2 Diastolic blood pressure (mmHg) 81.168.0 Alcohol intake (% of energy) 0.661.3 Total energy intake (kcal/d) 1,722.86440.4 Total energy intake/body weight 33.368.9  (kcal/d/kg) Protein intake (% of energy) 17.062.6 Fat intake (% of energy) 27.264.5 Carbohydrate intake (% of energy) 54.266.5 Sodium intake (mg/1,000 kcal) 2,498.06411.8 Potassium intake (mg/1,000 kcal) 1,752.46346.7 Calcium intake (mg/1,000 kcal) 372.7695.5 Magnesium intake (mg/1,000 kcal) 167.9627.5

Low (n524) Moderate (n524) High (n525) p for trend (16.7–21.5 kg/m2) (21.6–24.1 kg/m2) (24.2–34.3 kg/m2) 427.5618.8b 422.9623.4b,c 982.26112.1c 61.366.9c 71.664.1 2/22 6/18 5/19 1/23 19.861.4b,c 78.564.7b,c 137.2615.8 81.367.4 0.661.0 1,537.86369.6c 33.968.6

403.1619.4a 400.5625.5a 987.4685.8c 60.665.9c 71.563.8 1/23 5/19 2/22 0/24 22.660.8a,c 84.965.2a,c 136.0618.5 79.767.8 0.862.0 1,774.96443.3 35.269.5

430.0615.6b N.S. 405.5630.1a N.S. 894.76149.4a,b N.S. 67.1610.6a,b N.S. 72.864.2 N.S. 3/22 N.S. 9/16 N.S. 5/20 N.S. 1/24 N.S. 26.662.4a,b p,0.05 96.767.0a,b p,0.05 140.1617.7 N.S. 82.568.7 N.S. 0.460.7 N.S. 1,850.46456.9a p,0.05 30.868.2 N.S.

16.962.4 26.664.9 52.265.8 2,456.56529.6 1,718.56398.4 364.4697.1 163.5632.6

17.262.5 26.564.8 54.966.7 2,425.66244.6 1,774.56305.2 378.4678.6 168.5622.0

17.163.0 28.563.4 55.466.7 2,613.56396.5 1,765.86340.1 375.66111.4 171.9627.0

N.S. N.S. N.S. N.S. N.S. N.S. N.S.

Data are expressed as the means6SD. a  p,0.05, compared with the low group, b p,0.05, compared with the moderate group, c p,0.05, compared with the high group. BMI: body mass index.

the subject sitting in a chair after more than 5 min of rest, and was expressed as an average of duplicate measurements. The height and body weight were measured, while the body mass index (BMI) was calculated as the ratio of the body weight (kg) to the height squared (m2). The waist circumference was measured at the level of the umbilicus. Dietary assessment. The nutritional status was assessed using a brief self-administered diet history questionnaire (BDHQ) (21). The BDHQ is a validated four-page structured questionnaire, which assesses the dietary habits in the period of the preceding month. The BDHQ contains queries about the consumption frequencies of 58 foods and beverages, with specified serving sizes described in terms of the natural portion or the standard weight and volume measurement of servings commonly consumed by the general Japanese population. The BDHQ consists of five sections: (1) the intake frequency of food and nonalcoholic beverage items, (2) the daily intake of rice and miso soup, (3) the frequency of drinking and amount per drink for alcoholic beverages, (4) usual cooking methods and (5) general dietary behavior. The dietary intake of energy and nutrients was estimated using an ad hoc computer algorithm using the 58 foods and beverages included in the BDHQ and the Standard Tables of Food Composition in

Japan (22). The BDHQ was developed based on a comprehensive version of a validated self-administered diet history questionnaire (DHQ) (23–25). According to the validation study of the BDHQ using 16-d dietary records as the gold standard, the personal correlation coefficients for 37 nutrients in 92 Japanese males and 92 Japanese females ranging from 31–76 y of age were 0.50 and 0.62, respectively (21). Statistical analysis.  The data were expressed as the means6SD. The statistical analysis was performed using the StatView J-5.0 software package (SAS Institute, Cary, NC). The intakes of seven selected nutrients (protein, fat, carbohydrate, sodium, potassium, calcium and magnesium) were evaluated using a factor analysis on the basis of total energy-adjusted intake using a density method (26). The subjects were divided into three categories, which were defined as equally trisected distributions of the BMI (low, moderate and high groups). The inter-multiple group relationships were determined using a one-way repeated measures analysis of variance (ANOVA) and the Tukey-Kramer method. The linear-by-linear associations were determined using the Jonckheere-Terpstra trend test for continuous variables and Cochran-Armitage trend test for categorical variables. Pearson’s simple regression and the stepwise mul-

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Fig.  1.  The association of the QTc interval with the total energy, protein, fat and carbohydrate intake calculated by a simple regression analysis in the low, moderate and high BMI groups.

tivariate regression analyses were performed in order to determine the associations of the QTc interval with the nutritional status. A probability value ,0.05 was considered to be statistically significant. RESULTS Tables 1 and 2 summarize the subjects’ characteristics based on the three BMI categories of the elderly

male and female individuals. The QTc interval was significantly longer in the low and high BMI groups in comparison to the moderate BMI group in both elderly males and females (p,0.05, respectively). The QT interval was significantly longer in the moderate and high BMI groups in comparison to the low BMI group in both genders (p,0.05, respectively). The R-R interval was significantly shorter, while the heart rate was sig-

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Fig.  2.  The association of the QTc interval with the sodium, potassium, calcium and magnesium intake calculated by a simple regression analysis in the low, moderate and high BMI groups.

nificantly higher in the high BMI group in comparison to the low and moderate BMI groups in both genders (p,0.05, respectively). The waist circumference was significantly higher in the order of high . moderate . low BMI groups in both elderly males and females (p for trend ,0.05). The total energy intake was significantly higher in the high BMI group in comparison to the low and moderate BMI groups in both genders (p for trend

,0.05). In both elderly males and females, there were no significant differences in the age, cigarette smoking habit, systolic blood pressure, diastolic blood pressure, alcohol, total energy intake per body weight, protein, fat, carbohydrate, sodium, potassium, calcium or magnesium intake among the three BMI groups. Figures 1 and 2 show the association between the QTc interval and the dietary intake (total energy, protein, fat,

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Table  3.  The association between the QTc interval and nutritional status determined by a stepwise multiple regression analysis. Low BMI

Males   Sodium intake   Potassium intake Females   Sodium intake   Potassium intake

Moderate BMI

b

r2

p value

20.533

0.284

p,0.05

20.459

0.210

p,0.05

r2

b

0.446

0.199

High BMI p value

p,0.05

b

r2

p value

0.531

0.282

p,0.05

0.453

0.205

p,0.05

b: standard regression coefficient. In the stepwise multiple regression analysis, the QTc interval was entered as a dependent variable. The following factors were entered as independent variables: protein, fat, carbohydrate, sodium, potassium, calcium and magnesium intake.

carbohydrate, sodium, potassium, calcium and magnesium intake), determined by a simple regression analysis in the low, moderate and high BMI groups. In the low BMI group, the QTc interval negatively correlated with the total energy and potassium intake in both genders, and also negatively correlated with the protein, fat and calcium intake in females (p,0.05, respectively). In the moderate BMI group, the QTc interval positively correlated with the total energy, protein and sodium intake in females (p,0.05, respectively). In the high BMI group, the QTc interval positively correlated with the total energy and sodium intake in both genders (p,0.05, respectively). In a stepwise multiple regression analysis, the QTc interval was entered as a dependent variable, while the protein, fat, carbohydrate, sodium, potassium, calcium and magnesium intake were entered as independent variables. In the low BMI group, the QTc interval was independently associated with the potassium intake in both genders (males: r250.284, p,0.05, females: r250.210, p,0.05). In the moderate BMI group, the QTc interval was independently associated with the sodium intake in females (r250.199, p,0.05). In the high BMI group, the QTc interval was independently associated with the sodium intake in both males and females [males: r250.282, p,0.05, females: r250.205, p,0.05 (Table 3)]. DISCUSSION The major finding of this study was that the QTc interval was significantly longer in the low and high BMI groups compared to the moderate BMI group in both genders. In addition, a stepwise multiple regression analysis showed that the QTc interval was independently associated with the potassium intake in the low BMI group and with the sodium intake in the high BMI group in both genders. Our current findings suggest that the relationship of dietary electrolytes with a prolonged QT interval in elderly subjects may differ based on the body mass. However, the association between the nutritional status and the QTc interval had been previously unknown, despite the observation that both weight gain

and extreme weight loss influence the incidence of CVD and mortality. According to our data, the QTc interval was significantly longer in the low BMI group compared to the moderate BMI group; while a stepwise multiple regression analysis showed that the QTc interval was independently associated with the potassium intake in the low BMI group in both genders. Recent studies have demonstrated that a low dietary potassium intake is associated with a significantly higher incidence of CVD and mortality (1–4). In addition, several studies have reported that anorexia nervosa caused a prolonged QTc interval, decreased ventricular mass, systolic dysfunction and sudden cardiac death, and was correlated with a low potassium intake (17, 18). Facchini et al. (27) demonstrated that anorexia nervosa patients with a prolonged QTc interval were at risk of a significantly higher complication of hypopotassemia. Our previous cross-sectional study (28) noted that a prolonged QTc interval correlated negatively with a lower aerobic capacity, while it positively correlated with the serum sodium level and negatively correlated with the serum potassium concentration in postmenopausal overweight females. Moreover, Franzoni et al. (29) reported that patients with anorexia nervosa have a greater QT dispersion than normal body weight females, and oral potassium supplementation (two vials of K-Flebo d21560 mEq d21, per os) for 4 wk led to a significant reduction in the QT interval dispersion. These findings suggest that potassium intake may be important to protect the cardiovascular function in lean subjects. However, the causality between a low potassium intake and a prolonged QTc interval in lean subjects could not be elucidated, because the present study had a cross-sectional design. It has been well known that a prolonged QTc interval is reflected in the dysfunction of the cardiac autonomic nervous system (9), while the cardiac autonomic nervous system is influenced by eating disorders (18). Therefore, the association between a low potassium intake and prolonged QTc interval in lean subjects might be influenced by the dysfunction of the cardiac autonomic nervous system caused by

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malnutrition. On the other hand, the QTc interval was significantly longer in the high BMI group compared to the moderate BMI group. In particular, the R-R interval was significantly shorter, while the heart rate was significantly higher in the high BMI group in comparison to the low and moderate BMI groups in both genders. Previous studies have reported that morbid obesity is also correlated with a prolonged QTc interval (13). el-Gamal et al. (13) demonstrated the QTc interval is significantly associated with the body mass, and obesity may be one of the most common causes of a prolonged QTc interval. In addition, sympathetic nervous system dysfunction is also known to cause a prolonged QTc interval (7, 10). Previous studies have reported that morbid obesity also correlates with sympathetic nervous system dysfunction (30). Furthermore, our stepwise multiple regression analysis showed that the QTc interval was independently associated with the sodium intake in the high BMI group in both genders. It has been well known that a dietary high sodium intake is also associated with a significantly higher incidence of CVD and mortality (1–3, 5). Hoffmann and Cubeddu (31) observed that the dietary sodium intake in free-living subjects was markedly increased in subjects with metabolic syndrome, and the 24 h urinary sodium and potassium excretion was associated with obesity and higher blood pressure. The possible mechanisms underlying the relationship between a high sodium intake and metabolic disorders have been thought to be influenced by inadequate aldosterone suppression and increased mineralocorticoid receptor activation (32, 33). In addition, our stepwise multiple regression analysis showed that the QTc interval was independently associated with the sodium intake in the moderate BMI group in females. Unfortunately the causality of a sodium intake and prolonged QTc interval in normal body weight females could not be elucidated from the results of present study. However, because the relationship between sodium intake and prolonged QTc interval was similar in normal weight and overweight females, we can envision that this relationship has the same mechanisms for normal weight and overweight females. Therefore, the association between sodium intake and prolonged QTc interval in normal body weight and overweight subjects might be influenced by the sympathetic nervous system and caused by the sodium intake. The current findings suggest that the body mass, especially lean body mass and overweight, were associated with a prolonged QTc interval and dietary electrolytes, and monitoring the dietary electrolyte levels of elderly subjects depending on the body mass may help predict the risk of various cardiovascular diseases. Study limitations and clinical implications There are several limitations associated with this study. First, the limited study population included only community-dwelling, independent, elderly subjects. Therefore, it remains unclear whether our findings are consistent for young or middle-aged people, weak elderly subjects, patients with CVD and those with other com-

plications. Second, since the study had a cross-sectional design, it was not possible to clarify the causative role of the nutritional status on the QTc interval. Third, the QTc interval in this study was estimated using Bazett’s formula. Furthermore, abnormalities in wall motion, wall thickness and valvular activity, which also influence the QTc interval, could not be evaluated in our subjects. Modalities such as nuclear myocardial perfusion imaging or echocardiography will be needed to perform such studies. Finally, we could not distinguish the risk of sudden cardiac death due to secondary long QT syndrome (e.g. lethal arrhythmia caused by Torsade de pointes and drug-induced long QT syndrome) from other causes of a long QT interval. Moreover, it is unknown how long the nutritional status would need to be altered in order to affect the risk of sudden cardiac death caused by a prolonged QT interval. However, there is accumulating evidence suggesting that the dietary electrolytes are a sensitive factor that can predict the incidence of CVD and mortality (1–5). Moreover, a prolonged QTc interval has been observed to be associated with future sudden cardiac death and CVD (6–8). Therefore, the results of the present study showing the link between the dietary electrolyte levels and the QTc interval may confirm the hypothesis that a high sodium intake and a low potassium intake leads to the occurrence of future cardiac sudden death and the incidence of CVD. Based on our results, we consider that it is necessary to perform dietary counseling, especially focusing on the sodium and potassium intake, depending on the body mass. Additional research in a large number of subjects will be required to more precisely clarify the mechanisms, clinical implications and associations between the dietary electrolytes and the QTc interval following diet intervention. CONCLUSIONS In this study, the association between the nutritional status and QTc interval was investigated in elderly subjects. As a result, it was found that the QTc interval was significantly longer in the low and high BMI groups compared to the moderate BMI groups in both genders. A stepwise multiple regression analysis showed that the QTc interval was independently associated with the potassium intake in the low BMI group and the sodium intake in the high BMI group in both genders. These results suggest that the body mass, especially lean body mass and overweight, were associated with a prolonged QTc interval and dietary electrolytes in elderly subjects. Based on our results, we consider that it is necessary to perform dietary counseling, especially focusing on the sodium and potassium intake, depending on the body mass. Conflict of interest statement There are no conflicts of interest associated with this work. Acknowledgments We acknowledge the members of the Laboratory of

QTc Interval and Dietary Electrolyte

Exercise Physiology of Fukuoka University for their help with the data evaluation. We are grateful to the participants of this study. This work was performed with the support of the Fukuoka University Institute for Physical Activity via a Technology Scientific Research Budget Basic Research Grant (No. A19200049, Strategic Research Infrastructure) from the Ministry of Education, Culture, Sports, Science and Technology of Japan, and the Central Research Institute of Fukuoka University (No. 136009). REFERENCES 1) Geleijnse JM, Witteman JC, Stijnen T, Kloos MW, Hofman A, Grobbee DE. 2007. Sodium and potassium intake and risk of cardiovascular events and all-cause mortality: the Rotterdam Study. Eur J Epidemiol 22: 763–770. 2) Umesawa M, Iso H, Date C, Yamamoto A, Toyoshima H, Watanabe Y, Kikuchi S, Koizumi A, Kondo T, Inaba Y, Tanabe N, Tamakoshi A; JACC Study Group. 2008. Relations between dietary sodium and potassium intakes and mortality from cardiovascular disease: the Japan Collaborative Cohort Study for Evaluation of Cancer Risks. Am J Clin Nutr 88: 195–202. 3) Yang Q, Liu T, Kuklina EV, Flanders WD, Hong Y, Gillespie C, Chang MH, Gwinn M, Dowling N, Khoury MJ, Hu FB. 2011. Sodium and potassium intake and mortality among US adults: prospective data from the Third National Health and Nutrition Examination Survey. Arch Intern Med 171: 1183–1191. 4) Bazzano LA, He J, Ogden LG, Loria C, Vupputuri S, Myers L, Whelton PK. 2001. Dietary potassium intake and risk of stroke in US men and women: National Health and Nutrition Examination Survey I epidemiologic follow-up study. Stroke 32: 1473–1480. 5) Alderman MH, Cohen HW. 2012. Dietary sodium intake and cardiovascular mortality: controversy resolved? Am J Hypertens 25: 727–734. 6) Dekker JM, Schouten EG, Klootwijk P, Pool J, Kromhout D. 1994. Association between QT interval and coronary heart disease in middle-aged and elderly men. The Zutphen Study. Circulation 90: 779–785. 7) Straus SM, Kors JA, De Bruin ML, van der Hooft CS, Hofman A, Heeringa J, Deckers JW, Kingma JH, Sturkenboom MC, Stricker BH, Witteman JC. 2006. Prolonged QTc interval and risk of sudden cardiac death in a population of older adults. J Am Coll Cardiol 47: 362–367. 8) Dekker JM, Crow RS, Hannan PJ, Schouten EG, Folsom AR; ARIC Study. 2004. Heart rate-corrected QT interval prolongation predicts risk of coronary heart disease in black and white middle-aged men and women: The ARIC Study. J Am Coll Cardiol 43: 565–571. 9) Dekker JM, Feskens EJ, Schouten EG, Klootwijk P, Pool J, Kromhout D. 1996. QTc duration is associated with levels of insulin and glucose intolerance. The Zutphen Study. Diabetes 45: 376–380. 10) Festa A, Agostino RD Jr, Rautaharju P, Mykkanen L, Haffner SM. 2000. Relation of systemic blood pressure, left ventricular mass, insulin sensitivity and coronary artery disease to QT interval duration in nondiabetic and type 2 diabetic subjects. Am J Cardiol 86: 1117–1122. 11) Rautaharju PM, Zhou SH, Wong S, Chalhoun HP, Berenson CS, Prineas R, Davignon A. 1992. Sex difference in the evolution of the electrocardiographic QT interval with age. Can J Cardiol 8: 690–695.

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Influence of Dietary Sodium and Potassium Intake on the Heart Rate Corrected-QT Interval in Elderly Subjects.

It is well known that imbalances in the dietary electrolytes are associated with a significantly higher incidence of cardiovascular disease (CVD). On ...
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