Being Conscious of Water Intake Positively Associated with Sufficient Non-Alcohol Drink Intake Regardless of Seasons and Reasons in Healthy Japanese; the KOBE Study: A Cross Sectional Study
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Population
2.2. Evaluation of Non-Alcoholic and Alcoholic Drink Intake
2.3. Data Collection for Characteristics
2.4. Statistical Analysis
2.5. Ethics Approval and Consent to Participate
3. Results
3.1. Demographics Characteristics of the Participants and CWI
3.2. The Reasons for Being CWI According to Seasons
3.3. The Amount of Beverage Intake and Its Details, According to CWI
3.4. Association between Being Conscious of Water Intake and the Amount of Beverages Intake: Uni- and Multivariate Linear Regression Analyses.
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Steg, P.G.; Bhatt, D.L.; Wilson, P.W.; D’Agostino, R.; Ohman, E.M.; Röther, J.; Liau, C.S.; Hirsch, A.T.; Mas, J.L.; Ikeda, Y.; et al. One-Year Cardiovascular Event Rates in Outpatients With Atherothrombosis. JAMA 2007, 297, 1197–1206. [Google Scholar] [CrossRef] [PubMed]
- Kubo, M.; Kiyohara, Y.; Kato, I.; Tanizaki, Y.; Arima, H.; Tanaka, K.; Nakamura, H.; Okubo, K.; Iida, M. Trends in the Incidence, Mortality, and Survival Rate of Cardiovascular Disease in a Japanese Community. Stroke 2003, 34, 2349–2354. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Nishikawa, T.; Miyamatsu, N.; Higashiyama, A.; Hojo, M.; Nishida, Y.; Fukuda, S.; Hirata, T.; Ichiura, K.; Kubota, Y.; Kubo, S.; et al. Daily Habit of Water Intake in Patients with Cerebral Infarction before its Onset; Comparison with a Healthy Population: A Cross-Sectional Study. Cerebrovasc. Dis. 2019, 47, 143–150. [Google Scholar] [CrossRef] [PubMed]
- Cui, R.; Iso, H.; Eshak, E.S.; Maruyama, K.; Tamakoshi, A.; Group, J.S. Water intake from foods and beverages and risk of mortality from CVD: the Japan Collaborative Cohort (JACC) Study. Public Health Nutr. 2018, 21, 3011–3017. [Google Scholar] [CrossRef] [Green Version]
- Venketasubramanian, N.; Yoon, B.W.; Pandian, J.; Navarro, J.C. Stroke Epidemiology in South, East, and South-East Asia: A Review. J. Stroke 2017, 19, 286–294. [Google Scholar] [CrossRef]
- Huang, C.Y. Nutrition and stroke. Asia Pac. J. Clin. Nutr. 2007, 16, 266–274. [Google Scholar]
- Rodriguez, G.J.; Cordina, S.M.; Vazquez, G.; Suri, M.F.; Kirmani, J.F.; Ezzeddine, M.A.; Qureshi, A.I. The hydration influence on the risk of stroke (THIRST) study. Neurocritical Care 2009, 10, 187–194. [Google Scholar] [CrossRef]
- Basu, R.; Samet, J.M. Relation between elevated ambient temperature and mortality: A review of the epidemiologic evidence. Epidemiol. Rev. 2002, 24, 190–202. [Google Scholar] [CrossRef]
- Nadav, L.; Gur, A.Y.; Korczyn, A.D.; Bornstein, N.M. Stroke in hospitalized patients: are there special risk factors? Cerebrovasc. Dis. 2002, 13, 127–131. [Google Scholar] [CrossRef]
- Swerdel, J.N.; Janevic, T.M.; Kostis, W.J.; Faiz, A.; Cosgrove, N.M.; Kostis, J.B.; Myocardial Infarction Data Acquisition System Study, G. Association Between Dehydration and Short-Term Risk of Ischemic Stroke in Patients with Atrial Fibrillation. Transl. Stroke Res. 2017, 8, 122–130. [Google Scholar] [CrossRef]
- Ma, J.; Ma, Y.; Dong, B.; Bandet, M.V.; Shuaib, A.; Winship, I.R. Prevention of the collapse of pial collaterals by remote ischemic perconditioning during acute ischemic stroke. J. Cereb Blood Flow. Metab. 2017, 37, 3001–3014. [Google Scholar] [CrossRef] [PubMed]
- Song, S.H.; Kim, J.H.; Lee, J.H.; Yun, Y.-M.; Choi, D.-H.; Kim, H.Y. Elevated blood viscosity is associated with cerebral small vessel disease in patients with acute ischemic stroke. BMC Neurol. 2017, 17, 20. [Google Scholar] [CrossRef] [PubMed]
- Hadi, H.; D’Souza, S.; El-Omar, M. Hypovolemia-induced severe coronary spasm leading to acute myocardial infarction. Exp. Clin. Cardiol. 2012, 17, 74–76. [Google Scholar] [PubMed]
- European Food Safety Authority (EFSA). Scientific Opinion on Dietary Reference Values for water. EFSA J. 2010, 8, 1459. [Google Scholar]
- Mastrangelo, G.; Fedeli, U.; Visentin, C.; Milan, G.; Fadda, E.; Spolaore, P. Pattern and determinants of hospitalization during heat waves: an ecologic study. BMC Public Health 2007, 7, 200. [Google Scholar] [CrossRef]
- Kenefick, R.W.; Hazzard, M.P.; Mahood, N.V.; Castellani, J.W. Thirst sensations and AVP responses at rest and during exercise-cold exposure. Med. Sci. Sports Exerc. 2004, 36, 1528–1534. [Google Scholar] [CrossRef]
- Hynynen, M.; Ilmarinen, R.; Tikkanen, I.; Fyhrquist, F. Plasma atrial natriuretic factor during cold-induced diuresis. Graefe’s Arch. Clin. Exp. Ophthalmol. 1993, 67, 286–289. [Google Scholar] [CrossRef]
- Hong, Y.-C.; Rha, J.-H.; Lee, J.-T.; Ha, E.-H.; Kwon, H.-J.; Kim, H. Ischemic Stroke Associated with Decrease in Temperature. Epidemiology 2003, 14, 473–478. [Google Scholar] [CrossRef]
- Gomes, J.; Damasceno, A.; Carrilho, C.; Lobo, V.; Lopes, H.; Madede, T.; Pravinrai, P.; Silva-Matos, C.; Diogo, D.; Azevedo, A.; et al. The effect of season and temperature variation on hospital admissions for incident stroke events in Maputo, Mozambique. J. Stroke Cerebrovasc. Dis. 2014, 23, 271–277. [Google Scholar] [CrossRef]
- Vodonos, A.; Novack, V.; Horev, A.; Abu Salameh, I.; Lotan, Y.; Ifergane, G. Do Gender and Season Modify the Triggering Effect of Ambient Temperature on Ischemic Stroke? Women’s Health Issues 2017, 27, 245–251. [Google Scholar] [CrossRef]
- Volkert, D.; Kreuel, K.; Stehle, P. “Nutrition beyond 65”--amount of usual drinking fluid and motivation to drink are interrelated in community-living, independent elderly people. Z Gerontol. Geriatr. 2004, 37, 436–443. [Google Scholar] [CrossRef] [PubMed]
- Higashiyama, A.; Wakabayashi, I.; Kubota, Y.; Adachi, Y.; Hayashibe, A.; Nishimura, K.; Sugiyama, D.; Kadota, A.; Imano, H.; Miyamatsu, N.; et al. Does high-sensitivity C-reactive protein or low-density lipoprotein cholesterol show a stronger relationship with the cardio-ankle vascular index in healthy community dwellers? the KOBE study. J. Atheroscler. Thromb. 2012, 19, 1027–1034. [Google Scholar] [CrossRef] [PubMed]
- Hirata, T.; Higashiyama, A.; Kubota, Y.; Nishimura, K.; Sugiyama, D.; Kadota, A.; Nishida, Y.; Imano, H.; Nishikawa, T.; Miyamatsu, N.; et al. HOMA-IR Values are Associated With Glycemic Control in Japanese Subjects Without Diabetes or Obesity: The KOBE Study. J. Epidemiol. 2015, 25, 407–414. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sugiyama, D.; Higashiyama, A.; Wakabayashi, I.; Kubota, Y.; Adachi, Y.; Hayashibe, A.; Kawamura, K.; Kuwabara, K.; Nishimura, K.; Kadota, A.; et al. The Relationship between Lectin-Like Oxidized Low-Density Lipoprotein Receptor-1 Ligands Containing Apolipoprotein B and the Cardio-Ankle Vascular Index in Healthy Community Inhabitants: The KOBE Study. J. Atheroscler. Thromb. 2015, 22, 499–508. [Google Scholar] [CrossRef] [Green Version]
- Kubota, Y.; Higashiyama, A.; Imano, H.; Sugiyama, D.; Kawamura, K.; Kadota, A.; Nishimura, K.; Miyamatsu, N.; Miyamoto, Y.; Okamura, T. Serum polyunsaturated fatty acid composition and serum high-sensitivity C-reactive protein levels in healthy Japanese residents: The KOBE study. J. Nutr. Health Aging 2015, 19, 719–728. [Google Scholar] [CrossRef]
- Tatsumi, Y.; Higashiyama, A.; Kubota, Y.; Sugiyama, D.; Nishida, Y.; Hirata, T.; Kadota, A.; Nishimura, K.; Imano, H.; Miyamatsu, N.; et al. Underweight Young Women Without Later Weight Gain Are at High Risk for Osteopenia After Midlife: The KOBE Study. J. Epidemiol. 2016, 26, 572–578. [Google Scholar] [CrossRef] [Green Version]
- Chan, J.; Knutsen, S.F.; Blix, G.G.; Lee, J.W.; Fraser, G.E. Water, other fluids, and fatal coronary heart disease: the Adventist Health Study. Am. J. Epidemiol. 2002, 155, 827–833. [Google Scholar] [CrossRef]
- Okamura, T.; Tanaka, T.; Yoshita, K.; Chiba, N.; Takebayashi, T.; Kikuchi, Y.; Tamaki, J.; Tamura, U.; Minai, J.; Kadowaki, T.; et al. Specific alcoholic beverage and blood pressure in a middle-aged Japanese population: the High-risk and Population Strategy for Occupational Health Promotion (HIPOP-OHP) Study. J. Hum. Hypertens. 2004, 18, 9–16. [Google Scholar] [CrossRef]
- Worthley, L.I.G.; Guerin, M.; Pain, R.W. For Calculating Osmolality, the Simplest Formula is the Best. Anaesth. Intensiv. Care 1987, 15, 199–202. [Google Scholar] [CrossRef]
- Tanaka, T.; Okamura, T.; Miura, K.; Kadowaki, T.; Ueshima, H.; Nakagawa, H.; Hashimoto, T. A simple method to estimate populational 24-h urinary sodium and potassium excretion using a casual urine specimen. J. Hum. Hypertens. 2002, 16, 97–103. [Google Scholar] [CrossRef] [Green Version]
- Food and Nutrition Board, N.A. Dietary Reference Intakes for Water, Potassium, Sodium, Chloride, and Sulfate; The National Academies Press: Washington, DC, USA, 2004. [Google Scholar]
- Valtin, H. (With the Technical Assistance of Sheila A. Gorman). “Drink at least eight glasses of water a day.” Really? Is there scientific evidence for “8 × 8”? Am. J. Physiol. Integr. Comp. Physiol. 2002, 283, R993–R1004. [Google Scholar] [CrossRef] [PubMed]
- Stookey, J. The diuretic effects of alcohol and caffeine and total water intake misclassification. Eur. J. Epidemiol. 1999, 15, 181–188. [Google Scholar] [CrossRef] [PubMed]
- Tayie, F.A.; Beck, G.L.; Beck, G.L. Alcoholic beverage consumption contributes to caloric and moisture intakes and body weight status. Nutrition 2016, 32, 799–805. [Google Scholar] [CrossRef] [PubMed]
- Maughan, R.J.; Griffin, J. Caffeine ingestion and fluid balance: a review. J. Hum. Nutr. Diet. 2003, 16, 411–420. [Google Scholar] [CrossRef]
- Killer, S.C.; Blannin, A.K.; Jeukendrup, A.E. No Evidence of Dehydration with Moderate Daily Coffee Intake: A Counterbalanced Cross-Over Study in a Free-Living Population. PLoS ONE 2014, 9, e84154. [Google Scholar] [CrossRef]
- Yoshihara, T.; Zaitsu, M.; Shiraishi, F.; Arima, H.; Takahashi-Yanaga, F.; Arioka, M.; Kajioka, S.; Sasaguri, T. Influence of genetic polymorphisms and habitual caffeine intake on the changes in blood pressure, pulse rate, and calculation speed after caffeine intake: A prospective, double blind, randomized trial in healthy volunteers. J. Pharmacol. Sci. 2019, 139, 209–214. [Google Scholar] [CrossRef]
- Nakagawa, H.; Niu, K.; Hozawa, A.; Ikeda, Y.; Kaiho, Y.; Ohmori-Matsuda, K.; Nakaya, N.; Kuriyama, S.; Ebihara, S.; Nagatomi, R.; et al. Impact of Nocturia on Bone Fracture and Mortality in Older Individuals: A Japanese Longitudinal Cohort Study. J. Urol. 2010, 184, 1413–1418. [Google Scholar] [CrossRef]
- Link, B.G.; Phelan, J. Social Conditions As Fundamental Causes of Disease. J. Health Soc. Behav. 1995, 35, 80. [Google Scholar] [CrossRef] [Green Version]
- Zaitsu, M.; Kato, S.; Kim, Y.; Takeuchi, T.; Sato, Y.; Kobayashi, Y.; Kawachi, I. Occupational Class and Risk of Cardiovascular Disease Incidence in Japan: Nationwide, Multicenter, Hospital-Based Case-Control Study. J. Am. Hear. Assoc. 2019, 8, e011350. [Google Scholar] [CrossRef]
- Fukushima, Y.; Ohie, T.; Yonekawa, Y.; Yonemoto, K.; Aizawa, H.; Mori, Y.; Watanabe, M.; Takeuchi, M.; Hasegawa, M.; Taguchi, C.; et al. Coffee and Green Tea As a Large Source of Antioxidant Polyphenols in the Japanese Population. J. Agric. Food Chem. 2009, 57, 1253–1259. [Google Scholar] [CrossRef]
- Ji, K.; Kim, Y.; Choi, K. Water intake rate among the general Korean population. Sci. Total Environ. 2010, 408, 734–739. [Google Scholar] [CrossRef] [PubMed]
- Takahashi, N.; Nakao, R.; Ueda, K.; Ono, M.; Kondo, M.; Honda, Y.; Hashizume, M. Community Trial on Heat Related-Illness Prevention Behaviors and Knowledge for the Elderly. Int. J. Environ. Res. Public Health 2015, 12, 3188–3214. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Flynn, A.; McGreevy, C.; Mulkerrin, E. Why do older patients die in a heatwave? Qjm Int. J. Med. 2005, 98, 227–229. [Google Scholar] [CrossRef] [PubMed]
Overall (n = 988) | Consciousness of Water Intake | |||
---|---|---|---|---|
Conscious | Not Conscious | p Value | ||
(n = 644) | (n = 344) | |||
Women | 698 (70.6%) | 464 (72.0%) | 234 (68.0%) | 0.185 |
Age (y.o.) | 61.0 ± 8.6 | 62.1 ± 8.1 | 58.9 ± 9.0 | < 0.001 |
Height (m) | 159.1 ± 7.7 | 158.6 ± 7.6 | 160.0 ± 7.8 | 0.009 |
Weight (kg) | 54.8 ± 9.9 | 54.3 ± 9.5 | 55.5 ± 10.6 | 0.075 |
BMI(Kg/m2) | 21.5 ± 2.8 | 21.5 ± 2.7 | 21.5 ± 3.0 | 0.707 |
Hypertension | 124 (12.6%) | 85 (13.2%) | 39 (11.3%) | 0.400 |
Dyslipidemia | 459 (46.5%) | 305 (47.4%) | 154 (44.8%) | 0.436 |
Surveyed months; May-Oct vs. Nov-Apr | < 0.001 | |||
May-Oct | 434 (43.9%) | 310 (48.1%) | 124 (36.0%) | |
Nov-Apr | 554 (56.3%) | 334 (51.9%) | 220 (64.0%) | |
Lifestyles | ||||
Current Smoker | 41 (4.1%) | 21 (3.3%) | 20 (5.8%) | 0.055 |
Current Drinker | 472 (47.8%) | 297 (46.1%) | 175 (50.9%) | 0.154 |
Eating quickly (yes) | 332 (33.6%) | 209 (32.5%) | 123 (35.8%) | 0.295 |
Dinner within 2 hours before going to bed: ≥ 3 days/a week | 138 (13.9%) | 76 (11.8%) | 62 (18.0%) | 0.007 |
Late evening snack: ≥ 3 days/a week | 191 (19.3%) | 113 (17.5%) | 78 (22.7%) | 0.052 |
Skipping breakfast: ≥ 3 days/a week | 58 (5.9%) | 36 (5.6%) | 22 (6.4%) | 0.608 |
Eating until full stomach (yes) | 588 (59.5%) | 373 (57.9%) | 215 (62.5%) | 0.162 |
Regular use of vitamin tablets or supplements: once or more a week | 350 (35.4%) | 241 (37.4%) | 109 (31.7%) | 0.073 |
Walking habit: ≥ 2 days/a week, for ≥ 30 min. | 557 (56.4%) | 392 (60.9%) | 165 (48.0%) | <0.001 |
Daily use of a pedometer | 330 (33.4%) | 240 (37.3%) | 90 (26.2%) | <0.001 |
Sleeping time (hours) | 6.1 ± 1.0 | 6.2 ± 0.9 | 6.1 ± 1.0 | 0.23 |
Good health status | 837 (84.7%) | 556 (86.3%) | 281 (81.7%) | 0.053 |
Socioeconomic factors | ||||
Living alone | 101 (10.2%) | 66 (10.2%) | 35 (10.2%) | 0.971 |
Educational background (bachelor’s or higher degree) | 355 (35.9%) | 210 (32.6%) | 145 (42.2%) | 0.003 |
Current/ex- blue-collar worker | 545 (55.2%) | 355 (55.1%) | 190 (55.2%) | 0.974 |
Laboratory data | ||||
Serum sodium (mEq/L) | 143.4 ± 1.5 | 143.4 ± 1.5 | 143.3 ± 1.6 | 0.159 |
Serum potassium (mEq/L) | 4.2 ± 0.3 | 4.2 ± 0.3 | 4.3 ± 0.3 | 0.475 |
Serum chloride (mEq/L) | 104.2 ± 1.8 | 104.2 ± 1.8 | 104.1 ± 1.8 | 0.216 |
Blood urea nitrogen (mg/dL) | 14.2 ± 3.2 | 14.4 ± 3.2 | 14.0 ± 3.3 | 0.122 |
Fasting blood glucose (mg/dL) | 89.0 ± 8.0 | 89.2 ± 7.9 | 89.7 ± 8.2 | 0.316 |
Calculated serum osmolarity (Osm/L) | 296.8 ± 3.5 | 297.0 ± 3.4 | 296.6 ± 3.6 | 0.058 |
Estimated daily salt intake (g/day) | 8.4± 1.9 | 8.5 ± 1.8 | 8.3 ± 1.9 | 0.154 |
Total (n = 644) | May-Oct. (n = 310) | Nov.-Apr. (n = 334) | ||||
---|---|---|---|---|---|---|
Prevention of heat stroke with/without other reasons | 263 | (40.8%) | 163 | (52.5%) | 89 | (26.6%) |
Prevention of cerebral stroke with/without other reasons | 104 | (16.1%) | 33 | (10.6%) | 71 | (21.2%) |
Prevention of both heat stroke and cerebral stroke with/without other reasons | 84 | (13.0%) | 38 | (12.2%) | 46 | (13.7%) |
Limited to other reasons excluding prevention of heat stroke or cerebral stroke | 193 | (29.9%) | 67 | (21.6%) | 131 | (39.2%) |
Free comments for being CWI other than heat stroke and cerebral stroke | ||||||
Prevention of dehydration | 35 | (5.4%) | 10 | (3.2%) | 25 | (7.4%) |
Health | 34 | (5.2%) | 10 | (3.2%) | 24 | (7.2%) |
Prevention of constipation | 28 | (4.3%) | 12 | (3.8%) | 16 | (4.7%) |
Habit since young | 27 | (4.1%) | 11 | (3.5%) | 16 | (4.7%) |
Sweating | 21 | (3.2%) | 9 | (2.9%) | 12 | (3.5%) |
Thirst | 20 | (3.1%) | 7 | (2.2%) | 13 | (3.8%) |
Preference for drinking NAD | 10 | (1.5%) | 4 | (1.2%) | 6 | (1.7%) |
Prevention of renal stone | 11 | (1.7%) | 3 | (0.9%) | 8 | (2.3%) |
Ameliorating blood viscosity | 11 | (1.7%) | 3 | (0.9%) | 8 | (2.3%) |
Metabolism | 9 | (1.3%) | 5 | (1.6%) | 4 | (1.1%) |
Maintaining renal function | 9 | (1.3%) | 3 | (0.9%) | 6 | (1.7%) |
Prevention of gout | 5 | (0.7%) | 1 | (0.3%) | 4 | (1.1%) |
Others | 22 | (3.4%) | 8 | (2.5%) | 14 | (4.1%) |
Simple tabulation of free comments | 242 | 86 | 156 |
Overall (n = 988) | Conscious of Water Intake | |||
---|---|---|---|---|
Conscious | Not Conscious | p Value | ||
(n = 644) | (n = 344) | |||
Beverage intake | ||||
Total beverage (ml/day) | 1851.1 ± 704.2 | 1963.0 ± 693.6 | 1641.7 ± 676.5 | < 0.001 |
Details of total beverage | ||||
Total NAD (ml/day) | 1717.4 ± 682.3 | 1841.4 ± 672.9 | 1485.3 ± 638.5 | < 0.001 |
Total alcohol beverage (ml/day) | 133.7 ± 242.1 | 121.6 ± 227.8 | 156.4 ± 265.8 | 0.040 |
Alcohol/total beverage | 0.069 ± 0.114 | 0.058 ± 0.101 | 0.088 ± 0.134 | < 0.001 |
Alcohol consumption (g/day of ethanol) | 9.2 ± 17.6 | 8.5 ± 17.6 | 10.5 ± 17.6 | 0.086 |
Details of NAD intake | ||||
Caffeine drink (ml/day) | 1015.8 ± 611.5 | 1039.7 ± 612.1 | 971.2 ± 608.8 | 0.093 |
Coffee (n = 715) | 428.6 ± 282.8 | 406.8 ± 268.1 (n = 457) | 467.2 ± 303.8 (n=258) | 0.008 |
Green tea (n = 721) | 750.3 ± 489.7 | 781.8 ± 480.0 (n = 478) | 688.2 ± 503.4 (n = 243) | 0.015 |
Black tea (n = 216) | 342.6 ± 257.0 | 333.0 ± 238.8 (n = 142) | 361.0 ± 289.6 (n = 74) | 0.448 |
Others with caffeine (n =124) | 663.4 ± 472.9 | 688.6 ± 447.1 (n= 91) | 593.7 ± 539.0 (n = 33) | 0.325 |
Decaffeinated beverages (ml/day) | 701.3 ± 587.9 | 801.7 ± 607.2 | 513.5 ± 498.9 | < 0.001 |
Water (n = 576) | 629.1 ± 418.6 | 678.6 ± 439.4 (n = 419) | 497.2 ± 323.0 (n = 157) | < 0.001 |
Barley tea (n = 166) | 815.6 ± 522.6 | 851.5 ± 500.5 (n = 107) | 750.5 ± 559.0 (n = 59) | 0.235 |
Milk or milk beverage (n = 404) | 241.6 ± 132.0 | 243.9 ± 128.7 (n = 286) | 236.1 ± 140.2 (n = 118) | 0.593 |
Isotonic drink (n = 74) | 385.8 ± 199.2 | 400.3 ± 192.6 (n = 59) | 329.0 ±221.3 (n = 15) | 0.267 |
Soy milk (n = 45) | 227.1 ± 153.4 | 217.1 ± 160.9 (n = 32) | 251.5 ± 135.8 (n = 13) | 0.502 |
Others without caffeine (n = 213) | 276.6 ± 213.6 | 281.3 ± 220.2 (n = 144) | 267.0 ± 200.4 (n = 69) | 0.649 |
Decaffeinated beverages/NAD | 0.396 ± 0.274 | 0.426 ± 0.273 | 0.339 ± 0.269 | < 0.001 |
Conscious of Water Intake | Univariate | Beta | p Value | Model 1 | Beta | p Value | Model 2 | Beta | p Value | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|
B | 95% CI | B | 95% CI | B | 95% CI | |||||||
NAD intake | ||||||||||||
Not conscious | ref. | ref. | ref. | |||||||||
Conscious | 356.1 | (269.5, 442.8) | 0.25 | < 0.001 | 317.2 | (230.7, 403.7) | 0.22 | < 0.001 | 318.1 | (231.3, 405.0) | 0.22 | <0.001 |
Alcohol intake | ||||||||||||
Not conscious | ref. | ref. | ref. | |||||||||
Conscious | −34.8 | (−55.4, −3.1) | -0.07 | 0.031 | −21.3 | (-51.2, 8.5) | −0.04 | 0.162 | −22.5 | (−48.1, 3.0) | -0.04 | 0.084 |
Caffeine beverage intake | ||||||||||||
Not conscious | ref. | ref. | ref. | |||||||||
Conscious | 68.5 | (−11.5, 148.6) | 0.05 | 0.093 | 54.4 | (−26.9, 135.7) | 0.04 | 0.189 | 61.5 | (−20.2, 143.3) | 0.05 | 0.140 |
Decaffeinated beverage intake | ||||||||||||
Not conscious | ref. | ref. | ref. | |||||||||
Conscious | 287.5 | (212.6, 362.5) | 0.23 | < 0.001 | 262.8 | (189.1, 336.5) | 0.21 | < 0.001 | 262.8 | (189.1, 336.5) | 0.21 | < 0.001 |
Total beverage intake | ||||||||||||
Not conscious | ref. | ref. | ref. | |||||||||
Conscious | 321.3 | (231.2, 411.4) | 0.22 | < 0.001 | 295.9 | (205.4, 386.3) | 0.20 | < 0.001 | 295.6 | (205.4, 385.8) | 0.20 | < 0.001 |
NAD intake | ||||||||||||
Not conscious | ref. | ref. | ref. | |||||||||
Conscious | 361.0 | (253.2, 468.8) | 0.24 | < 0.001 | 334 | (226.0, 442.1) | 0.22 | < 0.001 | 339.8 | (230.5, 449.1) | 0.23 | < 0.001 |
Alcohol intake | ||||||||||||
Not conscious | ref. | ref. | ref. | |||||||||
Conscious | −31.4 | (−58.0, −4.8) | −0.09 | 0.021 | −25.3 | (−52.4, 1.7) | 0.07 | 0.066 | −20.9 | (−43.2, 1.4) | −0.06 | 0.066 |
Caffeine beverage intake | ||||||||||||
Not conscious | ref. | ref. | ref. | |||||||||
Conscious | 92.8 | (−5.9, 191.7) | 0.07 | 0.065 | 76.4 | (−24.1, 176.9) | 0.06 | 0.136 | 83.3 | (−18.6, 185.3) | 0.06 | 0.109 |
Decaffeinated beverage intake | ||||||||||||
Not conscious | ref. | ref. | ref. | |||||||||
Conscious | 268.1 | (178.8, 357.4) | 0.22 | < 0.001 | 257.6 | (170.1, 345.1) | 0.21 | < 0.001 | 256.5 | (168.3, 344.7) | 0.21 | < 0.001 |
Total beverage intake | ||||||||||||
Not conscious | ref. | ref. | ref. | |||||||||
Conscious | 329.6 | (219.5, 439.7) | 0.22 | < 0.001 | 308.7 | (198.2, 419.2) | 0.20 | < 0.001 | 318.9 | (207.7, 430.2) | 0.21 | < 0.001 |
NAD intake | ||||||||||||
Not conscious | ref. | ref. | ref. | |||||||||
Conscious | 324.6 | (184.4, 464.7) | 0.26 | < 0.001 | 275.5 | (134.2, 416.7) | 0.22 | < 0.001 | 310.6 | (161.5, 459.7) | 0.25 | < 0.001 |
Alcohol intake | ||||||||||||
Not conscious | ref. | ref. | ref. | |||||||||
Conscious | −15.6 | (−91.6, 60.0) | −0.02 | 0.684 | −15.7 | (−94.3, 62.8) | −0.02 | 0.694 | −52.4 | (−121.0, 16.0) | −0.08 | 0.133 |
Caffeine beverage intake | ||||||||||||
Not conscious | ref. | ref. | ref. | |||||||||
Conscious | −7.2 | (−139.2, 124.7) | −0.01 | 0.914 | 0.67 | (−136.3, 137.6) | 0.00 | 0.992 | 14.3 | (−129.4, 158.0) | 0.01 | 0.845 |
Decaffeinated beverage intake | ||||||||||||
Not conscious | ref. | ref. | ref. | |||||||||
Conscious | 331.8 | (192.6, 471.1) | 0.27 | < 0.001 | 274.8 | (135.7, 413.9) | 0.22 | < 0.001 | 296.3 | (152.3, 440.2) | 0.24 | < 0.001 |
Total beverage intake | ||||||||||||
Not conscious | ref. | ref. | ref. | |||||||||
Conscious | 308.9 | (151.8, 466.0) | 0.22 | < 0.001 | 259.7 | (101.6, 417.9) | 0.19 | 0.001 | 258.1 | (95.8, 420.3) | 0.19 | 0.002 |
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Nishikawa, T.; Miyamatsu, N.; Higashiyama, A.; Kubota, Y.; Nishida, Y.; Hirata, T.; Sugiyama, D.; Kuwabara, K.; Kubo, S.; Miyamoto, Y.; et al. Being Conscious of Water Intake Positively Associated with Sufficient Non-Alcohol Drink Intake Regardless of Seasons and Reasons in Healthy Japanese; the KOBE Study: A Cross Sectional Study. Int. J. Environ. Res. Public Health 2019, 16, 4151. https://doi.org/10.3390/ijerph16214151
Nishikawa T, Miyamatsu N, Higashiyama A, Kubota Y, Nishida Y, Hirata T, Sugiyama D, Kuwabara K, Kubo S, Miyamoto Y, et al. Being Conscious of Water Intake Positively Associated with Sufficient Non-Alcohol Drink Intake Regardless of Seasons and Reasons in Healthy Japanese; the KOBE Study: A Cross Sectional Study. International Journal of Environmental Research and Public Health. 2019; 16(21):4151. https://doi.org/10.3390/ijerph16214151
Chicago/Turabian StyleNishikawa, Tomofumi, Naomi Miyamatsu, Aya Higashiyama, Yoshimi Kubota, Yoko Nishida, Takumi Hirata, Daisuke Sugiyama, Kazuyo Kuwabara, Sachimi Kubo, Yoshihiro Miyamoto, and et al. 2019. "Being Conscious of Water Intake Positively Associated with Sufficient Non-Alcohol Drink Intake Regardless of Seasons and Reasons in Healthy Japanese; the KOBE Study: A Cross Sectional Study" International Journal of Environmental Research and Public Health 16, no. 21: 4151. https://doi.org/10.3390/ijerph16214151
APA StyleNishikawa, T., Miyamatsu, N., Higashiyama, A., Kubota, Y., Nishida, Y., Hirata, T., Sugiyama, D., Kuwabara, K., Kubo, S., Miyamoto, Y., & Okamura, T. (2019). Being Conscious of Water Intake Positively Associated with Sufficient Non-Alcohol Drink Intake Regardless of Seasons and Reasons in Healthy Japanese; the KOBE Study: A Cross Sectional Study. International Journal of Environmental Research and Public Health, 16(21), 4151. https://doi.org/10.3390/ijerph16214151