Gomez, Pierrick PhD; Mariani, Sabine Boesen PhD; Lambert, Jean-Louis PhD; Monrozier, Romain PhD
Pierrick Gomez, PhD, is from the Reims Management School and DRM Research Center, Université Paris Dauphine. His research focuses on the psychological mechanisms and motivations governing that underlie food decisions.
Sabine Boesen Mariani, PhD, is a behavior scientist at Danone Research.
Jean-Louis Lambert, PhD, is from the Reims Management School. His research interests focus on the sociological determinants of food consumption.
Romain Monrozier, PhD, is a behavior scientist at Danone Research.
This research was supported by Danone Research. Sabine Boesen Mariani and Romain Monrozier are employed as scientists by Danone Research. Pierrick Gomez and Jean-Louis Lambert serve as occasional consultants for Danone Research.
Correspondence: Sabine Boesen Mariani, PhD, Avenue de la Vauve, RD 128, Palaiseau, France ( firstname.lastname@example.org).
Insufficient water intake remains a significant health issue in many developed countries. Increasing data show that insufficient daily water intake may induce several chronic and acute diseases, particularly of the urinary and renal systems.1,2 In France, despite recommendations, approximately 70% of the adult population drinks less than 1.5 L of fluids per day.3 Recent results have suggested that increasing water intake in the French population above 2 L a day could lead to significant reduction in health costs associated with urolithiasis.4
Public health strategies that increase access to healthy options have proven their effectiveness.5 These interventions are based on evidence showing the limited capacity of the human information processing system and encourage the development of an environment that is more favorable to the adoption of health behaviors.6 Furthermore, interventions consisting of improving access to healthy products by modifying the presentation of choice options have proven their efficiency.7 For example, improving access to water by installing water fountains in schools significantly increases water intake levels,8,9 likely as a result of the visual proximity of the healthy option. Indeed, water intake during a meal increases significantly when water is within reach, compared with when it is located at a distance of just 6 m.10
In line with such research, we aimed at testing the effectiveness of combining education and easy access to water for women with low water intake. We anticipate that creating a favorable environment by making water accessible will reduce the cognitive effort required5 and facilitate the adoption of the targeted behavior, whereas providing educational content will help to maintain the new behavior over the time. To the best of our knowledge, no empirical research has addressed these objectives in relation to water intake in a single study.
Participants (25–65 years old) from 5 French cities were recruited by telephone following representativeness quotas on age, socio-professional categories, and household size. To be eligible, participants had to drink a small quantity of fluids (<1.2 L of total fluid intake and <300 mL of water per day), were to be healthy (ie, absence of chronic diseases), were to not be following any particular diet, and not reject the bottled water used in the intervention. The research was conducted between October 2010 and October 2011, and 310 participants who met the criteria agreed to sign a consent form. Participants have been informed of the aims, the methods, the sponsor, and the potential benefits or risks of the intervention. Participants were free to follow or not the given recommendations and to stop the protocol whenever they wished.
Of the initial 310 participants, 52 were excluded because their total fluid intake was too high (>1.2 L). In addition, 80 were excluded because of missing data after phase 1. At the end of phase 2, 155 participants remained in the study, and 143 remained for the 12-month follow-up period (retention rate, 80%).
After collecting baseline data, we conducted a 2-phase intervention over a 5-month period. In addition, our study featured several follow-ups (1 week after the second intervention and 6 months after the second intervention). Phase 1 lasted 4 weeks and entailed providing free bottled water at home to all the participants. Phase 2 targeted only those participants who did not increase their water intake sufficiently during phase 1.
Bottles of 0.5 L were delivered at participants’ homes. On the basis of goal-setting theory,11 we issued progressive consumption recommendations to participants to avoid motivation decreases. Participants were asked to drink 0.5 L of water every day during the first 5 days of phase 1 and to increase their water intake regularly to reach 1.5 L at the end of week 2. No instructions were provided for the third week. Intake data were collected 1 week after the end of phase 1.
The sample was split into 2 groups according to the participant’s increase in water intake during phase 1. The HIGH group consisted of participants who highly increased their water intake (consumed at least 1.0 L of water a day or increased their water intake by at least 150%), whereas the LOW group gathered those with lower increase. The LOW group continued to receive free bottled water at home for 4 additional months. These participants were also invited to attend 10 weekly online sessions, explaining water requirements and informing about related health benefits (such as cognitive and physical performance). The HIGH group was not stimulated; only their fluid intake was monitored. For both groups, 6 months after the end of phase 2, fluid intakes were again collected (free-living conditions).
The measures of fluid intake were conducted as baseline assessments at the end of the first and second stages of the program and then 12 months after the start of the study. Online diaries were used to assess total fluid and water intakes (7-day fluid-specific diary).12 To help participants to estimate quantities, the tool presented several images of containers (eg, glasses, mugs) with volume equivalency indicators. The integration of water intake into daily routine was assessed according to the Self-Report Index of Habit Strength13 using a 5-point agreement scale (α = .97).
We used the χ2 test and analysis of variance to compare the evolution of participants’ fluid intake at different points in time and to determine differences across groups of participants. For the assessment of the effectiveness of the 2 phases, we used t tests for paired samples and compared intake patterns for the same individuals at different times. Total fluid and water intakes at the baseline were compared with total fluid and water intakes at the end of phase 1, at the end of phase 2, and after 6 months (ie, 12 months after baseline). After phase 1, we systematically differentiated the participants into low or high water increase groups. The level of significance for all statistical tests was P < .05. All these analyses were carried out using SPSS (18.0) software.
Evolution of Water Intake: Phase 1
Water intake increased by 151% after 4 weeks (P < .001). Total fluid intake also increased by 84% (P < .001) in that same period. Drinking water habit strength also increased (P < .001).
After phase 1, the HIGH group participants drank, on average, 1149 mL of water, a 265% increase. The LOW group participants drank 522 mL of water (P < .001), which represented a 52% increase. We found no significant water intake or sociodemographic differences between the groups at baseline. The results are summarized in the Table.
Evolution of Water Intake: Phase 2
The results show a significant progression in the water intake of the LOW group participants: an increase of 67% between phases 1 and 2 (P < .001) and 154% compared with the baseline (P < .001). Total fluid intake also increased by 26% (P < .001) between phases and by 159% compared with the baseline (P < .001). Water intake became more habitual among these participants (P < .01). A comparison of the quantities of water and fluids consumed by participants of LOW versus HIGH groups showed that the differences recorded after phase 1 disappeared by the end of phase 2 (total fluid: HIGH group, 1425.5 mL; LOW group, 1279.8 mL; P = .23; water: HIGH group, 928.10 mL; LOW group, 871.85 mL; P = .58).
Evolution of Water Intake After 12 Months
On average, water intake increased significantly compared with the baseline, that is, by 163% (P < .001). The same trend is observed for total fluid intake (P < .001). Ultimately, LOW group participants reached the intake levels of the HIGH group participants. However, habit strength remained significantly higher in the latter group after 12 months (HIGH group, 33.97; LOW group, 28.00; P < .05).
Little research has tested the impacts on fluid intake obtained from programs that rely on the free and temporary provision of water.8,9 Our results show that a water intervention program helps low drinker participants to sustainably increase their water intake. Because these changes remained in place 6 months after the end of the program and as indicated by the habit strength index, behavior change had become habitual. Overall, participants increased their water intake by an average of 163%. The changes in consumption obtained were significantly higher than those found in previous studies.8,9 Our results thus confirm the importance of approaches that seek to improve the accessibility of healthy options,14 combined with educational content.
Despite its limitations (sample representativeness, difficulty to disentangle the impact of water affordance vs those of the educational program), our research shows very encouraging results and should drive researchers and practitioners to extend at a larger scale or to other populations similar programs combining access to water and education.
1. Strippoli G, Craig JC, Rochtchina E, Flood VM, Wang JJ, Mitchell P. Fluid and nutrient intake and risk of chronic kidney disease. Nephrology. 2011; 16:(3): 326–334.
2. Clark WF, Sontrop JM, Macnab JJ, et al. Urine volume and change in estimated GFR in a community-based cohort study. Clin J Am Soc Nephrol. 2011; 6:(11): 2634–2641.
3. Bellisle F, Thornton SN, Hebel P, Denizeau M, Tahiri M. A study of fluid intake from beverages in a sample of healthy French children, adolescents and adults. Eur J Clin Nutr. 2010; 64:(4): 350–355.
4. Lotan Y, Buendia Jimenez I, Lenoir-Wijnkoop I, et al. Primary prevention of nephrolithiasis is cost-effective for a national healthcare system. BJU Int. 2012;110(11):1060–1067.
5. Chandon P, Wansink B. Is food marketing making us fat? A multidisciplinary review. Foundations Trends Mark. 2011; 5:(3): 133–196.
6. Camerer C, Issacharoff S, Loewenstein G, O’Donoghue T, Rabin M. Regulation for conservatives: behavioral economics and the case for asymmetric paternalism. University of Pennsylvania Law Review. 2003;151(3):1211.
7. Thorndike AN, Sonnenberg L, Riis J, Barraclough S, Levy DE. A 2-phase labeling and choice architecture intervention to improve healthy food and beverage choices. Am J Public Health. 2012; 102:(3): 527–533.
8. Muckelbauer R, Libuda L, Clausen K, Toschke AM, Reinehr T, Kersting M. Promotion and provision of drinking water in schools for overweight prevention: randomized, controlled cluster trial. Pediatrics. 2009; 123:(4): e661–e667.
9. Patel AI, Bogart LM, Elliott MN, et al. Increasing the availability and consumption of drinking water in middle schools: a pilot study. Prev Chron Dis. 2011; 8:(3): 1–9.
10. Engell D, Kramer M, Malafi T, Salomon M, Lesher L. Effects of effort and social modeling on drinking in humans. Appetite. 1996; 26:(2): 129–138.
11. Locke EA, Latham GP . A Theory of Goal Setting and Task Performance. Englewood Cliffs, NJ: Prentice-Hall; 1990; .
12. Vergne S. Methodological aspects of fluid intake records and surveys. Nutr Today. 2012; 47:(4, suppl 1): S7–S10.
13. Verplanken B, Orbell S. Reflections on past behavior: a self-report index of habit strength. J Appl Soc Psychol. 2003; 33:(6): 1313–1330.
14. Loewenstein G, Brennan T, Volpp KG. Asymmetric paternalism to improve health behaviors. JAMA. 2007; 298:(20): 2415–2417.