Drinking microstructure in humans: A proof of concept study of a novel drinkometer in healthy adults☆
Graphical abstract
Direct measurement of human ingestive microstructure in high definition with the new drinkometer.
Introduction
In humans, initial insights on food intake and appetite can be provided by indirect measures such as verbal report of energy intake, food diaries, and dietary recall questionnaires (Adolphus et al., 2017; Gero, Steinert, le Roux, & Bueter, 2017; Paul, Rhodes, Kramer, Baer, & Rumpler, 2005). However, indirect measures are vulnerable to inaccuracy and, at best, only offer an estimate of the target behavior (Archer, Hand, & Blair, 2013; Dhurandhar et al., 2015; Hill & Davies, 2001; Livingstone, 1995; Livingstone & Black, 2003; Wehling & Lusher, 2017). Such methodological limitations can be improved by complementing existing findings with direct measures of feeding and drinking. With some notable exceptions discussed in subsequent pages, most studies to date that have applied direct measures of ingestive behavior in humans have focused mainly on what kind of food and how much of it was consumed, rather than investigating how the food was consumed. This might be due to the fact that the assessment of the temporal organization of ingestive behavior within a meal in humans poses significant methodological and conceptual challenges to researchers and study design (Adolphus et al., 2017).
In rodent studies, however, the temporal analysis of ingestive behavior has been very effectively exploited for decades (Blundell, 1986; Davis, 1989; Davis & Smith, 1988; Davis, Smith, Singh, & McCann, 2001; Kissileff, 2000). Such assessments with solid food can be obtained by direct visual observation, measurements of the weight of the nutrient container at regular intervals, or by using computerized feeders that record meal intake (Paulus, Geyer, & Sternberg, 1998; Tolkamp & Kyriazakis, 1999). The temporal structure of fluid intake in rodents can be conveniently assessed by measuring licking with electrical contact circuits, as first done by Hill et al. (Hill & Stellar, 1951) or with photobeams (Gril, 1987; Spector AC, 2004; Spector & Smith, 1984; Weijnen, 1998). In these cases continuous recording of drinking over time can occur without disturbing the animal (Smith, 2000).
Rats and mice structure their feeding and drinking behavior in clusters of events separated by pauses of various lengths. Very long pauses on the order of minutes or hours define meals, whereas shorter pauses define bursts of ingestion within a meal (Davis, 1989; Spector, Klumpp, & Kaplan, 1998; Tolkamp et al., 2011). Commonly, liquid diets are used so that licking can serve as an effective dependent measure of ingestion across time. For example, within meals rats lick in bursts separated by pauses. The interval between licks (the so-called inter-lick interval, ILI) is relatively uniform and is thought to be controlled by a central pattern generator (Corbit & Luschei, 1969; Davis, 1996; Halpern, 1977; Johnson, 2018; Lin, Pierce, Light, & Hayar, 2013; Wiesenfeld, Halpern, & Tapper, 1977). Indeed, from a neural standpoint, the brain circuits that turn this pattern generator on and off are the way that the central nervous system effects intake regulation (Travers, 1991; Travers, Dinardo, & Karimnamazi, 1997). The quantitative nature of these bursts, their number, size, duration, and temporal distribution, comprise what is referred to as the microstructure of drinking (Davis & Smith, 1992; Davis, Smith, & Singh, 1999; Spector et al., 1998; Spector & St John, 1998). Any intervention that affects total liquid diet intake can be entirely viewed as a function of its influence on licking patterns, which, through microstructural analysis, then can provide relevant information on the distinct motivational modulators of ingestive behavior, such as orosensory input, postoral events, physiological state, and prior experience (Daniels, 2010; Davis, 1989, 1996; Mathes, Bohnenkamp, le Roux, & Spector, 2015; Smith, 2001; Spector et al., 1998; Spector & St John, 1998). Because, in rodents, burst size (the number of licks in a burst) appears to increase monotonically as the concentration of a sugar solution is raised, it is thought to reflect the palatability of the stimulus. In contrast, burst number is non-monotonically related to sugar concentration and is heavily influenced by deprivation state (Davis & Perez, 1993). These microstructural parameters can reveal the impact of a given drug or neural manipulation on the controls of ingestive behavior (Schneider, Davis, Watson, & Smith, 1990; Wirtshafter, Davis, & Stratford, 2011). For example, when water-deprived rats are presented with a moderate concentration of a quinine solution (bitter to humans), they strikingly decrease their burst size and increase their burst number; the taste appears to be driving them away from the water hole and the physiological state appears to be driving them toward it. If the lingual gustatory nerves are transected, however, the licking microstructure returns to that seen with water (Spector & St John, 1998).
Two other microstructural parameters that appear to be heavily influenced by the orosensory properties of the stimulus in rodents are the size of the very first burst and the initial lick rate (in first min). The interpretive power of these two parameters is provided by an example from Mathes et al. (Mathes, Letourneau, Blonde, le Roux, & Spector, 2016). After Roux-en-Y gastric bypass (RYGB), nondeprived rats drank similar amounts of a fat emulsion as did sham-operated animals on the first 60-min test, but subsequently decreased their intake across the next few days until it was roughly half of that consumed by the control group. One possible interpretation is that the palatability of the stimulus is decreasing, perhaps as a result of the postingestive consequences of the fat ingestion. However, the size of the first burst as well as the first min licking rate increased across the same days in both groups, which had virtually identical values. This outcome is inconsistent with RYGB causing any decrease in the positive motivational potency of orosensory properties of the stimulus and thus the basis for the decreased intake in the RYGB rats relative to their control group lies somewhere else.
Given the context provided by the literature briefly summarized above, the aim of this study was to develop an instrument that enables the high definition assessment of the full spectrum of microstructural parameters of liquid ingestion over an entire drinking session in humans. We herein describe a novel “drinkometer”, which fulfills this aim by continuous recording the weight of a fluid reservoir, while participants drink via a tube. Drinking speed is derived from changes in weight over time and individual sucks and bursts including their respective volumes, durations and rates, as well as the pauses between them can be quantified. In the present methodological paper we report the technical features of the device, and details of the data processing algorithm, as well as results of a pilot study in normal weight human subjects to demonstrate feasibility.
Section snippets
General principles of the novel drinkometer
Fig. 1 illustrates the basic technical components of the drinkometer during an experiment. The measurement of drinking microstructure in humans involves the following steps: 1) the density of the test drink is computed before the start of each test-session by an ultrasonic distance sensor and an electronic weight sensor; 2) a polyethylene tube is immersed in the fluid reservoir and is filled by vacuum aspiration with a syringe; 3) the participant drinks via the tube while the weight of the
Study characteristics
The baseline characteristics of participants and their averaged reported night-sleep hours prior to drinking sessions are presented in Table 1. In the pooled analysis of all sessions, mean ± SD temperature of the fluid reservoir was 9.16 ± 1.26 °C. Further, the mean of Δ beginning session – end of session temperature within sessions was 0.63 ± 0.4 °C, indicating a high temperature stability of the test liquids throughout the sessions.
Identification of an optimal burst pause criterion
Results of the PDF with Kernel estimation and Gaussian
Discussion
This study demonstrates that the drinkometer is suitable for the detection of differences in the microstructural parameters of ingestive behavior within and between human subjects who consume fluids of different sucrose concentrations in fasted and non-fasted states. Characterization of ingestive behavior in this precise and quantitative manner has the potential to reveal fundamental principles of the control of food intake behavior in different experimental settings. Microstructural analysis
Final remarks
As mentioned at the start, the early meal measures, which precede the significant accumulation of the stimulus in postoral body compartments, are thought to be influenced by the orosensory properties of the stimulus and, in the context of a given physiological state, reflect their influence on the motivation to ingest. Microstructural patterns occurring later in the meal appear to be more influenced by post-ingestive/post-absorptive events and reflect the onset of satiation (Blundell et al.,
Authors' contribution
Study design: MB, AS, DG, RES.
Development of the “drinkometer” device (hardware + data acquisition software): JJ.
Development of data-processing algorithm: BF.
Data acquisition: DG.
Data analysis: DG, BF, LF, AS, MB.
Interpretation of data: MB, AS, DG, RES.
Drafting the manuscript: DG, MB, JJ, FB, AS.
Critically revision and final approval of the manuscript: AS, MB, DG, JJ, FB, RES, LF.
Disclosures
The authors have no commercial associations that might be a conflict of interest in relation to this article. R.E. Steinert is employed by DSM Nutritional Products.
Acknowledgments
We are grateful to all of the volunteers for having participated in this study. We acknowledge Daniel Kaufmann, MSc, Dominik Brügger, MSc, Richard Monteil, BSc and Jan Segessenmann, BSc from the Human-Centered Engineering Institute of Applied Sciences, Biel, Switzerland, for having contributed to the development of the drinkometer. We also thank Marcel André Schneider, MD for his help in statistical data-analysis in R software and Nikolaus Wick-Mazzarda for the photography.
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Communication: The study was presented as oral presentation at the 26th Annual Meeting of the Society for the Study of Ingestive Behavior in Bonita Springs, Florida, USA, on 20 July 2018