The influence of music type and transmission mode on food intake and meal duration: An experimental study

Abstract

The influence of auditory stimuli and their transmission mode on food intake and meal duration was assessed in healthy adults (73 male, 74 female) under laboratory conditions. The participants (18–30 years old) were randomized to one of five lunch groups. Five conditions were compared: eating in silence (control condition), eating while listening to background music via loudspeakers, eating while listening to background music via headphones, eating while listening to pop songs with English vocals and eating while listening to pop songs with German vocals. Results showed no association between listening to songs with different emotion-arousing potential and the amount of food consumed. Within-group comparisons revealed longer meal durations while listening to English music and unfamiliar background music via headphones than while listening to familiar German pop songs. The difference with the control condition just failed to reach significance. No differences were found for transmission mode. Further studies to examine the influence of music on food intake and eating behaviour, especially under controlled conditions, are needed.

Keywords

auditory stimuli emotional arousal food intake meal duration music

Food intake is influenced by many different environmental factors (Stroebele & de Castro, 2004; Wansink, 2004) and, although the impact of the environment on our eating behaviour seems to be mainly to promote food intake (Berthoud, 2012), it is important to further explore and identify various influencing aspects of the environment to better intervene at both ends of the spectrum of nutrition-related disorders, such as obesity (Hetherington, 2007) and malnutrition (Kimber, Gibbs, Weekes, & Baldwin, 2015).

One environmental stimulus shown to impact food and fluid intake is music (Bellisle, Dalix, & Slama, 2004; Stroebele & de Castro, 2006). Music can influence and regulate mood states (Juslin & Sloboda, 2001, 2013; Sloboda, 2010) and the presence of music can elicit arousal by changing physiological responses, e.g., by increasing heart rate (Fairclough, van der Zwaag, Spiridon, & Westerink, 2014; Rickard, 2004; van der Zwaag, Westerink, & van den Broek, 2011). Furthermore, many musical characteristics themselves such as tempo, intensity, and mode have an effect on emotional arousal and appear to have different emotion-arousing qualities (van den Bosch, Salimpoor, & Zatorre, 2013; van der Zwaag et al., 2011). For instance, loud music appears to be more arousing than soft music (Privitera, Diaz, & Haas, 2014). Also, music with vocals appears to have higher arousing potential than music without vocals (Loui, Bachorik, Li, & Schlaug, 2013; Weiss, Trehub, & Schellenberg, 2012). Even the familiarity of the music seems to affect a person’s arousal. It is suggested that familiar music has a higher arousing level than unfamiliar music (Pereira et al., 2011; Yalch & Spangenberg, 2000). With different levels of arousal, different levels of distraction are also observed. The more someone is aroused by the music, the more he or she is distracted by it (Rickard, 2004).

In regard to the impact of music on eating behaviour, distraction has been identified as one of the potential mechanisms that explain increased food and fluid consumption (Bellisle & Dalix, 2001; Bellisle et al., 2004; Stroebele & de Castro, 2006). Several studies carried out in natural settings have shown that background noises or music influence eating behaviour, including the amount and speed of eating and drinking (Caldwell & Hibbert, 2002; McCarron & Tierney, 1989; Péneau, et al., 2009; Stafford & Dodd, 2013), money spent in a restaurant (Milliman, 1986), and taste perception (Crisinel, et al., 2012; North, 2012; Spence, 2012; Spence & Deroy, 2013). Previous literature suggests that patrons stay longer in a restaurant and consume more beverages with slow tempo background music (Milliman, 1986), while loud music is associated with increased soft drink and alcohol consumption (Guéguen, Jacob, Le Guellec, Morineau, & Lourel, 2008; McCarron & Tierney, 1989; Stafford & Dodd, 2013). Music is a complex stimulus and the effects of many of its properties, such as familiarity, on food intake or meal duration have not been studied.

Furthermore, the mode of music transmission, such as through the use of headphones, which is particularly popular among adolescents as well as students and used frequently under various circumstances such as working, commuting, or eating (Lenhart, 2009), might play a role when looking at the influence of music on eating behaviour. So far, only a few studies have looked at mode of music transmission (Kallinen & Ravaja, 2007; Kristjánsdóttir & Kristjánsdóttir, 2011; Lloyd, Coates, Knopp, Oram, & Rowbotham, 2009) ranging from transportation studies looking at changes in interpersonal space to studies examining the change in anxiety levels when using different forms of music transmission (Kristjánsdóttir & Kristjánsdóttir, 2011; Lee, Chao, Yiin, Chiang, & Chao, 2011). The aim of using headphones in these studies was to distract or reduce discomfort (and/or anxiety). No studies could be found that looked at mode of music transmission and its impact on eating behaviour.

Thus, the present study examined the influence of music differing in familiarity on meal duration and intake as well as exploring the importance of transmission mode. It was hypothesized that different types of music differing in familiarity and with it arousing potential (popular German and English vocal pop music versus background music) as well as the type of transmission (headphones versus loudspeakers) would affect meal duration and meal intake. Familiar vocal music was expected to be the most distracting and therefore leading to higher food intake and longer meal duration compared to background music and the control condition (Avila, Furnham, & McClelland, 2011; Weiss et al., 2012). Headphones were used to test whether participants would be more distracted by and focused on the music and therefore eat a larger portion than when eating without headphones.

Methods

Participants

Participants were recruited on the campus of the University of Hohenheim, Germany. Advertisements were posted on campus for a taste test with a free lunch, listing the main selection criteria (aged 18–30 years, being enrolled in an agricultural science or economics university programme or studying biology, being non-vegetarian). Exclusion criteria included smell, taste or hearing impairments and a highly restrained eating score as measured by the German version of the Dutch Eating Behavior Questionnaire (DEBQ) (van Strien, Frijters, Bergers, & Defares, 1986). An equal number of men and women were randomly assigned to one of the five groups.

Experimental design

Participants sat at a table in an empty room and had lunch alone. The five conditions were: 1) Participant ate in silence – control condition (C); 2) Participant ate with instrumental background music via loudspeakers (BL); 3) Participant ate with instrumental background music via headphones (BH); 4) Participant ate with English pop songs (E); 5) Participant ate with German pop songs (G).

In conditions BL, E and G, the auditory stimuli were presented over loudspeakers at a mean intensity of 48.1 dB (SD = 4.7, range = 35.7–60.8). The sound samples were calibrated using a WS1361C digital sound level meter (Wensn, China). Participants in the BL and BH conditions listened to an instrumental jazz piece in repeat mode with those in the BH condition wearing HDR 170 headphones (Sennheiser, China), which covered the ears completely. The jazz piece (“Holiday Memories” by Ronny Matthes, 109 BPM) was chosen for its similarity to music pieces used in high-end restaurants and other shopping establishments to mask ambient noise and was expected to be unfamiliar to the participants. Participants in group E listened to a variety of 15 vocal songs with English lyrics from several genres in randomized order (mean tempo = 105 BPM, SD = 13.74, range = 87–133). All songs were in the top 10 of the charts in Germany between the years 2001 and 2008. Condition G contained a selection of 16 German vocal songs (mean tempo = 107 BPM, SD = 13.6, range = 86–135) that were also in the top 10 of the charts between 2001 and 2008. This range of years was selected based on the age range of the students at this university (titles and artists are shown in the online supplementary material).

Lunch consisted of a typical German dish, including pork schnitzel (boneless pork flattened with a meat tenderizer, coated with flour, beaten eggs and bread crumbs, and then fried in a pan), Swabian pasta, broccoli, carrots, cauliflower and cream sauce. The menu was identical under all meal conditions. Men were presented with a plate containing a total of 1144 grams (280 g of schnitzel, 394 g of pasta, 250 g of vegetables, 220 g of sauce), while the plate for women contained a total of 864 g (280 g of schnitzel, 364 g of pasta, 200 g of vegetables, 120 g of sauce). Mineral water (330 ml) was served at room temperature. One of the male participants (who was excluded from data analysis) and none of the female participants finished their meal.

Data assessment

Participants’ ratings of hunger and appetite before the meal were assessed using a 10 cm visual analogue scale (VAS). Mood was assessed using a seven-point Likert scale (extremely bad to extremely good). Furthermore, liking of the aroma and visual presentation of the meal was rated on a seven-point Likert scale before the participants started eating. Participants were also asked to rate the palatability of the four meal components (schnitzel, pasta, vegetables and sauce) after lunch, each one on a separate VAS. For data analysis, the four mean ratings of palatability were summed to one rating (see Table 1). At the end of the meal, participants were asked whether they were sated or not and if they had eaten more, the same amount or less than usual. Participants’ mood ratings after the meal were again assessed with the seven-point Likert scale (extremely bad to extremely good) and ratings of comfort were assessed using a VAS. To determine meal duration, a stopwatch was started at the first bite and stopped when the last bite was swallowed. Food intake in grams was measured with a KE 924 digital scale (ADE, Germany).

Table 1.

Participants’ characteristics (means ± SD).

Group	C	BL	BH	E	G	p	F
n	29	29	31	29	29
Men / Women	14 / 15	14 / 15	16 / 15	15 / 14	14 / 15
Age (years)	22.90 ± 2.78	23.38 ± 2.18	22.19 ± 2.12	23.24 ± 2.90	23.52 ± 2.53	ns	1.340
BMI (kg/m²)	22.37 ± 3.37	23.27 ± 3.01	22.71 ± 3.20	23.96 ± 2.81	22.87 ± 4.89	ns	0.872
Hunger before (cm)	6.11 ± 1.94	6.15 ± 1.77	6.84 ± 1.44	6.68 ± 1.57	6.42 ± 1.59	ns	1.092
Appetite before (cm)	7.04 ± 1.69	6.90 ± 1.52	7.47 ± 1.20	7.46 ± 1.64	7.30 ± 1.62	ns	0.790
Mood before lunch	5.07 ± 1.22	5.41 ± 0.87	5.42 ± 0.50	5.38 ± 1.29	5.62 ± 1.08	ns	1.237
Mood after lunch	5.10 ± 1.26	5.52 ± 0.83	5.55 ± 0.68	5.59 ± 0.57	5.69 ± 0.60	ns	2.157
Change of mood	0.03 ± 0.82	0.10 ± 0.62	0.13 ± 0.56	0.10 ± 0.49	0.24 ± 0.69	ns	0.394
Comfortableness	5.21 ± 2.30	6.23 ± 1.94	6.43 ± 2.10	6.46 ± 1.93	6.51 ± 1.79	ns	2.110
Palatability Summarized (cm)	24.79 ± 5.30	24.51 ± 5.25	24.74 ± 5.65	25.41 ± 6.21	24.05 ± 6.21	ns	0.213
Schnitzel (cm)	5.98 ± 2.13	6.67 ± 1.63	6.71 ± 1.80	6.67 ± 2.00	6.52 ± 2.02	ns	0.747
Swabian Pasta (cm)	6.30 ± 1.86	6.86 ± 1.61	6.31 ± 1.74	6.81 ± 1.52	6.31 ± 2.05	ns	0.782
Vegetables (cm)	5.69 ± 2.05	4.66 ± 2.01	5.00 ± 2.06	5.22 ± 2.55	4.72 ± 2.03	ns	1.097
Cream sauce (cm)	6.82 ± 1.92	6.33 ± 2.14	6.71 ± 2.33	6.71 ± 2.60	6.73 ± 2.21	ns	0.209

Note. C = control group; BL = background loudspeakers; BH = background headphones; E = English vocal music; G = German vocal music.

Procedure

The present study was conducted according to the guidelines of the Declaration of Helsinki and all procedures were approved by the local Ethics Committee of the University of Hohenheim. Written consent was obtained on the study day, before participants ate the offered lunch. Data collection took place on weekdays between 11:30 and 14:00 between January and June of 2014. The experiment took place in a seminar room with a two-way mirror. Music (with the exception of the control condition) was played the entire time. Participants in the BH group were asked to put on the headphones before filling out the questionnaires and to leave them on until they had finished eating and completed the questionnaire. Participants were informed that they could eat as long as they wanted and as much as they pleased. The experimenters observed the participants from an adjacent room via a two-way mirror to determine meal duration. Served plates were weighed before and after consumption.

Statistics

On the basis of the studies by Bellisle and colleagues (Péneau et al., 2009; Mekhmoukh, Chapelot, & Bellisle, 2012), our power calculation indicated that 31 participants per group would be necessary in order to show a significant 10% difference if lunch intake was 800 g with a standard deviation of 110 g, the α risk set a 0.05 and the power at 0.8. Lunch size was based on similar meals typically served at the university canteen. The independent variable was the environmental condition (five levels, between-groups). The dependent variables were meal intake, meal duration, and ratings of hunger, appetite, mood, palatability and comfort. Comparisons between the five conditions were made using ANOVAs. Student’s t-tests were used to compare data between genders. Wilcoxon signed-rank tests were used to compare mood before and after the meal. Kruskal–Wallis or Mann–Whitney U-tests were used comparing multiple non-normally distributed data such as food intake and meal duration followed by post hoc Bonferroni tests where appropriate. Partial correlations (Pearson) with gender as a covariate were used to analyse the relationships between food intake and palatability, comfort, mood, hunger and appetite. Means and standard deviations are presented in the text and tables. Statistical significance level was set at p < 0.05. Statistical tests were carried out using IBM Statistic SPSS for Windows, version 22.0.

Results

The total sample consisted of 150 participants. One male participant was excluded since he indicated that he was still hungry after the meal. Another male participant was excluded due to a handicap that caused movement difficulties with the cutlery. One female was also excluded because she used her mobile phone during the meal. Therefore, the results from 147 participants (74 females and 73 males) were analysed. The mean age was 23.03 years (SD = 2.53). In the sample, 2.04% of the participants were underweight, 75.51% had normal weight, 19.73% were overweight and 2.72% were obese. There were no significant group differences in age, BMI, pre-meal hunger and appetite level, or palatability across conditions (see Table 1). Combining palatability ratings of all meal components showed mean palatability ratings over all participants of 24.70 cm out of a possible 40 cm (SD = 5.68). There were no significant differences between the meal conditions, F(4,142) = 0.213, p = 0.931, or gender, t(145) = −0.188, p = 0.851.

As a manipulation check, pre- and post-meal mood ratings revealed higher ratings for the music conditions compared to the control condition with a significant mood improvement after the meal in the music conditions, pre-meal mood: z = −1.374, p = 0.170; post-meal mood: z = 2.106, p = 0.035. Also, mood ratings after lunch were significantly better than before lunch within the four music conditions, z = −2.594, p = 0.009, whereas the mood did not change in the control condition, z = −0.188, p = 0.851. Furthermore, significantly higher ratings of comfort in all four music conditions compared to the control condition were observed, t(145) = −2.876, p = 0.005.

Across all conditions, there was no significant difference in total food intake when comparing auditory stimuli or transmission mode in general, χ²(4, N = 147) = 3.498, p = 0.478 (see Table 2), in male participants, χ²(4, N = 147) = 7.770, p = 0.1, or in female participants, χ²(4, N = 147) = 0.911, p = 0.923. No significant differences were found for music transmission (loudspeakers versus headphones; z = −0.844, p = 0.399) or type of music, χ²(3, N = 147) = 3.413, p = 0.332 (see Table 2).

Table 2.

Food intake and meal duration (means ± SD) across the five lunch conditions.

Group	C	BL	BH	E	G	p	χ²
Food intake (g)	642.31 ± 181.03	698.59 ± 216.35	727.32 ± 260.14	700.52 ± 222.76	613.41 ± 166.17	ns	3.498
Meal duration (min)	13:50 ± 3:15	14:09 ± 3:32	14:02 ± 3:59	11:32 ± 2:55	14:05 ± 3:12	0.017	12.107
Music transmission	Loudspeakers (BL E, G)	Headphones (BH)				p	U
Food intake (g)	670.84 ± 205.07	727.32 ± 260.14				ns	1210
Type of music	BL, BH	E	G			p	χ²
	713.43 ± 238.40	700.52 ± 222.76	613.41 ± 166.17			ns	3.107

Note. C = control group; BL = background loudspeakers; BH = background headphones; E = English vocal music; G = German vocal music.

Figure 1 shows the total amount consumed (in grams) across the five conditions. In males, food intake also did not reach significance, χ²(4, N = 147) = 7.770, p = 0.1, between the five conditions, but there was a higher intake in group BH compared to group G, 906.06 ± 227.86 g versus 704.14 ± 169.78 g; z = −2.245, p = 0.025, and to control, 744.21 ± 160.38 g; z = −1.996, p = 0.046. As expected, male participants had a significantly higher intake than female participants, 809.81 ± 208.26 g versus 546.23 ± 117.36 g; z = −7.561, p < 0.001. Therefore, gender was entered as a covariate in our correlation model.

Hunger ratings, r(145) = 0.284, p = 0.001, and appetite ratings, r(145) = 0.256, p = 0.002, before lunch were significantly correlated with food intake. Comfort ratings, r(145) = 0.165, p = 0.047, and palatability ratings, r(145) = 0.265, p = 0.001, were also significantly correlated with food intake.

Meal duration differed significantly across the five conditions, χ²(4, N = 147) = 12.107, p = 0.017 (see Table 2). Post hoc comparisons showed that participants in group G spent significantly less time eating than participants in group BL, 11:32 ± 2:55 min versus 14:09 ± 3:32 min; z = −2.807, p = 0.005, and group E, 14:05 ± 3:12 min; z = −3.017, p = 0.003 but failed to reach significance compared to the control condition, 13:50 ± 3:15 min; U = 29.483, p = 0.084. Meal duration did not differ between genders, z = −1.038, p = 0.299, but meal duration did differ between meal conditions for females, χ²(4, N = 74) = 10.609, p = 0.031. Post hoc comparisons showed that women in group G ate significantly faster than female participants in group E, 10:44 ± 2:26 min versus 14:38 ± 3:15 min; U = 23.429, p = 0.003 (see Figure 2).

Conclusion

The present study examined the influence of different auditory stimuli on young adults’ food intake during a single eating occasion. Although previous studies suggest that listening to music stimulates food intake regardless of hunger, satiety, or palatability (Mekhmoukh et al., 2012; Stroebele & de Castro, 2006; Thomas & Smith, 2009), this effect could not be detected in this experimental study. There were no differences in food intake between the groups with auditory stimulation and the control group, except for a higher intake among men listening to background music via headphones while eating lunch. Combining all groups with auditory stimulation and comparing them with the control condition also revealed no significant difference in food intake. The hypothesis that music leads to an increase in food intake, based on the fact that music, and familiar music in particular, elicits emotional arousal, which distracts the eaters from the meals, could not be confirmed in this study. Previous studies have shown that distractions during a meal can affect the perception of hunger, appetite and the amount eaten (Brunstrom & Mitchell, 2006; Higgs & Woodward, 2009). Thus, unconscious eating and a lack of perceived satiety resulted in increased consumption (Brunstrom & Mitchell, 2006; Higgs & Woodward, 2009; Oldham-Cooper, Hardman, Nicoll, Rogers, & Brunstrom, 2011). In the present study, advertising the study as a taste test might have led to a reduction in auditory distraction by focusing solely on taste. The experiment from Bellisle and Dalix (2001) supports this hypothesis. In their work, participants consumed significantly less while listening to recorded instructions focusing on the sensory characteristics of the foods than while listening to a recorded detective story (Bellisle & Dalix, 2001). Nonetheless, the participants’ moods were better in the music conditions. Although not significant, higher mood ratings before and after the meal were observed for all music conditions compared to the control condition, which indicates that, despite the possible focus on taste, the music affected participants’ moods.

In partial accordance with the hypotheses, meal duration differed between the five conditions. It was found that unfamiliar background music and English pop songs lead to longer meal duration than familiar German vocal music whereas the study’s hypothesis stated that familiar vocal music (German music) would lead to the longest meal duration and with it higher food intake via a higher degree of distraction. However, according to Zentner, Grandjean, and Scherer (2008), jazzy background music triggers “complex and reflective” emotions, such as amazement, nostalgia and spirituality. As a result, listeners become calm, peaceful and reflective themselves (Zentner et al., 2008). This effect of jazzy background music could be reflected in the longer meal duration. Another explanation for the findings could be that the chosen English pop songs were more familiar than the German songs. However, in experimental settings, it is also possible that music familiarity does not substantially affect food intake. Further studies should look more closely at the impact of music familiarity on food intake and should consider asking each participant to rate their familiarity with the chosen songs to better control for familiarity.

In general, maybe other aspects of music are the driving factors that affect food intake, such as tempo and intensity. In the present study, although the songs differed widely in tempo within each music group, the set of chosen songs within each music group had a similar tempo range. In some previous studies, it was the tempo of the music that influenced the behaviour of the customers (Caldwell & Hibbert, 2002; Milliman, 1986). In addition, the present work controlled loudness by using the same mean intensity of 48 dB in all conditions. McCarron and Tierney (1989) used music played at 70 dB and 90 dB to influence the consumption of soft drinks. Another study also showed that loud music (88 dB) enhanced arousal and increased the number of drinks ordered in a bar (Guéguen et al., 2008). Maybe the volume used in the present study was not loud enough to enhance subjective arousal; this explanation is also supported by the findings of Privitera et al. (2014). However, all previous studies have used non-experimental settings with many people present where the overall volume of the setting in itself was considerably louder. Also, the impact of music intensity and tempo on eating behaviour was not the focus of this study.

No significant effects of music transmission on food intake or meal duration were found. Listening to music via headphones was expected to be more arousing and distracting and therefore leading to higher food intake (Kristjánsdóttir & Kristjánsdóttir, 2011). Male participants showed higher intake in the headphone condition than when listening to German songs via loudspeakers or when in the control condition. It can be speculated that males in particular might enjoy this mode of transmission. However, perhaps young people, such as those in the present study, frequently hear music with headphones and therefore the distracting effect of headphones during lunch was not as high as expected.

Several limitations should be mentioned. First and foremost, despite conducting a power calculation, the sample size in each group might have been too small to reveal significant differences given the variability of intake among the participants and the dropout rate. A larger sample size might have yielded significant findings. Some experimental studies using music in the field of eating behaviour have used larger samples (Fiegel, Meullenet, Harrington, Humble, & Seo, 2014) while others have not (Mekhmoukh et al., 2012; Péneau et al., 2009). Also, it is important to mention that the majority of the participants reported discomfort eating alone in a room without any type of distraction, which might have caused them to simply finish their meal as fast as possible regardless of whether music in the background was enjoyable. It seems that in our society, eating alone without any distracting devices such as television, print media or smart phones might have become rare and discomforting.

The results are based on a student meat-eating population and can therefore not be generalized to the general population and vegetarians.

Under controlled experimental conditions as presented in this study, the influence of music familiarity or mode of transmission as such might play a smaller role in influencing food intake than when present in complex real-world settings. Other properties of music such as intensity and tempo might be the determining factors. Nevertheless, at home, in supermarkets, in restaurants, and even in the car, we are surrounded and affected by auditory stimuli that impact on our behaviour, including our eating behaviour. Therefore, unconscious effects of auditory stimuli should not be underestimated when looking at potential influencing factors that impact people’s food intake given that, on one hand, the majority of people tend to eat too much but on the other hand, specific population groups such as the institutionalized elderly also tend to eat too little. Finding new and innovative ways to promote or decrease food intake is desirable in many clinical and non-clinical settings.

In summary, the present study of young adults shows an increase in meal duration was associated with listening to instrumental background music or English music compared to familiar German pop songs. Meal intake was not affected by differences in auditory stimulation. Further studies with more participants to improve effect size are needed to gain deeper insight into the dynamics of various music components affecting food intake and meal duration.

Footnotes

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

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