Listening to Music Can Reduce Calorie Intake and Increase Satiety: A Systematic literature Review and Additional Pilot Study

Article information

Exerc Sci. 2024;33(4):423-435

Publication date (electronic) : 2024 November 30

doi : https://doi.org/10.15857/ksep.2024.00500

Ah-Ram Kim, PhD¹, Jae-Won Kim, MS², Na-Young Kim, BS², Ho-Seong Lee, PhD^1,

¹Department of Exercise and Medical Science, Graduate School, Dankook University, Cheonan, Korea

²Digital Nutrition Corp., Cheongju, Korea

Corresponding author: Ho-Seong Lee Tel +82-41-550-3838 Fax +82-41-550-3838 E-mail hoseh28@dankook.ac.kr

Received 2024 September 24; Revised 2024 November 29; Accepted 2024 November 30.

Abstract

INTRODUCTION

Obesity represents a significant global social and medical challenge, with its prevalence having more than doubled over the past two decades, including in Korea [1]. Obesity rates have increased significantly world-wide, closely associated with poor eating habits and energy imbalance [2]. There is a strong correlation between obesity and an increased risk of developing a number of health conditions, including type 2 diabetes, dyslipidemia, hypertension, fatty liver disease, coronary heart disease, stroke, colorectal cancer, and breast cancer [3].

Obesity primarily stems from an imbalance between energy intake and expenditure, leading to the accumulation of excess fat [4]. Common eating disorders in obese individuals include bulimia and binge eating, where food consumption provides hedonic satisfaction and psychological rewards beyond nutritional and satiety benefits [5,6].

Music is known to activate dopaminergic and serotonergic pathways, influencing the reward system and enhancing satiety, which may reduce caloric intake [7]. The lateral hypothalamus integrates energy homeostasis information from arcuate nucleus of the hypothalamus (ARC) neurons and reward-related signals from the lateral raphe nucleus, which affect the mesolimbic dopaminergic system and influence satiety via projections to the hindbrain [8]. Dopamine and serotonin, which favour the hypothalamus during caloric intake, can increase satiety and suppress appetite [9-12]. These mechanisms suggest that enhancing the brain's reward system with diverse stimuli may have the potential to increase satiety while reducing food intake.

Recent studies have demonstrated the efficacy of non-invasive techniques based on auditory stimulation in enhancing psychological and physiological indicators [13-16]. Auditory stimulation has been shown to have a faster cortical processing speed than visual stimulation [17], rapidly synchronizing motor and perceptual areas of the cortex [18]. The music, rhythmic auditory stimulation (RAS), activates monoamine systems, including serotonergic and dopaminergic pathways in the brain, modulating reward mechanisms [19]. It also influences emotional states [20,21] and motor functions [22,23]. Research indicates that RAS can safely and non-invasively activate dopamine and serotonin pathways, thereby influencing reward mechanisms, mood, satiety, and appetite regulation. Despite the potential of music as a non-pharmacological in-tervention to influence eating behavior, existing research has revealed conflicting results regarding its impact on calorie intake. Consequently, further investigation is required to elucidate the precise effect of music on food intake.

The objective of this study is to conduct a comprehensive review of the existing literature regarding the impact of music and its constituent elements on eating behaviors, with a particular focus on food intake. Furthermore, the study aims to develop musical compositions that could potentially result in a reduction in food intake. The hypothesis that will be tested is whether listening to specific music during the consumption of calories increases feelings of fullness and reduces appetite. The research methodology involved an initial systematic literature review (Phase 1) and pilot studies to assess performance indicators and their real-world application (Phase 2).

METHODS

1. Systematic literature review

1) Literature search strategy

This systematic review is written according to the preferred reporting items for Systematic reviews (PRISMA 2020) guidelines [24]. A literature search was conducted to identify studies published before May 2024 that the relationship between auditory stimulation and calorie intake. Systematic reviews were excluded. No additional constraints were imposed on the study design or publication date. The studies were required to be published in English. It is important to note that no comparisons with other interventions or populations were conducted. However, articles that included a control group were consistently included in the review. In addition to randomized controlled trials (RCTs), feasibility studies were also considered to broaden the scope of the study selection. The eligibility criteria were informed by the PICOS (Population, Intervention, Comparison, Outcomes, Study design) framework, with a particular focus on healthy populations exposed to auditory interventions and the measurement of outcomes related to food intake and satiety (Fig. 1 and Table 1).

Fig. 1.

PRISMA 2020 flow diagram.

Table 1.

Population, intervention, comparator, outcome, and study design (PICOS) criteria for the systematic reviews

There were four relevant databases identified, American Psychological Association (PsycINFO), Web of Science, PubMed, and ProQuest Dissertations and Theses (PQDT), and these were used to conduct our literature search. Keywords commonly used in the field were supplemented with subject terms that aligned with the objectives of the study. To ensure a comprehensive search was conducted, the researchers modified the search terms and the sequence of database usage, repeating the search on different days to compare results. Major search terms for all databases included both controlled vocabulary and keywords on the topic of auditory stimulation and sleep (Table 2).

Table 2.

Databases and search strategies using keywords

2) Selection criteria

Articles were selected according to the following inclusion criteria: (a) published in English; (b) the amount of food consumed by participants/energy intake was measured (evaluation of food choice, behavioral intentions, or other measures did not qualify); (c) surveys and experiments were both included; and (d) there was no age limitation for participants. Conversely, articles were excluded if: (a) their abstracts did not include sufficient information to code; (b) they represented theoretical review papers; (c) they duplicated data from another study; or (d) they employed two or more approaches (e.g., auditory plus visual stimulation). Comparisons between music-on versus music-off conditions while presented with music-related stimuli were (e.g., television viewing) were also excluded. Thus, only music-off conditions without music-related stimuli were included (e.g., eating alone, eating in groups, etc.).

The data were retrieved and organized utilizing Mendeley Reference Manager 2.117.0 software from Elsevier Ltd (Amsterdam, Netherlands). Following this, a framework was pre-established for data coding purposes. This framework includes general study information and specifics related to the research inquiries.

3) Data items

The data extracted from each study encompassed the following elements: (1) total number of participants, and age range; (2) musical intervention type; (3) examination protocol; (4) outcome measures; and (5) main results.

4) Collating, summarizing, and reporting the results

This phase of the scoping review was guided by the methodological framework proposed by Levac et al. [25]. A comprehensive descriptive synthesis of the data presented in the charting table was conducted by two researchers, while two reviewers applied qualitative content analysis techniques to formulate clinical strategies for addressing presbyopia. The findings from the synthesis and qualitative analysis were subsequently employed to contextualize the results, particularly in relation to the research questions, and to inform the clinical implications of incorporating music therapy sessions for individuals with presbyopia. Moreover, these insights indicate potential avenues for future research.

2. A pilot study

1) Materials

The present study was structured as a controlled trial, with participants randomly allocated to experimental groups through a block randomization procedure. Throughout the experiment, participants were exposed to different auditory stimuli, including a background music group (BMG) and a silence group (CON). The stimuli were presented in a manner that ensured they were equally likely to evoke a response.

The allocation order was determined by the study statistician, who did not have direct interaction with the subjects. This was achieved using a random block randomization technique to ensure equal representation in the treatment groups [26]. The statistician assembled sealed and opaque envelopes, each labeled with a consecutive number on the exterior and containing the corresponding group allocation. These envelopes were handed to the participating team member, who subsequently distributed them to the participants in numerical order after collecting baseline data. Upon receiving the envelopes, participants unveiled them to ascertain their group assignment for the intervention.

2) Participants

A total of 42 healthy women (mean age=31.52 years; SD=3.86 years) were recruited for this study, with their demographic characteristics summarized in Table 4. The inclusion criteria were as follows: (1) age between 19 and 39 years; (2) no current medication use; (3) no history of hearing impairment, learning disabilities, neurological disorders, psychiatric conditions, or other factors potentially impacting the study (e.g., sleep deprivation); and (4) the ability to comprehend the general purpose and specific instructions of the study. The exclusion criteria were: (1) diagnosed eating disorders; (2) metabolic disorders; (3) inability to communicate effectively, rendering them unable to understand survey questions; (4) psychiatric diagnoses within the past three months coupled with ongoing medication use; (5) prior participation in auditory stimulation programs within the past six months; and (6) allergies to specific foods.

Table 4.

Characteristics demographic of BMG and CON

Participant eligibility was determined through comprehensive interviews and a biographical questionnaire. This study exclusively focused on healthy women aged 19-39 years to reduce confounding factors, such as metabolic conditions, hormonal variability, and sex-specific differences in eating behavior. The research was conducted in accordance with the principles outlined in the Declaration of Helsinki, and ethical approval was granted by the Public Institutional Review Board under the Ministry of Health and Welfare (approval number: P01-202305-01-012). All participants provided informed consent prior to their inclusion in the study.

3) Self-administered 24-hour dietary recall

In this study, dietary surveys to calculate total energy intake were conducted using a 24-hour recall method during three of the two weeks (two weekdays and one weekend day) of the dual-labelled water consumption experiment. To minimize the error of the self-report method, a trained researcher was interviewed in person to determine the type of food consumed and the portion size per person, using food photos or drawings. The following five steps were applied according to the National Health and Nutrition Examination Survey Questionnaire and Nutrition Survey Guidelines [27]. 1) collection of information on meals and food names; 2) use of tools (measuring cups, measuring spoons, thickness rulers, etc.) to measure the weight or volume of each food item; 3) identification of items requiring further investigation about the food or its preparation; 4) verification of the information on the food items investigated; and 5) supplementary questionnaire. The National Health and Nutrition Examination Survey conducts a three-stage cooking survey of home meals through home visits to investigate the types of condiments (including brands) used, but this study was not able to conduct such a three-stage survey.

Based on the data from the 24-hour recall method, nutrient intakes were analyzed using CAN-Pro 6.0 [28] for professionals developed by the Korean Nutrition Society. The data collected by food name in the 24-hour recall method were divided into each food ingredient, and the weight of the food consumed was entered, so the intake of the foods collected by volume was converted to weight using the Nutritional Composition DB Construction Project: Volume and Weight Conversion DB of Eye Weight [29], and nutrient intakes were analyzed. The average value of energy intake over three days (two weekdays and one weekend day) was used as the total energy intake (TEI).

4) Satiety

The assessment of satiety was conducted using visual analogue scales (VAS) prior to and following the consumption of experimental meals. The scales are horizontal lines measuring 100 mm in length, with phrases indicating the extremes of a particular sensation positioned at either end (for example, “ I am not at all full” and “ I am extremely full”) [30]. The participants were instructed to make a vertical mark with a pencil on the line corresponding to the intensity of their currently experienced sensations. The scores were obtained by measuring the distance in mm from the left end of the line to the mark made by the respondent.

5) Procedure

The experimental meals, provided by BMG and CON, were served between 12:00 and 13:00 in booths designated for each respective entity. During the experimental meal, BMG played 10 specially designed songs in the background based on musical components that have been demonstrated to be effective in controlling portion control, reducing calorie intake, and increasing satiety. In order to ascertain the effectiveness of the musical components in question, studies were considered which had been confirmed through systematic reviews and animal studies. These included the studies by Al-Etreby et al. [31], Divert et al. [32], Kaiser et al. [33], Lock et al. [34], Ragneskog et al. [35], and Stroebele et al. [36].

The BMG experimental meals were conducted with 60 dB of eating behavior-specific background music played via loudspeakers in the experimental dining area, while the CON experimental meals were conducted in silence, without background music. Participants in both the BMG and CON groups gave informed consent, completed a 24-hour food recall before the experimental meal, measured their satiety before and after the experimental meal, and ate at a single desk in a conference room during the experimental meal.

Each experimental meal provided 682.67 kcal, based on the recommended daily calorie intake of 2,000 kcal for adults in their 20s and 30s [37]. The meal consisted of 200 g white rice (300.00 kcal) as the main food, 39.3 g hamburger steak (54.88 kcal) as a side dish, 28 g fried shrimp (73.00 kcal), 21 g boneless chicken (56.00 kcal), 46 g pork bulgogi (65.00 kcal), 56.4 g radish dip (56.00 kcal), 4 g grilled seaweed without oil (8.23 kcal), 180 g miso soup (33.00 kcal), 7.2 g stewed anchovies (15.39 kcal), and 29.2 g Chinese cabbage kimchi (11.13 kcal).

6) Statistical analysis

All data were calculated as means and standard deviations using SPSS Ver 25.0. The Mann-Whitney U-test was used to analyze the difference in effect between the BMG and CON groups. This non-parametric test was chosen due to the possibility of a relatively small sample size in this study and because the assumption of normality of the data was not met. The Mann-Whitney U-test is a rank-based test that is less sensitive to extreme values, thus ensuring robustness.

The Mann-Whitney U-test assesses whether two independent populations have the same distribution by comparing the difference in medians between the populations. In addition to statistical significance, we analysed effect size was conducted to assess practical significance. For effect size analysis, we used rank-biserial correlation (r). Rank-biserial correlation is a method of measuring effect size used in conjunction with the Mann-Whitney U-test, expressing the difference in rank between two populations as a value between −1 and 1. A higher absolute value indicates a greater difference between the two populations. The interpretation criteria for rank-biserial correlation are as follows: | r|<0.3 indicates a small effect; 0.3≤| r|<0.5 indicates a medium effect; and | r|≥0.5 indicates a large effect.

RESULTS

1. Results of the individual studies

The results of the studies included in our systematic review are presented in separate sections, thus providing a clear overview. The following five databases were utilized: The databases PsycINFO, Web of Science, PubMed, and PQDT were used. The search query yielded 7,303 results, of which 1,262 were identified as duplicates and subsequently removed. In the initial screening phase, 1,702 articles were evaluated based on their titles and abstracts. This process led to the exclusion of 1,667 articles due to factors such as inappropriate population, duplicate status, outcome, and inaccurate study design. In the second stage of the process, the remaining 35 articles were subjected to a full-text screening. Following this screening process, two articles were excluded due to the incorrect population, four due to the inappropriate intervention, five due to the erroneous outcome, and seven due to the unsuitable study design. Fig. 1 depicts the PRISMA 2020 [24] flowchart, which provides a summary of the selection process and the reasons for the exclusion of studies. A total of eleven articles were deemed eligible for inclusion in this systematic review, comprising six randomised controlled trial studies and five non-randomised clinical trial studies (Table 3).

Table 3.

Study characteristics (n=11)

The relationship between music volume and caloric intake has been previously investigated in the literature. Mamalaki et al. [38] observed that the lowest caloric intake was observed in the 60 dB group (1,064±324 kcal), in comparison to the 90 dB group (1,136±311 kcal) and the control group (1,079±311 kcal). Although the 60 dB group exhibited the lowest caloric intake, the observed difference was not statistically significant (p =.697).

The relationship between music genres and caloric intake has been previously investigated in the literature. Fiegel et al. [39] identified significant differences in flavor pleasantness and overall impression of food between music genres (classical, jazz, hip-hop, and rock). Camphinho et al. [40] observed that specific flavors are more pronounced in certain musical genres. Hussain et al. [41] observed a reduction in the consumption of salt-containing foods (e.g., savoury foods such as noodles, eggs, burgers, pizza, chips, peanut butter) when classical music was played. Furthermore, classical music has been demonstrated to enhance the hedonic value of food intake and facilitate taste discrimination [42].

In particular, the tempo of music has been linked to the speed of food intake, which is a relevant factor in determining the amount of food consumed. Sato et al. [43] observed that listening to fast-tempo music and slow-tempo music, in comparison to normal-tempo music, resulted in a reduction in both the rate of food intake and the total calorie intake. Furthermore, Mathisen et al. [44,45] demonstrated that slow tempo music has been linked to an increase in eating duration and a reduction in caloric intake. Furthermore, the combination of slow tempo and legato articulation resulted in an additional increase in eating duration and a reduction in caloric intake compared to other conditions, including slow tempo + staccato, fast tempo + legato, fast tempo + staccato, and silence.

However, Livock et al. [46] demonstrated that there was no significant difference in satiety levels between those who watched television and those who listened to music during an ad libitum lunch. Furthermore, Mekhmoukh et al. [47] demonstrated that the consumption of calories was significantly higher when participants listened to music than when they ate alone or in groups, among those with a normal body mass index. However, in overweight participants, there was a significant reduction in caloric intake when listening to music compared to watching television.

A synthesis of the findings from previous studies indicates that listening to low-BPM music of classical and similar genres at a volume of 60 dB has the effect of reducing calorie intake and intake of salt-containing foods. Nevertheless, the evidence is insufficient to reach a definitive conclusion, and further investigation is required to examine the potential of music listening as a means of regulating calorie intake.

3. Compare the caloric intake and satiety of the BMG and CON

Total caloric intake during the experimental meal was significantly lower in BMG (459.21±112.49 kcal) compared to CON (579.73±96.61 kcal) (u=87.0, p =.001, r=.605). Satiety before the experimental meal was not significantly different between BMG (1.24±1.55 cm) and CON (1.97±1.88 cm) (u=159.0, p =.124, r=0.279). Satiety after the experimental meal was significantly higher in BMG (7.21±1.79 cm) compared to CON (5.96±1.45 cm) (u=120.5, p =.0012, r=-0.454), and the change in satiety from before to after the experimental meal was also significantly higher in BMG (5.98±1.87 cm) compared to CON (3.99±1.08 cm) (u=79.5, p =.001, r=-0.639) (Table 5).

Table 5.

Caloric intake and satisfied of BMG and CON

DISCUSSION

In recent years, there has been a growing interest in the potential of music-based interventions to influence psychological and physiological symptoms. This review and pilot study aimed to determine whether music affects appetite, representing a novel, non-invasive, and safe approach to healthy eating. Our systematic review revealed that slow-tempo classical music at a volume of 60 dB was the most effective in reducing calorie intake. This finding is consistent with Mamalaki et al. [38], who observed that the 60 dB group exhibited the lowest calorie intake. Additionally, the findings align with Mathisen et al. [44,45], indicating that slow-tempo music increases meal duration and decreases calorie consumption. The pilot study demonstrated that the background music group (BMG) had significantly lower calorie intake and higher satiety compared to the control group (CON). This aligns with Stroebele and de Castro [36], who found that background music slowed eating and reduced food consumption.

Previous research has shown that background music can influence caloric intake [35,48-50]. In our study, we developed novel music incorporating various components such as frequency, BPM, tempo, genre, noise, and major/minor key, building on several previous studies on appetite reduction. The results showed that the new appetite-reducing music was associated with lower calorie intake. Goldschmidt et al. [51] noted that caloric intake and eating behavior are influenced by internal physiological and external environmental factors. Sato et al. [43] found that music at 76 BPM significantly reduced caloric intake and eating speed compared to music at 96 BPM in healthy women. Generally, slow eating increases satisfaction and decreases food intake compared to fast eating [50]. In this study, we used music with a tempo of 60 to 80 BPM, suggesting that music below a certain tempo slows the rate of eating, resulting in reduced caloric intake.

The present study demonstrated that BMG significantly enhanced postprandial satiety compared to the control group, despite a reduction in calorie intake. Satiety refers to the inhibitory mechanism that occurs after eating, preventing the return of hunger for a variable duration. In animal models with constant access to food, satiety is recognized as a powerful mechanism that matches energy intake to energy needs by adjusting the postprandial interval based on the energy content of the previous meal [52]. However, in humans, satiety mechanisms are regulated by a combination of sensory inputs [53]. It is hypothesized that increased satiety involves the dopaminergic reward system [54], which can benefit from auditory stimulation, including music [21,55]. The music used in this study may have positively influenced the dopaminergic reward system, enhancing satiety even with a modest quantity of food intake.

The results indicate that background music, particularly slow-tempo music, may reduce caloric intake and increase satiety. However, it is crucial to acknowledge the limitations of generalizing these findings. The observed effects are likely influenced by specific factors such as the tempo, genre, and volume of the music. Prior research suggests that the impact of music on eating behavior is not uniform across all musical elements. According to Mathiesen et al. [44] discovered that slow-tempo music prolongs the duration of eating, whereas faster tempos may have minimal or even opposing effects on feelings of satiety and caloric intake. Similarly, Fiegel et al. [39] reported that the perceived pleasantness of food varies with the music genre. The results demonstrated that classical music was more effective than other genres in enhancing flavor discrimination. These findings underscore the context-dependent nature of physiological and psychological responses to music, suggesting that they may not be universally applicable. Furthermore, auditory stimuli, such as background music, may indirectly influence energy expenditure by modifying metabolic rates. Although direct evidence connecting music to resting energy expenditure (REE) or basal metabolic rate (BMR is scarce, studies on relaxation and heart rate (HR) reduction provide a theoretical basis for this association. For example, Brage et al. [56] posit that slow-tempo music may reduce energy expenditure during rest or meals by lowering the HR. Additionally, research indicates that slow-tempo music has the capacity to stabilize the autonomic nervous system, which in turn results in a reduction in HR. Bernardi et al. [57] demonstrated that listening to slow-tempo music (60-80 BPM) results in a decrease in HR and the suppression of stress responses. It may therefore be posited that this has an influence on satiety and eating behavior by promoting relaxation during meals. Similarly, Iwanaga et al. [58] investigated the impact of music tempo on physiological arousal and observed that slower music reduces physical tension and lowers HR. These findings lend support to the hypothesis that slow-tempo music may enhance feelings of fullness by modulating physiological states.

These findings align with the neurobiological theory that auditory stimulation affects the brain's reward system and appetite control mechanisms. As posited by Menon [19], musical stimulation activates serotonin and dopamine pathways, modulating reward mechanisms. This may result in increased feelings of fullness and reduced appetite. It is possible that the activity of pro-opiomelanocortin (POMC) neurons and neuropeptide Y (NPY)/agouti-related protein (AgRP) neurons in ARC is modulated by musical stimuli. Koelsch [20] further suggested that music influences emotional states, potentially through hypothalamic activity, and may also affect the nucleus tractus solitarius (NTS) in the brainstem, enhancing the processing of satiety signals, while Zatorre et al. [22] found that music impacts motor function, indirectly supporting this hypothesis. Similarly, moderate-intensity aerobic exercise is well-documented for its effects on appetite-related hormones, with Broom et al. [59] demonstrating that it reduces ghrelin levels and increases peptide YY (PYY), leading to appetite suppression, which provides a valuable comparison to the effects of music. Both music and exercise influence heart rate (HR) and the dopaminergic reward system, though through different mechanisms [60], and a comparative study could help clarify whether these interventions yield similar or complementary effects. Additionally, incorporating music during exercise has been shown to improve adherence to exercise regimens and mood [61], and the combination of slow-tempo music with exercise may further reduce calorie intake by enhancing both hormonal and psychological responses. Future research should explore whether these combined interventions provide additive benefits for appetite control and energy balance.

These findings indicate the potential of music therapy as a novel non-drug intervention for preventing and treating obesity. Gramaglia et al. [16] demonstrated that music therapy effectively improves psychological and physiological indicators, making it a promising avenue for obesity management. Appropriate background music can be used in various dining settings, including restaurants, cafeterias, and homes, to help individuals improve their eating habits. Kaiser et al. [33] reported positive effects of music on the dining environment, potentially informing public health policy. The findings may also apply to treating eating disorders. Pellegrino et al. [42] found that classical music enhances the hedonic value of caloric intake and facilitates flavour discrimination, supporting this approach.

While this study primarily assessed calorie intake and subjective satiety, future research should include a more comprehensive range of objective and physiological indicators. These could include blood levels of hormones such as ghrelin and leptin or neural activity using brain imaging techniques. Salimpoor et al. [21] used fMRI to identify dopamine release during music listening, which could be a valuable reference. Further investigation is also required to elucidate the differential impact of different music genres and characteristics (tempo, rhythm, harmony, etc.) on eating behaviors.

The present study evaluated the effectiveness of specific music in influencing eating behavior, but it is limited by several constraints. The limited sample size may affect statistical power and generalizability. It is a between-subject design for the BMG and CON groups, which does not consider individual differences in dietary preferences and habits. A within-subject design could provide more robust control by eliminating between-subject variability. Furthermore, the focus on short-term effects highlights the need for longitudinal studies to assess long-term effects. In addition, the inadequate control of variables such as psychological state, stress levels, and hormonal fluctuations suggests the need for more careful control in future studies.

One of the major limitations of this study is the lack of direct evidence supporting the neurobiological mechanisms underlying the observed effects of music on satiety and calorie intake. While previous research has linked musical stimulation to the activation of dopaminergic and serotonergic pathways, our study did not include direct measurements such as hormonal assays or brain imaging to validate these mechanisms. Future studies should incorporate physiological and neurobiological assessments, such as blood tests for ghrelin and leptin levels or functional neuroimaging, to elucidate the pathways through which music influences eating behavior.

The exclusive inclusion of women, due to known sex differences, requires further gender-specific research to ensure consistency across populations. In addition, limitations of the measurement tools include subjective biases in self-reported assessments, indirect measures of physiological markers, and potential inaccuracies in laboratory-based caloric intake measurements. It is recommended that future research addresses these issues by increasing sample sizes, extending study duration, refining measurement methods, and including diverse populations. This will improve the validity, reliability, and applicability of music-based strategies to regulate dietary behavior.

CONCLUSION

This study examined the effects of appetite-specific background music, developed from a systematic review, on calorie intake and satiety in healthy adults. The findings indicate that such music can reduce calorie consumption and enhance satiety when played during meals. This approach shows potential as a non-invasive strategy for managing obesity and promoting healthier eating behaviors.

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