Coffee Intake Reduces Short-Term Carbohydrate and Lipid Consumption

Abstract

Background: Epidemiological studies on the effect of coffee intake on food consumption have yielded conflicting results. We sought to study the immediate and short-term effects of coffee consumption on food preferences, total calories, and macronutrient consumption within a specific, closely supervised experimental protocol. Methods: Twenty-one normal-weight volunteers completed this crossover, randomized, controlled study. Each volunteer took part in two trials consuming (a) 200 mL of instant coffee providing 5 mg of caffeine/kg body weight or (b) 200 mL of water (control). In both trials, participants were offered an ad libitum lunch meal from a buffet for 30 min. Proteins, lipids, and carbohydrates, as well as total caloric consumption were recorded during the initial 30 min period of the experiment (immediate period) as well as during the rest of the day (short-term period). Results: Coffee intake resulted in a statistically significant lower intake of immediate and short-term carbohydrate consumption (p = 0.012 and p = 0.047), of immediate protein consumption (p = 0.019), and of short-term lipid consumption (p = 0.04) versus water consumption. As a result, the calories consumed both immediately upon coffee administration and during the rest of the day of the experiment were significantly lower (p = 0.026 and p = 0.006) in the coffee group. Conclusions: Coffee intake seems to exert an anorexigenic result that last for several hours upon its consumption, particularly for carbohydrates and lipids.

1. Introduction

Caffeine, a naturally occurring psychoactive substance found in coffee, tea, cocoa, and various other beverages, is one of the most widely consumed stimulants in the world. It is renowned for its effects on enhancing alertness, improving concentration, and mitigating fatigue, which has led to its integration into the daily routines of millions globally. Beyond its role as a central nervous system stimulant, caffeine has garnered significant attention in the scientific community due to its multifaceted effects on metabolism, energy expenditure, and dietary behaviors [1].

The intricate relationship between coffee consumption and its potential influence on dietary habits and body composition has spurred significant scientific interest. Since coffee is one of the most widely consumed beverages and an integral lifestyle component in Western societies, it has garnered attention for its possible impact on cardiovascular health and adiposity. Extensive investigations have been focused on discerning the effects of coffee consumption on these parameters, yet the findings have yielded a complex and often contradictory landscape of results. One limiting factor for reaching solid conclusions might be the exact cut-off amount for distinguishing low intake from regular and higher intake. For instance, an intake of 3–4 cups per day, when considered as low intake, is associated with a lower risk of Coronary Heart Disease (CHD) when compared to no intake or higher intake [2]. On the other hand, a higher intake of coffee has been modestly linked to lower adiposity, especially in male populations [3].

These varying outcomes are mirrored in the diverse conclusions drawn when analyzing the relationship between coffee intake, appetite regulation, and energy consumption. It has been shown that coffee consumption does not have a significant effect on dietary intake or appetite, both in normal-weight and overweight/obese individuals [4]. Likewise, coffee’s anorexigenic potential is not always manifested, even when comparing caffeinated versus decaffeinated beverages [5]. Yet again, others highlight enhanced thermogenesis and fat oxidation, and even promote a likely suppressive effect on appetite following coffee consumption [6].

In terms of energy intake, a significant trending correlation has been reported between coffee consumption and the increased intake of certain food groups, particularly meat, eggs, oils, and snacks [7]. It has been suggested that coffee drinkers may have a higher overall energy intake, potentially due to the complementary nature of coffee with these food items [8].

Thus, one can perceive coffee’s effect on energy intake and appetite to be due to specific individualistic traits, such as a genetic predisposition to caffeine metabolism [9] and also to environmental factors. Indeed, it has been suggested that coffee’s influence on food intake is highly context-dependent, capable of either increasing or decreasing consumption based on environmental factors such as food access, stressful conditions [10], and socio-environmental factors. As for the latter, it has been indicated that coffee drinkers often have higher rates of smoking and alcohol consumption, which are behaviors linked to increased energy intake and poorer dietary quality [11]. This suggests that the lifestyle choices associated with coffee consumption may further complicate the relationship between coffee intake and dietary patterns.

Interestingly, the effect of coffee consumption on macronutrient intake has undergone thorough research but only a few studies, including various methodological approaches incorporating the analysis of genetic predisposition and metabolic biomarkers. The results so far have shown that, indeed, increasing coffee consumption from low-to-moderate levels is associated with reductions in body fat, but without significant associations with macronutrient intake [12]. Moreover, Gavrieli et al. (2013) demonstrated that caffeinated coffee did not acutely affect energy intake but may influence appetite-related feelings, particularly in overweight individuals. In particular, coffee consumption prevented a radical fall in cortisol concentrations, suggesting potential long-term effects on metabolic regulation [4]. Likewise, an inverse association between coffee consumption and the prevalence of low skeletal muscle mass has been observed, highlighting potential links between coffee intake and protein metabolism. Nevertheless, no significant association has been reported between coffee consumption and protein intake [13]. On the other hand, nutrigenetic data indicate various relationships between coffee consumption and macronutrient intake, according to the genetic predisposition to caffeine metabolism [9]. Together, these studies suggest that coffee may influence macronutrient metabolism, though its direct impact on macronutrient intake remains unclear.

It becomes evident that a multitude of factors, including cultural habits, genetic predispositions [10], and gut microbiota variations [14], may interact to modulate the intricate interplay between coffee consumption and body mass index (BMI). Amidst this intricate web of variables, the immediate impact of coffee, the principal bioactive component of coffee, on dietary choices warrants in-depth investigation.

This paper seeks to examine the acute effects of coffee intake on food consumption, employing a controlled experimental setup. By isolating the influence of caffeine from the confounding factors of obesity, habitual dietary preferences, and cultural influences, we aim to elucidate its specific role in shaping short-term macronutrient intake. With the aim of shedding more light on the intricate interplay between coffee-derived caffeine, dietary choices, and potential downstream effects on metabolism and body composition, in this study, we present an empirically designed experiment that allows for a more precise examination of the direct effects of coffee consumption on dietary choices.

2. Materials and Methods

2.1. Participants

Participants in this study were recruited through local advertisements placed on the University of West Attica campus. The recruitment process was conducted only after obtaining full and formal approval of the experimental protocol from the university’s scientific and ethical committee. Each individual was assessed as being apparently healthy, with no indications of underlying health conditions. Individuals who were smokers, belonged to specific population groups (such as athletes or pregnant women), had any form of chronic or acute disease, or were currently on any form of medication were excluded from participating in this study. This strict selection process ensured a homogeneous and representative participant group, free from factors that could introduce variability or bias into the study results.

2.2. Experimental Protocol

All volunteers actively took part in two trials (separated by an interval of exactly 7 days between them) in a completely randomized order (determined by using a random number table). Female participants, specifically, were scheduled during the follicular phase of their menstrual cycle to avoid potential variability and fluctuations in appetite [15]. During the week that preceded each experimental day, participants were explicitly instructed to abstain entirely from all caffeine-containing substances. Furthermore, on the day directly preceding each experimental day, participants were specifically instructed to completely abstain from all sources of alcohol and physical exercise, to ensure they received sufficient and adequate sleep (~7 h), and to maintain constant and consistent eating patterns. Participants were required to arrive at the laboratory early in the morning, precisely at 9 a.m., following an overnight fasting period of exactly 10 h. Upon arrival, participants consumed a standardized breakfast snack together with one of the two distinct experimental drinks. The breakfast snack consisted of a single slice of white bread, 5 g of butter, and 10 g of white sugar, providing a total of 142 kilocalories (6.5% of the energy derived from proteins, 62.5% from carbohydrates, and 31.0% from lipids). The experimental drinks administered were either (a) 200 mL of instant coffee, providing precisely 5 mg of caffeine, or (b) 200 mL of water, which served as the control. Volunteers were instructed to consume both the standardized meal and the experimental drink fully and completely within a strict timeframe of 5 min. After a 3 h period, participants were offered an ad libitum lunch meal from a buffet, consisting of common Greek diet foods (pasta, tomato sauce, beef, salad, cheese, yogurt, fruits, and juice). They consumed as much food as they desired until they felt satiated, within 30 min. Researchers weighed both the initial amount of food placed on their plate as well as any leftovers to record the net amount of food consumed, thus their dietary intake. Recording of the exact amount was performed upon the consumption of each food. Once the participants had completed their buffet lunch, they were free to leave the laboratory and consume any food or beverage of their choice for the remainder of the experimental day, with the sole exception of caffeine and caffeinated beverages. To ensure accuracy and consistency, participants were required to maintain a detailed, weighted food diary. The participants recorded their food intake for one full experimental day, either for the coffee group or the water group. The information recorded in these diaries, including both nutrients and overall energy intake, was carefully assessed and evaluated using the “Nutritionists PRO” software. This software utilized databases from both the USDA and EFSA, which were specifically amended and customized to include Greek foods. The analysis of the food diaries and nutrient data was carried out exclusively by a single, highly trained, and well-qualified dietitian, ensuring uniformity and precision in the results.

2.3. Statistical Analysis

The continuous variables are presented as mean value and standard deviation, since the normality of their distribution was confirmed via the Kolmogorov–Smirnov test. Differences in these variables between the two cross-sectional groups were assessed by a two-tailed paired t-test. All statistical analyses were performed using SPSS software (version 26, IBM Corp., Armonk, NY, USA). The level of statistical significance was set at 5%.

3. Results

The basic characteristics of the participants are presented in

Table 1. Basic characteristics of the study’s participants (N = 21).

Age (years)	24.9 (1.5)
BMI (kg/m2)	24.8 (5.7)
Sex
Female	12
Male	6

Continuous variables are presented as mean and standard deviation.

. In total, a group of twenty-one volunteers, consisting of fifteen female participants and six male participants (15♀ and 6♂), all aged between 18 and 25 years old, successfully completed this crossover, randomized, and controlled study. All participants were of normal weight, defined as having a body mass index (BMI) of 18.5–24.9 kg/m².

As for the statistical results of this study, the consumption of the various macronutrients in grams during the first 3 h of the experiment (immediate consumption of macronutrients) and during the rest of the day (short-term consumption of macronutrients) is presented in

Table 2. Macronutrient and energy intake during the 2-stage experimental protocol.

	Experimental Day of Water Consumption	Experimental Day of Coffee Consumption	t-Statistic	Cohen’s d	p-Value
Proteins (g)
Immediate consumption	50.9 (17.8)	42.5 (18.3)	T = 2.60	0.48	p = 0.019
Short-term consumption	29.2 (17.9)	28.3 (23.7)	T = 0.279	0.04	p = 0.784
Carbohydrates (g)
Immediate consumption	93.0 (34.3)	78.3 (44.4)	T = 2.822	0.39	p = 0.012
Short-term consumption	104.0 (58.4)	76.0 (39.2)	T = 2.143	0.53	p = 0.047
Lipids (g)
Immediate consumption	48.7 (16.9)	44.9 (17.3)	T = 1.618	0.22	p = 0.124
Short-term consumption	42.6 (19.2)	28.1 (20.9)	T = 2.219	0.72	p = 0.040
Energy (kcal)
Immediate consumption	987.5 (298.8)	884.3 (372.6)	T = 2.438	0.31	p = 0.026
Short-term consumption	924.8 (445.3)	628.3 (301.3)	T = 3.123	0.78	p = 0.006

.

The analysis of the total energy intake revealed that participants in the coffee condition consumed an average of 10% fewer calories compared to the control condition. This reduction was statistically significant (p = 0.006), indicating a robust effect of coffee on overall dietary consumption.

The impact of coffee consumption on macronutrient intake revealed that participants in the coffee consumption intervention group consumed 15.7% (p = 0.012) and 27% (p = 0.047) fewer carbohydrates in the immediate consumption and short-term consumption conditions, respectively, compared to the control group. A more pronounced reduction was observed in lipid short-term consumption, with participants in the coffee group consuming 34.1% less fat than those in the control group. Finally, short-term protein consumption did not differ significantly between the coffee and water groups.

4. Discussion

Few studies have examined the impact of acute caffeinated coffee intake on energy and macronutrient intake [4,16,17], revealing a small effect on energy intake yet failing to yield a statistically significant impact on macronutrient consumption. However, a divergence in methodologies exists, with some studies utilizing bitter beverages instead of water as a control and administering lower caffeine doses. These studies often included diverse subject populations, introducing potentially confounding factors such as smoking status or variations in body weight. Additionally, most previous studies have focused on appetite rather than the detailed tracking of food choices beyond the caffeine’s half-life of approximately 4 h. The results of this study provide critical insights into the effects of coffee consumption on short-term dietary behaviors, specifically focusing on carbohydrate and lipid intake. Across the randomized, crossover trials, significant differences were observed between the coffee and control conditions. Participants who consumed coffee prior to their ad libitum meal exhibited a measurable reduction in total energy intake compared to those in the control group. This reduction was particularly evident in the consumption of lipid-rich and carbohydrate-rich food items.

An interesting finding of our study is the significant reduction in carbohydrate consumption, both immediately and in the short term, following coffee intake. This observation suggests that coffee consumption may exert specific effects on carbohydrate preferences, a phenomenon that warrants further physiological research. The neural and hormonal pathways underlying this selective macronutrient reduction remain largely unknown. Current evidence regarding the influence of caffeine and coffee on factors such as gastric emptying, appetite-regulating hormones, and subjective appetite perceptions remains equivocal [18]. Furthermore, the physiological processes that mediate these effects are likely complex and multifactorial, involving interactions between metabolic, hormonal, and neural mechanisms. For instance, caffeine’s known ability to enhance dopaminergic signaling could potentially influence food reward pathways, altering preferences for specific macronutrients such as carbohydrates. Furthermore, the sensory properties of coffee, including its aroma and flavor, may influence food preferences and consumption patterns. The physiological effects of caffeine are also noteworthy. Caffeinated coffee has been shown to increase the metabolic rate and thermogenesis, which can contribute to a decrease in appetite. This is particularly relevant for individuals seeking to manage their weight, as the reduction in caloric intake could facilitate weight loss or maintenance. Additionally, the diuretic effect of caffeinated coffee may lead to changes in hydration status, which can further influence appetite and food consumption [1].

In animal models, caffeine has demonstrated effects such as enhancing blood lipid and antioxidant levels, decreasing serum leptin concentrations, impeding fatty acid absorption, and downregulating the expression of pro-inflammatory cytokines such as IL-6 and TNF-α [19]. These findings align with the potential metabolic benefits that may contribute to the observed dietary changes in humans. In our prior publication [20], we highlighted diminished asprosin levels as a potential mediator of coffee’s anorexigenic effects, and we also reported genotype-dependent appetite regulation influenced by coffee consumption, specifically in individuals with the CYP1A2 rs762551 polymorphism. These findings hint at a complex interplay between genetics and the physiological effects of caffeinated coffee, which may explain inter-individual variability in dietary responses.

While our study presents valuable insights, it is essential to acknowledge its inherent limitations. One limitation of our study is the use of water as the control condition. Although water provides a straightforward and neutral baseline, it also precludes the potential for achieving blinding of the study’s methodology and consequently minimizing bias. Additionally, coffee includes various bioactive compounds in addition to caffeine, such as chlorogenic acids and polyphenols, which might affect dietary choices. Consequently, the impacts seen on macronutrient consumption cannot be entirely linked to caffeine alone. The use of decaffeinated coffee as a control would have been a more optimal design, as it would facilitate a clearer distinction of caffeine’s effects and enhance blinding. However, the decision to use water was driven by practical considerations, including simplicity and ensuring no residual effects of other coffee compounds in the control condition. One more limitation was the imbalance in the number of male and female participants. While this distribution reflects the demographic composition of the volunteers who responded to the recruitment process, it may limit the generalizability of the findings when interpreting the potential gender-specific effects of caffeine on dietary behaviors. Finally, this study did not include a pre-calculated sample size estimation to ensure sufficient statistical power. Although the sample size of 21 participants allowed for some significant findings, a larger cohort may have strengthened the reliability and generalizability of the results, as can be interpreted by post hoc analysis. Despite these limitations, the findings contribute valuable insights into the effects of caffeine on macronutrient intake and provide a strong foundation for future research in this area.

One strength of our study is its rigorous design, which employed a homogeneous cohort of healthy, young, normal-weight, non-smoking, and non-caffeine-dependent individuals. This careful participant selection minimized potential confounding variables that may have affected outcomes in previous studies.

In addition, the observed reduction in carbohydrate consumption has potential metabolic implications, such as improved glycemic control or weight management, which could have meaningful health outcomes. Future studies should explore whether these short-term effects translate into long-term changes in dietary habits or metabolic health. Finally, the interaction between coffee consumption and dietary patterns in individuals with different metabolic profiles or comorbid conditions remains an area ripe for further exploration. The implications of these findings are significant for dietary practices and public health recommendations. If coffee consumption can effectively reduce the intake of high-calorie macronutrients, it may serve as a useful tool in dietary interventions aimed at weight management [6]. Nutritionists and dietitians could consider incorporating moderate coffee consumption into dietary plans for individuals seeking to reduce their caloric intake without sacrificing overall satisfaction with meals [4]. However, it is essential to balance these recommendations with considerations of individual tolerance to caffeinated coffee and potential side effects, such as anxiety or sleep disturbances. Moreover, the timing of coffee consumption may play a critical role in its effects on food intake. Consuming caffeinated coffee before meals could potentially enhance its anorexigenic effects, leading to a more significant reduction in caloric intake. Conversely, excessive caffeine consumption may lead to negative health outcomes, including an increased heart rate and gastrointestinal discomfort, which could deter individuals from adhering to dietary recommendations [21].

Our findings contribute to the growing body of literature by highlighting the intricate relationship between coffee consumption and macronutrient intake, particularly the reduction in carbohydrate consumption. This previously unexplored facet of the caffeine–dietary relationship underscores the need for further investigation into the underlying mechanisms. Neural pathways, including those governing reward, appetite regulation, and decision-making, may play a significant role [5]. Advanced neuroimaging techniques or neurophysiological assessments could help elucidate the specific brain regions and circuits involved in mediating these dietary effects. In addition, longitudinal studies could provide insights into how habitual coffee consumption influences food preferences over time and also investigate the effects of different types of caffeinated beverages, such as energy drinks versus coffee, on macronutrient consumption [10]. Understanding the nuances of these relationships will be critical for developing comprehensive dietary guidelines. Finally, it would be equally important to examine the effects of caffeinated coffee in diverse populations, including those with varying body weights, metabolic rates, and dietary habits [14]. Such studies could help clarify whether the anorexigenic effects of coffee are consistent across different demographic groups or if they vary significantly based on individual characteristics.

5. Conclusions

In conclusion, the current study’s results suggest that coffee consumption has a significant impact on short-term food consumption, particularly in reducing the intake of carbohydrates, proteins, and lipids. As the prevalence of obesity continues to rise, understanding the role of dietary components like caffeine in appetite regulation and food preferences becomes increasingly important. Future research should aim to clarify these relationships and explore practical applications in dietary interventions. By integrating coffee into dietary strategies, health professionals may be able to assist individuals in achieving their weight management goals while promoting healthier eating patterns.