Coffee, a globally popular beverage, has been the subject of numerous studies exploring its potential effects on weight loss and obesity. While many studies have explored the relationship between coffee and obesity, the results have been inconsistent. Coffee is high in not only caffeine but also other bioactive compounds, such as polyphenol and chlorogenic acid that have been suggested to confer diverse health benefits. Considering that obesity has been established as a major underlying cause for the aforementioned health risks, it is plausible that coffee intake may be associated with reduced risk of obesity. This article aims to provide a comprehensive overview of the existing research, examining both the potential benefits and drawbacks of coffee consumption in relation to weight management.
Meta-Analysis of Coffee Intake and Adiposity
To systematically summarize the relationship between coffee intake and adiposity, a meta-analysis was conducted, compiling data from 12 epidemiologic studies identified from PubMed and Embase through February 2019. The design, analysis, and reporting of this meta-analysis were based on the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) checklist [19]. Three authors (AL, WL, SK) participated in literature search, study selection, and data extraction independently. PubMed and Embase were searched for epidemiologic studies published up to February 2019 using the provided search terms (Table S1). The language was restricted to English. Nonoriginal studies (e.g., case reports, commentaries, letters, and editorials) and animal experiments were excluded. The reference lists of all the articles included in this meta-analysis were reviewed for additional articles. Studies had to be an observational study (e.g., cross-sectional, case-control, and cohort studies) or experimental study (e.g., randomized controlled trials) that examined the relationship between coffee intake and adiposity as indicated by weight, BMI, or WC. Studies that tested the effect of coffee extract supplements were excluded. Studies that reported results only from univariable analyses because estimates from these studies are highly likely to be confounded by factors such as age, alcohol intake, and smoking were also excluded. Because obesity patterns in men and women generally differ, with men being more prone to abdominal adiposity (“apple shape”) and women more prone to lower-body adiposity (“pear shape”), coffee intake, if plays a role in inducing obesity, may exert differential effects by sex. For this reason, separate estimates by sex were extracted unless studies provided only a pooled estimate.
From each study, the following information was extracted: First author, publication year, study design, characteristics of study population (e.g., cohort name, country, age at enrollment, sex, sample size), unit and type of coffee intake, measure and definition of obesity, and variables controlled for. For studies that used continuous outcome (i.e., BMI, WC), mean or mean difference and corresponding standard deviation were extracted. For studies that used binary outcome (i.e., the status of overall and central obesity as indicated by BMI and WC, respectively), relative risk (RR) (odds ratio, rate ratio, or hazard ratio) and 95% confidence interval (CI) were extracted. To obtain summary estimates accounting for potential clinical and methodological variations across studies, the results were pooled using DerSimonian-Laird random effects model [20]. Heterogeneity in the relationship between coffee intake and adiposity across studies was quantified by I2 statistic, which represents the percentage of total variation across studies that is attributable to between-study heterogeneity [21]. Potential for small study effects, such as publication bias, was assessed using Egger’s test [22].
The included studies assessed obesity by body mass index (BMI, a measure of overall adiposity) or waist circumference (WC, a measure of central adiposity) and analyzed the measure as a continuous outcome or binary outcome. Using a random effects model, weighted mean difference (WMD) and 95% confidence interval (CI) were obtained for continuous outcomes; summary relative risk (RR) and 95% CI for the highest vs. lowest categories of coffee intake were estimated for binary outcome.
Key Findings
The meta-analysis revealed several notable findings:
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- BMI: For BMI, WMD was −0.08 (95% CI −0.14, −0.02); RR was 1.49 (95% CI 0.97, 2.29).
- WC: For WC, WMD was −0.27 (95% CI −0.51, −0.02) and RR was 1.07 (95% CI 0.84, 1.36).
- Sex Differences: In subgroup analysis by sex, evidence for an inverse association was more evident in men, specifically for continuous outcome, with WMD −0.05 (95% CI −0.09, −0.02) for BMI and −0.21 (95% CI −0.35, −0.08) for WC.
Impact of Caffeine Intake on Weight Loss: A Meta-Analysis of Randomized Controlled Trials
A separate systematic review and meta-analysis of randomized controlled trials (RCTs) was performed to summarize the effect of caffeine intake on weight loss. This review searched databases including MEDLINE, EMBASE, Web of Science, and Cochrane Central Register of Controlled Trials until November 2017. The relevant data were extracted and assessed for quality of the studies according to the Cochrane risk of bias tool. An intake-status regression coefficient (Beta) was estimated for each primary study, and the overall pooled Beta and SE were estimated using random effects meta-analysis on a double-log scale. Heterogeneity between studies was assessed by the Cochran Q statistic and I-squared tests (I2).
Data Analysis
Thirteen RCTs with 606 participants were included in the meta-analyses. The overall pooled Beta for the effect of caffeine intake was:
- 0.29 (95%CI: 0.19, 0.40; Q = 124.5, I2 = 91.2%) for weight
- 0.23 (95%CI: 0.09, 0.36; Q = 71.0, I2 = 93.0%) for BMI
- 0.36 (95% CI: 0.24, 0.48; Q = 167.36, I2 = 94.0%) for fat mass
For every doubling in caffeine intake, the mean reduction in weight, BMI, and fat mass increased 2 Beta-fold (20.29 = 1.22, 20.23 = 1.17, and 20.36 = 1.28), which corresponding to 22, 17, and 28 percent, respectively.
Diverse Studies on Coffee and Weight Management
Several studies have examined the effect of coffee intake on adiposity, as assessed by diverse anthropometric measures including body mass index (BMI) or waist circumference (WC). However, the results are largely inconsistent with results ranging from suggesting anti-obesity benefit [1,16,17] to reporting no effect [8,11] and even indicating increased obesity associated with higher coffee consumption [6,7].
Detailed Findings from the Meta-Analysis
The meta-analysis included a total of 12 studies. Detailed information on these studies is delineated in Table S2. In brief, out of the 12 studies, six studies provided the results for overall adiposity based on BMI [5,6,7,8,11,13] and 10 studies for central adiposity based on WC [4,6,8,9,10,11,12,13,14,15]. By study design, 11 studies were cross-sectional studies and one study was a cohort study [15]. By country, five studies were conducted in Asia [6,10,12,13,14], five studies in Europe [4,7,9,11,15], and two studies in America [5,8].
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Continuous BMI
Based on three studies [5,8,11] that reported outcomes in continuous BMI, the summary WMD in BMI comparing the highest vs. lowest categories of coffee intake was −0.08 (95% CI = −0.14, −0.02) (Figure 2A). While high heterogeneity was indicated (I2 = 65%), it was largely driven by difference in effect size and not by inconsistency in the direction of associations. There was no evidence of small study effects, such as publication bias (PEgger = 0.39). By sex, a significant inverse association was found in men (WMD = −0.05, 95% CI = −0.09, −0.02, I2 = 0%) but not in women (WMD = −0.12, 95% CI = −0.27, 0.03, I2 = 84%) (Table 1).
Overall Obesity Defined by BMI
A total of three studies were included [6,7,13], of which two Asian studies [6,13] analyzed overweight and obesity as a single category. The summary RR of overweight or obesity comparing the highest vs. lowest categories of coffee intake was 1.49 (95% CI = 0.97, 2.29). There was very high heterogeneity (I2 = 94%) (Figure 2B), with studies conducted in South Korea [6,13] showing variable but strong positive associations (summary RR = 1.71, 95% CI = 1.12, 2.61, I2 = 86%). Small study effects, such as publication bias, were not indicated (PEgger = 0.19). In subgroup analysis by sex, the association was not significantly heterogeneous (Pheterogeneity = 0.13), but a significant positive association was pronounced in women (summary RR = 2.01, 95% CI = 1.25, 3.21, I2 = 83%) than in men (summary RR = 1.25, 95% CI = 0.95, 1.65, I2 = not relevant) (Table 1).
Continuous WC
Based on four studies [8,10,11,15], the summary WMD in WC comparing the highest vs. lowest categories of coffee intake was −0.27 (95% CI = −0.51, −0.02), with moderate heterogeneity (I2 = 45%) (Figure 3A). There was no evidence of small study effects, such as publication bias (PEgger = 0.98). Within each sex, an inverse association was suggested, but it was statistically significant only in men (WMD = −0.21, 95% CI = −0.35, −0.08, I2 = 0%) (Table 1).
Central Obesity Defined by WC
A total of six studies were included in this meta-analysis [4,6,9,12,13,14]. In defining central obesity, the cutoff of WC ≥ 90 cm was used in men except for one study (WC ≥ 85 cm) [12] and WC ≥ 80 cm was used in women except for three studies (WC ≥ 85 cm) [12,13,14]. The summary RR of central obesity comparing the highest vs. lowest categories of coffee intake was 1.07 (95% CI = 0.84, 1.36) (Figure 3B). The degree of heterogeneity in the associations was very high (I2 = 82%), with studies published in Asia showing opposite associations [6,12,13,14]. Small study effects were not indicated (PEgger = 0.92). In subgroup analysis by sex, higher coffee intake was associated with reduced central obesity in men (summary RR = 0.90, 95% CI = 0.66, 1.23) but increased central obesity in women (summary RR = 1.18, 95% CI = 0.75, 1.86) (Table 1). However, the associations were not statistically significant and there was no evidence of heterogeneity by sex (Pheterogeneity = 0.59).
Observational Studies: Mixed Results
Many studies have explored the relationship between coffee-one of the most commonly consumed beverages today-and obesity. Despite inconsistent results, the relationship has not been systematically summarized. Several studies have examined the effect of coffee intake on adiposity, as assessed by diverse anthropometric measures including body mass index (BMI) or waist circumference (WC) [4,5,6,7,8,9,10,11,12,13,14,15]. However, the results are largely inconsistent with results ranging from suggesting anti-obesity benefit [1,16,17] to reporting no effect [8,11] and even indicating increased obesity associated with higher coffee consumption [6,7].
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Factors Influencing the Relationship
The relationship between coffee intake and weight management is complex and can be influenced by various factors:
- Type of Coffee: The type of coffee consumed (e.g., caffeinated vs. decaffeinated, sweetened vs. unsweetened, added cream vs. no cream) may have differential effects on adiposity.
- Cultural Differences: Studies conducted in Korea, where instant coffee mixes containing sugar and creamer account for a major proportion of overall coffee consumption, were included in the meta-analyses of binary outcome only, mostly contributing highly positive associations between coffee intake and obesity [6,13].
- Individual Variations: The effects of coffee on weight management may vary depending on individual factors such as genetics, metabolism, and lifestyle.
- Study Design: The cross-sectional nature of many studies limits the ability to infer temporal relationships between coffee intake and adiposity; residual confounding by smoking cannot be ruled out.
Biological Mechanisms
Despite the modest degree of association between coffee intake and continuous BMI and WC, there are several biological mechanisms that add support to the anti-obesity benefit of coffee. Biologically active compounds in coffee, such as chlorogenic acid, caffeine, trigonelline, and magnesium, have shown to be associated with anti-obesity benefits [1]. Supplementation with chlorogenic acid reduced body weight, visceral fat mass, and triglyceride content in adipose tissue in high-fat-fed mice [23]. In an in vitro study, trigonelline inhibited adipocyte proliferation and lipid accumulation in differentiating adipocytes [24].
Limitations
There are several limitations in our meta-analysis. First, our study extends the limitations of the included studies, which were mostly cross-sectional. Thus, the validity of our meta-analysis to infer temporal relationship between coffee intake and adiposity is compromised; residual confounding by smoking cannot be ruled out. Larson et al. performed a sensitivity analysis among never smokers and an association became attenuated and statistically nonsignificant [11]. Additionally, due to insufficient data, no meta-analysis was conducted by type of coffee (e.g., caffeinated vs. decaffeinated, sweetened vs. unsweetened, added cream vs. no cream, etc.), which may have differential effects on adiposity. It is notable in our meta-analysis on central obesity that most studies published in Korea, where instant coffee mixes containing sugar and cream are widely consumed, found a positive association [6,13]. In the Lee study [6], a positive association was found even after the adjustment for sugar and cream additive use as covariates in their multivariable regression models. On the contrary, in another study conducted in Korea that defined coffee consumption as drinking coffee without sugar and cream by selecting subjects who responded that they consumed coffee with “almost no sugar added” and “almost no cream added,” an inverse association, albeit not statistically significant, was observed [14]. Furthermore, the highest vs. lowest categories of coffee intake ranged from 0 cup/day to >6 cups/day among the studies included in our meta-analysis. However, we did not conduct a separate meta-analysis based on the difference in coffee intake levels between the extreme categories because only a few studies provided all required information for such analysis. Only three studies [6,7,15] provided an estimate for at least 3 cups/day of difference in intake and they reported discordant endpoints (continuous BMI, binary BMI, continuous WC, binary WC). Finally, our meta-analysis included a small number of studies. However, based on Egger’s test, we found no evidence of small study effects, such as publication bias, in our results even after using more strict cutpoint (PEgger < 0.1).