Researchers at the University of Oulu analysed data from 2,264 participants, all aged 46, to investigate whether habitual coffee consumption was linked to circulating metabolites, cardiometabolic risk markers and reproductive hormones. The participants belonged to a long-running population cohort that has followed individuals born in northern Finland since 1966. Because the study included detailed information about body composition, lifestyle and biochemical measurements, the researchers were able to examine relationships between coffee intake and several biological systems at the same time.

One of the clearest findings concerned body composition. People who reported drinking more coffee generally had lower amounts of total body fat and visceral fat than those who consumed less, despite having similar body mass indexes. Visceral fat is stored around internal organs and is considered metabolically active; excess amounts are associated with inflammation, impaired insulin action and a higher risk of cardiometabolic disease. The higher-consumption group also had greater skeletal muscle mass, a result that may indicate differences in energy metabolism or lifestyle that are not captured by BMI alone.

BMI is widely used to classify people according to weight relative to height, but it cannot distinguish fat from muscle or reveal where fat is stored. Two people with the same BMI can therefore have substantially different metabolic risk profiles. The Finnish findings underline why more detailed measures of body composition can provide information that conventional weight-based metrics miss. However, the researchers do not interpret the results as proof that coffee directly reduces visceral fat or builds muscle. Coffee drinkers may differ from non-drinkers in other ways, and even carefully adjusted observational studies cannot eliminate every possible source of confounding.

The study also identified a common metabolic signature in both men and women. Higher coffee consumption was associated with lower circulating concentrations of branched-chain amino acids, a group that includes leucine, isoleucine and valine. These amino acids are essential nutrients involved in protein synthesis and energy metabolism, but persistently elevated levels in the bloodstream have been linked in previous research with insulin resistance and an increased risk of type 2 diabetes. Abnormal branched-chain amino-acid metabolism may reflect changes in how the body processes nutrients, although the present study cannot determine whether coffee intake caused the lower concentrations.

The strongest associations appeared among men. Higher coffee consumption was linked to a more favourable glucose–insulin profile, suggesting better regulation of blood sugar and insulin signalling. Coffee intake was also associated with higher concentrations of total testosterone, bioavailable testosterone and sex hormone-binding globulin, or SHBG. SHBG is a transport protein produced primarily by the liver that binds sex hormones in the bloodstream and regulates how much of those hormones remains available to tissues.

At the same time, men who consumed more coffee had modestly lower free testosterone and a lower free androgen index. This may appear contradictory because total testosterone was higher, but the difference reflects the complex relationship between hormone production and hormone transport. When SHBG levels rise, more testosterone can become bound in the circulation, leaving a smaller proportion unbound or biologically available in some tissues. Total hormone measurements and free-hormone measurements therefore provide different information and may move in opposite directions.

Among women, the hormonal associations were more limited. Higher coffee intake was primarily linked to increased SHBG and lower measures of free androgens. Androgens are often described as male hormones, but they are also produced and used in women, where they contribute to sexual function, bone health, muscle biology and other physiological processes. The sex-specific pattern observed in the study suggests that coffee consumption may interact with hormonal regulation differently depending on sex, although the researchers emphasise that the mechanisms remain uncertain.

“Coffee is consumed by millions of people every day, yet we still know surprisingly little about how it relates to our metabolism and hormones,” said Luca Verroest, the study’s lead author and a doctoral researcher at the University of Oulu. He said the most striking feature of the results was a distinct hormonal signature that remained visible even after accounting for BMI and lifestyle factors, with several associations differing between men and women. The findings raise the possibility that hormonal pathways partly contribute to the relationship between coffee consumption and metabolic health.

Coffee contains hundreds of biologically active compounds, including caffeine, chlorogenic acids, diterpenes and other substances that may influence glucose regulation, inflammation, liver metabolism and hormone-related pathways. Caffeine can affect the nervous system and energy expenditure, while chlorogenic acids have been investigated for their possible effects on glucose absorption and metabolism. The Finnish study did not establish which compounds were responsible for the observed associations, nor did it determine whether preparation methods, serving size, caffeine content or additions such as sugar and cream altered the results.

The research is particularly relevant in Finland, where coffee consumption is among the highest in the world and annual intake averages approximately 11.8 kilograms per person. Yet the population’s strong coffee-drinking culture also makes it important to interpret the findings carefully. Participants were assessed at a single age, and their reported consumption reflected habitual behaviour rather than a controlled dietary intervention. People who drink coffee regularly may also differ in sleep patterns, occupation, physical activity, diet, alcohol use, smoking habits or underlying health conditions. Although the researchers adjusted for lifestyle and other factors, residual differences may still influence the results.

The investigators say the findings provide a foundation for future research, including animal experiments and eventually controlled human intervention studies. Such studies will be needed to determine whether coffee itself produces changes in body composition, branched-chain amino-acid metabolism or sex-hormone regulation, and whether those changes translate into lower disease risk. Until then, the results demonstrate associations rather than cause and effect and are not sufficient to support new dietary recommendations. The study, titled “Associations of habitual coffee intake with testosterone and cardiometabolic markers: the Northern Finland Birth Cohort 1966 study,” was published in the European Journal of Nutrition on 16 July 2026.

Subject of Research: People

Article Title: Associations of habitual coffee intake with testosterone and cardiometabolic markers: the Northern Finland Birth Cohort 1966 study

News Publication Date: 16 July 2026

Web References: https://www.oulu.fi/en/news/study-links-coffee-consumption-metabolic-health-and-sex-hormones

References: https://doi.org/10.1007/s00394-026-04038-z

Keywords: Coffee, caffeine, metabolic health, body composition, visceral fat, skeletal muscle, branched-chain amino acids, insulin resistance, type 2 diabetes, testosterone, sex hormones, SHBG, cardiometabolic health, University of Oulu, Northern Finland Birth Cohort 1966

The investigation zeroed in on a condition referred to as sarcopenic obesity, characterized by the coexistence of excess adiposity and diminished muscle mass and strength. The findings were striking: individuals with sarcopenic obesity exhibited more than a three-and-a-half-fold greater risk of developing type 2 diabetes compared to those with healthy body composition. Remarkably, this group was 19% more likely to develop diabetes than those with obesity alone and 91% more likely than those suffering solely from sarcopenia.

Lead author Zhongyang Guan emphasized that the findings disrupt the pervasive assumption that excess body weight is the primary driver of diabetes risk. “Our data indicate that muscle deterioration is a significant contributor,” he said. This insight suggests that clinical assessments for diabetes risk should broaden beyond simple weight metrics to include evaluations of muscle strength and mass.

The study’s granular analysis showed that about 15% of participants classified as having sarcopenic obesity developed type 2 diabetes within a decade. By contrast, incidence rates were closer to 11% among people with obesity alone and merely 3% in those without any muscle or fat abnormalities. The researchers also noted that the association between muscle health and diabetes risk was particularly pronounced in women and individuals under 60 years of age.

Professor Mario Siervo, senior lead on the project, underscored the practical implications of these results for preventive healthcare. “By integrating muscle health assessments into routine screenings, clinicians may better identify high-risk patients earlier,” he explained. As global populations age and obesity rates climb, interventions aimed at preserving muscle integrity through physical activity and nutrition become increasingly vital to curb the diabetes epidemic.

Jessica Weiss, Clinical Services Manager at Diabetes WA, contextualized the findings within the biology of glucose metabolism. She pointed out that skeletal muscles are major consumers of circulating glucose during physical activity, which helps regulate blood sugar levels. Additionally, exercise reduces insulin resistance, a key pathological factor in type 2 diabetes development. “Maintaining muscle mass and consistently engaging muscles can significantly enhance the body’s ability to prevent or manage diabetes,” Weiss noted.

This study represents a paradigm shift in understanding diabetes risk factors by illuminating the dual importance of adiposity and musculoskeletal health. It advocates a more nuanced, multi-dimensional approach to diabetes prevention that transcends conventional weight-focused strategies, offering new hope in the fight against a growing global health challenge.

Subject of Research: People
Article Title: Sarcopenic Obesity and Risk of Incident Type 2 Diabetes: A Prospective Cohort Study and Landmark Analysis From the UK Biobank
News Publication Date: 13-Jul-2026
References: 10.2337/dc26-0797
Keywords: Diabetes, Muscles, Sarcopenic Obesity, Type 2 Diabetes, Muscle Health, Obesity, Insulin Resistance

Traditional markers like BMI, though widely used due to their simplicity, have increasingly been criticized for their inability to accurately reflect body fat distribution and quantity, factors which are closely linked to metabolic health risks. This is where RFM introduces a refined lens, incorporating height and waist measurements into a ratio that more directly estimates fat mass relative to total body size. The TLGS researchers capitalized on this method to provide robust evidence supporting RFM’s predictive validity, answering a critical question in epidemiology and clinical practice: how can we better quantify obesity-linked risk to forecast diabetes development?

The Tehran Lipid and Glucose Study cohort, a diverse and representative population sample, offered an ideal foundation for this inquiry. Over the decade-long follow-up, participants’ anthropometric data, lifestyle habits, and metabolic biomarkers were periodically recorded. Utilizing advanced statistical modeling, Masrouri and colleagues identified that individuals with elevated RFM values demonstrated a markedly higher hazard ratio for incident T2DM, independent of confounding variables such as age, sex, and other cardiovascular risk factors. This relationship persisted even when adjusting for BMI and WC, underscoring RFM’s unique and potent association with diabetes risk.

Biologically, this association is compelling. Adipose tissue plays a critical role not only as an energy reservoir but also as an active endocrine organ influencing insulin sensitivity and inflammatory responses. The excess fat mass captured by RFM likely encompasses visceral adiposity—a metabolically active fat depot implicated in insulin resistance and beta-cell dysfunction. Since BMI cannot distinguish between lean and fat mass and WC may be influenced by factors such as abdominal distension unrelated to fat, RFM’s design offers a more nuanced reflection of the adipose tissue burden relevant to pathophysiologic mechanisms driving T2DM.

Further dissecting the findings, the study illuminated nuances in sex-specific responses. Women, whose fat distribution often differs markedly from men, showed slightly different risk gradients, pointing to the need for sex-tailored cutoffs when interpreting RFM in clinical settings. Such insights could fuel personalized medicine approaches, enabling healthcare providers to stratify risk with greater precision and implement lifestyle or pharmacological interventions earlier, potentially forestalling the progression to overt diabetes.

The implications extend beyond individual risk prediction to public health strategy. With type 2 diabetes incidence escalating globally, particularly in urbanizing regions undergoing nutritional and lifestyle transitions, accessible and reliable tools for risk stratification are urgently needed. RFM provides a simple, non-invasive, and inexpensive metric easily derived from routine clinical or community health screenings. Incorporating RFM into screening protocols could enhance the identification of high-risk individuals otherwise mislabeled by traditional metrics.

Moreover, this study invites a revisitation of existing guidelines that prioritize BMI and WC as primary markers of metabolic risk. Given the mounting evidence supporting RFM, medical societies and policy frameworks might consider revising diagnostic criteria or recommending routine calculation of RFM during health assessments. Encouraging such paradigm shifts requires continued dissemination of these findings through clinical channels and engagement with policymakers, emphasizing the tangible benefit in reducing diabetes-related morbidity and healthcare burden.

From a methodological perspective, the TLGS team’s approach exemplifies rigorous longitudinal epidemiology, leveraging a well-characterized cohort, repeated measurements, and sophisticated analytical techniques to tease out complex associations. Their work bolsters growing consensus that refined anthropometric indices hold key insights into chronic disease etiology, warranting broader application both in research and clinical arenas. This may stimulate further validation studies across diverse populations or integration with emerging technologies like imaging or metabolomics for comprehensive risk profiling.

An intriguing aspect arising from the study’s data is the dynamic nature of RFM over time and its relationship with diabetes risk trajectories. Rather than viewing fat mass as static, longitudinal tracking allowed researchers to capture evolving patterns, potentially identifying critical windows where interventions might exert greatest benefit. Importantly, since RFM calculation requires only basic anthropometric inputs, it can be feasibly repeated in various settings, amplifying its utility for monitoring disease risk progression or response to therapy.

Critically, the study recognized limitations inherent in observational data, including residual confounding and generalizability outside the Iranian demographic context. Nevertheless, by accounting for a wide range of lifestyle and metabolic factors, the investigators minimized bias, and their findings nevertheless echo parallel reports from other cohorts, reinforcing RFM’s robustness as a predictive metric. Future research might focus on mechanistic explorations linking RFM changes to molecular pathways underpinning glucose dysregulation.

This research underscores an indispensable shift toward precision in obesity-related risk stratification, transcending the one-size-fits-all paradigm traditionally dominated by BMI. For clinicians grappling with diabetes prevention in an era of escalating prevalence and complex patient phenotypes, adopting RFM-centric frameworks could enhance screening accuracy. Early identification of individuals most susceptible to metabolic dysfunction opens avenues for tailored interventions ranging from dietary counseling to pharmacotherapy, potentially altering disease courses at a population scale.

Beyond clinical and epidemiological dimensions, the study raises awareness about the nuanced roles of adiposity beyond simple weight indices. RFM encapsulates the intricate interplay between body fat distribution and metabolic health, spotlighting the perils of underestimating fat’s biological activity when relying on crude metrics. Embracing this complexity can inspire innovative public health messaging and empower individuals with clearer understanding of their personal health markers.

In synthesizing these insights, the researchers advocate for a paradigm shift in diabetes risk assessment tools to encompass relative fat mass, which captures metabolic nuances overlooked by BMI and WC. This alignment with metabolic realities promises improved preventive strategies essential in curbing the global diabetes epidemic. As clinicians, researchers, and policymakers absorb these findings, RFM may soon become a cornerstone in metabolic health evaluation.

Ultimately, this study not only clarifies a critical link between fat mass and diabetes risk but also enriches the toolbox for addressing one of the most pressing public health challenges of our time. By refining risk estimation through RFM, science advances towards more effective, individualized approaches that hold promise for a healthier future free from the burdens of type 2 diabetes.

Subject of Research: Association between relative fat mass and incidence of type 2 diabetes mellitus

Article Title: Association of relative fat mass with the incidence of type 2 diabetes: over a decade follow-up from the TLGS

Article References:
Masrouri, S., Ebrahimi, N., Soraneh, S. et al. Association of relative fat mass with the incidence of type 2 diabetes: over a decade follow-up from the TLGS. Int J Obes (2025). https://doi.org/10.1038/s41366-025-01858-7

Image Credits: AI Generated

DOI: https://doi.org/10.1038/s41366-025-01858-7