Scientists have created the first population-level reference charts for a single number that captures two of the most consequential changes in the aging human body: how much fat we carry and how much muscle we keep. The metric, known as the fat mass to fat-free mass ratio, or FM/FFM, was charted across ages 45 to 86 using data from 28,791 adults enrolled in the Canadian Longitudinal Study on Aging. The resulting curves, published in the Journal of Cachexia, Sarcopenia and Muscle, function much like the growth charts pediatricians have used for decades, allowing any older adult’s body composition to be placed on a percentile scale relative to peers of the same age and sex.

The motivation behind the work lies in a diagnostic gap that has frustrated clinicians for years. Sarcopenic obesity, the coexistence of excess fat and declining muscle, is widely recognized as more dangerous than either condition alone, with documented links to falls, fractures, cardiometabolic disease, worse cancer outcomes and all-cause mortality. Yet estimates of how common it is range wildly, from 3 percent to more than 20 percent of older adults, depending entirely on which definition and cutoffs researchers choose. Most approaches simply define obesity and sarcopenia independently, for example by combining a body mass index of 30 or above with low appendicular muscle mass, even though the two conditions interact pathophysiologically in ways that independent thresholds cannot capture.

The FM/FFM ratio was first proposed as a measure of sarcopenic obesity by nutrition scientist Carla Prado and colleagues in 2012, and it rests on an elegant conceptual framework known as the load-capacity model. Fat mass represents metabolic load, the magnitude of the insult placed on the body, encompassing inflammation, lipid accumulation and heightened metabolic demands. Fat-free mass represents metabolic capacity, the machinery available to offset that insult through glucose regulation, lipid metabolism and general metabolic function. A higher ratio therefore signals a state in which load disproportionately exceeds capacity, which is precisely the imbalance at the heart of sarcopenic obesity. Because the ratio is continuous, it scales fat mass to the amount of metabolically active tissue, meaning two people with identical fat mass can carry very different metabolic risk depending on how much muscle supports them.

To build the reference curves, the research team drew on the comprehensive cohort of the Canadian Longitudinal Study on Aging, a population-based study of 51,338 adults across all ten provinces. Participants in the comprehensive cohort underwent in-person physical assessments, including whole-body dual X-ray absorptiometry, the gold-standard technique that quantifies tissue composition by measuring how low-emission X-ray beams attenuate as they pass through fat, lean tissue and bone. The analytic sample of 28,791 participants had a weighted mean age of 59.6 years and was weighted to represent roughly 3.6 million Canadian adults. Total lean mass served as a surrogate for fat-free mass, an approximation the authors justify because cellular lipid content accounts for only a small fraction of total body weight, at most 3 percent in men and 5 percent in women.

The statistical engine behind the charts is the LMS method, developed by Tim Cole and Pamela Green, which summarizes a measurement’s shifting distribution through three parameters: lambda for skewness, mu for the median and sigma for the coefficient of variation. At each single year of age, the team solved a system of twelve equations spanning the 1st through 99th percentiles, minimizing squared errors and selecting model flexibility by balancing curve smoothness against fit using the Bayesian information criterion. The output includes both percentiles and corresponding z-scores, giving clinicians the option of greater precision. Sensitivity analyses with unweighted data confirmed the results, and graphical checks of observed versus predicted percentiles and Q-Q plots of z-scores showed adequate fit and normality.

The findings reveal striking sex differences. Men’s FM/FFM values were consistently lower than women’s at every percentile examined, and men’s curves changed far less across the lifespan, never exceeding 0.75 at any age. Women’s values, by contrast, started higher and climbed more steeply, exceeding 1.1 between ages 55 and 65 before falling sharply in older age. At the 95th percentile, the maximum value reached 0.62 at age 70 for men but 0.99 at age 65 for women. At the median, the peak was 0.42 at age 86 for men versus 0.71 at age 68 for women. The overall pattern reflects the average aging trajectory: fat mass rises while muscle mass declines, pushing the ratio upward until very old age, when the trend reverses, potentially reflecting reductions in resting metabolic rate and macronutrient oxidation.

The authors attribute the sex gap to sexual dimorphism in body composition, a biological divergence that begins at birth and persists into adulthood, leaving adult men with greater total lean mass and lower fat mass than women. Sex hormones are central players: estrogen shapes adipose tissue accumulation, metabolism and distribution, while testosterone promotes lean mass. Hormonal upheaval may also explain why women’s percentiles shift more dramatically with age, since the menopausal transition triggers substantial changes in body composition, increasing fat mass while reducing fat-free mass. At the cellular level, differences in sex chromosomes are thought to drive sex-specific gene expression, and at the population level the phenomenon manifests as higher obesity prevalence among women.

The Canadian curves align closely with earlier reference charts built from United States and Chinese data. Using DXA measurements from 13,236 American adults in the 1999 to 2004 National Health and Nutrition Examination Survey, Siervo and colleagues reported a maximum median FM/FFM of 0.46 at age 74 for men and 0.76 at age 66 for women, figures remarkably similar to the Canadian values. Chinese adults from the Ningxia cohort, measured with bioelectrical impedance analysis, showed lower ratios overall, an intriguing difference given evidence that some Asian populations carry higher body fat and lower lean mass, possibly due to hormonal or genetic factors. The authors caution that differing measurement technologies, DXA versus bioimpedance, could partly explain the divergence.

The study carries notable strengths, including its large, nationally representative dataset and its use of DXA rather than surrogate measures. Importantly, the cohort spans midlife, ages 45 to 64, capturing the period when age-related body composition changes begin and when interventions might prevent sarcopenic obesity from taking hold in later life. Limitations remain: most participants identified as white, so racial and ethnic differences in FM/FFM require further study, and survivor bias cannot be fully excluded, though recruitment from age 45 mitigates the concern. The ratio also omits muscle function, such as gait speed or grip strength, which current sarcopenic obesity definitions consider essential; the authors suggest future work should explore integrating functional parameters into the percentile framework.

The practical promise of the charts is considerable. By folding age, sex, obesity and sarcopenia into one interpretable metric, FM/FFM percentiles could serve as a screening tool to flag patients who need intervention before measurable muscle loss occurs, and they give researchers a standardized way to study sarcopenic obesity-related health outcomes across populations. Future studies are expected to track how the percentile curves respond to specific interventions, from resistance training to emerging obesity therapies. For now, the work offers clinicians and public health planners something they have never had for Canadian older adults: a continuous, population-anchored yardstick for the balance between metabolic load and metabolic capacity as it evolves across the second half of life.

Subject of Research: Age- and sex-specific reference percentile curves for the fat mass to fat-free mass ratio as a measure of sarcopenic obesity in older Canadian adults

Article Title: Age‐ and Sex‐Specific Percentile Curves for the FM/FFM Ratio Using Data From the Canadian Longitudinal Study on Aging

Article References: Kim, C., Cook, C. E., & Banack, H. R. (2026). Age‐ and Sex‐Specific Percentile Curves for the FM/FFM Ratio Using Data From the Canadian Longitudinal Study on Aging. Journal of Cachexia, Sarcopenia and Muscle, 17(5), Article e70399. https://doi.org/10.1002/jcsm.70399

Image Credits: AI Generated

DOI: 10.1002/jcsm.70399

Keywords: sarcopenic obesity, fat mass to fat-free mass ratio, body composition, Canadian Longitudinal Study on Aging, DXA, aging, percentile curves, LMS method, metabolic load, metabolic capacity, sex differences, muscle mass