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Body Mass Index

Where your DNA places you among other people, and the studies behind it.

General information

Not tailored to your result, and not medical advice

Focus on Diet Quality Over Calorie Counting: Replacing ultra-processed foods with whole foods (vegetables, fruits, legumes, whole grains, lean proteins) tends to lower caloric intake without rigid counting. Higher ultra-processed food intake is associated with higher BMI and waist circumference, while Mediterranean-style patterns are linked to healthier weight. Fiber and protein improve satiety, which can reduce overall food intake. Nutrients (PMC)

Maintain Regular Physical Activity: Exercise alone usually produces modest weight loss but is important for weight maintenance and metabolic health. A common target is 150-300 minutes/week of moderate activity or 75-150 minutes of vigorous activity. Resistance training helps preserve muscle mass during weight loss, which supports resting energy expenditure. Obesity Reviews (PMC)

Prioritize Sleep Quality: Short sleep (<7 hours) is associated with higher ghrelin (a hunger signal), lower leptin (a satiety signal), and reduced insulin sensitivity - a profile linked to weight gain. A systematic review found short sleep associated with weight gain, particularly in younger people. Consistent 7-9 hours of sleep is an underused lever for weight management. Obesity (PMC)

Manage Stress and Emotional Eating: Chronic stress is associated with elevated cortisol, abdominal fat accumulation, and reward-driven 'comfort' eating. Mindfulness-based approaches, cognitive behavioral strategies, and regular physical activity can each help reduce stress-driven overeating. Noticing emotional eating patterns is a useful first step toward addressing them. International Journal of Preventive Medicine (PMC)

Know When to Ask for Help: If sustained lifestyle change has not been enough, that is common and not a personal failure. Body weight is regulated by biology that pushes back against loss. A clinician can look for contributing factors such as thyroid problems, sleep apnoea, or the side effects of existing medication, which is worth doing before assuming effort is the missing ingredient.

Genetics vs Environment

How much of this is genetic?

Genetics explains 73% of why people differ in this trait. The rest is environment, daily habits and chance.

Heritability estimate: Min et al. 2013, Obesity Reviews

About Body Mass Index

Background and further reading

Body Mass Index (BMI) is a measurement, not a diagnosis: weight in kilograms divided by height in meters squared. It is a screening tool rather than a direct measure of body fat, and it does not distinguish fat from muscle or account for where fat sits on the body. Even so, it remains the most widely used population-level proxy for adiposity. At a group level, a higher BMI is associated with greater risk of type 2 diabetes, heart disease, several cancers, and earlier death, and US public-health data note that roughly 2 in 5 adults meet the threshold for obesity [5]. BMI is a continuous trait, and the differences between people reflect a mix of genetic and environmental influences.

Genetic Basis: BMI is substantially heritable. Twin studies span a wide range - a systematic review of 32 twin studies reported a median heritability of about 73%, with individual estimates from 31% to 90% - and the commonly cited 40-70% figure reflects the lower, adult end of that spread [4]. The trait is highly polygenic. A 2018 GIANT meta-analysis in roughly 700,000 people of European ancestry pinned down 941 near-independent BMI signals across more than 500 genomic regions, yet genome-wide significant variants together explained only about 6% of BMI variation in an independent sample [2]. The strongest common signal sits at FTO (the fat mass and obesity-associated gene): each copy of the risk allele is associated with roughly a 0.39 kg/m² higher BMI - about 1 kg of extra weight for an average-height adult - acting largely through appetite rather than metabolic rate [3]. Rare loss-of-function mutations in MC4R (the melanocortin-4 receptor) disrupt satiety signalling and can cause severe early-onset obesity. Pathway analyses of these loci repeatedly point to the central nervous system - appetite, reward, and energy balance - rather than the body's resting metabolism [1].

Environmental Factors: Heritability describes variation within a population at a point in time; it does not cap how much weight can shift when surroundings change. The rise in obesity prevalence over the past half-century has happened far too quickly for the gene pool to explain it [5], which points to environment doing the heavy lifting. The modern 'obesogenic environment' - abundant calorie-dense and ultra-processed food, largely sedentary days, short or disrupted sleep, and chronic stress - interacts with inherited predisposition to make weight gain easier. Socioeconomic status, the local food environment, access to safe places to be active, and cultural eating patterns all contribute. A useful way to hold both facts together: genes shape how strongly a person responds to these conditions, while the conditions themselves largely set where BMI lands.

How this was calculated

The published research behind your score, and the variants it draws on.

Study Details

83 published scores from 19 studies

The body mass index score combines 83 polygenic scores drawn from 19 published studies.

Smit RAJ (2025). Polygenic prediction of body mass index and obesity through the life course and across ancestries. Nat Med: 1.2M

Gunn S (2024). Comparison of Methods for Building Polygenic Scores for Diverse Populations. HGG Adv: 1.3M

Borisevich D (2021). Non-linear interaction between physical activity and polygenic risk score of body mass index in Danish and Russian populations. PLoS One: 1.9M

Shim I (2023). Clinical utility of polygenic scores for cardiometabolic disease in Arabs. Nature Communications: 1.1M

Zhang Y (2022). Genetic determinants of cardiometabolic and pulmonary phenotypes and obstructive sleep apnoea in HCHS/SOL. EBioMedicine: 749k

Campos AI (2021). Understanding genetic risk factors for common side effects of antidepressant medications Commun Med (Lond): 735k

Loesch DP (2025). Identification of plasma proteomic markers underlying polygenic risk of type 2 diabetes and related comorbidities. Nat Commun: 1.0M

Ma Y (2022). ExPRSweb: An online repository with polygenic risk scores for common health-related exposures. Am J Hum Genet: 7.4M

Weissbrod O (2022). Leveraging fine-mapping and multipopulation training data to improve cross-population polygenic risk scores. Nat Genet: 1.1M

Monti R (2024). Evaluation of polygenic scoring methods in five biobanks shows larger variation between biobanks than methods and finds benefits of ensemble learning. Am J Hum Genet: 1.0M

Chikowore T (2024). Variability of polygenic prediction for body mass index in Africa. Genome Med: 323k

Zhang H (2023). A new method for multiancestry polygenic prediction improves performance across diverse populations. Nat Genet: 742k

Truong B (2024). Integrative polygenic risk score improves the prediction accuracy of complex traits and diseases. Cell Genom: 4.5M

Jung H (2024). Integration of risk factor polygenic risk score with disease polygenic risk score for disease prediction. Commun Biol: 1.1M

Privé F (2022). Portability of 245 polygenic scores when derived from the UK Biobank and applied to 9 ancestry groups from the same cohort Am J Hum Genet: 990k

Ding Y (2022). Polygenic scoring accuracy varies across the genetic ancestry continuum in all human populations bioRxiv: 980k

Tanigawa Y (2023). Power of inclusion: Enhancing polygenic prediction with admixed individuals AJHG: 36k

Tanigawa Y (2022). Significant sparse polygenic risk scores across 813 traits in UK Biobank. PLoS Genet: 27k

Raben TG (2023). Biobank-scale methods and projections for sparse polygenic prediction from machine learning. Sci Rep: 26k

Sources

Locke AE, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature (2015)

Yengo L, et al. Meta-analysis of genome-wide association studies for height and body mass index in ~700,000 individuals of European ancestry. Human Molecular Genetics (2018)

Frayling TM, et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science (2007)

Min J, et al. Variation in the heritability of body mass index based on diverse twin studies: a systematic review. Obesity Reviews (2013)

Centers for Disease Control and Prevention About Obesity. U.S. Centers for Disease Control and Prevention (2024)

Related Traits

These traits are influenced by some of the same genes and variants as this one

Waist-Hip Ratio: The ratio of waist to hip circumference - a measure of abdominal fat distribution and cardiometabolic risk.

Type 2 Diabetes: A metabolic disorder characterized by insulin resistance and progressive beta cell dysfunction.

Coronary Artery Disease: Narrowing of coronary arteries due to atherosclerotic plaque, the leading cause of heart attacks.

Back to All Traits

Content updated August 2026.

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