Waist-to-Hip Ratio and Smoking
Waist-to-hip ratio (WHR) is calculated by dividing waist circumference by hip circumference and serves as one of the most widely used anthropometric measures of body fat distribution pattern. Unlike BMI, which captures total body size, WHR specifically reflects how fat is distributed between the central abdominal region and the peripheral hip and gluteal region. Large population studies have identified multiple genetic loci that contribute to an individual tendency toward a particular WHR, and this page summarizes what that research shows.
What is waist-to-hip ratio?
Waist-to-hip ratio is a dimensionless number obtained by dividing the circumference of the waist—typically measured at the narrowest point of the torso near the navel—by the circumference of the hips measured at the widest point around the buttocks. Population-derived reference values have historically been used in clinical settings, though these thresholds are not absolute standards.
WHR captures the distribution of adipose tissue rather than total adiposity. Two individuals with identical BMI can have very different WHR values—one with a pear-shaped distribution carrying proportionally more fat around the hips, the other with an apple-shaped distribution carrying more weight around the abdomen. These distribution patterns have different metabolic and physiological correlates, which is why WHR is studied as a distinct phenotype from total body weight.
Sex differences in WHR are substantial. On average, women have lower WHR than men due to hormonal effects on fat patterning—estrogen promotes gluteofemoral fat accumulation while androgens favor central deposition. After menopause, as estrogen levels decline, women typically see a shift toward higher WHR. This sex-specific biology is reflected in the genetic architecture: many WHR-associated genetic loci have markedly different effect sizes in males and females.
The genetics behind waist-to-hip ratio
WHR is a polygenic trait shaped by hundreds of common genetic variants with individually small effects. Genome-wide association studies (GWAS) have used WHR adjusted for BMI (WHRadjBMI) as the primary phenotype to identify loci that influence fat distribution independently of total body size.
Among the genes at associated loci in this research, several fall within intersecting biological pathways. ADAMTS9 encodes a secreted zinc metalloendopeptidase in the ADAMTS family—enzymes involved in extracellular matrix remodeling, including cleavage of the versican proteoglycan. Because extracellular matrix composition influences adipocyte differentiation, lipid storage capacity, and fat depot organization, genes like ADAMTS9 are biologically plausible candidates at fat distribution loci.
ABCA1 encodes a membrane-associated ATP-binding cassette transporter responsible for exporting cholesterol and phospholipids from cells to lipid-poor apolipoproteins, a key step in reverse cholesterol transport. ABCA1 variants are well established in the genetics of HDL cholesterol levels and lipid metabolism more broadly, which intersects with adipose tissue function and fat patterning. Population studies have identified ABCA1 variants in genomic contexts associated with WHR and related body composition traits.
ANKRD55, containing ankyrin repeat domains, has appeared in GWAS of multiple complex traits including adiposity-related phenotypes. Its presence in WHR-associated genomic regions has been reported in large-scale analyses, and it represents one of the loci with plausible adipose-tissue-relevant biology.
The genetic architecture of WHRadjBMI shows particularly pronounced sex differences compared to many other anthropometric traits. Several loci have effect sizes two to three times larger in women than in men, or appear specific to one sex. This suggests that genetic effects on fat distribution interact with the hormonal and developmental environment differently across sexes.
What the research says
Research base: Robust
WHR and its adjusted form WHRadjBMI have been extensively studied in large-scale GWAS, enabling robust identification of associated loci.
A large-scale genome-wide association analysis of waist-to-hip ratio measures involving hundreds of thousands of adults identified dozens of loci reaching genome-wide significance. A notable feature of the genetic architecture was sex-heterogeneity: multiple loci showed substantially larger effects in women than in men, consistent with the role of sex hormones in fat distribution regulation (Author et al., 2017, PMID: 28443625).
Heritability estimates for WHR from twin studies are in the range of 22 to 55 percent, with estimates varying by population and methodology. After adjusting for BMI—to focus on distribution rather than total adiposity—heritability remains meaningfully above zero, confirming that the pattern of fat storage has genetic influences independent of total fat mass.
Twin study analyses of WHRadjBMI estimate heritability in the range of 20–50%, indicating that genetic variation contributes to individual differences in central-versus-peripheral fat distribution patterns beyond what is explained by total body size.
The relationship between WHR genetics and downstream metabolic phenotypes has been explored through Mendelian randomization approaches, which use genetic variants as instruments to probe causal relationships. These analyses have suggested that the fat distribution pattern captured by WHR may have independent associations with cardiometabolic parameters beyond what BMI alone captures, though causal inference in this area remains an active research topic.
How waist-to-hip ratio affects you
WHR is one measure among many that describes body composition and fat distribution. A genetic tendency toward a particular WHR pattern reflects population-level statistical associations, not a fixed prediction of any individual measurements or health outcomes. Many individuals with higher genetic scores for WHR have lower measured WHR in practice, because lifestyle, hormonal status, age, and other factors have large independent effects.
Physical activity meaningfully influences WHR independent of total weight change. Aerobic exercise and resistance training are both associated with reductions in central adiposity relative to hip circumference in controlled studies. Dietary patterns—particularly those emphasizing fiber, reduced refined carbohydrates, and healthy fat sources—are associated with favorable shifts in fat distribution over time.
Hormonal changes including those related to menopause or hormonal medication use are major modifiers of WHR in females. Sleep quality and stress-related cortisol dynamics also influence central fat accumulation. A genetic tendency is one factor operating within this complex system.
Working with your waist-to-hip ratio profile
The ExomeDNA WHR result reflects genetic associations identified in large population studies. It should be understood as a population-level tendency, not a measurement of current WHR or a fixed biological outcome.
For individuals interested in supporting a healthier fat distribution pattern, the strongest lifestyle levers include:
- Aerobic exercise: Sustained moderate-to-vigorous aerobic activity has robust evidence for reducing visceral and abdominal adiposity, including effects on WHR independent of total weight loss.
- Resistance training: Building muscle mass through resistance exercise increases basal metabolic rate and shifts body composition toward reduced relative central adiposity over time.
- Dietary fiber and food quality: Diets higher in fiber, vegetables, and minimally processed foods are associated with more favorable fat distribution patterns in large observational studies.
- Sleep and stress management: Elevated cortisol from poor sleep or chronic stress preferentially promotes central fat deposition; addressing these modifiable factors may support healthier WHR trajectories.
For questions about body composition, fat distribution, and personal health goals, a healthcare professional or registered dietitian can provide individualized guidance.
Research base: Robust. This genetic association is supported by large-scale, replicated GWAS evidence. Association does not imply causation, and individual outcomes depend on many genetic and non-genetic factors. See our methodology page for how ExomeDNA evaluates evidence quality.
Related traits and genes
WHR shares substantial genetic overlap with body fat distribution more broadly. Loci identified for WHRadjBMI are often the same loci detected in analyses of body fat distribution, waist circumference, and related anthropometric indices.
The ADAMTS metalloproteinase family—including ADAMTS9—appears at multiple body composition loci in GWAS, pointing to ECM remodeling as a recurring pathway in the genetics of fat patterning. ABCA1 connects WHR research to lipid metabolism pathways, reflecting the known relationship between central adiposity and lipid profiles.
Related traits: Body Fat Distribution | Body Mass Index Tendency | Waist Circumference Tendency | HDL Cholesterol Tendency | Triglyceride Levels
Frequently asked questions
What is WHR and how is it calculated? Waist-to-hip ratio is calculated by dividing waist circumference (measured at the narrowest torso point, near the navel) by hip circumference (measured at the widest buttocks point). A lower number indicates a more peripheral fat distribution pattern; a higher number indicates a more central pattern.
Is waist-to-hip ratio more informative than BMI? WHR and BMI capture different aspects of body composition. BMI reflects total body size and weight relative to height; WHR reflects the pattern of fat distribution independent of total adiposity. Each provides different information. GWAS phenotypes like WHRadjBMI are specifically designed to capture distribution pattern by statistically removing the influence of total body mass.
What genes are associated with waist-to-hip ratio? GWAS have identified dozens of loci significantly associated with WHRadjBMI. Genes at these loci include ADAMTS9 (an extracellular matrix metalloproteinase), ABCA1 (a cholesterol transporter with roles in lipid metabolism), and ANKRD55 (associated with adiposity-related phenotypes in population studies), among others.
Why do sex differences exist in WHR genetics? Multiple WHR-associated loci show substantially larger effects in women than in men. This sex-specific genetic architecture likely reflects the role of estrogen in promoting gluteofemoral fat accumulation, which creates the lower WHR commonly observed in females before menopause. Variants that relate to hormonal regulatory pathways may explain much of this sex heterogeneity.
Can lifestyle changes influence WHR regardless of genetics? Studies consistently show that aerobic exercise, resistance training, dietary quality, and sleep optimization influence fat distribution patterns, including central-versus-peripheral adiposity ratios. While genetic tendencies shape baseline tendencies, they do not determine the response to lifestyle interventions.
Written by Scott Peeples, BS Biomedical Sciences | ExomeDNA Founder Reviewed by ExomeDNA Editorial Process
Results are not a clinical test, not a treatment recommendation, and not a substitute for professional healthcare. This page provides wellness education and is not a substitute for clinical care.
References
- Author et al. (2017). Genome-wide association study of waist-to-hip ratio and body fat distribution. PMID: 28443625.
Data sources: GWAS Catalog | Open Targets | ClinVar | ClinGen