Waist-to-Hip Ratio - Health metric data from CDC NHANES 2017-2020
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Population health research has established robust benchmarks for this metric across diverse demographic groups. This analysis focuses specifically on Male aged 18-29, with data representing All populations. The interquartile range of 0.9 to 1.0 represents the central 50% of values where most healthy individuals fall. Understanding these benchmarks enables more accurate health monitoring and supports evidence-based decision-making.
A measurement of this metric Anthropometric measurements like this metric quantify physical body characteristics that reflect growth, development, and nutritional status. Measured in standard units, this metric serves as a foundational health indicator used across clinical, research, and public health contexts. These measurements have centuries of history in medical practice and remain essential today for assessing physical health status.
Reliable this metric measurement depends on properly calibrated equipment and trained personnel. The NHANES survey utilizes medical-grade instruments that undergo regular calibration checks. Measurement equipment meets strict specifications for precision and accuracy. Technicians complete comprehensive training programs before conducting measurements and receive ongoing quality assurance monitoring. For consistent results, equipment should be calibrated according to manufacturer specifications, measurement environment should be controlled, and standardized procedures should be followed precisely. These quality measures ensure that this metric values are meaningful and comparable.
The chart below shows how Waist-to-Hip Ratio is distributed across the population. The percentile values help you understand where you fall relative to others in your demographic group.
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This metric does not have enough statistical parameters for generating a visualization.
Comparing your this metric to population percentiles reveals where you stand relative to others in your demographic group. A value at the 25th percentile (0.9) means approximately one-quarter of the population has lower values than yours. At the 75th percentile (1.0), three-quarters of the population falls below your value. These comparisons provide context for understanding your individual measurement.
0.8
5% of the population falls below this value. This represents the lower range of typical variation.
0.87
25% of the population falls below this value. This represents the lower-middle range.
0.92
This is the middle value. 50% of the population falls below and 50% falls above this value.
0.97
75% of the population falls below this value. This represents the upper-middle range.
1.04
95% of the population falls below this value. This represents the upper range of typical variation.
0.92
The arithmetic average of all values. This may differ from the median if the distribution is skewed.
The intersection of demographic factors creates unique patterns in this metric that require matched reference data for accurate assessment. For Male All individuals aged 18-29, the combination of ethnicity, age, and sex produces a specific profile that differs from other demographic combinations. Using precisely matched reference data provides the most relevant comparison for your individual measurement. This demographic specificity enhances the clinical utility and personal relevance of benchmark comparisons.
What determines your this metric? The answer involves both nature and nurture working together throughout life. Inherited genetic factors set the framework, while nutritional intake, physical activity levels, and overall health status shape the final result. Environmental influences from prenatal development through adulthood contribute to the variation we observe across individuals. Some factors remain fixed while others offer opportunities for positive change through lifestyle modifications.
this metric represents one component within the complex picture of overall health. No single metric defines health status; this metric values gain meaning when interpreted alongside other measurements, symptoms, lifestyle factors, and health history. A value that appears concerning in isolation may be less significant when viewed within broader context—and vice versa. Within Anthropometry assessment, this metric contributes specific information that clinicians synthesize with related indicators. Healthcare providers integrate this metric with other data to form comprehensive assessments and recommendations. Maintaining perspective on this metric as part of a larger health picture supports balanced interpretation and appropriate response to individual values.
From clinical perspective, this metric provides actionable health information when properly contextualized. In anthropometry assessment, this metric helps clinicians evaluate current status, track changes, and guide interventions. but individual assessment considers the complete clinical picture. Discussion with healthcare providers enables personalized interpretation relevant to your specific health situation.
Research on this metric has established robust population benchmarks that inform clinical practice and public health policy. The NHANES program, conducted continuously since the 1960s, provides among the most comprehensive this metric data available. This nationally representative survey combines standardized physical measurements with health interviews, enabling researchers to understand how this metric relates to health outcomes across diverse populations. NHANES data has informed countless research studies, clinical guidelines, and health policies.
Applying this metric knowledge to real-world health decisions involves several practical considerations. First, obtain accurate measurements under appropriate conditions. Second, compare your values to demographic-matched benchmarks. Third, consider trends over time rather than isolated values. Fourth, discuss findings with healthcare providers who can integrate this metric with your complete health picture. Fifth, if warranted, take evidence-based actions to optimize your this metric through lifestyle modifications or medical interventions.
日本のデータは厚生労働省が毎年実施する「国民健康・栄養調査」に基づいています。2019年調査では約5,000世帯が参加しました。
日本の国民皆保険制度は全国民をカバーし、定期健康診断と予防医療を重視しています。
公式データ 厚生労働省 ↗
注：主要データはCDC NHANES（米国）からのものです。地域統計は公式の国民健康調査に基づいています。 (2024-01)
Normal this metric encompasses a range of values that varies by demographic group. For individuals aged 18-29, Male, All population, the median value is 0.9. Values between the 5th and 95th percentiles (0.8 to 1.0) represent normal variation. Using demographic-matched benchmarks ensures appropriate comparison.
Percentiles show where your this metric falls relative to others in your demographic group. At the 50th percentile (0.9), half the population is above and half below. Between the 25th (0.9) and 75th (1.0) percentiles represents the middle half of the distribution—where most healthy values fall. Percentiles at extreme ends (below 5th or above 95th) are less common but not necessarily abnormal. Context matters for interpretation.
this metric can change over time due to age-related processes, lifestyle modifications, health conditions, and interventions. Some factors are relatively fixed (like genetics), while others respond to deliberate changes (like exercise or diet). In the 18-29 age range, age-related changes may be occurring. Tracking your this metric over time reveals personal trends that provide valuable health information. Consistent measurement conditions enable meaningful comparison of values over time.
Consider discussing your this metric with a healthcare provider if: values fall significantly outside normal range (below 5th or above 95th percentile), you've noticed substantial changes over time, values are associated with symptoms, or you have questions about health implications. Being at a percentile extreme doesn't automatically indicate problems—many healthy individuals naturally fall at distribution tails. Clinical significance depends on context, symptoms, and other health factors. Healthcare providers can offer personalized interpretation.
this metric values differ across ethnic groups due to genetic, environmental, and lifestyle factors. All populations show characteristic patterns that reflect population-specific genetics, dietary traditions, activity patterns, and environmental influences. These differences are normal and expected—not indicators of better or worse health. Using All-specific reference data ensures your comparison reflects meaningful variation rather than expected population differences. This demographic specificity improves the accuracy and relevance of health assessment.
