BMI - Health metric data from CDC NHANES 2017-2020
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How does your this metric compare to others in your demographic group? For All population of Male in the 18-29 age range, understanding normal variation is crucial for meaningful health assessment. Values typically range from 15.9 to 37.3, encompassing 90% of the population. This guide provides the data-driven insights you need to interpret your measurements accurately and make informed decisions about your health.
A measurement of this metric this metric belongs to the category of anthropometric measurements that form the basis of physical health assessment. Expressed in standard units, this measurement enables comparison across individuals and populations. From pediatric growth charts to adult health screening, anthropometric data like this metric inform countless healthcare decisions.
The procedure for measuring this metric follows evidence-based protocols designed to maximize accuracy and reproducibility. NHANES measurements adhere to detailed procedural manuals that specify every aspect of the measurement process. From subject preparation to data recording, each step follows standardized procedures that minimize measurement error. Key procedural elements include: appropriate subject positioning, correct equipment use, consistent timing, and accurate recording. When these elements are standardized, this metric measurements provide reliable data for health assessment and comparison.
The chart below shows how BMI 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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The range of this metric values in the population spans considerable variation, all within normal bounds. From 15.9 to 37.3, the 5th-to-95th percentile range of 21.4 represents typical population variation. The narrower interquartile range of 8.8 (from 22.2 to 31) captures where most values concentrate. This natural variation reflects the diversity in healthy populations.
15.9
5% of the population falls below this value. This represents the lower range of typical variation.
22.2
25% of the population falls below this value. This represents the lower-middle range.
26.6
This is the middle value. 50% of the population falls below and 50% falls above this value.
31
75% of the population falls below this value. This represents the upper-middle range.
37.3
95% of the population falls below this value. This represents the upper range of typical variation.
26.6
The arithmetic average of all values. This may differ from the median if the distribution is skewed.
Demographic factors shape this metric values in meaningful ways that must be considered for accurate interpretation. Ethnicity influences this metric through genetic, environmental, and cultural factors unique to All populations. Research consistently shows demographic-specific patterns that make matched reference data essential. Age-related changes in the 18-29 group reflect developmental, hormonal, and lifestyle factors characteristic of this life stage. Biological sex differences affect this metric through hormonal influences, body composition variations, and physiological distinctions between Male individuals and others. Using demographic-matched benchmarks ensures your comparison reflects meaningful variation rather than expected population differences.
Multiple layers of influence shape this metric at both population and individual levels. Genetic variation explains why different demographic groups show different typical ranges. Within those ranges, lifestyle factors including nutrition, activity, and health habits determine individual positioning. Environmental factors such as socioeconomic status, access to healthy foods, and physical activity opportunities further contribute to observed patterns. This multifactorial nature makes this metric a reflection of overall life circumstances.
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。
日本は先進国の中でBMI平均が最も低い国の一つです。特定健診（メタボ健診）制度により40歳以上の健康状態が継続的にモニタリングされています。
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 26.6. Values between the 5th and 95th percentiles (15.9 to 37.3) 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 (26.6), half the population is above and half below. Between the 25th (22.2) and 75th (31) 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.
