BODY BENCHMARKS

Name: Body Benchmarks Human Metrics Database
Creator: Body Benchmarks

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Body Fat Percentage, 18-29, Male, All

Body Fat Percentage - Health metric data from CDC NHANES 2017-2020

Body Benchmarks Research TeamMPH, MS

Health Metrics Specialists

Dedicated team of health scientists and data analysts specializing in body metrics research and population health data.

About Body Publications

Reviewed by: Health Metrics Team

Comprehensive Guide to Body Fat Percentage, 18-29, Male, All

Evidence-based health assessment relies on accurate population benchmarks. this metric measurements for Male aged 18-29 (All population) provide essential reference points backed by rigorous scientific methodology. With a median value of 19, the distribution reveals meaningful patterns about population health. This comprehensive analysis examines measurement protocols, statistical distributions, clinical significance, and practical implications for health monitoring.

What is Body Fat Percentage?

A measurement of this metric this metric serves as an important indicator within comprehensive health assessment. Expressed in standard units, this measurement enables meaningful comparisons to population benchmarks and personal health tracking over time.

How is Body Fat Percentage Measured?

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.

Distribution & Percentiles

The chart below shows how Body Fat Percentage is distributed across the population. The percentile values help you understand where you fall relative to others in your demographic group.

Insufficient data for visualization

This metric does not have enough statistical parameters for generating a visualization.

Understanding Percentile Distribution

Comparing your this metric to population percentiles reveals where you stand relative to others in your demographic group. A value at the 25th percentile (13.9) means approximately one-quarter of the population has lower values than yours. At the 75th percentile (24.1), three-quarters of the population falls below your value. These comparisons provide context for understanding your individual measurement.

Percentile Values Breakdown

5th Percentile (P5)

6.7

5% of the population falls below this value. This represents the lower range of typical variation.

25th Percentile (P25)

13.9

25% of the population falls below this value. This represents the lower-middle range.

50th Percentile (Median)

This is the middle value. 50% of the population falls below and 50% falls above this value.

75th Percentile (P75)

24.1

75% of the population falls below this value. This represents the upper-middle range.

95th Percentile (P95)

31.3

95% of the population falls below this value. This represents the upper range of typical variation.

Mean (Average)

The arithmetic average of all values. This may differ from the median if the distribution is skewed.

Statistical Summary

Standard Deviation7.5

Distribution TypeNormal

Population18-29, Male

Demographic Variations in Body Fat Percentage

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.

Factors Affecting Body Fat Percentage

What determines your this metric? Multiple factors contribute, from inherited genetic traits to daily lifestyle choices. Environmental influences, health conditions, and life stage all play roles in shaping individual values. Recognizing this multifactorial nature supports realistic interpretation and informed health decisions. Some influences offer opportunities for modification while others must simply be understood and accepted.

Health Implications of Body Fat Percentage

Interpreting this metric within proper context requires balanced consideration of population benchmarks and individual factors. Values within typical ranges generally indicate normal variation rather than health concerns. Values outside these ranges warrant contextual interpretation rather than automatic alarm—many healthy individuals fall at the extremes. Clinical significance depends on: how far values deviate from expected ranges, whether changes have occurred over time, presence of associated symptoms, and relationship to other health indicators. Consultation with healthcare providers enables personalized interpretation that accounts for your complete health picture.

Clinical Significance

Healthcare providers interpret this metric within comprehensive clinical assessment. but clinical interpretation weighs individual values against patient history, symptoms, other measurements, and treatment goals. Within Body Composition assessment, this metric contributes specific diagnostic and monitoring value. Clinicians use this metric data for screening, diagnosis, treatment monitoring, and outcome assessment—always interpreted within individual clinical context.

Research Insights

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.

Practical Applications

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.

🇩🇪 Regionale Gesundheitsdaten: Deutschland

✓Verifizierte Daten aus offiziellen Quellen

Die deutschen Daten stammen aus der DEGS1-Studie (Studie zur Gesundheit Erwachsener in Deutschland) des Robert Koch-Instituts mit über 7.000 gemessenen Teilnehmern.

Das deutsche Gesundheitssystem bietet universelle Krankenversicherung mit regelmäßigen Vorsorgeuntersuchungen und Gesundheits-Check-ups.

Offizielle Daten von Robert Koch-Institut ↗

Hinweis: Primärdaten stammen von CDC NHANES (USA). Lokale Statistiken stammen aus offiziellen nationalen Gesundheitserhebungen. (2024-01)

📊Data Transparency & Sources

Sources & References

Source Citation

Source:CDC NHANES 2017-2020

Year:2017-2020

Population:18-29 Male (All)

Evidence Level:Level 1 (nationally representative survey)

View Original Source →

Frequently Asked Questions

Is my this metric within normal limits?

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 19. Values between the 5th and 95th percentiles (6.7 to 31.3) represent normal variation. Using demographic-matched benchmarks ensures appropriate comparison.

How should I interpret my this metric percentile?

Percentiles show where your this metric falls relative to others in your demographic group. At the 50th percentile (19), half the population is above and half below. Between the 25th (13.9) and 75th (24.1) 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.

Is it possible to change my this metric?

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.

Should I worry about my this metric measurement?

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.

What explains ethnic variation in this metric?

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.

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