BODY BENCHMARKS

Name: Body Benchmarks Human Metrics Database
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Height, 18-29, Male, All

Height - 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.

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Reviewed by: Health Metrics Team

Comprehensive Guide to Height, 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 176.9, 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 Height?

A measurement of this metric Within the field of anthropometry—the science of human body measurement—this metric stands as a key indicator of physical status. Measured in appropriate units, it provides quantifiable data for health assessment, research studies, and clinical practice. Understanding this metric helps contextualize an individual's physical characteristics within broader population norms.

How is Height Measured?

Standardized measurement protocols ensure this metric data remains comparable across studies and populations. The CDC's NHANES program employs rigorously validated procedures developed over decades of population health research. Trained technicians use calibrated equipment following detailed protocols that specify positioning, timing, and environmental conditions. Multiple quality control measures—including regular equipment calibration, inter-rater reliability checks, and data validation—ensure measurement accuracy. Accurate this metric measurement requires attention to standardized conditions: appropriate equipment calibration, consistent measurement technique, proper subject preparation, and trained personnel. These factors minimize variability and ensure reliable results.

Distribution & Percentiles

The chart below shows how Height 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

From a clinical perspective, this metric percentiles guide interpretation and decision-making. The 5th percentile (164.6) marks the lower boundary where only 5% of the population falls below. Values in this range may warrant clinical attention depending on context. Similarly, the 95th percentile (189.2) represents the upper threshold, with only 5% exceeding this value. Clinicians use these benchmarks alongside other factors to assess individual health status.

Percentile Values Breakdown

5th Percentile (P5)

164.6

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

25th Percentile (P25)

171.8

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

50th Percentile (Median)

176.9

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

75th Percentile (P75)

182

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

95th Percentile (P95)

189.2

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

Mean (Average)

176.9

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 Height

Age significantly influences this metric through biological processes that vary across the lifespan. Young adults aged 18-29 typically demonstrate values reflecting peak physical development and physiological efficiency. For Male All individuals, age-specific benchmarks account for these developmental patterns. Age-appropriate reference data ensures accurate interpretation regardless of life stage.

Factors Affecting Height

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.

Health Implications of Height

What can your this metric measurement tell you about potential health actions? Values within normal ranges generally require continued monitoring rather than intervention. Values at extremes may suggest opportunities for lifestyle modification or the need for further evaluation. Key questions to consider: Has your this metric changed significantly over time? Do you have symptoms related to this metric? Do other health indicators suggest concern? Are lifestyle modifications possible? Many factors influencing this metric respond to lifestyle modifications, making proactive health management potentially impactful.

Clinical Significance

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 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.

🇰🇷 지역 건강 데이터: 대한민국

✓공식 출처에서 확인된 데이터

한국 데이터는 질병관리청이 매년 실시하는 국민건강영양조사(KNHANES)에 기반합니다. 이 조사는 전국적으로 약 10,000명을 대상으로 직접 측정을 실시합니다.

지역 비교

평균 남성173.5 cm출처: 국민건강영양조사 2021

평균 여성160.4 cm출처: 국민건강영양조사 2021

한국의 국민건강영양조사는 미국 NHANES를 모델로 설계되어 국제 비교가 용이합니다. 직접 측정 방식으로 높은 정확도를 보장합니다.

한국의 국민건강보험제도는 전 국민을 대상으로 하며, 국가건강검진 프로그램을 통해 정기적인 건강 모니터링을 제공합니다.

공식 데이터 질병관리청 ↗

참고: 주요 데이터는 CDC NHANES(미국)에서 가져온 것입니다. 지역 통계는 공식 국가 건강 조사에서 가져온 것입니다. (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

What is a normal this metric value?

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 176.9. Values between the 5th and 95th percentiles (164.6 to 189.2) represent normal variation. Using demographic-matched benchmarks ensures appropriate comparison.

What does my this metric percentile mean?

Percentiles show where your this metric falls relative to others in your demographic group. At the 50th percentile (176.9), half the population is above and half below. Between the 25th (171.8) and 75th (182) 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.

What influences changes in 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.

When is this metric a health concern?

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.

Should I use ethnicity-specific this metric benchmarks?

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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