BODY BENCHMARKS

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

Hemoglobin - 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 Hemoglobin, 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 16, 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 Hemoglobin?

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 Hemoglobin Measured?

Quality assurance in this metric measurement involves multiple layers of verification and standardization. The NHANES program implements comprehensive quality control including equipment maintenance schedules, technician certification requirements, duplicate measurement protocols, and statistical monitoring of measurement distributions. These measures ensure data integrity across the entire survey period. Whether in clinical settings or research contexts, quality this metric measurement requires: validated equipment, trained personnel, standardized protocols, and ongoing quality monitoring. These elements combine to produce trustworthy health data.

Distribution & Percentiles

The chart below shows how Hemoglobin 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

Interpreting your this metric measurement requires understanding what percentiles mean in practical terms. If your value matches the 50th percentile (16), you're exactly at the population median—neither high nor low relative to others. Values between 15 and 17 (25th to 75th percentile) are considered typical, representing the central half of the distribution. The extremes—below 14 or above 18—represent the outer 10% where values are less common but not necessarily abnormal. Percentile position helps contextualize your measurement within the broader population.

Percentile Values Breakdown

5th Percentile (P5)

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

25th Percentile (P25)

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)

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

95th Percentile (P95)

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 Deviation1.2

Distribution TypeNormal

Population18-29, Male

Demographic Variations in Hemoglobin

Population-specific patterns in this metric reflect the complex interplay of genetics, environment, and health behaviors. All populations exhibit characteristic this metric distributions that differ from other groups due to genetic predisposition, dietary patterns, physical activity norms, and environmental factors. These differences are well-documented in health research and inform demographic-specific reference ranges. Within All Male aged 18-29, these patterns become more specific, reflecting the intersection of multiple demographic factors. Acknowledging these differences doesn't imply better or worse—just different normal ranges that enable more accurate assessment.

Factors Affecting Hemoglobin

The factors influencing this metric span genetic inheritance, lifestyle behaviors, environmental conditions, and overall health status. This complexity means that individual values reflect numerous influences working together. While genetic factors set certain parameters, lifestyle modifications may still influence where values fall within those limits. Understanding these determinants supports meaningful interpretation of individual measurements.

Health Implications of Hemoglobin

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 Blood Count 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.

🇫🇷 Données de Santé Régionales: France

✓Données vérifiées de sources officielles

Les données françaises proviennent de l'étude ESTEBAN (Étude de SanTé sur l'Environnement, la Biosurveillance, l'Activité physique et la Nutrition), menée par Santé Publique France.

Le système de santé français offre une couverture universelle avec un accent sur la médecine préventive et le suivi régulier des indicateurs de santé.

Données officielles de Santé Publique France ↗

Note : Les données principales proviennent de CDC NHANES (USA). Les statistiques locales sont issues d'enquêtes nationales officielles. (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 16. Values between the 5th and 95th percentiles (14 to 18) represent normal variation. Using demographic-matched benchmarks ensures appropriate comparison.

Where does my this metric rank compared to others?

Percentiles show where your this metric falls relative to others in your demographic group. At the 50th percentile (16), half the population is above and half below. Between the 25th (15) and 75th (17) 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.

What this metric values require medical attention?

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.

Why do this metric values differ across ethnic groups?

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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