BODY BENCHMARKS

Name: Body Benchmarks Human Metrics Database
Creator: Body Benchmarks

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Ferritin (Adult, Male), Adult, Male, All

Ferritin (Adult, Male) - 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 Ferritin (Adult, Male), Adult, Male, All

Evidence-based health assessment relies on accurate population benchmarks. this metric measurements for Male aged Adult (All population) provide essential reference points backed by rigorous scientific methodology. With a median value of 150, 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 Ferritin (Adult, Male)?

A measurement of this metric This health metric, measured in appropriate units, provides valuable information for health assessment and monitoring. Understanding what this metric represents and how it varies across populations helps individuals and healthcare providers make informed decisions.

How is Ferritin (Adult, Male) Measured?

Measurement context significantly influences this metric values, making standardization essential. NHANES protocols carefully control measurement conditions to minimize contextual variability. Survey centers maintain consistent environments, and measurement timing follows prescribed schedules. These controls enable meaningful comparison of values across the entire survey population. Factors such as time of day, recent physical activity, food intake, and environmental conditions can affect this metric. Standardized measurement protocols account for these variables, ensuring that observed differences reflect true variation rather than measurement artifacts.

Distribution & Percentiles

The chart below shows how Ferritin (Adult, Male) 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 (150), you're exactly at the population median—neither high nor low relative to others. Values between 82.5 and 217.5 (25th to 75th percentile) are considered typical, representing the central half of the distribution. The extremes—below 15 or above 314.5—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)

82.5

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

50th Percentile (Median)

150

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

75th Percentile (P75)

217.5

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

95th Percentile (P95)

314.5

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

Mean (Average)

150

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

Statistical Summary

Standard Deviation100

Distribution TypeNormal

PopulationAdult, Male

Demographic Variations in Ferritin (Adult, Male)

Biological sex creates distinct patterns in this metric through hormonal, anatomical, and physiological differences. Male individuals demonstrate characteristic this metric distributions shaped by sex-specific hormonal profiles, body composition, and metabolic patterns. These differences emerge during puberty and persist throughout adulthood, making sex-specific reference data essential. Within All populations aged Adult, sex-based differences remain consistent with broader patterns while showing population-specific nuances. Using sex-matched benchmarks enables meaningful comparison that accounts for fundamental biological variation.

Factors Affecting Ferritin (Adult, Male)

Multiple determinants shape this metric at individual and population levels. Inherited factors, developmental conditions, lifestyle choices, and current health status all contribute to observed values. Environmental and socioeconomic factors further influence patterns. Understanding these diverse influences supports nuanced interpretation of this metric measurements and realistic health goal setting.

Health Implications of Ferritin (Adult, Male)

Tracking this metric over time provides more valuable health information than single measurements. While individual values inform current status, trends reveal important patterns: stable values suggest consistent health status, while changing values may indicate developing conditions or successful interventions. Establishing your personal baseline—through repeated measurements under similar conditions—enables meaningful comparison over time. Regular monitoring, whether through clinical visits or personal tracking, supports early detection of meaningful changes and evaluation of health interventions.

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.

🇩🇪 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:2020-2024

Population:Adult Male (All)

Evidence Level:Level 1 (nationally representative survey)

View Original Source →

Frequently Asked Questions

What this metric range is typical?

Normal this metric encompasses a range of values that varies by demographic group. For individuals aged Adult, Male, All population, the median value is 150. Values between the 5th and 95th percentiles (15 to 314.5) represent normal variation. Using demographic-matched benchmarks ensures appropriate comparison.

How do percentiles work for this metric?

Percentiles show where your this metric falls relative to others in your demographic group. At the 50th percentile (150), half the population is above and half below. Between the 25th (82.5) and 75th (217.5) 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 Adult 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 should I be concerned about my this metric?

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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