BODY BENCHMARKS

Name: Body Benchmarks Human Metrics Database
Creator: Body Benchmarks

You need to enable JavaScript to run this application.

ESR, Adult, Male, All

ESR - 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 ESR, Adult, Male, All

Whether you're tracking your health or interpreting clinical measurements, this metric benchmarks provide essential context. For Adult Male of All background, having demographic-specific reference data matters significantly for accurate interpretation. The population median of 10 serves as a central reference point, though individual optimal values may vary. Explore the complete distribution, understand what influences these measurements, and discover how to apply this knowledge to your health journey.

What is ESR?

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 ESR 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 ESR 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

The distribution of this metric values across the population follows a characteristic pattern that reveals important health insights. The central 90% of values fall between 2 (5th percentile) and 25 (95th percentile), defining the typical range for healthy individuals. At the center, the median value of 10 indicates that half the population falls above and half below this point. The interquartile range—5 to 15—encompasses the middle 50% of values, representing the most common range. Understanding where your measurement falls within this distribution provides meaningful context for health assessment.

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 Deviation8

Distribution TypeRight-skewed

PopulationAdult, Male

Demographic Variations in ESR

Age significantly influences this metric through biological processes that vary across the lifespan. 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 ESR

this metric emerges from the interplay of nature and nurture across the lifespan. Genetic factors establish physiological frameworks, while lifestyle choices, environmental conditions, and health status shape specific values. Age-related changes add another layer of influence. Recognizing this complexity helps interpret measurements accurately and identify realistic opportunities for health optimization.

Health Implications of ESR

this metric values contribute to overall health risk assessment when interpreted alongside other factors. Extreme values—particularly those below the 5th or above the 95th percentile—may indicate increased health risks depending on the specific metric and clinical context. However, being at an extreme doesn't automatically mean poor health; some individuals naturally fall at distribution tails. Risk assessment considers: absolute values, trends over time, family history, lifestyle factors, and co-existing health conditions. Within Blood Count, this metric contributes specific risk information that clinicians integrate with broader health assessment. Understanding your this metric as one piece of a larger health puzzle supports informed decision-making.

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:Adult Male (All)

Evidence Level:Level 1 (NHANES 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 Adult, Male, All population, the median value is 10. Values between the 5th and 95th percentiles (2 to 25) 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 (10), half the population is above and half below. Between the 25th (5) and 75th (15) 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 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.

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.

Content Information