BODY BENCHMARKS

Name: Body Benchmarks Human Metrics Database
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RBC Count, Adult, Male, All

RBC Count - 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 RBC Count, 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 5 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 RBC Count?

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 RBC Count 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 RBC Count 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 range of this metric values in the population spans considerable variation, all within normal bounds. From 4.3 to 5.7, the 5th-to-95th percentile range of 1.3 represents typical population variation. The narrower interquartile range of 0.5 (from 4.7 to 5.3) captures where most values concentrate. This natural variation reflects the diversity in healthy populations.

Percentile Values Breakdown

5th Percentile (P5)

4.34

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

25th Percentile (P25)

4.73

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)

5.27

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

95th Percentile (P95)

5.66

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 Deviation0.4

Distribution TypeNormal

PopulationAdult, Male

Demographic Variations in RBC Count

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 RBC Count

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 RBC Count

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.

🇮🇹 Dati Sanitari Regionali: Italia

✓Dati verificati da fonti ufficiali

I dati italiani provengono dall'indagine multiscopo ISTAT "Aspetti della vita quotidiana" che raccoglie informazioni sulla salute di circa 20.000 famiglie ogni anno.

Il Servizio Sanitario Nazionale (SSN) italiano garantisce copertura universale con servizi di prevenzione e monitoraggio della salute.

Dati ufficiali da ISTAT / Ministero della Salute ↗

Nota: I dati principali provengono da CDC NHANES (USA). Le statistiche locali sono da indagini sanitarie nazionali ufficiali. (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

What is a normal this metric value?

Normal this metric encompasses a range of values that varies by demographic group. For individuals aged Adult, Male, All population, the median value is 5. Values between the 5th and 95th percentiles (4.3 to 5.7) represent normal variation. Using demographic-matched benchmarks ensures appropriate comparison.

What's the significance of this metric percentiles?

Percentiles show where your this metric falls relative to others in your demographic group. At the 50th percentile (5), half the population is above and half below. Between the 25th (4.7) and 75th (5.3) 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.

Will my this metric stay the same throughout life?

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.

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.

How does ethnicity affect 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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