BODY BENCHMARKS

Name: Body Benchmarks Human Metrics Database
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MCV, Adult, All, All

MCV - 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 MCV, Adult, All, All

Clinical interpretation of this metric requires nuanced understanding of population distributions and demographic variation. This reference guide addresses All in the Adult age bracket, specifically within All populations, providing healthcare-relevant benchmarks. With a central tendency of 90 and well-characterized percentile distributions, these data support informed clinical decision-making. From measurement methodology to health implications, this analysis covers the essential aspects that practitioners and patients alike need to understand.

What is MCV?

A measurement of this metric Healthcare providers and researchers utilize this metric (in appropriate units) as part of thorough health evaluation. This metric contributes to understanding overall health status and identifying potential areas of concern.

How is MCV 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 MCV 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 81.8 (5th percentile) and 98.2 (95th percentile), defining the typical range for healthy individuals. At the center, the median value of 90 indicates that half the population falls above and half below this point. The interquartile range—86.6 to 93.4—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)

81.78

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

25th Percentile (P25)

86.63

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)

93.38

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

95th Percentile (P95)

98.23

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 Deviation5

Distribution TypeNormal

PopulationAdult, All

Demographic Variations in MCV

The intersection of demographic factors creates unique patterns in this metric that require matched reference data for accurate assessment. For All All individuals aged Adult, the combination of ethnicity, age, and sex produces a specific profile that differs from other demographic combinations. Using precisely matched reference data provides the most relevant comparison for your individual measurement. This demographic specificity enhances the clinical utility and personal relevance of benchmark comparisons.

Factors Affecting MCV

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 MCV

this metric represents one component within the complex picture of overall health. No single metric defines health status; this metric values gain meaning when interpreted alongside other measurements, symptoms, lifestyle factors, and health history. A value that appears concerning in isolation may be less significant when viewed within broader context—and vice versa. Within Blood Count assessment, this metric contributes specific information that clinicians synthesize with related indicators. Healthcare providers integrate this metric with other data to form comprehensive assessments and recommendations. Maintaining perspective on this metric as part of a larger health picture supports balanced interpretation and appropriate response to individual values.

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.

🇧🇷 Dados de Saúde Regionais: Brasil

✓Dados verificados de fontes oficiais

Os dados antropométricos brasileiros vêm da Pesquisa de Orçamentos Familiares (POF) 2008-2009 do IBGE, com medições diretas de mais de 180.000 pessoas.

O Sistema Único de Saúde (SUS) oferece cobertura universal gratuita com programas de atenção básica e monitoramento de saúde populacional.

Dados oficiais de IBGE / Ministério da Saúde ↗

Nota: Os dados principais são do CDC NHANES (EUA). As estatísticas locais são de pesquisas nacionais oficiais. (2024-01)

📊Data Transparency & Sources

Sources & References

Source Citation

Source:CDC NHANES 2017-2020

Year:2020-2024

Population:Adult All (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 Adult, All, All population, the median value is 90. Values between the 5th and 95th percentiles (81.8 to 98.2) 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 (90), half the population is above and half below. Between the 25th (86.6) and 75th (93.4) 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.

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