BODY BENCHMARKS

Name: Body Benchmarks Human Metrics Database
Creator: Body Benchmarks

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MMA, Adult, All, All

MMA - Health metric data from Clinical Laboratory Standards

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 MMA, 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 180 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 MMA?

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 MMA Measured?

Measurement context significantly influences this metric values, making standardization essential. 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 MMA 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 (180), you're exactly at the population median—neither high nor low relative to others. Values between 126 and 234 (25th to 75th percentile) are considered typical, representing the central half of the distribution. The extremes—below 48.4 or above 311.6—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)

48.4

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

25th Percentile (P25)

126

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

50th Percentile (Median)

180

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

75th Percentile (P75)

234

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

95th Percentile (P95)

311.6

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

Mean (Average)

180

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

Statistical Summary

Standard Deviation80

Distribution TypeNormal

PopulationAdult, All

Demographic Variations in MMA

Biological sex creates distinct patterns in this metric through hormonal, anatomical, and physiological differences. All 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 MMA

this metric values reflect the combined influence of genetic factors, lifestyle choices, environmental conditions, and health status. While some determinants remain fixed, others respond to deliberate intervention. Understanding which factors influence this metric helps contextualize individual measurements and identify opportunities for positive change. Age-related changes, health conditions, and medications may also affect values over time.

Health Implications of MMA

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

From clinical perspective, this metric provides actionable health information when properly contextualized. In metabolic assessment, this metric helps clinicians evaluate current status, track changes, and guide interventions. but individual assessment considers the complete clinical picture. Discussion with healthcare providers enables personalized interpretation relevant to your specific health situation.

Research Insights

Scientific understanding of this metric continues to evolve through ongoing research. Current research explores how this metric relates to health outcomes, what factors influence it, and how benchmarks should be updated as populations change. This evolving science ensures that reference values remain relevant and useful.

Practical Applications

this metric data serves practical purposes across multiple contexts. For individuals: understanding your values relative to benchmarks, tracking changes over time, and informing health discussions with providers. For healthcare: screening, diagnosis, treatment monitoring, and outcome assessment. For researchers: studying population health trends, evaluating interventions, and identifying health disparities. For public health: surveillance, policy development, and health promotion. This multi-level utility makes this metric benchmarks valuable across the health ecosystem.

🇫🇷 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:Clinical Laboratory Standards

Year:2020-2024

Population:Adult All (All)

Evidence Level:Level 2 (clinical studies)

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 180. Values between the 5th and 95th percentiles (48.4 to 311.6) 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 (180), half the population is above and half below. Between the 25th (126) and 75th (234) 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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