BODY BENCHMARKS

Name: Body Benchmarks Human Metrics Database
Creator: Body Benchmarks

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Calcium, Adult, All, All

Calcium - 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 Calcium, 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 9.5 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 Calcium?

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 Calcium 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 Calcium 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 8.8 to 10.2, the 5th-to-95th percentile range of 1.3 represents typical population variation. The narrower interquartile range of 0.5 (from 9.2 to 9.8) captures where most values concentrate. This natural variation reflects the diversity in healthy populations.

Percentile Values Breakdown

5th Percentile (P5)

8.84

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

25th Percentile (P25)

9.23

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

50th Percentile (Median)

9.5

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

75th Percentile (P75)

9.77

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

95th Percentile (P95)

10.16

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

Mean (Average)

9.5

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, All

Demographic Variations in Calcium

Demographic factors shape this metric values in meaningful ways that must be considered for accurate interpretation. Ethnicity influences this metric through genetic, environmental, and cultural factors unique to All populations. Research consistently shows demographic-specific patterns that make matched reference data essential. Age-related changes in the Adult group reflect developmental, hormonal, and lifestyle factors characteristic of this life stage. Biological sex differences affect this metric through hormonal influences, body composition variations, and physiological distinctions between All individuals and others. Using demographic-matched benchmarks ensures your comparison reflects meaningful variation rather than expected population differences.

Factors Affecting Calcium

What determines your this metric? Multiple factors contribute, from inherited genetic traits to daily lifestyle choices. Environmental influences, health conditions, and life stage all play roles in shaping individual values. Recognizing this multifactorial nature supports realistic interpretation and informed health decisions. Some influences offer opportunities for modification while others must simply be understood and accepted.

Health Implications of Calcium

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

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

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.

🇩🇪 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 All (All)

Evidence Level:Level 1 (nationally representative survey)

View Original Source →

Frequently Asked Questions

What's considered a healthy this metric?

Normal this metric encompasses a range of values that varies by demographic group. For individuals aged Adult, All, All population, the median value is 9.5. Values between the 5th and 95th percentiles (8.8 to 10.2) represent normal variation. Using demographic-matched benchmarks ensures appropriate comparison.

What does my this metric percentile mean?

Percentiles show where your this metric falls relative to others in your demographic group. At the 50th percentile (9.5), half the population is above and half below. Between the 25th (9.2) and 75th (9.8) 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.

Can my this metric change over time?

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 indicate potential problems?

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.

What explains ethnic variation in 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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