BODY BENCHMARKS

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

ApoB - Health metric data from ESC/EAS Dyslipidemia Guidelines 2019

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.

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Reviewed by: Health Metrics Team

Comprehensive Guide to ApoB, 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 ApoB?

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 ApoB 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 ApoB 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

From a clinical perspective, this metric percentiles guide interpretation and decision-making. The 5th percentile (48.9) marks the lower boundary where only 5% of the population falls below. Values in this range may warrant clinical attention depending on context. Similarly, the 95th percentile (131.1) represents the upper threshold, with only 5% exceeding this value. Clinicians use these benchmarks alongside other factors to assess individual health status.

Percentile Values Breakdown

5th Percentile (P5)

48.88

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

25th Percentile (P25)

73.13

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)

106.88

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

95th Percentile (P95)

131.13

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 Deviation25

Distribution TypeNormal

PopulationAdult, All

Demographic Variations in ApoB

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 ApoB

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 ApoB

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

Clinical utility of this metric extends beyond simple comparison to population norms. Healthcare providers consider: how values compare to demographic-matched benchmarks, whether significant changes have occurred, presence of associated symptoms, and relationship to other clinical findings. individual clinical significance depends on broader context. this metric contributes specific information to blood lipids evaluation. This nuanced approach enables meaningful clinical decision-making.

Research Insights

Research on this metric has established robust population benchmarks that inform clinical practice and public health policy. Population research on this metric combines rigorous measurement protocols with representative sampling to establish reliable benchmarks. These data support clinical practice, public health surveillance, and ongoing research.

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.

🇪🇸 Datos de Salud Regionales: España

✓Datos verificados de fuentes oficiales

Los datos españoles provienen de la Encuesta Nacional de Salud (ENSE) 2017, realizada por el Ministerio de Sanidad y el INE con más de 23.000 participantes.

El Sistema Nacional de Salud español ofrece cobertura universal gratuita con énfasis en atención primaria y medicina preventiva.

Datos oficiales de Ministerio de Sanidad ↗

Nota: Los datos principales son de CDC NHANES (EE.UU.). Las estadísticas locales son de encuestas nacionales oficiales. (2024-01)

📊Data Transparency & Sources

Sources & References

Source Citation

Source:ESC/EAS Dyslipidemia Guidelines 2019

Year:2019-2023

Population:Adult All (All)

Evidence Level:Level 1 (ESC/EAS Guidelines)

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 (48.9 to 131.1) 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 (73.1) and 75th (106.9) 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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