BODY BENCHMARKS

Name: Body Benchmarks Human Metrics Database
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ALP (Adult, Male), Adult, Male, All

ALP (Adult, Male) - 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 ALP (Adult, Male), 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 70 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 ALP (Adult, Male)?

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 ALP (Adult, Male) 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 ALP (Adult, Male) 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 (70), you're exactly at the population median—neither high nor low relative to others. Values between 56.5 and 83.5 (25th to 75th percentile) are considered typical, representing the central half of the distribution. The extremes—below 37.1 or above 102.9—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)

37.1

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

25th Percentile (P25)

56.5

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)

83.5

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

95th Percentile (P95)

102.9

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 Deviation20

Distribution TypeNormal

PopulationAdult, Male

Demographic Variations in ALP (Adult, Male)

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 ALP (Adult, Male)

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 ALP (Adult, Male)

Tracking this metric over time provides more valuable health information than single measurements. While individual values inform current status, trends reveal important patterns: stable values suggest consistent health status, while changing values may indicate developing conditions or successful interventions. Establishing your personal baseline—through repeated measurements under similar conditions—enables meaningful comparison over time. Regular monitoring, whether through clinical visits or personal tracking, supports early detection of meaningful changes and evaluation of health interventions.

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 hepatic 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. 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.

🇪🇸 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:CDC NHANES 2017-2020

Year:2020-2024

Population:Adult Male (All)

Evidence Level:Level 1 (nationally representative survey)

View Original Source →

Frequently Asked Questions

How do I know if my this metric is normal?

Normal this metric encompasses a range of values that varies by demographic group. For individuals aged Adult, Male, All population, the median value is 70. Values between the 5th and 95th percentiles (37.1 to 102.9) represent normal variation. Using demographic-matched benchmarks ensures appropriate comparison.

How should I interpret my this metric percentile?

Percentiles show where your this metric falls relative to others in your demographic group. At the 50th percentile (70), half the population is above and half below. Between the 25th (56.5) and 75th (83.5) 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.

How might my this metric change as I age?

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.

When is this metric a health concern?

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.

Are this metric values different for All populations?

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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