AST (Adult, Male) - Health metric data from CDC NHANES 2017-2020
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Population health research has established robust benchmarks for this metric across diverse demographic groups. This analysis focuses specifically on Male aged Adult, with data representing All populations. The interquartile range of 17.9 to 34.1 represents the central 50% of values where most healthy individuals fall. Understanding these benchmarks enables more accurate health monitoring and supports evidence-based decision-making.
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.
Standardized measurement protocols ensure this metric data remains comparable across studies and populations. The CDC's NHANES program employs rigorously validated procedures developed over decades of population health research. Trained technicians use calibrated equipment following detailed protocols that specify positioning, timing, and environmental conditions. Multiple quality control measures—including regular equipment calibration, inter-rater reliability checks, and data validation—ensure measurement accuracy. Accurate this metric measurement requires attention to standardized conditions: appropriate equipment calibration, consistent measurement technique, proper subject preparation, and trained personnel. These factors minimize variability and ensure reliable results.
The chart below shows how AST (Adult, Male) is distributed across the population. The percentile values help you understand where you fall relative to others in your demographic group.
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From a clinical perspective, this metric percentiles guide interpretation and decision-making. The 5th percentile (6.3) 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 (45.7) represents the upper threshold, with only 5% exceeding this value. Clinicians use these benchmarks alongside other factors to assess individual health status.
6.26
5% of the population falls below this value. This represents the lower range of typical variation.
17.9
25% of the population falls below this value. This represents the lower-middle range.
26
This is the middle value. 50% of the population falls below and 50% falls above this value.
34.1
75% of the population falls below this value. This represents the upper-middle range.
45.74
95% of the population falls below this value. This represents the upper range of typical variation.
26
The arithmetic average of all values. This may differ from the median if the distribution is skewed.
Age significantly influences this metric through biological processes that vary across the lifespan. For Male All individuals, age-specific benchmarks account for these developmental patterns. Age-appropriate reference data ensures accurate interpretation regardless of life stage.
Multiple determinants shape this metric at individual and population levels. Inherited factors, developmental conditions, lifestyle choices, and current health status all contribute to observed values. Environmental and socioeconomic factors further influence patterns. Understanding these diverse influences supports nuanced interpretation of this metric measurements and realistic health goal setting.
this metric values contribute to overall health risk assessment when interpreted alongside other factors. Extreme values—particularly those below the 5th or above the 95th percentile—may indicate increased health risks depending on the specific metric and clinical context. However, being at an extreme doesn't automatically mean poor health; some individuals naturally fall at distribution tails. Risk assessment considers: absolute values, trends over time, family history, lifestyle factors, and co-existing health conditions. Within Hepatic, this metric contributes specific risk information that clinicians integrate with broader health assessment. Understanding your this metric as one piece of a larger health puzzle supports informed decision-making.
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 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.
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.
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)
Normal this metric encompasses a range of values that varies by demographic group. For individuals aged Adult, Male, All population, the median value is 26. Values between the 5th and 95th percentiles (6.3 to 45.7) represent normal variation. Using demographic-matched benchmarks ensures appropriate comparison.
Percentiles show where your this metric falls relative to others in your demographic group. At the 50th percentile (26), half the population is above and half below. Between the 25th (17.9) and 75th (34.1) 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.
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.
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.
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.
