ALT (Adult, Male) - Health metric data from CDC NHANES 2017-2020
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How does your this metric compare to others in your demographic group? For All population of Male in the Adult age range, understanding normal variation is crucial for meaningful health assessment. Values typically range from 5.3 to 54.7, encompassing 90% of the population. This guide provides the data-driven insights you need to interpret your measurements accurately and make informed decisions about your health.
A measurement of this metric Healthcare providers and researchers utilize this metric (in appropriate units) as part of thorough health evaluation. This metric contributes to understanding overall health status and identifying potential areas of concern.
Measurement context significantly influences this metric values, making standardization essential. NHANES protocols carefully control measurement conditions to minimize contextual variability. Survey centers maintain consistent environments, and measurement timing follows prescribed schedules. These controls enable meaningful comparison of values across the entire survey population. 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.
The chart below shows how ALT (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 (5.3) 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 (54.7) represents the upper threshold, with only 5% exceeding this value. Clinicians use these benchmarks alongside other factors to assess individual health status.
5.32
5% of the population falls below this value. This represents the lower range of typical variation.
19.88
25% of the population falls below this value. This represents the lower-middle range.
30
This is the middle value. 50% of the population falls below and 50% falls above this value.
40.13
75% of the population falls below this value. This represents the upper-middle range.
54.68
95% of the population falls below this value. This represents the upper range of typical variation.
30
The arithmetic average of all values. This may differ from the median if the distribution is skewed.
Population-specific patterns in this metric reflect the complex interplay of genetics, environment, and health behaviors. All populations exhibit characteristic this metric distributions that differ from other groups due to genetic predisposition, dietary patterns, physical activity norms, and environmental factors. These differences are well-documented in health research and inform demographic-specific reference ranges. Within All Male aged Adult, these patterns become more specific, reflecting the intersection of multiple demographic factors. Acknowledging these differences doesn't imply better or worse—just different normal ranges that enable more accurate assessment.
this metric emerges from the interplay of nature and nurture across the lifespan. Genetic factors establish physiological frameworks, while lifestyle choices, environmental conditions, and health status shape specific values. Age-related changes add another layer of influence. Recognizing this complexity helps interpret measurements accurately and identify realistic opportunities for health optimization.
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.
Os dados antropométricos brasileiros vêm da Pesquisa de Orçamentos Familiares (POF) 2008-2009 do IBGE, com medições diretas de mais de 180.000 pessoas.
O Sistema Único de Saúde (SUS) oferece cobertura universal gratuita com programas de atenção básica e monitoramento de saúde populacional.
Dados oficiais de IBGE / Ministério da Saúde ↗
Nota: Os dados principais são do CDC NHANES (EUA). As estatísticas locais são de pesquisas nacionais oficiais. (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 30. Values between the 5th and 95th percentiles (5.3 to 54.7) 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 (30), half the population is above and half below. Between the 25th (19.9) and 75th (40.1) 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.
