Weight - 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 18-29, with data representing All populations. The interquartile range of 69.1 to 96.1 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 Anthropometric measurements like this metric quantify physical body characteristics that reflect growth, development, and nutritional status. Measured in standard units, this metric serves as a foundational health indicator used across clinical, research, and public health contexts. These measurements have centuries of history in medical practice and remain essential today for assessing physical health status.
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.
The chart below shows how Weight 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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This metric does not have enough statistical parameters for generating a visualization.
Interpreting your this metric measurement requires understanding what percentiles mean in practical terms. If your value matches the 50th percentile (82.6), you're exactly at the population median—neither high nor low relative to others. Values between 69.1 and 96.1 (25th to 75th percentile) are considered typical, representing the central half of the distribution. The extremes—below 49.7 or above 115.5—represent the outer 10% where values are less common but not necessarily abnormal. Percentile position helps contextualize your measurement within the broader population.
49.7
5% of the population falls below this value. This represents the lower range of typical variation.
69.1
25% of the population falls below this value. This represents the lower-middle range.
82.6
This is the middle value. 50% of the population falls below and 50% falls above this value.
96.1
75% of the population falls below this value. This represents the upper-middle range.
115.5
95% of the population falls below this value. This represents the upper range of typical variation.
82.6
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 18-29, 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.
The factors influencing this metric range from fixed genetic determinants to modifiable lifestyle choices. Hereditary factors establish physiological parameters that define potential ranges. Growth and development conditions during childhood and adolescence shape adult values. Ongoing lifestyle factors—diet quality, exercise frequency, sleep adequacy, stress management—affect current measurements. Health conditions and medications may also influence this metric. Understanding this complexity helps interpret measurements and identify opportunities for positive change.
this metric represents one component within the complex picture of overall health. No single metric defines health status; this metric values gain meaning when interpreted alongside other measurements, symptoms, lifestyle factors, and health history. A value that appears concerning in isolation may be less significant when viewed within broader context—and vice versa. Within Anthropometry assessment, this metric contributes specific information that clinicians synthesize with related indicators. Healthcare providers integrate this metric with other data to form comprehensive assessments and recommendations. Maintaining perspective on this metric as part of a larger health picture supports balanced interpretation and appropriate response to individual values.
From clinical perspective, this metric provides actionable health information when properly contextualized. In anthropometry 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 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.
Les données françaises proviennent de l'étude ESTEBAN (Étude de SanTé sur l'Environnement, la Biosurveillance, l'Activité physique et la Nutrition), menée par Santé Publique France.
L'étude ESTEBAN, menée entre 2014 et 2016, a mesuré plus de 4 000 adultes selon des protocoles standardisés comparables aux normes internationales.
Le système de santé français offre une couverture universelle avec un accent sur la médecine préventive et le suivi régulier des indicateurs de santé.
Données officielles de Santé Publique France ↗
Note : Les données principales proviennent de CDC NHANES (USA). Les statistiques locales sont issues d'enquêtes nationales officielles. (2024-01)
Normal this metric encompasses a range of values that varies by demographic group. For individuals aged 18-29, Male, All population, the median value is 82.6. Values between the 5th and 95th percentiles (49.7 to 115.5) 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 (82.6), half the population is above and half below. Between the 25th (69.1) and 75th (96.1) 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 18-29 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.
