BODY BENCHMARKS

Name: Body Benchmarks Human Metrics Database
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HbA1c, 18-29, Male, All

HbA1c - 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 HbA1c, 18-29, Male, All

Evidence-based health assessment relies on accurate population benchmarks. this metric measurements for Male aged 18-29 (All population) provide essential reference points backed by rigorous scientific methodology. With a median value of 5.3, the distribution reveals meaningful patterns about population health. This comprehensive analysis examines measurement protocols, statistical distributions, clinical significance, and practical implications for health monitoring.

What is HbA1c?

A measurement of this metric As a quantifiable health indicator measured in appropriate units, this metric enables systematic health assessment. Understanding normal ranges and what influences this metric empowers better health management.

How is HbA1c Measured?

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.

Distribution & Percentiles

The chart below shows how HbA1c 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 (4) 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 (6.6) 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)

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

25th Percentile (P25)

4.8

25% of the population falls below this value. This represents the lower-middle range.

50th Percentile (Median)

5.3

This is the middle value. 50% of the population falls below and 50% falls above this value.

75th Percentile (P75)

5.8

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

95th Percentile (P95)

6.6

95% of the population falls below this value. This represents the upper range of typical variation.

Mean (Average)

5.3

The arithmetic average of all values. This may differ from the median if the distribution is skewed.

Statistical Summary

Standard Deviation0.8

Distribution TypeNormal

Population18-29, Male

Demographic Variations in HbA1c

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.

Factors Affecting HbA1c

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.

Health Implications of HbA1c

What can your this metric measurement tell you about potential health actions? Values within normal ranges generally require continued monitoring rather than intervention. Values at extremes may suggest opportunities for lifestyle modification or the need for further evaluation. Key questions to consider: Has your this metric changed significantly over time? Do you have symptoms related to this metric? Do other health indicators suggest concern? Are lifestyle modifications possible? Many factors influencing this metric respond to lifestyle modifications, making proactive health management potentially impactful.

Clinical Significance

From clinical perspective, this metric provides actionable health information when properly contextualized. In metabolic 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 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

this metric data serves practical purposes across multiple contexts. For individuals: understanding your values relative to benchmarks, tracking changes over time, and informing health discussions with providers. For healthcare: screening, diagnosis, treatment monitoring, and outcome assessment. For researchers: studying population health trends, evaluating interventions, and identifying health disparities. For public health: surveillance, policy development, and health promotion. This multi-level utility makes this metric benchmarks valuable across the health ecosystem.

🇷🇺 Региональные данные о здоровье: Россия

✓Проверенные данные из официальных источников

Данные о здоровье населения России собираются Росстатом в рамках выборочных наблюдений состояния здоровья населения.

Система здравоохранения России обеспечивает бесплатную медицинскую помощь через систему обязательного медицинского страхования (ОМС) и включает регулярную диспансеризацию.

Официальные данные Росстат / Минздрав ↗

Примечание: Основные данные из CDC NHANES (США). Местная статистика из официальных национальных обследований здоровья. (2024-01)

📊Data Transparency & Sources

Sources & References

Source Citation

Source:CDC NHANES 2017-2020

Year:2017-2020

Population:18-29 Male (All)

Evidence Level:Level 1 (nationally representative survey)

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 18-29, Male, All population, the median value is 5.3. Values between the 5th and 95th percentiles (4 to 6.6) 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 (5.3), half the population is above and half below. Between the 25th (4.8) and 75th (5.8) 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 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.

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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