BODY BENCHMARKS

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

LDL Cholesterol - 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.

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Reviewed by: Health Metrics Team

Comprehensive Guide to LDL Cholesterol, 18-29, Male, All

Whether you're tracking your health or interpreting clinical measurements, this metric benchmarks provide essential context. For 18-29 Male of All background, having demographic-specific reference data matters significantly for accurate interpretation. The population median of 95 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 LDL Cholesterol?

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.

How is LDL Cholesterol 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 LDL Cholesterol 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

The range of this metric values in the population spans considerable variation, all within normal bounds. From 37 to 153, the 5th-to-95th percentile range of 116 represents typical population variation. The narrower interquartile range of 48 (from 71 to 119) captures where most values concentrate. This natural variation reflects the diversity in healthy populations.

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)

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)

119

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

95th Percentile (P95)

153

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 Deviation35

Distribution TypeNormal

Population18-29, Male

Demographic Variations in LDL Cholesterol

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 18-29, 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 LDL Cholesterol

this metric values reflect the combined influence of genetic factors, lifestyle choices, environmental conditions, and health status. While some determinants remain fixed, others respond to deliberate intervention. Understanding which factors influence this metric helps contextualize individual measurements and identify opportunities for positive change. Age-related changes, health conditions, and medications may also affect values over time.

Health Implications of LDL Cholesterol

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 Blood Lipids 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.

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 blood lipids 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.

🇰🇷 지역 건강 데이터: 대한민국

✓공식 출처에서 확인된 데이터

한국 데이터는 질병관리청이 매년 실시하는 국민건강영양조사(KNHANES)에 기반합니다. 이 조사는 전국적으로 약 10,000명을 대상으로 직접 측정을 실시합니다.

한국의 국민건강보험제도는 전 국민을 대상으로 하며, 국가건강검진 프로그램을 통해 정기적인 건강 모니터링을 제공합니다.

공식 데이터 질병관리청 ↗

참고: 주요 데이터는 CDC NHANES(미국)에서 가져온 것입니다. 지역 통계는 공식 국가 건강 조사에서 가져온 것입니다. (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

What's considered a healthy this metric?

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 95. Values between the 5th and 95th percentiles (37 to 153) represent normal variation. Using demographic-matched benchmarks ensures appropriate comparison.

What does my this metric percentile mean?

Percentiles show where your this metric falls relative to others in your demographic group. At the 50th percentile (95), half the population is above and half below. Between the 25th (71) and 75th (119) 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.

Can my this metric change over time?

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 indicate potential problems?

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.

What explains ethnic variation in this metric?

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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