BNP - Health metric data from American Heart Association
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How does your this metric compare to others in your demographic group? For All population of All in the Adult age range, understanding normal variation is crucial for meaningful health assessment. Values typically range from 3.5 to 84.3, 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 Cardiovascular metrics like this metric serve as windows into the complex workings of the heart and blood vessels. Expressed in appropriate units, this measurement helps clinicians assess cardiovascular health, track treatment effectiveness, and predict potential complications. Understanding your cardiovascular benchmarks empowers proactive health management.
Quality assurance in this metric measurement involves multiple layers of verification and standardization. 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 BNP 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.
The range of this metric values in the population spans considerable variation, all within normal bounds. From 3.5 to 84.3, the 5th-to-95th percentile range of 80.8 represents typical population variation. The narrower interquartile range of 40.5 (from 14.8 to 55.3) captures where most values concentrate. This natural variation reflects the diversity in healthy populations.
3.5
5% of the population falls below this value. This represents the lower range of typical variation.
14.75
25% of the population falls below this value. This represents the lower-middle range.
35
This is the middle value. 50% of the population falls below and 50% falls above this value.
55.25
75% of the population falls below this value. This represents the upper-middle range.
84.35
95% of the population falls below this value. This represents the upper range of typical variation.
35
The arithmetic average of all values. This may differ from the median if the distribution is skewed.
Demographic factors shape this metric values in meaningful ways that must be considered for accurate interpretation. Ethnicity influences this metric through genetic, environmental, and cultural factors unique to All populations. Research consistently shows demographic-specific patterns that make matched reference data essential. Age-related changes in the Adult group reflect developmental, hormonal, and lifestyle factors characteristic of this life stage. Biological sex differences affect this metric through hormonal influences, body composition variations, and physiological distinctions between All individuals and others. Using demographic-matched benchmarks ensures your comparison reflects meaningful variation rather than expected population differences.
Cardiovascular function, as reflected in this metric, responds to a constellation of lifestyle, genetic, and health factors. Regular exercise strengthens cardiovascular efficiency, while dietary choices affect blood vessel health and metabolic function. Stress management and adequate sleep support optimal cardiovascular function. Genetic inheritance shapes underlying physiology, while health conditions and medications may modify values. Recognizing these diverse influences enables comprehensive approaches to cardiovascular wellness.
Tracking this metric over time provides more valuable health information than single measurements. While individual values inform current status, trends reveal important patterns: stable values suggest consistent health status, while changing values may indicate developing conditions or successful interventions. Establishing your personal baseline—through repeated measurements under similar conditions—enables meaningful comparison over time. Regular monitoring, whether through clinical visits or personal tracking, supports early detection of meaningful changes and evaluation of health interventions.
Healthcare providers interpret this metric within comprehensive clinical assessment. but clinical interpretation weighs individual values against patient history, symptoms, other measurements, and treatment goals. Within Cardiovascular assessment, this metric contributes specific diagnostic and monitoring value. Clinicians use this metric data for screening, diagnosis, treatment monitoring, and outcome assessment—always interpreted within individual clinical context.
Research on this metric has established robust population benchmarks that inform clinical practice and public health policy. Population research on this metric combines rigorous measurement protocols with representative sampling to establish reliable benchmarks. These data support clinical practice, public health surveillance, and ongoing research.
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.
日本のデータは厚生労働省が毎年実施する「国民健康・栄養調査」に基づいています。2019年調査では約5,000世帯が参加しました。
日本の国民皆保険制度は全国民をカバーし、定期健康診断と予防医療を重視しています。
公式データ 厚生労働省 ↗
注：主要データはCDC NHANES（米国）からのものです。地域統計は公式の国民健康調査に基づいています。 (2024-01)
Normal this metric encompasses a range of values that varies by demographic group. For individuals aged Adult, All, All population, the median value is 35. Values between the 5th and 95th percentiles (3.5 to 84.3) 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 (35), half the population is above and half below. Between the 25th (14.8) and 75th (55.3) 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.
