Fasting Insulin (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 1.3 to 17.7, 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 This health metric, measured in appropriate units, provides valuable information for health assessment and monitoring. Understanding what this metric represents and how it varies across populations helps individuals and healthcare providers make informed decisions.
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 Fasting Insulin (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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This metric does not have enough statistical parameters for generating a visualization.
Comparing your this metric to population percentiles reveals where you stand relative to others in your demographic group. A value at the 25th percentile (6.1) means approximately one-quarter of the population has lower values than yours. At the 75th percentile (12.9), three-quarters of the population falls below your value. These comparisons provide context for understanding your individual measurement.
1.28
5% of the population falls below this value. This represents the lower range of typical variation.
6.13
25% of the population falls below this value. This represents the lower-middle range.
9.5
This is the middle value. 50% of the population falls below and 50% falls above this value.
12.88
75% of the population falls below this value. This represents the upper-middle range.
17.73
95% of the population falls below this value. This represents the upper range of typical variation.
9.5
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 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.
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.
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 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.
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.
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)
Normal this metric encompasses a range of values that varies by demographic group. For individuals aged Adult, Male, All population, the median value is 9.5. Values between the 5th and 95th percentiles (1.3 to 17.7) 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 (9.5), half the population is above and half below. Between the 25th (6.1) and 75th (12.9) 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.
