This study aims to investigate the significance of measuring fasting insulin and the
homeostatic model assessment of insulin resistance (HOMA-IR) in identifying metabolic
health across various demographic and clinical factors. Specifically, the study will
examine the influence of age, sex, race/ethnicity, BMI, and polycystic ovary syndrome
(PCOS) diagnosis on insulin levels and insulin resistance as essential indicators of
metabolic dysfunction.
Metabolic health disorders, such as insulin resistance and impaired glucose metabolism,
are known to be associated with an increased risk of developing conditions like type 2
diabetes, cardiovascular diseases, and metabolic syndrome. Traditionally, glucose levels
have been used to assess metabolic health; however, fasting insulin and HOMA-IR provide
valuable insights into the underlying insulin dysregulation that precedes the onset of
these conditions.
Disparities in insulin levels have been observed across different racial and ethnic
groups. These variations may arise from genetic predispositions, differences in
lifestyle, or a combination of both, thus highlighting the need to explore these factors
comprehensively. BMI, a measure of body composition, has been strongly associated with
elevated insulin levels and insulin resistance. Individuals with obesity often exhibit
dysregulated insulin metabolism, leading to higher fasting insulin and HOMA-IR values.
Furthermore, PCOS, a common endocrine disorder affecting reproductive-age women, is
frequently associated with insulin resistance. Studying the insulin profiles among women
with PCOS will shed light on the potential metabolic implications and help tailor
interventions for this at-risk population.
The study will employ a cross-sectional design, enrolling a large sample of participants
from diverse backgrounds. Fasting insulin levels will be measured using standardized
laboratory methods, and HOMA-IR scores will be calculated based on fasting insulin and
glucose values. Statistical analyses, including regression models and subgroup
comparisons, will be conducted to assess the associations between fasting insulin,
HOMA-IR, and the demographic and clinical factors of interest.
This research aims to emphasize the importance of incorporating fasting insulin and
HOMA-IR measurements alongside glucose assessments to enhance the identification and
understanding of metabolic health disorders. The findings are expected to contribute to a
more comprehensive approach in diagnosing, managing, and preventing metabolic diseases,
ultimately leading to improved patient outcomes and public health interventions.
