Objective:
To investigate the association between habitual coffee consumption and metabolic and hormonal profiles in middle-aged adults.
Approach:
- Study Design: A cross-sectional study analyzing data from 2264 participants in the Northern Finland Birth Cohort 1966, all aged 46 years.
- Data Collection: Combined reported coffee consumption with clinical measurements, hormone testing, and nuclear magnetic resonance metabolomics.
- Metabolomics Analysis: Quantified 164 lipid and metabolite measures to assess associations with coffee consumption.
Key Findings:
- Higher coffee consumption was associated with lower concentrations of branched-chain amino acids (BCAAs), which are linked to insulin resistance.
- Men showed lower fasting insulin and measures of insulin resistance with greater coffee intake, along with higher insulin sensitivity.
- Hormonal testing indicated higher total and bioavailable testosterone and SHBG in men, but lower free testosterone and free androgen index.
- Among women, associations were limited but showed higher SHBG and lower free testosterone.
- Higher coffee intake correlated with lower total and visceral fat and greater skeletal muscle mass.
Interpretation:
The study indicates that habitual coffee intake may be associated with variations in metabolic and endocrine biomarker profiles, with differences observed between sexes.
Limitations:
- Coffee intake was self-reported.
- Biomarkers were measured at a single time point.
- The Finnish cohort may not represent other populations with different coffee-drinking patterns.
- The findings do not establish causation.
Conclusion:
Longitudinal and intervention studies are needed to determine if the observed metabolic and hormonal changes can inform individual diagnostic or risk-assessment decisions.
Sources:
This content is an AI-generated, fully rewritten summary based on a published scholarly article. It does not reproduce the original text and is not a substitute for the original publication. Readers are encouraged to consult the source for full context, data, and methodology.
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