Korelasi Pemeriksaan Antropometri Dasar dengan Tekanan Darah, Gangguan Metabolik, dan Fungsi Ginjal

Olivia Charissa; Alexander Halim Santoso; Bryan Anna Wijaya

doi:10.55606/jurrike.v5i1.7976

Authors

Olivia Charissa Universitas Tarumangara Jakarta
Alexander Halim Santoso Universitas Tarumangara Jakarta
Bryan Anna Wijaya Universitas Tarumangara Jakarta

DOI:

https://doi.org/10.55606/jurrike.v5i1.7976

Keywords:

Anthropometry, Blood Pressure, Dyslipidemia, Metabolic, Renal Function

Abstract

The increasing prevalence of metabolic syndrome and chronic kidney disease underscores the need for simple, low-cost, and community-applicable screening indicators. This study aimed to evaluate the association between basic anthropometric parameters and blood pressure, metabolic indicators, and renal function among adults in the Badui Luar community. A cross-sectional design was employed involving 41 participants who underwent anthropometric assessment, biochemical measurements, and blood pressure evaluation. Pearson correlation analysis was used to examine linear associations between variables. The results demonstrated that neck circumference exhibited significant correlations with dyslipidemia components, including LDL (r = 0.377), TC/HDL ratio (r = 0.516), and HDL (r = –0.433), indicating cervical adiposity as a strong marker of atherogenic risk. Calf circumference showed protective correlations with fasting glucose (r = –0.352) and eGFR (r = 0.322), suggesting the metabolic relevance of peripheral muscle mass in glycemic regulation and renal status. Body mass index showed a weak correlation with systolic blood pressure (r = 0.149), whereas waist and hip circumferences exhibited mild, clinically insignificant correlations with triglycerides and total cholesterol. Overall, these findings highlight that simple anthropometric measures—particularly neck and calf circumference—may serve as early indicators of cardiometabolic and renal risk in community-based screening. Further longitudinal studies with larger and more heterogeneous populations are required to validate these associations and determine the predictive power of anthropometric indicators.

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