Relationship Between Fasting Blood Glucose Levels and Lipid Profiles in Type 2 Diabetes Mellitus Patients with Hypertension

Background: Diabetes Mellitus (DM) is a global health emergency that experiences an increasing trend every year. Diabetes mellitus can cause complications if not treated properly. One of the complications that arises is hypertension. Type 2 DM patients with hypertension may have a higher risk of complications than type 2 DM patients without hypertension. Aim: To prove the relationship between Fasting Blood Glucose (FBG) levels and lipid profile levels in type 2 DM patients with hypertension. Methods: This research is an analytical observational study using a cross-sectional approach. This study used secondary data from type 2 DM patients with hypertension medical records at Diponegoro National Hospital, with as many as 38 respondents from 2021 to 2023. Results: Spearman Rank’s analysis showed that in type 2 DM patients with hypertension, the correlation between GDP levels and total cholesterol levels was p = 0.073 and r = 0.295, HDL cholesterol p = 0.232 and r = 0.199, LDL cholesterol p=0.048 and r=0.323, and triglyceride p=0.371 and r=0.149. Conclusion: There was a significant positive correlation between GDP levels and LDL cholesterol levels in type 2 DM patients with hypertension.

Authors

Institutions

Publication Details

Journal
Jurnal Kedokteran Diponegoro (Diponegoro Medical Journal)
Published
2024-08-31
DOI
https://doi.org/10.14710/dmj.v13i5.42645
Citations
1
Primary Topic
Liver Disease Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.39
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Relationship Between Fasting Blood Glucose Levels and Lipid Profiles in Type 2 Diabetes Mellitus Patients with Hypertension

Banundari Rachmawati, Aryu Candra, Edward Kurnia Setiawan Limijadi, Sarah Syifa Lestari
1 citations
Jurnal Kedokteran Diponegoro (Diponegoro Medical Journal)
Liver Disease Diagnosis and Treatment
0.39
article

Relationship Between Fasting Blood Glucose Levels and Lipid Profiles in Type 2 Diabetes Mellitus Patients with Hypertension

Banundari Rachmawati, Aryu Candra, Edward Kurnia Setiawan Limijadi, Sarah Syifa Lestari
article en
1 citations

Abstract

Background: Diabetes Mellitus (DM) is a global health emergency that experiences an increasing trend every year. Diabetes mellitus can cause complications if not treated properly. One of the complications that arises is hypertension. Type 2 DM patients with hypertension may have a higher risk of complications than type 2 DM patients without hypertension. Aim: To prove the relationship between Fasting Blood Glucose (FBG) levels and lipid profile levels in type 2 DM patients with hypertension. Methods: This research is an analytical observational study using a cross-sectional approach. This study used secondary data from type 2 DM patients with hypertension medical records at Diponegoro National Hospital, with as many as 38 respondents from 2021 to 2023. Results: Spearman Rank’s analysis showed that in type 2 DM patients with hypertension, the correlation between GDP levels and total cholesterol levels was p = 0.073 and r = 0.295, HDL cholesterol p = 0.232 and r = 0.199, LDL cholesterol p=0.048 and r=0.323, and triglyceride p=0.371 and r=0.149. Conclusion: There was a significant positive correlation between GDP levels and LDL cholesterol levels in type 2 DM patients with hypertension.

Jurnal Kedokteran Diponegoro (Diponegoro Medical Journal)Vol. 13(5)
Diponegoro University (ID)
Decent work and economic growth
Openalex Percentile: Top 35%
Liver Disease Diagnosis and Treatment
0.39
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.