Spatial Analysis of Determinants of Hypertension Incidence in Kota Lama Subdistrict, Kupang, Indonesia

Background: Cardiovascular diseases such as hypertension, heart attack, and stroke are chronic non-communicable diseases influenced by genetic, physiological, environmental, and behavioral factors. Geographic Information Systems (GIS) can be utilized for spatial analysis to identify risk factors, distribution patterns, and determinants of diseases, including hypertension. This study aims to examine the determinants of hypertension using a spatial analysis approach in Kota Lama Subdistrict, Kupang City.Subjects and Method: This study employed an ecological study design using an observational analytic method with a cross-sectional approach. The population consisted of residents aged ≥18 years in Kota Lama Subdistrict. A total of 400 individuals diagnosed with hypertension were selected using simple random sampling. The variables examined were age, overweight, lack of physical activity, high-salt diet, alcohol consumption, medication adherence, economic level, and distance to health facilities. Instruments used included a sphygmomanometer, microtoise, weight scale, and questionnaire. Spatial analysis was conducted using the GeoDa application with Regression, Bivariate Local Moran’s Index, Multivariate Local Geary, and Spatial Empirical Bayes tests.Results: The results showed significant associations and clustered spatial autocorrelation with low-to-high relative risk (RR) observed in the subdistricts of LLBK, Bonipoi, Solor, Fatubesi, Oeba, Nefonaek, and Pasir Panjang for the variables: age (p=0.001, I=0.70), overweight (p<0.001, I=0.64), lack of physical activity (p=0.00, I=0.63), high-salt diet (p=0.00, I=0.63), and alcohol consumption (p<0.001, I=0.69). There were no significant associations for variables such as irregular medication intake, economic level, and distance to health facilities, with p-values of 1.000 > α (0.050).Conclusion: Age, overweight, physical inactivity, high-salt diet, and alcohol consumption are significant determinants and show positive clustered spatial autocorrelation with hypertension. It is recommended that individuals over 40 years of age regularly monitor their blood pressure, maintain a healthy diet, engage in sufficient physical activity, and for those with hypertension, adhere to regular medication intake.

Authors

Institutions

Publication Details

Journal
Journal of Epidemiology and Public Health
Published
2025-04-16
DOI
https://doi.org/10.26911/jepublichealth.2025.10.02.07
Primary Topic
Food Security and Socioeconomic Dynamics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Spatial Analysis of Determinants of Hypertension Incidence in Kota Lama Subdistrict, Kupang, Indonesia

Pius Weraman, Anderias Umbu Roga, Yendris Krisno Syamruth, Apris A. Adu et al.
1 links
Journal of Epidemiology and Public Health
Food Security and Socioeconomic Dynamics
article

Spatial Analysis of Determinants of Hypertension Incidence in Kota Lama Subdistrict, Kupang, Indonesia

Pius Weraman, Anderias Umbu Roga, Yendris Krisno Syamruth, Apris A. Adu, Dominggus Agustinus Isak Lenda
article en

Abstract

Background: Cardiovascular diseases such as hypertension, heart attack, and stroke are chronic non-communicable diseases influenced by genetic, physiological, environmental, and behavioral factors. Geographic Information Systems (GIS) can be utilized for spatial analysis to identify risk factors, distribution patterns, and determinants of diseases, including hypertension. This study aims to examine the determinants of hypertension using a spatial analysis approach in Kota Lama Subdistrict, Kupang City.Subjects and Method: This study employed an ecological study design using an observational analytic method with a cross-sectional approach. The population consisted of residents aged ≥18 years in Kota Lama Subdistrict. A total of 400 individuals diagnosed with hypertension were selected using simple random sampling. The variables examined were age, overweight, lack of physical activity, high-salt diet, alcohol consumption, medication adherence, economic level, and distance to health facilities. Instruments used included a sphygmomanometer, microtoise, weight scale, and questionnaire. Spatial analysis was conducted using the GeoDa application with Regression, Bivariate Local Moran’s Index, Multivariate Local Geary, and Spatial Empirical Bayes tests.Results: The results showed significant associations and clustered spatial autocorrelation with low-to-high relative risk (RR) observed in the subdistricts of LLBK, Bonipoi, Solor, Fatubesi, Oeba, Nefonaek, and Pasir Panjang for the variables: age (p=0.001, I=0.70), overweight (p<0.001, I=0.64), lack of physical activity (p=0.00, I=0.63), high-salt diet (p=0.00, I=0.63), and alcohol consumption (p<0.001, I=0.69). There were no significant associations for variables such as irregular medication intake, economic level, and distance to health facilities, with p-values of 1.000 > α (0.050).Conclusion: Age, overweight, physical inactivity, high-salt diet, and alcohol consumption are significant determinants and show positive clustered spatial autocorrelation with hypertension. It is recommended that individuals over 40 years of age regularly monitor their blood pressure, maintain a healthy diet, engage in sufficient physical activity, and for those with hypertension, adhere to regular medication intake.

Journal of Epidemiology and Public HealthVol. 10(2)
University of Nusa Cendana (ID)
Openalex Percentile: Top 74%
Food Security and Socioeconomic Dynamics
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.