* Corresponding Author
Spatial Distribution Pattern of Hypertension: Case of Jakarta, Indonesia
https://doi.org/10.22146/ijg.72615 Martya Rahmaniati Makful(1*), Yohana Septianty Isabel(2), Verry Adrian(3)
(1) Biostatistics and Population Studies Department, Faculty of Public Health, Universitas Indonesia, Depok, Indonesia
(2) Biostatistics and Population Studies Department, Faculty of Public Health, Universitas Indonesia, Depok, Indonesia
(3) Health office DKI Jakarta, Jakarta, Indonesia
(*) Corresponding Author
Abstract
Hypertension is one type of Non-communicable Disease (NCD) that is a burden on the government in disease control every year. Hypertension is caused by various risk factors. Most of the risk factors for hypertension are lifestyles that can be changed. This study aims to determine the pattern of distribution of hypertension cases based on risk factors, social factors, health care facilities. The spatial approach was used to determine the spatial relationship between hypertension risk factors and hypertension cases in the Jakarta province. The spatial approach was used to determine the spatial relationship between hypertension risk factors and hypertension cases in the Jakarta province. The results showed that the screening program variable had a spreading pattern with a negative spatial relationship and there was a spatial interaction between the screening program variables and hypertension cases. Improving the quality and quantity of Non-communicable Disease Integrated Assistance Post activities of local health centers, which are the front line in preventive and promotive activities is expected to be the key to successful control of hypertension cases in the Jakarta.
Keywords
Full Text:
PDFReferences
Alcocer, L., & Cueto, L. (2008). Review: Hypertension, a health economics perspective. Therapeutic Advances in Cardiovascular Disease, 2(3), 147–155. https://doi.org/10.1177/1753944708090572
Anselin, L., & Getis, A. (1992). Spatial statistical analysis and geographic information systems. The Annals of Regional Science, 26(1), 19–33. https://doi.org/10.1007/BF01581478
Azhari, M. H. (2017). Faktor-Faktor yang Berhubungan dengan Kejadian Hipertensi di Puskesmas Makrayu Kecamatan Ilir Barat II Palembang. Jurnal Aisyah : Jurnal Ilmu Kesehatan, 2(1), 23–30. https://doi.org/10.30604/jika.v2i1.29
Benjamin, E. J., Muntner, P., Alonso, A., Bittencourt, M. S., Callaway, C. W., Carson, A. P., Chamberlain, A. M., Chang, A. R., Cheng, S., Das, S. R., Delling, F. N., Djousse, L., Elkind, M. S. V., Ferguson, J. F., Fornage, M., Jordan, L. C., Khan, S. S., Kissela, B. M., Knutson, K. L., … On behalf of the American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee. (2019). Heart Disease and Stroke Statistics—2019 Update: A Report From the American Heart Association. Circulation, 139(10). https://doi.org/10.1161/CIR.0000000000000659
Cromley, E. K., & McLafferty, S. (2012). GIS and public health (2nd ed). The Guilford Press.
Damayantie, N., Heryani, E., & Muazir, M. (2018). Faktor-Faktor yang Mempengaruhi Perilaku Penatalaksanaan Hipertensi oleh Penderita di Wilayah Kerja Pskesmas Sekernan Ilir Kabupaten Muaro Jambi tahun 2018. Jurnal Ners Dan Kebidanan (Journal of Ners and Midwifery), 5(3), 224–232. https://doi.org/10.26699/jnk.v5i3.ART.p224-232
Darmawan, D., & Zulfa, S. (2015). PENGARUH PROMOSI KESEHATAN TERHADAP MOTIVASI PASIEN HIPERTENSI TENTANG PELAKSANAAN DIET HIPERTENSI DI POLIKLINIK PENYAKIT DALAM RS. RAJAWALI BANDUNG. JURNAL PENDIDIKAN KEPERAWATAN INDONESIA, 1(1), 56. https://doi.org/10.17509/jpki.v1i1.1187
Di Chiara, T., Scaglione, A., Corrao, S., Argano, C., Pinto, A., & Scaglione, R. (2017). Education and hypertension: Impact on global cardiovascular risk. Acta Cardiologica, 72(5), 507–513. https://doi.org/10.1080/00015385.2017.1297626
Elias, M. A., Pati, M. K., Aivalli, P., Srinath, B., Munegowda, C., Shroff, Z. C., Bigdeli, M., & Srinivas, P. N. (2018). Preparedness for delivering non-communicable disease services in primary care: Access to medicines for diabetes and hypertension in a district in south India. BMJ Global Health, 2(Suppl 3), e000519. https://doi.org/10.1136/bmjgh-2017-000519
Greenland, S., & Morgenstern, H. (1989). Ecological Bias, Confounding, and Effect Modification. International Journal of Epidemiology, 18(1), 269–274. https://doi.org/10.1093/ije/18.1.269
Grekousis, G. (2020). Spatial Analysis Methods and Practice: Describe – Explore – Explain through GIS (1st ed.). Cambridge University Press. https://doi.org/10.1017/9781108614528
Griffith, D. A., Amrhein, C. G., & Desloges, J. R. (1991). Statistical analysis for geographers. Prentice Hall.
Grotto, I., Huerta, M., & Sharabi, Y. (2008). Hypertension and socioeconomic status. Current Opinion in Cardiology, 23(4), 335–339. https://doi.org/10.1097/HCO.0b013e3283021c70
Kayima, J., Nankabirwa, J., Sinabulya, I., Nakibuuka, J., Zhu, X., Rahman, M., Longenecker, C. T., Katamba, A., Mayanja-Kizza, H., & Kamya, M. R. (2015). Determinants of hypertension in a young adult Ugandan population in epidemiological transition—The MEPI-CVD survey. BMC Public Health, 15(1), 830. https://doi.org/10.1186/s12889-015-2146-y
Kim, M. J., & Park, N. H. (2018). Analysis of Spatial Distribution of Hypertension Prevalence and Its Related Factors based on the Model of Social Determinants of Health. Journal of Korean Academy of Community Health Nursing, 29(4), 414. https://doi.org/10.12799/jkachn.2018.29.4.414
Kitron, U., & Kazmierczak, J. J. (1997). Spatial Analysis of the Distribution of Lyme Disease in Wisconsin. American Journal of Epidemiology, 145(6), 558–566. https://doi.org/10.1093/oxfordjournals.aje.a009145
Koenig, W. D. (1999). Spatial autocorrelation of ecological phenomena. Trends in Ecology & Evolution, 14(1), 22–26. https://doi.org/10.1016/S0169-5347(98)01533-X
Kuupiel, D., Adu, K. M., Bawontuo, V., Tabong, P. T. N., Adogboba, D. A., & Mashamba-Thompson, T. P. (2020). Geographical access to point-of-care testing for hypertensive disorders of pregnancy as an integral part of maternal healthcare in Ghana. BMC Pregnancy and Childbirth, 20(1), 733. https://doi.org/10.1186/s12884-020-03441-6
Laohasiriwong, W., Puttanapong, N., & Singsalasang, A. (2018). Prevalence of hypertension in Thailand: Hotspot clustering detected by spatial analysis. Geospatial Health, 13(1). https://doi.org/10.4081/gh.2018.608
Legendre, P., & Fortin, M. J. (1989). Spatial pattern and ecological analysis. Vegetatio, 80(2), 107–138. https://doi.org/10.1007/BF00048036
Lepper, M. J. C. de, Scholten, H. J., Stern, R. M., NetLibrary, I., World Health Organization, & Regional Office for Europe. (1995). The Added value of geographical information systems in public and environmental health. Kluwer Academic Publishers.
Littenberg, B. (1990). Screening for Hypertension. Annals of Internal Medicine, 112(3), 192. https://doi.org/10.7326/0003-4819-112-3-192
Mills, K. T., Stefanescu, A., & He, J. (2020). The global epidemiology of hypertension. Nature Reviews Nephrology, 16(4), 223–237. https://doi.org/10.1038/s41581-019-0244-2
Minkler, M. (1989). Health Education, Health Promotion and the Open Society: An Historical Perspective. Health Education Quarterly, 16(1), 17–30. https://doi.org/10.1177/109019818901600105
Musinguzi, G., Bastiaens, H., Wanyenze, R. K., Mukose, A., Van geertruyden, J.-P., & Nuwaha, F. (2015). Capacity of Health Facilities to Manage Hypertension in Mukono and Buikwe Districts in Uganda: Challenges and Recommendations. PLOS ONE, 10(11), e0142312. https://doi.org/10.1371/journal.pone.0142312
Nurhasana, R., & Hartono, R. K. (2021). The Risk of Non-Communicable Diseases after being Exposed to the Urban Flood; A Literature Review and Meta-Analysis. Indonesian Journal of Geography, 53(3). https://doi.org/10.22146/ijg.65401
Okuyama, K., Akai, K., Kijima, T., Abe, T., Isomura, M., & Nabika, T. (2019). Effect of geographic accessibility to primary care on treatment status of hypertension. PLOS ONE, 14(3), e0213098. https://doi.org/10.1371/journal.pone.0213098
Pandit, A. U., Tang, J. W., Bailey, S. C., Davis, T. C., Bocchini, M. V., Persell, S. D., Federman, A. D., & Wolf, M. S. (2009). Education, literacy, and health: Mediating effects on hypertension knowledge and control. Patient Education and Counseling, 75(3), 381–385. https://doi.org/10.1016/j.pec.2009.04.006
Park, S.-Y., Kwak, J.-M., Seo, E.-W., & Lee, K.-S. (2016). Spatial analysis of the regional variation of hypertensive disease mortality and its socio-economic correlates in South Korea. Geospatial Health, 11(2). https://doi.org/10.4081/gh.2016.420
Pou, S. A., Tumas, N., Sánchez Soria, D., Ortiz, P., & Díaz, M. del P. (2017). Large-scale societal factors and noncommunicable diseases: Urbanization, poverty and mortality spatial patterns in Argentina. Applied Geography, 86, 32–40. https://doi.org/10.1016/j.apgeog.2017.06.022
Rawal, L. B., Biswas, T., Khandker, N. N., Saha, S. R., Bidat Chowdhury, M. M., Khan, A. N. S., Chowdhury, E. H., & Renzaho, A. (2017). Non-communicable disease (NCD) risk factors and diabetes among adults living in slum areas of Dhaka, Bangladesh. PLOS ONE, 12(10), e0184967. https://doi.org/10.1371/journal.pone.0184967
Samal, D., Greisenegger, S., Auff, E., Lang, W., & Lalouschek, W. (2007). The Relation Between Knowledge About Hypertension and Education in Hospitalized Patients With Stroke in Vienna. Stroke, 38(4), 1304–1308. https://doi.org/10.1161/01.STR.0000259733.43470.27
Sartik, S., Tjekyan, RM. S., & Zulkarnain, M. (2017). RISK FACTORS AND THE INCIDENCE OF HIPERTENSION IN PALEMBANG. Jurnal Ilmu Kesehatan Masyarakat, 8(3), 180–191. https://doi.org/10.26553/jikm.2017.8.3.180-191
Senadza, B. (2012). Education inequality in Ghana: Gender and spatial dimensions. Journal of Economic Studies, 39(6), 724–739. https://doi.org/10.1108/01443581211274647
Shapiro, M. F., Shu, S. B., Goldstein, N. J., Victor, R. G., Fox, C. R., Tseng, C.-H., Vangala, S., Mogler, B. K., Reed, S. B., Villa, E., & Escarce, J. J. (2020). Impact of a Patient-Centered Behavioral Economics Intervention on Hypertension Control in a Highly Disadvantaged Population: A Randomized Trial. Journal of General Internal Medicine, 35(1), 70–78. https://doi.org/10.1007/s11606-019-05269-z
Siangphoe, U., & Wheeler, D. C. (2015). Evaluation of the Performance of Smoothing Functions in Generalized Additive Models for Spatial Variation in Disease. Cancer Informatics, 14s2, CIN.S17300. https://doi.org/10.4137/CIN.S17300
Souris, M. (2018). Epidemiology and geography: Principles, methods and tools of spatial analysis. Iste Ltd/John Wiley and Sons Inc.
Suroto, Mahdalena, & Rajiani, I. (2019). Spatial Analysis of Hypertension Risk Factors Incidence in South Kalimantan Province. Indian Journal of Public Health Research & Development, 10(2), 414. https://doi.org/10.5958/0976-5506.2019.00325.5
Taher Buyong. (2007). Spatial data analysis for geographic information science. Penerbit Universiti Teknologi Malaysia.
Thill, J.-C. (Ed.). (2018). Spatial Analysis and Location Modeling in Urban and Regional Systems (1st ed. 2018). Springer Berlin Heidelberg : Imprint: Springer. https://doi.org/10.1007/978-3-642-37896-6
Tsai, P.-J., Lin, M.-L., Chu, C.-M., & Perng, C.-H. (2009). Spatial autocorrelation analysis of health care hotspots in Taiwan in 2006. BMC Public Health, 9(1), 464. https://doi.org/10.1186/1471-2458-9-464
Tuoane-Nkhasi, M., & van Eeden, A. (2017). Spatial patterns and correlates of mortality due to selected non-communicable diseases among adults in South Africa, 2011. GeoJournal, 82(5), 1005–1034. https://doi.org/10.1007/s10708-016-9725-z
Unger, T., Borghi, C., Charchar, F., Khan, N. A., Poulter, N. R., Prabhakaran, D., Ramirez, A., Schlaich, M., Stergiou, G. S., Tomaszewski, M., Wainford, R. D., Williams, B., & Schutte, A. E. (2020). 2020 International Society of Hypertension Global Hypertension Practice Guidelines. Hypertension, 75(6), 1334–1357. https://doi.org/10.1161/HYPERTENSIONAHA.120.15026
Wang, Z., Chen, Z., Zhang, L., Wang, X., Hao, G., Zhang, Z., Shao, L., Tian, Y., Dong, Y., Zheng, C., Wang, J., Zhu, M., Weintraub, W. S., Gao, R., & On behalf of the China Hypertension Survey Investigators*. (2018). Status of Hypertension in China: Results From the China Hypertension Survey, 2012–2015. Circulation, 137(22), 2344–2356. https://doi.org/10.1161/CIRCULATIONAHA.117.032380
World Health Organization (2019), https://www.who.int/news-room/events/world-hypertension-day-2019/hypertension
Yadav, A., Ladusingh, L., & Gayawan, E. (2015). Does a geographical context explain regional variation in child malnutrition in India? Journal of Public Health, 23(5), 277–287. https://doi.org/10.1007/s10389-015-0677-4
Yosmar, R., Almasdy, D., & Rahma, F. (2018). Survei Risiko Penyakit Diabetes Melitus Terhadap Masyarakat Kota Padang. Jurnal Sains Farmasi & Klinis, 5(2), 134. https://doi.org/10.25077/jsfk.5.2.134-141.2018
Zhang, X., & Kanbur, R. (2005). Spatial inequality in education and health care in China. China Economic Review, 16(2), 189–204. https://doi.org/10.1016/j.chieco.2005.02.002
Zhang, Y., Zhou, Z., Gao, J., Wang, D., Zhang, Q., Zhou, Z., Su, M., & Li, D. (2016). Health-related quality of life and its influencing factors for patients with hypertension: Evidence from the urban and rural areas of Shaanxi Province, China. BMC Health Services Research, 16(1), 277. https://doi.org/10.1186/s12913-016-1536-x
Zhou, J., Lurie, M. N., Bärnighausen, T., McGarvey, S. T., Newell, M.-L., & Tanser, F. (2012). Determinants and spatial patterns of adult overweight and hypertension in a high HIV prevalence rural South African population. Health & Place, 18(6), 1300–1306. https://doi.org/10.1016/j.healthplace.2012.09.001
DOI: https://doi.org/10.22146/ijg.72615
Article Metrics
Abstract views : 1783
| 
views : 1440
Refbacks
- There are currently no refbacks.
Copyright (c) 2023 Martya Rahmaniati Makful
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Accredited Journal, Based on Decree of the Minister of Research, Technology and Higher Education, Republic of Indonesia Number 225/E/KPT/2022, Vol 54 No 1 the Year 2022 - Vol 58 No 2 the Year 2026 (accreditation certificate download)
ISSN 2354-9114 (online), ISSN 0024-9521 (print)