* Corresponding Author
Mengungkap Distribusi dan Pola Spasial Diabetes Melitus di Kabupaten Sleman
https://doi.org/10.22146/mgi.114166 Muhammad Arif Fahrudin Alfana(1*), Agus Joko Pitoyo(2), Umi Listyaningsih(3)
(1) Fakultas Geografi, Universitas Gadjah Mada, Yogyakarta, Indonesia and Program Doktoral Geografi Universitas Gadjah Mada, Yogyakarta, Indonesia
(2) Fakultas Geografi, Universitas Gadjah Mada, Yogyakarta, Indonesia
(3) Fakultas Geografi, Universitas Gadjah Mada, Yogyakarta, Indonesia
(*) Corresponding Author
Abstract
Abstrak. Diabetes melitus merupakan salah satu penyakit tidak menular yang prevalensinya terus meningkat, termasuk di Kabupaten Sleman, sehingga diperlukan bukti ilmiah mengenai bagaimana penyakit ini terdistribusi secara spasial dalam kaitannya dengan struktur ruang dan dinamika kependudukan wilayah. Pemahaman terhadap distribusi dan pola spasial diabetes melitus menjadi penting karena penyakit kronis sering kali tidak tersebar secara acak, melainkan dipengaruhi oleh faktor lingkungan, demografi, serta karakteristik sosial yang melekat pada ruang. Penelitian ini bertujuan mengidentifikasi distribusi dan pola spasial kasus diabetes melitus di Kabupaten Sleman pada tahun 2019 dan 2021 dengan menerapkan analisis kuantitatif spasial. Data kasus diperoleh dari Dinas Kesehatan Kabupaten Sleman dan dianalisis menggunakan Global Moran’s I untuk mengetahui autokorelasi spasial secara keseluruhan serta Local Indicators of Spatial Association (LISA) untuk mengidentifikasi klaster lokal pada tingkat kapanewon. Hasil penelitian menunjukkan bahwa nilai Global Moran’s I pada kedua tahun pengamatan berada pada kisaran yang relatif rendah, menandakan lemahnya autokorelasi spasial secara global. Meskipun demikian, analisis LISA berhasil mengungkap adanya klaster signifikan bertipe High–High, terutama di wilayah urban seperti Kapanewon Mlati dan Depok, yang menunjukkan konsentrasi kasus tinggi yang dikelilingi oleh wilayah dengan kasus tinggi pula. Temuan ini menegaskan bahwa meskipun pola global tampak lemah, pola spasial lokal tetap terbentuk dan memberikan informasi penting bagi penentuan prioritas intervensi. Analisis spasial lokal terbukti lebih sensitif dalam menangkap dinamika wilayah dan variasi risiko kesehatan berbasis ruang, sehingga relevan mendukung perencanaan kesehatan daerah yang lebih terarah. Ke depan, penelitian dapat dikembangkan dengan memasukkan variabel sosial-ekonomi-lingkungan untuk memperdalam pemahaman terhadap mekanisme pembentukan klaster diabetes melitus.
Abstract. Diabetes mellitus is a major non-communicable disease with a continuously increasing prevalence, including in Sleman Regency, thus requiring scientific evidence on its spatial distribution in relation to regional spatial structure and population dynamics. Understanding the spatial distribution and patterns of diabetes mellitus is essential, as chronic diseases are rarely randomly distributed but are influenced by environmental, demographic, and social characteristics embedded in space. This study aims to identify the spatial distribution and spatial patterns of diabetes mellitus cases in Sleman Regency in 2019 and 2021 using quantitative spatial analysis. Case data were obtained from the Sleman District Health Office and analyzed using Global Moran’s I to assess overall spatial autocorrelation and Local Indicators of Spatial Association (LISA) to identify local clusters at the kapanewon level. The results indicate that Global Moran’s I values in both observation years were relatively low, suggesting weak global spatial autocorrelation. Nevertheless, LISA analysis revealed significant High–High clusters, particularly in urban areas such as Mlati and Depok, indicating concentrations of high case numbers surrounded by neighboring areas with similarly high values. These findings confirm that although global spatial patterns appear weak, local spatial patterns remain evident and provide important insights for prioritizing health interventions. Local spatial analysis proves more sensitive in capturing regional dynamics and space-based variations in health risk, thereby supporting more targeted local health planning. Future research may incorporate socio-economic and environmental variables to further elucidate the mechanisms underlying diabetes mellitus clustering.
Submitted: 2025-12-11 Revisions: 2026-01-21 Accepted: 2026-02-01 Published: 2024-02-06
Keywords
References
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DOI: https://doi.org/10.22146/mgi.114166
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