Comparative analysis of DALY in people with diabetes mellitus between Central Java and Yogyakarta

Akbar Eka Nugraha; Devi Yanthre Manurung

doi:10.35814/jifi.v24i2.2069

Penulis

Akbar Eka Nugraha Departement of Pharmacy, Faculty of Medicine, Universitas Sebelas Maret, Surakarta 57126, Indonesia
Devi Yanthre Manurung Departement of Pharmacy, Faculty of Medicine, Universitas Sebelas Maret, Surakarta 57126, Indonesia

DOI:

https://doi.org/10.35814/jifi.v24i2.2069

Kata Kunci:

Diabetes mellitus, DALY, YLD, YLL

Abstrak

Diabetes mellitus (DM) is a non-communicable disease with an increasing health burden. Differences in disease burden in Indonesia can be attributed to various factors. Therefore, a comparative analysis of disease burden based on DALY is needed to understand the differences in the epidemiological characteristics of DM in Central Java and Yogyakarta. This study is a comparative descriptive study with a quantitative approach using secondary data. DALY and its components were analyzed to observe trends, calculate the Compound Annual Growth Rate (CAGR), and statistically tested using independent t-test to assess differences in DALY values. The values showed an increasing trend in both provinces during the observation period. Yogyakarta had significantly higher DALY values than Central Java, with an average DALY rate of 1062.48 in Yogyakarta and a DALY rate of 807.01 in Central Java (p < 0.05). The rate of disease burden growth was also higher in Yogyakarta (2.38%) than in Central Java (2.21%). The proportion of YLL was greater than that of YLD, indicating that DM had a greater impact on premature death than on disability. These results emphasize the need for regional health policies that focus on preventing premature death and strengthening early detection of DM.

Referensi

[1] K. L. Ong et al., ‘Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021’, The Lancet, vol. 402, no. 10397, pp. 203–234, 2023, doi: 10.1016/S0140-6736(23)01301-6.

[2] M. Wahidin et al., ‘Projection of diabetes morbidity and mortality till 2045 in Indonesia based on risk factors and NCD prevention and control programs’, Sci. Rep., vol. 14, no. 1, pp. 1–17, 2024, doi: 10.1038/s41598-024-54563-2.

[3] Badan Pusat Statistik, ‘Statistik Penduduk Lanjut Usia 2024’, Badan Pusat Statistik, vol. 21, no. 1, pp. 1–273, 2024, [Online]. Available: https://www.bps.go.id/id/publication/2024/12/31/a00d4477490caaf0716b711d/statistik-penduduk-lanjut-usia-2024.html

[4] P. Liamputtong, Handbook of Research Methods in Health Social Sciences. Singapore: Springer Nature, 2019. doi: 10.1007/978-981-10-5251-4_96.

[5] I. F. de A. Tonetto, M. H. B. Baptista, D. dos S. Gomides, and A. E. Pace, ‘Quality of life of people with diabetes mellitus’, Revista da Escola de Enfermagem, vol. 53, pp. 1–8, 2019, doi: 10.1590/S1980-220X2018002803424.

[6] K. Dulyapach, P. Ngamchaliew, P. Vichitkunakorn, P. Sornsenee, and K. Choomalee, ‘Prevalence and Associated Factors of Delayed Diagnosis of Type 2 Diabetes Mellitus in a Tertiary Hospital: A Retrospective Cohort Study’, Int. J. Public Health, vol. 67, no. November, pp. 1–9, 2022, doi: 10.3389/ijph.2022.1605039.

[7] G. Li et al., ‘Cardiovascular mortality, all-cause mortality, and diabetes incidence after lifestyle intervention for people with impaired glucose tolerance in the Da Qing Diabetes Prevention Study: A 23-year follow-up study’, Lancet Diabetes Endocrinol., vol. 2, no. 6, pp. 474–480, 2014, doi: 10.1016/S2213-8587(14)70057-9.

[8] M. Alijanzadeh et al., ‘Availability and affordability of diabetes healthcare services associated with the frequency of diabetes-related complications’, BMC Health Serv. Res., vol. 24, no. 1, 2024, doi: 10.1186/s12913-024-12065-x.

[9] E. M. M. Gkrinia and A. Belančić, ‘A Narrative Review on the Risk Factors and Healthcare Disparities of Type 2 Diabetes’, Diabetology, vol. 6, no. 4, pp. 1–14, 2025, doi: 10.3390/diabetology6040025.

[10] K. Jáuregui-Renaud et al., ‘Health-related quality of life related to diabetes multisensory deficits and derealization’, Sci. Rep., vol. 15, no. 1, pp. 1–13, 2025, doi: 10.1038/s41598-025-13356-x.

[11] J. Zhang et al., ‘Impact of COVID-19 infection on mortality, diabetic complications and haematological parameters in patients with diabetes mellitus: A systematic review and meta-Analysis’, BMJ Open, vol. 15, no. 3, pp. 1–8, 2025, doi: 10.1136/bmjopen-2024-090986.

[12] F. Al Rashdi, S. Al Harrasi, M. Al Ismaili, A. G. AL Yaaqubi, Z. Atwan, and C. Tabche, ‘The profound impact of COVID-19 on the control and care of diabetic patients: a comprehensive retrospective cohort study’, BMC Primary Care, vol. 25, no. 1, 2024, doi: 10.1186/s12875-024-02672-2.

[13] U. Religioni, R. Barrios-Rodríguez, P. Requena, M. Borowska, and J. Ostrowski, ‘Enhancing Therapy Adherence: Impact on Clinical Outcomes, Healthcare Costs, and Patient Quality of Life’, Medicina (Lithuania), vol. 61, no. 1, pp. 1–12, 2025, doi: 10.3390/medicina61010153.

[14] Z. Ismail, W. I. W. Ahmad, S. H. Hamjah, and I. K. Astina, ‘The impact of population ageing: A review’, Iran. J. Public Health, vol. 50, no. 12, pp. 2451–2460, 2021, doi: 10.18502/ijph.v50i12.7927.

[15] M. Choi, J. K. Sempungu, E. H. Lee, and Y. H. Lee, ‘Living longer but in poor health: healthcare system responses to ageing populations in industrialised countries based on the Findings from the Global Burden of Disease Study 2019’, BMC Public Health, vol. 24, no. 1, pp. 1–12, 2024, doi: 10.1186/s12889-024-18049-0.