Given the increasing burden of chronic diseases in Indonesia, characteristics of chronic multimorbidities have not been comprehensively explored. Therefore, this research evaluated chronic multimorbidity patterns among Indonesians using Indonesian National Health Insurance (INHI) sample data. We included 46 chronic diseases and analyzed their distributions using population-weighted variables provided in the datasets. Results showed that chronic disease patients accounted for 39.7% of total patients who attended secondary health care in 2015–2016. In addition, 43.1% of those were identified as having chronic multimorbidities. Findings also showed that multimorbidities were strongly correlated with an advanced age, with large numbers of patients and visits in all provinces, beyond those on Java island. Furthermore, hypertension was the leading disease, and the most common comorbidities were diabetes mellitus, cerebral ischemia/chronic stroke, and chronic ischemic heart disease. In addition, disease proportions for certain disease dyads differed according to age group and gender. Compared to survey methods, claims data are more economically efficient and are not influenced by recall bias. Claims data can be a promising data source in the next few years as increasing percentages of Indonesians utilize health insurance coverage. Nevertheless, some adjustments in the data structure are accordingly needed to utilize claims data for disease control and surveillance purposes.

Background: Modern contraceptives are proven as the most effective birth control methods. However, it was a change in the pattern of modern method use in Indonesia to traditional. Objectives: This study investigated the pattern of contraceptive use and its determinant in Indonesia between 2007 and 2017. Methods: The study employed data from the Indonesian Demographic and Health Survey (IDHS) 2007, 2012, and 2017. Eligible participants included all women aged 15–49 who were married/living together with a partner. The dependent variable was contraceptive method use categorized as long-term, short-term, and traditional. Weighted pooled logistic regression analysis was applied to determine the shifting patterns of the independent variables related to contraceptive use over time. Results: The trend of contraceptive use in Indonesia has shifted over the three periods of the IDHS. During the three survey periods, contraceptive use was still dominated by short-term contraception, although over the last five years, the proportion has shown a decline of around 9%. Traditional contraceptive adoption followed the same patterns as long-acting reversible contraception (LARC), although having a smaller prevalence. Education level was significantly unassociated with the use of the traditional method at the beginning of the observation. However, more educated and knowledgeable women about contraceptive methods were more likely to use traditional contraceptives, switched from long-acting use following the next five and ten years. Long-term methods were no longer significantly more common among women in Java and Bali after five and ten years; the likelihood of using traditional methods in Java and Bali was growing. Conclusion: This study showed that contraceptive use and determinants were always dynamic over time. Therefore, family planning strategies and policies should adapt accordingly. Giving an understanding of contraceptive methods' benefits and risks through adequate method information is encouraged to prevent contraceptive dropout or switch to less-effective methods.

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BACKGROUND: eHealth literacy can affect one’s health behavior through the intention to motivate individuals and allow them to make health-related choices. AIM: This study aimed to examine the association between eHealth literacy and self-care behavior among youths in Yogyakarta during the coronavirus disease pandemic. METHODS: In this cross-sectional study, 455 never-married youths aged 15–24 years who lived in Yogyakarta Province completed the online survey that was conducted from October 5 to October 19, 2020. There were some indicators measured in the survey: eHealth Literacy, health information-seeking behavior, the intention of health maintenance, self-maintenance of health behavior, perceived behavioral control, subjective norms, and attitude toward health maintenance. Path analysis was conducted to determine the influencing factors of eHealth literacy and self-care behavior. RESULTS: Five in 10 youths accessed the internet more than 4 hours a day, though more than half of youths had low eHealth literacy levels. Intention (β = 0.09; 95% CI = 0.01–0.18; p = 0.037), perceived behavioral control (β = 0.46; 95% CI = 0.38–0.54; p ≤ 0.001), and subjective norms (β = 0.24; 95% CI = 0.16–0.33; p ≤ 0.001) had a significant positive direct effect on youth self-care behavior. Attitude indirectly affects self-care behavior through the intention (β = 0.46; 95% CI = 0.39–0.53; p ≤ 0.001) together with eHealth literacy (β = 0.11; 95% CI= 0.04–0.18; p = 0.001). CONCLUSION: Health literacy does not explicitly affect youths’ self-care behavior, but it becomes crucial when it builds youths’ intention to behave healthier. The positive impact of intention to enhance self-health care seems to have occurred only if eHealth literacy was adopted.