Pandemic Pressure: Changes in Hypertensive Management Adherence in Indonesia.

PURPOSE: This study aimed to determine factors associated with changes in adherence to hypertension management (medication adherence and blood pressure control) in respondents with hypertension before and during the COVID-19 pandemic in Bogor city, Indonesia. METHODS: An observational study was conducted using two sources of data (before and during COVID-19 pandemic). Data before the pandemic were derived from the 2019 Cohort Study of non-communicable disease risk factors. Data during the pandemic were derived from an online survey conducted in September and October 2020. Information from 880 participants were analyzed. The dependent variable was the change in adherence to hypertension management before and during the COVID-19 pandemic. Multivariate analysis was performed using logistic polynomial regression. RESULTS: Respondents who adhered to hypertension management decreased from 82.0% in 2019 to 47.8% in 2020. The likelihood of non-adherence (respondents who did not adhere to hypertension management both before and during the pandemic) increased in respondents below 55 years old, who did not own any healthcare insurance, who were not obese, and who had no other comorbidities. In the partial adherence group (respondents who did not adhere to hypertension management either before or during the pandemic), we found that most respondents adhered before the pandemic but no longer adhered during the COVID-19 pandemic. We found an increased partial adherence in young and highly educated respondents. CONCLUSIONS: Efforts to improve adherence to hypertension management after the COVID-19 pandemic should target those who were young, highly educated, who did not have any healthcare insurance, and who did not perceive themselves as not having comorbidities.

Urban-rural distinction of potential determinants for prediabetes in Indonesian population aged ≥15 years: a cross-sectional analysis of Indonesian Basic Health Research 2018 among normoglycemic and prediabetic individuals.

BACKGROUND: Based on Basic Health Research (RISKESDAS) conducted by Ministry of Health, Indonesia, prediabetes prevalence tends to increase from 2007 until 2018. The numbers are relatively higher in rural than those in urban area despite of small discrepancies between the two (~ 2-4%). The purpose of this study was to identify urban-rural differences in potential determinants for prediabetes in Indonesia. METHODS: This analysis used secondary data collected from nationwide Health Survey in 2018. Respondents were aged ≥15 years who met inclusion criteria of analysis with no history of diabetes mellitus. Prediabetes criteria followed American Diabetes Association 2019. Multiple logistic regression was also employed to assess the transition probability of potential determinants for prediabetes in urban and rural Indonesia. RESULTS: Up to 44.8% of rural respondents were prediabetics versus their urban counterparts at 34.9%, yet non-response bias was observed in the two. Young adults aged 30 years were already at risk of prediabetes. Urban-rural distinction for marital status and triglyceride level was observed while other determinants tended to overlap across residence. Several modifiable factors might contribute differently in both population with careful interpretation. CONCLUSIONS: The minimum age limit for early prediabetes screening may start from 30 years old in Indonesia. Urban-rural distinction for marital status and triglyceride level was observed, yet non-response bias between the two groups could not be excluded. A proper model for early prediabetes screening need to be developed from a cohort study with adequate sample size.