Nikson Sitorus

The consequences associated with pregnancy termination have garnered attention from healthcare professionals, particularly in Indonesia. However, national-level evidence on the factors driving pregnancy termination in Indonesia remains limited. This research aimed to identify patterns and characteristics associated with pregnancy termination among reproductive-age women in Indonesia. A cross-sectional study analyzed secondary data from the 2012 and 2017 Indonesian Demographic and Health Survey, involving women aged 15–49. The weighted sample included 42,269 individuals in 2012 and 47,001 in 2017. Binary logistic regression identified the correlates of pregnancy termination. Among 89,270 women of reproductive age, the prevalence of pregnancy termination was 12.68% in 2012 and 12.95% in 2017. Pregnancy termination was more frequently reported among women aged 44–49 years (adjusted odds ratio (AOR): 4.34, 95% confidence interval (CI): 3.54–5.33), those with secondary education (AOR: 1.29, 95% CI: 1.14–1.46), married women (AOR: 195.40, 95% CI: 114.70–332.90), employed women (AOR: 1.05, 95% CI: 1.00–1.09), individuals with health insurance (AOR: 1.07, 95% CI: 1.02–1.11), those who had experienced domestic violence (AOR: 1.07, 95% CI: 1.02–1.11), and regular television viewers (AOR: 1.10, 95% CI: 1.05–1.15). Conversely, pregnancy termination was less commonly reported among women with 1–2 living children (AOR: 0.80, 95% CI: 0.74–0.87), those who expressed no preference for having more children (AOR: 0.89, 95% CI: 0.84–0.94), and women using modern contraception (AOR: 0.76, 95% CI: 0.72–0.80). The findings revealed that the prevalence did not observe any changes in the incidence of pregnancy terminations between 2012 and 2017. Further evaluation by healthcare professionals is crucial to understanding the reasons behind pregnancy termination, especially among women of reproductive age. Insights into factors related to pregnancy termination, especially sociodemographic factors, can help mitigate the pregnancy termination in this population.

Objectives: The aim of this study was to investigate the relationship between the number of patient comorbidities and the delays in seeking treatment for coronary heart disease (CHD).Methods: This longitudinal study utilized secondary data from the Non-Communicable Disease Risk Factor (NCDRF) cohort study conducted in Bogor City. Individuals who participated in the NCDRF cohort study and were diagnosed with CHD within the 6-year study period met the inclusion criteria. Respondents who were not continuously monitored up to the 6th year were excluded. The final sample included data from respondents with CHD who participated in the NCDRF cohort study and were monitored for the full 6-year duration. The final logistic regression analysis was conducted on data collected from 812 participants.Results: Among the participants with CHD, 702 out of 812 exhibited a delay in seeking treatment. The risk of a delay in seeking treatment was significantly higher among individuals without comorbidities, with an odds ratio (OR) of 3.5 (95% confidence interval [CI], 1.735–7.036; p<0.001). Among those with a single comorbidity, the risk of delay in seeking treatment was still notable (OR, 2.6; 95% CI, 1.259–5.418; p=0.010) when compared to those with 2 or more comorbidities. These odds were adjusted for age, sex, education level, and health insurance status.Conclusion: The proportion of patients with CHD who delayed seeking treatment was high, particularly among individuals with no comorbidities. Low levels of comorbidity also appeared to correlate with a greater tendency to delay in seeking treatment.

Objectives: Several previous studies have stated that consuming certain foods and beverages might increase the risk of chronic kidney disease (CKD). This study aimed to examine the relationships of food and beverage consumption with other risk factors for CKD.Methods: Data sources included the 2018 Basic Health Research (Riskesdas) and the National Socio-Economic Survey (Susenas), which were analyzed using a cross-sectional design. The study samples were households from 34 provinces in Indonesia, and the analysis was performed with provincial aggregates. Data were analyzed using risk factor analysis followed by linear regression to identify relationships with CKD.Results: The prevalence of CKD in Indonesia was 0.38%. The province with the highest prevalence was North Kalimantan (0.64%), while the lowest was found in West Sulawesi (0.18%). Five major groups were formed from 15 identified risk factors using factor analysis. A linear regression model presented 1 significant selected factor (p=0.006, R2=31%). The final model of risk factors included water quality, consumption of fatty foods, and a history of diabetes.Conclusion: Drinking water quality, fatty food consumption, and diabetes are associated with CKD. There is a need to monitor drinking water, as well as to promote health education and provide comprehensive services for people with diabetes, to prevent CKD.

Purpose: Indonesia is facing an increasing occurrence of non-communicable diseases (NCDs) every year. We assessed the modifiable, non-modifiable, and physiological risk factors of NCDs among the Indonesian population. Methods: Secondary data was analyzed from the 2018 Indonesian basic health research (RISKESDAS). The national survey included participants aged 15– 54 years and obtained 514,351 responses. Linear systematic two-stage sampling was conducted by RISKESDAS. Furthermore, chi-square and binary logistic regression were utilized to explore the determinant of NCDs with a significance level of 95%. Results: We found that almost 10% respondents in Indonesia had NCDs. We observed that depression has a higher odd (aOR: 2.343; 95% CI: 2.235– 2.456) contributed to NCDs and followed other factors such as no education (aOR: 1.049; 95% CI: 1.007– 1.092), passive smoking (aOR: 0.910; 95% CI: 0.878– 0.942), fatty food (aOR: 1.050; 95% CI: 1.029– 1.073), burnt food (aOR: 1.033; 95% CI: 1.005– 1.062), food with preservatives (aOR: 1.038; 95% CI: 1.002– 1.075), seasoned food (aOR: 1.057; 95% CI: 1.030– 1.084), soft drinks (aOR: 1.112; 95% CI: 1.057– 1.169), living in an urban area (aOR: 1.143; 95% CI: 1.119– 1.168), living in central Indonesia (1.243; 95% CI: 1.187– 1.302), being female (aOR: 1.235; 95% CI: 1.177– 1.25), and obese (aOR: 1.787; 95% CI: 1.686– 1.893). Conversely, people in Indonesia who undertook vigorous activity (aOR: 0.892; 95% CI: 0.864– 0.921), had employment (aOR: 0.814; 95% CI: 0.796– 0.834), had access to improved sources of drinking water (aOR: 0.910; 95% CI: 0.878– 0.942), and were aged 35– 44 years (aOR: 0.457; 95% CI: 0.446– 0.467) were less likely to develop NCDs. Conclusion: Modifiable, non-modifiable, and physiological risk factors have a significant influence on NCDs in Indonesia. This finding can be valuable information for Indonesian Government to arrange a cross-collaboration between government, healthcare workers, and society through advocacy, partnership, health promotion, early detection, and management of NCDs.