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

Dany, Frans; Dewi, Rita Marleta; Tjandrarini, Dwi Hapsari; Pradono, Julianty; Delima, Delima; Sariadji, Kambang; Handayani, Sarwo; Kusumawardani, Nunik

doi:10.1186/s12889-020-09592-7

Cited by 22 publications

(25 citation statements)

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“…This study was conducted in full accordance with the World Medical Association Declaration of Helsinki [15]. This was a secondary analysis of data from the Indonesian National Oral Health Survey (INOHS) of 2018 which was part of the Indonesian Basic Health Research (IBHR) [16,17]. The IBHR is a national survey that is conducted every five years and covers all households in Indonesia [16].…”

Section: Methodsmentioning

confidence: 99%

Validation of self-reported oral health among Indonesian adolescents

et al. 2021

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Background and aim With the recognition of health as a subjective state, self-reported oral health has been applied in many epidemiological studies. However, the validity of self-reports may vary across different age groups and socio-cultural backgrounds and by using different tools. This study aimed to assess the validity of self-reported oral health of 15-year-old Indonesian adolescents. Materials and methods This study used data from the Indonesian National Oral Health Survey, a part of the Indonesian Basic Health Survey 2018. The study included 572 15-year-old Indonesian adolescents. We compared the presence of clinically assessed dental caries, tooth loss, and fillings following the World Health Organization Basic Health Survey method and questionnaire-based self-reported oral conditions using McNemar test. The sensitivity (Sn), specificity (Sp), and likelihood ratios (LRs) of self-reports were calculated using clinical assessment as the reference standard. The overall accuracy of self-reports in identifying the clinical condition was assessed using the area under the curve (AUC) of a receiver operating characteristic curve. Results Self-reports significantly underestimated the clinical presence of caries (39.3% and 67.1%) and overestimated the clinical presence of tooth loss (9.3% and 4.2%) and filling (4.7% and 2.4%, p < 0.05). All self-reported conditions had higher Sp (at least 70.3%) than Sn (max 54.2%) and the AUC for all self-reported conditions were < 0.7. Self-reporting the presence of fillings had the highest LR+ = 11. Conclusions Self-reporting oral health in Indonesian adolescents had low accuracy. Further studies of other methods of self-reporting are needed before they can be used to assess adolescents’ oral health in epidemiological surveys.

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Section: Methodsmentioning

confidence: 99%

Validation of self-reported oral health among Indonesian adolescents

et al. 2021

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“…Individual blood specimen was taken for laboratory test only in 25,000 households representing the national population. To explore public health answers and inspection procedures, structured interviews were carried out by enumerators who had been trained by the research team (Dany et al, 2020;NIHRD, 2018).…”

Section: Methodsmentioning

confidence: 99%

How Well Does Body Mass Index (BMI) Predict Undiagnosed Hypertension and Diabetes in Indonesian Adults Community Population?

Mubasyiroh¹,

Kusumawardani²,

Rachmalina³

et al. 2021

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BACKGROUND: Previous studies have reported that Body Mass Index (BMI) cut-off was related to non-communicable diseases. This study aimed to give the latest evidence related to the accuracy of BMI cut-off towards undiagnosed hypertension and diabetes in the Indonesian population. METHODS: This was A cross-sectional study that involved data of the 2018 national population-based health survey, with the samples were 15,516 male and female populations aged between 19 years old and above. This study only included those claimed to have never been diagnosed as suffering from diabetes and hypertension by health workers. Receiver operating characteristic (ROC) analysis was conducted to assess the optimal BMI cut-off. The logistic regression was performed to assess the association of BMI on undiagnosed hypertension and diabetes controlled by several variables. RESULTS: The average BMI sample was 24 kg/m2 (SD = 4.6 kg/m2. The proportion of undiagnosed hypertension was 36.9%, and 12.3% for the proportion of undiagnosed diabetes. According to the ROC, the result shows BMI was more sensitive to hypertension conditions compared to diabetes. BMI cut-off points at 23.9 kg/m2 (AUC=0.59;Se=64.3%;Sp=53.4%) was the optimum value to predict hypertension and 24.9 kg/m2 (AUC=0.55;Se=53.1%;Sp=56.4%) was the optimum for diabetes. CONCLUSIONS: Based on the optimal AUC cut-off points for BMI which is around 0.5, BMI needs to be reconsidered as an anthropometric index in predicting undiagnosed hypertension and diabetes. And an assessment can be made using other anthropometric indices, such as waist circumference to predict undiagnosed hypertension and diabetes.

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“…Recent study reported that the prevalence of prediabetes in rural and urban Indonesia has reached 44.8% and 34.9% respectively.1³ Interestingly, the risk of prediabetes has already increased starting from the age of 30. 13 In line with this finding, around one-quarter of people with DM in Indonesia are less than 45 years old,2 or commonly grouped as an early onset DM, which is associated with worse outcomes. At the community level, it is urgently needed to start the screening for metabolic diseases in Indonesia at an earlier age.…”

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confidence: 88%