Prevalence and associated factors for prehypertension and hypertension among Indonesian adolescents: a cross-sectional community survey.

OBJECTIVE: To estimate the prevalence and determine the associated factors for developing prehypertension and hypertension among Indonesian adolescents. DESIGN: National cross-sectional study. SETTING: This study was conducted in all the provinces in Indonesia. PARTICIPANTS: The population in this study were all household members in Basic Health Research 2013 aged 15-19 years. The sample was all members of the 2013 Riskesdas household aged 15-19 years with the criteria of not having physical and mental disabilities, and having complete data. The number of samples analysed was 2735, comprising men (n=1319) and women (n=1416). MAIN OUTCOME: Dependent variables were prehypertension and hypertension in adolescents based on blood pressure measurements. RESULTS: The results of the analysis showed that the prevalence of prehypertension in adolescents was 16.8% and hypertension was 2.6%. In all adolescents, the risk factors for prehypertension were boys (adjusted OR, aOR 1.48; 95% CI 1.10 to 1.97), 18 years old (aOR 14.64; 95% CI 9.39 to 22.80), and 19 years old (aOR 19.89; 95% CI 12.41 to 31.88), and obese (aOR 2.16; 95% CI 1.02 to 4.58). Risk factors for hypertension in all adolescents included the age of 18 years old (aOR 3.06; 95% CI 1.28 to 7.34) and 19 years (aOR 3.25; 95% CI 1.25 to 8.41) and obesity (aOR 5.69; 95% CI 2.20 to 14.8). In adolescent girls, the chance of developing prehypertension increased with increasing age and low-density lipoprotein (LDL) cholesterol levels. Several risk factors for hypertension in adolescent boys were age, central obesity and LDL cholesterol levels. CONCLUSION: This study shows that the trend of prehypertension in adolescents has appeared, besides hypertension. There are distinct patterns of factors that influence it in adolescent girls and boys, which can be useful to sharpen of planning and implementing health programmes.

Geo-clusters and socio-demographic profiles at village-level associated with COVID-19 incidence in the metropolitan city of Jakarta: An ecological study.

The Special Capital Region of Jakarta is the epicentre of the transmission of COVID-19 in Indonesia. However, much remains unknown about the spatial and temporal patterns of COVID-19 incidence and related socio-demographic factors explaining the variations of COVID-19 incidence at local level. COVID-19 cases at the village level of Jakarta from March 2020 to June 2021 were analyzed from the local public COVID-19 dashboard. Global and local spatial clustering of COVID-19 incidence was examined using the Moran's I and local Moran analysis. Socio-demographic profiles of identified hotspots were elaborated. The association between village characteristics and COVID-19 incidence was evaluated. The COVID-19 incidence was significantly clustered based on the geographical village level (Moran's I = 0.174; p = .002). Seventeen COVID-19 high-risk clusters were found and dynamically shifted over the study period. The proportion of people aged 20-49 (incidence rate ratio [IRR] = 1.016; 95% confidence interval [CI]: 1.012-1.019), proportion of elderly (≥50 years) (IRR = 1.045; 95% CI = 1.041-1.050), number of households (IRR = 1.196; 95% CI = 1.193-1.200), access to metered water for washing, and the main occupation of the residents were village level socio-demographic factors associated with the risk of COVID-19. Targeted public health responses such as restriction, improved testing and contact tracing, and improved access to health services for those vulnerable populations are essential in areas with high-risk COVID-19.

Spatial and temporal variation of dengue incidence in the island of Bali, Indonesia: An ecological study.

BACKGROUND: Dengue fever control in the tropical island of Bali in Indonesia carries important significance both nationally and globally, as it is one of the most endemic islands in Indonesia and a worldwide popular travel destination. Despite its importance, the spatial and temporal heterogeneity in dengue risk and factors associated with its variation in risk across the island has not been not well explored. This study was aimed to analyze for the first time the geographical and temporal patterns of the incidence of dengue and to quantify the role of environmental and social factors on the spatial heterogeneity of dengue incidence in Bali. METHODS: We analyzed retrospective dengue notification data at the sub-district level (Kecamatan) from January 2012 to December 2017 which obtained from the Indonesian Ministry of Health. Seasonality in notified dengue incidence was assessed by seasonal trend decomposition analysis with Loess (STL) smoothing. Crude standardized morbidity rates (SMRs) of dengue were calculated. Moran's I and local indicators of spatial autocorrelation (LISA) analysis were employed to assess spatial clustering and high-risk areas over the period studied. Bayesian spatial and temporal conditional autoregressive (CAR) modeling was performed to quantify the effects of rainfall, temperature, elevation, and population density on the spatial distribution of risk of dengue in Bali. RESULTS: Strong seasonality of dengue incidence was observed with most cases notified during January to May. Dengue incidence was spatially clustered during the period studied with high-risk kecamatans concentrated in the south of the island, but since 2014, the high-risk areas expanded toward the eastern part of the island. The best-fitted CAR model showed increased dengue risk in kecamatans with high total annual rainfall (relative risk (RR): 1.16 for each 1-mm increase in rainfall; 95% Credible interval (CrI): 1.03-1.31) and high population density (RR: 7.90 per 1000 people/sq.km increase; 95% CrI: 3.01-20.40). The RR of dengue was decreased in kecamatans with higher elevation (RR: 0.73 for each 1-m increase in elevation; 95% CrI: 0.55-0.98). No significant association was observed between dengue RR and year except in 2014, where the dengue RR was significantly lower (RR: 0.53; 95% CrI: 0.30-0.92) relative to 2012. CONCLUSIONS: Dengue incidence was strongly seasonal and spatially clustered in Bali. High-risk areas were spread from kecamatans in Badung and Denpasar toward Karangasem and Klungkung. The spatial heterogeneity of dengue risk across Bali was influenced by rainfall, elevation, and population density. Surveillance and targeted intervention strategies should be prioritized in the high-risk kecamatans identified in this study to better control dengue transmission in this most touristic island in Indonesia. Local health authorities should recommend travelers to use personal protective measures, especially during the peak epidemic period, before visiting Bali.