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Kata kunci : Stroke¸ Penderita Hipertensi, Perdesaan, Dewasa, Indonesia, Riskesdas
Stroke was recorded as the second-highest mortality cause at the age of 45- 54 years in rural areas of Indonesia. Stroke is multicausal brain function disorder due to vascular abnormalities. This study aimed to determine the frequency and determinants of stroke based on risk factors in hypertensive patients aged ≥ 45 years in rural areas of Indonesia. This study is a further analysis of the Riskesdas 2013 data which used cross-sectional study design. The sample of this study is hypertensive patients who aged ≥ 45 years old and lived in rural areas. The results of this study showed that the prevalence of stroke in adult hypertensive patients in rural areas amounted to 5.3%. The highest prevalence of stroke was found in North Maluku province (7.2%) and the lowest in Papua province (1.7%). In the studied variables, gender, stress, physical activity, consumption of anti-hypertensive drugs, smoking and education have relation to the prevalence of stroke in adult hypertensive patients (≥ 45 years) in rural areas of Indonesia.
Keywords : Stroke¸ Hypertensive Patient, Rural, Adult, Indonesia, Riskesdas
Hipertensi merupakan penyebab kematian No.3 di Indonesia, dengan prevalensi 31,7%, hipertensi tidak terdiagnosis sebesar 76%, berbagai indeks antropometri berhubungan dengan kejadian hipertensi, namun terdapat perbedaan mengenai cut off point. Penelitian ini bertujuan untuk menguji tiga indeks antropometri Indeks Masa Tubuh (IMT), Lingkar Pinggang (LP), dan Rasio Lingkar Pinggang Tinggi Badan (RLPTB) terhadap hipertensi. Penelitian ini menggunakan desain cross sectional, dengan menggunakan data sekunder Riskesdas tahun 2007. Penelitian ini merupakan penelitian uji diagnostik untuk melihat nilai cut off point yang optimal, AUC (Area Under The Curve) dengan receiver operating characteristic (ROC), sensitifitas, dan spesifisitas, Positive predictive value, Negative predictive value, Likelihood Rasio Positive, Likelihood Rasio Negative, pre-test dan post-test probability IMT, LP, RLPTB. Prevalensi hipertensi di Indonesia 27,15%, nilai cut off untuk IMT 22,2-23 kg/m2, LP nilai cut off 75,9 cm-79,5 cm, RLPTB nilai cut off 0,47- 0,5. Indeks antropometri dapat di gunakan sebagai alat skrening walaupun dengan kekuatan diagnostik yang lemah. Kemampuan diagnostik pada penelitian ini lebih untuk menduga mereka yang tidak sakit dengan nilai Negative predictive value yang cukup baik. Studi ini merekomemdasikan penggunaan ingkar pinggang sebaga alat skrening terhadap hipertensi karena lebih muda dan murah.
Hypertension is the third a leading cause of death in Indonesia, with a prevalence of 31.7%, and undiagnosed hypertension by 76%, various anthropometric indices associated with the incidence of hypertension, but there are differences regarding the cut off point. This study aims to test three anthropometric indexes as a screening tool of undiagnosed hypertension. This study uses cross-sectional design, using secondary data Riskesdas 2007. This research is a diagnostic test to see the optimal cut off point, AUC (Area Under the Curve) with a receiver operating characteristic (ROC), sensitivity, and specificity. The prevalence of hypertension in Indonesia 27.15%, cut-off point for BMI 22.6 kg/m2- 23 kg/m2. For the wasit Circumference cut-off point of 75.9 cm-79,5 cm. Waist to Stature Ratio cutt off point of 0.47- 0.51. Anthropometric indices can be used as screening tool even with a weak diagnostic power. Diagnostic capability in this study is more to suspect they are not sick with Negative predictive value is good. This study recommends to use of waist circumference as a screening tool for hypertension because is easier and cheaper to use.
Heart failure is a clinical syndrome that occurs when the heart fails to meet the body’s demand for oxygen and nutrients. The prevalence and mortality rate of heart failure in Indonesia are relatively high compared to other Southeast Asian countries. The occurrence of heart failure in young adults increases the risk of premature death, recurrent rehospitalization, reduced quality of life, and a greater burden on the healthcare system. Several factors such as obesity, type 2 diabetes mellitus (T2DM), hypertension, smoking, dyslipidemia, family history of premature coronary artery disease (PCAD), and sex have been identified as being associated with heart failure. Developing a predictive model to identify the most influential risk factors for heart failure in young adults is crucial for preventive strategies and early interventions. This study employed a fixed retrospective cohort design involving patients aged 18–54 years who visited the cardiology outpatient clinic or were hospitalized at four tertiary hospitals in Indonesia (National Cardiovascular Center Harapan Kita, Jakarta; Hasan Sadikin Hospital, Bandung; Sebelas Maret University Hospital, Solo; and Adam Malik Hospital, Medan) in 2021. Patients without an initial diagnosis of heart failure were included, and their risk factors were recorded according to the study variables. The patients were followed monthly from 2021 until the end of observation in 2024 to determine whether they developed heart failure. Descriptive, bivariate, and multivariable analyses were conducted using the Poisson Generalized Linear Model (GLM) to estimate coefficients, incidence rate ratios (IRR) with 95% confidence intervals, and to construct the most accurate predictive model. Based on the model, a scoring system and probability value for the occurrence of heart failure were developed. A total of 321 participants met the inclusion and exclusion criteria, with a median age of 51 years (P25–P75: 46–52 years). After four years of observation, the cumulative probability of developing heart failure was 0.713 (95% CI: 0.661–0.760). The analysis identified three significant predictors for heart failure in young adults: obesity (IRR 1.87; 95% CI 1.31–2.68), dyslipidemia (IRR 2.58; 95% CI 1.87–3.56), and T2DM (IRR 2.79; 95% CI 2.01–3.87). The IDD Score (Body Mass Index–Dyslipidemia–Diabetes) was developed as a predictive scoring system for heart failure in young adults, with a total score of 13 corresponding to a 76.8% probability. Obesity, dyslipidemia, and T2DM were found to be significant risk factors for heart failure in young adults. The proposed IDD Score demonstrated good sensitivity and specificity in predicting the occurrence of heart failure within this population.
Kata kunci :Hipertensi, aktivitas fisik, cross sectional, cox regression, IFLS 5.
Hypertension is the leading causes for prematur death worldwide. Globally, WHOreported about nearly one billion people living with hypertension and it is estimated thatthis number will escalate to more than 1,5 billion by the year 2025. Insufficient physicalactivity is one of the modifiable risk factors for hypertension, which is not required greateffort and cost. In 2013, the prevalence of hypertension among Indonesian adults was25,8% and the proportion of insufficient physical activity was 26,1%. This study aims toknow the prevalence of hypertension, the proportion of insufficient physical activity andalso its relationship among the Indonesian adults based on IFLS 5 data in 2014. A cross-sectional study was conducted among 26.043 respondents in IFLS 5 aged 18 years andabove. The JNC-7 guidelines used to defined hypertension (if systolic blood pressure≥140 mmHg and/or diastolic ≥90 mmHg), whereas physical activity measured by thehabit of performing physical activity for at least 10 minutes a week. Statistical test onbivariate and multivariate analysis using cox regression. The prevalence of hypertensionwas 24,09% and the proportion of insufficient physical activity was 35,68%. Statisticaltest shown there was a significant relationship between physical activity and hypertension(P value 0,000), people with insufficient physical activity at risk 1,15 times havinghypertension than those with active physical activity (PR: 1,15; 95 % CI: 1,09-1,21).Adults should do at least 30 minutes walking everyday, province/district health officeneeds to use social media such as Facebook, Instagram, Twitter, etc, in order to promotingthe benefit of physical activity.
Keywords :Hypertension, physical activity, cross sectional, cox regression, IFLS 5.
Keywords: Hypertension, Fast Food, Soft Drink, Meat and IFLS-5.