Social Demographic Factor on Early Detection Ability of Acute Coronary Syndrome in Blitar Regency Indonesia

Novita Ana Anggraini; Faridah Moh Said; Nur Syazana Umar; Rahmania Ambarika; Reni Nurhidayah

doi:10.30994/jnp.v6i2.368

Authors

Novita Ana Anggraini Department of Nursing, Institut Ilmu Kesehatan STRADA Indonesia, Kediri, Indonesia
Faridah Moh Said Lincoln University College, Malaysia
Nur Syazana Umar Department of Nursing, Institut Ilmu Kesehatan STRADA Indonesia, Kediri, Indonesia
Rahmania Ambarika Department of Nursing, Institut Ilmu Kesehatan STRADA Indonesia, Kediri, Indonesia
Reni Nurhidayah Department of Nursing, Institut Ilmu Kesehatan STRADA Indonesia, Kediri, Indonesia

DOI:

https://doi.org/10.30994/jnp.v6i2.368

Keywords:

ACS, early detection, socio demographic

Abstract

Background: The prevalence of ACS in Indonesia is high, at least 2 million people in Indonesia are diagnosed with ACS. It is one of the main causes of death among adults in many countries around the world, including Indonesia with prevalence of heart disease in Indonesia is estimated at 2 million ACS cases. One of the causes of the high ACS mortality rate is a prehospital delay. Decision time delay refers to the length of time the patient takes for early detection or to make a decision to seek help. This study will focus on the influence of social demographic factors on the ability of early detection of ACS.

Purpose: This study aims to explain the relationship between treatment-seeking behavior, transportation, and socio-demographic factors (age, gender, socio-economic, educational status, health insurance).

Methods: A prospective cross-sectional study was conducted in this study. The samples will be obtained in Blitar regency with 22 public health center sub-districts with sample 126 respondents. The correlation among variables was analyzed using chi-squared (?2), and for determining the dominant factors, multiple logistic regression with the enter method was used. A p value <0.05 was considered significant.

Results: The study found that the age, health insurance status, education level, and employment status of the patients were significant factors for early detection. Delay to early detection increased with the increase in age of the patients, although it was not significant by logistic regression.

Conclusions: This study reveals that several sociodemographic factors that can affect early detection abilities are education, employment status, and health insurance.

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