In this study the relationship between neighborhood deprivation and the unmet health care needs of elderly individuals (≥ 65 years) was examined. Some previous studies suggested that neighborhood characteristics affect access to health care, yet research on the unmet needs of older individuals is limited.
Multilevel logistic regression analysis was used to assess the relationship of neighborhood-level factors with unmet health care needs due to costs, adjusting for individual-level factors, in individuals ≥ 65 years in the 2017 Korean Community Health Survey (
There were 2.6% of elderly individuals who experienced unmet health care needs due to costs. Following adjustment for individual and neighborhood characteristics, the neighborhood deprivation in urban areas was found to have an inverse association with unmet needs (odds ratio = 0.50; 95% confidence interval = 0.24–1.06) for the most deprived quartile versus the least deprived quartile). However, in rural areas neighborhood deprivation was not a significant variable. Among the individual-level variables, household income was one of the strongest correlates with unmet needs in both urban and rural areas.
The present findings suggest that targeted policy interventions reflecting both neighborhood and individual characteristics, should be implemented to reduce the unmet health care needs of elderly individuals.
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This study aimed to develop a high-risk drinking scorecard using cross-sectional data from the 2014 Korea Community Health Survey.
Data were collected from records for 149,592 subjects who had participated in the Korea Community Health Survey conducted from 2014. The scorecard model was developed using data mining, a scorecard and points to double the odds approach for weighted multiple logistic regression.
This study found that there were many major influencing factors for high-risk drinkers which included gender, age, educational level, occupation, whether they received health check-ups, depressive symptoms, over-moderate physical activity, mental stress, smoking status, obese status, and regular breakfast. Men in their thirties to fifties had a high risk of being a drinker and the risks in office workers and sales workers were high. Those individuals who were current smokers had a higher risk of drinking. In the scorecard results, the highest score range was observed for gender, age, educational level, and smoking status, suggesting that these were the most important risk factors.
A credit risk scorecard system can be applied to quantify the scoring method, not only to help the medical service provider to understand the meaning, but also to help the general public to understand the danger of high-risk drinking more easily.
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