Association between preventive health management and high-risk drinking among women of childbearing age: a correlational study of the ninth Korea National Health and Nutrition Examination Survey

TL;DR

This study found that 9.5% of women of childbearing age in Korea engage in high-risk drinking, with factors like smoking and skipping breakfast being significant contributors.

Contribution

The study identifies specific modifiable factors associated with high-risk drinking among women of childbearing age in Korea.

Findings

9.5% of women of childbearing age were classified as high-risk drinkers.

Smoking status had the strongest association with high-risk drinking (OR=4.20).

Skipping breakfast and lower education levels were also significantly linked to high-risk drinking.

Abstract

This study aimed to investigate the prevalence of high-risk drinking among women of childbearing age and to identify factors associated with high-risk drinking.

Data were obtained from the first (2022) and second (2023) years of the ninth Korea National Health and Nutrition Examination Survey. The study sample comprised 2,101 women of childbearing age (19–49 years). Data were analyzed using complex sample analysis to appropriately account for population weights, survey clustering, and stratified sampling.

Among respondents, 9.5% were classified as high-risk drinkers. Significant differences in alcohol consumption were observed according to education level, employment status, skipping breakfast in the past 2 days, physical activity intensity, perceived stress level, smoking status, and dental check-up status. In the multiple logistic regression analysis, education level (odds ratio [OR]=1.26, p=.015), employment status (OR=1.44, p=.045), skipping breakfast in the past 2 days (OR=1.81, p<.001), smoking status (OR=4.20, p<.001), and dental check-up status (OR=1.70, p=.002) remained significantly associated with high-risk drinking.

These findings highlight the need for targeted public health strategies to reduce high-risk drinking among women of childbearing age. Healthcare providers may use these findings to design interventions that strengthen preventive health behaviors, promote regular meal patterns, support smoking cessation, and encourage routine dental check-ups. Public health practitioners may also utilize these results to develop programs that promote healthy lifestyle practices in this population. Further research is needed to refine and enhance intervention strategies.

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