Health Status Assessment Tool Development based on Dietary Patterns in Middle-Aged Women

Hye-Jin Lee; Kyung-Hea Lee

doi:10.5720/kjcn.2016.21.1.37

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Lee and Lee: Health Status Assessment Tool Development based on Dietary Patterns in Middle-Aged Women

Research Article

Korean Journal of Community Nutrition 2016; 21(1): 37-52.

Published online: 29 February 2016

DOI: https://doi.org/10.5720/kjcn.2016.21.1.37

Health Status Assessment Tool Development based on Dietary Patterns in Middle-Aged Women

Hye-Jin Lee, Kyung-Hea Lee

Department of Food and Nutrition, Changwon National University, Gyeongnam, Korea.

Corresponding author: Kyung-Hea Lee. Department of Food and Nutrition, Changwon National University, 20 Changwondaehakro, Uichang-gu, Changwon, Gyeongnam, 51140, Korea. Tel: (055) 213-3514, Fax: (055) 281-7480, khl@changwon.ac.kr

Received 3 January 2016 Revised 13 February 2016 Accepted 13 February 2016

(open-access):

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Objectives

This study was performed to develop an assessment tool for middle aged women's health status based on dietary patterns, which will have practical applications in the working field of health and hygiene, aiming at improving the middle aged women's quality of life through their health improvement.

Methods

As a first step, a literature review was conducted and the original data of '2008~2009 Korea Health and Nutrition Examination Survey' were reanalyzed. This analysis identified 65 preliminary questions that may be relevant to the study. After verifying the content validity by experts, the 65 questions were reduced into 51 questions. In order to secure higher validity of the candidate items, verification of their clinical validity was conducted among women aged between 45 and 60 years. Finally, an assessment tool was developed by applying weight and scoring.

Results

Selected 51 questions were used to verify clinical validity and the results showed that 20 questions were relevant, nine questions ('regular meal time', 'regular amount of meal', 'intake frequency of dairy products', 'intake frequency of fruits', 'intake frequency of meat products', 'intake frequency of high cholesterol foods', 'intake frequency of salty foods', 'appetite', 'eat breakfast everyday') were related to dietary life. Eleven other questions ('self-rated health status', 'deep sleep', 'smoking', 'frequency of drinking', 'stress levels', 'health-related fitness levels', 'pounding of the heart', 'strange feelings on the skin', 'interfere with daily life', 'menopause will bring you a chance to see the life in a different perspective', and 'body mass index') were selected as valid questions. For the response scale for each question, 5 point Likert scale was used to make total 100 point score.

Conclusions

This study is the first attempt to develop a health status assessment tool for middle aged women based on their dietary patterns. We conclude that this tool is expected to be a useful and practical tool in the field.

Keywords: health status assessment tool, dietary patterns, middle aged women, women's health

Figures and Tables

Table 1

Components of the preliminary questions

Table 2

Content validity analysis results of the developed questionnaire for health status assessment

1) CVI: Content Validity Index.

Table 3

General information of the study subjects

1) Mean±SD

Table 4

Averages of clinical indicators

1) N (%)

Table 5

Mean value and significant correlations between health-related questions and clinical indicators

1) Maximum score is 5, 2) BMD: Bone Mass Density, 3) SBP: Systolic Blood Pressure, 4) DBP: Diastolic Blood Pressure, 5) TG: Triglyceride

^*: p < 0.05, ^**: p < 0.01, ^***: p < 0.001

Table 6

Mean value and significant correlations of between diet-related questions and clinical indicators

1) Maximum score is 5

^*: p < 0.05, ^**: p < 0.01, ^***: p < 0.001.

Table 7

Multiple regression analysis of questions with clinical indicators

Calculated by Regression analysis method

Table 8

Results of expert survey for setting weights of questions

Table 9

Applying to the calculation of weighted score

Table 10

The developed questionnaire for health status assessment tool

Acknowledgments

This research was supported by a grant from the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (grant number. 2011-0013053).

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ORCID iDs: Kyung-Hea Lee
https://orcid.org/http://orcid.org/0000-0003-0444-4824
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