| Summary: | 碩士 === 國立陽明大學 === 衛生福利研究所 === 102 === Prevalence of obesity is found to be on an increasing trend in both developed and developing countries, and is an important risk factor of many chronic diseases. Health Promotion Administration, Ministry of Health and Welfare especially emphasizes the importance of obesity-related chronic problems. Although the negative correlation between obesity and health-related quality of life (HRQoL) has partially been confirmed by some studies, there is not yet data discussed by scholars at the national level to explore whether social variation impacts the relationship between obesity and HRQoL (health-related quality of life). Therefore the purpose of this study is, based on the Drug Abuse Data of year 2005 National Health Interview Survey, to explore a.) the relationship between the degree of obesity (body mass index, BMI) and HRQoL (SF-36) - physical and mental component score (PCS and MCS), and b.) whether the relationship between obesity (BMI) and HRQoL differs among various socio-economic status (SES), assessed based on education level, work status, and household monthly income.
The method of the study is cross-sectional with secondary data analysis, by controlling possible socio-demographic variables, including demographic variables ( age, gender, living arrangements , religion , marital status ), health status ( the number of chronic diseases , mental illness ) and health behavior (drinking, smoking, chewing betel nut and sports ), to study the relationship between the degree of obesity (BMI) and HRQoL and whether the relationship differs due to SES variation.
All data were compiled and statistically analyzed with SAS 9.2 packaged software, T-test and one-way ANOVA were used to conduct descriptive and bivariate analysis, multiple regression were used to control personal qualities to perform multivariate analysis, and stratified analysis by using educational degrees, work status, and household income to investigate how these factors correlate to the independent and dependent variables. The results are as follows :
a.) With other relevant factors under control, the underweight and severely obese groups both score significantly lower than the normal weight on HRQoL – PCS, while those of mild obesity score significantly higher than the normal weight. As for MCS, the underweight group scores significantly lower than the normal weight, while those who are overweight, of mild obesity and moderate obesity all score significantly higher than those of normal weight. For those of severe obesity, even though their score of MCS is lower than those of normal weight, the result was found to be with no statistical significance.
b.) Based on SES to study in stratification on the relationship between obesity and HRQoL (for both PCS, MCS), the overall relationship between the two does not vary due to different degrees of education or household income. However the score is found to decrease more obviously for the group with lower income and higher degree of obesity. Alternatively, working condition is found to be an influencing factor between the relationship of the degree of obesity and PCS. For severe-obesity group who have work, the PCS is found to have no statistical significance comparing to that of the group with normal weight, but for severe-obesity group who don’t work, the PCS is found significantly lower in comparison (β=-2.38，p<0.0001 ). In terms of MCS, it was found that the group with heavier weight had better HRQoL score whether they have work or not.
The results of this study can be used by health-related units, while intending obesity-related policy, on economical side, to consider more on socioeconomic factors and pay attention on how obesity affects HQRL to impact on the groups of low socioeconomic status. If HRQoL scores can be used to develop quality indicators to be included in the regular survey, then it can be more clearly understood the change and importance on how obesity impacts on HRQoL, and it can also urge health units to take control on growing obesity prevalence and to improve the situation of lowering HRQoL caused by obesity. Regular survey and monitoring can also reflect policy objectives with actual figures.
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