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Gender differences in health-related quality of life associated with abdominal obesity in a Korean population

Objectives Overall obesity, as measured by body mass index (BMI), has been associated with a low level of health-related quality of life (HRQOL), but little is known about abdominal obesity. This cross-sectional study aimed to determine whether abdominal obesity, as measured by waist circumference (WC), would be significantly associated with HRQOL independent of overall obesity, and if so, whether the association would differ by gender among the Korean population. Design Cross-sectional study. Setting South Korea. Participants Using data from the 2007–2009 Korea National Health and Nutrition Examination Survey, a total of 13 754 men and women aged 19–65 years were selected, and information about height (cm), weight (kg), WC (cm) and the EuroQOL-5 Dimensions (EQ-5D) scores for HRQOL were taken. Results Not only an overall obesity (as categorised into obese, overweight or non-overweight groups based on BMI) but also an abdominal obesity (defined by WC ≥90 cm for men and ≥85 cm for women) was significantly associated with lower EQ-5D scores, after adjusting for age, gender, socioeconomic variables and a number of comorbidities. Even after adjusting BMI effect, the association between abdominal obesity and lower EQ-5D scores remained significant for women, but not for men. Conclusions Among the Korean population aged 19–65 years, abdominal obesity was associated with impaired HRQOL, independently of overall obesity. Furthermore, this association differed by gender, being significant only for women. Therefore, primary healthcare professionals should pay attention to gender differences in the impact of obesity on HRQOL when evaluating population-based health programmes.

The authors conducted a study on the impact of obesity and abdominal obesity on quality of life using a national, populationbased survey. They conclude that abdominal obesity is significantly and independently associated with lower health-related quality of life in women, but not in men.

Major comments
1. The authors conclude that there is an effect of abdominal obesity on HRQOL in women but not in men. Looking at the coefficients provided in tables 3 and 4, it seems that the magnitude of the effect is quite small, -0.002 point changes for being abdominally obese (table 4, model III) and -0.017 points for being a woman with abdominal obesity (table 4, model III). The difference is somewhat magnified in the figures due to the fact that the y axis starts at 0.90 and encompasses only 0.07 units of the HRQOL scale. The authors should discuss if this statistically significant difference (probably due to the large sample size) is also clinically meaningful.
2. Similarly, in the methods (page 7, lines 5 to 12) the authors indicate that a score of zero in the HRQOL scale is equivalent to death and negative scores to status worse than death, but do not indicate what is the maximum score.
According to the values provided in the figure and table 2, it seems that the scale they use has a maximum value of one.
If it is the case, then most participants score quite high in their quality of life and it might be possible that the impact of obesity/abdominal obesity in QOL is rather modest.
3. Looking further at the data from table 2, it seems that most participants do not report any problem in the EQ-5D scale. This is expected due to their relatively young age (<65 years), as the prevalence of disease (and deterioration of QOL) increases after this age. Hence, the sample might not be optimal for assessing the effect of obesity/abdominal obesity on QOL, as QOL is very high for almost all participants. Further, the authors could implement their analysis by assessing the impact of obesity / abdominal obesity on each component of the EQ-5D (as indicated in table 2) using chi-square and logistic regression.
4. Statistical analyses. The authors adequately took into account the complex sampling frame, but some issues have to be assessed. For instance, in table 1, the number of participants with co-morbidities ≥3 is extremely small (only 2 participants with ≥4), thus precluding the use of chi-square as the computed frequencies will be lower than 5. Using such unbalanced groups might also lead to spurious results in the multivariate analysis. It would be better that the authors group the categories "3" and "≥4" co-morbidities, or even that they merge the last three ones into a "≥2 comorbidities" to have adequate cell sizes during multivariate adjustment.
5. The authors make recommendations in their abstract (and main text) for "primary healthcare professional to pay attention to gender differences in the impact of obesity on health outcomes". Still, they did not assess the associations between health outcomes and obesity but rather between health-related quality of life and obesity. This is a different issue, as a severely diseased person might consider himself/herself with a good quality of life, whereas a less diseased (or even healthy) person might rate his/her quality of life to a lower degree.

Minor comments
1. In  Figure 1 firstly, and then Table 3 and 4. 2. How did they judge gender difference? 3. I don't agree to the data analyses in Table 3 and 4. The authors should do the subgroup analyses of BMI or WC categories and life quality by sex to see the gender differences. 4. Besides results in Table 3 and 4, life quality can also be considered as category variable and logistical analysis can be performed to test the effect of BMI or WC categories.
Minor concerns Last line of Table 4: should be "Model III"

Reviewer comments Responses
The effect of abdominal obesity appears to be quite small. It might be statistically significant due to the large sample size, but clinically unmeaningful.
The sample selection might not be optimal for assessing the study question: the authors focused on relatively young participants (<65 years), in whom quality of life is quite high.
We thank you for your thoughtful consideration and comments. We have revised our manuscript in response to your comments, which have made it a more robust paper.
We addressed the issues of clinically meaningful effects of abdominal obesity on HRQOL and the sample selection in the following descriptions.
The authors conducted a study on the impact of obesity and abdominal obesity on quality of life using a national, population-based survey. They conclude that abdominal obesity is significantly and independently associated with lower healthrelated quality of life in women, but not in men.
Major comments 1. The authors conclude that there is an effect of abdominal obesity on HRQOL in women but not in men. Looking at the coefficients provided in tables 3 and 4, it seems that the magnitude of the effect is quite small, -0.002 point changes for being abdominally obese ( The authors should discuss if this statistically significant difference (probably due to the large sample size) is also clinically meaningful.
We really appreciate your comments. We corrected the y axis starting at 0.70 and ended at 1.00 in Figure 1 (see page 17).
Moreover, we revised Figure 1  According to the values provided in the figure and table 2, it seems that the scale they use has a maximum value of one. If it is the case, then most participants score quite high in their quality of life and it might be possible that the impact of obesity/abdominal obesity in QOL is rather We really appreciate your comments.

We indicated the maximum EQ-5D score (1.0 point) in the text. (see page 7.)
We addressed the impact of abdominal obesity by referring to the MCID value in our response to your prior comment. modest.

3.
Looking further at the data from table 2, it seems that most participants do not report any problem in the EQ-5D scale. This is expected due to their relatively young age (<65 years), as the prevalence of disease (and deterioration of QOL) increases after this age.
Hence, the sample might not be optimal for assessing the effect of obesity/abdominal obesity on QOL, as QOL is very high for almost all participants. Further, the authors could implement their analysis by assessing the impact of obesity / abdominal obesity on each component of the EQ-5D (as indicated in table 2) using chi-square and logistic regression.

previous version in Page 6.
In addition, the fairly high EQ-5D score may be explained by culturally different valuation of EQ-5D as well as the age range (19-65 years). The valuation varies by population.
Based on your comment, we conducted the analyses by assessing the impact of obesity/abdominal obesity on each component of EQ-5D) using a chi-square test and logistic regression. We would like to report the analytic findings with supplemental figures and tables that were attached in this revised version. We described the findings in the section of Results (see pages 10 -11).
In the supplemental Table 4, we found that significant associations of abdominal obesity with EQ-5D domains occurred across all the domains of EQ-5D only in women (except for self-care domain) in fully-adjusted logistic regression models.
4. Statistical analyses. The authors adequately took into account the complex sampling frame, but some issues have to be assessed. For instance, in table 1, the number of participants with co-morbidities ≥3 is extremely small (only 2 participants with ≥4), thus precluding the use of chisquare as the computed frequencies will be lower than 5. Using such unbalanced groups might also lead to spurious results in the multivariate analysis. It would be better that the authors group the categories "3" and "≥4" co-morbidities, or even that they merge the last three ones into a "≥2 co-morbidities" to have adequate cell sizes during multivariate adjustment.
According to your comment, we revised the section of co-morbidities in Table 2 by collapsing the last three into≥2 co-morbidities.
After collapsing the levels of co-morbidities, we included the modified variable for co-morbidities in the regression models, which slightly changed the magnitudes of coefficients and p-values in the main text and Tables 3 and 4. We highlighted them in red.
5. The authors make recommendations in their abstract (and main text) for "primary healthcare professional to pay attention to gender differences in the impact of obesity on health outcomes". Still, they did not assess the associations between health outcomes and obesity but rather between health-related quality of life and obesity. This is a different issue, as a severely diseased person might consider himself/herself with a good quality of life, whereas a less diseased (or even healthy) person might rate his/her quality of life to a lower degree.
Based on your comment, we replaced the phrase, "health outcomes" by "HRQOL" in the last sentence of the abstract. We have corrected the erratum.
Thank you very much for all your comments.

Reviewer's comments Responses
Jina et al. conducted a cross-sectional study to examine gender differences in health-related quality of life associated with abdominal obesity in a Korean population. A total of 13,754 men and women aged 19-65 years were included. The sample size in this study was large enough to draw the conclusions. I suggest the authors consider several issues.
We thank you for your thoughtful consideration and comments. We have revised our manuscript in response to your comments, which have made it a more robust paper.
Major concerns 1. The authors should describe Figure 1 firstly, and then Table 3 and 4.
According to your comments, we described Figure 1 first, and then Tables 3 and 4 (see page 10).

How did they judge gender difference?
We tested whether there would be gender differences in the associations between obesity/abdominal obesity and HRQOL using an interaction model. Namely, the gender difference was judged by statistical significances of an interaction term between gender and BMI/WC on HRQOL. Tables 3 and 4 indicated such significant interaction effects.
More specifically, Table 3 shows the finding for the significant interaction effects between gender and the BMI category (see the interaction terms: women * obese effect and women * overweight effect). Table 4 also shows the finding for the significant interaction effects between gender and the WC category (please refer to the interaction term: women * abdominal obesity). Table 3 and 4. The authors should do the subgroup analyses of BMI or WC categories and life quality by sex to see the gender differences.