Introduction
Physical health-related quality of life (HRQoL) is a clinically relevant predictor of adverse health outcomes e.g. disability [
1], cancer, coronary heart disease and all-cause mortality [
2]. Obesity has been associated with reduced physical HRQoL in numerous studies [
3,
4] with a stronger association in women compared to men [
5‐
8]. Several recent studies have demonstrated that even a “metabolically healthy obese” phenotype, i. e. persons with obesity in the absence of metabolic risk factors or comorbidities, show reduced scores of physical HRQoL compared to the group of metabolically healthy non-obese (MHNO) [
9‐
11]. However, these previous studies applied different definitions of metabolic health and HRQoL and considered various subsets of potential confounders. Potential confounders of the association between obesity and lower HRQoL include higher age, low educational status, health-related behaviours [
12], and chronic health conditions [
13]. In general, metabolic health is associated with higher HRQoL, however, sex-specific associations are still unclear [
14]. Previous studies described similar effects among men and women [
15] as well as different associations among both sexes, with a negative effect of an impaired health status observed only among women [
14]. To our knowledge only one previous study on obesity among metabolic health men and women conducted sex-specific analyses and found that metabolic health had a greater impact on HRQoL than obesity in men while similar effects for metabolic health and obesity were seen in women [
9].
Against this background the aim of this study was (1) to determine whether obesity is related to lower HRQoL independent of metabolic health status also considering age, low educational status, health-related behaviours, and comorbidities as potential confounders, and (2) whether associations are similar among men and women.
Results
Table
1 (men) and Table
2 (women) present the study characteristics by strata of metabolic health status and obesity. In men the distribution of participants was MHNO (
n = 1900), MUNO (
n = 608), MHO (
n = 196), MUO (
n = 594) and in women it was MHNO (
n = 2193), MUNO (
n = 514), MHO (
n = 277), MUO (
n = 578). MHNO (mean age men: 42.1 years, women: 42.4 years) were younger than MHO and MUO; MUNO (men: 55.6 years, 59.3 years) was the oldest group. Percentage of low educational status was lowest in MHNO (men: 30.7%, women: 27.8%) and highest in MUO (men: 51.3%, women: 59.5%). Percentages of daily smoking and physical activity ≥ 2.5 h were lower among metabolically unhealthy men and women. Percentages of high alcohol consumption were highest among MUNO for men (22.7%) and highest among MHNO for women (14.9%). The prevalence of comorbidities was higher among metabolically unhealthy men and women. The PCS was highest among MHNO (men: 54.0, women: 53.1) and lowest among MUO (men: 47.0, women: 44.1).
Table 1
Study characteristics among men (mean/% and 95% confidence interval)
Age (mean, years) | 0 | 42.1 (41.3–42.9) | 56.8 (55.2–58.4) | 44.4 (42.3–46.6) | 55.6 (54.2–57.1) |
Educational status (%) | 21 | | | | |
Low | | 30.7 (27.5–34.0) | 41.3 (35.8–47.0) | 41.2 (32.3–50.7) | 51.3 (45.5–57.2) |
Middle | | 51.3 (48.4–54.2) | 38.8 (33.9–43.8) | 48.3 (39.3–57.4) | 38.3 (32.7–44.1) |
High | | 18.0 (15.9–20.4) | 20.0 (16.0–24.6) | 10.5 (6.7–16.0) | 10.4 (8.0–13.5) |
Smoking (%) | 17 | | | | |
No | | 64.1 (60.9–67.2) | 74.0 (68.1–79.2) | 66.8 (57.0–75.4) | 72.1 (66.7–76.9) |
Occasionally | | 7.5 (6.2–9.1) | 4.3 (2.5–7.3) | 5.9 (3.4–10.3) | 5.6 (3.6–8.7) |
Daily | | 28.4 (25.6–31.4) | 21.7 (17.0–27.2) | 27.3 (18.9–37.6) | 22.3 (17.9–27.6) |
Physical activity ≥ 2.5 h (%) | 116 | 28.2 (25.5–31.0) | 18.4 (14.6–22.9) | 30.0 (22.5–38.6) | 18.9 (15.0–23.4) |
Alcohol consumption (%) | 55 | | | | |
Never | | 10.4 (8.4–12.8) | 8.4 (5.8–11.9) | 11.3 (6.7–18.3) | 9.2 (6.2–13.3) |
Moderate | | 72.0 (69.1–74.8) | 68.9 (64.9–72.7) | 72.6 (63.7–80.0) | 71.5 (65.9–76.4) |
High | | 17.6 (15.6–19.8) | 22.7 (19.3–26.5) | 16.1 (10.7–23.4) | 19.4 (15.4–24.1) |
One or more comorbidities (%) | 29 | 25.7 (23.2–28.3) | 51.9 (46.8–57.0) | 25.7 (23.2–28.3) | 49.5 (44.1–54.9) |
Physical component summary (mean)a
| 158 | 54.0 (53.6–54.5) | 49.8 (48.8–50.9) | 51.8 (50.4–53.3) | 47.0 (45.9–48.2) |
Table 2
Study characteristics among women (mean/% and 95% confidence interval)
Age (mean, years) | 0 | 42.4 (41.7–43.1) | 61.9 (60.6–63.3) | 47.0 (45.0–48.9) | 59.3 (57.8–60.8) |
Educational status (%) | 17 | | | | |
Low | | 27.8 (25.3–30.6) | 55.9 (49.9–61.8) | 45.1 (37.0–53.4) | 59.5 (53.8–65.0) |
Middle | | 56.2 (53.3–59.1) | 36.0 (30.3–42.1) | 49.9 (42.0–57.9) | 36.5 (31.4–41.9) |
High | | 16.0 (13.6–18.6) | 8.1 (6.1–10.7) | 5.0 (3.1–8.0) | 4.0 (2.5–6.2) |
Smoking (%) | 17 | | | | |
No | | 69.9 (67.0–72.7) | 78.9 (73.4–83.5) | 74.5 (67.8–80.3) | 79.1 (74.3–83.2) |
Occasionally | | 7.7 (6.4–9.2) | 2.1 (1.1–4.1) | 4.1 (2.1–7.7) | 1.5 (0.7–3.3) |
Daily | | 22.4 (20.0–25.0) | 19.0 (14.8–24.1) | 21.4 (16.1–27.9) | 19.4 (15.5–24.1) |
Physical activity ≥ 2.5 h (%) | 110 | 15.9 (14.1–18.0) | 13.7 (10.3–18.1) | 16.9 (12.0–23.2) | 14.0 (10.5–18.4) |
Alcohol consumption (%) | 44 | | | | |
Never | | 16.3 (14.5–18.3) | 17.0 (13.0–21.8) | 21.0 (15.6–27.8) | 29.7 (25.1–34.7) |
Moderate | | 68.8 (66.2–71.3) | 70.8 (65.3–75.8) | 68.9 (60.7–76.1) | 61.1 (55.8–66.1) |
High | | 14.9 (13.1–16.9) | 12.2 (8.8–16.8) | 10.0 (5.5–17.4) | 9.2 (6.2–13.6) |
One or more comorbidities (%) | 22 | 26.0 (23.7–28.6) | 54.6 (49.4–59.7) | 40.2 (34.0–46.7) | 59.9 (54.7–64.9) |
Physical component summary (mean)a
| 150 | 53.1 (52.7–53.6) | 47.6 (46.4–48.7) | 49.2 (47.8–50.6) | 44.1 (43.1–45.1) |
Table
3 shows the PCS in relation to categories of metabolic health and obesity for men and women. Additionally, Table S1 (Additional file
2) presents the estimations for physical functioning. Compared with MHNO, all other categories of metabolic health and obesity were consistently associated with lower PCS values among men and among women. The inverse association with PCS was strongest for MUO (men: −7.0, women: −9.0), intermediate for MUNO (men: −4.2, women: −5.6) and least pronounced for MHO (men: −2.2, women −3.9. Adjusting for age (Model 2) and further adjustment for sociodemographic characteristics, lifestyle variables and comorbidities (Model 3) decreased the association among all strata of metabolic health and obesity. After adjusting for confounding variables, the effect was strongest for MUO (men: −3.9, women: −4.9), intermediate for MHO (men: −1.8, women: −2.1) and least pronounced for MUNO (men: −1.3, women: −1.5). The results for the PCS were similar to the results found in sensitivity analyses using the physical functioning score as dependent variable (Additional file
2: Table S1).
Table 3
Linear regression models for physical component summary (SF-36 v2) according to metabolic health and obesity status
Men |
Model 1 | 3140 | Reference | −4.2 | −5.3 | −3.1 | <.001 | −2.2 | −3.6 | −0.8 | .003 | −7.0 | −8.2 | −5.8 | <.001 |
Model 2 | 3140 | Reference | −1.7 | −2.7 | −0.6 | .002 | −1.9 | −3.3 | −0.5 | .006 | −4.7 | −5.9 | −3.5 | <.001 |
Model 3 | 2988 | Reference | −1.3 | −2.3 | −0.3 | .014 | −1.8 | −3.1 | −0.5 | .009 | −3.9 | −5.1 | −2.7 | <.001 |
Women |
Model 1 | 3412 | Reference | −5.6 | −6.8 | −4.4 | <.001 | −3.9 | −5.4 | −2.5 | <.001 | −9.0 | −10.2 | −7.9 | <.001 |
Model 2 | 3412 | Reference | −2.1 | −3.3 | −0.9 | <.001 | −3.3 | −4.7 | −1.9 | <.001 | −6.2 | −7.4 | −5.0 | <.001 |
Model 3 | 3270 | Reference | −1.5 | −2.7 | −0.3 | .018 | −2.1 | −3.2 | −1.0 | <.001 | −4.9 | −6.1 | −3.6 | <.001 |
Table
4 presents gender differences in PCS for categories of metabolic health and obesity status. PCS scores were consistently lower among women compared to men in all strata. Gender differences were lowest among MHNO (−0.9) and highest among MUO (−2.9). After adjusting for confounding variables differences remained statistically significant only among MHNO.
Table 4
Gender differences (reference = men) in physical component summary (SF-36 v2) in categories of metabolic health and obesity status
Model 1 | −0.9 | −1.5 | −0.2 | .007 | −2.3 | −3.7 | −0.8 | .003 | −2.7 | −4.8 | −0.5 | .014 | −2.9 | −4.5 | −1.4 | <.001 |
Model 2 | −0.8 | −1.5 | −0.2 | .008 | −1.1 | −2.4 | 0.2 | .084 | −2.1 | −4.2 | −0.1 | .043 | −2.3 | −3.7 | −0.8 | .003 |
Model 3 | −0.8 | −1.4 | −0.1 | .019 | −1.0 | −2.4 | 0.3 | .130 | −1.2 | −3.1 | 0.6 | .200 | −1.1 | −2.6 | 0.5 | .180 |
Discussion
Obesity and metabolic aberration alone and in combination were associated with impaired physical HRQoL in both sexes. The effect of both factors in combination corresponds approximately to the effects for obesity and metabolic aberration alone. These results underline previous findings suggesting that MHO individuals are not always completely healthy with regard to HRQoL [
10,
11] as well as morbidity of cardiovascular diseases [
30,
31] and all-cause mortality [
32,
33]. A recent clinical study found similar levels of HRQoL among MHO and MUO individuals [
34]. This finding seems to contrast with our results with larger effects of MUO vs. MHNO compared to MHO vs. MHNO. The discrepancies may be caused by the clinical setting as patients who are willing to be treated probably are likely to suffer from obesity. However, in conclusion both studies support the finding that MHO is not a healthy state.
The association between physical HRQoL, metabolic health and obesity categories is stronger among women, as lower PCS values were found in all strata of metabolic health and obesity among women compared to men. Furthermore, differences between strata were greater among women than among men. Lower values of physical HRQoL among women compared to men were also reported in previous studies analysing the association with obesity [
7,
8] and obesity in combination with metabolic health [
9,
10] opposed to one meta-analysis where no gender differences were found [
3]. In the present study, adjustment for potential confounders including education, health-related behaviours and comorbidities gender differences were attenuated. Thus, lower HRQoL among women than men might be partially explained by sex-differences in the prevalence of obesity-related comorbidities [
35] and health-related behaviours e.g. physical activity [
36]. Among both, men and women physical HRQoL was highest for the MHNO group followed by MHO and MUNO and lowest for the group of MUO. This is in contrast to findings of a Korean cross-sectional study [
9], where HRQoL were measured using the euroqol-5 dimensions questionnaire. Among Korean men physical HRQoL was lowest among the group of MUNO, suggesting that an unhealthy metabolic status have a greater impact than obesity. In this previous study, no differences in physical HRQoL were observed between groups of metabolic status and obesity among men after adjusting for age, sociodemographic variables, lifestyle and comorbidity. Among Korean women, the results were similar to the findings of our study.
Persons in the different categories of obesity and metabolic health status substantially differed according to mean age, educational status and prevalence of one or more comorbidities. Previous studies reported lower values of HRQoL at higher age, among persons with chronic diseases, and in low educational status groups [
13,
21,
37,
38]. Considering these potential confounders in multivariable regression analyses in the present study reduced the effect of lower physical HRQoL among all strata of metabolic health and obesity status compared to MHNO, but remained statistically significant among both sexes. A difference of two to three points in the PCS is considered clinically relevant [
20]. Thus, after adjusting for confounding variables lower values of physical HRQoL among MHO compared to MHNO remained clinically relevant only among women. Adjustment for confounding factors had the largest impact among MUNO as differences in comparison to MHNO do not remain clinically significant.
The strength of this study is its large sample of the general population which allows stratification for gender and adjustment for potential confounding variables. Furthermore, anthropometric parameters were measured by standard protocols and trained staff and valid data collection tools were used to assess physical HRQoL, diseases, and various health determinants, and biological parameters. A few limitations have to be acknowledged. Since this is a cross-sectional study the direction of the causal pathway between physical HRQoL and metabolic health according to obesity category cannot be identified. Poorer physical HRQoL, characterized by sedentary behaviour, might increase weight gain and vice versa. Due to the study design we used different cut-offs among fasting and non-fasting participants for serum glucose and triglycerides. Finally, bias due to misclassification cannot be ruled out completely.
Conclusion
Obesity was significantly related to lower physical HRQoL, independent of metabolic health status, which underlines previous findings that MHO status is not necessarily a healthy state. This inverse relationship can be partly explained by age, educational status, health-related behaviors, and comorbidities. The associations were found in both sexes and were consistently more pronounced among women compared to men.
Acknowledgements
Not applicable.
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