Multiple linear regression analysis was initially utilized, followed by an examination of the potential for a good nonlinear matchmaking present from the in addition to quadratic and you will cubic versions. Modified [R.sup.2] and basic error of estimate (SEE) values were used evaluate the brand new overall performance of your own predictive model regarding BF%.
All accounts out of p was in fact a couple-sided and you can p less than 0.05 are experienced mathematically extreme. All of the analyses were did using STATA app variation 12.0 (STATA Corp, College Route, Tx, USA) and you can SPSS version 17.0 (SPSS Inc., Chi town, USA).
3.1. Study Population and Baseline Characteristics. All 2,771 participants in this study were over 18 years and comprised 64% women with a median age of 52 years (IQR, 43-60) and 36% men with a median age of 60 years (IQR, 47-68). The BF% in men was statistically significantly lower than in women (27% and 34%, resp.; p < 0.001). The difference in HWDI between men and women was also statistically significant (101 [IQR, 95-107] for men and 98 [IQR, 92-104] for women; p < 0.001) (see Table 1).
In our research, HWDI, a somewhat the latest obesity dimension sign, try discovered for an enthusiastic inverse reference to BF% both in someone
Profile 1 shows the connection ranging from mediocre Bmi and you will many years. It had been discovered that, throughout the age 18 so you’re able to 39 decades, this new mean Bmi grows given that ages grows however,, immediately following interacting with sixty years old, the latest imply Body mass index minimizes since the ages expands (discover Profile step 1(a)). The reverse can be found into matchmaking ranging from imply HWDI and you will many years.
3.2. Relationship between HWDI and BF%. Figure 2 shows the relationship between HWDI and BF%. Pearson’s correlation coefficient (r) = -0.200 (p < 0.001) in men and r = -0.473 (p < 0.001) in women. In contrast, the direct relationship was found between BMI and BF%, r = 0.144 (p < 0.001) in men and r = 0.421 (p < 0.001) in women. Furthermore, the relationship between HWDI and BF% was statistically significant even when analyzed with respect to age group and gender (p < 0.001) (see Figure 3).
Mathematically, an enthusiastic inverse relationships ranging from HWDI and you can BF% is located because HWDI increased whenever you are BF% value rather reduced
3.3. The Effect of Age, Gender, and HWDI on BF%. The study of the effect of age, gender, and HWDI on BF% showed all three variables’ relationship with BF% to be statistically significant for building a prediction model (p < 0.001 for all variables). HWDI and BF% by age and gender resulted in r = -0.629/ - 0.518 (men/women) for the 18-39-year age group, r = -0.372/ - 0.560 for the 40-59-year age group, and r = -0.125/ - 0.369 for age group over 60 years (see Figure 3).
3.4. Predictive Modeling of BF% by Gender. In this study, several forms of relationship between HWDI and BF% were studied: linear, quadratic, and cubic. However, Figure 3 shows that the relationship tended bicupid aansluiting to be in linear form more than the others, and so we elected to use a linear form in the construction of the BF% prediction model. The results of a multivariate linear regression analysis, which includes the HWDI and age variables, yielded a BF% for men of – 0.159 (HWDI) + 0.161 (age) [adjusted [R.sup.2] = 0.215, standard error of estimate (SEE) = 5.37%, p < 0.001], and, for women, - 0.265 (HWDI) + 0.132 (Age) [adjusted [R.sup.2] = 0.337, SEE = 4.39%, p < 0.001] (see Table 2).
Although not, Pearson’s relationship coefficients was seen to be reasonable (r = -0.20 for males and you can r = -0.47 for females) when compared to previous knowledge you to used other carrying excess fat analysis systems that have BF% [sixteen,18, 19]. For the 1996, Gallagher mais aussi al. analyzed the connection between Body mass index and BF% and claimed beliefs out-of roentgen = 0.58 for males and r = 0.72 for women. Ilman et al. keeps said roentgen = 0.85 for men and you may roentgen = 0.83 for females. For every single study explained a definite BF% forecast design. It absolutely was in earlier times reported that, as well as ages and you will intercourse, other factors including nationality, ethnicity, and you may faith may also help boost the precision regarding a great BF% anticipate model [sixteen,19-23].