Several linear regression investigation was initially made use of, followed by a study of the possibility of a great nonlinear relationships current by together with quadratic and you may cubic versions. Modified [Roentgen.sup.2] and you may fundamental mistake away from estimate (SEE) thinking were used examine this new abilities of predictive model off BF%.
All account off p was in fact a couple of-sided and you can p below 0.05 is considered mathematically significant. All the analyses was performed using STATA app variation twelve.0 (STATA Corp, College or university Channel, Colorado, USA) and you can SPSS type 17.0 (SPSS Inc., il, 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).
Inside our investigation, HWDI, a fairly the newest carrying excess fat measurement signal, are located to own an inverse relationship with BF% in everyone
Shape 1 suggests the connection ranging from average Bmi and you will age. It absolutely was found that, regarding ages of 18 so you can 39 decades, new indicate Bmi expands given that ages develops however,, just after interacting with 60 years of age, new mean Body mass index decrease once the years expands (see Figure step 1(a)). The reverse can be acquired on the relationships ranging from mean HWDI and you will 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).
Statistically, an inverse dating anywhere between HWDI and you can BF% was receive as the HWDI improved when you are BF% well worth notably diminished
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 sugar daddy in Missouri 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).
Yet not, Pearson’s relationship coefficients were discovered to be low (r = -0.20 for males and you will r = -0.47 for women) when compared to earlier degree one to put almost every other being obese analysis systems having BF% [16,18, 19]. From inside the 1996, Gallagher et al. read the connection ranging from Body mass index and you will BF% and reported viewpoints regarding roentgen = 0.58 for men and roentgen = 0.72 for females. Ilman et al. enjoys claimed roentgen = 0.85 for males and roentgen = 0.83 for ladies. For each study described a definite BF% forecast design. It actually was previously stated that, along with ages and you may intercourse, other variables such nationality, ethnicity, and you can religion also may help increase the accuracy out-of a good BF% prediction design [16,19-23].