Each WHtR cutoff was a highly significant predictor ( P < 0.0001) with the inclusion of constructs for race, smoking, age, and sex.
Excerpts
The stepwise backward logistic regression procedure revealed a highly significant model (model χ 2 = 720, 25 df, p < 0.0001) with the factor COUNTRY as the most significant factor (Table 3 ).
The inter annual total case count difference was highly significant (F 11,132 : 36.305, p < 0001).
All of the smoking behavior groups exhibited a positive trend in BMI (trend test p < 0.0001) (Table 3 ).
When cross-classifying condom use and frequency of condom use (see Table 4 ), a highly significant association was found between the two responses (P < 0.0001).
This trend was highly significant (P<0.0001), and also significant at each schedule point (Table 2 ).
The apparent 10.2/7.6 mmHg difference between inpatients and outpatients was only slightly reduced to 8.0/5.1 mmHg after adjustment for baseline and remained highly significant (p < 0.0001/p < 0.0001) even after correction for cluster effects.
After adjusting for potential confounders (multivariable Poisson regression analysis), the positive correlation between WDD and FGPD remained highly significant, β:0.15(95%CI 0.13–0.16, P < 0.0001), Furthermore, the negative correlation between WDD and attaining tertiary education,β:0.05(95% CI:-0.095- -0.0005) remained significant after running a multivariable analysis (Table 2 ).
The test for trend across the time points showed that this increase was highly significant (p < 0.0001).
The final model had a highly significant (p = 0.0002) likelihood.
Results Participants characteristics The PIR exhibited a highly significant correlation with the risk of DR ( P = 0.0002).
With increasing numbers of substances, a positive trend was observed in high-fat food intake (p = 0.0003).
1 ; the proportion of urban cases declined over the years, which was also found to be highly significant (Cochrane-Armitage x 2 = 123.064, df = 1, p < 0.0005).
These differences were highly significant (paired t-test, p < 0.0005 for both comparisons).
Statistical testing showed highly significant differences between all four profiles ( p < 0.0009), regardless of building period.
The division displayed a highly significant association with care-seeking behavior across all three study periods ( p < 0.001), emphasizing substantial regional differences in healthcare-seeking practices.
In cases where the value exceeded 11.35, the significance was considered more robust ( p < 0.01), and above 16.27, the association between the cluster and the terms was highly significant ( p < 0.001).
Although all time points demonstrated highly significant statistical differences between classes ( p < 0.001), the gap between Class 1 and Class 2 narrowed over time, with their difference decreasing from 1.25 points at T1 to 0.43 points by T4, while Class 3 remained distinctly lower throughout all time points (Fig. 3 ).
Furthermore, women predominate in all academic years, from the first to the seventh, with highly significant differences ( p < 0.001) in each yearly comparison.
The intervention group demonstrated a highly significant improvement in their mean scores of MHL at the end of day three of the workshop (mean difference 19.08, 95% CI 17 to 21.16, Cohen’s d = 2.63; p < 0.001) and also in the second post intervention assessment after 3 months (mean difference 16.61, 95% CI 13.96 to 19.26, Cohen’s d = 1.86; p < 001) (Table 3 ).
The difference in paternal age between non-Down syndrome and Down syndrome babies was highly significant in both samples: t = 12.94 (P < 0.001) in California and t = 5.04 (P < 0.001) in the Czech Republic.
Furthermore, there was a significant trend in the categorical age group analysis (χ2/F = 234.953, p < 0.001).
Previous research in Bangladesh found a highly significant association ( p < 0.001) between tobacco use, alcohol intake, added salt intake, physical inactivity, and health profession categories, accentuating a close link.
According to the Cochran-Armitage trend test, the incidence of psychogenic AEFIs showed a decreasing trend from 2020 to 2023, with statistical significance (Z=-5.427, P < 0.001).
Regarding age distribution, the number of psychogenic AEFI cases in the age groups ≤ 6, 7–17, and ≥ 18 years were 20, 61, and 340, respectively, corresponding to a proportion rate of 0.02%(95% CI: 0.01–0.03), 0.07%(95% CI: 0.05–0.09), and 0.38%(95% CI: 0.34–0.42), respectively, showing an increasing trend with age ( P < 0.001).