Excerpts

The gender gap in this case was highly significant, with girls’ decline being 7.15 points larger than that of boys ( p < 0.01).

The ASR of YLD and DALY showed an increasing trend from 1990 to 2021 ( P < 0.01), but the ASR of mortality and YLL showed a decreasing trend ( P < 0.01).

In the multivariate model, living in severe poverty was only marginally significant ( p < 0.01) associated with having increased odds of having experienced a most unsafe abortion.

However, the null hypothesis is strongly rejected at the first difference for every variable, as indicated by the highly significant negative statistics (p < 0.01).

For Attica and Northern Greece, the difference was highly significant with a p value< 0.01.

In contrast, cognitive social capital was highly significant at p < 0.01.

Among males, an increasing trend was observed from 2013 to 2018 ( APC = 10.29%, P < 0.01), followed by a significant decrease starting in 2018 ( APC =−30.78%, P < 0.01).

The item “As regards the HPV vaccination, I was clear about the best choice for my daughter” was borderline significant ( r = .09; p = .01); mothers seemed more likely to let their daughter receive the HPV vaccination if they agreed with this statement.

Female students (83.5 %) had higher perception about TB as a public health problem than male (75.0 %), and the association between the knowledge about TB as public health problems and gender was highly significant (p < 0.01).

Education and net monthly income were highly significant predictors of HL ( p < 0.01) when other sociodemographic variables were controlled.

This represents the interaction between intervention and stage, which is highly significant ( p = 0.01) (OR = 0.68; 95%CI 0.52, 091).

For PHIs, before GB, there was a decreasing trend in the proportion of drug costs ( β 1 = −0.293, P < 0.01) and an increasing trend in the proportion of testing and inspection costs ( β 1 = 0.214, P < 0.05).

When the findings in the correlation matrix are examined, there is a positive, weakly significant relationship between trust in public health authorities and distrust in health systems ( r = 0.162, p < 0.01), and a negative, moderately significant relationship with health literacy ( r =-0.405, p < 0.01) is available.

Regarding sleep, the children’s CSHQ scores were better after the lockdown than before the lockdown, with a highly significant difference in CSHQ scores ( p < 0.01).

From this map we can interpret that under 5 child mortality of four states (Uttar Pradesh, Madhya Pradesh, Jharkhand, Karnataka) are moderately significant ( p < 0.01) that those are affected by the prevalence of under 5 child mortality of neighbouring states.

There was a significant trend in the survivor functions (i.e., probability of remaining free from diabetes) across the quartiles of greenspace ( p = 0.010) (Fig. 1b ); the probability of remaining free from diabetes amongst those in the greenest areas was 2.4% higher than those in the least green at age 80.

Multilevel linear regression analysis showed a trend towards higher anxiety scores with longer waited times (p = 0.012) among the inguinal hernia patients (Table 6 ).

However, after fully adjusting for confounding factors (Model 3), while cardiovascular mortality risk remained elevated (HR = 1.11, 95% CI: 1.00–1.23; P = 0.042), the overall risk of all-cause mortality associated with clinical obesity shifted to a marginally significant inverse relationship (HR = 0.93, 95% CI: 0.89–0.99; P = 0.013) compared to the no obesity group.

Those reporting a BI showed a trend towards greater declines on the SF-12 Physical health component summary scores than those without a BI (interaction effect: F (1, 5889) 6.05, p = .014: estimated marginal means at wave one and two: BI = 50.2 (SE .7): 47.0 (SE .8), Non-BI = 51.0 (SE .1), 50.2 (SE .1)).

When stratified into age groups, BMI showed a decreasing trend in both genders, areas, and all age groups across the studies, but most so among the youngest men in the FIN-D2D area (27.6 ± 4.2 vs. 27.0 ± 4.2 kg/m 2 , p = 0.015).

Having children showed a trend towards lower willingness (OR = 0.490, p = 0.015).

Also, there are no statistical differences in percent probability of dying among the four positive categories (excellent/very good/good/fair) (0.76%, 0.93%, 0.85%, 0.85%); but negative categories (poor/very poor) were more likely to die (1.21%, 1.39%) and when negative categories combined are compared to positive categories combined the difference in percent probability (0.86% vs 1.23%) is quite significant (p = 0.015).

Moreover, there was a significant association ( P = .010) between vitamin D status and sex, there being a higher prevalence of vitamin D insufficiency among the girls (77.5%) than boys (66.1%) Further analysis of the association between vitamin D status and BMI-for-age revealed a significant trend only for the boys (χ 2 = 5.958; P = .016) (Table 4 ).

A decreasing trend was observed for mortality (3.02%, p = 0.017).

While a similar trend was seen when using the continuous exposure measure, the difference did not reach statistical significance (Table 3 , p = 0.018 with threshold of 0.017 after Bonferroni’s adjustment).