In this case, the additional estimated effect of country-level PM2.5 (defined as in Equation 1) on center-level prevalence was estimated as –0.172 955% CI: –0.306, –0.038) (Table 2).
Randomization took place on healthcare center level.
The higher the ICC, the greater the influence of the center level on the quality-of-care indicator.
While respondents agreed with this requirement in principle, they noted that it strained facility capacity, particularly in the evening when only one or two providers are on duty at the health center level.
Field assessment at provincial, operational district and health center level, based on an adapted version of the GAVI draft tools for the assessment of immunization services, was done.
Those who attend the training sessions do not replicate the trainings at the health center level; they complain on not receiving additional benefits (per diem) for participating on the sessions.
Benefits cover low risk events treated at the health center level, including medicines on the national Essential Medicines List (EML), all preventive and curative services, prenatal care, delivery care, laboratory exams, and referral transport to district hospitals.
For PM2.5 and NO2, we also added individual cross-level interaction terms to fully adjusted random intercept/random slope models to investigate potential modifying effects of country-level variables on the center-level effects (slopes) of air pollutants.
The unadjusted correlation for O3 across all centers was strongly positive with PM2.5 and moderately strongly negative with asthma prevalence; in the main analysis however, the influence of O3 on the center-level estimates for PM2.5 was small.
We found no evidence of any modifying effect on the center-level slope by GNI per capita (p = 0.440) or country-level altitude (p = 0.664), latitude (p = 0.971), prevalence of current rhinoconjunctivitis (p = 0.224), log PM2.5 (p = 0.489), or log NO2 (p = 0.280).
However, we found no evidence of any modifying effects on the center-level slope of other country-level variables including GNI per capita (p = 0.944), altitude (p = 0.751), latitude (p = 0.302), prevalence of rhinoconjunctivitis (p = 0.541), log PM2.5 (p = 0.199), or log NO2 (p = 0.563).
