Assuming that the effect of sitting time on all-cause mortality risk is independent of physical activity, reducing sitting time plays an important role in active lifestyle promotion, which is an important aspect of premature mortality prevention worldwide.

In Brazil, physical inactivity has a major impact on NCDs and mortality, principally in the southeastern and central-west regions. Public policies and interventions promoting physical activity will significantly improve the health of the population.

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The aim of this study was to critically evaluate the quality of the models used in economic evaluations of screening strategies for cervical cancer prevention. We systematically searched multiple databases, selecting model-based full economic evaluations (cost-effectiveness analyses, cost-utility analyses, and cost-benefit analyses) of cervical cancer screening strategies. Two independent reviewers screened articles for relevance and performed data extraction. Methodological assessment of the quality of the models utilized formal checklists, and a qualitative narrative synthesis was performed. Thirty-eight articles were reviewed. The majority of the studies were conducted in high-income countries (82%, n=31). The Pap test was the most used screening strategy investigated, which was present in 86% (n=33) of the studies. Half of the studies (n=19) used a previously published Markov model. The deterministic sensitivity analysis was performed in 92% (n=35) of the studies. The mean number of properly reported checklist items was 9 out of the maximum possible 18. Items that were better reported included the statement of decision problem, the description of the strategies/comparators, the statement of time horizon, and information regarding the disease states. Compliance with some items of the checklist was poor. The Markov models for economic evaluation of screening strategies for cervical cancer varied in quality. The following points require improvement: 1) assessment of methodological, structural, heterogeneity, and parameter uncertainties; 2) model type and cycle length justification; 3) methods to account for heterogeneity; and 4) report of consistency evaluation (through calibration and validation methods).