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      The Brazilian National Oral Health Policy and oral cancer mortality trends: An autoregressive integrated moving average (ARIMA) model

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          Abstract

          Objective

          This study analyzes the effect of the Brazilian National Oral Health Policy (NOHP) on oral cancer mortality rates (OCMR).

          Method

          This is an ecological study with secondary oral cancer death data, using interrupted time series analysis (ARIMA, Autoregressive Integrated Moving Average). Annual death data were collected from the Mortality Information System (1996–2019). The outcome was the OCMR, standardized by gender and age We considered the NOHP, categorized as “0” (before its implementation), from 1996 to 2004, and “1 to 15”, from 2005 to 2019. ARIMA modeling was carried out for temporal analysis, and regression coefficient estimation (RC).

          Results

          The Brazilian NOHP implementation was associated with an increase in OCMR in the North region (CR = 0.16; p = 0.022) and with a decrease in the Southeast region (CR = -0.04; p<0.001), but did not affect the other macro-regions nor Brazil. The forecast models estimated an increase in OCMR for the North, and Northeast, a decrease for the Southeast, and stability for the South and Brazil.

          Conclusion

          The Brazilian NOHP is not being effective in reducing the OCMR. The trends behaved differently in the Brazilian territory, highlighting health inequities. We recommend that the NOHP strengthen the oral health care network, incorporating oral cancer as a notifiable disease, adopting strategies for prevention, screening, and providing opportunities for early treatment of the disease.

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          Most cited references31

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          Interrupted time series regression for the evaluation of public health interventions: a tutorial

          Abstract Interrupted time series (ITS) analysis is a valuable study design for evaluating the effectiveness of population-level health interventions that have been implemented at a clearly defined point in time. It is increasingly being used to evaluate the effectiveness of interventions ranging from clinical therapy to national public health legislation. Whereas the design shares many properties of regression-based approaches in other epidemiological studies, there are a range of unique features of time series data that require additional methodological considerations. In this tutorial we use a worked example to demonstrate a robust approach to ITS analysis using segmented regression. We begin by describing the design and considering when ITS is an appropriate design choice. We then discuss the essential, yet often omitted, step of proposing the impact model a priori. Subsequently, we demonstrate the approach to statistical analysis including the main segmented regression model. Finally we describe the main methodological issues associated with ITS analysis: over-dispersion of time series data, autocorrelation, adjusting for seasonal trends and controlling for time-varying confounders, and we also outline some of the more complex design adaptations that can be used to strengthen the basic ITS design.
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            Revisiting the Behavioral Model and Access to Medical Care: Does it Matter?

            The Behavioral Model of Health Services Use was initially developed over 25 years ago. In the interim it has been subject to considerable application, reprobation, and alteration. I review its development and assess its continued relevance.
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              Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life Years for 29 Cancer Groups From 2010 to 2019 : A Systematic Analysis for the Global Burden of Disease Study 2019

              Question What was the burden of cancer globally and across Sociodemographic Index (SDI) groupings in 2019, and how has incidence, morbidity, and mortality changed since 2010? Findings In this systematic analysis, there were 23.6 million new global cancer cases in 2019 (17.2 million when excluding those with nonmelanoma skin cancer), 10.0 million cancer deaths, and an estimated 250 million disability-adjusted life years estimated to be due to cancer; since 2010, these represent increases of 26.3%, 20.9%, and 16.0%, respectively. Absolute cancer burden increased in all SDI quintiles since 2010, but the largest percentage increases occurred in the low and low-middle SDI quintiles. Meanings The study results suggest that increased cancer prevention and control efforts are needed to equitably address the evolving and increasing burden of cancer across the SDI spectrum. Importance The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. Objective To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. Evidence Review The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs). Findings In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. Conclusions and Relevance The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world. The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 examines cancer burden and trends globally for 204 countries and territories and by Socio-demographic Index quintiles from 2010 to 2019.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: Writing – review & editing
                Role: Formal analysisRole: InvestigationRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: Writing – review & editing
                Role: Data curationRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                21 September 2023
                2023
                : 18
                : 9
                : e0291609
                Affiliations
                [1 ] Public Health Department, Federal University of Maranhão, São Luís, Maranhão, Brazil
                [2 ] Department of Electrical Engineering, Federal University of Maranhão, São Luís, Maranhão, Brazil
                [3 ] Duke Global Health Institute, Duke University, Durham, North Carolina, United States of America
                Lithuanian University of Health Sciences, LITHUANIA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0001-5364-0384
                Article
                PONE-D-22-26030
                10.1371/journal.pone.0291609
                10513197
                37733703
                1f242105-092e-4d19-9e79-b6f5a928e665
                © 2023 Costa et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 19 September 2022
                : 1 September 2023
                Page count
                Figures: 2, Tables: 3, Pages: 12
                Funding
                Funded by: Brazilian Coordination for the Improvement of Higher Education Personnel
                Award ID: finance code 001
                Funded by: National Council for Scientific and Technological Development
                Award ID: 306592/2018-5 and 308917/2021-9
                Funded by: Federal University of Maranhão
                Funded by: Maranhão Research and Scientific and Technological Development Foundation
                This work was supported by the Maranhão Research and Scientific and Technological Development Foundation (FAPEMA); the Brazilian Coordination for the Improvement of Higher Education Personnel (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior–CAPES: finance code 001); the National Council for Scientific and Technological Development (Conselho Nacional de Desenvolvimento Científico e Tecnológico–CNPq: research productivity grant – processes 306592/2018-5 and 308917/2021-9); the Federal University of Maranhão (Universidade Federal do Maranhão–UFMA). However, the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                People and places
                Geographical locations
                South America
                Brazil
                Medicine and Health Sciences
                Oral Medicine
                Oral Health
                Medicine and Health Sciences
                Oncology
                Cancers and Neoplasms
                Engineering and Technology
                Signal Processing
                Autocorrelation
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Autocorrelation
                Physical Sciences
                Mathematics
                Statistics
                Statistical Methods
                Autocorrelation
                Medicine and Health Sciences
                Oncology
                Cancer Treatment
                Medicine and Health Sciences
                Health Care
                Health Care Policy
                Biology and Life Sciences
                Population Biology
                Population Metrics
                Death Rates
                Medicine and Health Sciences
                Medical Conditions
                Oral Diseases
                Medicine and Health Sciences
                Oral Medicine
                Oral Diseases
                Custom metadata
                The time-dependent variable for this study was the oral cancer mortality rate, standardized by gender and age using the direct standardization technique. Oral Cancer deaths were collected and classified according to the International Classification of Diseases (ICD-10), considering codes C-00 to C-10, from 1996-2019. The number of OC deaths was collected from the Mortality Information System (acronym in Portuguese, SIM), openly available at https://datasus.saude.gov.br/transferencia-de-arquivos/. The denominator was the total population obtained from the Brazilian Institute of Geography and Statistics (acronym in Portuguese, IBGE), considering the 1991, 2000, and 2010 censuses, and inter-census projections. The data referring to the Brazilian population were gathered from the DATASUS, available at https://datasus.saude.gov.br/populacao-residente. For this study, we calculated the oral cancer mortality rates for every 100 thousand inhabitants. This study was based on secondary data from Brazilian public domain databases, with no need to be approved by an Ethics Committee.

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