Effects of Community-Wide Teen Pregnancy Prevention Initiatives on Local Teen Birth Rates in the United States: A Synthetic Control Approach.

The impact of community-wide teen pregnancy prevention initiatives (CWIs) on local U.S. birth rates among adolescents aged 15 to 19 years was examined using synthetic control methodology within a quasi-experimental design. CWIs were implemented in 10 U.S. communities from 2010 to 2015. Each initiative implemented evidence-based teen pregnancy prevention interventions at local organizations and enhanced best practices in adolescent reproductive health care at local health centers, while engaging diverse community sectors. The synthetic control method was used to estimate the impact of each CWI on overall and race- and ethnicity-specific teen births relative to rates in synthetic control communities. Additionally, we estimated the overall effect of CWIs across communities by pooling results from the 10 synthetic control case studies using the mean percentile rank. Pooled data across all 10 communities indicated an estimated average of 6.6 fewer births per 1000 teens per year overall during the initiative relative to each community's synthetic control (p = .001). By race and ethnicity, there were an estimated average of 6.4 fewer births per 1000 teens per year among Black teens (p = .03), 10.7 fewer births among Hispanic teens (p = .03), and 4.2 fewer births (p = .10) among White teens. Results from individual communities indicated an intervention effect on overall and/or race/ethnicity-specific teen birth rates in five communities. This study demonstrates the value of synthetic control methods in evaluating community-level outcomes of programmatic efforts. Findings indicate the CWIs had a positive impact on teen birth rates and have the potential to address racial and ethnic disparities in those rates.

Mortality Burden Due to Short-term Exposure to Fine Particulate Matter in Korea.

OBJECTIVES: Excess mortality associated with long-term exposure to fine particulate matter (PM2.5) has been documented. However, research on the disease burden following short-term exposure is scarce. We investigated the cause-specific mortality burden of short-term exposure to PM2.5 by considering the potential non-linear concentration-response relationship in Korea. METHODS: Daily cause-specific mortality rates and PM2.5 exposure levels from 2010 to 2019 were collected for 8 Korean cities and 9 provinces. A generalized additive mixed model was employed to estimate the non-linear relationship between PM2.5 exposure and cause-specific mortality levels. We assumed no detrimental health effects of PM2.5 concentrations below 15 µg/m3. Overall deaths attributable to short-term PM2.5 exposure were estimated by summing the daily numbers of excess deaths associated with ambient PM2.5 exposure. RESULTS: Of the 2 749 704 recorded deaths, 2 453 686 (89.2%) were non-accidental, 591 267 (21.5%) were cardiovascular, and 141 066 (5.1%) were respiratory in nature. A non-linear relationship was observed between all-cause mortality and exposure to PM2.5 at lag0, whereas linear associations were evident for cause-specific mortalities. Overall, 10 814 all-cause, 7855 non-accidental, 1642 cardiovascular, and 708 respiratory deaths were attributed to short-term exposure to PM2.5. The estimated number of all-cause excess deaths due to short-term PM2.5 exposure in 2019 was 1039 (95% confidence interval, 604 to 1472). CONCLUSIONS: Our findings indicate an association between short-term PM2.5 exposure and various mortality rates (all-cause, non-accidental, cardiovascular, and respiratory) in Korea over the period from 2010 to 2019. Consequently, action plans should be developed to reduce deaths attributable to short-term exposure to PM2.5.

The potential impact fraction of population weight reduction scenarios on non-communicable diseases in Belgium: application of the g-computation approach.

BACKGROUND: Overweight is a major risk factor for non-communicable diseases (NCDs) in Europe, affecting almost 60% of all adults. Tackling obesity is therefore a key long-term health challenge and is vital to reduce premature mortality from NCDs. Methodological challenges remain however, to provide actionable evidence on the potential health benefits of population weight reduction interventions. This study aims to use a g-computation approach to assess the impact of hypothetical weight reduction scenarios on NCDs in Belgium in a multi-exposure context. METHODS: Belgian health interview survey data (2008/2013/2018, n = 27 536) were linked to environmental data at the residential address. A g-computation approach was used to evaluate the potential impact fraction (PIF) of population weight reduction scenarios on four NCDs: diabetes, hypertension, cardiovascular disease (CVD), and musculoskeletal (MSK) disease. Four scenarios were considered: 1) a distribution shift where, for each individual with overweight, a counterfactual weight was drawn from the distribution of individuals with a "normal" BMI 2) a one-unit reduction of the BMI of individuals with overweight, 3) a modification of the BMI of individuals with overweight based on a weight loss of 10%, 4) a reduction of the waist circumference (WC) to half of the height among all people with a WC:height ratio greater than 0.5. Regression models were adjusted for socio-demographic, lifestyle, and environmental factors. RESULTS: The first scenario resulted in preventing a proportion of cases ranging from 32.3% for diabetes to 6% for MSK diseases. The second scenario prevented a proportion of cases ranging from 4.5% for diabetes to 0.8% for MSK diseases. The third scenario prevented a proportion of cases, ranging from 13.6% for diabetes to 2.4% for MSK diseases and the fourth scenario prevented a proportion of cases ranging from 36.4% for diabetes to 7.1% for MSK diseases. CONCLUSION: Implementing weight reduction scenarios among individuals with excess weight could lead to a substantial and statistically significant decrease in the prevalence of diabetes, hypertension, cardiovascular disease (CVD), and musculoskeletal (MSK) diseases in Belgium. The g-computation approach to assess PIF of interventions represents a straightforward approach for drawing causal inferences from observational data while providing useful information for policy makers.

Improving consistency in estimating future health burdens from environmental risk factors: Case study for ambient air pollution.

Future changes in exposure to risk factors should impact mortality rates and population. However, studies commonly use mortality rates and population projections developed exogenously to the health impact assessment model used to quantify future health burdens attributable to environmental risks that are therefore invariant to projected exposure levels. This impacts the robustness of many future health burden estimates for environmental risk factors. This work describes an alternative methodology that more consistently represents the interaction between risk factor exposure, population and mortality rates, using ambient particulate air pollution (PM2.5) as a case study. A demographic model is described that estimates future population based on projected births, mortality and migration. Mortality rates are disaggregated between the fraction due to PM2.5 exposure and other factors for a historic year, and projected independently. Accounting for feedbacks between future risk factor exposure and population and mortality rates can greatly affect estimated future attributable health burdens. The demographic model estimates much larger PM2.5-attributable health burdens with constant 2019 PM2.5 (∼10.8 million deaths in 2050) compared to a model using exogenous population and mortality rate projections (∼7.3 million), largely due to differences in mortality rate projection methods. Demographic model-projected PM2.5-attributable mortality can accumulate substantially over time. For example, ∼71 million more people are estimated to be alive in 2050 when WHO guidelines (5 µg m-3) are achieved compared to constant 2019 PM2.5 concentrations. Accounting for feedbacks is more important in applications with relatively high future PM2.5 concentrations, and relatively large changes in non-PM2.5 mortality rates.

Multi-disciplinary diabetic limb salvage programme in octogenarians with diabetic foot ulcers is not futile: An observational study with historical controls.

This study evaluated the effectiveness of a multi-disciplinary diabetic limb salvage programme in improving clinical outcomes and optimising healthcare utilisation in 406 patients aged ≥80 years with diabetic foot ulcers (DFUs), compared to 2392 younger patients enrolled from June 2020 to June 2021 and against 1716 historical controls using one-to-one propensity score matching. Results showed that elderly programme patients had lower odds of amputation-free survival (odds ratio: 0.64, 95% CI: 0.47, 0.88) and shorter cumulative length of stay (LOS) compared to younger programme patients (incidence rate ratio: 0.45, 95% CI: 0.29, 0.69). Compared to the matched controls, participating in the programme was associated with 5% higher probability of minor lower extremity amputation, reduced inpatient admissions and emergency visits, shorter LOS but increased specialist and primary care visits (all p-values <0.05). The findings suggest that the programme yielded favourable impacts on the clinical outcomes of patients aged≥80 years with DFUs. Further research is needed to develop specific interventions tailoring to the needs of the elderly population and to determine their effectiveness on patient outcomes while accounting for potential confounding factors.

Modeling chronic disease risk across equity factors using a population-based prediction model: the Chronic Disease Population Risk Tool (CDPoRT).

BACKGROUND: Predicting chronic disease incidence at a population level can help inform overall future chronic disease burden and opportunities for prevention. This study aimed to estimate the future burden of chronic disease in Ontario, Canada, using a population-level risk prediction algorithm and model interventions for equity-deserving groups who experience barriers to services and resources due to disadvantages and discrimination. METHODS: The validated Chronic Disease Population Risk Tool (CDPoRT) estimates the 10-year risk and incidence of major chronic diseases. CDPoRT was applied to data from the 2017/2018 Canadian Community Health Survey to predict baseline 10-year chronic disease estimates to 2027/2028 in the adult population of Ontario, Canada, and among equity-deserving groups. CDPoRT was used to model prevention scenarios of 2% and 5% risk reductions over 10 years targeting high-risk equity-deserving groups. RESULTS: Baseline chronic disease risk was highest among those with less than secondary school education (37.5%), severe food insecurity (19.5%), low income (21.2%) and extreme workplace stress (15.0%). CDPoRT predicted 1.42 million new chronic disease cases in Ontario from 2017/2018 to 2027/2028. Reducing chronic disease risk by 5% prevented 1500 cases among those with less than secondary school education, prevented 14 900 cases among those with low household income and prevented 2800 cases among food-insecure populations. Large reductions of 57 100 cases were found by applying a 5% risk reduction in individuals with quite a bit workplace stress. CONCLUSION: Considerable reduction in chronic disease cases was predicted across equity-defined scenarios, suggesting the need for prevention strategies that consider upstream determinants affecting chronic disease risk.

A novel approach to deriving the fine-scale daily NO2 dataset during 2005-2020 in China: Improving spatial resolution and temporal coverage to advance exposure assessment.

Surface NO2 pollution can result in serious health consequences such as cardiovascular disease, asthma, and premature mortality. Due to the extensive spatial variation in surface NO2, the spatial resolution of a NO2 dataset has a significant impact on the exposure and health impact assessment. There is currently no long-term, high-resolution, and publicly available NO2 dataset for China. To fill this gap, this study generated a NO2 dataset named RBE-DS-NO2 for China during 2005-2020 at 1 km and daily resolution. We employed the robust back-extrapolation via a data augmentation approach (RBE-DA) to ensure the predictive accuracy in back-extrapolation before 2013, and utilized an improved spatial downscaling technique (DS) to refine the spatial resolution from 10 km to 1 km. Back-extrapolation validation based on 2005-2012 observations from sites in Taiwan province yielded an R2 of 0.72 and RMSE of 10.7 µg/m3, while cross-validation across China during 2013-2020 showed an R2 of 0.73 and RMSE of 9.6 µg/m3. RBE-DS-NO2 better captured spatiotemporal variation of surface NO2 in China compared to the existing publicly available datasets. Exposure assessment using RBE-DS-NO2 show that the population living in non-attainment areas (NO2 ≥ 30 µg/m3) grew from 376 million in 2005 to 612 million in 2012, then declined to 404 million by 2020. Unlike this national trend, exposure levels in several major cities (e.g., Shanghai and Chengdu) continued to increase during 2012-2020, driven by population growth and urban migration. Furthermore, this study revealed that low-resolution dataset (i.e., the 10 km intermediate dataset before the downscaling) overestimated NO2 levels, due to the limited specificity of the low-resolution model in simulating the relationship between NO2 and the predictor variables. Such limited specificity likely biased previous long-term NO2 exposure and health impact studies employing low-resolution datasets. The RBE-DS-NO2 dataset enables robust long-term assessments of NO2 exposure and health impacts in China.

Simulating desegregation through affordable housing development: an environmental health impact assessment of Connecticut zoning law.

Residential segregation shapes access to health-promoting resources and drives health inequities in the United States. Connecticut's Section 8-30g incentivizes municipalities to develop a housing stock that is at least 10% affordable housing. We used this implicit target to project the impact of increasing affordable housing across all 169 Connecticut municipalities on all-cause mortality among low-income residents. We modeled six ambient environmental exposures: fine particulate matter (PM2.5), ozone (O3), nitrogen dioxide (NO2), summertime daily maximum heat index, greenness, and road traffic noise. We allocated new affordable housing to reach the 10% target in each town and simulated random movement of low-income households into new units using an inverse distance weighting penalty. We then quantified exposure changes and used established exposure-response functions to estimate deaths averted stratified by four ethnoracial groups: Asian, Hispanic or Latino, non-Hispanic Black, and non-Hispanic White. We quantified racialized segregation by computing a multi-group index of dissimilarity at baseline and post-simulation. Across 1,000 simulations, in one year (2019) we found on average 169 (95% CI: 84, 255) deaths averted from changes in greenness, 71 (95% CI: 49, 94) deaths averted from NO2, 9 (95% CI: 4, 14) deaths averted from noise, and marginal impacts from other exposures, with the highest rates of deaths averted observed among non-Hispanic Black and non-Hispanic White residents. Multi-group index of dissimilarity declined on average in all eight Connecticut counties post-simulation. Sensitivity analyses simulating a different population movement strategy and modeling a different year (2018) yielded consistent results. Strengthening desegregation policy may reduce deaths from environmental exposures among low-income residents. Further research should explore non-mortality impacts and additional mechanisms by which desegregation may advance health equity.

Impact of digital services on healthcare and social welfare: An umbrella review.

BACKGROUND: Digital services can be effective and cost-efficient options for treating non-communicable diseases, but generalizability is limited due to heterogeneous treatment effects. This umbrella review aims to evaluate the impact of digital services on population health, costs, and patient and healthcare professional satisfaction, and to identify facilitators and barriers to using digital services in healthcare and social welfare. METHODS: The protocol of the study was registered on the 4th of September 2022 to the International Prospective Register of Systematic Reviews, PROSPERO (CRD42022355635). The review was performed using the Centre for Reviews and Dissemination, Cochrane, Ovid Medline, Scopus, and Web of Science in June 2022. The methodological quality of the included reviews was assessed. The impact of digital services was categorized as no evidence, no dominance, and mixed and positive effect. Inductive content analysis was used to identify facilitators and barriers. RESULTS: A total of 66 studies were included in the review, 64 % of which were evaluated as high quality. Studies on the impact of digital services in social welfare were not identified. Sixty-five percent of reviews evaluated the impact of digital services on population health with mixed effects; 21 % were on costs with mixed effects; 27 % were on patient satisfaction with positive effects; and 7.6 % were on healthcare professionals' satisfaction with mixed effects. Various features, allocation, end-user support, organized services, and service development facilitated the use of digital services. Correspondingly, barriers were related to service limitations, digital competency, funding- and service strategies, resources and change management. CONCLUSIONS: Compared to usual care, digital services had a mixed impact on population health and costs with high satisfaction in patients. Mixed healthcare professionals' satisfaction was associated with the use of digital services, and it was less studied. To ensure successful implementation and sustainability of digital services, attention must be paid to address barriers and supporting facilitators at all levels.

Acceptability of self-administered antigen test for COVID-19 in the Philippines.

OBJECTIVES: In response to the Omicron surge in early 2022, the HTA Philippines evaluated the acceptability of Filipinos in using self-administered antigen tests (SAAgTs) as part of COVID-19 HTAs in the Philippines. METHODS: Scoping review from literature databases was initially conducted to identify preset codes in the use of SAAgT. Preset codes were used to establish the questions for focus group discussions (FGDs). Semi-structured questionnaires were created through Delphi technique. FGDs with four stakeholder groups (i.e., nine healthcare workers [HCWs], seven representatives of at-risk groups, six economic frontliners, and seven representatives of micro-small-medium-sized enterprises) were conducted. RESULTS: Discomfort in being a target of stigma and being prescribed an "illness identity" when suspected or confirmed COVID-19-positive, along with lack of confidence to perform self-test, caused hesitancy in self-testing among participants. The need for subsidies for test kits from the government or employers was emphasized to increase its accessibility. Having a designated access point and reporting system for SAAgT was highlighted to avoid nepotism (padrino system attributed to debt of gratitude), inequitable distribution, and lapses in reporting. A participatory approach to education was perceived as crucial to reduce any misconceptions associated with the use of SAAgT. CONCLUSIONS: All FGD groups expressed favorable reviews on the implementation of SAAgT because it can potentially reduce the burden of health facility-administered tests. These findings were considered by the HTA Council in the recommendation of SAAgT as part of the overarching national strategies for the diagnosis and screening of COVID-19.

Estimating the health impacts of exposure to Air pollutants and the evaluation of changes in their concentration using a linear model in Iran.

In big and industrial cities of developing countries, illness and mortality from long-term exposure to air pollutants have become a serious issue. This research was carried out in 2019-2020 to estimate the health impacts of PM10, NO2 and O3 pollutants by using AirQ+ and R statistical programming software in Arak, Isfahan, Tabriz, Shiraz, Karaj, and Mashhad. Mortality statistics, number of people in required age groups, and amount of pollutants were gathered respectively from different agencies like Statistics and Information Technology of the Ministry of Health, Statistical Center, and Department of Environment and by using Excel, the average 24-hour and 1-hour concentration and maximum 8-hour concentration for PM10, NO2 and O3 pollutants were gathered. We used linear mixed impacts model to account for the longitudinal observations and heterogeneity of the cities. The results of the study showed high number of deaths due to chronic bronchitis in adults, premature death of infants, and respiratory diseases in Mashhad. This research highlights the importance of estimation of health impacts from exposure to air pollutants on residents of the studied cities.

Health implications of urban tree canopy policy scenarios in Denver and Phoenix: A quantitative health impact assessment.

BACKGROUND: Urban tree canopy (UTC) goals are a popular policy to increase urban vegetation, support climate strategies, and encourage a healthy environment. Health studies related to UTC are needed across cities to support evidence-based decision-making. METHODS: We used a quantitative Health Impact Assessment (HIA) to model the annual number of premature deaths prevented, and the number of stroke and dementia cases, under UTC goals in Denver, Colorado, and Phoenix, Arizona, USA, using standing policy goals (20% and 25% UTC, respectively) and 50% ("half-way") attainment scenarios from current levels (16.5% and 13% UTC, respectively), using publicly accessible national datasets, and a proportional representation of UTC change to standardize across methodologies. We estimated UTC health impacts by relating UTC with scenario-based changes in the Normalized Difference Vegetation Index (NDVI) and considered health equity in UTC distributions and benefits. RESULTS: We projected that at 2020 populations, uniform 20% UTC attainment across Denver block groups would avert 200 (95% uncertainty interval: (UI) 100, 306) annual premature deaths among adults 18 and older, along with 4.1 (95% UI: 2.2, 6.7) annual cases of stroke (adults ≥35), and 2.6 (95% UI: 1.5, 4.1) cases of dementia (adults ≥65), with "halfway" attainment from current levels (16.5% UTC) capturing ∼64% of these benefits. In Phoenix, uniform 25% UTC would annually prevent 368 (95% UI: 181, 558) premature deaths, 8.7 (95% UI: 4.7, 13.9) cases of stroke, and 5,1 (95% UI: 2.9, 8.0) of dementia, with the "halfway" scenario (17% UTC) achieving ∼44% of these results. Both cities saw significantly different greenspace exposures and health outcomes by socioeconomic vulnerability. Denver had more spatially and socioeconomically heterogeneous projected health benefits than Phoenix. CONCLUSIONS: Implementing UTC goals can prevent excess mortality and chronic diseases among urban residents. UTC goals can be used as a health promotion and prevention tool.

Effectiveness of COVID-19 vaccine mandates in raising vaccination rates among the elderly and general population in Europe: Controlled interrupted time series analysis.

BACKGROUND: During the COVID-19 pandemic, three European countries (Austria, Greece, Italy) announced and/or implemented mandatory COVID-19 vaccination for high-risk groups in the general population. Besides the ethical justification for this policy, it is important to assess and quantify the effectiveness of the mandate in raising vaccination rates. METHODS: Controlled interrupted time series analysis of first-dose vaccination rates in the targeted age groups (Greece: ≥60 years; Italy: ≥50 years) relative to a control group (Greece: 50-59 years; Italy: 25-49 years) between week 35/2021 and week 50/2022. For Austria an uncontrolled analysis was performed, as the vaccine mandate targeted all adults ≥18 years. RESULTS: Announcement of mandatory vaccination substantially increased vaccination rates in the targeted age groups compared to control in both Greece (RR = 4.36, 95 % CI: 3.57-5.32) and Italy (RR = 2.90, 95 % CI: 2.37-3.56), an effect which persisted throughout the study period. There were 176,428 (95 % CI: 164,097-187,226) mandate-attributable first-dose vaccinations in Greece and 316,192 (95 % CI: 282,467-346,678) in Italy, most of which occurred before the mandate came into effect. In Austria no discernible increase in vaccination rates was observed after the announcement of mandatory vaccination. At the end of the study period, 9.5 % of ≥60 year-olds in Greece, 4.9 % of ≥50 year-olds in Italy and 13.8 % of ≥18 year-olds in Austria remained unvaccinated. CONCLUSIONS: In Greece and Italy - though not in Austria - simple announcement of a vaccine mandate rapidly increased COVID-19 vaccination rates in the targeted age groups, without fully closing the vaccination gap. Mandatory vaccination appears to effectively target complacency but not vaccine hesitancy, and its public health benefits need to be weighted against possible detrimental effects on confidence and trust.

Urban green spaces and behavioral and cognitive development in children: A health impact assessment of the Barcelona "Eixos Verds" Plan (Green Axis Plan).

BACKGROUND: Urban environments lack natural features, while nature exposure in cities has been associated with health benefits, including children's neurodevelopment. Through extensive street greening, Barcelona's Eixos Verds (Green Axis) Plan enhances safety, environment, and climate resilience. We aimed to assess the Eixos Verds Plan's potential impact on children's behavioral and cognitive development due to the increased green space expected under the Eixos Verds implementation. METHODS: We performed a quantitative health impact assessment for Barcelona children at census-tract level (n = 1068). We assessed the Eixos Verds Plan's impact by comparing baseline green space distribution with the proposed plan, translating it into percentage green area (%GA) and Normalized Difference Vegetation Index (NDVI). By combining these exposure metrics with child-specific risk estimates and population data, we estimated potential improvements in children's behavioral and cognitive development due to full Eixos Verds implementation. RESULTS: With the full Eixos Verds implementation, citywide, %GA increased by 6.9% (IQR: 6.4%; range: 0-23.1%) and NDVI by 0.065 (IQR: 0.083; range: 0.000-0.194). Child behavioral and cognitive development outcomes are expected to improve compared to the baseline. Based on NDVI increases, children's Total Difficulties and Hyperactivity/Inattention scores, based on the Strengths and Difficulties Questionnaire (SDQ), are projected to decrease by 5% (95% CI: 0-15%) and 6% (95% CI: 0-17%). Working Memory and Superior Working Memory scores are expected to increase by 4% and 5%, respectively, based on the computerized n-back test, while the Inattentiveness score could be reduced by 1%, based on the computerized attentional test (ANT). INTERPRETATION: Urban greening as planning tool can improve behavioral and cognitive development in city children. Methods and results of our study are applicable to many cities worldwide, and similar results for children of real-life urban greening interventions can be expected.

Increase in sick leave episodes from short-term fine particulate matter exposure: A case-crossover study in Stockholm, Sweden.

Air pollution's short-term effects on a wide range of health outcomes have been studied extensively, primarily focused on vulnerable groups (e.g., children and the elderly). However, the air pollution effects on the adult working population through sick leave have received little attention. This study aims to 1) estimate the associations between particulate matter ≤2.5 µm3 (PM2.5) and sick leave episodes and 2) calculate the attributable number of sick leave days and the consequential productivity loss in the City of Stockholm, Sweden. Individual level daily sick leave data was obtained from Statistics Sweden for the years 2011-2019. Daily average concentrations of PM2.5 were obtained from the main urban background monitoring station in Stockholm. A case-crossover study design was applied to estimate the association between short-term PM2.5 and onset of sick leave episodes. Conditional logistic regression was used to estimate the relative increase in odds of onset per 10 µg/m3 of PM2.5, adjusting for temperature, season, and pollen. A human capital method was applied to estimate the PM2.5 attributable productivity loss. In total, 1.5 million (M) individual sick leave occurrences were studied. The measured daily mean PM2.5 concentration was 4.2 µg/m3 (IQR 3.7 µg/m3). The odds of a sick leave episode was estimated to increase by 8.5% (95% CI: 7.8-9.3) per 10 µg/m3 average exposure 2-4 days before. Sub-group analysis showed that private sector and individuals 15-24 years old had a lower increase in odds of sick leave episodes in relation to PM2.5 exposure. In Stockholm, 4% of the sick leave episodes were attributable to PM2.5 exposure, corresponding to €17 M per year in productivity loss. Our study suggests a positive association between PM2.5 and sick leave episodes in a low exposure area.

Impact of a research-action on vaccination indicators in the state of Minas Gerais, Brazil / Impacto de uma pesquisa-ação nos indicadores vacinais em Minas Gerais

ABSTRACT OBJECTIVE Analyze the impact of the state research-action project on immunization indicators (vaccination coverage - VC, homogeneity of vaccination coverage - HVC, dropout rate - DR, and risk rating) before and after the intervention in municipalities and priority Regional Health Administrations/Regional Health Superintendencies (RHA/RHS). METHODS The state research-action project was a before-after community clinical trial conducted in 212 municipalities belonging to eight RHA/RHS in the state of Minas Gerais, Brazil. The study sample comprised RHA/RHS with a decreasing trend for routine vaccination coverage in children under one year from 2015 to 2020. This study used secondary VC and DR data from 10 immunobiologicals recommended for children younger than two years from January to December 2021 (pre-intervention period, prior to the state research-action project) and from January to December 2022 (post-intervention period). The categorical variables were presented in proportions, and initially, a comparison was made between those of DR, HVC, and the risk rating for the transmission of vaccine-preventable diseases, according to the two periods (2021 and 2022), using the McNemar test. RESULTS All immunization indicators increased after conducting the research-action project. In 2021, 80.66% of the state's municipalities had a risk rating for the transmission of vaccine-preventable diseases as "high and very high." In 2022, the value reduced to 68.40%. CONCLUSIONS Risk rating for the transmission of vaccine-preventable diseases is an important mechanism to assist managers in defining priorities. The state research-action project used a method that enabled the construction and execution of unique action plans for each municipality, directing the improvement of immunization indicators in the state.

RESUMO OBJETIVO Analisar o impacto do projeto estadual de pesquisa-ação nos indicadores de imunização (coberturas vacinais - CV, homogeneidade de cobertura vacinal - HCV, taxa de abandono - TA e classificação de risco) antes e após a intervenção em municípios e Gerências Regionais de Saúde/Superintendências Regionais de Saúde (GRS/SRS) prioritários. MÉTODOS O projeto estadual de pesquisa-ação foi um ensaio clínico comunitário, do tipo antes-depois, realizado em 212 municípios pertencentes a oito GRS/SRS do estado de Minas Gerais, Brasil. Compuseram a amostra do estudo as SRS/GRS com tendência decrescente para a cobertura vacinal de rotina em crianças menores de 1 ano, no período de 2015 a 2020. Neste estudo, foram utilizados dados secundários de CV e TA de 10 imunobiológicos recomendados para crianças menores de 2 anos, no período de janeiro a dezembro de 2021 (período pré-intervenção, anterior ao projeto estadual de pesquisa-ação) e de janeiro a dezembro de 2022 (período pós-intervenção). As variáveis categóricas foram apresentadas em proporções e, inicialmente, realizou-se a comparação entre as de TA, HCV e a classificação de risco para a transmissão de doenças imunopreveníveis, segundo os dois períodos (2021 e 2022), utilizando-se o teste McNemar. RESULTADOS Observou-se um aumento de todos os indicadores de imunização após a realização do projeto de pesquisa-ação. No ano de 2021, 80,66% dos municípios do estado tiveram a classificação de risco para transmissão de doenças imunopreveníveis como "alto e muito alto risco". Em 2022, o valor foi reduzido para 68,40%. CONCLUSÕES A classificação de risco para transmissão de doenças imunopreveníveis é um mecanismo importante para auxiliar os gestores na definição de prioridades. O projeto estadual de pesquisa-ação empregou um método que possibilitou a construção e a execução de planos de ação singulares a cada município, direcionando a melhoria dos indicadores de imunização no estado.

Avaliação do impacto da implantação do novo sistema de informações da atenção primária à saúde nos registros de atendimentos e visitas domiciliares no Brasil / Evaluation of the impact of the implementation of the new primary health care information system on records of patient care and home visits in Brazil / Evaluación del impacto de la implantación del nuevo sistema de informaciones de la atención primaria de salud en los registros de atención y visitas domiciliarias en Brasil

Resumo: A substituição do Sistema de Informação da Atenção Básica (SIAB, 1998-2015), a partir de janeiro de 2016, pelo novo Sistema de Informação em Saúde para a Atenção Básica (SISAB) determinou novas formas de coleta, processamento e uso das informações, com possível impacto nos registros das atividades desenvolvidas na atenção primária à saúde no Brasil. O objetivo deste estudo foi avaliar o impacto da implantação do novo sistema de informação sobre registros de atendimentos de médicos e enfermeiros, e de visitas domiciliares de agentes comunitários de saúde (ACS) brasileiros entre 2007 e 2019. Para tal, utilizou-se uma abordagem bayesiana de modelo estrutural para séries temporais, com base em uma regressão difusa de espaço-estado. Ao longo do período de 2016 a 2019, foram registrados 463,47 milhões de atendimentos médicos, 210,61 milhões de atendimentos de enfermagem e 1,28 bilhão de visitas de ACS. Seguindo a tendência registrada antes da implantação, seriam esperados 598,86 milhões, 430,46 milhões e 1,5 bilhão de atendimentos de médicos, enfermeiros e visitas de ACS, respectivamente. Em termos relativos, houve um decréscimo de 25% nos atendimentos médicos, 51% nos atendimentos de enfermagem e 15% nas visitas de ACS quando comparado com o valor esperado pelo método bayesiano. O impacto negativo no registro de atendimentos e de visitas domiciliares identificado neste estudo, seja por dificuldade de adaptação ao novo sistema, seja por diminuição de registros indevidos, merece ser alvo de investigação para que se possa, de forma planejada, compreender e superar o desafio da melhoria do sistema de informação da atenção primária.

Abstract: The replacement of the Primary Care Information System (SIAB, 1998-2015), as of January 2016, by the new Health Information System for Primary Care (SISAB) determined new forms of collecting, processing, and using information, with a possible impact on the records of activities carried out in primary health care in Brazil. This study aimed to evaluate the implementation impact of the new information system on records of physicians' and nurses' patient care and home visits of community health workers (CHW) in Brazil from 2007 to 2019. To this end, a Bayesian structural time-series model approach was used, based on a diffuse state-space regression. From 2016 to 2019, 463.47 million physician care, 210.61 million nursing care, and 1.28 billion CHW visits were recorded. Following the trend recorded before the implementation, 598.86 million, 430.46 million, and 1.5 billion physician and nursing appointments and CHW visits would be expected, respectively. In relative terms, there was a decrease of 25% in physician care, 51% in nursing care, and 15% in CHW visits when compared to the value expected by the Bayesian method. The negative impact on the records of patient care and home visits identified in this study, whether due to difficulties in adapting to the new system or a reduction in improper records, must be investigated so that the challenge of improving the primary care information system can be understood and overcome in a planned way.

Resumen: La sustitución del Sistema de Información de la Atención Básica (SIAB, 1998-2015), desde enero de 2016, por el nuevo Sistema de Información en Salud para la Atención Básica (SISAB) estableció nuevas maneras para recolectar, procesar y utilizar las informaciones, con posibles impactos en los registros de las actividades desarrolladas en la atención primaria de salud en Brasil. El objetivo de este estudio fue evaluar el impacto de la implantación del nuevo sistema de información sobre los registros de atención de médicos y enfermeros y de visitas domiciliarias de agentes comunitarios de salud (ACS) en Brasil entre 2007 y 2019. Para eso, se utilizó un enfoque bayesiano de modelo estructural para series temporales basadas en una regresión difusa de espacio de estado. Entre los años 2016 y 2019, se registraron 463,47 millones de consultas médicas, 210,61 millones de consultas de enfermería y 1,28 mil millones de visitas de ACS. Siguiendo la tendencia registrada antes de la implantación, se esperarían 598,86 millones, 430,46 millones y 1,5 mil millones de consultas médicas y de enfermería y visitas de ACS respectivamente. En términos relativos, hubo una disminución del 25% en las consultas médicas, del 51% en las consultas de enfermería y del 15% en las visitas de ACS en comparación con el valor esperado por el método bayesiano. El impacto negativo en el registro de consultas y visitas domiciliarias identificado en este estudio, ya sea por dificultades en la adaptación al nuevo sistema o por la disminución de los registros indebidos, merece ser objeto de investigación para que se pueda, de manera planificada, comprender y superar el desafío continuo de mejorar el sistema de información de la atención primaria.

Evaluating Racial/Ethnic Equity in Planning-Related U.S. Health Impact Assessments Involving Parks and Greenspaces: A Review.

Problem research strategy and findings: Health impact assessment (HIA) reports are used by government agencies, other organizations, and stakeholders to evaluate potential health effects of plans/policies/projects. HIAs have the potential to promote anti-racist practices. We developed and used the Tool for the Racial/Ethnic Equity Evaluation of Health Impact Assessments (TREE-HIA) to score 50 U.S. HIA reports on planning-related projects/plans involving parks and greenspaces (2005-2020). More recent and more comprehensive HIA reports addressed racial/ethnic equity to a greater degree (e.g., median TREE-HIA scores: -1.3 in 2009-2012, 4.0 in 2017-2020, where higher scores indicate greater racial/equity considerations). Overall, HIA reports addressed racial/ethnic equity to a lesser degree than expected given the principal tenet of equity guiding HIAs and urban planning alike (42% had negative TREE-HIA scores indicating inadequate racial/ethnic equity consideration). However, the limited number and types of HIAs included in this study may affect generalization to all HIAs. Takeaway for practice: HIAs incorporating racial/ethnic equity comprehensively throughout the HIA process will better enable urban planners, HIA practitioners, decision makers, and communities of color to work together to combat racist planning practices through the shared goals of addressing health disparities and equity. TREE-HIA provides professionals and researchers with a brief tool that can be used/adapted to guide and evaluate future HIAs for racial/ethnic equity considerations.

Evaluating Person-Centred Integrated Care to People with Complex Chronic Conditions: Early Implementation Results of the ProPCC Programme.

Introduction: The evaluation of integrated care programmes for high-need high-cost older people is a challenge. We aim to share the early implementation results of the ProPCC programme in the North-Barcelona metropolitan area, in Catalonia, Spain. Methods: We analysed the intervention with retrospective data from May 2018 to December 2021 by describing the cohort complexity and by showing its 6-months pre-post impact on time spent at home and resources used: primary care visits, emergency department visits, hospital admissions and hospital stay. Findings: 264 cases were included (91% at home; 9% in nursing homes). 6-month pre vs. 6-months post results were (mean, p-value): primary care visits 8.2 vs. 11.5 (p < 0.05); emergency department visits 1.4 vs. 0.9 (p < 0.05); hospital admissions 0.7 vs. 0.5 (p < 0.05); hospital stay 12.8 vs. 7.9 days (p < 0.05). Time spent at home was 169.2 vs.174.2 days (p < 0.05). Conclusion: Early implementation of the ProPCC programme results in an increase in time spent at home (up to 3%) and significant reductions in emergency department attendance (-37.2%) and hospital stays (-38.3%). The increased use of primary care resources is compensated by the hospital resources savings, with a result in the average total cost of -46.3%.

Estimated effect of age of marriage on utilisation of India's Integrated Child Development Service programme.

BACKGROUND: Age of marriage among women is considered an important indicator of their readiness for familial integration and parenting. This study estimated the effect of age of marriage of young mothers (aged 15-24 years) on utilisation of various services for their children, provided under the Integrated Child Development Service (ICDS) programme in India. METHODS: Data from the nationally representative 2019-2021 National Family Health Survey of India were analysed. Mothers' age of menarche was used as an instrumental variable to isolate the effect of age of marriage on whether their children received (1) food, (2) health check-up, (3) immunisation, (4) early childhood care or preschooling or (5) weight measurement services from ICDS. RESULTS: Nationally, 67.9% (95% CI 67.6%, 68.3%) of children received food (sample: 60 578), 61.8% (95% CI 61.4%, 62.1%) received a health check-up (sample: 60 316), 60.0% (95% CI 59.6%, 60.4%) received immunisation services (sample: 60 537), 52.0% (95% CI 51.6%, 52.4%) received early childhood care or preschooling (sample: 60 458) and 62.9% (95% CI 62.5%, 63.3%) received weight measurement services (sample: 60 278). Findings from instrumental variable analysis suggest that a 1-year increase in age of marriage could yield a 9 percentage point increase (95% CI 4%-13%; p<0.001) in utilisation of immunisation services. Although postponement of marriage positively affected utilisation of each of the other four ICDS components, these effects were not statistically significant. CONCLUSION: Postponing age of marriage among young women is an effective intervention for promoting uptake of child immunisation services. Our findings support the Government of India's 2021 Bill to raise legal age of marriage of women.