Nivel de prevención de seguridad ciudadana en percepción del poblador del Distrito de Huacho, 2016

El propósito del trabajo es contribuir en la búsqueda de alternativas efectivas desde la gestión multisectorial para la prevención y lucha de la inseguridad ciudadana que resulten validas en la toma de decisiones acertadas de la política de salud pública a nivel del distrito de Huacho, formulando para ello: ¿Cuál es el nivel de prevención de seguridad ciudadana que percibe la población del distrito de Huacho 2016?, objetivo general: Determinar el nivel de prevención de seguridad ciudadana que percibe la población y como específicos describir el nivel de Servicios de Prevención situacional, servicio de prevención social y comunitaria. El estudio es de tipo descriptivo - transversal, la muestra estuvo constituida por 200 pobladores mayores de 18 años del distrito de Huacho. La técnica de recolección fue la encuesta, el instrumento un cuestionario de prevención previamente validado, para el análisis de los datos se aplicó la estadística descriptiva, haciendo uso del programa SPSS v.23. Respecto al nivel de prevención de seguridad ciudadana se encuentra que la población tiene una percepción de nivel medio de prevención con un 51 % sin evidenciar una diferencia significativa entre el nivel bajo y alto con un 25% y 24% respectivamente.Trabajo de investigació

Intracranial Arterial Calcification Relates to Long-Term Risk of Recurrent Stroke and Post-stroke Mortality

Background: Intracranial arterial calcification (IAC) is highly prevalent in ischemic stroke patients. However, data on the association of IAC with stroke recurrence and mortality remains limited. We examined the effect of IAC on the long-term recurrence of stroke and the risk of post-stroke mortality. Methods: Using a prospective stroke registry, we recruited 694 patients (mean age 71.6 ± 12.4; male sex 50.3%) since December 2004. IAC was visualized using the computed tomography exam that was made at hospital admission and was quantified with the Agatston method. All patients were regularly followed up till July 2016. The impacts of IAC on stroke recurrence and mortality were assessed using Cox-regression models with adjustments for age, sex, and relevant cardiovascular risk factors. Results: During a median follow-up period of 8.8 years, 156 patients (22.5%) suffered a recurrent stroke and 84 died (12.1%). We found that a higher IAC Agatston score related to a higher risk of stroke recurrence (HR per 1-SD increase in IAC: 1.30; 95% CI, 1.08–1.56, p = 0.005) and a higher risk of post-stroke mortality (HR per 1-SD increase, 1.44; 95% CI, 1.06–1.96, p = 0.019). After investigating etiology-specific risks of stroke-recurrence, we found that a higher IAC Agatston score specifically associated with small-vessel occlusive stroke. Conclusions: IAC is a strong risk factor for recurrent stroke and post-stroke mortality. Among stroke subtypes, IAC relates to higher risk of stroke recurrence among patients with small-vessel disease, which indicates chronic calcification detected in large cerebral arteries may have potential effects on the cerebrovascular beds extending to small vessels

Angiotensin-(1-7) prevents lipopolysaccharide-induced autophagy via the Mas receptor in skeletal muscle

Skeletal muscle atrophy, which occurs in lipopolysaccharide (LPS)-induced sepsis, causes a severe muscle function reduction. The increased autophagy contributes to sepsis-induced skeletal muscle atrophy in a model of LPS injection, increasing LC3II/LC3I ratio, autophagy flux, and autophagosomes. Angiotensin-(1-7) (Ang-(1-7)) has anti-atrophic effects via the Mas receptor in skeletal muscle. However, the impact of Ang-(1-7) on LPS-induced autophagy is unknown. In this study, we determined the effect of Ang-(1-7) on sepsis-induced muscle autophagy. C57BL6 wild-type (WT) mice and mice lacking the Mas receptor (KO Mas) were injected with LPS together with the systemic administration of Ang-(1-7) to determine autophagy in skeletal muscle. We also evaluated autophagy and p38 and c-Jun N-terminal kinase (JNK)activation. Our results show that Ang-(1-7) prevents LPS-induced autophagy in the diaphragm, tibialis anterior, and gastrocnemius of WT mice, which is demonstrated by a decrease in the LC3II/LC3I ratio and mRNA levels of lc3b and ctsl. This effect was lost in KO Mas mice, suggesting the role of the Mas receptor. The results in C2C12 cells show that Ang-(1-7) reduces several LPS-dependent effects, such as autophagy (LC3II/LC3I ratio, autophagic flux, and autophagosomes), activation of p38 and JNK, B-cell lymphoma-2 (BCL2) phosphorylation, and disassembly of the Beclin1/BCL2 complex. In conclusion, Ang-(1-7)/Mas receptor reduces LPS-induced autophagy in skeletal muscle. In vitro assays indicate that Ang-(1-7) prevents LPS-induced autophagy and modifies the MAPK signaling and the disassembly of a complex involved at the beginning of autophagy

High white matter hyperintensity burden in strategic white matter tracts relates to worse global cognitive performance in community-dwelling individuals

BACKGROUND: White matter hyperintensities (WMH) are associated with cognitive impairment. The impact of WMH on cognitive domains (e.g. processing speed, executive functioning) depends on location. We determined whether the relevance of WMH location also applies to global cognitive functioning by testing if WMH in strategic white matter tracts are associated with global cognitive functioning independent of total WMH burden. METHODS: We included 830 community-dwelling individuals. WMH volume within two a priori specified strategic white matter tracts (forceps minor and anterior thalamic radiation) were entered in a linear regression model with the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) as outcome variables and corrected for total WMH volume and other MRI markers for vascular injury and neurodegenerations (i.e. brain parenchymal fraction, and the presence of lacunes and microbleeds). RESULTS: WMH in the forceps minor and left anterior thalamic radiation inversely correlated with MoCA, and WMH in the forceps minor inversely correlated with MMSE, independent of total WMH volume and other MRI markers. CONCLUSION: The impact of WMH on global cognitive functioning depends on location. Whether this reflects accumulated impairment in isolated cognitive domains or disruption of a network that is crucially involved in global cognitive performance remains to be determined

Clinical associations and prognostic value of MRI-visible perivascular spaces in patients with ischemic stroke or TIA: a pooled analysis

BACKGROUND AND OBJECTIVES: Visible perivascular spaces are an MRI marker of cerebral small vessel disease and might predict future stroke. However, results from existing studies vary. We aimed to clarify this through a large collaborative multicenter analysis. METHODS: We pooled individual patient data from a consortium of prospective cohort studies. Participants had recent ischemic stroke or transient ischemic attack (TIA), underwent baseline MRI, and were followed up for ischemic stroke and symptomatic intracranial hemorrhage (ICH). Perivascular spaces in the basal ganglia (BGPVS) and perivascular spaces in the centrum semiovale (CSOPVS) were rated locally using a validated visual scale. We investigated clinical and radiologic associations cross-sectionally using multinomial logistic regression and prospective associations with ischemic stroke and ICH using Cox regression. RESULTS: We included 7,778 participants (mean age 70.6 years; 42.7% female) from 16 studies, followed up for a median of 1.44 years. Eighty ICH and 424 ischemic strokes occurred. BGPVS were associated with increasing age, hypertension, previous ischemic stroke, previous ICH, lacunes, cerebral microbleeds, and white matter hyperintensities. CSOPVS showed consistently weaker associations. Prospectively, after adjusting for potential confounders including cerebral microbleeds, increasing BGPVS burden was independently associated with future ischemic stroke (versus 0-10 BGPVS, 11-20 BGPVS: HR 1.19, 95% CI 0.93-1.53; 21+ BGPVS: HR 1.50, 95% CI 1.10-2.06; = 0.040). Higher BGPVS burden was associated with increased ICH risk in univariable analysis, but not in adjusted analyses. CSOPVS were not significantly associated with either outcome. DISCUSSION: In patients with ischemic stroke or TIA, increasing BGPVS burden is associated with more severe cerebral small vessel disease and higher ischemic stroke risk. Neither BGPVS nor CSOPVS were independently associated with future ICH

Network impact score is an independent predictor of post-stroke cognitive impairment: A multicenter cohort study in 2341 patients with acute ischemic stroke

BACKGROUND: Post-stroke cognitive impairment (PSCI) is a common consequence of stroke. Accurate prediction of PSCI risk is challenging. The recently developed network impact score, which integrates information on infarct location and size with brain network topology, may improve PSCI risk prediction. AIMS: To determine if the network impact score is an independent predictor of PSCI, and of cognitive recovery or decline. METHODS: We pooled data from patients with acute ischemic stroke from 12 cohorts through the Meta VCI Map consortium. PSCI was defined as impairment in ≥ 1 cognitive domain on neuropsychological examination, or abnormal Montreal Cognitive Assessment. Cognitive recovery was defined as conversion from PSCI 24 months) and cognitive recovery or decline using logistic regression. Models were adjusted for age, sex, education, prior stroke, infarct volume, and study site. RESULTS: We included 2341 patients with 4657 cognitive assessments. PSCI was present in 398/844 patients (47%) 24 months. Cognitive recovery occurred in 64/181 (35%) patients and cognitive decline in 26/287 (9%). The network impact score predicted PSCI in the univariable (OR 1.50, 95%CI 1.34-1.68) and multivariable (OR 1.27, 95%CI 1.10-1.46) GEE model, with similar ORs in the logistic regression models for specified post-stroke intervals. The network impact score was not associated with cognitive recovery or decline. CONCLUSIONS: The network impact score is an independent predictor of PSCI. As such, the network impact score may contribute to a more precise and individualized cognitive prognostication in patients with ischemic stroke. Future studies should address if multimodal prediction models, combining the network impact score with demographics, clinical characteristics and other advanced brain imaging biomarkers, will provide accurate individualized prediction of PSCI. A tool for calculating the network impact score is freely available at https://metavcimap.org/features/software-tools/lsm-viewer/

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019 : a systematic analysis for the Global Burden of Disease Study 2019

Background In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990-2010 time period, with the greatest annualised rate of decline occurring in the 0-9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10-24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10-24 years were also in the top ten in the 25-49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50-74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and development investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve

Global burden of 87 risk factors in 204 countries and territories, 1990–2019 : a systematic analysis for the Global Burden of Disease Study 2019

Background Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. Methods GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk-outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk-outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk-outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden. Findings The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10.8 million (95% uncertainty interval [UI] 9.51-12.1) deaths (19.2% [16.9-21.3] of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8.71 million (8.12-9.31) deaths (15.4% [14.6-16.2] of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253-350) DALYs (11.6% [10.3-13.1] of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0-9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10-24 years, alcohol use for those aged 25-49 years, and high systolic blood pressure for those aged 50-74 years and 75 years and older. Interpretation Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public

Tracking development assistance for health and for COVID-19 : a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990–2050

Background: The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods: We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings: In 2019, health spending globally reached$8·8 trillion (95% uncertainty interval [UI] 8·7–8·8) or $1132 (1119–1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total,$40·4 billion (0·5%, 95% UI 0·5–0·5) was development assistance for health provided to low-income and middle-income countries, which made up 24·6% (UI 24·0–25·1) of total spending in low-income countries. We estimate that $54·8 billion in development assistance for health was disbursed in 2020. Of this,$13·7 billion was targeted toward the COVID-19 health response. $12·3 billion was newly committed and$1·4 billion was repurposed from existing health projects. $3·1 billion (22·4$2·4 billion (17·9%) was for supply chain and logistics. Only $714·4 million (7·7$1519 (1448–1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation: Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. Funding: Bill & Melinda Gates Foundation