scholarly journals Metropolitan age-specific mortality trends at borough and neighborhood level: The case of Mexico City

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0244384
Author(s):  
Karol Baca-López ◽  
Cristóbal Fresno ◽  
Jesús Espinal-Enríquez ◽  
Miriam V. Flores-Merino ◽  
Miguel A. Camacho-López ◽  
...  
Keyword(s):  
Public Policy ◽  
Mexico City ◽  
Study Groups ◽  
Mortality Rates ◽  
Spatial And Temporal Patterns ◽  
Mortality Trends ◽  
Mixed Effect ◽  
Specific Mortality ◽  
Spatio Temporal ◽  
The One

Understanding the spatial and temporal patterns of mortality rates in a highly heterogeneous metropolis, is a matter of public policy interest. In this context, there is no, to the best of our knowledge, previous studies that correlate both spatio-temporal and age-specific mortality rates in Mexico City. Spatio-temporal Kriging modeling was used over five age-specific mortality rates (from the years 2000 to 2016 in Mexico City), to gain both spatial (borough and neighborhood) and temporal (year and trimester) data level description. Mortality age-specific patterns have been modeled using multilevel modeling for longitudinal data. Posterior tests were carried out to compare mortality averages between geo-spatial locations. Mortality correlation extends in all study groups for as long as 12 years and as far as 13.27 km. The highest mortality rate takes place in the Cuauhtémoc borough, the commercial, touristic and cultural core downtown of Mexico City. On the contrary, Tlalpan borough is the one with the lowest mortality rates in all the study groups. Post-productive mortality is the first age-specific cause of death, followed by infant, productive, pre-school and scholar groups. The combinations of spatio-temporal Kriging estimation and time-evolution linear mixed-effect models, allowed us to unveil relevant time and location trends that may be useful for public policy planning in Mexico City.

scholarly journals Metropolitan age-specific mortality trends at borough and neighbourhood level: The case of Mexico City

2020 ◽  
Author(s):  
Karol Baca-Lopez ◽  
Cristobal Fresno ◽  
Jesus Espinal-Enriquez ◽  
Miriam V. Flores-Merino ◽  
Miguel A. Camacho-Lopez ◽  
...  
Keyword(s):  
Public Policy ◽  
Time Evolution ◽  
Mexico City ◽  
Study Groups ◽  
Mortality Rates ◽  
Mortality Trends ◽  
Mixed Effect ◽  
Mixed Effect Models ◽  
Specific Mortality ◽  
Spatio Temporal

Abstract Background Understanding the spatial and temporal patterns of mortality rates in a highly inhomogeneous metropolis, is a matter of public policy interest. In this context, there is no previous study that correlates both spatio-temporal and age-specific mortality rates in Mexico City. Methods Spatio-temporal kriging modelling was used over six age-specific mortality rates (from the years 2000 to 2016 in Mexico City), to gain both spatial (borough and neighbourhood) and temporal (year and trimester) data level description. Resulting data were modelled using time-evolution mixed effect models to unblurred mortality age-specific patterns. Posterior tests were carried out to compare mortality averages between geospatial locations. Results Mortality correlation extends in all study groups for as long as 12 years and as far as 13.27 km. The highest mortality rate takes place in the Cuauhtémoc borough, as it is the commercial, touristic and cultural core downtown Mexico City. On the contrary, Tlalpan borough is the one with the lowest mortality rates in all the study groups. Interestingly, post-productive mortality is the first age-specific cause of death, followed by infant, productive, pre-school and scholar groups. Conclusion The combinations of spatio-temporal Kriging estimation and time-evolution mixed effect models, allowed us to unveil relevant time and location trends that may be useful for public policy planning in Mexico City.

scholarly journals Metropolitan age-specific mortality trends at borough and neighbourhood level: The case of Mexico City

2020 ◽  
Author(s):  
Karol Baca-Lopez ◽  
Cristobal Fresno ◽  
Jesus Espinal-Enriquez ◽  
Miriam V. Flores-Merino ◽  
Miguel A. Camacho-Lopez ◽  
...  
Keyword(s):  
Public Policy ◽  
Time Evolution ◽  
Mexico City ◽  
Study Groups ◽  
Mortality Rates ◽  
Mortality Trends ◽  
Mixed Effect ◽  
Mixed Effect Models ◽  
Specific Mortality ◽  
Spatio Temporal

Abstract Background Understanding the spatial and temporal patterns of mortality rates in a highly inhomogeneous metropolis, is a matter of public policy interest. In this context, there is no previous study that correlates both spatio-temporal and age-specific mortality rates in Mexico City. Methods Spatio-temporal kriging modelling was used over six age-specific mortality rates (from the years 2000 to 2016 in Mexico City), to gain both spatial (borough and neighbourhood) and temporal (year and trimester) data level description. Resulting data were modelled using time-evolution mixed effect models to unblurred mortality age-specific patterns. Posterior tests were carried out to compare mortality averages between geospatial locations. Results Mortality correlation extends in all study groups for as long as 12 years and as far as 13.27 km. The highest mortality rate takes place in the Cuauhtémoc borough, as it is the commercial, touristic and cultural core downtown Mexico City. On the contrary, Tlalpan borough is the one with the lowest mortality rates in all the study groups. Interestingly, post-productive mortality is the first age-specific cause of death, followed by infant, productive, pre-school and scholar groups. Conclusion The combinations of spatio-temporal Kriging estimation and time-evolution mixed effect models, allowed us to unveil relevant time and location trends that may be useful for public policy planning in Mexico City.

scholarly journals Metropolitan age-specific mortality trends at borough and neighbourhood level: The case of Mexico City

2020 ◽  
Author(s):  
Karol Baca-Lopez ◽  
Cristobal Fresno ◽  
Jesus Espinal-Enriquez ◽  
Miriam V. Flores-Merino ◽  
Miguel A. Camacho-Lopez ◽  
...  
Keyword(s):  
Public Policy ◽  
Time Evolution ◽  
Mexico City ◽  
Study Groups ◽  
Mortality Rates ◽  
Mortality Trends ◽  
Mixed Effect ◽  
Mixed Effect Models ◽  
Specific Mortality ◽  
Spatio Temporal

Abstract BackgroundUnderstanding the spatial and temporal patterns of mortality rates in a highly inhomogeneous metropolis, is a matter of public policy interest. In this context, there is no previous study that correlates both spatio-temporal and age-specific mortality rates in Mexico City. Methods Spatio-temporal kriging modelling was used over six age-specific mortality rates (from the years 2000 to 2016 in Mexico City), to gain both spatial (borough and neighbourhood) and temporal (year and trimester) data level description. Resulting data were modelled using time-evolution mixed effect models to unblurred mortality age-specific patterns. Posterior tests were carried out to compare mortality averages between geospatial locations. Results Mortality correlation extends in all study groups for as long as 12 years and as far as 13.27 km. The highest mortality rate takes place in the Cuauhtémoc borough, as it is the commercial, touristic and cultural core downtown Mexico City. On the contrary, Tlalpan borough is the one with the lowest mortality rates in all the study groups. Interestingly, post-productive mortality is the first age-specific cause of death, followed by infant, productive, pre-school and scholar groups. Conclusion The combinations of spatio-temporal Kriging estimation and time-evolution mixed effect models, allowed us to unveil relevant time and location trends that may be useful for public policy planning in Mexico City.

scholarly journals Mapping Mortality: Using Lexis surfaces to identify complex patterns in age-year specific mortality rates within and between populations

2018 ◽  
Author(s):  
Jonathan Minton
Keyword(s):  
Health Inequalities ◽  
Social Groups ◽  
Mortality Rates ◽  
Mortality Trends ◽  
Specific Mortality ◽  
Different Populations ◽  
Complex Patterns

This project will introduce ways of reasoning about mortality trends over the Lexis surface, for different populations, and how these contribute to health inequalities between countries and other social groups

scholarly journals Pneumonia mortality trends in all Brazilian geographical regions between 1996 and 2012

2017 ◽  
Vol 43 (4) ◽  
pp. 274-279
Author(s):  
Rosemeire de Olanda Ferraz ◽  
Jane Kelly Oliveira-Friestino ◽  
Priscila Maria Stolses Bergamo Francisco
Keyword(s):  
Temporal Trends ◽  
Secondary Data ◽  
Mortality Rates ◽  
Mortality Trends ◽  
Annual Percent Change ◽  
Percent Change ◽  
The North ◽  
Geographical Regions ◽  
The One ◽  
Increasing Trends

ABSTRACT Objective: To analyze the temporal trends in pneumonia mortality rates (standardized by age, using the 2010 population of Brazil as the standard) in all Brazilian geographical regions between 1996 and 2012. Methods: This was an ecological time-series study examining secondary data from the Mortality Database maintained by the Information Technology Department of the Brazilian Unified Health Care System. Polynomial and joinpoint regression models, and corresponding 95% CIs, were used for trend analysis. Results: The pneumonia mortality rates in the South, Southeast, and Central-West showed a decreasing behavior until 2000, followed by increases, whereas, in the North and Northeast, they showed increasing trends virtually throughout the period studied. There was variation in annual percent change in pneumonia mortality rates in all regions except the North. The Central-West had the greatest decrease in annual percent change between 1996 and 2000, followed by an increase of the same magnitude until 2005. The 80 years and over age group was the one most influencing the trend behavior of pneumonia mortality rates in all regions. Conclusions: In general, pneumonia mortality trends reversed, with an important increase occurring in the years after 2000.

scholarly journals Impacts of the COVID-19 lockdown on air quality and its association with human mortality trends in megapolis Mexico City

2020 ◽  
Author(s):  
Gurusamy Kutralam-Muniasamy ◽  
Fermín Pérez-Guevara ◽  
Priyadarsi D. Roy ◽  
I. Elizalde-Martínez ◽  
V.C. Shruti
Keyword(s):  
Air Pollution ◽  
Latin America ◽  
Air Quality ◽  
Mexico City ◽  
Air Pollutants ◽  
Mortality Rates ◽  
Quality Data ◽  
Mortality Trends ◽  
Human Mortality ◽  
Air Quality Data

Abstract Mexico City is the second most populated city in Latin America, and it went through two partial lockdowns between April 1 and May 31, 2020 for reducing the COVID-19 propagation. The present study assessed air quality and its association with human mortality rates during the lockdown by estimating changes observed in air pollutants (CO, NO2, O3, SO2, PM10 and PM2.5) between the lockdown (April 1 - May 31) and pre-lockdown (January 1 – March 31) periods, as well as by comparing the air quality data of lockdown period with the same interval of previous five-years (2015-2019). Concentrations of NO2 (-29%), SO2 (-55%) and PM10 (-11%) declined and the contents of CO (+1.1%), PM2.5 (+19%) and O3 (+63%) increased during the lockdown compared to the pre-lockdown period. This study also estimated that NO2, SO2, CO, PM10 and PM2.5 reduced by 19-36%, and O3 enhanced by 14% compared to the average of 2015-2019. Reduction in traffic as well as less emission from vehicle exhausts led to remarkable decline in NO2, SO2 and PM10. The significant positive associations of PM2.5, CO and O3 with the numbers of COVID-19 infections and deaths, however, underscored the necessity to enforce air pollution regulations to protect human health in one of the important cities of the northern hemisphere.

THE NEW RADIOCARBON DATASET FOR TRILITH MONUMENTS OF SOUTHEASTERN ARABIA

Radiocarbon ◽  
2020 ◽  
pp. 1-11
Author(s):  
R Garba ◽  
P Demján ◽  
I Svetlik ◽  
D Dreslerová
Keyword(s):  
Iron Age ◽  
Temporal Patterns ◽  
Temporal Analysis ◽  
Coastal Plains ◽  
Spatial And Temporal Patterns ◽  
Two Phase ◽  
Stone Monuments ◽  
South Central ◽  
Geographical Expansion ◽  
Spatio Temporal

ABSTRACT Triliths are megalithic monuments scattered across the coastal plains of southern and southeastern Arabia. They consist of aligned standing stones with a parallel row of large hearths and form a space, the meaning of which is undoubtedly significant but nonetheless still unknown. This paper presents a new radiocarbon (14C) dataset acquired during the two field seasons 2018–2019 of the TSMO (Trilith Stone Monuments of Oman) project which investigated the spatial and temporal patterns of the triliths. The excavation and sampling of trilith hearths across Oman yielded a dataset of 30 new 14C dates, extending the use of trilith monuments to as early as the Iron Age III period (600–300 BC). The earlier dates are linked to two-phase trilith sites in south-central Oman. The three 14C pairs collected from the two-phase trilith sites indicated gaps between the trilith construction phases from 35 to 475 years (2 σ). The preliminary spatio-temporal analysis shows the geographical expansion of populations using trilith monuments during the 5th to 1st century BC and a later pull back in the 1st and 2nd century AD. The new 14C dataset for trilith sites will help towards a better understanding of Iron Age communities in southeastern Arabia.

scholarly journals Modelling local patterns of child mortality risk: a Bayesian Spatio-temporal analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Alejandro Lome-Hurtado ◽  
Jacques Lartigue-Mendoza ◽  
Juan C. Trujillo
Keyword(s):  
High Risk ◽  
Mexico City ◽  
Child Mortality ◽  
Mortality Risk ◽  
Temporal Analysis ◽  
Health Concern ◽  
The North ◽  
Greater Mexico ◽  
Spatio Temporal ◽  
Child Mortality Rate

Abstract Background Globally, child mortality rate has remained high over the years, but the figure can be reduced through proper implementation of spatially-targeted public health policies. Due to its alarming rate in comparison to North American standards, child mortality is particularly a health concern in Mexico. Despite this fact, there remains a dearth of studies that address its spatio-temporal identification in the country. The aims of this study are i) to model the evolution of child mortality risk at the municipality level in Greater Mexico City, (ii) to identify municipalities with high, medium, and low risk over time, and (iii) using municipality trends, to ascertain potential high-risk municipalities. Methods In order to control for the space-time patterns of data, the study performs a Bayesian spatio-temporal analysis. This methodology permits the modelling of the geographical variation of child mortality risk across municipalities, within the studied time span. Results The analysis shows that most of the high-risk municipalities were in the east, along with a few in the north and west areas of Greater Mexico City. In some of them, it is possible to distinguish an increasing trend in child mortality risk. The outcomes highlight municipalities currently presenting a medium risk but liable to become high risk, given their trend, after the studied period. Finally, the likelihood of child mortality risk illustrates an overall decreasing tendency throughout the 7-year studied period. Conclusions The identification of high-risk municipalities and risk trends may provide a useful input for policymakers seeking to reduce the incidence of child mortality. The results provide evidence that supports the use of geographical targeting in policy interventions.

Towards a computational theory of social groups: A finite set of cognitive primitives for representing any and all social groups in the context of conflict

2021 ◽  
pp. 1-62
Author(s):  
David Pietraszewski
Keyword(s):  
Social Group ◽  
Group Representation ◽  
Social Groups ◽  
Study Groups ◽  
Human Mind ◽  
Computational Theory ◽  
Mistaken Belief ◽  
Finite Set ◽  
The One ◽  
Definition Of

Abstract We don't yet have adequate theories of what the human mind is representing when it represents a social group. Worse still, many people think we do. This mistaken belief is a consequence of the state of play: Until now, researchers have relied on their own intuitions to link up the concept social group on the one hand, and the results of particular studies or models on the other. While necessary, this reliance on intuition has been purchased at considerable cost. When looked at soberly, existing theories of social groups are either (i) literal, but not remotely adequate (such as models built atop economic games), or (ii) simply metaphorical (typically a subsumption or containment metaphor). Intuition is filling in the gaps of an explicit theory. This paper presents a computational theory of what, literally, a group representation is in the context of conflict: it is the assignment of agents to specific roles within a small number of triadic interaction types. This “mental definition” of a group paves the way for a computational theory of social groups—in that it provides a theory of what exactly the information-processing problem of representing and reasoning about a group is. For psychologists, this paper offers a different way to conceptualize and study groups, and suggests that a non-tautological definition of a social group is possible. For cognitive scientists, this paper provides a computational benchmark against which natural and artificial intelligences can be held.

scholarly journals Monitoring progress with national and subnational health goals by integrating verbal autopsy and medically certified cause of death data

2021 ◽  
Vol 6 (5) ◽  
pp. e005387
Author(s):  
Tim Adair ◽  
Sonja Firth ◽  
Tint Pa Pa Phyo ◽  
Khin Sandar Bo ◽  
Alan D Lopez
Keyword(s):  
Cause Of Death ◽  
Verbal Autopsy ◽  
Integration Method ◽  
Mortality Rates ◽  
Vital Statistics ◽  
Death Registration ◽  
Chronic Respiratory Diseases ◽  
Health Goals ◽  
Specific Mortality ◽  
Four Causes

IntroductionThe measurement of progress towards many Sustainable Development Goals (SDG) and other health goals requires accurate and timely all-cause and cause of death (COD) data. However, existing guidance to countries to calculate these indicators is inadequate for populations with incomplete death registration and poor-quality COD data. We introduce a replicable method to estimate national and subnational cause-specific mortality rates (and hence many such indicators) where death registration is incomplete by integrating data from Medical Certificates of Cause of Death (MCCOD) for hospital deaths with routine verbal autopsy (VA) for community deaths.MethodsThe integration method calculates population-level cause-specific mortality fractions (CSMFs) from the CSMFs of MCCODs and VAs weighted by estimated deaths in hospitals and the community. Estimated deaths are calculated by applying the empirical completeness method to incomplete death registration/reporting. The resultant cause-specific mortality rates are used to estimate SDG Indicator 23: mortality between ages 30 and 70 years from cardiovascular diseases, cancers, chronic respiratory diseases and diabetes. We demonstrate the method using nationally representative data in Myanmar, comprising over 42 000 VAs and 7600 MCCODs.ResultsIn Myanmar in 2019, 89% of deaths were estimated to occur in the community. VAs comprised an estimated 70% of community deaths. Both the proportion of deaths in the community and CSMFs for the four causes increased with older age. We estimated that the probability of dying from any of the four causes between 30 and 70 years was 0.265 for men and 0.216 for women. This indicator is 50% higher if based on CSMFs from the integration of data sources than on MCCOD data from hospitals.ConclusionThis integration method facilitates country authorities to use their data to monitor progress with national and subnational health goals, rather than rely on estimates made by external organisations. The method is particularly relevant given the increasing application of routine VA in country Civil Registration and Vital Statistics systems.

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