Evidence map›Paper›PMID 40863215›Full record

ArticleDiseases (Basel, Switzerland)2025

Spatiotemporal Patterns of Non-Communicable Disease Mortality in the Metropolitan Area of the Valley of Mexico, 2000-2019.

Constantino González-Salazar, Kathia Gasca-Gómez, Omar Cordero-Saldierna

Abstract read
In one paragraph

Article in Diseases (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Constantino González-SalazarICAyCC-Instituto de Ciencias de la Atmósfera y Cambio Climático, UNAM-Universidad Nacional Autónoma de México, Mexico City 04510, Mexico.ORCID 0000-0001-7347-714X
Kathia Gasca-GómezICAyCC-Instituto de Ciencias de la Atmósfera y Cambio Climático, UNAM-Universidad Nacional Autónoma de México, Mexico City 04510, Mexico.
Omar Cordero-SaldiernaICAyCC-Instituto de Ciencias de la Atmósfera y Cambio Climático, UNAM-Universidad Nacional Autónoma de México, Mexico City 04510, Mexico.

Funding

SECTEI SECTEI/134/2024
6 · The paper itself

Abstract

backgroundNon-communicable diseases (NCDs) are a leading cause of mortality globally, contributing significantly to the burden on healthcare systems. Understanding the spatiotemporal patterns of NCD mortality is crucial for identifying vulnerable populations and regions at high risk.

objectivesHere, we evaluated the spatiotemporal patterns of NCD mortality in the Metropolitan Area of the Valley of Mexico (MAVM) from 2000 to 2019 for five International Classification of Diseases chapters (4, 5, 6, 9, and 10) at two spatial scales: the municipal level and metropolitan region.

methodsMortality rates were calculated for the total population and stratified by sex and age groups at both spatial scales. In addition, the relative risk (RR) of mortality was estimated to identify vulnerable population groups and regions with a high risk of mortality, using women and the 25-34 age group as reference categories for population-level analysis, and the overall MAVM mortality rate as the reference for municipal-level analysis.

resultsMortality trends showed that circulatory-system diseases (Chapter 9) are emerging as a concerning health issue, with 45 municipalities showing increasing mortality trends, especially among older adults. Respiratory-system diseases (Chapter 10), mental and behavioral disorders (Chapter 5) and nervous-system diseases (Chapter 6) predominantly did not exhibit a consistent general mortality trend. However, upon disaggregating by sex and age groups, specific negative or positive trends emerged at the municipal level for some of these chapters or subgroups. Endocrine, nutritional, and metabolic diseases (Chapter 4) showed a complex pattern, with some age groups presenting increasing mortality trends, and 52 municipalities showing increasing trends overall. The RR showed men and older age groups (≥35 years) exhibiting higher mortality risks. The temporal trend of RR allowed us to identify spatial mortality hotspots mainly in chapters related to circulatory, endocrine, and respiratory diseases, forming four geographical clusters in Mexico City that show persistent high risk of mortality.

conclusionsThe spatiotemporal analysis highlights municipalities and vulnerable populations with a consistently elevated mortality risk. These findings emphasize the need for monitoring NCD mortality patterns at both the municipal and metropolitan levels to address disparities and guide the implementation of health policies aimed at reducing mortality risk in vulnerable populations.

Indexed as

chronic diseaseshealth determinantsmortality hotspotsnon-communicable diseasesspatial epidemiology

Identifiers

PMID40863215
PMCPMC12385793

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.