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Patterns of global burden of 13 diseases attributable to lead exposure, 1990–2019
OBJECTIVES: Understanding the spatio-temporal patterns of the global burden of various diseases resulting from lead exposure is critical for controlling lead pollution and disease prevention. METHODS: Based on the 2019 Global Burden of Disease (GBD) framework and methodology, the global, regional, a...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10262405/ https://www.ncbi.nlm.nih.gov/pubmed/37308890 http://dx.doi.org/10.1186/s12889-023-15874-7 |
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author | Xu, Tongtong Lin, Kangqian Cao, Miao Miao, Xinlu Guo, Heng Rui, Dongsheng Hu, Yunhua Yan, Yizhong |
author_facet | Xu, Tongtong Lin, Kangqian Cao, Miao Miao, Xinlu Guo, Heng Rui, Dongsheng Hu, Yunhua Yan, Yizhong |
author_sort | Xu, Tongtong |
collection | PubMed |
description | OBJECTIVES: Understanding the spatio-temporal patterns of the global burden of various diseases resulting from lead exposure is critical for controlling lead pollution and disease prevention. METHODS: Based on the 2019 Global Burden of Disease (GBD) framework and methodology, the global, regional, and national burden of 13 level-three diseases attributable to lead exposure were analyzed by disease type, patient age and sex, and year of occurrence. Population attributable fraction (PAF), deaths and disability-adjusted life years (DALYs), age-standardized mortality rate (ASMR) and age-standardized DALYs rate (ASDR) obtained from the GBD 2019 database were used as descriptive indicators, and the average annual percentage change (AAPC) was estimated by a log-linear regression model to reflect the time trend. RESULTS AND CONCLUSIONS: From 1990 to 2019, the number of deaths and DALYs resulting from lead exposure increased by 70.19% and 35.26%, respectively; however, the ASMR and ASDR decreased by 20.66% and 29.23%, respectively. Ischemic heart disease (IHD), stroke, and hypertensive heart disease (HHD) showed the highest increases in deaths; IHD, stroke, and diabetes and kidney disease (DKD) had the fastest-growing DALYs. The fastest decline in ASMR and ASDR was seen in stroke, with AAPCs of -1.25 (95% CI [95% confidence interval]: -1.36, -1.14) and -1.66 (95% CI: -1.76, -1.57), respectively. High PAFs occurred mainly in South Asia, East Asia, the Middle East, and North Africa. Age-specific PAFs of DKD resulting from lead exposure were positively correlated with age, whereas the opposite was true for mental disorders (MD), with the burden of lead-induced MD concentrated in children aged 0–6 years. The AAPCs of ASMR and ASDR showed a strong negative correlation with the socio-demographic index. Our findings showed that the global impact of lead exposure and its burden increased from 1990 to 2019 and varied significantly according to age, sex, region, and resulting disease. Effective public health measures and policies should be adopted to prevent and control lead exposure. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-15874-7. |
format | Online Article Text |
id | pubmed-10262405 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-102624052023-06-15 Patterns of global burden of 13 diseases attributable to lead exposure, 1990–2019 Xu, Tongtong Lin, Kangqian Cao, Miao Miao, Xinlu Guo, Heng Rui, Dongsheng Hu, Yunhua Yan, Yizhong BMC Public Health Research OBJECTIVES: Understanding the spatio-temporal patterns of the global burden of various diseases resulting from lead exposure is critical for controlling lead pollution and disease prevention. METHODS: Based on the 2019 Global Burden of Disease (GBD) framework and methodology, the global, regional, and national burden of 13 level-three diseases attributable to lead exposure were analyzed by disease type, patient age and sex, and year of occurrence. Population attributable fraction (PAF), deaths and disability-adjusted life years (DALYs), age-standardized mortality rate (ASMR) and age-standardized DALYs rate (ASDR) obtained from the GBD 2019 database were used as descriptive indicators, and the average annual percentage change (AAPC) was estimated by a log-linear regression model to reflect the time trend. RESULTS AND CONCLUSIONS: From 1990 to 2019, the number of deaths and DALYs resulting from lead exposure increased by 70.19% and 35.26%, respectively; however, the ASMR and ASDR decreased by 20.66% and 29.23%, respectively. Ischemic heart disease (IHD), stroke, and hypertensive heart disease (HHD) showed the highest increases in deaths; IHD, stroke, and diabetes and kidney disease (DKD) had the fastest-growing DALYs. The fastest decline in ASMR and ASDR was seen in stroke, with AAPCs of -1.25 (95% CI [95% confidence interval]: -1.36, -1.14) and -1.66 (95% CI: -1.76, -1.57), respectively. High PAFs occurred mainly in South Asia, East Asia, the Middle East, and North Africa. Age-specific PAFs of DKD resulting from lead exposure were positively correlated with age, whereas the opposite was true for mental disorders (MD), with the burden of lead-induced MD concentrated in children aged 0–6 years. The AAPCs of ASMR and ASDR showed a strong negative correlation with the socio-demographic index. Our findings showed that the global impact of lead exposure and its burden increased from 1990 to 2019 and varied significantly according to age, sex, region, and resulting disease. Effective public health measures and policies should be adopted to prevent and control lead exposure. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-15874-7. BioMed Central 2023-06-12 /pmc/articles/PMC10262405/ /pubmed/37308890 http://dx.doi.org/10.1186/s12889-023-15874-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Xu, Tongtong Lin, Kangqian Cao, Miao Miao, Xinlu Guo, Heng Rui, Dongsheng Hu, Yunhua Yan, Yizhong Patterns of global burden of 13 diseases attributable to lead exposure, 1990–2019 |
title | Patterns of global burden of 13 diseases attributable to lead exposure, 1990–2019 |
title_full | Patterns of global burden of 13 diseases attributable to lead exposure, 1990–2019 |
title_fullStr | Patterns of global burden of 13 diseases attributable to lead exposure, 1990–2019 |
title_full_unstemmed | Patterns of global burden of 13 diseases attributable to lead exposure, 1990–2019 |
title_short | Patterns of global burden of 13 diseases attributable to lead exposure, 1990–2019 |
title_sort | patterns of global burden of 13 diseases attributable to lead exposure, 1990–2019 |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10262405/ https://www.ncbi.nlm.nih.gov/pubmed/37308890 http://dx.doi.org/10.1186/s12889-023-15874-7 |
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