TY - JOUR
T1 - Metabolic risk factors attributed burden in Iran at national and subnational levels, 1990 to 2019
AU - Moradi, Soroush
AU - Parsaei, Amirhossein
AU - Moghaddam, Sahar Saeedi
AU - Aryannejad, Armin
AU - Azadnajafabad, Sina
AU - Rezaei, Nazila
AU - Mashinchi, Baharnaz
AU - Esfahani, Zahra
AU - Shobeiri, Parnian
AU - Rezaei, Nazila
AU - Aali, Amirali
AU - Abbasi-Kangevari, Mohsen
AU - Abbasi-Kangevari, Zeinab
AU - Abdollahi, Shima
AU - Absalan, Abdorrahim
AU - Afaghi, Siamak
AU - Ahmadi, Ali
AU - Ahmadi, Amir Moghadam
AU - Ahmadi, Sepideh
AU - Ajami, Marjan
AU - Akhlaghdoust, Meisam
AU - Alatab, Sudabeh
AU - Alimohamadi, Yousef
AU - Amir-Behghadami, Mehrdad
AU - Amiri, Sohrab
AU - Anvari, Davood
AU - Arabloo, Jalal
AU - Askari, Elaheh
AU - Athari, Seyyed Shamsadin
AU - Avan, Abolfaz
AU - Azari, Samad
AU - Babamohamadi, Hassan
AU - Baghcheghi, Nayereh
AU - Bagherieh, Sara
AU - Baradaran, Hamid Reza
AU - Bashiri, Azadeh
AU - Dianatinasab, Mostafa
AU - Djalalinia, Shirin
AU - Dodangeh, Milad
AU - Dolatshahi, Mahsa
AU - Edalati, Sareh
AU - Farrokhpour, Hossein
AU - Fatehizadeh, Ali
AU - Ghadirian, Fataneh
AU - Ghashghaee, Ahmad
AU - Gholami, Ali
AU - Goleij, Pouya
AU - Hafezi-Nejad, Nima
AU - Hasani, Hamidreza
AU - Hassanipour, Soheil
AU - GBD 2019 Iran Collaborators
N1 - Funding Information:
A Fatehizadeh acknowledges support from the Department of Environmental Health Engineering of Isfahan University of Medical Sciences, Isfahan, Iran.
As a part of the Global Burden of Disease study, this study was funded by the Bill & Melinda Gates Foundation. The funders of the study had no role in the study design, data collection, data analysis, data interpretation, or writing of this publication.
PY - 2023/6/1
Y1 - 2023/6/1
N2 - Introduction: Metabolic risk factors (MRFs) predispose populations to a variety of chronic diseases with a huge burden globally. With the increasing burden of these risk factors in Iran, in this study, we aimed to report the estimated burden attributed to MRFs at national and subnational scales in Iran, from 1990 to 2019. Methods: Based on the comparative risk assessment method of the Global Burden of Disease (GBD) Study 2019, data of deaths and disability-adjusted life years (DALYs) attributable to four top MRFs in Iran including high systolic blood pressure (SBP), high fasting plasma glucose (FPG), high body mass index (BMI), and high low-density lipoprotein (LDL) for the 1990–2019 period, were extracted. The socio-demographic index (SDI) was used to report the data based on the corresponding socio-economic stratifications. The results were reported in national and subnational 31 provinces of Iran to discover disparities regarding the attributable burden to MRFs. Furthermore, we reported the causes of diseases to which the attributable burden to MRFs was related. Results: Overall, the age-standardized high LDL, high SBP, high BMI, and high FPG-attributed death rate changed by −45.1, −35.6, +2.8, and +19.9% from 1990 to 2019, respectively. High SBP was the leading risk factor regarding attributed age-standardized death rates reaching 157.8 (95% uncertainty interval: 135.3–179.1) and DALY rates reaching 2973.4 (2652.2–3280.2) per 100,000 person-years, in 2019. All rates increased with aging, and men had higher rates except for the +70 years age group. At the subnational level, provinces in the middle SDI quintile had the highest death and DALY rates regarding all four MRFs. Total deaths, DALYs, YLLs and YLDs number by the causes of diseases linked to MRFs increased over the study period. Cardiovascular diseases, diabetes mellitus, and kidney diseases were the main causes of burden of disease attributable to MRFs. Conclusion: Herein, we found divergent patterns regarding the burden of MRFs as well as disparities in different regions, sex, and age groups for each risk factor and related causes. This could provide policymakers with a clearer vision toward more appropriate decision-making and resource allocation to prevent the burden of MRFs in Iran.
AB - Introduction: Metabolic risk factors (MRFs) predispose populations to a variety of chronic diseases with a huge burden globally. With the increasing burden of these risk factors in Iran, in this study, we aimed to report the estimated burden attributed to MRFs at national and subnational scales in Iran, from 1990 to 2019. Methods: Based on the comparative risk assessment method of the Global Burden of Disease (GBD) Study 2019, data of deaths and disability-adjusted life years (DALYs) attributable to four top MRFs in Iran including high systolic blood pressure (SBP), high fasting plasma glucose (FPG), high body mass index (BMI), and high low-density lipoprotein (LDL) for the 1990–2019 period, were extracted. The socio-demographic index (SDI) was used to report the data based on the corresponding socio-economic stratifications. The results were reported in national and subnational 31 provinces of Iran to discover disparities regarding the attributable burden to MRFs. Furthermore, we reported the causes of diseases to which the attributable burden to MRFs was related. Results: Overall, the age-standardized high LDL, high SBP, high BMI, and high FPG-attributed death rate changed by −45.1, −35.6, +2.8, and +19.9% from 1990 to 2019, respectively. High SBP was the leading risk factor regarding attributed age-standardized death rates reaching 157.8 (95% uncertainty interval: 135.3–179.1) and DALY rates reaching 2973.4 (2652.2–3280.2) per 100,000 person-years, in 2019. All rates increased with aging, and men had higher rates except for the +70 years age group. At the subnational level, provinces in the middle SDI quintile had the highest death and DALY rates regarding all four MRFs. Total deaths, DALYs, YLLs and YLDs number by the causes of diseases linked to MRFs increased over the study period. Cardiovascular diseases, diabetes mellitus, and kidney diseases were the main causes of burden of disease attributable to MRFs. Conclusion: Herein, we found divergent patterns regarding the burden of MRFs as well as disparities in different regions, sex, and age groups for each risk factor and related causes. This could provide policymakers with a clearer vision toward more appropriate decision-making and resource allocation to prevent the burden of MRFs in Iran.
KW - cardiometabolic risk factors
KW - Global Burden of Disease
KW - hyperglycemia
KW - hyperlipidemia
KW - hypertension
KW - Iran
KW - obesity
UR - http://www.scopus.com/inward/record.url?scp=85162150750&partnerID=8YFLogxK
U2 - 10.3389/fpubh.2023.1149719
DO - 10.3389/fpubh.2023.1149719
M3 - Article
C2 - 37325329
AN - SCOPUS:85162150750
SN - 2296-2565
VL - 11
JO - Frontiers in public health
JF - Frontiers in public health
M1 - 1149719
ER -