Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
Deprecated: Implicit conversion from float 251.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
Deprecated: Implicit conversion from float 251.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
Deprecated: Implicit conversion from float 251.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Cad+Saude+Publica 2021 ; 37 (7): e00345920 Nephropedia Template TP
gab.com Text
Twit Text FOAVip
Twit Text #
English Wikipedia
Perfiles de transicion epidemiologica-nutricional y carga de morbi-mortalidad por COVID-19 en Argentina: un estudio ecologico #MMPMID34287589
Scruzzi GF; Tumas N; Pou SA
Cad Saude Publica 2021[]; 37 (7): e00345920 PMID34287589show ga
The study aimed to identify epidemiological-nutritional profiles in Argentina and to compare the burden of morbimortality from COVID-19. A multigroup ecological study was conducted with 24 geographic units in Argentina. We estimated the percent change from 2005 to 2018 in indicators of the epidemiological-nutritional transition and sociodemographic indicators according to geographic unit. We performed principal components analysis and hierarchical cluster analysis to identify geographic groupings to define profiles in the epidemiological-nutritional transition. By group, we calculated summary measures of COVID-19 cumulative incidence (CI), mortality, and case fatality (epidemiological week 50), establishing comparisons via Student's t test. Three profiles were identified: (1) reemergence of infectious diseases, (2) persistence of cardiovascular diseases despite social, health, and lifestyle improvements, and (3) consolidation of the triad obesity-sedentarism-cardiometabolic diseases. Mean COVID-19 cumulative incidence and mortality were higher in provinces with profile 1 compared to profile 2 (CI: p = 0.0159; mortality: p = 0.0187) and profile 3 (CI: p = 0.0205). Case-fatality was higher in profile 3, which includes provinces with more unfavorable socioeconomic conditions, showing significant differences from profile 2 (p=0.0307). In conclusion, there are distinct epidemiological-nutritional profiles in Argentina which tend to differ in terms of their COVID-19 epidemiological situation. Strategies to fight COVID-19 should consider the underlying epidemiological, nutritional, and sociodemographic characteristics.