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Tytuł pozycji:

Association between body mass index and blood pressure levels across socio-demographic groups and geographical settings: analysis of pooled data in Peru

Tytuł:
Association between body mass index and blood pressure levels across socio-demographic groups and geographical settings: analysis of pooled data in Peru
Autorzy:
Antonio Bernabe-Ortiz
Rodrigo M. Carrillo-Larco
J. Jaime Miranda
Temat:
Blood pressure
Body mass index
Hypertension
Obesity
Medicine
Źródło:
PeerJ, Vol 9, p e11307 (2021)
Wydawca:
PeerJ Inc., 2021.
Rok publikacji:
2021
Kolekcja:
LCC:Medicine
Typ dokumentu:
article
Opis pliku:
electronic resource
Język:
English
ISSN:
2167-8359
Relacje:
https://peerj.com/articles/11307.pdf; https://peerj.com/articles/11307/; https://doaj.org/toc/2167-8359
DOI:
10.7717/peerj.11307
Dostęp URL:
https://doaj.org/article/128fd9ab4a5d4692a5704052f57b19cb  Link otwiera się w nowym oknie
Numer akcesji:
edsdoj.128fd9ab4a5d4692a5704052f57b19cb
Czasopismo naukowe
Background Understanding the relationship between BMI and blood pressure requires assessing whether this association is similar or differs across population groups. This study aimed to assess the association between body mass index (BMI) and blood pressure levels, and how these associations vary between socioeconomic groups and geographical settings. Methods Data from the National Demographic Health Survey of Peru from 2014 to 2019 was analyzed considering the complex survey design. The outcomes were levels of systolic (SBP) and diastolic blood pressure (DBP), and the exposure was BMI. Exposure and outcomes were fitted as continuous variables in a non-linear quadratic regression model. We explored effect modification by six socioeconomic and geographical variables (sex, age, education level, socioeconomic position, study area, and altitude), fitting an interaction term between each of these variables and BMI. Results Data from 159, 940 subjects, mean age 44.4 (SD: 17.1), 54.6% females, was analyzed. A third (34.0%) of individuals had ≥12 years of education, 24.7% were from rural areas, and 23.7% lived in areas located over 2,500 m above sea level. In the overall sample mean BMI was 27.1 (SD: 4.6) kg/m2, and mean SBP and DBP were 122.5 (SD: 17.2) and 72.3 (SD: 9.8) mmHg, respectively. In the multivariable models, greater BMI levels were associated with higher SBP (p-value < 0.001) and DBP (p-value < 0.001). There was strong evidence that sex, age, education level, and altitude were effect modifiers of the association between BMI and both SBP and DBP. In addition to these socio-demographic variables, socioeconomic position and study area were also effect modifiers of the association between BMI and DBP, but not SBP. Conclusions The association between BMI and levels of blood pressure is not uniform on a range of socio-demographic and geographical population groups. This characterization can inform the understanding of the epidemiology and rise of blood pressure in a diversity of low-resource settings.

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