Relationship between SIRI and android and gynoid fat related to obesity and cardiovascular risk: a cross-sectional study of NHANES 2017-2018

OBJECTIVE

Inflammation has a crucial role in several metabolic diseases, such as obesity. The author aimed to investigate the relationship between the system inflammation response index (SIRI) and android fat composition and distribution.

METHODS

Data for individuals aged 8-59 years, SIRI, android percent fat, and android-to-gynoid ratio from the 2017 to 2018 National Health and Nutrition Examination Survey were used. Weighted multiple linear regression and smooth curve fitting were used to test for linear and nonlinear associations. Additional subgroup analyses were performed. Threshold effect analysis was performed using a two-linear regression model.

RESULTS

Multiple linear regression showed a positive correlation between SIRI and android percent fat (β 0.92, 95% confidence interval [CI] 0.25-1.59) and between SIRI and the android-to-gynoid ratio (β 0.01, 95% CI 0.00-0.03) in 3783 Americans aged 8-59 years. The results showed that the effect of factors, other than smoking status, on the relationship between SIRI and android percent fat and android-to-gynoid ratio was not significant. There was a nonlinear relationship between SIRI and both android percent fat and android-to-gynoid ratio.

CONCLUSIONS

Elevated SIRI levels were associated with an increased android percent fat and android-to-gynoid ratio. Larger prospective studies are needed to validate the findings.

Body Mass Index Z Score vs Weight-for-Length Z Score in Infancy and Cardiometabolic Outcomes at Age 8-10 Years

OBJECTIVES

To confirm that World Health Organization weight-for-length z scores (zWFL) and World Health Organization body mass index z scores (zBMI) in infancy are associated with adiposity and cardiometabolic measures at 8-10 years old and to compare the predictive ability of the 2 methods.

STUDY DESIGN

zWFL and zBMI at 6, 12, and 18 months of age were computed using data extracted from health booklets, among participants in the Québec Adipose and Lifestyle InvesTigation in Youth prospective cohort (n = 464). Outcome measures at 8-10 years included adiposity, lipid profile, blood pressure, and insulin dynamics. The relationships between zWFL, zBMI, and each outcome were estimated using multivariable linear regression models. Outcome prediction at 8-10 years was compared between the 2 methods using eta-squared and the Lin concordance correlation coefficient.

RESULTS

zWFL and zBMI were associated with all measures of adiposity at 8-10 years. Associations with other cardiometabolic measures were less consistent. For both zWFL and zBMI across infancy, eta-squared were highly similar and the Lin coefficients were markedly high (≥0.991) for all outcomes.

CONCLUSIONS

There was no evidence that zBMI and zWFL in infancy differed in their ability to predict adiposity and cardiometabolic measures in childhood. This lends support to the sole use of zBMI for growth monitoring and screening of overweight and obesity from birth to 18 years.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT03356262.