Abstract

Background: Obesity, a complex metabolic condition, is linked to chronic diseases and reduced quality of life (QoL) (Ben Othman et al., 2023). Traditional metrics like Body Mass Index (BMI)fail to capture the full spectrum of metabolic health impacts (Iacobini et al., 2019). A nuanced classification into obesity subtypes—metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MuHNW), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO)—reveals significant variations in health outcomes (Després, 2023). Understanding these differences in bio-psycho-behavioral aspects and QoL is crucial but underexplored.

Aim: This study examines bio-psycho-behavioral factors and QoL variations across different obesity subtypes.

Methods: In this cross-sectional study, 257 participants from a Taiwanese health center were classified as MHNW, MuHNW, MHO, or MUO based on BMI (≥24 kg/m2 as obese) and metabolic health (fewer than two metabolic syndrome criteria and no history of hypertension, diabetes, or cardiovascular disease). Psychological distress (DASS-21), dietary habits, physical activity (IPAQ), sleep quality (PSQI), and QoL (WHOQoL-BREF) were assessed. Biological indicators included heart rate variability (HRV) and insulin resistance (HOMA-IR).

Results: Subtype distribution was 35.1% MHNW, 7.7% MuHNW, 20.8% MHO, and 35.5% MUO. The MUO group exhibited higher psychological distress and poorer sleep quality than MHNW and MHO (p < 0.001), comparable to MuHNW. Physical activity was lower in MUO compared to MHNW, MHO, and MuHNW (p < 0.05). HRV indices (SDNN, RMSSD) were reduced in MUO compared to MHNW and MHO (p < 0.001), with levels similar to MuHNW. HOMA-IR was higher in MUO than MHNW (p < 0.05) but not significantly different from MuHNW or MHO. QoL was notably lower in MUO, marked by reduced satisfaction and general health perception (p < 0.05).

Conclusion: Significant differences in psychological, behavioral, and biological factors exist across obesity subtypes. Despite normal weight, MuHNW participants faced risks similar to MUO, indicating hidden health concerns (Oliveira et al., 2020; Tebar et al., 2021). Although metabolically healthier, MHO participants showed elevated insulin resistance (Barazzoni et al., 2018). These findings underscore the limitations of BMI alone for health risk assessment, highlighting the need for multidimensional evaluations and targeted interventions for specific obesity subtypes (Wu et al., 2022).

Notes

References:

Barazzoni, R., Gortan Cappellari, G., Ragni, M., & Nisoli, E. (2018). Insulin resistance in obesity: an overview of fundamental alterations. Eat Weight Disord, 23(2), 149-157. https://doi.org/10.1007/s40519-018-0481-6

Ben Othman, R., Ben Amor, N., Mahjoub, F., Berriche, O., El Ghali, C., Gamoudi, A., & Jamoussi, H. (2023). A clinical trial about effects of prebiotic and probiotic supplementation on weight loss, psychological profile and metabolic parameters in obese subjects. Endocrinol Diabetes Metab, 6(2), e402. https://doi.org/10.1002/edm2.402

Iacobini, C., Pugliese, G., Blasetti Fantauzzi, C., Federici, M., & Menini, S. (2019). Metabolically healthy versus metabolically unhealthy obesity. Metabolism, 92, 51-60. https://doi.org/10.1016/j.metabol.2018.11.009

Oliveira, C., Silveira, E. A., Rosa, L., Santos, A., Rodrigues, A. P., Mendonça, C., Silva, L., Gentil, P., & Rebelo, A. C. (2020). Risk factors associated with cardiac autonomic modulation in obese individuals. Journal of Obesity, 2020(1), 7185249.

Tebar, W. R., Ritti-Dias, R. M., Mota, J., Saraiva, B. T., Damato, T. M., Delfino, L. D., Farah, B. Q., Vanderlei, L. C. M., & Christofaro, D. G. (2021). Relationship of cardiac autonomic modulation with cardiovascular parameters in adults, according to body mass index and physical activity. Journal of cardiovascular translational research, 1-9.

Wu, Q., Xia, M. F., & Gao, X. (2022). Metabolically healthy obesity: Is it really healthy for type 2 diabetes mellitus? World journal of diabetes, 13(2), 70-84. https://doi.org/10.4239/wjd.v13.i2.70

Description

Despite normal weight, MuHNW participants faced risks similar to MUO; metabolically healthier, MHO participants showed elevated insulin resistance.

Author Details

Ching-Ling Lin, PhD student; Yu-Ju Chen, PhD; Lih-Yeu Huang, MD, attending physician; Shu-Ling Chu, Nurse Practitioner

Sigma Membership

Non-member

Type

Poster

Format Type

Text-based Document

Study Design/Type

Cross-Sectional

Research Approach

Other

Keywords:

Primary Care, Public and Community Health, Obesity, Quality of Life, Taiwan

Conference Name

36th International Nursing Research Congress

Conference Host

Sigma Theta Tau International

Conference Location

Seattle, Washington, USA

Conference Year

2025

Rights Holder

All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record.

Review Type

Abstract Review Only: Reviewed by Event Host

Acquisition

Proxy-submission

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Variations in Bio-Psycho-Behavioral Profiles and Quality of Life Among Obesity Subtypes

Seattle, Washington, USA

Background: Obesity, a complex metabolic condition, is linked to chronic diseases and reduced quality of life (QoL) (Ben Othman et al., 2023). Traditional metrics like Body Mass Index (BMI)fail to capture the full spectrum of metabolic health impacts (Iacobini et al., 2019). A nuanced classification into obesity subtypes—metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MuHNW), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO)—reveals significant variations in health outcomes (Després, 2023). Understanding these differences in bio-psycho-behavioral aspects and QoL is crucial but underexplored.

Aim: This study examines bio-psycho-behavioral factors and QoL variations across different obesity subtypes.

Methods: In this cross-sectional study, 257 participants from a Taiwanese health center were classified as MHNW, MuHNW, MHO, or MUO based on BMI (≥24 kg/m2 as obese) and metabolic health (fewer than two metabolic syndrome criteria and no history of hypertension, diabetes, or cardiovascular disease). Psychological distress (DASS-21), dietary habits, physical activity (IPAQ), sleep quality (PSQI), and QoL (WHOQoL-BREF) were assessed. Biological indicators included heart rate variability (HRV) and insulin resistance (HOMA-IR).

Results: Subtype distribution was 35.1% MHNW, 7.7% MuHNW, 20.8% MHO, and 35.5% MUO. The MUO group exhibited higher psychological distress and poorer sleep quality than MHNW and MHO (p < 0.001), comparable to MuHNW. Physical activity was lower in MUO compared to MHNW, MHO, and MuHNW (p < 0.05). HRV indices (SDNN, RMSSD) were reduced in MUO compared to MHNW and MHO (p < 0.001), with levels similar to MuHNW. HOMA-IR was higher in MUO than MHNW (p < 0.05) but not significantly different from MuHNW or MHO. QoL was notably lower in MUO, marked by reduced satisfaction and general health perception (p < 0.05).

Conclusion: Significant differences in psychological, behavioral, and biological factors exist across obesity subtypes. Despite normal weight, MuHNW participants faced risks similar to MUO, indicating hidden health concerns (Oliveira et al., 2020; Tebar et al., 2021). Although metabolically healthier, MHO participants showed elevated insulin resistance (Barazzoni et al., 2018). These findings underscore the limitations of BMI alone for health risk assessment, highlighting the need for multidimensional evaluations and targeted interventions for specific obesity subtypes (Wu et al., 2022).