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Obesities, Volume 5, Issue 3 (September 2025) – 4 articles

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16 pages, 516 KiB  
Article
Trends and Subgroup Comparisons of Obesity and Severe Obesity Prevalence Among Mississippi Adults, 2011–2021
by Stephanie McLeod, Xiaoshan Z. Gordy, Jana Bagwell, Christina Ferrell, Jerome Kolbo and Lei Zhang
Obesities 2025, 5(3), 52; https://doi.org/10.3390/obesities5030052 - 4 Jul 2025
Abstract
Mississippi has long been one of the most obese states in the U.S., with its obesity rates consistently exceeding the national average. The state’s severe obesity rate is also among the highest in the nation. This study utilized the 2011 to 2021 data [...] Read more.
Mississippi has long been one of the most obese states in the U.S., with its obesity rates consistently exceeding the national average. The state’s severe obesity rate is also among the highest in the nation. This study utilized the 2011 to 2021 data from the Mississippi Behavioral Risk Factor Surveillance System (BRFSS) to conduct a comprehensive analysis of obesity and severe obesity trends in Mississippi by sex, age, and race and ethnicity. The data set included a BMI variable calculated by using self-reported height and weight, which the authors categorized into two obesity classification groups—obesity (BMI: 30.00 to 39.99) and severe obesity (BMI: 40.00 or greater)—and demographic characteristics such as sex, age, race and ethnicity. The data were analyzed using SAS 9.4 software to account for the complex design. Weighted prevalence estimates and associated standard errors (SEs) for obesity and severe obesity were calculated. Changes in the prevalence over time were assessed using logistic regression models. The prevalence estimates and SEs were exported to Joinpoint software to calculate the annual percentage change (APC) and associated 95% confidence intervals (CIs) and p-values for the trends. Our analysis of the data revealed a consistent increase in severe obesity, regardless of age, sex, or race. A concerning trend exists where individuals are moving from the obese category to the severely obese category, indicating a worsening trend in overall weight status. This is likely to accelerate the development of chronic disease and, hence, place additional strain on an economically disadvantaged state. Future research should explore the underlying drivers of this shift, including biological, behavioral, and socioeconomic factors, while also evaluating the effectiveness of existing obesity prevention and treatment programs. Full article
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10 pages, 687 KiB  
Brief Report
Multicomponent-Type High-Intensity Interval Training Improves Vitamin D Status in Adults with Overweight/Obesity
by Maria Protopapa, Dimitrios Draganidis, Alexandra Avloniti, Ioannis G. Fatouros, Theodoros Stampoulis, Dimitrios Pantazis, Dimitrios Balampanos, Nikolaos Orestis Retzepis, Athanasios Poulios, Nikolaos Zaras, Maria Bampali, Ioannis Karakasiliotis, George Mastorakos, Theodore J. Angelopoulos, Maria Michalopoulou, Antonis Kambas, Athanasios Z. Jamurtas and Athanasios Chatzinikolaou
Obesities 2025, 5(3), 51; https://doi.org/10.3390/obesities5030051 - 4 Jul 2025
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Abstract
Vitamin D deficiency is highly prevalent in individuals with overweight/obesity and this can be largely attributed to the entrapment of VitD in adipose tissue due to impaired lipolytic stimulation. Considering the well-described role of exercise in stimulating lipolysis, the present study investigated the [...] Read more.
Vitamin D deficiency is highly prevalent in individuals with overweight/obesity and this can be largely attributed to the entrapment of VitD in adipose tissue due to impaired lipolytic stimulation. Considering the well-described role of exercise in stimulating lipolysis, the present study investigated the efficacy of multicomponent-type high-intensity interval training (m-HIIT) in increasing 25-hydroxyvitamin D [25(OH)D] levels in males with overweight/obesity. Twenty middle-aged males (43.5 ± 5 years, BMI: 30.7 ± 3.3 kg/m2) participated in three weekly supervised m-HIIT sessions over a 12-week period and underwent assessments at baseline, 6, and 12 weeks. Primary outcomes were total body fat mass, android fat, hepatorenal index, and serum 25(OH)D. Participants’ daily physical activity and dietary intake habits remained unaltered throughout the 12-week training period. The m-HIIT intervention reduced fat mass (by 3% at 12 weeks), android fat (by 3.7% at 6 weeks and 4.4% at 12 weeks), and hepatorenal index (by 8% at 12 weeks). Serum 25(OH)D levels increased by ~14% (+3.21 ng/mL, p = 0.002) and ~31% (+7.24 ng/mL, p < 0.001) at 6 and 12 weeks, respectively. The elevation of 25(OH)D levels at 12 weeks was inversely related to fat mass loss (R = 0.53, p = 0.016). Plasma SGPT, SGOT, ALP, γ-GT, fetuin-A, and calcium levels remained unaltered after the 12-week training period. In conclusion, m-HIIT may be useful as a non-pharmacological intervention to increase circulating VitD levels in adults with overweight/obesity. Full article
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12 pages, 761 KiB  
Article
Investigating Environmental and Socioeconomic Contributors to Adult Obesity in the Rio Grande Valley
by John Nicholas Cauba, Jihoo Woo, Russell W. Wiggins and Shizue Mito
Obesities 2025, 5(3), 50; https://doi.org/10.3390/obesities5030050 - 1 Jul 2025
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Abstract
Obesity in the Rio Grande Valley (RGV) of Texas remains a critical public health concern, with rates (46.9%) significantly exceeding those of Texas (36%) and the U.S. (34%) (p < 0.001). This study used 2024 County Health Rankings data to analyze environmental [...] Read more.
Obesity in the Rio Grande Valley (RGV) of Texas remains a critical public health concern, with rates (46.9%) significantly exceeding those of Texas (36%) and the U.S. (34%) (p < 0.001). This study used 2024 County Health Rankings data to analyze environmental and socioeconomic contributors to obesity across 240 Texas counties, with a population-weighted focus on Hidalgo, Cameron, Starr, and Willacy counties. The RGV exhibited markedly poorer access to exercise, higher rates of physical inactivity, lower Food Environment Index scores (FEI = 4.3 vs. 5.7 in Texas), higher rates of uninsurance, worse patient-to–primary care physician (PCP) ratios (2152:1 vs. Texas 1660:1), and increased preventable hospitalizations. Multiple linear regression identified physical inactivity (β = 0.6, p = 0.01) and access to exercise (β = −0.02, p = 0.02) as significant predictors of obesity. Notably, higher uninsured rates were associated with lower reported obesity, likely due to underdiagnosis in the absence of routine care. These findings emphasize the need for targeted interventions addressing food access, environmental and recreational infrastructure, along with healthcare infrastructure in the RGV, where socioeconomic disadvantage and structural barriers magnify the impact of national obesity trends on the regional level. Full article
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15 pages, 253 KiB  
Article
“I Don’t Approve of a Fat Person…”: A Cross-Sectional Survey Exploring the Perceptions of Health, Weight and Obesity
by Jordan D. Beaumont, Tina Reimann, Rosie Wyld and Beverley O’Hara
Obesities 2025, 5(3), 49; https://doi.org/10.3390/obesities5030049 - 20 Jun 2025
Viewed by 181
Abstract
Despite being acknowledged as a complex and multi-faceted condition, the prevailing view within society is that obesity is the result of individual choices and can be reversed simply by “eating less and moving more”. This is oversimplistic and leads to the view that [...] Read more.
Despite being acknowledged as a complex and multi-faceted condition, the prevailing view within society is that obesity is the result of individual choices and can be reversed simply by “eating less and moving more”. This is oversimplistic and leads to the view that obesity is the individual’s fault and is therefore their responsibility to remedy. These views are grounded in individuals’ beliefs around health and contribute to weight bias and stigma. In the present study, participants (n = 143) completed a cross-sectional survey which explored views around weight and health and whether weight bias or stigma differed based on demographic characteristics, weight status, and prior experience of weight stigma. Results indicate differences in the way individuals living with overweight and obesity are viewed in comparison with those of a healthy weight, with the former viewed in a more negative light. Interestingly, while women presented with higher weight bias scores (p = 0.036), men scored higher for externalised weight stigma (p = 0.001). Weight status was seen as an important factor contributing to overall health. These results demonstrate that weight bias and stigma are prevalent and highlight the need for further measures to reduce stigmatising views of people living with overweight and obesity. Full article
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