Understanding Emotional Eating in Obesity: Demographic Associations, Gender Differences, and BMI-Based Prediction

The term emotional eating refers to eating behavior due to emotional state and not physiological hunger. In many cases, obesity patients tend to indulge in emotional eating. This cross-sectional study investigates whether body mass index is a predictor of emotional eating in obese individuals, if there are any differences between male and female participants in relation to their emotional eating behavior, and also assesses the relative effect of gender, age, and body mass index on the emotional eating behavior through a neural network. Purposive sampling was used to select 250 obese participants (125 male and 125 females) with a body mass index above 30 kg/m2. BMI significantly and positively predicted emotional eating, B = 0.339, β = .176, t = 2.81, p = .005, but explained only 3.1% of the variance, F(1, 248) = 7.90, p = .005. Women (M = 27.02, SD = 2.45) reported significantly higher emotional eating than men (M = 23.06, SD = 5.45), t(172.39) = −7.43, p < .001, 95% CI [−5.02, −2.91], a large difference (d ≈ 0.94). In the neural network, gender was the most important predictor (normalized importance = 100%), followed by BMI (24.1%) and age (4.7%), although predictive accuracy was modest (relative error = .818 for training and .827 for testing). Findings suggest that, within an obese sample, gender distinguishes emotional eating more strongly than BMI does. Weight-management programs may therefore benefit from gender-sensitive screening and support for emotional eating.

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Publication Details

Journal
Journal of Language Literature & Social Affairs
Published
2026-10-27
DOI
https://doi.org/10.63056/jllsa.2.10.2026.421
Primary Topic
Eating Disorders and Behaviors
Type
article
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article

Understanding Emotional Eating in Obesity: Demographic Associations, Gender Differences, and BMI-Based Prediction

Iram Naz, Samra Rani, Hamyle Javaid, Nimra Shahzadi
Journal of Language Literature & Social Affairs
Eating Disorders and Behaviors
article

Understanding Emotional Eating in Obesity: Demographic Associations, Gender Differences, and BMI-Based Prediction

Iram Naz, Samra Rani, Hamyle Javaid, Nimra Shahzadi
article en

Abstract

The term emotional eating refers to eating behavior due to emotional state and not physiological hunger. In many cases, obesity patients tend to indulge in emotional eating. This cross-sectional study investigates whether body mass index is a predictor of emotional eating in obese individuals, if there are any differences between male and female participants in relation to their emotional eating behavior, and also assesses the relative effect of gender, age, and body mass index on the emotional eating behavior through a neural network. Purposive sampling was used to select 250 obese participants (125 male and 125 females) with a body mass index above 30 kg/m2. BMI significantly and positively predicted emotional eating, B = 0.339, β = .176, t = 2.81, p = .005, but explained only 3.1% of the variance, F(1, 248) = 7.90, p = .005. Women (M = 27.02, SD = 2.45) reported significantly higher emotional eating than men (M = 23.06, SD = 5.45), t(172.39) = −7.43, p < .001, 95% CI [−5.02, −2.91], a large difference (d ≈ 0.94). In the neural network, gender was the most important predictor (normalized importance = 100%), followed by BMI (24.1%) and age (4.7%), although predictive accuracy was modest (relative error = .818 for training and .827 for testing). Findings suggest that, within an obese sample, gender distinguishes emotional eating more strongly than BMI does. Weight-management programs may therefore benefit from gender-sensitive screening and support for emotional eating.

Journal of Language Literature & Social AffairsVol. 2(10)
University of Gujrat (PK)
Openalex Percentile: Top 8%
Eating Disorders and Behaviors
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Understanding Emotional Eating in Obesity: Demographic Associations, Gender Differences, and BMI-Based Prediction — Iram Naz, Samra Rani, et al. · Journal of Language Literature & Social Affairs (2026) | TGRS Research Map | TGRS