Objectives: Given the limitations of body mass index (BMI) as a metric and the lack of data on the relationship between various anthropometric indices of obesity and immune fitness (IF), this study aimed at exploring the possible association between various anthropometric indicators and the immune fitness among an adult sample of the Saudi population residing in Makkah. Methods: A structured self-reported questionnaire, with questions covering age, sex, anthropometric and immune fitness assessment data, was distributed online to a convenience sample of target population. The Immune Status Questionnaire (ISQ) was utilized to assess respondents’ IF over the past 12 months, while perceived momentary immune fitness (PMIF) was measured using a single-item scale. A total of 1135 responses were included in the study. Results: Overall, 530 male (46.7%) and 605 female (53.3%) respondents were included in the analysis. Of these, 478 (42.1%) had a normal BMI, and 343 (30.2%) were classified as overweight, 184 (16.2%) as obese, and 130 (11.5%) as underweight. Participants with reduced ISQ score (<6) were more likely to be underweight (p < 0.001), have a high weight-adjusted waist index (WWI) (p = 0.035), and exhibit an increased conicity index (C index) (p = 0.037) compared to those with an ISQ score ≥ 6. After controlling for age and sex, weight (p = 0.003), height (p < 0.001), and WWI (p = 0.01) were found to have significant correlations with past-year IF, while only height (p = 0.004) showed a significant positive correlation with PMIF. A multiple linear regression analysis revealed that sex and height and waist circumference (WC) were significant predictors of IF. Specifically, males and those who were taller had higher IF scores. Whereas individuals with high-risk WC values reported lower IF scores than those with low-risk WC. Conclusions: Sex (male) and anthropometric measures (lower WC, and taller height) were the most informative predictors of higher IF scores. The findings highlight the association between anthropometric measures and IF. A deeper understanding of these associations can inform the development of targeted interventions aimed at improving IF and overall health outcomes.
Azzah S. Alharbi (2026) studied this question.