In this study, 421 residents of Fasa were examined, of whom 294 were women (69.8%) and 127 were men (30.2%). Mean age of the participants was 37.3 ± 11.5 years old and their mean BMI was 25.1 ± 5.1. Their demographic characteristics are presented in Table 1. Some of these variables were significantly correlated with fast food intake; e.g., fast food intake was higher in those with low income (p= 0.005) or unstable income (p = 0.023). Mean age of fast food consumers was 36.2 ± 11.9 years old and that of non-consumers was 38.3 ± 11.1 years old (p = 0.056).
Based on the findings, 49 persons (11.6%) had a membership card in fast food restaurants, indicating a tendency for the repeated intake of fast food in the future. Different types of sandwich and hot dog had the highest rate of intake (60.8%, n=256). This was followed by pizza (n=147, 34.9%) and other ready-made meals such as snacks, fried chicken, French fries, and other fried foods (n=80, 19.0%). Among fast foods, sandwiches (43.3%, n=182) and pizzas (27.1%, n=114) ranked the first and second in that order of their consumption. Steak ranked the least in the studied population (3.8%, n=16). Moreover, 249 people (82.9%) consumed sauces with fast food and 281 (66.7%) drank soft drinks with it.
Of all the studied individuals, 286 people (67.9%) had fast food for dinner, whereas 113 people (26.8%) had it for lunch. Also, 22 people (5.2%) had fast food for breakfast or supper. In addition, 304 people (72.2%) consumed fast food with their family, suggesting that the consumption of these foods is institutionalized in families. Also, 96 people (22.8%) had fast food with friends and 21 (5.0%) had it alone. The motivation for fast food was enjoyment and fun for 280 people (66.5%). Furthermore, 36 people (8.6%) had fast food owing to the ease of access and low price, and 116 (27.6%) consumed it because they were busy and had little time. The place of consumption was outside the house for 233 people (55.3%) and in the house for 188 people (44.7%). Also, 292 people (69.4%) were completely aware of the ingredients in the fast foods and 381 (90.5%) were aware of the harmful nature of these ingredients. Moreover, 321 (76.2%), 90 (21.4%), and 10 (2.4%) mentioned their priority factors in choosing such food as hygiene, diversity, and price, respectively. The cost of buying fast food was less than IRR 50,000 per week for 275 (65.3%) and more than IRR 100,000 per week for 40 (9.5%). The results showed that 16 people (3.8%) consumed fast food more than twice a week, 107 (25.4%) once or twice a week, 88 (20.9%) once or twice a month, and 210 (49.9%) less than once a month. Therefore, based on the definitions, 16 people (8.3%) were excessive users, 295 (70.8%) were low users, and the rest were moderate users. Findings of HELIA are presented in Table 2.
Table 3 compares the mean HELIA scores of consumers and non-consumers. Results revealed that mean HELIA was significantly lower in consumers (68.16 ±23.85) than non-consumers (73.15 ± 20.15) (p = 0.021). The same was true about the subscales of reading, appraisal, and decision-making (p < 0.001, p= 0.039, and p = 0.011, respectively).
Also, based on Pearson’s correlation, a significantly negative correlation existed between health literacy and fast food intake (i.e., multiple times a week, once or twice a week, once or twice a month, and less than once a month) (r = -0.108, p = 0.026). Higher health literacy correlated with a lower level of fast food intake, which was also true for the subscales of reading (r = -0.176, p < 0.001) and decision-making (r = -0.115, p = 0.018).
As noted before, the HELIA score is classified as inadequate, problematic, sufficient, and excellent. Logistic regression showed that by increasing the level of HELIA score compared to the group belonging to the inadequate level, the preventive effect of health literacy on fast food intake was also increased.
The odds of fast food intake in the groups with problematic, sufficient, and excellent health literacy was 0.693 times (p = 0.253), 0.616 times (p = 0.076), and 0.554 times (p = 0.034) compared to the group with inadequate literacy.
As already mentioned, the HELIA score was lower in the consumers than non-consumers. In other words, health literacy was a factor preventing the intake of fast food. Logistic regression analysis, in which fast food intake was the output variable, showed that per 1 score increase in health literacy, the odds of fast food intake was reduced by 0.990 with the CI of 0.981-0.998. However, this relationship must be corrected due to the existence of confounding variables. By removing the confounding variables one by one, this relationship still holds; even when all confounding variables are placed in the model, the preventive relationship of health literacy and fast food intake persists (OR = 0.990, 95%CI = 0.981-0.999) (Table 4).
In the previous analysis, reading, appraisal, and decision-making abilities had a preventive effect on fast food intake. The multivariate regression analysis showed that, after removing the effect of confounding variables, the ability of reading (R = 0.985, 95%CI = 0.975 – 0.993) and decision-making (OR = 0.986, 95%CI = 0.072 – 0.999) still had preventive effects on fast food intake (Table 5).