[Application of digital transformations of dietary microdata and factor analysis to study the nutritional patterns of breakfast and its significance in providing the nutritional value of the diet of adults]

Vopr Pitan. 2023;92(5):48-59. doi: 10.33029/0042-8833-2023-92-5-48-59. Epub 2023 Sep 26.
[Article in Russian]

Abstract

Eating disorders with skipping meals are considered as a risk factor for chronic non-communicable diseases. Frequent skipping of meals is associated with the risk of developing metabolic syndrome, type 2 diabetes, and obesity. Breakfast is considered to be the most important meal of the day. However, studies on the impact of skipping breakfast on the risk of overweight and obesity are highly controversial. The aim of this study was to analyze the prevalence of skipping the morning breakfast meal and its impact on the actual daily intake of nutrients and energy in the Russian adult population. Material and methods. The data from a sample survey of dietary intake conducted in 2013 by the Russian Federal State Statistics Service have been used. The analysis included adult respondents (19 years and older) in the amount of 163 000 people in 2 stages of the survey (in April and September). The dietary intake of all members of the surveyed households was studied using the 24-hour recall method. Since the survey questionnaires did not contain information about type of meals, therefore, with the help of binning in thзe SPSS program, time intervals of the maximum food energy intake by the respondents were established, which were taken as evidence of the main meals and snacks. Results. Of the main meals, the largest proportion of respondents skipped dinner (23.1%), then breakfast (13.0%), and the smallest proportion skipped lunch (5.7%).The proportion of men and women who skipped breakfast was 12.6 and 13.3%, respectively, a greater frequency of skipping breakfast was observed at a young age (19-30 years, 19.3%) and at an old age (75 years and older, 16.1%). With an increase in the average monthly income of a family, the percentage of those who skip breakfast increases. Adult members of families with many children (3 or more children), whose average per capita income is lower than those in families with 2 children, skip breakfast less frequently. The smallest share of people skipping breakfast was found in the North Caucasian and Southern districts, and the maximum in the Siberian and Far Eastern districts. Adults who skipped breakfast had a higher percentage of malnourished (BMI <18.5 kg/m2) and normal nutritional status (BMI 18.5-24.9 kg/m2). At the same time, the proportion of people who consumed breakfast was significantly higher in overweight people (25.0-29.9 kg/m2), and no differences were found among obese people. It is shown that skipping breakfast is accompanied by a decrease in the energy value of the daily diet by an average of 200 kcal. Despite the increase in the caloric content of the 2nd breakfast, afternoon snack and evening snack in absolute terms (р<0.01), there was no compensation for the loss of energy value in the absence of breakfast. A decrease in the absolute values of nutrient intake associated with a decrease in energy consumption was established. However, skipping breakfast showed a decrease in added sugar intake as a per cent of total calorie intake (12.1±8.6 vs 13.2±9.1%, р<0.01), while the contribution of other macronutrients to energy intake did not change significantly. In connection with the heterogeneity of the actual dietary intake of the population, factor analysis was used to describe the main food models of the breakfast using the principal component method. 6 factors were identified that determine the eating patterns of breakfasts and correlate with 2-4 individual food items of actual dietary intake. Conclusion. The results obtained are consistent in a number of positions with the literature data, in particular, indicating a decrease in daily energy consumption when skipping breakfast.

Keywords: adults; breakfast; breakfast food patterns; diet; skipping meals.

Publication types

  • English Abstract

MeSH terms

  • Adult
  • Aged
  • Breakfast*
  • Child
  • Diabetes Mellitus, Type 2*
  • Diet
  • Factor Analysis, Statistical
  • Female
  • Humans
  • Male
  • Nutritive Value
  • Obesity / epidemiology
  • Overweight
  • Young Adult