Social inequalities shape diet composition among urban Colombians: The Colombian Nutritional Profiles cross-sectional study

Abstract

Objective: To explore the influence of socioeconomic position on habitual dietary intake in Colombian cities.

Design: We conducted a cross-sectional, population-based study in five Colombian cities. Dietary intake was assessed with a 157-item semi-quantitative food frequency questionnaire previously developed for the Colombian population. Nutrient analysis was performed using national and international food composition tables. Socioeconomic position was assessed with two indicators: a government-defined, asset-based, household-level index called socioeconomic stratum (SES) and, among adults, highest educational level attained.

Setting: The five main urban centers of Colombia: Bogotá, Medellin, Barranquilla, Cali and Bucaramanga.

Participants: Probabilistic, multistage sample of 1865 participants (n=1491 for analyses on education).

Results: For both sexes, increasing SES was associated with a lower consumption of energy (p-trend <0.001 in both sexes), carbohydrates (p-trend ˂0.001 in both sexes), sodium (p-trend=0.005 in males, <0.001 in females), saturated fatty acids (p-trend <0.001 in both sexes) and among females, cholesterol (p-trend=0.002). More educated men consumed significantly less energy and carbohydrates (p-trend=0.036 and ˂0.001, respectively). Among men, intake of trans fats increased monotonically with educational level, being 21% higher among college graduates relative to those with only elementary education (p-trend=0.023). Among women, higher educational level was associated with higher MUFA intake (p-trend=0.027).

Conclusions: SES and educational level are strong correlates of the usual diet of urban Colombians. Economically deprived and less educated segments of society display dietary habits that make them vulnerable to chronic diseases and should be the primary target of public health nutrition policies.

Keywords: Diet; Education; Inequality; Risk Factors; Socioeconomic position; Urban.

Fig. 1

Estimated intake of macronutrients by socio-economic stratum (Panel A) and educational level (Panel B) (n 1491 for Panel B). Each coloured area represents the proportion of total energy intake from the corresponding macronutrient. ^† P < 0·001 v lowest category, ^‡ P < 0·01 v lowest category. , carbohydrates; , lipids; , protein

Fig. 2

Estimated contribution of different dietary fat types to total energy intake by socio-economic stratum (Panel A) and educational level (Panel B) (n 1491 for Panel B). SFA, saturated fats; MUFA, monounsaturated fats; PUFA, polyunsaturated fats. ^† P < 0·001 v lowest category, ^‡ P < 0·01 v lowest category. , PUFA; , MUFA; , SFA

Fig. 3

Estimated dietary intake of trans fats by age group (Panel A) and socio-economic stratum (Panel B), and dietary intake of Na by socio-economic stratum (Panel C), and educational level (Panel D) (n 1491 for Panel D). In all panels, significant P-values for the comparison v the reference category are indicated by an asterisk. This test involves all participants (male and female) in each category. In Panel A, the reference category is age 12–17, in Panels B–D, the reference category is the lowest. , male; , female