A systematic review of studies on socioeconomic inequalities in dietary intakes associated with weight gain and overweight/obesity conducted among European adults

Abstract

This Review examined socioeconomic inequalities in intakes of dietary factors associated with weight gain, overweight/obesity among adults in Europe. Literature searches of studies published between 1990 and 2007 examining socioeconomic position (SEP) and the consumption of energy, fat, fibre, fruit, vegetables, energy-rich drinks and meal patterns were conducted. Forty-seven articles met the inclusion criteria. The direction of associations between SEP and energy intakes were inconsistent. Approximately half the associations examined between SEP and fat intakes showed higher total fat intakes among socioeconomically disadvantaged groups. There was some evidence that these groups consume a diet lower in fibre. The most consistent evidence of dietary inequalities was for fruit and vegetable consumption; lower socioeconomic groups were less likely to consume fruit and vegetables. Differences in energy, fat and fibre intakes (when found) were small-to-moderate in magnitude; however, differences were moderate-to-large for fruit and vegetable intakes. Socioeconomic inequalities in the consumption of energy-rich drinks and meal patterns were relatively under-studied compared with other dietary factors. There were no regional or gender differences in the direction and magnitude of the inequalities in the dietary factors examined. The findings suggest that dietary behaviours may contribute to socioeconomic inequalities in overweight/obesity in Europe. However, there is only consistent evidence that fruit and vegetables may make an important contribution to inequalities in weight status across European regions.

Social Determinants of Risk and Outcomes for Cardiovascular Disease

“…219 Socioeconomic gradients exist for multiple health behaviors over the life course, and the combination of several unhealthy behaviors adds up to explain a large part of the socioeconomic health gap. Smoking, poor diet, inactivity, obesity, and medication nonadherence tend to be more prevalent among individuals of low SEP. [220][221][222][223][224][225] Furthermore, SEP in childhood helps account for unhealthy behaviors and health risk in the adult years. For example, a British cohort study that followed up subjects from birth to 66 years of age found that both childhood and adult SEP (ie, father's occupational class and mother's education) accounted for a significant portion of health inequalities in mortality risk by shaping exposure to smoking and other risk behaviors.…”

Food neophobia associates with lower dietary quality and higher BMI in Finnish adults

“…Finally, we conducted a two-way ANOVA to explore associations and potential interactions of the FNS score level and educational level (fixed factors) and the variables listed above, again separately in women and men. We performed this analysis to separate the effects of food neophobia from the effects of education (as a proxy measure for socio-economic status), because we assumed socio-economic position to be associated to food neophobia (12) , consumption of vegetables (35) and BMI (36) . Women and men were analysed separately for associations of FNS scores with the other variables because the genders differed significantly in age (t test, t (1910) = − 8·93, P < 0·001) and educational level (Pearson χ 2 ð1Þ = 55·82, P < 0·001): women were, on average, younger and more highly educated than men (Table 1).…”

The contribution of three components of nutrition knowledge to socio-economic differences in food purchasing choices

“…It is well established that those with lower levels of income and education make food choices less consistent with dietary guideline recommendations compared with their more affluent or educated counterparts (1)(2)(3) . The resulting poorer dietary profile of those of low socioeconomic position (SEP) may contribute to their higher rates of morbidity and mortality for many health conditions, including type 2 diabetes (4,5) , heart disease (6)(7)(8) , obesity (9)(10)(11) and stroke (6,12) .…”