This study aimed to estimate disparities in fruit and vegetable intake between groups at the intersection of educational level and gender in northern Sweden, and to assess the discriminatory accuracy of the intersectional groups. Substantial differences between intersectional groups were found in the prevalence of inadequate intake of fruits and vegetables combined, and separately. Gender made a greater contribution overall to the inequalities than education did, except for fruit intake where little to no difference was seen between the two referent disparities. Variations in direction, magnitude and significance were seen in the excess intersectional disparities across outcomes, suggesting a complex intersectional pattern for these related but distinct dietary outcomes. The discriminatory accuracy of the covariates and gender and education was moderate and suggested an importance of these two inequality dimensions, but consideration of their cross-classification did not contribute to any additional discriminatory power.
The finding that the referent disparity for gender consistently explained a large portion of the joint disparity is in line with previous research indicating that women have in general a higher fruit and vegetable consumption than men (6, 20, 21), and healthier behaviors overall (13, 17-19). Although to a lesser extent, the referent disparity for education also explained a substantial fraction of the joint disparities. This is consistent with the literature on educational inequalities in fruit and vegetable consumption (6-10, 14, 15), and other types of health behaviors (11-13). Several potential mechanisms have been proposed to explain this relationship between education level and health behaviors (16).
The finding that the excess intersectional disparity varied greatly across outcomes illustrates the potential usefulness of intersectional approaches in epidemiology. The intersection of multiple disadvantages for fruit and vegetable intake appeared to be associated with a unique pattern of consumption not entirely explained by the addition of gender and education. Specifically, for combined intake of fruits and vegetables, the intersection of male gender and low education appeared to be unexpectedly protective against unhealthy dietary patterns.
As pointed out by Jackson et al. (30), it should also be noted that the existence and magnitude of the joint disparity should not be dismissed if the excess intersectional disparity is non-existent or negative. Even if a group does not display any excess intersectional disparity, it can still experience the sum of the two referent disparities. In this study, the joint disparity in consumption of fruits, vegetables, and fruits and vegetables between high educated women and low educated men, although inconsistently affected by the excess intersectional disparity, was still great in magnitude; inadequate intake of fruits and vegetables combined was 34.59 pp more prevalent for low educated men than for high educated women.
The discriminatory accuracy of the intersectional groups for identifying inadequate intake of fruits and vegetables as measured by the AU-ROC was close to - but below - 0.7 and could therefore be considered moderate. Most importantly, the lack of additional discriminatory power of the cross-classification found in this study is recurrent in empirical studies using intersectional approaches to study inequalities in Sweden (34, 38, 39). Those two findings would be commonly interpreted as evidence in favor of universal rather than targeted intervention in the context of proportionate universalism. For the present study, this would suggest that the targeting of specific intersectional groups is not suitable as the sole guiding principle for health promotion planning. However, while this interpretation is straightforward when the goal is general health promotion in the population, e.g. increase fruit and vegetable intake, it is not as evident when the goal is promotion of equity in health, e.g. reducing inequalities in fruit and vegetable intake.
Moreover, the AU-ROC method comes from signal detection theory (50), and there is no clear-cut threshold that would label a discrimination as high enough for intersectional approaches in epidemiology. Indeed, examinations of both novel and traditional risk factors for coronary heart disease have yielded similarly disappointing results when it comes to discriminatory accuracy (51), despite many of them being established in clinical practice. While discriminatory accuracy represents a necessary complement to means-centric examinations of health inequalities, and to traditional epidemiology more generally, a cautious interpretation of its implications specifically in the context of equity promotion is therefore warranted.
Further research and public health relevance
To our knowledge, this Swedish study is the first of its kind investigating disparities in fruit and vegetable consumption across intersectional groups defined by gender and education. The intersectional approach was helpful to shed light on the complex inequality patterns of inadequate intake of fruits and vegetables. In addition, as the estimated disparities are additive rather than relative measure of inequality, they can be used to determine the absolute benefits in population health if a disparity were to be eliminated (30).
The findings from this study will hopefully help to give a more nuanced understanding of the structural patterning of disparities in diet, and thereby improve the effectiveness of equity-promoting public health interventions and policies. Although the moderate discriminatory accuracy in this study could suggest that universal interventions and policies might be more effective for improving diet quality in Sweden, there is a risk that they would mostly benefit those already advantaged, and could therefore contribute to widening inequalities in health (52). A combination of universal and targeted measures to improve diet quality could be a way forward, in line with proportionate universalist principles (53). This study could then contribute to giving guidance as to where are the largest disparities, and what are the most relevant groups to prioritize.
Future research on diet quality could consider operationalizing groups at the intersection of gender, education, and other inequality dimensions. This could help identify intersectional groups with higher discriminatory accuracy and facilitate targeted interventions to improve health equity.
Strengths and limitations
Since random sampling procedures were used to draw a sample from the general population, selection bias is limited to some extent. However, the response rate varied between 42.4% for Västerbotten (46) and 45.8% for Jämtland/Härjedalen (44). Since most people contacted to answer the survey did not answer it, it is unknown whether the final sample is truly representative of the target population.
It is also not known to which degree the results can be generalized outside of Sweden. Indeed, the implications of the intersection of gender and education can be expected to differ between contexts. In addition, the results cannot be generalized to other countries and settings with different patterns of health and nutrition. The socioeconomic and gender inequalities in fruit and vegetable intake observed in this Swedish sample might be very different in other social, economic and cultural settings (54-56).
The use of gender as one of the two variables for the operationalization of the intersectional groups can be questioned. Since this study was interested in investigating social inequalities in health behaviors, and not potential biological inequalities in health, gender seemed more appropriate as designating a social construct rather than a biological construct. However, what is measured by available register data is biological sex recorded at birth, and thus might not always represent gender identity accurately. The adequateness of using one term or the other in epidemiology has been discussed elsewhere (57).
It was assumed that the frequency of fruit and vegetable intake reported was synonymous with the amount consumed. Reporting bias could be a concern here. Over-reporting may, for example, have occurred more in those with higher education since they might be more conscious of the existing recommendations for fruit and vegetable intake. Under-reporting may have occurred among those with relatively lower education due to potentially weaker health and nutrition knowledge (58). In contrast, the exposure variables and the potentially confounding variables came from high-quality register data and therefore were not affected by self-report bias.
Since this study is cross-sectional in design, it cannot be used to determine causality, even though reverse causality is unlikely. In addition, despite adjusting for potential confounders, it is not impossible that some residual confounding may subsist. However, the associations found between intersectional group and prevalence of inadequate fruit and vegetable intake are not easily affected by confounders. Indeed, most third variables such as income or occupation are likely to be determined in part by gender and education, and if included would risk over-adjustment and result in under-estimation of the inequalities.
Finally, the method described by Jackson et al. (30) allows to quantitatively investigate disparities at the intersection of multiple social positions and identities, in a way that corresponds to the different possibilities for an intersectional group to experience disadvantage (24). However, this approach limits the number of social positions that can be considered simultaneously (30). In addition, it measures additive interactions, whereas the AU-ROC is based on multiplicative interactions. This may partly explain why measures of discriminatory accuracy did not identify any intersectional interaction from Model 2 to Model 3, whereas substantial excess intersectional disparities were estimated for two out of the three outcomes.