Artigos

Introduction

Food insecurity is the condition of not having reliable access to sufficient affordable and nutritious food without compromising other basic human needs. Life circumstances related to poverty and low-income increase the vulnerability to food insecurity, and have implications for the individual and society’s health and nutrition as a whole 1, 2.
In 2020, approximately 690 million habitants worldwide lived in hunger 3, an extremely serious degree of food insecurity 4. In Latin America and the Caribbean, 22.1% of the population was in moderate food insecurity, and 9.6% in an extreme degree 3. In Brazil, the prevalence of food insecurity in 2020 was 55.2% 5. This estimate is consistent with the consequences of the COVID-19 pandemic and the increasing rates of food insecurity previously observed between 2013 and 2017 (24.0% to 51.0%) 5. This scenario is related to major economic and political instabilities that stem from governmental austerity measures that reduce funding for many social and food security policies 5, 6. This instability has been leading to a decrease in income and an increase in unemployment, inflation rates, and food prices since 2014 7.
Food insecurity is a double burden for pregnant women, as it affects not only the mother but also her child 8. The impact of food insecurity on fetal development can lead to birth defects 9, 10, shorter pregnancy duration, low birth weight, restriction of intrauterine growth, and neonatal mortality 9, 11, 12. Furthermore, the long-lasting effects of suffering hunger in pregnancy and unfavorable outcomes in childhood and adulthood are well known 8. Food deprivation leads to metabolic changes 8, 12 that subsequently promote energy expenditure reduction, with abdominal fat distribution, gestational diabetes 10, higher rates of school absenteeism 8, and a cycle of lower educational and income levels across generations 13, 14.
It is remarkable that food insecurity results from social deprivation. Further, it was associated in different studies with socioeconomic vulnerability indicators such as low levels of income and education, unemployment, and lack of sanitation and water treatment 13, 14. Social and economic backgrounds are often reproduced across generations. In that sense, the child’s education is highly correlated with his or her parents’ educational level. That means a child’s educational success is to some degree predetermined by the level of education of his or her parents, considering current social mobility 14.
Social mobility refers to an approach in the life-course perspective that compares the socioeconomic patterns in different life periods 15. Those can result either in immobility, as well as in upward or downward socioeconomic mobility. Different variables have been applied to construct social mobility models, namely income, occupation, and education 16. The educational mobility models have their conceptual basis built on a wide sum of influences combining expositions in childhood, adolescence, and adulthood that lead to certain conditions on adult life 15, 17, 18.
Indeed, education is a determinant of social mobility and lifts individuals and their families out of poverty. Food insecurity and education are bidirectionally related 19. Children with food insecurity and malnutrition in early childhood have limitations in cognitive growth and poor educational performance with possible effects on adult life 20. On the other hand, a measure of human capital is associated with the individual's productivity and efficiency. Thus, education has direct and broad returns for family members and society with increased income, improved health, and decision-making 21.
Most studies that investigated socioeconomic determinants of food insecurity focused on current information measures, such as income and education. Those studies investigating parents’ education are restricted to children13, whereas measures combining childhood and adolescent exposure considering the parental socioeconomic background, giving a life course perspective in adulthood, are poorly explored, mainly in relation to food insecurity 22.
The studies that evaluated the relationship of intergenerational educational mobility focused on chronic diseases such as hypertension, health-related behaviors 23, and general health status 24. Few studies have examined the intergenerational effects on social mobility and food insecurity regarding economically vulnerable women from low- and middle-income countries 25. Investigating the intergenerational transmission of education along with the analysis of food insecurity might assist policies aimed at reducing social vulnerability across generations 22.
This information may be useful for a better understanding of the relations between current education, and mainly the intergenerational education mobility of pregnant women in relation to their father and mothers with food insecurity. Considering that this condition is difficult to overcome during the lifetime of the affected individuals and can persist over generations 22, this study aims to evaluate the association between food insecurity and intergenerational educational mobility of pregnant women.


Methods and Materials
Design
This is a cross-sectional study in a prospective cohort named “Study of life and health conditions of pregnant and postpartum women”. The study was conducted with pregnant women who underwent prenatal care in public primary health care facilities of the Brazilian Unified Health System (SUS) in the city of Colombo, state of Paraná, between February 2018 and September 2019. The SUS aims to guarantee access to universal and free healthcare throughout the national territory for Brazilians, through a set of health actions and services provided by federal, state and municipal public bodies and institutions, in which private institutions can act in a complementary way. 26

Context and Sample
The municipality of Colombo is located in the state of Paraná, southern Brazil. It has an average size with an estimated population of 240,840 inhabitants as of 2018 27 and a maternal mortality rate of 27.05/100,000 live births (2017). In 2010, the Gini’s index was 0.4196 and o Human Development Index was 0.733.27 In 2018, the period of data collection, the municipality had 24 health units. In 2018, the period of data collection, the municipality had 24 health units.
In 2017, according to an estimate by the Municipal Health Department of Colombo, 3,807 women underwent prenatal care in public primary health care facilities. For the sample definition, the expected prevalence of food insecurity was 50.0%—to maximize the sample size and allow investigating multiple outcomes in the study—with a margin of error of 4 percentage points and 95% of confidence level, resulting in a minimum sample of 520 participants. Considering a percentage of refusals of 30.0% the sample comprised 676 pregnant women. We observed the presence of incomplete questionnaires during the consolidation of fieldwork, and, to keep the number of complete questionnaires close the minimum sample estimated (n=520) another 59 (11.3%) pregnant women were selected (n=735). Sample size calculations were performed using the OpenEpi version 3.01 online application. Considering our analytical sample of 602 pregnant women, keeping the 95% level of confidence, a prevalence of 13.8% could be found in those with food security, and 22.6% among those with some degree of food insecurity, resulting in a prevalence ratio (PR) of 1.64.
The sample was proportionally distributed according to the number of pregnant women registered in each health unit and they all were consecutively invited at the prenatal appointment, the additional sample followed the proportional distribution according to health units. The following inclusion criteria were adopted: being pregnant and undergoing prenatal care in the public primary health care facilities. The interviews were performed in the waiting rooms for the routine prenatal visit.

Variables
The demographic variable investigated was age group (in years, < 20, 20-29, ? 30). The investigated socioeconomic variables were level of education (in years of study, ? 10, ? 11), and per capita household income in Brazilian reais (BRL). Income was classified in three tertiles: 1st tertile R$ 0.00 to R$ 475.00; 2nd tertile R$ 476.00 to R$ 750.00; 3rd tertile R$ 751.00 to R$ 3,000.00. The Brazilian minimum wage in 2018 and 2019 ranged from R$ 954.00 to R$ 998.00, equivalent to USD 228 to USD 238.5. The value of 1 BRL on October 1st, 2019 was USD 0.239.
Food insecurity was investigated using the Brazilian Food Insecurity Scale (EBIA) 28. The EBIA is composed of 14 questions about the household food situation in the 90 days prior to the survey, with 5 questions exclusively for households with individuals under 18 years old. For each question answered “yes”, 1 point was given.
For this study, we adopted the cutoff points proposed by Interlenghi et al. 29, based on a latent class factor analysis for identifying the optimal cutoffs for EBIA in a nationwide representative sample. The results indicated that households with an overall score of 1 were closer to those scoring negative on all items, meaning only one question replied as “yes” on the scale was not enough to classify the household as having food insecurity 28. Thus, those with two or more positive answers to EBIA questions, were considered food insecurity.
The educational level of the pregnant woman was classified as low when there were less than 11 years of education. In 2006, there was a change in the number of years to complete high school in the Brazilian Education system, going from 11 to 12 years. In this study, we had participants from both systems, and, after collecting the data, we standardized for 11 years of study as complete high school, 0-8 as elementary school, and above 11 years as beginning higher education. In this way, women with 12 years were equivalent to 11 years in the previous system. The cutoff point of 11 years was established because a small proportion of women had 12 years of education or more (n=55, 10.1%), equivalent to having completed one year or more of a college degree in Brazil.
The parental education was categorized according to the parents’ median years of schooling according to pregnant women age 17:
1) for each range of pregnant women’s age, the median years of schooling of their fathers and mothers were estimated, then:
2) the education of father and mother were classified as low when their father or mother’s years of education was lower or equal to the median, and high in case of values above the median.

Two measures of intergenerational education mobility were constructed based on the combination of the mother's or father's and the pregnant woman's educational level: 1) Stable-low: when the educational level of the parents and that of the pregnant woman were both low; 2) Downward: when the educational level of the parents was high and that of the pregnant women was low; 3) Upward: when the educational level of the parents was low and that of the pregnant women was high; 4) Stable-high: when the educational level of the parents and that of the pregnant women were both high.
For the measures of education of the pregnant woman's parents, as well as measures that combined such information (mobility), the category “missing” was added. This insertion considered that the lack of knowledge of this information is not randomly distributed: the median education level of pregnant women who did not know the educational level of their parents was lower than those who were able to inform it.

Procedures
All interviewers received training and the data collection instrument was submitted to pre-test stages in different health units. Also, a test was applied in one of the participating health care units. The pilot study was conducted at all stages of the research. Participants in the pre-test, instrument test, and pilot study phases were not included in the sample.
Quality control was carried out in 11.6% (n=70) of the questionnaires, through telephone contact with the participants, using a reduced version of the instrument with four questions: full name, age, education, and full address of the participants. Small differences were observed concerning the length of study (1 year of difference in 3 cases), and the information was corrected on the dataset. The intraclass correlation coefficient obtained for the variable was 0.99 (95%CI 0.98 – 1.00). The other items informed in the interview coincided in both moments.

Statistical Analyses
Variables were described using means, standard deviation, number (n), percentage (%), and 95% confidence interval. For data analysis, only records with complete information on the study variables were considered, using the listwise deletion procedure.
The proportion of variance of pregnant women’s education explained by parents’ educational attainment and between both parents was estimated through the coefficient of determination, measured through R-squared linear regression models, which is an estimate of how well the regression predicts the real data points. For this analysis we used the discrete variables of years of schooling.
The association of food insecurity and the variables: age group, pregnant women’s own education, father's education, mother's education, and pregnant woman’s intergenerational educational mobility regarding father’s and mother’s level of education were investigated by unadjusted Poisson’s regression models, with robust adjustment of the variance. The prevalence ratios (PR) and 95% confidence intervals (95%CI) of food insecurity and p-value were estimated using Wald’s test. The dichotomized variables of the median years of schooling of the 1) father; 2) mother; and the resulting intergenerational mobility education of pregnant women’s considering their 3) father; and 4) mothers were not adjusted in the analysis. The association of these variables with the outcome was not adjusted for the age of the pregnant woman, because, in constructing the measures of parents' education levels and intergenerational education mobility, the age range of the pregnant woman was taken into account: for each age range of pregnant women, the median education level of both the father and the mother was calculated. Considering those aspects, only the association between food insecurity and the pregnant women own education was adjusted for age.

Ethics
This research was approved by the Human Research Ethics Committee of the Health Sciences Sector of the Federal University of Paraná according to opinion number 2405347 on 11/29/2017 and was conducted within the ethical standards required by this committee. All pregnant women participating in the study signed the Free and Informed Consent Form (FICF) and those under the age of 18 signed the Free and Informed Assent Term while their legal guardians signed the FICF.



Results
Sample characterization
A total of 735 women were considered eligible, of which 604 (82.2%) responded to the questionnaire, and 602 presented complete data for all variables. The mean age of participants was 26.0 years old (95%CI 25.5-26.4). Most pregnant women were between 20.0 and 29.0 years old (62.3%), with less than 11 years of education (56.2%) (Table 1).
While among pregnant women 43.8% had 11 years or more of education, 77.9% of their fathers and 82.9% of their mothers had less than 10 years of schooling. (Figure 1).
The coefficient of determination (R-squared) of father and mother’s schooling on the pregnant woman’s schooling reached 0.028 and 0.065, respectively, and between both parents was 0.241. Pregnant women remained at a low education level as their fathers and mothers (stable-low) in 21.8% and 28.7% of cases, respectively (Table 1).

Prevalence of food insecurity and association with schooling

The prevalence of food insecurity was 28.2% (95%CI 24.7-31.8). Pregnant women with more than 11 years of schooling presented lower prevalence of food insecurity (RP 0.63 95%CI 0.48-0.83) (Table 2), that association remained significant after adjustment for age (RP 0.62 95%CI 0.47-0.82) (data not shown).

Association with intergenerational education mobility

The prevalence of food insecurity was higher among participants exhibiting stable-low mobility (PR 1.63, 95% CI 1.03-2.56) and among those unable to provide information on their father's educational attainment (PR 1.66, 95% CI 1.08-2.56). Pregnant women classified with downward (PR 1.72, 95% CI 1.12-2.63) or stable-low (PR 1.70, 95% CI 1.13-2.52) intergenerational education mobility, in comparison to those with stable-high educational mobility, demonstrated a higher prevalence of food insecurity (Table 2)


Discussion

This study examined the association between measures of education, and food insecurity in a sample of pregnant women from Colombo (Paraná State, Brazil) mainly under the perspective of intergenerational mobility. In our study pregnant women classified in the stable-low level of intergenerational education mobility in relation to both: father and mother, presented higher prevalence of food insecurity. While the downward intergenerational mobility was associated only in relation to their mother’s education.
Those findings highlight the importance of the improvements and maintenance high levels of education in pregnant women in relation to their parents, protecting against food insecurity. In the urban context, the effect of education on food insecurity acts through proxies such as employment, family income and decision-making. These indicators influence the dimensions of access, use and availability of food security.30 Education is a major contributor to intergenerational income mobility and educational differences tend to persist across generations. Higher education increases the likelihood of better employment status, with more secure well-paying job. Also, education can provide better knowledge about nutrition and budgeting, which can help them make informed decisions about food. 31
The paths thought upward intergenerational education mobility is related to food insecurity are interconnected and can vary according to individual context, societal norms, and broader economic conditions. The effect of educational mobility is shaped for a range of family characteristics and includes ethnic origin, family size and structure, and socioeconomic and cultural background of the parents. In other hand, the intergenerational immobility can affect occupational status, which also has a high persistence rate among generations related to race, and migrant status, for example.32
Mostly, previous studies investigating associations between food insecurity and education rely exclusively on current education, showing gaps in exploring its association with parental education, mainly considering separately each parent, and in the adulthood13. A systematic review found higher food insecurity in pregnant women with black skin color, holders of social protection programs, and with low education levels. No information about pregnant women parent’s education, or intergenerational mobility was provided. 33 In fact, the relation of intergenerational educational mobility or parents of pregnant women education and food insecurity is unexplored on the systematic reviews about the theme 11, 33, 34, even when focused on high income countries35.
Furthermore, in our study, the prevalence of food insecurity was higher among women who were unable to provide information about their fathers’ education level. In most Brazilian studies on food insecurity, the father’s level of education is typically inferred indirectly through the schooling of the head of the family 13, 36. In families of pre-school children receiving cash transfer from the Bolsa Família Program from Viçosa (Minas Gerais, Brazil), only maternal education was associated with food insecurity. In addition, more than 15.0% of the mothers were unaware of the educational level of their child’s father 36.
Given the high number of households headed by women in Brazil - 40.5% in 201537 - and the expressive amount of birth certificate records lacking the father’s name, the inability to provide information about the father's education level may indicate his absence throughout the life course. This, in turn, can have adverse effects on the educational, economic, and socio-emotional well-being of the offspring over their lifetime 38. Households in which a woman is the family's head had a higher prevalence of food insecurity (15.3%) than those headed by men (10.8%). In situations of marriage dissolution, women represent the group at greatest risk for poverty.38
These findings underscore the relevance of including fathers' education in analyses, particularly given the higher rate of missing data on fathers' education in our study. This aspect should be attentively considered in other studies focusing on parental education, particularly those that rely solely on the highest level of education attained by one parent.
Another aspect may be related to the weaker predictive roles of the education of pregnant women and their parents, as opposed to the higher correlation between the years of schooling for the father and mother. Those results may be partially explained by the higher education improvements observed in Brazil at the beginning of the new century 17, 30, 39. Despite advances in Brazilian education in recent decades, access to higher education remains an important bottleneck in the educational system in the country, especially for children whose parents have lower education levels 40.
Still, the way in which the variable on parental education was constructed—considering the age of the pregnant woman—may have limited the comparison with other studies. However, it provides a more direct comparison between parents’ educational levels in different generations of women, considering the increase in education observed in Brazil in recent decades, a strategy used by other authors 17. The combination of other measures of social position, such as type of employment, would provide an additional explanation for the educational mobility of food insecurity. Furthermore, the low heterogeneity of the sample—most participants were undergoing exclusive prenatal care in public primary health care facilities —may not allow inferences from the data to other populations. Furthermore, the retrospective information used in this study is subject to memory bias, although education has a more stable characteristic in relation to other socioeconomic variables.
Even though we had the option of working with the education variable in its continuous format, incurring higher rates of non-response, considering pregnant women’s parents, we built our mobility variables starting from a variable of education with two categories, classified as low and high education. The categorized variable allowed considering the high rate of non-response for education, creating the missing category, and estimating its association with food insecurity. In addition, the visualization of mobility between pregnant women and their parents is more intuitive with this format. Expanding the number of categories would decrease the capacity to identify significant associations.
We categorize food insecurity into two groups: 'yes' or 'no'. The tool used for assessing food insecurity, EBIA, allows for the evaluation of the degree of food insecurity 28, but not its continuity over the long term, as its usual recall period covers the three previous months. However, it's important to recognize that food insecurity encompasses both a temporal and an intensity dimension 41. Understanding these aspects can enhance our comprehension of how various intergenerational education indicators influence food insecurity. Advancing our understanding of the relationship between food insecurity and socioeconomic background may be facilitated by incorporating different variables and employing more complex models to evaluate both direct and indirect effects. Additionally, qualitative methods, such as in-depth interviews, can contribute to a deeper comprehension of the perceptions and dimensions involved.
This study is one of the first to explore the role of intergenerational educational mobility and food insecurity in Brazilian pregnant women, as well as to give information about how different measures of education were associated with food insecurity in pregnancy. The consistent association of food insecurity in pregnancy and the combination of intergenerational education mobility categories with high pregnant women own education attainment, reinforce the importance of pregnant women’s current education on food insecurity levels, as well as the probability of reducing the impact of the parents’ low schooling with increasing women’s education. Improving education is a powerful policy tool to combat the rise in social inequalities. The potential for expanding education is important not only to promote economic growth but also to interrupt the intergenerational transmission of poverty and reduce inequalities in opportunities, with the potential to impact future income 3.
Finally, considering the huge prevalence of food insecurity during pregnancy and its potential impact on unfavorable long-lasting effects in its different outcomes, which can be continued in the offspring, the importance of public policies to improve female education in a timely manner is highlighted. For example, expanding access to early childhood education (i.e., daycare centers) is an effective strategy for women’s entry or return to paid work and would also support those who desire to continue their education after giving birth 2, 21, 42, thus, contributing to obtaining better-paid jobs. Furthermore, it is necessary to strengthen the social protection mechanisms that promote greater employment stability, including access to paid and extended maternity leave, to reduce the impact of gender inequalities on food insecurity in pregnancy, and in the child's first years of life.


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