Next Article in Journal
Third-Line Antiretroviral Therapy: What Do We Do When the Appropriate Formulations Are Not Available?
Next Article in Special Issue
Body Composition and Cardiovascular Risk Factors in a Paediatric Population
Previous Article in Journal
Making Hardware Removal Unnecessary by Using Resorbable Implants for Osteosynthesis in Children
Previous Article in Special Issue
Determinants of Gender Disparity in Nutritional Intake among Children in Pakistan: Evidence from PDHS
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Moderators of Food Insecurity and Diet Quality in Pairs of Mothers and Their Children

by
Christine Aggeli
1,†,
Maria Patelida
2,†,
Maria G. Grammatikopoulou
2,*,
Ekaterini-Avrakomi Matzaridou
2,‡,
Marina Berdalli
2,‡,
Xenophon Theodoridis
1,
Konstantinos Gkiouras
1,
Angeliki Persynaki
2,
Kyriaki Tsiroukidou
3,
Theodore Dardavessis
4,
Christos Tzimos
5,
Dimitrios G. Goulis
6 and
Tonia Vassilakou
7,*
1
Department of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, GR-56429 Thessaloniki, Greece
2
Department of Nutritional Sciences & Dietetics, Faculty of Health Sciences, International Hellenic University, Alexander Campus, GR-57400 Thessaloniki, Greece
3
3rd Department of Pediatrics, Hippokration General Hospital of Thessaloniki, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, Greece
4
Laboratory of Hygiene, Social & Preventive Medicine and Medical Statistics, Faculty of Health Sciences, School of Medicine, Aristotle University of Thessaloniki, GR-56429 Thessaloniki, Greece
5
Northern Greece Statistics Directorate, Hellenic Statistical Authority, 218 Delfon Str., GR-54646 Thessaloniki, Greece
6
Unit of Reproductive Endocrinology, 1st Department of Obstetrics and Gynecology, Faculty of Health Sciences, Medical School, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, Greece
7
Department of Public Health Policy, School of Public Health, University of West Attica, Athens University Campus, GR-11521 Athens, Greece
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
These authors contributed equally to this work.
Children 2022, 9(4), 472; https://doi.org/10.3390/children9040472
Submission received: 8 January 2022 / Revised: 23 March 2022 / Accepted: 26 March 2022 / Published: 29 March 2022

Abstract

:
Research has suggested that maternal diet and characteristics may influence the diet of offspring during childhood. The present cross-sectional study aimed to assess the influence of distinct maternal characteristics and the diet quality of mothers on the prevalence of household food insecurity (FI) and the diet quality of children. A total of 179 mother–child pairs were recruited from two primary schools in the metropolitan area of Thessaloniki. The children were aged between 10 and 12 years old. Diet quality was assessed as the level of adherence to the Mediterranean diet (MD), with the use of the KIDMED for the children and the MedDietScore for the mothers. The household FI and the social and demographic characteristics of the mothers were also recorded, and anthropometric measures of both the mothers and their children were collected. Approximately ¼ (26.3%) of the pairs reported some degree of FI, with a greater prevalence (64.7%) within single-mother families. Moreover, FI affected the level of maternal MD adherence (p = 0.011). On the other hand, FI was decreased in households with a greater maternal educational level (OR: 0.25; 95% CI: 0.10–0.63) and conjugal family status (OR: 0.15; 95% CI: 0.87–0.52). Maternal adherence to the MD was inversely related to the respective adherence of their offspring (OR: 0.93; 95% CI: 0.86–0.997), suggesting that during periods of financial constraints, maternal diet quality is compromised at the expense of affording a better diet for the minors in the family.

1. Introduction

Since the 2008 financial crisis, austerity measures and the rise in commodity prices have increased the prevalence of food insecurity (FI) in many European countries, including Greece [1,2,3]. By the end of 2007, the recorded price index of important food commodities, including staples, increased by 24%, with dairy products being pricier by 58% [4]. The observed increases in food prices had a widespread impact on the nutritional and health status of affected populations [4]. The World Health Organization (WHO) and the Group of Eight (G8) summit recognized the financial crisis as a threat to global health, ringing the alarm for the onset of health inequalities [5]. Diet diversity is negatively related to food prices, with simulations showing that the mean energy consumption per capita declined during the period 2006–2010, increasing the number of people who were food-insecure and at risk of being hungry [6]. Vulnerable populations, including women, older adults, and children, appear to be particularly affected [1,2,7,8,9], with family structure [10], financial burdens [11], and parental unemployment [12] affecting the prevalence of FI and reducing diet quality [11,13,14,15,16,17].
A large body of evidence suggests that children living in food-insecure households demonstrate a lower dietary diversity score (DDS) and diet quality, a reduced intake of key micronutrients, and an increased intake of energy-dense foods [16,18,19,20,21]. Individuals experiencing FI are more likely to consume energy-dense, nutritionally poor foods, in order to suppress the feeling of hunger [8,22,23]. Within families, however, it has been suggested that parents tend to shield their children from the negative health effects of FI by reducing their own diet quality while catering for the younger ones [19,24]. Moreover, we are aware that the quality of a mother’s diet is positively associated with her children’s dietary indicators [25,26], and that individual parental characteristics, such as education or employment status, may act as important effectors of a minor’s diet quality [27,28,29]. Furthermore, maternal dietary diversity is representative of the average household nutrient adequacy [30], with a low maternal diet diversity score being related to infant stunting [31] and child underweight [32].
The present cross-sectional study aimed to evaluate the relationship between maternal characteristics, maternal diet quality, household FI, and the quality of children’s diets in a sample of mother–child pairs.

2. Materials and Methods

2.1. Sample Collection

During the year 2017, a total of 179 pairs of mothers and their children (10–12 years old) attending two public primary schools in Thessaloniki (from the areas of Neapoli and Ampelokipi), Greece, were recruited.
Inclusion criteria were: (1) adolescent children, aged 10–12 years old (students in the two senior primary school classes); (2) willing to participate; and (3) with an adult mother living the in same household as them. Exclusion criteria were: (1) children of younger ages; (2) no provision of parental/guardian participation consent; (3) having adolescent mothers; and (4) having mothers who were not residing with them in the same household. Sample characteristics are presented in Table 1.

2.2. Weight Status and Anthropometry

In children, body weight was measured during morning hours using a digital Seca 874 scale (Seca GmbH and Co., Hamburg, Germany) [33]. Height of children was measured with a portable stadiometer (Seca 214, Seca GmbH and Co., Hamburg, Germany). Maternal weight and height were reported.
Waist circumference was measured at the iliac crest [34,35], and waist-to-height ratio (WHtR) was also calculated.
Body mass index (BMI) was calculated for each participant (mother or child) as the body mass (kg) divided by height squared (m2). For the assessment of body weight status, the International Obesity Task Force (IOTF) [36] criteria were employed for the children, and the World Health Organization (WHO) cutoffs for BMI were used for the mothers [33].

2.3. Diet Quality

Diet quality was evaluated as the level of adherence to the Mediterranean diet (MD). For children, the Mediterranean Diet Quality index for children and adolescents (KIDMED) questionnaire was used [37]. The KIDMED consists of 16 food-frequency questions based on the main components of the MD. Total KIDMED scores range between 0 and 12, with greater scores being indicative of greater MD adherence. Scores >8 indicate optimal adherence and diet quality, scores ranging between 4 and 7 suggest moderate adherence, and scores <3 indicate the adoption of a diet in need of improvement.
Similarly, for the women, the Mediterranean Diet Score (MedDietScore) [38] was employed. Total scores range between 0 and 55, with greater scores suggesting better diet quality on the basis of the MD principles. Maternal diet quality was categorized as good when the MedDietScore exceeded 45 points, average at 23 < MedDietScore < 45, and low when the calculated score was below 23 points in total.

2.4. Dietary Intake

Dietary intake was assessed using 24 h recalls, with the assistance of experienced dietitians (M.P., E.-A.M., and M.B.). Records were analyzed using Food Processor software (ESHA Research, Salem, Oregon), and the daily intake of energy, protein, and selected micronutrients was calculated for each participant.

2.5. Diet Diversity

The household diet diversity score (HDDS) [39] was employed to evaluate variety in the dietary intake of mothers and their children. The questionnaire consists of 12 binary (yes/no) questions, each receiving 0/1 points, evaluating the consumption of different food groups. Scores closer to 12 (maximum score) are indicative of greater diet diversity. The HDDS has been previously used in the Greek population [2].

2.6. Household FI

Household FI was evaluated using the Household Food Insecurity Access Scale (HFIAS) [39]. The questionnaire consists of 9 questions evaluating uncertainty and stress regarding food access, food quality, and food quantity during the past month. The total HFIAS score ranges between 0 and 27, with greater scores being indicative of greater FI. The questionnaire has been previously used in the Greek population [1,2].

2.7. Statistical Analyses

Normality in the distribution of the variables was assessed through graphs and the Kolmogorov–Smirnoff test. Independent sample t-tests were used to identify differences in normally distributed variables, and the Mann–Whitney U test for non-normally distributed data. Data are presented as means ± standard deviation (SD) (normally distributed data), or as medians and their respective interquartile ranges (IQR) for non-normally distributed data. McNemar–Bowker test was used to assess differences between nominal parameters. Spearman’s correlation coefficient assessed the correlation between children’s KIDMED and mothers’ MEDDIET scores.
Univariate logistic regressions were performed to identify the association between children’s MD adherence and FI (dependent variables) and each independent variable. Children’s MD adherence was coded as moderate/greater MD adherence versus lower MD adherence (reference group), while FI categories included any level of FI (low, moderate, or severe) vs. food security (reference category). In the aforementioned regressions, maternal MD adherence was the main variable of interest, and the rest of the independent variables can be seen as covariates. For the multivariate (ML) models, only those variables with a p-value < 0.200 were included. Similarly, the diet quality of the children (dependent) was also assessed through ML analysis.
Data were analyzed using Τhe Jamovi project (version 1.2.27.0) [40] and PASW Statistics 21.0 (IBM SPSS Inc., Hong Kong, China).

3. Results

3.1. Weight Status

The majority of mothers were normoweight (57.9%) (Table 2), with 31.4% of the mothers being classified as overweight, and the remaining 10.7% as obese. Likewise, the majority of children were normoweight (64%), 26.4% demonstrated an excess in body weight, and the remaining 9.6% were classified as obese. However, based on the McNemar–Bowker test, no statistical association was observed between the weight statuses of mothers and children.

3.2. MD Adherence

Only one of the mothers demonstrated optimal MD adherence (Table 3). The majority (98.9%) exhibited moderate adherence to the MD. On the other hand, the majority of children (59.8%) followed a diet of moderate quality, 25.7% adhered to a diet of optimal quality, and the remaining 14.5% demonstrated low diet quality.
There was a weak negative correlation between children’s KIDMED and mothers’ MEDDIET continuous scores, as tested by Spearman’s correlation coefficient (r = −0.101, p = 0.181). When children’s diet quality was explained through logistic regression, it was revealed that maternal MD adherence was a negative effector of a child’s adherence to the MD (Table 4).

3.3. Household FI

The HFIAS revealed that the majority of the mother–child pairs (74%) were food secure. On the other hand, 26% reported some degree of FI, with 11% experiencing mild FI, 8% living in moderate FI, and the remaining reporting severe FI. Between food secure and insecure households, mothers residing in the latter exhibited lower MD adherence (Table 5), but no other differences were noted regarding the characteristics of participant pairs (age, BMI, etc.), their dietary intake, or their diet diversity.
The prevalence of FI within single-parent families was 64.7%. As a result, single-parent families were more frequently encountered in the food-insecure households as compared to the food-secure ones (23.4% vs. 4.55%, respectively, p ≤ 0.001). No differences were noted in the prevalence of maternal or child overweight and obesity between food-secure and -insecure households or between single- and two-parent families (data not shown).
The ML model revealed that higher maternal education appeared to act protectively against the onset of FI, whereas having a single-parent family, with mothers being the primary caretakers, increased the odds of food insecurity vs. food security (Table 6).

4. Discussion

The present study indicates that 26.3% of the households with an adolescent aged between 10 and 12 years old experience some degree of FI. This prevalence is even greater (64.7%) within single-parent families with the mothers as the primary caregivers. Furthermore, the results suggest that household FI is dependent on maternal education and single-parent family status with mothers being the primary caregivers. Moreover, an early adolescent’s diet quality appears to be inversely related to the diet quality of the child’s mother. No differences were noted in the weight status of participants or their dietary intake between food-secure and -insecure households.
Previous research in Canada suggested that the children of food-insecure mothers tend to consume more unhealthy foods and demonstrate a reduced consumption of fruits and vegetables [20]. In the present study, FI was not an effector of a child’s diet quality; however, maternal diet quality was inversely associated with children’s adherence to the MD. According to a recent Spanish study [41] assessing the diet quality of mother–child (8–10 years old) pairs, the maternal intake of vegetables, fish, fruits, legumes, pasta/rice, dairy products, nuts, and baked goods was positively related with the corresponding child behaviors. Similarly, in Norway, maternal diet quality was the strongest prospective predictor of a child’s respective MD adherence at 3 and 8 years of age [42]. Similarly, research in Australia suggested that the maternal postnatal diet was more strongly associated with a child’s diet quality and fruit and vegetable variety compared to the diet adopted during the gestational period [43]. This indicates that children may also act mimetically, copying their mothers’ habits. In less-affluent countries, however, this pattern is slightly altered, but still valid. In rural Timor-Leste, mothers appear to adhere to a strikingly poor diet, low in animal-source foods, while providing more animal-source foods to their children [25]. Nevertheless, maternal dietary quality still explains a child’s diet in Timor-Leste [25] and Ethiopia [29]. In the present study, the inverse relationship between maternal and children’s diet quality is in contrast to the aforementioned examples. However, research has suggested that when experiencing financial difficulties, mothers tend to lower their diet quality in order to afford a good diet for their offspring [19,24]. Thus, it is likely that a tight financial situation might have been the driver of this behavior. Recently, another group of researchers also noted similar behaviors in Greece [44], with the parents reducing the quality of their own diet in an effort to secure a better diet for their children.
Research in adults has associated FI with reduced MD adherence [2,11,45] and low diet quality [13,14,15,19,46,47,48,49,50,51]. Among food insecure adolescents, those living in Lebanon exhibit a lower adherence to the MD [52,53], and in Taiwan they exhibit a diet of lower diet diversity [16]. In the U.S. [19], children with FI tend to have a lower intake than recommended for many important micronutrients, and in Canada, reduced diet quality is observed in food-insecure children, paired with a greater energy intake from ultra-processed foods [48]. However, the number of studies conducted on children and adolescents is limited; thus, it is difficult to discern if household FI has a significant effect on the diet quality of adolescents living in more affluent countries [18]. According to a meta-analysis [19] pooling a sample of U.S. adults and children, although FI is associated with a lower diet quality in the former, the children’s results appear less consistent.
Underemployment contributes to the defining characteristics of FI, namely economic strain, financial vulnerability, and poverty. A plethora of studies have shown that unemployment [54,55,56] and underemployment [57] are both associated with an increased risk of FI. In Quebec, food-insecure individuals are more likely to perform multiple jobs to reach a viable income and report higher job stress [57]. Moreover, gaining full-time employment status has been shown to decrease the severity of FI among low-income Canadian adults [58].
In the present study, the risk of FI was higher among single-mother families, whereas a greater maternal educational attainment reduced the odds of FI. Inevitably, when only one member of the family is bringing money into the household, the risk of FI increases [57]. Thus, research from Canada, Australia, and the U.S. agrees in the fact that FI is greater in single-mother households [57,59,60]. Herein, the prevalence of FI tripled in single-mother homes. In the U.S., 27.8% of households headed by a single woman were food-insecure during the year 2018, whereas in the present study, the respective prevalence was approximately triple. Nevertheless, is should be noted that the sample was not representative of the single mothers residing in the country, while in parallel, it is well-known that the results of the 2008 economic crisis were direr in Greece compared to other countries.
In the U.S., a 1% increase in annual inflation was associated with a 0.5% increase in the prevalence of FI [61], indicating the direct relationship between food prices and the incidence of FI. Thus, maternal diet quality and, by inference, FI are closely related to the SES and the level of educational attainment of mothers [62,63]. Moreover, FI appears to affect diet quality through the employment of specific food-shopping practices, driven mainly by an effort to reduce costs for food [15,64]. As a result, individuals with FI often select energy-dense foods of low micronutrient quality [15] and tend to make fewer shopping trips, relying mainly on nonfresh produce [65]. Low maternal education is associated with lower levels of nutrition knowledge, and this may affect household FI, through the inability or reduced ability to manage food resources. As a result, several lines of evidence have associated maternal education [63,66] and nutrition knowledge with household FI [67,68]. On the other hand, a greater ability and self-confidence in managing food resources in the household is associated with a lower risk of FI [69]. Thus, interventions aiming to increase maternal nutritional knowledge can also improve household FI [70,71].
The limitations of the present study include the relatively small sample and the lack of a representative sampling strategy. Nevertheless, this effort constitutes the first of its kind in the country, using mother–child pairs and aiming to evaluate diet quality. Previous research in Greece has revealed a similar prevalence of overweight and obesity among adolescents as well as a similar diet quality [72,73], indicating that the present sample was rather representative of the child population.

5. Conclusions

Even marginal FI has been positively associated with adverse health outcomes [74], and the need to break the vicious cycle of life-long FI is evident. The present findings indicate that, irrespective of the general financial strain the Greeks are enduring, single-mother homes are particularly affected and require multidisciplinary state actions to alleviate the prevalence of FI and improve diet quality among children. Furthermore, the findings suggest that during periods of financial constraints, maternal diet quality is compromised at the expense of affording a better diet for the minors in the family.

Author Contributions

Conceptualization, M.G.G., T.V. and D.G.G.; methodology, M.G.G., C.T. and D.G.G.; formal analysis, C.T., X.T., M.G.G., C.A. and K.G.; investigation, M.P., E.-A.M. and M.B.; resources, M.G.G., D.G.G., T.D. and T.V.; data curation, M.P., M.G.G. and X.T.; writing—original draft preparation, M.G.G. and C.A.; writing—review and editing, T.V., M.G.G., D.G.G., C.A., A.P. and K.T.; visualization, M.G.G., K.G. and C.T.; supervision, M.G.G., T.V. and D.G.G.; project administration, M.G.G. and T.V. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the Alexander Technological Educational Institute of Thessaloniki (protocol code: ID 18.10.2018; approval date: 18 October 2018).

Informed Consent Statement

Informed consent was obtained from the guardians/parents of all subjects involved in the study.

Data Availability Statement

Data are available upon request to M.G.G.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Gkiouras, K.; Cheristanidis, S.; Papailia, T.D.; Grammatikopoulou, M.G.; Karamitsios, N.; Goulis, D.G.; Papamitsou, T. Malnutrition and Food Insecurity Might Pose a Double Burden for Older Adults. Nutrients 2020, 12, 2407. [Google Scholar] [CrossRef]
  2. Grammatikopoulou, M.G.; Gkiouras, K.; Theodoridis, X.; Tsisimiri, M.; Markaki, A.G.; Chourdakis, M.; Goulis, D.G. Food insecurity increases the risk of malnutrition among community-dwelling older adults. Maturitas 2019, 119, 8–13. [Google Scholar] [CrossRef] [PubMed]
  3. Grimaccia, E.; Naccarato, A. Food Insecurity in Europe: A Gender Perspective. Soc. Indic. Res. 2020, 1–19. [Google Scholar] [CrossRef] [PubMed]
  4. Christian, P. Impact of the Economic Crisis and Increase in Food Prices on Child Mortality: Exploring Nutritional Pathways. J. Nutr. 2010, 140, 177S. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. G8 urged to act on food crisis and health. Bull. World Health Organ. 2008, 86, 503–504. [CrossRef] [PubMed]
  6. Brinkman, H.J.; De Pee, S.; Sanogo, I.; Subran, L.; Bloem, M.W. High Food Prices and the Global Financial Crisis Have Reduced Access to Nutritious Food and Worsened Nutritional Status and Health. J. Nutr. 2010, 140, 153S–161S. [Google Scholar] [CrossRef]
  7. Zaçe, D.; Di Pietro, M.L.; Caprini, F.; de Waure, C.; Ricciardi, W. Prevalence and correlates of food insecurity among children in high-income European countries. A systematic review. Ann. Ist. Super. Sanita 2020, 56, 90–98. [Google Scholar] [CrossRef]
  8. Grammatikopoulou, M.G.; Gkiouras, K.; Pepa, A.; Persynaki, A.; Taousani, E.; Milapidou, M.; Smyrnakis, E.; Goulis, D.G. Health status of women affected by homelessness: A cluster of in concreto human rights violations and a time for action. Maturitas 2021, 154, 31–45. [Google Scholar] [CrossRef]
  9. Rodrigues, D.; Carmo, A.; Gama, A.; Machado-Rodrigues, A.M.; Nogueira, H.; Rosado-Marques, V.; Silva, M.R.; Padez, C. The Great Recession weighted on Portuguese children: A structural equation modeling approach considering eating patterns. Am. J. Hum. Biol. 2021, e23692. [Google Scholar] [CrossRef] [PubMed]
  10. Creedon, P.; Schmeer, K.; Taylor, C.; Clark, J.; Hooker, N.; Garner, J. Prevalence of Food Insecurity by Household Structure: Counterintuitive Findings for Two-‘Parent’ Families. Curr. Dev. Nutr. 2021, 5, 114. [Google Scholar] [CrossRef]
  11. Theodoridis, X.; Grammatikopoulou, M.G.; Gkiouras, K.; Papadopoulou, S.E.; Agorastou, T.; Gkika, I.; Maraki, M.I.; Dardavessis, T.; Chourdakis, M. Food insecurity and Mediterranean diet adherence among Greek university students. Nutr. Metab. Cardiovasc. Dis. 2018, 28, 477–485. [Google Scholar] [CrossRef]
  12. Men, F.; Urquia, M.L.; Tarasuk, V. The role of provincial social policies and economic environments in shaping food insecurity among Canadian families with children. Prev. Med. 2021, 148, 106558. [Google Scholar] [CrossRef] [PubMed]
  13. Leung, C.W.; Epel, E.S.; Ritchie, L.D.; Crawford, P.B.; Laraia, B.A. Food insecurity is inversely associated with diet quality of lower-income adults. J. Acad. Nutr. Diet. 2014, 114, 1943–1953. [Google Scholar] [CrossRef] [PubMed]
  14. Leung, C.W.; Tester, J.M. The Association between Food Insecurity and Diet Quality Varies by Race/Ethnicity: An Analysis of National Health and Nutrition Examination Survey 2011–2014 Results. J. Acad. Nutr. Diet. 2019, 119, 1676–1686. [Google Scholar] [CrossRef] [PubMed]
  15. Ranjit, N.; Macias, S.; Hoelscher, D. Factors related to poor diet quality in food insecure populations. Transl. Behav. Med. 2020, 10, 1297–1305. [Google Scholar] [CrossRef] [PubMed]
  16. Yeh, C.W.; Lo, Y.T.C.; Chen, Y.C.; Chen, W.C.; Huang, Y.C. Perceived food insecurity, dietary quality, and unfavorable food intake among children and adolescents from economically disadvantaged households. Nutrients 2021, 13, 3411. [Google Scholar] [CrossRef] [PubMed]
  17. Koulierakis, G.; Dermatis, A.; Vassilakou, N.T.; Pavi, E.; Zavras, D.; Kyriopoulos, J. Determinants of healthy diet choices during austerity in Greece. Br. Food J. 2021, 883. [Google Scholar] [CrossRef]
  18. Bell, Z.; Scott, S.; Visram, S.; Rankin, J.; Bambra, C.; Heslehurst, N. Food insecurity and the nutritional health and well-being of women and children in high-income countries: Protocol for a qualitative systematic review. BMJ Open 2021, 11, e048180. [Google Scholar] [CrossRef]
  19. Hanson, K.L.; Connor, L.M. Food insecurity and dietary quality in US adults and children: A systematic review. Am. J. Clin. Nutr. 2014, 100, 684–692. [Google Scholar] [CrossRef] [Green Version]
  20. Cunningham, T.J.; Barradas, D.T.; Rosenberg, K.D.; May, A.L.; Kroelinger, C.D.; Ahluwalia, I.B. Is Maternal Food Security a Predictor of Food and Drink Intake Among Toddlers in Oregon? Matern. Child Health J. 2012, 16, 339. [Google Scholar] [CrossRef] [Green Version]
  21. Landry, M.J.; van den Berg, A.E.; Asigbee, F.M.; Vandyousefi, S.; Ghaddar, R.; Davis, J.N.; Landry, M.J.; van den Berg, A.E.; Asigbee, F.M.; Vandyousefi, S.; et al. Child-Report of Food Insecurity Is Associated with Diet Quality in Children. Nutrients 2019, 11, 1574. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Kirkpatrick, S.I.; Tarasuk, V. Food insecurity is associated with nutrient inadequacies among Canadian adults and adolescents. J. Nutr. 2008, 138, 604–612. [Google Scholar] [CrossRef] [PubMed]
  23. Drewnowski, A.; Specter, S.E. Poverty and obesity: The role of energy density and energy costs. Am. J. Clin. Nutr. 2004, 79, 6–16. [Google Scholar] [CrossRef] [PubMed]
  24. Martin, M.A.; Lippert, A.M. Feeding Her Children, but Risking Her Health: The Intersection of Gender, Household Food Insecurity and Obesity. Soc. Sci. Med. 2012, 74, 1754. [Google Scholar] [CrossRef] [Green Version]
  25. Bonis-Profumo, G.; Stacey, N.; Brimblecombe, J. Maternal diets matter for children’s dietary quality: Seasonal dietary diversity and animal-source foods consumption in rural Timor-Leste. Matern. Child Nutr. 2021, 17, e13071. [Google Scholar] [CrossRef] [PubMed]
  26. Amugsi, D.A.; Mittelmark, M.B.; Oduro, A. Association between Maternal and Child Dietary Diversity: An Analysis of the Ghana Demographic and Health Survey. PLoS ONE 2015, 10, e0136748. [Google Scholar] [CrossRef] [Green Version]
  27. Koivuniemi, E.; Gustafsson, J.; Mäkelä, I.; Koivisto, V.J.; Vahlberg, T.; Schwab, U.; Niinikoski, H.; Laitinen, K. Parental and Child Factors Associated With 2- to 6-Year-Old Children’s Diet Quality in Finland. J. Acad. Nutr. Diet. 2022, 122, 129–138.e4. [Google Scholar] [CrossRef] [PubMed]
  28. van der Velde, L.A.; Nguyen, A.N.; Schoufour, J.D.; Geelen, A.; Jaddoe, V.W.V.; Franco, O.H.; Voortman, T. Diet quality in childhood: The Generation R Study. Eur. J. Nutr. 2019, 58, 1259–1269. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  29. Guja, T.; Melaku, Y.; Andarge, E. Concordance of Mother-Child (6–23 Months) Dietary Diversity and Its Associated Factors in Kucha District, Gamo Zone, Southern Ethiopia: A Community-Based Cross-Sectional Study. J. Nutr. Metab. 2021, 2021, 8819846. [Google Scholar] [CrossRef]
  30. Becquey, E.; Martin-Prevel, Y.; Traissac, P.; Dembélé, B.; Bambara, A.; Delpeuch, F. The household food insecurity access scale and an index-member dietary diversity score contribute valid and complementary information on household food insecurity in an urban West-African setting. J. Nutr. 2010, 140, 2233–2240. [Google Scholar] [CrossRef] [Green Version]
  31. Hasan, M.; Islam, M.M.; Mubarak, E.; Haque, M.A.; Choudhury, N.; Ahmed, T. Mother’s dietary diversity and association with stunting among children <2 years old in a low socio-economic environment: A case-control study in an urban care setting in Dhaka, Bangladesh. Matern. Child Nutr. 2019, 15, e12665. [Google Scholar] [CrossRef]
  32. Bosha, T.; Lambert, C.; Riedel, S.; Melesse, A.; Biesalski, H.K. Dietary Diversity and Anthropometric Status of Mother–Child Pairs from Enset (False Banana) Staple Areas: A Panel Evidence from Southern Ethiopia. Int. J. Environ. Res. Public Health 2019, 16, 2170. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. World Health Organization. Physical Status: The Use and Interpretation of Anthropometry; Report of a WHO Expert Committee, WHO Technical ReportSeries, N. 854. G. 19; World Health Organization: Geneva, Switzerland, 2013. [Google Scholar]
  34. Fernández, J.R.; Brown, M.B.; López-Alarcón, M.; Dawson, J.A.; Guo, F.; Redden, D.; Allison, D.B. Changes in Pediatric Waist Circumference Percentiles Despite Reported Pediatric Weight Stabilization in the United States. Pediatr. Obes. 2016, 12, 347–355. [Google Scholar] [CrossRef]
  35. Lean, M.E.J.; Han, T.S.; Morrison, C.E. Waist circumference as a measure for indicating need for weight management. BMJ 1995, 311, 158. [Google Scholar] [CrossRef] [Green Version]
  36. Cole, T.J.; Lobstein, T. Extended international (IOTF) body mass index cut-offs for thinness, overweight and obesity. Pediatr. Obes. 2012, 7, 284–294. [Google Scholar] [CrossRef]
  37. Serra-Majem, L.; Ribas, L.; Ngo, J.; Ortega, R.M.; García, A.; Pérez-Rodrigo, C.; Aranceta, J. Food, youth and the Mediterranean diet in Spain. Development of KIDMED, Mediterranean Diet Quality Index in children and adolescents. Public Health Nutr. 2004, 7, 931–935. [Google Scholar] [CrossRef] [PubMed]
  38. Panagiotakos, D.B.; Pitsavos, C.; Arvaniti, F.; Stefanadis, C. Adherence to the Mediterranean food pattern predicts the prevalence of hypertension, hypercholesterolemia, diabetes and obesity, among healthy adults; the accuracy of the MedDietScore. Prev. Med. 2007, 44, 335–340. [Google Scholar] [CrossRef]
  39. Coates, J.; Swindale, A.; Bilinsky, P. Household Food Insecurity Access Scale (HFIAS) for Measurement of Household Food Access: Indicator Guide (v. 3); FHI 360/FANTA: Washington, DC, USA, 2007; ISBN 9780874216561. [Google Scholar]
  40. The Jamovi Project Jamovi. 2020. Available online: https://www.jamovi.org/about.html (accessed on 7 January 2022).
  41. Juton, C.; Lerin, C.; Homs, C.; Esteve, R.C.; Berruezo, P.; Cárdenas-Fuentes, G.; Fíto, M.; Grau, M.; Estrada, L.; Gómez, S.F.; et al. Prospective Associations between Maternal and Child Diet Quality and Sedentary Behaviors. Nutrients 2021, 13, 1713. [Google Scholar] [CrossRef]
  42. Sørensen, L.M.N.; Aamodt, G.; Brantsæter, A.L.; Meltzer, H.M.; Papadopoulou, E. Diet quality of Norwegian children at 3 and 7 years: Changes, predictors and longitudinal association with weight. Int. J. Obes. 2021, 46, 10–20. [Google Scholar] [CrossRef]
  43. Ashman, A.M.; Collins, C.E.; Hure, A.J.; Jensen, M.; Oldmeadow, C. Maternal diet during early childhood, but not pregnancy, predicts diet quality and fruit and vegetable acceptance in offspring. Matern. Child Nutr. 2016, 12, 579–590. [Google Scholar] [CrossRef]
  44. Kosti, R.I.; Kanellopoulou, A.; Notara, V.; Antonogeorgos, G.; Rojas-Gil, A.P.; Kornilaki, E.N.; Lagiou, A.; Panagiotakos, D.B. Household food spending, parental and childhood’s diet quality, in financial crisis: A cross-sectional study in Greece. Eur. J. Public Health 2021, 31, 822–828. [Google Scholar] [CrossRef]
  45. Gregório, M.J.; Rodrigues, A.M.; Graça, P.; de Sousa, R.D.; Dias, S.S.; Branco, J.C.; Canhão, H. Food Insecurity Is Associated with Low Adherence to the Mediterranean Diet and Adverse Health Conditions in Portuguese Adults. Front. Public Health 2018, 6, 38. [Google Scholar] [CrossRef]
  46. Leung, C.W.; Wolfson, J.A. Food Insecurity Among Older Adults: 10-Year National Trends and Associations with Diet Quality. J. Am. Geriatr. Soc. 2021, 69, 964–971. [Google Scholar] [CrossRef] [PubMed]
  47. Larson, N.; Laska, M.N.; Neumark-Sztainer, D. Food insecurity, diet quality, home food availability, and health risk behaviors among emerging adults: Findings from the EAT 2010-2018 study. Am. J. Public Health 2020, 110, 1422–1428. [Google Scholar] [CrossRef]
  48. Hutchinson, J.; Tarasuk, V. The relationship between diet quality and the severity of household food insecurity in Canada. Public Health Nutr. 2021, 25, 1013–1026. [Google Scholar] [CrossRef] [PubMed]
  49. Pei, C.S.; Appannah, G.; Sulaiman, N. Household food insecurity, diet quality, and weight status among indigenous women (Mah Meri) in Peninsular Malaysia. Nutr. Res. Pract. 2018, 12, 135–142. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  50. Kehoe, S.H.; Wrottesley, S.V.; Ware, L.; Prioreschi, A.; Draper, C.; Ward, K.; Lye, S.; Norris, S.A. Food insecurity, diet quality and body composition: Data from the Healthy Life Trajectories Initiative (HeLTI) pilot survey in urban Soweto, South Africa. Public Health Nutr. 2021, 24, 1629–1637. [Google Scholar] [CrossRef] [PubMed]
  51. Nicklett, E.J.; Johnson, K.E.; Troy, L.M.; Vartak, M.; Reiter, A. Food Access, Diet Quality, and Nutritional Status of Older Adults During COVID-19: A Scoping Review. Front. Public Health 2021, 9, 1943. [Google Scholar] [CrossRef] [PubMed]
  52. Jomaa, L.; Naja, F.; Kharroubi, S.; Itani, L.; Hwalla, N. A Lebanese Mediterranean Dietary Pattern Is Associated with Lower Food Insecurity Among Lebanese Adolescents: A Cross-Sectional National Study (P04-055-19). Curr. Dev. Nutr. 2019, 3, 232. [Google Scholar] [CrossRef] [Green Version]
  53. Naja, F.; Itani, L.; Kharroubi, S.; Diab El Harake, M.; Hwalla, N.; Jomaa, L. Food insecurity is associated with lower adherence to the Mediterranean dietary pattern among Lebanese adolescents: A cross-sectional national study. Eur. J. Nutr. 2020, 59, 3281–3292. [Google Scholar] [CrossRef]
  54. Raifman, J.; Bor, J.; Venkataramani, A. Association Between Receipt of Unemployment Insurance and Food Insecurity Among People Who Lost Employment During the COVID-19 Pandemic in the United States. JAMA Netw. Open 2021, 4, e2035884. [Google Scholar] [CrossRef] [PubMed]
  55. Etana, D.; Tolossa, D. Unemployment and Food Insecurity in Urban Ethiopia. Afr. Dev. Rev. 2017, 29, 56–68. [Google Scholar] [CrossRef]
  56. Owens, M.R.; Brito-Silva, F.; Kirkland, T.; Moore, C.E.; Davis, K.E.; Patterson, M.A.; Miketinas, D.C.; Tucker, W.J. Prevalence and Social Determinants of Food Insecurity among College Students during the COVID-19 Pandemic. Nutrients 2020, 12, 2515. [Google Scholar] [CrossRef] [PubMed]
  57. McIntyre, L.; Bartoo, A.C.; Emery, J.C.H. When working is not enough: Food insecurity in the Canadian labour force. Public Health Nutr. 2014, 17, 49–57. [Google Scholar] [CrossRef] [Green Version]
  58. Loopstra, R.; Tarasuk, V. Severity of Household Food Insecurity Is Sensitive to Change in Household Income and Employment Status among Low-Income Families. J. Nutr. 2013, 143, 1316–1323. [Google Scholar] [CrossRef]
  59. Coleman-Jensen, A.; Rabbitt, M.P.; Gregory, C.A.; Singh, A. Household Food Security in the United States in 2018. Econ. Res. Rep. 2019, 270, 173. [Google Scholar]
  60. Savage, B. Food insecurity in Brisbane: The single mother’s struggle. Agri-Food XVI-Annu. Meet. Agri-food Res. Netw. 2009, unpublished. [Google Scholar]
  61. Nord, M.; Coleman-Jensen, A.; Gregory, C. Prevalence of U.S. Food Insecurity Is Related to Changes in Unemployment, Inflation, and the Price of Food. Econ. Res. Serv. Rep. 2014, 167, 1477. [Google Scholar]
  62. McLeod, E.R.; Campbell, K.J.; Hesketh, K.D. Nutrition Knowledge: A Mediator between Socioeconomic Position and Diet Quality in Australian First-Time Mothers. J. Am. Diet. Assoc. 2011, 111, 696–704. [Google Scholar] [CrossRef]
  63. Getacher, L.; Egata, G.; Aynalem, Y.A.; Molla, A.; Tesfaye, A.; Abebe, H.; Bayih, W.A.; Habtegiorgis, S.D. Food insecurity and its predictors among lactating mothers in North Shoa Zone, Central Ethiopia: A community based cross-sectional study. BMJ Open 2020, 10, e040627. [Google Scholar] [CrossRef]
  64. Gorman, K.S.; McCurdy, K.; Kisler, T.; Metallinos-Katsaras, E. Maternal Strategies to Access Food Differ by Food Security Status. J. Acad. Nutr. Diet. 2017, 117, 48–57. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  65. Ma, X.; Liese, A.D.; Hibbert, J.; Bell, B.A.; Wilcox, S.; Sharpe, P.A. The Association between Food Security and Store-Specific and Overall Food Shopping Behaviors. J. Acad. Nutr. Diet. 2017, 117, 1931–1940. [Google Scholar] [CrossRef] [PubMed]
  66. Sarki, M.; Robertson, A.; Parlesak, A. Association between socioeconomic status of mothers, food security, food safety practices and the double burden of malnutrition in the Lalitpur district, Nepal. Arch. Public Health 2016, 74, 35. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  67. Iqbal, S.; Ali, I. Maternal food insecurity in low-income countries: Revisiting its causes and consequences for maternal and neonatal health. J. Agric. Food Res. 2021, 3, 100091. [Google Scholar] [CrossRef]
  68. Yeganeh, S.; Motamed, N.; Najafpourboushehri, S.; Ravanipour, M. Assessment of the knowledge and attitude of infants’ mothers from Bushehr (Iran) on food security using anthropometric indicators in 2016: A cross-sectional study. BMC Public Health 2018, 18, 621. [Google Scholar] [CrossRef] [Green Version]
  69. Jomaa, L.; Na, M.; Eagleton, S.G.; Diab-El-harake, M.; Savage, J.S. Caregiver’s Self-Confidence in Food Resource Management Is Associated with Lower Risk of Household Food Insecurity among SNAP-Ed-Eligible Head Start Families. Nutrients 2020, 12, 2304. [Google Scholar] [CrossRef]
  70. Mortazavi, Z.; Dorosty, A.R.; Eshraghian, M.R.; Ghaffari, M.; Ansari-Moghaddam, A. Nutritional Education and Its Effects on Household Food Insecurity in Southeastern Iran. Iran. J. Public Health 2021, 50, 798. [Google Scholar] [CrossRef]
  71. Mbogori, T.; Murimi, M. Effects of a nutrition education intervention on maternal nutrition knowledge, dietary intake and nutritional status among food insecure households in Kenya. Int. J. Community Med. Public Health 2019, 6, 1831–1837. [Google Scholar] [CrossRef]
  72. Grammatikopoulou, M.G.; Maraki, M.I.; Giannopoulou, D.; Poulimeneas, D.; Sidossis, L.S.; Tsigga, M. Similar Mediterranean diet adherence but greater central adiposity is observed among Greek diaspora adolescents living in Istanbul, compared to Athens. Ethn. Health 2018, 23, 221–232. [Google Scholar] [CrossRef]
  73. Grammatikopoulou, M.G.; Poulimeneas, D.; Gounitsioti, I.S.; Gerothanasi, K.; Tsigga, M.; Kiranas, E.; ADONUT Study Group. Prevalence of simple and abdominal obesity in Greek adolescents: The ADONUT study. Clin. Obes. 2014, 4, 303–308. [Google Scholar] [CrossRef]
  74. Cook, J.T.; Black, M.; Chilton, M.; Cutts, D.; de Cuba, S.E.; Heeren, T.C.; Rose-Jacobs, R.; Sandel, M.; Casey, P.H.; Coleman, S.; et al. Are food insecurity’s health impacts underestimated in the U.S. population? Marginal food security also predicts adverse health outcomes in young U.S. children and mothers. Adv. Nutr. 2013, 4, 51–61. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Table 1. Characteristics of the participating mother–child pairs (N = 179).
Table 1. Characteristics of the participating mother–child pairs (N = 179).
Child sex (boy/girl) (n)92/87
Child age (years)11.0 ± 0.9
Maternal age (years)42.0 ± 4.6
Single-parent family (yes/no)17/162
Maternal employment status (maternal leave/unemployed/employed part-time/employed full-time) (n)8/44/101/26
Maternal educational level (primary school/secondary school/lyceum/university/postgraduate) 44/21/47/52/15
Table 2. Pairs of mothers and children in each weight status category (%, n).
Table 2. Pairs of mothers and children in each weight status category (%, n).
Mothers (N = 178) *
Children
(N = 178) *
Normoweight Overweight Obese Total
(Children)
p
n (%)n (%)n (%)
Normoweight 41.6% (n = 74)18% (n = 32)3.9% (n = 8)64% (n = 114) 0.624 ¥
Overweight 12.9% (n = 23)4.5% (n = 18)3.4% (n = 6)26.4% (n = 47)
Obese 3.4% (n = 6)3.4% (n = 6)2.8% (n = 5)9.6% (n = 17)
Total (mothers)57.9% (n = 103)31.4% (n = 56)10.7% (n = 19)100% (n = 178)
* Data were missing for one participant; according to the World Health Organization criteria [33]; according to the World Obesity criteria [36]. ¥ refers to the McNemar–Bowker test.
Table 3. Pairs of mothers and children in each MD adherence category (%, n).
Table 3. Pairs of mothers and children in each MD adherence category (%, n).
Mothers (N = 179)
Children
(N = 179)
Low MD
Adherence
Moderate MD
Adherence
Optimal MD
Adherence
Total
(Children)
Low MD adherence 0% (n = 0)14.5% (n = 26)0.0% (n = 0)14.5% (n = 26)
Moderate MD adherence 0.6% (n = 1)58.7% (n = 105)0.6% (n = 1)59.8% (n = 107)
Optimal MD adherence 0% (n = 0)25.7% (n = 46)0.0% (n = 0)25.7% (n = 46)
Total (mothers)0.6% (n = 1)98.9% (n = 117)0.6% (n = 1)100% (n = 179)
KIDMED, Mediterranean Diet Quality Index for children and adolescents [37]; MD, Mediterranean diet; MedDietScore, Mediterranean Diet Score [38]; based on the MedDietScore [38]; based on the KIDMED [37].
Table 4. Univariate and multivariate logistic regression models explaining children’s MD adherence.
Table 4. Univariate and multivariate logistic regression models explaining children’s MD adherence.
VariablesUnivariate AnalysisMultivariate Analysis
OR95% CIpOR95% CIp
Being FI (vs. food-secure)1.330.63 to 2.780.456
Single-parent family (vs. non-single-parent family)1.140.35 to 3.680.830
Maternal MD adherence (continuous)0.930.87 to 1.000.0380.930.86 to 0.9970.041
Maternal ΒΜΙ (continuous)0.950.88 to 1.030.1880.940.86 to 1.010.100
Employed (vs. unemployed)0.900.42 to 1.940.7830.690.32 to 1.470.333
Tertiary education (vs. lower educational level)0.580.28 to 1.200.139
BMI, body mass index; CI, confidence intervals; FI, food insecure [39]; MD, Mediterranean diet; OR, odds ratio; based on the MedDietScore [38]. Note: the dependent variable was maternal high/moderate MD adherence vs. low MD adherence (reference group).
Table 5. Differences in maternal and child characteristics between food-secure and -insecure households (means ± SD, or medians and their respective IQR).
Table 5. Differences in maternal and child characteristics between food-secure and -insecure households (means ± SD, or medians and their respective IQR).
Characteristics of ParticipantsFood Secure
(n = 132)
Food Insecure
(n = 47)
p
Child
characteristics
Age (years)10.9 ± 0.911.1 ± 0.9NS
BMI (kg/m2)20.0 ± 3.920.6 ± 4.7NS
WHtR0.47 ± 0.050.47 ± 0.06NS
KIDMED6.2 ± 2.46.0 ± 2.8NS
HDDS7.4 ± 1.86.96 ± 1.65NS
Energy intake (kcal/day)1408 (1155, 1605)1270 (1086, 1688)NS
Protein intake (g/kg of BW/day)1.22 (0.9, 1.61)1.17 (0.93, 1.48)NS
Trans fat intake (g/day)0.64 (0.48, 0.91)0.56 (0.47, 0.77)NS
Maternal
characteristics
Age (years)42.1 ± 4.341.9 ± 5.4NS
BMI (kg/m2)25.2 ± 5.024.0 ± 3.8NS
MedDietScore34.3 ± 5.032.2 ± 4.60.011
HDDS7.85 ± 1.97.87 ± 2.45NS
Energy intake (kcal/day)1217 (958, 1436)1255 (982, 1410)NS
Protein intake (g/kg of BW/day)0.75 (0.56, 0.95)0.72 (0.56, 0.84)NS
BMI, body mass index; BW, body weight; HDDS, household diet diversity score [39]; IQR, interquartile range; KIDMED, Mediterranean Diet Quality Index for children and adolescents [37]; MedDietScore, Mediterranean Diet Score [38]; NS, not significant; SD, standard deviation; WHtR, waist-to-height ratio.
Table 6. Univariate and multivariate logistic regression models explaining household FI.
Table 6. Univariate and multivariate logistic regression models explaining household FI.
VariablesUnivariate AnalysisMultivariate Analysis
OR95% CIpOR95% CIp
Maternal BMI (continuous)0.950.87 to 1.030.1740.920.84 to 1.000.917
Conjugal family (vs. single-parent family)0.160.05 to 0.45<0.0010.150.87 to 0.520.003
Maternal MD adherence (continuous)0.920.85 to 0.980.0130.940.87 to 1.020.149
Higher maternal education (vs. lower educational level)0.210.09 to 0.50<0.0010.250.10 to 0.630.003
Maternal employment status (vs. unemployment)0.800.38 to 1.710.569
BMI, body mass index; CI, confidence intervals; FI, food insecurity; MD, Mediterranean diet; OR, odds ratio; based on the MedDietScore (continuous variable) [38]. Note: the dependent variable includes being food-insecure vs. food-secure (reference group).
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Aggeli, C.; Patelida, M.; Grammatikopoulou, M.G.; Matzaridou, E.-A.; Berdalli, M.; Theodoridis, X.; Gkiouras, K.; Persynaki, A.; Tsiroukidou, K.; Dardavessis, T.; et al. Moderators of Food Insecurity and Diet Quality in Pairs of Mothers and Their Children. Children 2022, 9, 472. https://doi.org/10.3390/children9040472

AMA Style

Aggeli C, Patelida M, Grammatikopoulou MG, Matzaridou E-A, Berdalli M, Theodoridis X, Gkiouras K, Persynaki A, Tsiroukidou K, Dardavessis T, et al. Moderators of Food Insecurity and Diet Quality in Pairs of Mothers and Their Children. Children. 2022; 9(4):472. https://doi.org/10.3390/children9040472

Chicago/Turabian Style

Aggeli, Christine, Maria Patelida, Maria G. Grammatikopoulou, Ekaterini-Avrakomi Matzaridou, Marina Berdalli, Xenophon Theodoridis, Konstantinos Gkiouras, Angeliki Persynaki, Kyriaki Tsiroukidou, Theodore Dardavessis, and et al. 2022. "Moderators of Food Insecurity and Diet Quality in Pairs of Mothers and Their Children" Children 9, no. 4: 472. https://doi.org/10.3390/children9040472

APA Style

Aggeli, C., Patelida, M., Grammatikopoulou, M. G., Matzaridou, E. -A., Berdalli, M., Theodoridis, X., Gkiouras, K., Persynaki, A., Tsiroukidou, K., Dardavessis, T., Tzimos, C., Goulis, D. G., & Vassilakou, T. (2022). Moderators of Food Insecurity and Diet Quality in Pairs of Mothers and Their Children. Children, 9(4), 472. https://doi.org/10.3390/children9040472

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop