Diet Quality and Physical Activity in Children and Caregivers From PAVILA Shelter in Northern México

Abstract

This study assessed diet quality and physical activity levels in children and caregivers at the PAVILA shelter in northern Mexico. Researchers examined eating habits and exercise to determine whether they met healthy diet recommendations. The study included 27 children and 10 caregivers, analyzing their food intake, physical activity, and body measurements. Results showed that, on average, their diet quality was moderate (57.76 out of 100). Only 2.70% had a good-quality diet, 75.68% had an intermediate-quality diet, and 21.62% had a poor-quality diet. Participants ate few vegetables, dairy products, and fish, while their consumption of sugars and saturated fats was high. Children had worse diet quality compared to caregivers. Their eating habits did not meet national or international nutrition guidelines. These findings are important because a poor diet and lack of physical activity can increase the risk of diseases such as diabetes, obesity, and heart problems. The study highlights the need for better nutrition at the shelter, encouraging more nutritious foods and reducing sugars and fats.

Keywords

healthy eating index sugars vegetables children

Introduction

The pandemic of non-communicable diseases (NCDs) is on the rise, both in developed and developing countries, despite efforts to establish recommendations and guidelines for healthy eating¹; the increase in NCDs is the result of a multifactorial combination involving genetic, physiological, environmental, and behavioural factors, facilitating the development of cardiovascular diseases, cancer, respiratory diseases, overweight, and type 2 diabetes mellitus^2
-4; therefore, the role of diet quality in the prevention of these diseases is increasingly indisputable.⁵

Currently, researchers are studying and developing systems and indicators to evaluate the quality of the population’s diet based on current knowledge of nutrition and health.⁶ These efforts promote healthy lifestyle habits and assess risk factors related to non-communicable chronic diseases (NCDs).⁷ Over 20 indicators have been created, with 5 standing out for validity. It is important to note that existing indices do not predict disease or mortality.⁸ Instead, they target the general population and rely on considerations based on different dietary patterns and health guidelines, such as the Dietary Guidelines for Americans (DGA), which researchers tailor to meet the purposes and needs of specific populations.⁹

Children living in group homes represent a highly vulnerable sector of the population due to the circumstances that led to their separation from their families, living in contexts of poverty, domestic violence, abandonment, orphanhood, or situations of forced migration. According to UNICEF data, many of them have experienced psychological trauma before arriving at these institutions, which exacerbates their physical and emotional vulnerability.¹⁰ A high percentage come from dysfunctional homes with a history of abuse, neglect, or financial inability to provide for them.¹¹ Most are school-aged children and adolescents, although there are also infants and preschoolers. Due to their circumstances, they present higher rates of anxiety, depression, and attachment disorders compared to children raised in families.¹² Group homes vary in quality depending on their funding (public, private, or religious), but they share common challenges such as: Overcrowding: Spaces with a high density of children per caregiver, limiting individualized attention; Limited access to basic services: Although they receive shelter and food, many lack quality care. This can create a chronic-stress environment, which, combined with inadequate nutrition, negatively impacts their overall development.^13,14

Their nutritional status is often critical due to multiple socioeconomic, institutional, and structural factors. Studies indicate that these children frequently face monotonous, micronutrient-deficient, and unbalanced diets, which can lead to deficiencies with short- and long-term consequences.¹⁵ While group homes provide basic shelter, they often operate with limited resources, which directly impacts the quality of food.

It is worth noting that in institutional environments such as shelters, both children and caregivers share the same food environment, meal schedules, and daily routines.¹⁶ Caregivers are responsible for food preparation and supervision, and they play a key role in shaping children’s eating and physical activity behaviours. Therefore, including both groups in the present study allowed for a broader understanding of the shelter’s overall nutritional environment and the potential interrelation between the dietary habits of caregivers and children.^17,18

Caregivers in these institutions play a dual role: they are both recipients of the same food environment and active agents influencing children’s dietary behaviours. Assessing diet quality in both groups allows for a more comprehensive understanding of the institutional nutritional ecosystem.

The HEI-2020 scoring system includes 13 components (food groups) divided into adequacy and moderation categories.⁴ The adequacy group focuses on increasing the consumption of certain foods. These include total fruits: All types of fruits, whether fresh, frozen, dried, or canned. Whole fruits: Fruits consumed in their whole form, excluding juices. Total vegetables: All forms of vegetables. Green vegetables and legumes: Emphasizes the consumption of leafy green vegetables and legumes. Whole grains: Whole or intact grains. Dairy: Milk, yoghurt, and cheese (in any form or fat content). Total protein foods: Animal and plant proteins, including seafood and plant-based proteins. Fatty acids: Measures the ratio of unsaturated to saturated fats, promoting healthy fats. Each component has a maximum score ranging from 5 to 10 points, depending on its importance. The total score of HEI-2020 is 100 points, with 100 indicating the highest-quality diet. Diets that achieve higher scores closely follow dietary recommendations, while lower scores highlight areas where nutrition improvements are needed.¹⁹

To our knowledge, no previous study has applied the HEI-2020 to evaluate diet quality in a Mexican shelter setting, highlighting an important gap in the literature and supporting the public health relevance of this exploratory assessment.

Therefore, this study aims to determine the Healthy Eating Index (HEI-2020) in subjects enrolled and caregivers at the PAVILA shelter in the Laguna region and to assess individuals at risk of developing non-communicable chronic diseases.

Materials and Methods

We conducted an exploratory, observational and cross-sectional study between May and September 2022 involving 27 children and 10 caregivers from the PAVILA shelter, located in the Northern-Central region of Mexico known as the Comarca Lagunera (La Laguna). This area encompasses 2 states (Durango and Coahuila) and 15 municipalities, with the shelter located in the municipality of Lerdo. The region is characterized by a strong dairy and poultry production sector, which may directly influence local dietary patterns and nutrient availability.^20,21 Participants were selected through non-probabilistic convenience sampling, based on the voluntary participation of children and caregivers residing in the shelter during the study period. All residents who met eligibility criteria were invited; however, participation depended on availability during scheduled evaluation days and provision of consent/assent. Data collection was conducted on-site. At the time of the study, the shelter housed ~50 children and 15 caregivers. The final sample included 27 children and 10 caregivers who met inclusion criteria and provided complete data. Therefore, the analyzed sample does not represent the entire shelter population at that time but rather the subset of residents who fulfilled eligibility criteria and completed all assessments.

Although children and caregivers have different physiological nutritional requirements, analyzing both groups provides insight into how a shared institutional food environment may differentially affect age groups. This comparison enables identification of whether dietary inadequacies stem from systemic food provision or age-specific behavioural patterns.

Both groups were included because they shared the same living and dietary environment within the shelter, allowing the study to capture the overall nutritional and lifestyle context of this institutional setting. Inclusion criteria were: (1) residence in the shelter for at least 3 months, (2) age between 2 and 16 years for children and ⩾18 years for caregivers, and (3) completion of the dietary and physical activity questionnaires with signed informed consent (and assent for minors). Exclusion criteria included acute illness, use of medications that could alter appetite or metabolism, and refusal to participate. Elimination criteria were incomplete dietary records or implausible anthropometric data after quality control. The Faculty of Medicine and Nutrition FAMEN Ethics Committee (CEI-FAMEN-36) approved the protocol. We invited the tutors or parents to participate and explained the project details to them. Those who agreed to participate signed the informed consent form, while the children signed the assent form.

We calculated the Healthy Eating Index (HEI-2020) using a previously validated Food Frequency Questionnaire by Macedo-Ojeda et al.²² The HEI-2020 was selected because it provides a comprehensive measure of diet quality based on nutrient density and food group adequacy. Although it was developed according to U.S. dietary guidelines, it has been widely used in Latin American populations as a standardized framework for assessing dietary patterns. In this study, the scoring system was adapted using gram-based cut-off points derived from Mexican food composition tables and typical portion sizes to ensure cultural and nutritional appropriateness. We measured weight using an OMRON digital scale, and height was measured using a portable stadiometer. Additionally, we applied the International Physical Activity Questionnaire (IPAQ), which classifies a person’s physical activity level into 3 categories: low, moderate, and high. These categories depend on the time individuals dedicate to physical activities of different intensities during a typical week. The questionnaire evaluates activity in 4 areas: vigorous activities, moderate activities, walking, and sitting time. The IPAQ converts the time spent on various activities into a MET-minutes/week value to determine these levels (metabolic equivalent of task [MET]). We recorded the Food Frequency Questionnaire data in the Evalfinut 2.0 program to determine energy and nutrient intake. The plausibility of reported energy intake was evaluated using the Goldberg cut-off method according to the EFSA (2013) protocol.²³ Implausible energy reporters were identified but not excluded, following EFSA methodological recommendations to avoid selection bias.

The Ibero-American Nutrition Foundation (FINUT) developed EVALFINUT to assess individual diets using dietary records, 24-hour recalls, or Food Frequency Questionnaires. We utilized the Spanish Food Composition Database BEDCA 2.0 and the National Nutrient Database for Standard Reference (Release 28; USDA, United States) for nutritional analysis. Finally, we assigned HEI-2020 healthy eating index scores to each individual.^24,25

Statistical Analysis

Based on the variable distributions, we applied frequencies, percentages, and measures of central tendency and dispersion. We compared means using the Student’s t-test or Mann-Whitney U test. We determined the mean healthy eating index score and categorized subjects into optimal, average, and poor eating index groups. We performed statistical analyses using STATA 16 and GraphPad Prism Version 10.3.1. No a priori sample size or power calculation was performed because this was an exploratory study that included all eligible participants available during the study period. Given the small sample size, analyses were limited to descriptive statistics and univariate comparisons to avoid model overfitting. Future studies with larger samples will allow for multivariable modelling to adjust for potential confounding variables such as age, sex, and socioeconomic status.

Results

Sample Description

We analyzed data from 37 subjects from the PAVILA shelter: 27 children (72.97%) whose parents or caregivers agreed to participate and answered the food frequency questionnaires (51.85% boys and 48.15% girls) and 10 caregivers (27.03%), of whom 10% were men and 90% were women (data not shown). The median age was 13 years, with a minimum of 2 years and a maximum of 60 years. The overall Body Mass Index (BMI) for all participants was 24.10 ± 7.97; among children, the BMI was 21.37 ± 5.37, and among caregivers, it was 31.47 ± 9.39. Based on BMI classification, participants were categorized as having normal weight (15 children), overweight (8 children), and obese (4 children and 10 caregivers; Table 1).

Table 1.

Characterization of the PAVILA Shelter Sample. Energy Consumption and Distribution in Children and Caregivers of the PAVILA Shelter.

Variables	Overall (n = 37)	Children (n = 27)	Caregivers (n = 10)
Age (y)	13 (2-60)	11 (2-16)	38 (27-60)
Total kilocalories	2907 (1162.89-7846.70)	2861 (1242.66-6676.61)	3312 (1162.89-7846.77)
Energy adequacy (%)	147.21 (51.43-437.76)	147.21 (51.43-340.48)	151.45 (53.23-437.76)
Total protein (g)	130 (40.26-349.81)	120.90 (65.41-349.81)	132.14 (40.26-337.4)
Total lipids (g)	99.12 (38.16-349.47)	97.62 (40.13-349.47)	131.30 (38.16-348.84)
Total carbohydrates (g)	422.27 (153.69-1254.5)	422.27 (153.69-917.62)	404.21 (174.01-1254.5)
Protein (%)	17.4 ± 3.78 (95% CI: 16.14-18.66)	17.87 ± 3.97 (95% CI: 16.30-19.44)	16.15 ± 3.04 (95% CI: 13.98-18.32)
Lipids (%)	32.59 ± 6.90 (95% CI: 30.29-34.89)	31.69 ± 6.72 (95% CI: 29.03-34.35)	35.01 ± 7.14 (95% CI: 29.90-40.12)
Carbohydrates (%)	53.06 ± 9.29 (95% CI: 49.96-56.16)	53.50 ± 8.93 (95% CI: 49.97-57.03)	51.86 ± 10.60 (95% CI: 44.28-59.44)
BMI	24.10 ± 7.97 (95% CI: 21.44-26.76)	21.37 ± 5.37 (95% CI: 19.25-23.49)	31.47 ± 9.39 (95% CI: 24.75-38.19)
Normal weight (%)	15 (40.50; 95% CI: 26.30-56.50)	15 (55.60; 95% CI: 37.30-72.40)	0 (0.0; 95% CI: 0.0-27.80)
Overweight (%)	8 (21.60; 95% CI: 11.40-37.20)	8 (29.60%; 95 CI: 15.90-48.50)	0 (0.0%; 95 CI: 0.0-27.80)
Obesity (%)	14 (37.80; 95% CI: 24.10-53.90)	4 (14.80; 95% CI: 5.90-32.50)	10 (100.0; 95% CI: 72.20-100.0)
Sedentary PA (%)	24 (64.90; 95% CI: 48.80-78.20)	16 (59.30; 95% CI: 40.70-75.50)	8 (80.0; 95% CI: 49.0-94.30)
Light PA (%)	8 (21.60; 95% CI: 11.40-37.20)	7 (25.90; 95% CI: 13.20-44.70)	1 (10.0; 95% CI: 1.80-40.40)
Moderate PA (%)	0 (0.0; 95% CI: 0.0-9.40)	0 (0.0; 95% CI: 0.0-12.50)	0 (0.0; 95% CI: 0.0-27.80)
Intense PA (%)	5 (13.50; 95% CI: 5.90-28.0)	4 (14.80; 95% CI: 5.90-32.50)	1 (10.0; 95% CI: 1.80-40.40)

Continuous variables are presented as mean ± SD with 95% confidence intervals (or median [EISR] for non-normal distributions). Categorical variables are presented as n (%) with 95% confidence intervals estimated using the Wilson method (exact binomial for small samples).

Physical activity was classified into 4 categories: sedentary physical activity included 24 participants (16 children and 8 caregivers); light physical activity included 8 participants (7 children and 1 caregiver); no participants were classified under moderate physical activity; and vigorous physical activity included 5 participants (4 children and 1 caregiver; Table 1). Variables, such as BMI category and physical activity level, differed in distribution between the 2 groups and could act as potential confounders in the interpretation of dietary and activity outcomes. These factors were not adjusted for due to the exploratory nature and limited sample size of the study but should be considered in future research.

Energy Intake

Our results indicate that the percentage of adequate energy intake was 147% for children and 151% for caregivers, and there were no significant differences between the plausible reporters and the total sample (Table 1 and Figure 1).

Figure 1.

Energy intake declaration of the total population and plausible subjects. There is a difference between the declared energy intakes, but it is insignificant, P = .275, Mann-Whitney U test.

Macronutrient Profile and Distribution

Table 1 presents the percentage of macronutrients contributing to total dietary energy intake for children and caregivers. In children, carbohydrates contributed the highest percentage (53.50%) to dietary energy, followed by fats (31.69%) and proteins (17.87%). In caregivers, carbohydrates also represented the highest proportion (51.86%) of dietary energy intake, followed by fats (35.01%) and proteins (16.15%). Although children had a slightly higher carbohydrate intake (53.50%) than caregivers (51.86%), the difference was insignificant. Meanwhile, caregivers had a higher lipid and protein intake than children.

Healthy Eating Index (HEI-2020)

We evaluated dietary quality using the Healthy Eating Index (HEI-2020), which ranges from 0 to 100, with 100 representing the highest score. The total sample obtained an average score of 57.76 ± 10.24. Children scored lower (56.68 ± 8.56) than caregivers (60.68 ± 13.98; Figure 2). 2.70 % of the subjects met the criteria for a good-quality diet, while 75.68% had an intermediate-quality diet, and 21.62% had a low-quality diet (Table 2). The moderation component scores showed that participants consumed the most saturated fats and sugars. The lowest adequacy component scores indicated insufficient intake of vegetables, fish, and dairy products, meaning their consumption was below recommended daily levels (Table 3).

Figure 2.

Radar chart of the HEI-2020 (HEI-2020 of children and caregivers of the PAVILA shelter). The radar charts show the score of each component and are represented as a percentage of their maximum points on the 13 different axes. The outer edge of the radar represents 100% of the maximum score for the respective component; the centre represents 0% of the maximum score for any component.

Table 2.

Cut-Off Points for Interpreting the HEI-2020 in Children and Caregivers of the PAVILA Shelter.

Group	Poor quality diet, n (%)	Intermediate quality diet, n (%)	Good quality diet, n (%)
Children (n = 27)	7 (25.93)	20 (74.07)	0 (0.00)
Caregivers (n = 10)	1 (10.00)	8 (80.00)	1 (10.00)
Total (n = 37)	8 (21.62)	28 (75.68)	1 (2.70)

n, Frequency; %, Percentage.

Percentages are calculated within group (row-wise).

Table 3.

Score of Each of the Components of the HEI-2020 in Children and Caregivers of the PAVILA Shelter.

Components	Maximum points	Overall	Children	Caregivers
Components of adequacy
Total fruits	5	3.18	3.40	2.56
Whole fruits	5	2.48	2.67	1.98
Vegetables	5	1.67	1.52	2.09
Legumes	5	3.24	3.19	3.37
Whole grains	10	6.32	6.35	6.23
Dairy	10	4.42	4.72	3.59
Total proteins	5	2.90	2.97	2.69
Fish	5	1.92	1.88	2.03
Fatty acids	10	3.79	3.05	5.81
Components of moderation
Refined grains	10	6.65	6.52	7.00
Sodium	10	9.20	8.95	9.88
Added sugars	10	5.10	4.88	5.69
Saturated fats	10	6.83	6.51	7.71
		57.76	56.68	60.68

Misreporting

Our analysis showed that 51.34% of the samples were plausible declarers, while 48.63% were non-plausible declarers. Among the non-plausible declarers, 18.91% were under-declarers, and 29.71% were over-declarers (Table S1). There were no significant differences in HEI-2020 scores between the total population and plausible subjects (Figure 3). The cut-off points for energy intake and physical activity level to calculate misreporting are shown in Table S2.

Figure 3.

Radar graph of the HEI-2020 of the subjects of the total population and the plausible subjects of the PAVILA shelter. The radar graph shows the scores of each of the 13 axes, observing differences between the total population and the plausible subjects in total fruits, legumes, whole grains and refined flour; however, the difference is not significant, P > .05, Mann-Whitney U test.

Discussion

Energy Intake

According to the IOM recommendations, the study subjects consumed 147% of the recommended energy intake for children and 151% for caregivers.²⁶ These results contrast with a study by the National Health and Nutrition Survey 2006, which reported an adequacy percentage of 88% for school-aged children and a median energy intake of 1501 kcal/day. The study eliminated implausible reporters, but our study did not exclude them, as doing so did not change our results (Figure 1).²⁷ Moreover, according to EFSA recommendations, we did not exclude potentially erroneous informants from the analysis (European Food Safety Authority).²³

Profile and Distribution of Macronutrients

Both groups exceeded the upper tolerable limit of energy intake from proteins recommended by the IOM.²⁸ The USDA dietary reference intake for total proteins is ~0.95 to 1.14 g/kg of body weight for children and 0.83 g/kg for adults. Given that we had data on the weight of both study groups, we analyzed the adequacy of protein intake, which was 2.24 times higher for children and 2.02 times higher for adults than the EFSA recommendations.²⁹

Healthy Eating Index (HEI-2020)

The results suggest that the modernization of society has introduced sociocultural changes that impact dietary habits.³⁰ People now spend less time shopping and preparing food, opting for processed or fast foods, which often leads to excessive consumption of animal products, especially meat and derivatives, as well as pastries and refined cereals. These changes increase the risk of developing NCDs in the future, in 2016, 40.5 million (71%) of the 56.9 million deaths from NCDs occurred in people aged 30.³¹ In Mexico, NCDs such as type 2 diabetes and ischemic heart disease are the leading causes of death.³² In 2019, the age-adjusted mortality rate for communicable diseases was 52.4/100 000 inhabitants, while the rate for non-communicable diseases was much higher, reaching 412/100 000 inhabitants.³³ The main risk factors for NCDs include elevated fasting plasma glucose levels, high BMI, high blood pressure, and an unhealthy diet, which account for more than half of the attributable deaths.^34,35 Notably, the incidence rate of diabetes in Mexico increased from 367 to 496/100 000 inhabitants between 2006 and 2019.³⁶ This underscores the need to assess the dietary habits of the general population, especially more vulnerable groups, such as children.³⁷ A key point is that as income decreases, people tend to consume more low-cost foods.³⁸ Unhealthy foods are often cheaper than nutrient-rich foods, with those high in fats and sugars costing less than foods with less energy density.³⁹ This pattern is evident in this vulnerable population. These findings highlight the importance of targeted nutritional strategies within institutional settings, this suggest the need for structured nutritional strategies to support healthier eating behaviours among children, including an adequate consumption of fruits, vegetables, whole grains, and legumes, while reducing their intake of saturated fats, animal-based foods, and processed meats. These changes can lead to better nutrition and a more active lifestyle. A healthy diet provides essential nutrients to function optimally, maintain an appropriate weight, and reduce the risk of chronic diseases.^40
-42 The Healthy Eating Index HEI-2020 helps identify individuals at risk of developing NCDs based on the frequency with which they consume certain food groups associated with these diseases.

According to the HEI-2020, the overall diet quality of participants at the PAVILA shelter was below optimal. Both children and caregivers scored below 65 points, which, based on interpretive guidance for the HEI-2015⁴³ and consistent with the HEI-2020 framework,⁴⁴ corresponds to a “D” grade, indicating diets that need improvement. Although the mean difference between children (56.7) and caregivers (60.7) was modest, it suggests slightly better adherence to healthy eating patterns among caregivers, possibly related to greater autonomy in food selection and meal supervision. Importantly, children exhibited lower adequacy scores for fruits, vegetables, dairy, and whole grains, as well as lower moderation scores for added sugars and saturated fats indicating higher consumption of these components. This pattern reflects insufficient intake of nutrient-dense foods and higher intake of energy-dense, low-nutrient foods. National data from the Mexican National Health and Nutrition Survey (ENSANUT) support these findings, showing that more than half of the Mexican population, particularly children, exceed the World Health Organization’s recommendation of limiting free sugars and saturated fats to <10% of total energy, while consumption of fruits, vegetables, and dairy remains low and sugar-sweetened beverages are the main source of added sugars.^45
-48 In practical terms, these results underscore the need for targeted interventions within the shelter environment to reduce added sugars and saturated fats ideally replacing them with polyunsaturated and monounsaturated fats and to increase access to and consumption of fruits, vegetables, and dairy products, in accordance with WHO guidelines^49,50 and the adequacy components of the HEI-2020.

In this study, we evaluated the plausibility of EI. Table S2 shows the physical activity level (PAL) assigned to individuals and groups according to EFSA recommendations and the energy intake data from 24-hour records. We classified the subjects as having plausible, insufficient, or excessive energy consumption based on the ratio between reported EI and estimated energy needs (Table S1).⁵¹

Using the Goldberg and Black formula, we calculated the lower 95% confidence limits (±2 standard deviation limits). According to these criteria, we classified subjects with reported EIs below the limits as under-reporters, those with EIs within the cut-off points as plausible reporters, and those with EIs above the limits as over-reporters.⁵²

Nearly half of participants were classified as implausible reporters; however, no significant differences in HEI-2020 scores were observed between analyses including all participants and those restricted to plausible reporters (Figure 1). This finding suggests that the interpretation of suboptimal diet quality remains robust regardless of reporting plausibility. While misreporting is common in dietary assessment studies,⁵³ particularly in small and heterogeneous samples, its impact in this study did not materially alter the overall conclusions regarding diet quality within the shelter environment.

Unlike community-based populations, residents of institutional shelters depend largely on centrally planned meals.¹⁶ And several studies have shown that nutritional status in shelters is strongly influenced by institutional resources, food procurement systems,^16,54,55 therefore, dietary inadequacies identified in this study may reflect procurement practices, budgetary constraints, or menu planning decisions rather than solely individual preferences.

These findings suggest opportunities for institutional-level interventions, such as increasing procurement of fresh produce, improving menu diversity, and implementing caregiver-focused nutrition training programs. Because caregivers directly influence food preparation and supervision, enhancing their nutritional awareness could indirectly benefit children’s diet quality.

Strengths and Limitations

This study offers several methodological strengths, particularly the use of appropriate methodologies to analyze populations’ diets, which enhances the analysis of the obtained data.

However, this study has certain limitations. The sample size was small, and all participants were recruited from a single shelter, which may introduce selection bias. Consequently, the findings reflect the specific living and dietary conditions of the PAVILA shelter and may not be generalizable to other shelters or community-based vulnerable populations. Despite this limitation, the study provides valuable exploratory insight into the nutritional and physical activity context of institutionalized children and their caregivers. Finally, because of the cross-sectional design, the observed associations between diet quality, physical activity, and anthropometric outcomes cannot be interpreted as causal relationships. The descriptive comparison in Table 1 suggests differences in BMI categories and physical activity levels between children and caregivers. The absence of multivariable adjustment limits the ability to disentangle the independent effects of BMI, sex distribution, and physical activity on diet quality. Although these factors were not included as covariates, they may influence the observed dietary patterns and should be addressed in future studies with larger samples. One notable strength is the use of the HEI-2020 diet quality index, which evaluates the components of the diet and their alignment with North American dietary guidelines.⁴⁴ This is an advantage, as the HEI components represent basic food groups that can apply to any culture. While the HEI reflects dietary guidance designed in the United States, it can also serve as a valuable tool for assessing diet quality in countries without an index or when comparing associations between specific diet definitions and health outcomes. Researchers have used the HEI, or adapted versions, to assess diet quality in several countries beyond the United States, including Brazil, Iran, China, Greece, Italy, Spain, Belgium, Sweden, France, Malaysia, and now Mexico. It is important to note that there is no specific diet quality index for this population in Mexico, so researchers need adapted and validated indicators to assess Mexican dietary recommendations. Additionally, over time, societies have developed various food combinations based on local availability, leading to traditional dietary patterns, such as the Mediterranean, Japanese, and vegetarian diets, which have shown beneficial associations with health.⁵⁶

Additionally, due to the exploratory nature of the study, no a priori sample size or power calculation was conducted, which may limit the ability to detect small differences. The analyses were restricted to descriptive and univariate comparisons to avoid model overfitting given the small sample size; therefore, potential confounding factors such as age, sex, and physical activity level were not controlled for and could partly explain some of the observed patterns. These considerations, together with the non-probabilistic sampling from a single shelter, indicate that the results should be interpreted with caution and mainly as exploratory evidence. It is also important to note that the PAVILA shelter represents the first institution sampled within a broader ongoing project that will include other shelters, which will allow for larger and more representative analyses in future stages.

Conclusion

Children had a higher prevalence of poor diet quality (25.93%) than caregivers (10.0%). None of the children had a good-quality diet. Dietary patterns in both groups do not align with national and international dietary guidelines.

The objective of conducting such studies is to comprehensively measure these indicators so that dietary quality patterns or indices can be globally standardized.

Supplemental Material

sj-docx-1-nmi-10.1177_11786388261445757 – Supplemental material for Diet Quality and Physical Activity in Children and Caregivers From PAVILA Shelter in Northern México

Supplemental material, sj-docx-1-nmi-10.1177_11786388261445757 for Diet Quality and Physical Activity in Children and Caregivers From PAVILA Shelter in Northern México by Ortega-Ramírez Irving Gerardo, Muñoz-Yáñez Claudia, Soto-Méndez María José, Aba-Guevara Jackeline and Guangorena-Gómez Janeth Oliva in Nutrition and Metabolic Insights

Footnotes

Acknowledgements

The authors thank Dr Fabiana Salas and the PAVILA home caregivers who collaborated in carrying out this study.

Abbreviations

Noncommunicable diseases (NCDs)

Healthy Eating Index (HEI)

Dietary Guidelines for Americans (DGA)

United States Department of Agriculture (USDA)

National Cancer Institute (NCI)

Centre for Nutrition Policy and Promotion (CNPP)

Department of Health and Human Services (HHS)

International Physical Activity Questionnaire (IPAQ)

Metabolic equivalent of task (MET)

Fundación Iberoamericana de Nutrición (FINUT)

Base de Datos Española de Composición de Alimentos (BEDCA)

The Institute of Medicine (IOM)

Encuesta Nacional de Salud y Nutrición (ENSANUT)

European Food Safety Authority (EFSA)

Body mass index (BMI)

Energy intake (EI)

Physical activity level (PAL)

Basal metabolic rate (BMR)

ORCID iDs

Ortega-Ramírez Irving Gerardo

Soto-Méndez María José

Aba-Guevara Jackeline

Guangorena-Gómez Janeth Oliva

Ethical Considerations

The research adhered to the ethical guidelines outlined in the Declaration of Helsinki and received approval from the local ethics committee, specifically the Faculty of Medicine and Nutrition FAMEN Ethics Committee (CEI-FAMEN-36) at the Universidad Juárez del Estado de Durango.

Consent to Participate

Participation in the study required informed consent from the parents or legal guardians, as well as a letter of consent from the child.

Author Contributions

JOGG study design and article writing. CMY article writing. IGOR preparation of tables and figures, article writing, and participation in sampling. JAG preparation of tables and figures and article writing. SMMJ article review.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The Science and Technology Council of the State of Durango partially funded this study.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request. Access may be subject to ethical approval due to the inclusion of data from minors residing in a protected institutional setting.

Supplemental Material

Supplemental material for this article is available online.

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