Multilevel analysis concerning the relationship between social vulnerability and the healthy use of leisure time in children and adolescents in Argentina: A national population-based study

Study design and sample

This was a cross-sectional, analytical study of a secondary database of the Module on Activities of Girls, Boys and Adolescents (MANNyA)²¹ that was included as part of the Annual Urban Household Survey (EAHU, by its Spanish initials) during 2012. The MANNyA²¹ was carried out on the basis of an inter-institutional initiative between the Ministry of Labor, Employment and Social Security, the National Secretariat for Children, Youth and Family, the National Commission for the Eradication of Child Labor, the National Institute of Statistics and Censuses (INDEC, by its Spanish initials) and the Provincial Statistical Offices.

Argentina is divided into 6 regions: Gran Buenos Aires: Autonomous City of Buenos Aires and 24 districts of Buenos Aires. Northwest Region (NOA): Provinces of Catamarca, Tucumán, Jujuy, La Rioja, Salta and Santiago del Estero. Northeast Region (NEA); Provinces of Corrientes, Formosa, Chaco and Misiones. Cuyo Region: Provinces of Mendoza, San Juan and San Luis. Pampeana Region: Provinces of Buenos Aires (except the 24 districts of Greater Buenos Aires), Entre Ríos, Córdoba, Santa Fe and La Pampa. Patagonia Region: Provinces of Río Negro, Neuquén, Chubut, Santa Cruz and Tierra del Fuego.

According to data from the last National Population, Household and Housing Census carried out in 2010²², the country had 40,117,096 inhabitants, 91% of whom lived in urban areas, with a male/female ratio of 0.95/1. The composition of the population in large age groups showed significant differences between each of the provinces; the lowest percentage of girls, boys, and young people registered in CABA (16.3%) (Gran Buenos Aires region), and the highest percentage in the province of Misiones (32.5%) (NEA region).

The MANNyA²¹ was oriented to the population aged 5 to 17 years and framed in the conceptual field of child labor surveys in Argentina. Within this survey, a block of questions was included to collect data on the use of leisure time.

The sample consisted of children and adolescents aged 5 to 17 from urban conglomerates in Argentina. It was a probabilistic, stratified and multi-stage sample of 34,487 households, with a total of 25,915 children and adolescents surveyed (Figure 1)²¹.

The MANNyA²¹ sample design was based on the sample design of the Annual Survey of Urban Households (EAHU) of the Directorate of Statistical Methodology of INDEC, which considers towns with 2,000 and more inhabitants.

Figure 1. Stages of data collection²¹.

Non-response represented 0.97% of the cases, that was not possible to interview the boy, girl, and/or adolescent is, in 141 households.

The secondary database of the MANNyA²¹, had the weighting of the survey data from three factors: 1) defined by the inverse of the probability of selection of each dwelling in the sample; 2) adjusted the data for non-response of a part of the households, 3) adjusted before the population projections for the survey domains. This last factor calibration process uses marginals that consider the structure of the population by sex and age groups.

Data collection instruments

The data from the MANNyA secondary database²¹, the basis of this analysis, was collected using a self-administered instrument. The databases of MANNyA 2012²¹ are public and can be obtained in the web site of INDEC.

The information-gathering stage was carried out between July and October 2012, during which time each of the selected dwellings visited and applied corresponding questionnaires.

The instrument included closed-ended questions aimed at obtaining what children and adolescents usually do in their leisure time.

During the process of elaboration of the instrument, including the phases of conceptual design, questionnaire tests, preparation of manuals, the training process on data collection, input and criticism of information guided by professionals from the government area included. The provincial statistical offices supervised fieldwork for the survey implementation.

The leisure time questions module designed so that the informants were self-responding. When the child or adolescent was absent or the responsible adults refused to answer the questionnaire, it was determined that the informants could be either the older siblings or another adult in the household.

To facilitate the implementation of the questions of the leisure time block within the MANNyA²¹ in the youngest children, the interviewer had a card of illustrations.

Outcome "Healthy use of leisure time", defined as the time for rest and leisure activities, play and recreational activities suitable for the age. It also implies the right to participate freely in cultural life and the arts⁹. In the framework of the analyzed module, leisure time activities are defined as everything that the child does before or after school, or on the weekends²¹.

The dimensions of analysis for this study were:

Explanatory variable

"Social vulnerability", defined as the situations of insecurity and defenselessness experienced by communities, families, and individuals in their livelihood conditions, as a consequence of the impact caused by any socio-economic event. In addition, the management of resources and the strategies used by them to cope with the effects of this event were considered. Today, social vulnerability is considered one of the main social determinants of health¹³, where most health problems can be attributed to people's socio-economic conditions.

For the construction of this variable, a Social Vulnerability Index (SVI) was prepared (Table 1) based on the data from the MANNyA secondary database²¹. The dimensions and weighting values of the conceptualization of social vulnerability were based on previous publications^22,23.

The categories included material assets, such as employment and housing, and non-material assets, such as those related to human capital (access to the health system and educational system of the head of household).

The construction of the SVI was based on the selection of dimensions represented by different categories which, depending on the risk situation, were defined as «moderate» or «critical».

Since each of the selected categories may have different levels of intensity, it was decided to define differential weights within them²⁴.

Next, the SVI of each household where the child or adolescent is living was categorized as follows: without SVI was assigned to those cases with a value of 0.00; low SVI was assigned to those cases with values between >0.00 and ≤0.30; moderate SVI was assigned to those cases with values between >0.30 and ≤0.45; high SVI was assigned to those cases with values greater than 0.45. These categories were defined and adapted by taking the cohort points proposed in a previous study de Argentina²⁴.

Co-variables

“Household activities”. Of the child/adolescent defined as: activities carried out in the home in an intensive and/or non-intensive manner in the reference week.

Includes those who took care of their siblings (including the transfer to school) or some other person living at home, who washed the dishes, clothes or ordered the house, and those who did the shopping or errands alone. Household activities can be intensive and non-intensive. Intensive domestic activities defined as those that were carried out for 10 hours or more in the week in the case of children (5 to 13 years) and 15 hours or more in the week for adolescents (14 to 17 years).

“Economic activities”. Of the child/adolescent defined as: working in the reference week.

This group is made up of those who carried out an activity that generates goods or services that have a market value for at least one hour. Economic activities include paid in money or in-kind and unpaid (ad-honorem work activities and non-paid activities carried out to help a family member obtain an income).

“Production activities”. Of the child/adolescent defined as: the production activities for self-consumption in the reference week.

Those who carried out productive activities for household consumption for more than one hour includes those who helped in the construction or repair of their own home, cultivated; and/or harvested in the garden; and/or taking care of the farm; and/or farm animals to consume at home and those who went out to fetch water or firewood.

“Age”. Is defined as childhood <10 years old and adolescence ≥ 10 to 19 years old according to the World Health Organization (WHO) classification²⁵.

“School Attendance”. Of the child/adolescent defined as: self-report of attending school at the time of the survey.

“Decile group of total household income in the region (DGHIR)”²⁶. Variable elaborated and defined by the government agency and found included in the secondary database²¹.

It is defined as the total family income, at of the total income of all its members. The construction of deciles consists of ordering the population or households by income amounts from lowest to highest according to the defined income variable and then grouping it into subsets that each contain 10% of the units (households). From this ordering, the income intervals corresponding to each of the ten subsets formed (income deciles) were determined. The potential of this indicator is that categorizes households taking two dimensions: region and household income.

Statistical analysis

The variables of interest were analyzed descriptively using position and dispersion measurements and frequency distribution.

Weighting proportions in descriptive analysis was, used considering the sample method proposed by the MANNyA secondary database²¹.

Firstly, it was carried out a univariate analysis and the variables that presented statistical significance were introduced for the fix-effects multivariate model^27–29. Given the hierarchical structure of the data (individuals grouped in regions of the country), we conducted a multilevel logistic regression analysis to explore the relationship between the social vulnerability and the healthy use of leisure time. The models considered socio-economic and socio-demographic variables at two levels: an individual level, relating to the child/adolescent (domestic, production, and economic activities, gender, age and, school attendance), and a contextual level (decile group of total household income in the region ). An empty model (Model 0) was performed, and calculated the level 2 variance and the intraclass correlation coefficient (ICC). The proportion of the variance at level 2 explained (PVE) by the different models was calculated as PVE= (V) × 100.

We have performed AIC-BIC statistics to judge the goodness of fit shown in each table.

The statistical package Stata® v14.2 (Stata Corporation, College Station, Texas, USA) was used for all the analyses, and a p<0.05 value was considered statistically significant.

Ethical considerations

The study was carried out on the basis of a secondary analysis of the MANNyA database²¹, compiled by different public bodies under the leadership of the INDEC. In Argentina, public statistics produced by the State are part of the National Statistical System created by Law No. 17622, which guarantees confidentiality and the Protection of Personal Data through Law No. 25326.

The database is currently public and open-access, and is de-identified by the responsible public body³⁰. Thus, this study did not require an evaluation by an ethics committee and, in addition, qualifies for the status of being exempt from obtaining informed consent.

Descriptive phase

As shown in Table 2, the sample consisted of 52.6% males and 63.5% adolescents, where 6.9% are less than 6 years old. In total, 32.2% of the respondents were from Gran Buenos Aires and 30.9% from the Pampeana region. It is also observed that 95.5% were attending school at the time of the survey and 58.1% had some kind of health coverage.

Table 3 shows the prevalence of activities of healthy use of leisure time, according to socio-demographic characteristics. It was observed that the prevalence of performance of school activities was 90.1%. Art and other courses activities (21.8%) had the lowest prevalence of performance as compared to the other activities of free-time use.

The socialization, sports/recreational activities, use of ICTs and the Internet showed an intermediate prevalence between 51.1% and 74.2%, being, in most cases, higher in males than in females.

Table 4 shows the main results of the subgroup analysis. In the group without SVI (10.9% of the sample), it was observed that the highest prevalence was the performance of school activities (90.9%), with the art and other courses activities being the least prevalent (19.2%).

Among those with a low or moderate SVI (87.1%), the distribution of the performance of leisure time activities was the same as that of the group without SVI, although with higher values in the cases of ICT (75.1%), Internet (66.7%) and Art and other course (22.4%).

In the group composed of those with a high SVI (2.1%), the distribution of the performance of leisure time activities changes as compared to the other two groups of SVI. While school activities (83.1%) and Art and other course (11.4%) continues to be the most and least popular choice, respectively, Sports are in second place (48.1%), replacing ICT, which have moved into third place (45.1%). In turn, Socialization activities (36.3%) were more prevalent than Internet use (33.7%).

Analytical phase

In the multilevel models, statistically significant associations between some leisure time use activities and social vulnerability are seen (Table 5).

Regarding the relationship between moderate/high SVI and the non-performance of Art and other course, an OR of 1.398 was found to be statistically significant (p<0.001).

The empty model of the dependent variable of Art and other course shows a variance between the deciles of household income in the region of 0.20, a standard error (SE) of 0.37, and an ICC of 0.058. In other words, 5.8% of the variability observed in the non-performance of art activities is attributable to the decile of household income at the regional level. It was introduced the explanatory variable and other covariates into the model, this variability decreases to 0.09, with a SE of 0.21 and an ICC of 0.026, and the PVE is 55.45% (Table 5).

Similarly, this was reflected in the relationship between SVI in the highest stratum and the internet use activities (OR 1.586 and p=0.000).

On the other hand, it could be observed that the non-use of the ICT during leisure time in the group with moderate/high SVI yielded an OR of 1.580, being significant (p<0.001).

Based on the aforementioned, in the final models (Model 2), which considered individual and contextual variables, an increase in the likelihood of unhealthy use of leisure time is observed when there are increased moderate/high SVI levels in the cases of Art and other course, ICT, and the Internet.

Principal findings

Our results highlighted the impact of a moderate/high social vulnerability index on the reduced performance of some healthy leisure time activities such as art, ICT and internet use, among children and adolescents in Argentina.

Some risk factors from the social sphere where biographies of children and adolescents are developed may have an impact on the ways in which they perform in society. The fact that a significant part of the risk to their health and quality of life occurs in this context was highlighted in the field of social epidemiology³¹.

Comparison with prior studies

As Feito⁵ suggests that vulnerability has a dimension of susceptibility to harm, conditioned by intrinsic and extrinsic factors, anchored in the radical fragility of the human being, but undoubtedly largely attributable to social and environmental elements. In this sense, our study showed that a part of the population under analysis had some degree of social vulnerability.

Regarding the healthy use of leisure time in the population under analysis, it was observed that some activities were more prevalent than others; generally, art sports, and socialization activities were less frequent. This information is important because, as other authors have shown^32,33, these activities should be proposed as strategies to promote the health of children and adolescents at social risk³⁴, since they contribute to the psychosocial and physical state of children and adolescents, while at the same time promoting life skills.

Another aspect to consider is that of gender differences in the performance of activities during leisure time. For example, it is observed that “sexual division in the activities between men and women is already established in childhood and adolescence”³⁵. Our results showed that boy tended to do more ICT activities and girl more art activities. These differences between boys and girls already had been found in other previous studies^36,37.

Furthermore, it should be noted that the use of digital-free time, mainly focused on the use of the Internet and ICT, has become increasingly present in the activities of children and adolescents and has become an agent of socialization³⁸.

However, our results show that the use of the Internet is significantly conditioned by social vulnerability. In this sense, it was observed that, in the group with the highest level of vulnerability, there is a much better chance of not using the Internet and ICT. This is relevant and shows how the condition of vulnerability becomes a determinant barrier when accessing certain goods and services, especially if progress is to be made in reducing digital divides³⁹.

Our findings on the use of ICT were similarly, reflected in the use of the Internet (models adjusted); it was observed that there was a risk of not using ICT and Internet in the groups with moderate/high levels of social vulnerability. It should be noted that two years before this survey, Argentina implemented the “Connecting Equality” policy⁴⁰, a federal broad-scope program. This is important because the effectiveness of the digital divide reduction policies, especially among the most vulnerable groups, could present certain barriers to access⁴¹.

These results in the use of screens were opposite to what Auhuber et al.¹⁶ in her study published in 2019 in children and adolescents in Germany. The results revealed that girls, children with lower leisure-economic status as well as older children reported using screen-based media more often (models adjusted). These differences may be differential access to ICT between countries with high vs. middle-low income. Also, to the period difference between our study with the work carried out in German children and adolescents.

There were also marked differences with respect to art activities, where it was found that the higher the social vulnerability index, the higher the probability of not performing these activities. However, this result highlights the importance of promoting this type of activity in children and adolescents, since, according to the evidence and based on the findings by Wald⁴², the changes perceived as a result of participating in art workshops are closely linked to feelings of well-being, the development of personal capacities and the strengthening of group relations, which may be linked in a broad sense to the paradigm of health promotion. A narrative study postulated the need to focus on mental health risk related to social vulnerability aspects in children and adolescents in Sub-Saharan Africa⁴³.

A relevant fact of this study is that it was observed that the contextual level had a greater weight in the definition of the activities carried out during the free time of children and adolescents. Being consistent with other studies that highlighted the positive association between variables of the physical and social environment of the home with the performance of the always activity^44,45.

In some free time use activities, such as internet use, ICT, and art, statistically significant associations were found with OR less than one between low IVS and not performing these activities. The low IVS in this case, acts as a factor of protector to leisure time activities.

This protective effect could be because despite having a low IVS, children and adolescents could have still resilience capacity⁴⁶. In this line, a study carried out in children in Chile, demonstrated the resilience capacity even with low resources⁴⁷.

This result may also be related to the presence of capitals⁴⁸ (economic, cultural and social capitals) in this group. Where Individuals and groups draw on a variety of resources—capitals—to maintain and enhance their positions in the social order⁴⁹.

Also, in this way, it would facilitate the recognition of strengths in groups usually considered "vulnerable"⁵⁰. This interesting result will be need to be addressed in future research.

Strengths and limitations

The weakness of the proposal is that the research question was addressed based on the analysis of a secondary data source, so it is possible that some aspects related to the construction of the SVI were left out. However, the methodology for the construction of this index is flexible and there is not a sole theoretical frame of reference.

Regarding the construction of the social vulnerability index and where it was visualized that a part of the sample had a certain degree of vulnerability, it could be a limitation when achieving better discrimination between the strata and considering other variables of the socio-economic sphere that were not available in the secondary database. However, this work serves as a background for the generation of new studies and lines of work using other methodologies.

This approach has potential because it arose from the data itself, although it was guided by a previous antecedent in our country²⁴. However, from the scientific literature search, we found the construction of other social vulnerability indices applied to health outcomes, where they take the dimensions included in our proposal in a similar way^51,52.

Another limitation was the data collection date (2012), where some aspects may have been modified so far.

Also, the public database did not have data on non-responders, which may have led to selection biases. Although according to the institution that carried out the survey, this percentage was less than 1 % of the selected households represented by 141 households.

The advantages of using multilevel analysis in social problems are clear, both from the statistical point of view⁵³; and from the interactions of individual and social factors analysis⁵⁴.

In the case, the hierarchical cluster analysis provided additional information about the percentage of the residual variance is explained by the variable “deciles of household income according to the region”.

Estimating the effect of this contextual variable has a relevant contribution to the sociological debate, accounting for the “social structure” of the family⁵⁵, assigning added value to the problem explored in this work and to the development of public policies and their differentiated impacts among the different classes that make up a specific society.

However, in some specific activities, such as school, sports, and socialization, lower quality models were observed, with high ICCs. These findings could be due to the multilevel analysis method; where some findings through this method could be difficult to explain⁵⁶, so the creation of more evidence will be needed. Also, more complicated models may be closer to reality but testing model fit and examination of model assumptions is more difficult^57,58.

However, this study has many important strengths. Among them, the large sample size stands out. It allowed for multivariate and multilevel analyses and the national representativeness of the sample, since the survey of the secondary database was coupled to the Annual Urban Household Survey (EAHU)²¹ by following the application of a rigorous probabilistic sampling, thus ensuring the accuracy of the data obtained and the scope of the entire urban population of the country.

This study can serve as the basis for new research lines in the field of leisure time in the child and adolescents, where there are few published antecedents in the Southern Cone and low- and middle-income countries. Future national surveys will need to deepen aspects related to the leisure time activities such as type of activity, frequency, number of hours per week carried out, etc.

The results may serve as a baseline for monitoring policies and programs aimed at the healthy use of leisure time, considering the context of the social inequalities.