Abstract
Aim
The objective was to identify if family social exclusion is associated with child motor and social development delay in Southeastern Brazil.
Design
A cross‐sectional study was conducted using data from a sample of 348 children under 3 years, proportional to the number of children registered in the primary care centres of the municipality.
Methods
Child development was measured using the “Developmental Surveillance Instrument” which was developed by the Ministry of Health in Brazil and is used for public health nurses and clinicians in their practice. An index was used to evaluate social exclusion.
Results
The prevalence of child motor and socioemotional developmental delay was 27.6% and 17.2%, respectively. Children in the most social excluded group were more likely to have delayed motor development (OR = 3.4; 95% CI = 1.14; 10.55) and socioemotional developmental delay (OR = 3.9; 95% CI = 1.05; 9.02) than children in the least social excluded group.
Keywords: child development, cross‐sectional study, developing countries, social deprivation, social disadvantage
1. BACKGROUND
The early years of life are crucial for shaping children's developmental potential across the life course. However, an estimated 250 million children under 5 years in low‐ and middle‐income countries are at risk of not reaching their full learning, social and emotional development potential, which has a negative impact on their future (Lu et al., 2016). The family's low socioeconomic status position and the environmental context in which children have been associated with a negative impact on the infant development include the domains motor, psychosocial and cognitive development (Black et al., 2017; Johnson et al., 2016; Ursache & Noble, 2016).
Recognition of the importance of early childhood development (ECD) can be evidenced by the growth of countries that have adopted multi‐sectoral policies to promote ECD and their inclusion among the 2015–2030 Sustainable Development Goals (Richter et al., 2017). Over the past three decades, Brazil has shown a substantial improvement in child health indicators with improvements in child survival; however, this occurs unequally within country and among the income quintiles (Carvalho et al., 2020; Victora et al., 2011). Therefore, it is still necessary to overcome the inequalities of the most vulnerable groups to ensure that children achieve healthy and holistic development. In early childhood, biological and social determinants directly affect children's brain, cognitive, motor, social and emotional development (Walker et al., 2011). More specifically, poverty, lack of stimulation, excessive stress, poor caregiver‐child relationships and the surrounding social environment have been identified as important risk factors for child development (McCoy et al., 2015; Walker et al., 2011). Social inequality and adverse early childhood experiences have long‐term physiological and epigenetic impact on brain development and cognition (Shonkoff & Garner, 2012).
Studies conducted in different regions of the world showed that ECD is closely related to the family's socioeconomic situation. A study from India, Indonesia, Peru and Senegal revealed socioeconomic gradients of ECD and specifically found that children under 2 years from the wealthiest households had higher developmental scores and better growth than children from the poorest households (Fernald & Hidrobo, 2011). Research in Iran has found that home affordance, parental education, house space, availability of toys and attending daycare were associated with children's motor development (Valadi et al., 2020).
However, a growing body of research indicates that economic poverty alone does not explain the large disparities in maternal and child health care between rich and poor families. Consequently, it is necessary to develop new methodologies and guidelines that can address social inequality and socioeconomic positions that can link these measures with health (Krieger et al., 1997). Without specific measures to address the family social roots, social inequality in health cannot be addressed (Shiffman, 2000). A systematic review found that social excluded families were affected by greater health problems than privileged social families (Yonekura, 2011), and new approaches to analyse wealth inequalities have been proposed, despite being widely studied (Barros et al., 2020). Social exclusion, defined as a structural and multidimensional process that involves a lack of material resources, work opportunities and social relationships (OPS, 2003), has been considered by several Latin American researchers (Facchini, 1995; Salum & Queiroz, 1997; Trapé, 2011) as a specific indicator to understand the health‐disease process and analyse social determinants.
A study from Australia observed that social exclusion had a negative impact on maternal and child health, considering various indicators as poor accommodation, unemployment of mother, no access to a car, difficult financial situation, marital status, low education of mother, small social support network, poor health outcomes and unplanned pregnancy (Eastwood et al., 2013). A study from South Korea found that maternal job strain during the pregnancy is a determinant of infant neurodevelopment delay at 6 and 12 months (Kim et al., 2015). In China, a study observed that social inequality was associated with poor neurodevelopment for children under 3 years in a poor rural area (Zhang et al., 2017). In Peru, a study highlighted that children between 0 and 5 years in rural areas whose mothers had low schooling and lived in households with unsatisfied basic needs had lower developmental scores (Díaz et al., 2017). Researchers in Colombia showed that children who lived in poor areas had more development problems than children who lived in rich areas (Rubio‐Codina et al., 2016). A cohort study in three different cities in Brazil showed a stagnation on reducing rates of child mortality that could be associated with economic decline and increased poverty (Carvalho et al., 2020).
Besides poverty, the magnitude of social exclusion indicators in Brazil has not been fully elucidated. Thus, this study is based on the operational model of Trapé (2011) that developed a social exclusion index that assesses differences in social exclusion between families, taking into account different variables, with more precise evaluation for the Brazilian population. This new index allowed us to investigate the relationship between social exclusion and early child motor and socioemotional development in Southeastern Brazil.
2. METHODS
2.1. Study design and sample
This cross‐sectional study analysed data from a broader study entitled “Effect of nutritional counseling from Integrated Management of Childhood Illness strategy on eating habits, nutritional status and child development” (Palombo et al., 2018). The study was conducted in a sample of 348 children under 3 years of age, enrolled at 12 primary health care centres of a municipality with 48,000 inhabitants, located in São Paulo State, in Southeastern Brazil. The municipality is located 70 km west of the State's capital, which is Brazil's financial centre, and the Southeastern region is one of the most developed, richest, yet with higher social inequality in the country.
For the broader study, the sample size was estimated based on the number of children under 3 years of age registered at all 12 primary care centres (n = 3904), 50% prevalence rate of children with inadequate food practices, 95% confidence level and 5% margin of error, which indicating a necessary sample size of 350 children. Inclusion criteria were: child under 3 years of age who resided with their biological mother in the study municipality. In the case of more than one child younger than 3 years, the youngest child was selected for participation. We excluded non‐biological children, twins, children with health problems such as metabolic syndrome, genetic and/or neurological problems and children with a previous diagnosis of sickle cell anaemia. Research Ethics Committee approval was granted by the Research Ethics Committee of the University. An informed consent was obtained from all participants and parent/guardian of each participant under 18 years of age.
2.2. Data collection and variables
2.2.1. Outcome
Early childhood development was measured using the “Developmental Surveillance Instrument” (Brasil, 2002) which was developed by the Ministry of Health in Brazil, based on adaptations of the Denver‐II (Bonner et al., 1984) and Gesell (1996). This tool is organized into 11 age groups, which correspond to different developmental stages recommended for consultations of children between 0 and 6 years of age (Brasil, 2002; Freitas, 2015). For each age group, there are four indicators related to the domains of language, motor, socioemotional and cognitive to follow the process of child development (Brasil, 2002). Although it does not provide a diagnosis of child development, this instrument serves as a guide for primary care practitioners to monitor whether children are able or not able to attain basic developmental milestones (e.g. the child lying face down holds the head for 1 s; Recognize when someone is talking to him) and identify children at risk of potential developmental delays. For this study, we focused on children's motor that refers to the gradual process of refinement and integration of biomechanical skills and basic movement patterns such as running, jumping and catching proficiently, especially during childhood (Utesch & Bardid, 2019), and socioemotional development (refers to the social interaction of the baby to the mother and others) (Brasil, 2002). There is a scarcity of studies involving social exclusion and these two domains of development, which justified the selection for this study.
To assess development, at the time of the interview, the child was observed by the researchers (two Registered Nurses, one master's student, and one doctoral student) as to the achievement of developmental milestones. When necessary, mothers were also consulted to confirm the acquisition of skills relative to the child's age at that moment. We followed the recommendation of the Ministry of Health (Brasil, 2002) to identify children with healthy development according to the child's age (children who attained 90% of the developmental milestones in the domain for the age group) or children presenting developmental delay (children who attained less than 90% of reached milestones development in the domain for the age group).
2.2.2. Exposure
The present study used a pre‐tested instrument proposed by Trapé (2011) in order to operationalize an index that could measure family social exclusion in Brazil. This index was constructed based upon theories and methods from the field of social determinants of health (Breilh & Granda, 1989), including the role of work as it relates to family life (consumption based on the capitalist accumulation process). The families were interviewed regarding social inclusion in society. Trapé (2011) initially used a set of 34 empirical variables to represent the concept of social inclusion of families who lived in different social spaces, from a representative sample from a municipality in the Metropolitan Region of São Paulo. The data were analysed using multivariate statistical analysis and factor analysis to select those variables statistically significant and to establish the cutoff points for the composition of the four social groups (GS) (Trapé, 2011). As a last step, a discriminant linear analysis was performed, which again tested the variables to assess the degree of importance of each one, which generated equations for the construction for the social classification of families. The final variables that better represent social exclusion are presented in the Figure 1. Three family social groups were constructed: least social excluded, moderately excluded and most excluded (Trapé, 2011).
FIGURE 1.
Family social groups categories.
2.2.3. Covariates
Drawing on the available evidence of children presenting developmental delays on the literature, four types of covariates were included in the analysis: (i) whether the family was a beneficiary of “Bolsa Família”, the conditional cash transfer programme in Brazil (no or yes), (ii) family sociodemographic characteristics: maternal age (≤ 20, 20–29, and ≥30 years), maternal and paternal education (<8 and ≥8 of former schooling), number of siblings (1, 2 or ≥3); (iii) clinical and obstetric history: number of antenatal care visits (<6 or ≥6), type of delivery (vaginal or caesarean section); (iv) child characteristics: child age; birth weight – collected from the child health booklet (<2500 and ≥2500 g), hospitalization in the last 12 months (yes or no), breastfeeding (yes or no) and whether child attended day care (yes or no).
2.3. Statistical analysis
To determine the relationship between exposures and ECD domain outcomes, we used one‐way ANOVA and χ2 tests. The association between children presenting developmental delays and its possible determinants was initially examined using univariate analysis and then following with hierarchical multiple logistic regressions using STATA software version 14.1. The hierarchical multiple regression blocks were tested to estimate the association between the exposure (family social groups) upon including additional relevant covariates in each model. We considered two dependent variables: children with motor and socioemotional developmental delays. In the dimension of societal structural processes, we considered in block 1 the relationship between family social group and child development outcomes. In the dimension of processes in the child's immediate environment, we added to the block 2 maternal characteristics: mother age, maternal occupation, number of siblings and Bolsa Família. Moreover, in block 3 we added obstetric and prenatal characteristic: number of antenatal care appointments and type of delivery. In the dimension of the child's individual processes, we added child characteristics such as child age, gender, birth weight, hospitalization in the last 12 months, breastfeeding and day care attendance. The magnitude of the association between dependent and independent variables was estimated by the odds ratio (OR) and their respective 95% confidence intervals and p‐value < 0.05. The hierarchical logistic regressions were performed according to the theoretical model defined a priori (Figure 2).
FIGURE 2.
Conceptual model for the analysis of the child development.
3. RESULTS
The sample comprised 358 children under 3 years of age. The average child age was 27.4 months and 54.6% were female. In the sample, 27.6% of children presented with motor developmental delay, and 17.2% children presented with socioemotional developmental delays. Study population characteristics are presented in Table 1.
TABLE 1.
Family social groups, family and child characteristics, according to motor and socioemotional development in children under 3 years old (n = 358). Municipality of São Paulo State, Brazil, 2013.
| Variables | Total | Motor development | p‐value | Socioemotional development | p‐value | ||
|---|---|---|---|---|---|---|---|
| Delay | Adequate | Delay | Adequate | ||||
| N (%) | N (%) | N (%) | N (%) | N (%) | |||
| Family social groups | 0.02 | 0.04 | |||||
| Least social excluded | 69 (19.8) | 11 (11.5) | 58 (23.0) | 8 (13.3) | 61 (21.2) | ||
| Moderately social excluded | 142 (40.8) | 39 (40.6) | 103 (40.9) | 20 (33.3) | 122 (42.4) | ||
| Most social excluded | 137 (39.4) | 46 (47.9) | 91 (36.1) | 32 (53.4) | 105 (36.4) | ||
| Bolsa Família cash transfer programme | 0.04 | 0.23 | |||||
| No | 275 (79.0) | 69 (71.9) | 206 (81.7) | 44 (73.3) | 231 (80.2) | ||
| Yes | 73 (21.0) | 27 (28.1) | 46 (18.3) | 16 (26.7) | 57 (19.8) | ||
| Mother age, years (N = 345) | 0.17 | 0.74 | |||||
| <20 | 43 (12.8) | 9 (10.2) | 34 (13.8) | 6 (10.5) | 37 (13.3) | ||
| 20–29 | 174 (51.9) | 41 (46.6) | 133 (53.8) | 32 (56.2) | 142 (51.1) | ||
| ≥30 | 118 (35.3) | 38 (43.2) | 80 (32.4) | 19 (33.3) | 99 (35.6) | ||
| Maternal education, years (N = 345) | 0.13 | 0.38 | |||||
| <8 | 77 (22.4) | 26 (27.9) | 51 (20.3) | 16 (26.7) | 61 (21.5) | ||
| ≥8 | 267 (77.6) | 67 (72.1) | 200 (79.7) | 44 (73.3) | 223 (78.5) | ||
| Paternal education, years (N = 345) | 0.66 | 0.40 | |||||
| <8 | 71 (24.5) | 20 (26.3) | 51 (23.8) | 14 (29.2) | 57 (23.5) | ||
| ≥8 | 219 (75.5) | 56 (73.7) | 163 (76.2) | 34 (70.8) | 185 (76.5) | ||
| Maternal occupation | 0.85 | 0.58 | |||||
| Unpaid | 212 (61.5) | 57 (60.6) | 155 (61.8) | 35 (58.3) | 177 (62.1) | ||
| Paid | 133 (38.5) | 37 (39.4) | 96 (38.2) | 25 (41.7) | 108 (37.9) | ||
| Number of siblings | 0.02 | 0.28 | |||||
| 1 | 147 (42.2) | 36 (37.5) | 111 (44.1) | 21 (35.0) | 126 (43.7) | ||
| 2 | 106 (30.5) | 24 (25.0) | 82 (32.5) | 18 (30.0) | 88 (30.6) | ||
| ≥3 | 95 (27.3) | 36 (37.5) | 59 (23.4) | 21 (35.0) | 74 (25.7) | ||
| Number of antenatal care visitsa | 0.23 | 0.40 | |||||
| <6 | 33 (9.6) | 12 (12.6) | 21 (8.4) | 4 (6.67) | 29 (10.2) | ||
| ≥6 | 312 (90.4) | 83 (87.4) | 229 (91.6) | 56 (93.3) | 256 (89.8) | ||
| Type of delivery (345) | 0.19 | 0.41 | |||||
| Vaginal | 163 (47.3) | 39 (41.5) | 124 (49.4) | 25 (42.4) | 138 (48.3) | ||
| Caesarean section | 182 (52.7) | 55 (58.5) | 127 (50.6) | 34 (57.6) | 148 (51.7) | ||
| Gender | 0.05 | 0.61 | |||||
| Female | 158 (45.4) | 44 (45.8) | 146 (57.9) | 29 (48.3) | 129 (44.8) | ||
| Male | 190 (54.6) | 52 (54.2) | 106 (42.1) | 31 (51.7) | 159 (55.2) | ||
| Child age (months) | 0.05 | <0.001 | |||||
| <12 | 128 (36.9) | 27 (28.4) | 101 (40.1) | 8 (13.3) | 120 (41.8) | ||
| ≥12 | 219 (63.1) | 68 (71.6) | 151 (59.9) | 52 (86.7) | 167 (58.2) | ||
| Birth weight | 0.10 | 0.22 | |||||
| <2500 g | 42 (12.1) | 16 (16.7) | 26 (10.3) | 10 (16.7) | 32 (11.1) | ||
| ≥2500 g | 306 (87.9) | 80 (83.3) | 226 (89.7) | 50 (83.3) | 256 (88.9) | ||
| Hospitalization in the last 12 months (N = 345) | 0.48 | 0.001 | |||||
| No | 305 (88.4) | 83 (86.5) | 222 (89.2) | 45 (76.3) | 260 (90.9) | ||
| Yes | 40 (11.6) | 13 (13.5) | 27 (10.8) | 14 (23.7) | 26 (9.1) | ||
| Breastfeeding | 0.05 | <0.001 | |||||
| No | 160 (45.9) | 52 (54.2) | 108 (42.8) | 41 (68.3) | 119 (41.3) | ||
| Yes | 188 (54.1) | 44 (45.8) | 144 (57.2) | 19 (31.7) | 169 (58.7) | ||
| Child attend day care (N = 345) | 0.18 | 0.39 | |||||
| No | 46 (13.3) | 87 (90.6) | 214 (85.3) | 50 (83.3) | 251 (87.5) | ||
| Yes | 299 (86.7) | 9 (9.4) | 37 (14.7) | 10 (16.7) | 36 (12.5) | ||
Variables with missing information.
The majority of children presenting motor and socioemotional developmental delays belonged to the most social excluded families, based on results from the Chi‐square test which showed differences in psychomotor and social developmental delay between the family social groups. Not being enrolled in the “Bolsa Família” cash transfer showed association with motor developmental delay (p‐value = 0.04) in univariate analysis. The number of siblings was associated with socioemotional development delay (p‐value = 0.02). Have been hospitalized in the last 12 months and not breastfed were associated with socioemotional development delay (p‐value < 0.001) (Table 1).
Table 2 shows the results from the four hierarchical multiple logistic regression models for the associations between all variables and motor development delay. Children in the most excluded social groups had a greater odds of motor development delay (OR = 3.4, 95% CI = 1.14; 10.55) compared with those of the least vulnerable groups. Also, children who were hospitalized in the last 12 months had a greater odds of presenting motor development delay (OR = 2.64, 95% C = 1.10; 6.31) than children who were not hospitalized in the past 12 months. Children who were breastfed were 0.53 times less likely (95% CI: 0.23; 0.98) to have motor development delay than children who were not breastfed.
TABLE 2.
Predictors of motor development delay in children under 3 years old (n = 358). Municipality of the São Paulo State, Brazil, 2013.
| Variables | Block 1 | Block 2 | Block 3 | Block 4 | ||||
|---|---|---|---|---|---|---|---|---|
| OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | |
| Family social groups | ||||||||
| Least vulnerable | 1 | 1 | 1 | 1 | ||||
| Moderately vulnerable | 1.99 | 0.89; 4.45 | 2.60 | 0.99; 6.83 | 2.46 | 0.92; 6.53 | 2.91 | 0.96; 8.75 |
| Most vulnerable | 2.46 | 1.10; 5.48 | 3.03 | 1.13; 8.11 | 2.85 | 1.05; 7.69 | 3.47 | 1.14; 10.55 |
| Bolsa Família cash transfer programme | ||||||||
| No | 1 | 1 | 1 | 1 | ||||
| Yes | 1.68 | 0.95; 3.00 | 2.00 | 0.98; 4.07 | 2.00 | 0.97; 4.15 | 1.54 | 0.70; 3.38 |
| Mother age, years a | ||||||||
| <20 | 1 | 1 | 1 | |||||
| 20–29 | 2.46 | 0.78; 7.79 | 2.43 | 0.76; 7.72 | 2.76 | 0.82; 9.30 | ||
| ≥39 | 2.59 | 0.77; 8.65 | 2.54 | 0.75; 8.56 | 2.19 | 0.59; 8.07 | ||
| Maternal education, years a | ||||||||
| <8 | 1 | 1 | 1 | |||||
| ≥8 | 1.19 | 0.54; 2.61 | 1.28 | 0.56; 2.88 | 1.54 | 0.60; 3.93 | ||
| Paternal education, years a | ||||||||
| < 8 | 1 | 1 | 1 | |||||
| ≥ 8 | 0.94 | 0.45; 1.94 | 0.85 | 0.41; 1.78 | 0.79 | 0.35; 1.77 | ||
| Maternal occupation a | ||||||||
| No | 1 | 1 | 1 | |||||
| Yes | 0.86 | 0.46; 1.60 | 0.88 | 0.47; 1.65 | 0.89 | 0.45; 1.79 | ||
| Number of siblings | ||||||||
| 1 | 1 | 1 | 1 | |||||
| 2 | 1.30 | 0.64; 2.65 | 1.29 | 0.63; 2.62 | 1.56 | 0.71; 3.45 | ||
| ≥3 | 1.36 | 0.63; 2.93 | 1.23 | 0.55; 2.72 | 1.22 | 0.50; 2.94 | ||
| Number of antenatal care appointments a | ||||||||
| <6 | 1 | 1 | ||||||
| ≥6 | 0.86 | 0.31; 2.35 | 0.65 | 0.21; 2.00 | ||||
| Type of delivery a | ||||||||
| Vaginal | 1 | 1 | ||||||
| Caesarean section | 1.01 | 0.55; 1.88 | 1.92 | 0.46; 1.83 | ||||
| Child age a (months) | ||||||||
| <12 | 1 | |||||||
| ≥12 | 2.14 | 0.91; 5.01 | ||||||
| Gender | ||||||||
| Female | 1 | |||||||
| Male | 0.49 | 0.24; 0.99 | ||||||
| Birth weight | ||||||||
| <2500 g | 1 | |||||||
| ≥2500 g | 0.89 | 0.33; 2.35 | ||||||
| Hospitalization in the last 12 months a | ||||||||
| No | 1 | |||||||
| Yes | 2.64 | 1.10; 6.31 | ||||||
| Breastfeeding | ||||||||
| No | 1 | |||||||
| Yes | 0.47 | 0.23; 0.98 | ||||||
| Day care a | ||||||||
| No | 1 | |||||||
| Yes | 0.66 | 0.23; 1.87 | ||||||
Variables with missing data <10%.
Table 3 shows the results from the hierarchical multiple logistic regression for the associations with children's socioemotional development delay. Children in the moderately social excluded group (OR = 3.20; 95% CI = 1.10; 9.31) and in the most social excluded group had a greater odds of socioemotional developmental delay (OR = 3.09; 95% CI = 1.05; 9.02) comparing those of least social excluded groups. We found no statistical association with the other variables.
TABLE 3.
Predictors of socioemotional development delay in children between under 3 years old (n = 358). Municipality of São Paulo State, Brazil, 2013.
| Variables | Block 1 | Block 2 | Block 3 | Block 4 | ||||
|---|---|---|---|---|---|---|---|---|
| OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | |
| Family social groups | ||||||||
| Least vulnerable | 1 | 1 | 1 | 1 | ||||
| Moderately vulnerable | 1.78 | 0.79; 4.00 | 2.54 | 0.96; 6.68 | 2.39 | 0.89; 6.41 | 3.20 | 1.10; 9.31 |
| Most vulnerable | 2.15 | 0.96; 4.81 | 2.72 | 1.0; 7.29 | 2.79 | 1.03; 7.59 | 3.09 | 1.05; 9.02 |
| Bolsa Família cash transfer programme | ||||||||
| No | 1 | 1 | 1 | 1 | ||||
| Yes | 1.53 | 0.84; 2.78 | 2.01 | 0.98; 4.08 | 2.01 | 0.97; 4.17 | 1.16 | 0.52; 2.56 |
| Mother age, years a | ||||||||
| < 20 | 1 | 1 | 1 | |||||
| 20–29 | 1.33 | 0.49; 3.65 | 1.28 | 0.46; 3.53 | 1.00 | 0.33; 3.03 | ||
| ≥ 39 | 1.71 | 0.59; 4.95 | 1.80 | 0.62; 5.27 | 1.33 | 0.41; 4.35 | ||
| Maternal education, years a | ||||||||
| < 8 | 1 | 1 | 1 | |||||
| ≥8 | 0.99 | 0.45; 2.17 | 1.08 | 0.48; 2.41 | 1.03 | 0.41; 2.58 | ||
| Paternal education, years a | ||||||||
| <8 | 1 | 1 | 1 | |||||
| ≥8 | 1.09 | 0.52; 2.28 | 0.99 | 0.47; 2.08 | 1,15 | 0.50; 2.62 | ||
| Maternal occupation a | ||||||||
| No | 1 | 1 | 1 | |||||
| Yes | 0.96 | 0.52; 1.78 | 0.98 | 0.52; 1.83 | 1,07 | 0.53; 2.16 | ||
| Number siblings | ||||||||
| 1 | 1 | 1 | 1 | |||||
| 2 | 0.81 | 0.39; 1.67 | 0.80 | 0.38; 1.65 | 0.87 | 0.39; 1.96 | ||
| ≥3 | 1.10 | 0.52; 2.33 | 0.98 | 0.45; 2.14 | 1.04 | 0.43; 2.50 | ||
| Number of antenatal care appointments a | ||||||||
| <6 | 1 | 1 | ||||||
| ≥6 | 0.64 | 0.24; 1.68 | 0.50 | 0.16; 1.55 | ||||
| Type of delivery a | ||||||||
| Vaginal | 1 | 1 | ||||||
| Caesarean section | 1.09 | 0.59; 2.02 | 1.03 | 0.51; 2.09 | ||||
| Child age a (months) | ||||||||
| <12 | 1 | |||||||
| ≥12 | 2.14 | 0.91; 5.01 | ||||||
| Gender | ||||||||
| Female | 1 | |||||||
| Male | 1.29 | 0.64; 2.59 | ||||||
| Birth weight | ||||||||
| <2500 g | 1 | |||||||
| ≥2500 g | 0.88 | 0.34; 2.26 | ||||||
| Hospitalization in the last 12 months a | ||||||||
| No | 1 | |||||||
| Yes | 1.62 | 0.66; 3.96 | ||||||
| Breastfeeding | ||||||||
| No | 1 | |||||||
| Yes | 0.93 | 0.45; 1.91 | ||||||
| Day care a | ||||||||
| No | 1 | |||||||
| Yes | 1.55 | 0.53; 4.49 | ||||||
Variables with some loss less than 10%.
4. DISCUSSION
In the present study, we explored the association between family social exclusion and early child motor and socioemotional delay, using a new social inequality index to measure family social exclusion. Our results confirm that children from families that belonged to the most excluded social groups had a greater odds of presenting motor and socioemotional delays, which confirms our hypothesis. Previous studies have similarly shown associations between family social determinants and ECD delays using a variety of different measures of social exclusion and child development (Díaz et al., 2017; Kim et al., 2015; Zhang et al., 2017).
The majority of previous studies have focused only on socioeconomic characteristics without including variables to measure social exclusion. For instance, a community‐based cross‐sectional study in South‐West Ethiopia (Worku et al., 2018) observed that children in extreme poverty performed more poorly than the reference children in all the developmental domains comparing with children from the richest group. The authors explained that differences in the developmental outcomes between the two groups might be related because of the adverse early experiences and the socioeconomic inequality of children in extreme poverty (Worku et al., 2018). Another study using data from Cambodia, China, Mongolia, Papua New Guinea, Timor‐Leste and Vanuatu found that poor socioeconomic gradients were directly related to lower levels of children's socioemotional, cognitive and language development and emergent literacy (Richards et al., 2018). A comprehensive review also showed that poverty and food insecurity could detrimentally affect the development of young children aged from birth to 3 years (Chilton et al., 2007).
Our findings are also consistent with previous studies in Brazil regarding the social determinants of ECD. Researchers found that of the 37% of children with suspected development delay, the majority belonged to families with low income (Biscegli et al., 2007). Paiva et al. (2010) verified a high prevalence of children with language development delays in families of the lower quartile of the socioeconomic index (Paiva et al., 2010). Veleda et al. (2011) identified that the highest proportion of children with psychomotor development delay belonged to lower‐income families (Veleda et al., 2011).
These associations can be explained by the fact that the quality of housing, sanitation, hygiene and food conditions are poorer in socially disadvantaged families, contributing to the increase of diseases and inadequate ECD (Walker et al., 2011). Also, a study evaluating child development among employed and unemployed parents revealed the negative influence of parent's unemployment status on ECD (Paiva et al., 2010). Indeed, analysis between economics and developmental psychology suggested that job loss can affect mental health academic performance and increase income inequality, particularly among African‐American students and those from the poorest families (Ananat et al., 2017).
Our study also confirms another documented correlate of ECD. More specifically, breastfed children had a lower chance of present a delayed motor development compared with children who were not breastfed after controlling for other variables. Breastfeeding is associated with numerous benefits for the developing infant in both the short and the long term, including psychological development (Jardi et al., 2018). A study that examined how breastfeeding during the first 4 months of life affects the mental and motor development of children aged 6 and 12 years showed that children who were breastfed for at least 4 months had a higher motor development at 6 and 12 months of age (Jardi et al., 2018). Breastmilk contains adequate amounts of micronutrient and is vital for optimal growth and development. On the other hand, children who have been hospitalized in the last 12 months had a higher change of delayed motor development (Bortolote & Bretas, 2008). Hospitalization negatively affects the child's social environment and routine activities and habits, which may impact development due to stressful procedures and experiences (Bortolote & Bretas, 2008).
In our study, there was no association between the “Bolsa Família” cash transfer programme and child development. However, a recent study showed the importance of “Bolsa Família” as a benefit for low‐income families and reducing infant mortality, especially in poorer regions, where the return of the federal health investments in addressing infant mortality is higher (Castro et al., 2019). However, other studies have shown the importance of poverty alleviation programmes for ECD (Fernald et al., 2008; Fernald & Hidrobo, 2011). In Mexico, for example, cash transfer programmes have shown statistically significant improvement in height, cognition and language development (Castro et al., 2019).
This study advances the understanding of child development from the perspective of social inclusion, as it uses a novel indicator developed originally in Latin America to classify family social exclusion. A limitation of the study is that the data were collected from São Paulo State, in Southeastern Brazil and not all areas in Brazil, and the ECD assessment instrument used in this study, as available in the Child Health Handbook, is widely used by physicians and nurses working in the primary health care setting in Brazil (Freitas, 2015) and has proven useful in tracking early changes in child development, reiterating the importance of its use in primary care. However, it is not specific to diagnose changes in the child's development and, therefore, constitutes a limitation in this study. Additionally, we did not have information about father and mother behaviour as stimulation, quality of interaction and mental health that could impact child development.
5. CONCLUSION
Our results showed that children from socially excluded families were more likely to have delays in motor and socioemotional development.
Inequalities begin during pregnancy and in the early years of life. Children who experience adverse experiences from the beginning of life are at a disadvantage to reach their potential development. In this context, families are one of the most crucial and nurturing environments for children. There is a great need to understand how family inequality influences ECD in different contexts worldwide, especially in Brazil, so this study is of great high significance for filling the gap.
Therefore, we suggest that the government and policymakers can provide social and economic support and regular analyses of the families' social inclusion to ensure that the less privileged women and children are effectively reached with essential interventions.
AUTHOR CONTRIBUTIONS
CVRO: conceptualization, data curation, formal analysis, methodology and writing – original draft preparation; CNTP: investigation, project administration, supervision and writing – review & editing; JJ: writing – review & editing; KMSC: review & editing. EF: conceptualization, funding acquisition, investigation, resources, supervision and writing – review & editing. The authors affirm that the methods used in the data analyses are suitably applied to their data within their study design and context, and the statistical findings have been implemented and interpreted correctly.
FUNDING INFORMATION
This research was funded by São Paulo Research Foundation (FAPESP, Process n° 2011/509309).
CONFLICT OF INTEREST STATEMENT
We have no conflicts of interest to disclose, and we state that the project's development has adhered to ethical standards.
ETHICS STATEMENT
The project was approved by the Research Ethics Committee of the School of Nursing of the University of São Paulo (process nº 193.468) and authorized by the Municipal Health Board, in accordance with the determinations of Resolution CNS/MS 196/96, which regulates the ethics in research involving human beings in Brazil.
ACKNOWLEDGEMENTS
We are thankful to all participants and professional health workers involved in this study, to the Municipal Health Secretariat and the Primary Health Care Units. We would like to thank CAPES and FAPESP for Financial Suport (Grant: 2011/509309).
Ramos De Oliveira, C. V. , Palombo, C. N. T. , Jeong, J. , Cordero, K. M. S. , & Fujimori, E. (2023). Is family social exclusion associated with child motor and socioemotional development delay? A cross‐sectional exploratory study. Nursing Open, 10, 5024–5034. 10.1002/nop2.1736
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are openly available in MEDRXIV at https://www.medrxiv.org/content/10.1101/2022.05.26.22275658v1, reference number https://doi.org/10.1101/2022.05.26.22275658v1.
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Associated Data
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Data Availability Statement
The data that support the findings of this study are openly available in MEDRXIV at https://www.medrxiv.org/content/10.1101/2022.05.26.22275658v1, reference number https://doi.org/10.1101/2022.05.26.22275658v1.