Introduction

An estimated 370 million people or more are classified as Indigenous or Aboriginal people worldwide [1]. In Malaysia, indigenous people are known as Orang Asli (OA), and they numbered approximately 4.4 million in 2015 [2]. Malaysia’s OA consist of 18 ethnic subgroups, which are divided into three major tribal groups: Semang (Negrito), Senoi, and Proto Malay (Aboriginal Malay). The OA commonly live in poor environments with an inadequate intake of energy, have a poor nutritional status, are exposed to high rates of infections such as those caused by parasites [3], and have specific deficiencies of nutrients including iron and iodine deficiencies [4,5].

Over the years, the Malaysian government has implemented various programs aimed primarily at improving the quality of life and general welfare of the OA. Examples of these programs include resettling, increasing income through cash-cropping and commercial activities, and physical support such as electricity, water supply, roads, houses, and foods [6]. However, little success has been achieved when OA are compared to other ethnic groups in Malaysia. Namely, the OA still face poverty as well as poor nutritional and health status, particularly where young children are concerned [6–8].

Cognition refers to the psychological process of memory, attention, learning, language, reasoning, and coordination of motor outputs [9]. Poverty, low socioeconomic status, poor health status, malnutrition, intestinal parasitic infections, poor home environment, low education level of parents, and micronutrient deficiencies are among the various factors that may contribute to children’s low cognitive performance [10–15]. These factors are common problems encountered by indigenous populations. A significant cognitive gap was found between indigenous and non-indigenous children due to the higher rate of poor nutritional and health status among indigenous children [16].

The preschool years represent a critical period for the development of mental processes that support an effective, goal-oriented approach to learning, particularly working memory and attention control [17]. These mental processes are often delayed in children growing up in poverty [18]. Research has shown that working memory and attention control lead to growth in emergent literacy and numeracy skills during the pre-kindergarten years [17]. Therefore, it is important to examine the cognitive performance of preschool children, especially indigenous children.

Children living in poverty usually experience fewer cognitive encouragements and enrichments in comparison to children from wealthier backgrounds. Children from low-income families frequently lack stimulation and the social skills necessary to prepare them for schooling [19]. For example, low-income parents interact less with their children and are minimally involved in their education due to unmanageable daily levels of stress [20]. Apart from a poor socioeconomic status, OA children in Malaysia have persistent problems of malnutrition, low birth weight, and poor iron status [21–23]. There is a concern that these types of health problems in OA children can negatively affect their cognition and academic achievement later on.

In Malaysia, no studies have been published on the cognitive performance of OA children. Several small-scale studies of OA children have focused on their body weight [8,23], dietary intake [7], parasitic infections [24], and food security [25]. Yet children need to have optimal cognitive development in order to prepare them for schooling. Hence, it is necessary to study the determining factors associated with OA children’s cognitive performance. Identifying factors associated with cognitive performance is crucial to improve health status, counter school dropout rates, and improve the academic performance and school attendance of OA children.

Materials and method

Results

Table 1 shows the characteristics of the OA children. A total of 269 children with a mean age of 4.04±1.21 years participated, out of 280 OA children aged 2 to 6 in the 14 villages. Approximately one third of the OA children (35%) had positive parasitic infections, in which 58% of them were infected by Trichuris trichiuria, 11% by Ascaris lumbricoides, and 36% by both parasites. Furthermore, 36% of the OA children were stunted, 28% were underweight, 6% were wasted/thin, and 22% were anemic.

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Table 1. Characteristics of the participants (n = 269).

https://doi.org/10.1371/journal.pone.0219841.t001

Multiple linear regression results showed that higher WMI was significantly associated with more years of father’s education (β = 0.262, p = 0.007), higher father’s income (β = 0.358, p < 0.001), presence of parasites (β = -0.222, p = 0.026), more learning materials available at home (β = 0.263, p = 0.031), higher responsiveness of the parent to the child (β = 0.192, p = 0.049), and more variety in daily stimulation (β = 0.302, p = 0.007) (Table 2). These factors predicted 32% of the variance in WMI. The father’s income was the most significant predictor of WMI. In addition, findings of the separate analyses for WMI among OA children aged 2 to 3 years old and 4 to 6 years old are displayed at the Supplementary Material (S1 and S2 Tables).

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Table 2. Simple linear regression and multiple linear regression results for the factors associated with Working Memory Index.

https://doi.org/10.1371/journal.pone.0219841.t002

The father’s years of education (β = 0.342, p = 0.001), child’s hemoglobin level (β = 0.221, p = 0.031), availability of learning materials at home (β = 0.425, p = 0.002), and responsiveness of the parent to the child (β = 0.249, p = 0.016) had significant associations with PSI (Table 3). These factors predicted 40% of the variance in PSI. The most significant predictor of PSI was the availability of learning materials at home.

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Table 3. Simple linear regression and multiple linear regression results for the factors associated with Processing Speed Index.

https://doi.org/10.1371/journal.pone.0219841.t003

More years of the father’s education (β = 0.289, p = 0.007), higher father’s income (β = 0.191, p = 0.049), higher hemoglobin level (β = 0.237, p = 0.020), higher responsiveness of the parent to the child (β = 0.331, p = 0.002), more learning materials available at home (β = 0.400, p = 0.002), and more variety in daily stimulation (β = 0.327, p = 0.009) were significantly associated with CPI (Table 4). These factors predicted 42% of the variance in CPI. The availability of learning materials at home was the most significant predictor of CPI. Overall, the father’s years of education, availability of learning materials at home, and responsiveness of the parent to the child were the factors consistently associated with all three cognitive indices (WMI, PSI, and CPI).

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Table 4. Simple linear regression and multiple linear regression results for the factors associated with Cognitive Proficiency Index.

https://doi.org/10.1371/journal.pone.0219841.t004

Discussion

This study shows that a father’s years of education and home environment, specifically the availability of learning materials at home and the responsiveness of the parent to the child, consistently appeared as the significant predictors for all three cognitive indices (WMI, PSI, CPI) for the OA children. To the best of our knowledge, this is the first study to demonstrate the associations of sociodemographic factors, nutritional factors, and environmental factors on cognitive performance in a sample of OA children aged 2 to 6 years old in Malaysia.

This study shows that more years of father’s education were associated with better working memory, processing speed, and cognitive proficiency performance for the children. These are all cognitive processes necessary for a child to prepare themselves prior to starting primary education. The findings accord with those of previous studies [34,35], where father’s education was associated with children’s cognitive performance. There is a possible explanation for the suggestion that a father’s level of education affects a child’s cognitive performance. It could be inferred that those fathers who had received higher education would have better job prospects, which in turn would increase the family’s income level and lead to their investment in better education and the health of their children [36]. In addition, higher education increases knowledge related to health, education, and parenting; for example, the father’s involvement in nurturing the children at an early age and having a positive attitude toward parenting were associated with better growth development in children [37]. Cabrera et al. [35] found that highly educated fathers spent more time with their children and were more supportive (characterized by emotional support and enthusiasm for the child’s autonomous work, responsiveness, and active attempts to expand the child’s knowledge and abilities), where these would improve children’s cognitive performance across ages. Furthermore, the results of a recent study showed that father-child time was strongly associated with children’s cognitive performance when said time was spent on educational activities (such as reading or educational play) [34]. These findings highlight the importance of the father’s involvement in a child’s cognitive performance. Thus, future interventions to improve the cognitive performance of OA children could promote positive parenting by fathers and encourage fathers to spend more time with their young children.

The present study also shows that higher father’s income was significantly associated with better working memory and cognitive proficiency in the OA children. This concurs with previous studies that found a positive correlation between income and children’s cognitive performance [37,38]. According to Dickerson and Popli [14], poor income families were limited in their ability to invest in their children’s education, which further decreased the children’s cognitive performance. Therefore, improving parents’ education levels and combating poverty are essential for the OA population to ensure parents have an adequate income and the knowledge to enable them to play an active role in their children’s education.

Beside sociodemographic factors, we found that the subscales from the HOME inventory contributed to the children’s cognitive performance, namely, the availability of learning materials at home, variety in daily stimulation, and parental responsiveness. These factors agree with several studies that also indicated that home environment had a significant correlation with children’s cognitive performance [15,39–42]. A longitudinal study of American children from birth to school age found that cognitive stimulation at home was more effective in increasing children’s learning abilities in their early childhood than the stimulation found in primary school [41]. Another study found that children with a poor quality of home environment had poorer cognitive performance than their counterparts who did not [42]. OA children are typically from a low socioeconomic background where they are less exposed to stimulating environments that promote cognitive performance.

Parents who provide learning materials at home, such as books or flashcards of letters and brain games that are either electronic or physical games, play the most significant role in improving the cognitive outcomes of their children, specifically their working memory and processing speed [38,43,44]. Meanwhile, parents’ responsive behaviors allow children to engage in more problem-solving skills involved in cognitive proficiency [45]. In general, the provision of a cognitively stimulating home environment during preschool years enhances a child’s cognitive development, for example, parents’ frequent reading to the child or helping the child with building blocks to learn letters and numbers [37]. Therefore, parents who are actively involved in stimulating children’s learning play a vital role in the improvement of their children’s cognitive performance. Combating poverty is important in the OA population to ensure that parents have adequate income and knowledge to provide a better home environment for their children and thus enhance their children’s cognitive performance.

It is well known that parasitic infections are among the neglected and highly prevalent tropical diseases among the OA in peninsular Malaysia [3,7]. In this study, one third of the OA children (35%) had parasitic infections. Further, parasitic infection was one of the significant predictors of the children’s working memory performance. These findings are consistent with several other studies that also found that parasitic infections impair children’s cognitive function and learning ability [12,46,47]. For example, Ezeamama et al. [46] showed significant associations of parasitic infections with learning ability, memory, and verbal fluency in children. Perignon et al. [12] also noted that parasitic infections were associated with poor working memory in children. A possible explanation of these results is that infected children are vulnerable to illness and frequently have diarrhea, stomach discomfort, and malabsorption of micronutrients, thus making it easy for them to lose their concentration and attention while doing the cognitive test [12,48].

Anemic children become tired easily and are hesitant, less playful, less attentive, and less willing to explore their environment [49]. This study found that Hb level significantly contributed to the processing speed and cognitive proficiency of the OA children, consistent with the results of Al-Mekhlafi et al. [10]. A longitudinal cohort study performed by Ai et al. [50] on 171 children from a developing region of China reported that children with low Hb levels had significantly lower scores on an IQ performance test. A cross-sectional study by Yang et al. [51] on 7331 children aged 4 to 6 years in 21 counties/cities in China found that anemic children were 1.3 times more likely to have poor scores in operational IQ and verbal IQ tests and 1.4 times more likely to have poor scores in full-scale IQ tests as compared to non-anemic children. Therefore, anemia is an important factor in children’s cognitive development.

Some study limitations deserve attention in future research. First, this was a cross-sectional study, and therefore causality between the factors associated with the children’s cognitive performance could not be well established. Cohort studies should be conducted in the future. Second, this study used Hb concentration as a proxy indicator of anemia and did not take into account serum ferritin and iron. Future studies should consider including serum ferritin and iron in order to identify the different types of anemia. Third, the total intelligence, Full-scale IQ (FSIQ) by WPPSI IV could not be calculated because not all of the WPPSI IV subtests were administered and it is a Western-based cognitive function test. Certain subtests that were most appropriate for children with limited educational opportunities living in a rural environment were chosen such as picture memory, zoo location, bug search, and cancellation tests, and these non-verbal tests were used to assess cognitive performance. Some items in the tests may be culturally biased. For example, a few pictures might not be familiar to the OA children such as bicycle helmet, hourglass, planet, and fire extinguisher. Furthermore, the composite index scores for WMI, PSI, and CPI in the WPPSI IV are based on the United States norm as no Malaysian norm is available. However, the WPPSI IV has been used in other Asian countries including Indonesia [39] and Pakistan [52]. Future studies should develop a Malaysian norm for the WPPSI IV. Fourth, the HOME scale has not been validated in Malaysia and may not truly reflect the culture of OA. However, this instrument has been widely used in developing countries [53] and is a useful measurement tool for factors that are correlated with cognitive performance in homes which stimulate thinking and learning [15,39]. Finally, the study sample may not represent OA children population in the state of Negeri Sembilan as there were only 14 out of 30 OA villages agreed to participate in this study. Despite these limitations, the current study provides insights into the factors that affect cognitive performance in the indigenous population, which could be translated into approaches to improve cognition among OA children.

Conclusions

Our findings demonstrate that the father’s education level, father’s income, child’s Hb level, parasitic infections, and home environment, particularly the availability of learning materials, parental responsiveness to the child, and variety of daily stimulation were associated with the cognitive performance of OA children. Efforts to increase the education level of OA adults, improve the health and nutritional status of OA children, and increase cognitive stimulation at home should be emphasized in future interventions aimed at improving OA children’s cognitive performance. Moreover, appropriate early childhood interventions should be implemented to reduce the severity of the effects of poor cognitive performance; such interventions, in turn, could improve the readiness of OA children to learn in school and prevent dropouts.

Supporting information

Acknowledgments

The authors would like to show their appreciation to the Department of Orang Asli Development Malaysia (JAKOA) for allowing us to conduct this study. We also wish to express our gratitude and acknowledge the help and cooperation received from Tok Batin (the chief village) and all of the respondents throughout the study period. We would also like to thank Enago for proofreading this manuscript.