Table 1 illustrates information collected from 335 elementary school children who took part in the study. The participant sample spanned across 3 different grades: 3rd grade (119 participants, 35.5%), 4th grade (113 participants, 33.7%), and 5th grade (103 participants, 30.7%). The study also had a slight male majority, with 174 (51.9%) males and 161 (48.1%) females. The participants' ages ranged from 9 to 12 years, with 10 years as the average. In the assessment, 19.7% of participants were identified as having anemia, and 22.1% were found to have working memory deficits. Additionally, 5.4% of participants were assessed and found to have short stature (Table 2).

The relationship between clinical parameters and working memory status is presented in Table 3. Our analysis revealed significant relationships between clinical parameters and working memory status. For height-for-age status, 44.4% of children with short stature had compromised working memory compared to 20.8% of those with normal stature (p=0.035, OR=3.04, 95% CI: 1.15-8.01). Mean hemoglobin levels were significantly lower in students with compromised working memory (12.1±1.1 g/dL) compared to those with normal working memory (12.4±0.9 g/dL, p=0.035). While 28.8% of anemic children showed compromised working memory compared to 20.4% of non-anemic children, this difference was not statistically significant (p=0.194).

The analysis of two groups of students, anemic and non-anemic, who were students at the same level of total energy intake and had the same total energy intake and total energy intake (Table 4). Total energy intake was the same for both groups (anemic: 85.2%, range 23-163%; non-anemic: 83.5%, range 22-175%; p=0.758), and the total carbohydrate intake was similar for both groups (anemic: 36.5%, range 31-94%; non-anemic: 41.5%, range 31-94%; p=0.109). Students with anemia had higher fat intake (47.4%, range 44-48%) compared to non-anemic students (46.3%, range 44-48%; p=0.010) and lower protein intake (46.3%, range 40-64%) compared to non-anemics (52.6%, range 40-64%; p=0.010).

Our analysis showcased significant constructive engagements regarding malnourished elementary school children and their cognitive development. Our study revealed that among the total anemic participants, 29% exhibited clinically significant deficits in working memory. This event suggests that working memory may be particularly susceptible to iron deficiency. This effect was displayed in our analysis of hemoglobin levels; on average, children who had working memory deficits exhibited lower levels (12.1 ± 1.1 g/dL) versus those who had no deficits (12.4 ± 0.9 g/dL, p = 0.035), which shows that small changes in cognitive function could be attributed to differences in cognitive function [15, 16].

The plausible theory regarding the fundamental explanatory assumptions holds that iron deficiency affects the construction of specific neurotransmitters and the myelination of the central nervous system [17, 18]. particularly the working memory, which is the ability to both mentally hold onto and manipulate information, appears to be in the domain of the central nervous system, which is in the domain of loss of oxygen to the brain and the consequent changes in neurotransmitters [19, 20]. Our various studies and analyses indicated that working memory is in the domain of iron status among children, and that cognitive development among school-age children is in the domain of working memory [21].

Our study results that, compared to their peers, children with short stature had working memory scores that were more than three times as likely to be low (OR = 3.04, 95% CI: 1.15-8.01), indicating the impact of chronic malnutrition on cognitive development. This impact is reported in other works [22] and indicates low levels of nutrition in early life and less developed brains.

The combined phenomena of short stature and hemoglobin deficiency, in relation to working memory deficits, point to a more intricate case of both chronic and acute malnutrition's impact on cognitive development. Even though both relationships were statistically significant, it is important to state that not all nutritionally deficient children experienced working memory difficulties. This cognitive outcome variability is likely due to the timing and degree of nutrition deficiency and during development, compensatory influences [23].

The possible connection between cognitive function and anthropometric status is likely due to the long-term effects of chronic under-nutrition, which stunts brain development. Detected changes in malnutrition during the period of brain development evidenced regional changes in the brain and in the regions that perform core functional activities of memory and executive function [24]. This underlines the need for an integrated focus on school-aged children's management of both acute and chronic malnutrition, coupled with early and sustained monitoring of cognitive and nutritional function.

It is particularly disconcerting that all participants show universal inadequacies in fat and protein intake (100%), which highlights the multitudinous concerns surrounding our study population. Previous researchers similarly found Indonesian children to have widespread deficiencies in similar micronutrients [25, 26]; however, the universal inadequacies within our study’s participants are particularly concerning. Numerous studies have documented insufficient access to animal protein and protein-rich foods, and the prevailing practice of carbohydrate-based consumption, coupled with the prevailing low-socioeconomic food purchasing ability [27], likely explains the indisputable protein deficits. The cross-study inadequacies of protein intake and anemia likely have far-reaching impacts on the protein deficit, especially for neurotransmitter synthesis and neural growth [12]. Your study revealed that anemic participants had a statistically significant lower protein intake (46.3% vs 52.6%, p = 0.010), which is similar to other studies reporting that lower protein intake is associated with reduced iron bioavailability/dietary protein [28]. The dual problems of anemia and lower protein intake likely exert a serious, compounded adverse effect on cognitive development [29], perpetuating a cycle of nutritional deficiencies and reduced learning ability. This suggests that improving protein intake is associated with reduced anemia and enhanced cognitive ability [30], which is best achieved through school-based nutrition programs that prioritize protein and nutrition education for children’s caretakers.

The concern regarding the universally low fat intake documented in the study should consider the established effects of dietary fat, especially Polyunsaturated Fatty Acids (PUFAs), on the brain development and functioning of children [31, 32]. Recent studies of fat intake in children across 33 countries show that low fat intake is a global phenomenon; 88% of children aged 1-3 years do not consume enough total fat [33]. This is also the case for Indonesian children, whose median total fat intake is only 26.7% of total energy, which is still below the recommendation [34].

The positive effect of dietary fat and cognitive performance is now more recognized. Studies show that dietary fat has positive, significant correlations with several measures of cognitive performance in children, particularly reaction time and cognitive flexibility [35]. Polyunsaturated fatty acids, more specifically omega-3 fatty acids like Docosahexaenoic Acid (DHA), are crucial for fluidity of neural membranes and synaptic plasticity and are important for neurotransmitter activity [36, 37]. The combination of inadequate fat intake and the iron deficiency anemia present in the study population may multiplicatively adversely affect working memory and cognitive development.

Considering public health, there is a need for more integrated approaches to the problems associated with the deficiency of certain fats. School feeding programs can improve the provision of important micronutrients and macronutrients, including the healthy fats that children need. One systematic review and meta-analysis of school feeding programs in low and middle-income countries showed that these programs had a positive effect on the education and health of school-aged children and adolescents, which indicates the potential of school feeding programs for nutritional interventions [38]. Combining local agriculture with Home Grown School Feeding programs has the potential to improve the economic situation of the local community, as well as the nutritional quality of school meals. It would be relevant for further research to use randomized controlled trials to examine school- and community-based interventions to improve children's fat intake in Indonesia.

The numbers we found for anemia (19.7%) and working memory deficits (22.1%) in our sample exemplify a significant public health concern. Our findings stress the need to design and implement integrated school-based nutrition programs aimed at eliminating iron deficiency and improving overall nutrition. The combined presence of these conditions is likely to erode academic and developmental outcomes even further.

School-based nutrition programs can integrate micronutrient supplementation, dietary diversification, and nutrition education. A life course approach to Iron Deficiency Anemia (IDA) advocating integrated strategies across multiple life stages was proposed by Sungkar et al. this approach posits that nutritional measures taken during the school-age years will immediately address existing gaps but will also instill healthy dietary practices that will carry into later life, thereby disrupting the multigenerational transmission of poor nutrition and cognitive deficits [39]. Past successful interventions illustrate that integrated strategies that simultaneously target nutritional and cognitive outcomes yield positive improvements in academic performance and in the overall development of children [22, 40].

While our study on nutritional status and cognitive function in elementary school children has revealed important findings, it has also identified potential areas for future research. The cross-sectional design has documented sufficient evidence for associating memory and nutrition, and this research can be expanded through longitudinal designs, so as to describe and analyze relationships in time across constructs. A 24-hour dietary recall documented useful population-level estimates of nutritional intake. In future research, it would be useful to have multiple dietary recalls to assess individual dietary intake more accurately and to include a food frequency questionnaire to analyze micronutrient intake. The assessment of working memory employed significant standardized tools, providing empirical evidence to support the assessment of other cognitive domains. Given the findings of the study, additional research would include longitudinal studies to assess developmental trajectories; implementation studies of targeted nutritional interventions; advanced cognitive assessments; expanded dietary assessment approaches; studies on micronutrient interactions; and studies on the provision of additional cognitive domains. These research studies will reinforce the evidence and will be of great help in designing effective strategies to address the nutritional and cognitive needs of school-aged children.

There are some limitations in this research work. A cross-sectional research design captured associations between anemia and working memory deficits at one time. The purposive sampling of two Jakarta schools imposes limitations on generalizing findings to other Indonesian populations. Longitudinal research is required to assess the temporal relationship between nutritional status and cognitive development. Moreover, research studies employing different nutrition assessment methods, comprehensive cognitive assessments, beyond hemoglobin level cognitive tests, teacher evaluations, and varied research populations from both rural and urban locations in Indonesia would yield better studies on the nutrition and cognition relationship of school-aged children. The sample size of 335 participants and statistical power showed more than sufficient power to recognize effect sizes of moderate and over; however, certain patterns did not reach statistical significance. The effect size in working memory groups' level hemoglobin average of 0.3 g/dL demonstrates a meaningful, clinically significant difference; both statistical and clinical significance should be considered.