Neuroretinal and neuropsychological functional deficit in preadolescent children with stunted growth

Neuroretinal and neuropsychological functional deficit in preadolescent children with stunted growth | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Neuroretinal and neuropsychological functional deficit in preadolescent children with stunted growth Mary Amoako, Isaiah Osei Duah Junior, Dorcas Adu-Owusu, Fiifi Amoako Atta Payin Essiam, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6908758/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Background Given the brain and eyes high sensitivity to nutrient deficiency, and stunting as a marker of chronic malnutrition, we hypothesized that children with stunted growth would show impaired neuroretinal and neuropsychological function compared to age-matched-well-nourished controls. This study examined the link between nutritional status, visual function, and cognitive performance in preadolescent children with stunted growth, aiming to identify early markers of malnutrition-related developmental risk. Methods Fifteen stunted and 275 non-stunted children (ages 8–13) were assessed using dietary recall, visual tests (ETDRS LogMAR, Pelli-Robson, heterochromatic flicker photometry), and CANTAB neuropsychological assessments. Results Stunted children consumed fewer macro- and micronutrients, including lutein and zeaxanthin, and showed reduced macular pigment optical density (MPOD) and critical flicker frequency (CFF). Cognitive testing revealed significant impairments in spatial planning, problem-solving, and visuospatial working memory. After adjusting for confounders, stunted children were more likely to show poor spatial planning on the Stockings of Cambridge (SOC) task (AOR = 1.43, 95% CI: 1.00–2.66; p = 0.049). Conclusion These results suggest that stunting is associated with both neuroretinal and neurocognitive deficits. The findings underscore the value of visual and cognitive biomarkers in detecting early functional effects of stunting and the critical need for timely nutritional interventions in at-risk children. chronic malnutrition neuroretinal impairment cognitive impairment macular pigment optical density critical flicker frequency spatial planning spatial working memory Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Optimal nutrient intake is essential for maintaining the structural integrity and functional health of mammalian organs including the brain, the eyes and overall body composition [ 1 – 4 ]. Macronutrients—carbohydrates, proteins, and lipids—support bioenergetics and serve distinct roles: carbohydrates fuel cellular respiration, proteins provide structural components for tissues, and lipids support enzymatic functions, membrane formation, hormone synthesis [ 5 ]. Micronutrients, such as vitamins, iron and zinc, function as enzyme cofactors, regulate gene expression, and play critical roles in brain health and energy metabolism [ 1 , 6 , 7 ]. Xanthophyll carotenoids, particularly lutein and zeaxanthin, are vital for brain and visual system development[ 8 – 10 ]. Deficiencies in macro- or micronutrients disrupt cellular metabolism and homeostasis, potentially impairing growth and leading to abnormal developmental patterns in children[ 11 – 13 ]. Stunting, a clinical indicator of chronic nutrient deficiency, is defined by the Centers for Disease Control and Prevention (CDC) as low height-for-age, reflecting prolonged undernutrition and impaired growth potential [ 14 – 16 ]. Globally, stunting remains a major public health issue, with an estimated prevalence of around 30%, and the highest burden occurring in West Africa [ 17 ]. The Global Nutrition Report estimates that 17.5% of children under five are stunted, compared to a regional average of 30.7% in Africa. A multilevel study similarly reported prevalence rates ranging from 8–28% [ 18 ]. However, most studies have focused on children under five, leaving a significant gap in data on stunting among preadolescent children; an age characterized by high energy demand and increase cognitive task. While the under-five period is critical for identifying stunting, assessing complex biological outcomes such as visual and cognitive function is more feasible in preadolescent children, particularly in low-resource settings. To date, there remain a paucity of studies exploring the visual and cognitive impacts of stunting in preadolescence. Vision and cognitive function are closely linked and play a vital role in child development, forming the basis for sensorimotor coordination and overall quality of life [ 19 , 20 ]. Visual input supports the development of hand-eye coordination and fine motor skills, which are essential for tasks like writing, and modulates brain pathways involved in pattern recognition, learning, and memory [ 19 , 20 ]. Cognitive function, in turn, supports both higher-order processes—such as spatial planning, problem-solving, and self-regulation—and lower-order functions like attention, psychomotor speed, and memory. Impairments in these areas can negatively affect academic performance, social interaction, emotional well-being, and overall development. The brain and eyes are particularly vulnerable to nutritional deficiencies due to their high metabolic demands. Neuroretinal biomarkers such as CFF, which reflects visual processing speed, and MPOD, which indicates retinal lutein and zeaxanthin levels, have been used to assess carotenoid status in the eyes and brain [ 21 ]. However, their application in the context of chronic undernutrition -stunting has not been explored. Given that stunting is a key indicator of chronic undernutrition, we hypothesized that stunted children would exhibit reduced visual and cognitive function compared to non-stunted children. This study investigated the nutritional, visual, and cognitive profiles of stunted preadolescent children relative to their age-matched non-stunted children. Overall, stunted children exhibited modest reductions in macro- and micronutrient levels, with more than a twofold decrease in lutein (alone and combined with zeaxanthin) and in neuroretinal function such as MPOD, along with lower foveal and perifoveal CFF. Additionally, significant declines in Stock of Cambridge scores indicated impairments in spatial planning and working memory, suggesting reduced capacity for retaining and manipulating visuospatial information. These findings highlight the potential clinical value of MPOD and CFF as early biomarkers of chronic nutritional deficiencies. We advocate for the implementation of targeted nutritional interventions to mitigate visual and cognitive deficits in children at risk of stunting. Methods Study design, participants, and experimental design This was a cross-sectional study. Preadolescent Ghanaian children aged 8–13 years, attending either public or private schools in the Ashanti Region the second most populous region in Ghana—were enrolled in the study from May 2023 to August 2023.The sample included 15 chronically malnourished children, classified as stunted according to World Health Organization criteria, and 275 well-nourished children who served as healthy controls. The two groups did not differ significantly in age, sex, religion, ethnicity or grade level. All participants underwent demographic and nutritional assessments, followed by comprehensive visual evaluations, including tests of visual acuity, contrast sensitivity, critical flicker frequency, and macular pigment optical density. A subset of participants also completed neuropsychological assessments, including Delayed Matching to Sample (DMS), Paired Associates Learning (PAL), Reaction Time (RTI), Stockings of Cambridge (SOC), and Spatial Working Memory (SWM) tasks ( Figure 1: Study Flow chat). Participants Stunted group Anthropometric indices—including body weight and height were measured using standard procedures, Chronic undernutrition was assessed through anthropometric measurements, with stunting defined as low height-for-age based on age- and grade-appropriate norms. Classification followed the WHO anthropometric assessments following WHO Child growth standards, with stunting defined as height-for-age z-scores less than -2SD below the median of the WHO Child growth standards [22, 23]. Non-Stunted children (control group) Non-stunted children matched with the stunted group were selected from the same schools to control for differences in socioeconomic background, as well as home and school environments. Based on WHO Child growth standards, children with height-for-age z-scores greater or equal to -2SDs were included in this group [22, 23]. Eligibility criteria (Inclusion and exclusion) The study included children aged 7 to 13 years with best corrected visual acuity (BCVA) of ≥0.3 log MAR units, no clinical or self-reported ocular lesions, and no neurological or hearing impairments. Children were excluded if their caregivers did not provide written informed consent or if they had medical conditions that could interfere with comprehension of the clinical assessments or confound the study outcomes. Instruments and procedure Biographical data Structured questionnaire Biographical data—including age, sex, ethnicity, iris color, and medical and ocular history—were collected using a structured questionnaire. Anthropometric data Height and weight of the children were measured using standardized procedures outlined by the World Health Organization (WHO, 2006). Height was measured to the nearest 0.1cm using a portable stadiometer (Seca 213, 213-1821129, China) with the children standing upright without shoes, feet together, and head positioned in the Frankfurt horizontal plane. Weight was measured to the nearest 0.1kg using a calibrated digital scale (HBF-514C, 20200302714F, China), with children wearing light clothing and no shoes. Height-for-age Z-scores (HAZ) were calculated using the WHO Anthroplus software for children aged 5-19 years. Children with HAZ <-2 standard deviations (SD) from the median of the WHO growth standards were classified as stunted. Those with HAZ ³ -2 SD were considered non-stunted. Anthropometric measurements were taken twice, and the average value was used in the analysis to ensure accuracy and reliability. Diet data Dietary questionnaire Participants’ macronutrient, micronutrient, and carotenoid intake were assessed using a 24-hour dietary recall in triplicates with household measures. Food consumption over the past three days (two weekdays and one weekend day) was estimated using scoops, teaspoons, and food models. Lutein and zeaxanthin software Intake of lutein (L), zeaxanthin (Z), and their combined amount (L/Z) was calculated using the LZQ™ dietary estimation software [24]. Visual function data ETDRS log MAR chart Best corrected visual acuity, a measure of spatial visual acuity was assayed using Early Treatment Diabetic Retinopathy Study (ETDRS) Logarithm of the Minimum Angle of Resolution (LogMAR) chart at 4 meters [24]. Pelli Robson chart Contrast sensitivity was assessed with the Pelli-Robson chart at 1 meter [24]. Photo screener A licensed optometrist determined refractive status using a Photorefractive Vision Screener, with all measurements converted to spherical equivalents for analysis [25]. Macular densitometry Macular carotenoids were quantified in vivo as macular pigment optical density via customized heterochromatic flicker photometry (cHFP), measuring macular pigment optical density (log I central /I peripheral ) at 1° retinal eccentricity. Participants used their best-corrected eye or, if both eyes had equal visual acuity, their dominant eye to match the peripheral green flicker with the central blue non-flicker stimulus under iso-illuminance conditions. Temporal visual acuity was measured as a function of critical flicker fusion frequency at the fovea, parafovea, and perifovea retinal regions [24]. Cognition data CANTAB Neuropsychological performance assayed in preadolescent children [26]. Neuropsychological performance was assessed using the Cambridge Neuropsychological Test Automated Battery (CANTAB; www.cambridgecognition.com/cantab), as previously described [61]. Tests were administered via a touchscreen tablet and push pad. Prior to each task, examiners used standardized scripts from the CANTAB manual to instruct participants and demonstrate touchscreen use. Voice-over instructions in English guided participants throughout the ~45-minute evaluation. The following five subtests were administered: Memory functions 1. Delayed Matching to Sample (DMS): Participants viewed an abstract visual pattern, followed by four similar patterns after a delay (0, 4, or 12 seconds). They selected the exact match. Outcomes included response latency, correct selections, and error probability. Desired performance: high accuracy and low error probability. 2. Paired Associates Learning (PAL): Patterns were hidden in boxes, then presented one at a time for recall. Participants identified the original box locations. Errors and trials to correct recall were measured. Desired outcome: high correct recall, low error rate. Attention and psychomotor speed 3. Reaction Time (RTI): Participants held a button and responded to a visual cue by selecting a highlighted circle. Both simple (1-choice) and complex (5-choice) versions were used. Measures included reaction and movement times. Desired outcome: faster response and movement times. Executive functions 4. Stockings of Cambridge (SOC): Participants rearranged colored balls in a bottom display to match a pattern in a top display using the fewest moves possible. Outcome measures included problem difficulty, average moves, and planning time. Desired outcome: fewer moves and longer planning time. 5. Spatial Working Memory (SWM): Participants searched colored boxes to find hidden yellow tokens, avoiding repeated selections of empty or already visited boxes. Outcome measures included error count and search strategy. Desired outcome: fewer errors and more efficient strategies. Data analysis and visualization Raw data were initially checked for duplicates and missing entries using Microsoft Excel. The cleaned data were then imported into SPSS version 25 (Windows 10 compatible) for analysis. Normality was assessed using the Kolmogorov-Smirnov test. Demographic, anthropometric, dietary, visual, and cognitive variables were compared by stunting using independent t-tests for normally distributed continuous data, Mann-Whitney U tests for skewed continuous data, and chi-square tests for categorical data, with corresponding Hedge’s g effect sizes reported as appropriate. Significant variables were showed graphically using Graphpad Prism version 10.4.2 compatible with MacBook, Bivariate logistic regressions examined associations between independent and outcome variables. Bivariate variables with a p≤0.05 were included in multiple linear regression models adjusting for potential confounders. Statistical significance was set at p ≤ 0.05. Ethical approval Written approval was obtained from school principals, and informed consent was secured from caregivers after explaining the study protocol. The Committee on Human Research Publication and Ethics at Kwame Nkrumah University of Science and Technology (CHRPE/AP/477/22) formally approved the study. All procedures adhered strictly to the Declaration of Helsinki. Results Stunted children showed clinically significant reductions in micronutrient and macronutrient intake, dietary diversity, and total energy levels compared to age- and sex-matched controls Table 1 summarizes the biographical and nutritional characteristics of stunted children and their age (Student t-test; t = -1.112, g = 0.298; p = 0.2670 ) and sex-matched (Chi-square test; x 2 = 0.895, V = 0.056, p = 0.3440 ) healthy controls. There were significantly lower anthropometric indices (p≤0.05) in stunted compared to well-nourished controls of similar age group ( Figure 2: showed anthropometric characteristics between groups). Most of stunted children were female (66.7%), aged 11–13 years (80%), and had no reported medical conditions (86.7%). Compared to healthy controls, stunted children showed a marked decrease in dietary carotenoid intake. Specifically, the zeaxanthin levels were similar between groups (0.10 ± 0.08 vs. 0.09 ± 0.07; fold change = 1.11; U = 1988.0, r = -0.014; p = 0.8156 ), while lutein alone (1.54 ± 2.46 vs. 0.90 ± 1.75; fold change = 1.71, r = -0.087; p = 0.1402 ) and combined lutein and zeaxanthin (1.64 ± 2.46 vs. 0.99 ± 1.73; fold change = 1.65, r = -0.076; p = 0.1977 ) were approximately twofold lower in stunted children ( p > 0.05 ; see Figure 3 dietary carotenoids and macular carotenoids measured as MPOD). Egg is a rich source of lutein and zeaxanthin and the consumption of eggs per week in the stunted children were relatively lower compared to controls (2.33 versus 2.40). Stunted children showed an overall decline in micronutrient intake (see Figure 4 micronutrients and macronutrient intake between groups), with similar reductions in macronutrients—carbohydrates, lipids, proteins, total energy—and dietary diversity scores compared to healthy controls (see Figure 4 ). Table 1: Biographical and nutritional markers of growth patterns Variable Growth patterns Statistic, p-value, Effect size Healthy controls (n = 275; 95%) Stunted (n = 15; 5%) Biographical characteristics Sex Male 126 (45.8%) 5 (33.3%) x 2 = 0.895, p = 0.344, V = 0.056 Female 149 (54.2%) 10 (66.7%) Age (y) 10.81, 1.32 11.20, 1.01 t = -1.112, p = 0.267, g = 0.298 Age group n = 275 n = 15 8-10 107 (38.9%) 3 (20%) x 2 = 2.160, p = 0.142, V = 0.086 11-13 168 (61.1%) 12 (80%) Medical condition n = 275 n = 15 Yes 22 (8%) 2 (13.3%) x 2 = 0.533, p = 0.465, V = 0.043 No 253 (92.0%) 13 (86.7%) Dietary measures n = 275 n = 15 Lutein (mg/d) 1.54 ± 2.46 0.90 ± 1.75 U = 1594.5, p = 0.1402, r = -0.087 Zeaxanthin (mg/d) 0.10 ± 0.08 0.09 ± 0.07 U = 1988.0, p = 0.8156, r = -0.014 Lutein + Zeaxanthin (mg/d) 1.64 ± 2.46 0.99 ± 1.73 U = 1653.0, p = 0.1977, r = -0.076 Egg consumption/week 2.40 ± 2.09 2.33 ± 1.97 U = 2054.0, p = 0.9792, r = -0.002 Vitamins IU 2391.43 ± 1214.95 1918.51 ± 868.95 U = 1618.0, p = 0.1619, r = -0.083 Retinol (mg/d) 160.43 ± 193.58 121.87 ± 160.62 U = 1682.0, p = 0.2318, r = -0.07 Zinc (mg/d) 12.13 ± 1.421 10.67 ± 3.45 U = 1779.0, p = 0.3971, r = -0.05 Iron (mg/d) 18.65 ± 8.92 16.07 ± 4.74 U = 1772.0, p = 0.3627, r = -0.054 Carbohydrates (g) 377.29 ± 153.22 308.76 ± 83.16 U = 1476.0, p =0.0635, r = -0.109 Proteins (g) 80.29 ±34.75 69.45 ± 22.88 U = 1715.0, p = 0.2755, r = -0.065 Lipids (g) 73.98 ± 30.44 63.14 ± 23.50 U = 1611.0, p = 0.2943, r = -0.084 Total energy consumed (kcal) 2468.27 ± 905.25 2049.60 ± 430.04 U = 1462.0, p = 0.0573, r = -0.112 Dietary diversity score (counts) 8.11 ± 1.06 7.93 ± 1.34 U = 1968.5, p = 0.7591, r = -0.019 a Number of participants for this test slightly differs: Normal (139), Stunted (9). SD: Standard deviation; OD, Oculus dexter; OS, Oculus sinister; CFF, Critical Flicker Frequency; MPOD, Macular Pigment Optical Density; Statistical significance set at p<0.05. Stunted children exhibited reduced neuroretinal function—reflected in lower MPOD and CFF—and significant impairments in spatial planning and working memory Table 2 presents the neuroretinal and neuropsychological characteristics of stunted and age-matched healthy controls. Visual acuity and refractive error did not differ significantly between stunted and non-stunted children ( p > 0.05 ). However, contrast sensitivity was slightly better in non-stunted children by about three letters or 0.06 log units (OS: 1.53 ± 0.19 vs. 1.47 ± 0.27, r = -0.049, p = 0.401 ; OD: 1.53 ± 0.19 versus 1.47 ± 0.27, r = -0.056, p = 0.338 ). Neuroretinal indices such as MPOD was approximately twofold lower in stunted compared to non-stunted children (0.20±0.13 versus 0.33±0.34; fold change = 1.65, U = 1594.5, r = -0.087, p = 0.140 ; Figure 3 ). Foveal (18.16± 3.94 versus 17.05± 4.13, r = -0.042, p = 0.475 ) and perifoveal CFF (20.78±5.24 versus 22.61± 5.00; U = 475.0, r = -0.101, p = 0.217 ) were also reduced in stunted relative to controls. Neurocognitive testing showed no significant differences in delayed matching to sample, paired associate learning, or reaction time ( p > 0.05 ). However, stunted children showed significant impairments in spatial planning (SOC Mean Moves: U = 287.50, r = -0.0317, p = 0.040 ; see Figure 5 shows significant differences in specific neurocognitive task between groups) and spatial working memory (SWM Between Errors: U = 354.0, r = -0.182, p = 0.0245 ; Figure 5 ) as seen in Table 2 . Table 2: Visual and neuropsychological metrics in stunted and healthy matched controls Variable Growth patterns Statistic, p-value, Effect size Control group Stunted group Vision measures n = 275 n = 15 Visual acuity (OD) 0.08 ± 0.10 0.10 ± 0.12 U = 1811.0, p = 0.420, r = -0.047 Visual acuity (OS) 0.08 ± 0.09 0.06 ± 0.09 U = 1690.5, p = 0.234, r = -0.070 Contrast sensitivity (OD) 1.53 ± 0.19 1.47 ± 0.27 U = 1758.0, p = 0.338, r = -0.056 Contrast sensitivity (OS) 1.54 ±0.19 1.47 ± 0.24 U =1794.0, p = 0.401, r = -0.049 Refractive correction in spherical equivalence (OD) -0.02 ± 0.54 0.00 ± 0.66 U = 1991.50, p = 0.822, r = -0.013 Refractive correction in spherical equivalence (OS) 0.00 ±0.56 0.05± 0.63 U = 2016.5, p = 0.884, r = -0.009 MPOD fovea 0.33 ± 0.34 0.20 ± 0.13 U = 1594.50, p = 0.1400, r = -0.087 Fovea CFF 18.16 ± 3.94 17.05 ± 4.13 U = 1422.0, p = 0.475, r = -0.042 Parafovea CFF 16.53 ± 5.59 17.86 ± 7.60 U = 523.0, p = 0.294, r = -0.121 Perifovea CFF 22.61 ± 5.00 20.78 ± 5.24 U = 475.0, p = 0.217, r = -0.101 Neuropsychological measures Delayed Matching to Sample (n = 150) n = 141 n = 9 DMS Accuracy Covert (0 seconds delays) 70.64 ± 25.92 77.78 ± 32.32 U = 493.5, p = 0.249, r = -0.094 DMS Accuracy Covert (4 seconds delays) 64.26 ± 24.59 55.56 ± 37.12 U = 560.0, p = 0.544, r = -0.050 DMS Accuracy Covert (12seconds delays) 58.30 ± 26.24 55.56 ±37.12 U = 617.5, p = 0.891, r = -0.011 DMS Accuracy Covert (All seconds delays) 64.39 ± 18.11 63.11 ± 29.43 U = 576.5, p = 0.644, r = -0.038 DMS Accuracy Overt (Simultaneous) 91.21 ± 14.81 88.89 ± 10.54 U = 523.000, p = 0.294, r = -0.121 DMS Probability of an error after an incorrect response a 0.24 ± 0.21 0.33 ± 0.23 U = 475.000, p = 0.217, r = -0.101 Paired Associates Learning ( n = 150) n = 141 n = 9 PAL Accurate (Correct recall of pattern location) 11.20 ± 4.06 9.44 ± 4.04 U = 486.0, p = 0.239, r = -0.096 PAL Total Errors (Number of times to incorrectly recall a pattern location) 19.62 ± 14.82 25.44 ± 15.81 U = 467.5, p = 0.186, r = -0.108 Reaction Time (n = 150) n = 141 n = 9 RTI Median Five-Choice Movement Time 300.45 ± 55.97 290.167 ± 68.17 t = 0.528, p = 0.599, g = 0.181 RTI Median Five-Choice Reaction Time 379.14 ± 46.53 389.61 ± 40.47 t = -0.659, p = 0.511, g = 0.227 RTI Simple Median Movement Time 276.805 ± 61.43 281.44 ± 80.93 t = -0.215, p = 0.830, g = 0.074 RTI Simple Median Reaction Time 341.22 ± 48.59 347.28 ± 42.28 U = 580.0, p = 0.669, r = -0.035 Stocking of Cambridge (n = 140) n = 131 n = 9 SOC Initial Thinking Time Median (5 Moves) 2473.25 ± 3069.38 2405.00 ± 2237.58 U = 570.000, p = 0.868, r = -0.014 SOC Mean Moves (5 Moves) 8.2099 ± 1.73 9.89 ± 1.74 U = 287.50, p = 0.040, r = -0.0317‡ SOC Subsequent Thinking Time Median (5 Moves) 875.93 ± 1352.03 2958.01 ± 4781.92 U = 373.000, p = 0.063, r = -0.157 Spatial Working Memory (n = 150) n = 141 n = 9 SWM Between Error 20.10 ± 6.70 24.78 ± 5.45 U = 354.0, p = 0.0245, r = -0.182‡ SWM Between errors 4 boxes 1.20 ± 1.33 1.78 ± 1.64 U = 493.0, p = 0.240, r = -0.096 SWM Between errors 6 boxes 5.84 ± 3.05 7.11 ± 2.85 U = 535.5, p = 0.430, r = -0.065 SWM Between errors 8 boxes 13.06 ± 4.65 15.89 ± 4.57 U = 453.5, p = 0.150, r = -0.117 SWM Strategy (6-8 boxes) 9.13 ± 1.99 10.11 ± 1.83 U = 456.0, p = 0.152, r = -0.117 ‡, significant difference between groups. DMS: Delayed Matching to Sample assesses both simultaneous visual matching ability and short-term visual recognition memory, for non-verbalisable patterns; PAL: Paired Associates Learning assesses visual memory and new learning; RTI: Reaction Time (RTI) provides assessments of motor and mental response speeds, as well as measures of movement time, reaction time, response accuracy and impulsivity; SOC: Stockings of Cambridge (SOC) is a test of spatial planning that requires individuals to use problem-solving strategies to match two sets of stimuli; SWM: Spatial Working Memory requires retention and manipulation of visuospatial information. This self-ordered test has notable executive function demands and provides a measure of strategy as well as working memory errors. OD, Oculus dexter; OS, Oculus sinister; CFF, Critical Flicker Frequency; MPOD, Macular Pigment Optical Density; Statistical significance set at p<0.05. Stunting in children was significantly associated with deficits in spatial planning Bivariate logistic regression showed significant deficits in SOC mean moves (OR = 1.70, p = 0.010), SOC thinking time (OR = 1.00, p = 0.019), and SWM errors (OR = 1.18, p = 0.037) in stunted children. After adjustment, SOC mean moves remained significantly associated with stunting (AOR = 1.43, p = 0.049) suggestive of significant impairment in spatial planning as seen in Table 3 . Table 3: Bivariate and multiple regression of factors associated with stunting Variable Bivariate regression Multiple regression OR 95%CI p-value AOR 95%CI p-value Biographical characteristics Sex Male 1.00 Female 1.69 0.56 - 5.08 0.349 Age (y) 1.27 0.83 -1.93 0.269 Age group 8-10 1.00 11-13 2.55 0.70 - 9.24 0.155 Medical condition: no versus yes 1.77 0.38 - 8.35 0.471 Nutrition measures Lutein (mg/d) 0.85 0.62 - 1.18 0.335 Zeaxanthin (mg/d) 0.56 0.00 - 339.33 0.860 Lutein + Zeaxanthin (mg/d) 0.85 0.62 - 1.18 0.331 Egg consumption/week 0.98 0.76 - 1.27 0.904 Vitamins IU 1.00 0.10 - 1.00 0.135 Retinol 1.00 0.10 - 1.00 0.449 Zinc 0.94 0.84 - 1.06 0.301 Iron 0.96 0.89 - 1.03 0.264 Carbohydrates (g) 1.00 0.99 - 1.00 0.082 Proteins (g) 0.99 0.97 - 1.01 0.232 Lipids (g) 0.99 0.97 - 1.01 0.172 Energy consumed in kcal 1.00 0.10 - 1.00 0.074 Dietary diversity score 0.86 0.55 - 1.36 0.528 Vision measures Visual acuity (OD) 9.75 0.05 - 19.31 0.399 Visual acuity (OS) 0.08 0.00 - 24.58 0.387 Contrast sensitivity (OD) 0.21 0.02 - 2.18 0.191 Contrast sensitivity (OS) 0.19 0.02 - 2.10 0.177 Refractive correction in spherical equivalence (OD) 1.05 0.40 - 2.71 0.927 Refractive correction in spherical equivalence (OS) 1.16 0.47 - 2.87 0.749 MPOD fovea 0.07 0.00 - 2.18 0.131 Fovea CFF 0.92 0.79 - 1.08 0.316 Parafovea CFF 1.04 0.95 - 1.13 0.412 Perifovea CFF 0.92 0.82 - 1.04 0.198 Neuropsychological measures Delayed Matching to Sample (n = 150) DMS Accuracy Covert (0 seconds delays) 1.01 0.98 - 1.04 0.431 DMS Accuracy Covert (4 seconds delays) 0.99 0.96 - 1.01 0.322 DMS Accuracy Covert (12seconds delays) 1.00 0.97 - 1.02 0.766 DMS Accuracy Covert (All seconds delays) 1.00 0.96 - 1.03 0.843 DMS Accuracy Overt (Simultaneous) 0.99 0.95 - 1.03 0.644 DMS Probability of an error after an incorrect response a 7.41 0.30 – 18.4 0.222 Paired Associates Learning ( n = 150) PAL Accurate (Correct recall of pattern location) 0.90 0.76 - 1.06 0.215 PAL Total Errors (Number of times to incorrectly recall a pattern location) 1.02 0.98 - 1.07 0.261 Reaction Time (n = 150) RTI Median Five-Choice Movement Time 1.00 0.98 - 1.01 0.596 RTI Median Five-Choice Reaction Time 1.01 0.99 - 1.02 0.509 RTI Simple Median Movement Time 1.00 0.99 - 1.01 0.828 RTI Simple Median Reaction Time 1.00 0.99 - 1.02 0.714 Stocking of Cambridge (n = 140) SOC Initial Thinking Time Median (5 Moves) 1.00 1.00 - 1.00 0.947 SOC Mean Moves (5 Moves) 1.70 1.14 - 2.55 0.010‡ 1.43 1.00 – 2.66 0.049‡ SOC Subsequent Thinking Time Median (5 Moves) 1.00 1.00 - 1.00 0.019‡ 1.00 1.00- 1.00 0.825 Spatial Working Memory (n = 150) SWM Between Error 1.18 1.01 - 1.38 0.037‡ 1.20 0.97-1.39 0.096 SWM Between errors 4 boxes 1.32 0.85 - 2.07 0.220 SWM Between errors 6 boxes 1.15 0.92 - 1.45 0.223 SWM Between errors 8 boxes 1.20 0.98 - 1.46 0.074 SWM Strategy (6-8 boxes) 1.36 0.90 - 2.0 0.148 DMS: Delayed Matching to Sample assesses both simultaneous visual matching ability and short-term visual recognition memory, for non-verbalisable patterns; PAL: Paired Associates Learning assesses visual memory and new learning; RTI: Reaction Time (RTI) provides assessments of motor and mental response speeds, as well as measures of movement time, reaction time, response accuracy and impulsivity; SOC: Stockings of Cambridge (SOC) is a test of spatial planning that requires individuals to use problem-solving strategies to match two sets of stimuli; SWM: Spatial Working Memory requires retention and manipulation of visuospatial information. This self-ordered test has notable executive function demands and provides a measure of strategy as well as working memory errors. OD, Oculus dexter; OS, Oculus sinister; CFF, Critical Flicker Frequency; MPOD, Macular Pigment Optical Density; OR, Odds Ratio; AOR, Adjusted Odds Ratio; CI confidence interval; Bivariate logistic regression; p-value of p<0.05 considered for inclusion in the multivariate model; Statistical significance set at p ≤ 0.05; Statistical significance set at p<0.05. Discussion Stunting, a form of chronic undernutrition characterized by reduced height-for-age (see Figure 1), is resulting from prolonged inadequate intake of energy, protein and essential micronutrients, often compounded by repeated infections and poor caregiving practices. In preadolescent children, the brain and eyes are still developing and require an adequate nutrient supply for proper function [27]. Given the high sensitivity of the brain and the eyes to nutrient deficiency and the fact that stunting is a key indicator of chronic undernutrition, reflecting long-term nutritional deprivation[1, 2, 28, 29], we hypothesized that children with stunted growth would exhibit impaired neuroretinal and neuropsychological function deficits relative to their age-matched, well-nourished controls. Consistent with our hypothesis, we observed a marked decline in both neuroretinal and neuropsychological function among the stunted group. Specifically, stunted children demonstrated clinically significant reductions in macular pigment optical density and critical flicker fusion frequency (Table 2), as well as statistically significant deficits in spatial planning and spatial working memory compared to healthy controls (Figure 4). Moreover, stunted children were more likely to experience impaired spatial planning compared to aged-matched controls (Table 4). In our study, children with stunting exhibited reduced neuroretinal function, as reflected by decreased MPOD and CFF compared to age-matched controls (Table 2). These findings suggest diminished brain and retinal carotenoid status [30, 31] and as well as impaired temporal visual processing. MPOD and CFF typically increase with age in premature children, but are significantly impaired in those with retinopathy of prematurity [32-35]. This suggests a link between retinal maturation and the development of these neuroretinal parameters [32-35]. This highlights the value of MPOD and CFF as objective tools for diagnosing and monitoring chronic undernutrition, particularly in resource-limited settings with a high burden of undernutrition, and their potential for assessing neural health in affected children [36]. Unlike non-stunted children, children with stunting exhibited impaired spatial planning and spatial working memory. Our observation corroborates with previous studies that demonstrated the impact of stunting on critical cognitive systems such as visual working memory [37]. The poor neuropsychological performance may mechanistically be due to reduced engagement of the left anterior intraparietal sulcus (a region involved in maintaining visual working memory) and greater suppression in the right temporoparietal junction (a region involved in shifting attention) [37]. Furthermore, stunted children were more likely to show an increase in the mean number of SOC moves, which indicates impaired cognition, particularly with regard to spatial planning. The findings are similar to studies by Lestari et al , that showed diminished neurocognitive performance in stunted relative to non-stunted Indonesian children [38] as well as Sanou and coworkers that showed poorer neuro-psychological outcomes among children in rural Burkina Faso [39]. Collectively, the findings demonstrate the functional impact of stunting on brain health and underscore the need for comprehensive cognitive evaluation in children with chronic undernutrition. This study presents a novel report on the deficit in neuroretinal and neurocognitive function under stunted condition and unravel the diagnostic potential of MPOD and CFF as neuroretinal biomarker to monitor chronic undernutrition. However, there are some few limitations worth mentioning. The sample size for the stunted group was relatively small, which may limit the generalizability of the findings. Nonetheless, the inclusion of a larger control group enhanced statistical power and improved the robustness of detecting subtle differences between groups. The findings have broad implications at the intersection of nutrition, ophthalmology, and neuroscience, highlighting the need for a multidisciplinary approach to addressing stunting. Conclusion This study presents data that extend beyond dietary status to examine the influence of stunting on neuroretinal and neuropsychological performance. Overall, there was a declining trend in macronutrient and micronutrient intake, including the retinal and brain carotenoids lutein and zeaxanthin (Figure 2), accompanied by clinical deficits in neuroretinal function and significant impairments in cognitive performance (Table 2 and Figure 4). The sensitivity of macular pigment optical density (MPOD) and critical flicker frequency (CFF) in identifying stunting-related changes highlights their potential as diagnostic tools for monitoring neural health in chronic undernutrition. These findings collectively support the need for targeted nutritional interventions to help mitigate visual and cognitive deficits in children at risk of stunting. Abbreviations AOR Adjusted Odds Ratio B.M.I. Body Mass Index CANTAB Cambridge Neuropsychological Test Automated Battery C.F.F. Critical Flicker Frequency CS Contrast Sensitivity D.M.S. Delayed Matching to Sample MPOD Macular Pigment Optical Density L Lutein O.R. Odds Ratio P.A.L. Paired Associates Learning R.T.I. Retention Time S.O.C. Stock of Cambridge S.W.M. Spatial Working Memory Z Zeaxanthin. Declarations Acknowledgment The authors thank the school authorities and staff for their cooperation, and the caregivers and students for their participation. We also acknowledge the research assistants for their support in data collection, and Dr. Emmanuel Asamoah Agyemang for providing the iPad used for the CANTAB™ test. Special thanks to Cambridge Cognition for supplying the CANTAB™ test battery, financial support for travel, and expert guidance in test administration. The authors appreciate the support of Bernice Lebene Tettey of the Department of Chemistry, College of Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana for assisting in the preparation of the figure for the study workflow. Author contributions M.A.: conceptualization, methodology, project management, resources, experimental design, data curation, data validation, investigation, software, formal analysis, formatting, writing review, and editing. I.O.D.J.: conceptualization, methodology, project management, resources, experimental design, data curation, data validation, prepared figures, investigation, software, formal analysis, formatting, writing original draft, writing review, and editing, correspondence. D.A.O: methodology, project management, resources, experimental design, data collection, investigation, software, writing review, and editing. F.A.A.P: methodology, project management, resources, experimental design, formal analysis, writing review, and editing. W.O. A: methodology, project management, resources, investigation, software, formal analysis, writing review, and editing. N.A.S.A: methodology, project management, resources, experimental design, data collection, investigation, software, writing review, and editing. E.J.J: methodology, resources, data curation, data validation, investigation, software, formal analysis, writing review and editing S.A.A: methodology, data curation, writing reviews and editing, B.A.A: methodology, data visualization, writing reviews and editing, J.A.B: methodology, resources, data collection, writing reviews and editing, P.A.S.A: methodology, writing original draft, writing reviews and editing. K.O.A: conceptualization, methodology, project management, resources, experimental design, data curation, data validation, investigation, software, formal analysis, writing review, and editing, supervision, correspondence. Funding This work was supported in part by a primary research award to N.A.S.A. from Cambridge Cognition. The CANTAB™ research grant included a CANTAB™ Connect license for 150 assessments, funding for site visits, and expert training in test administration. Cambridge Cognition had no role in the design, conduct, or interpretation of the study data. K.O.A. received the George Britton Early Investigator of the Year Award 2022 from the Brain and Ocular Nutrition (BON) Conference, which provided partial funding; BON likewise had no role in the study’s design, conduct, or data interpretation. K.O.A. also received partial funding through a Small Research Grant from Volunteer Optometric Services to Humanity (VOSH) International, which supported logistics and travel. VOSH had no role in the design, conduct, or interpretation of the study findings. Availability of data materials All relevant data and materials supporting the conclusion of this article is/are available within the manuscript and its supporting information files. Ethical consideration Written approval was obtained from school principals, and informed consent was secured from caregivers after explaining the study protocol. The Committee on Human Research Publication and Ethics at Kwame Nkrumah University of Science and Technology (CHRPE/AP/477/22) formally approved the study. All procedures adhered strictly to the Declaration of Helsinki. Clinical trial number Not applicable Consent for publication Not applicable Competing interests All authors declare no competing interests. References Bourre J-M: Effects of nutrients (in food) on the structure and function of the nervous system: update on dietary requirements for brain. Part 1: micronutrients . Journal of nutrition health and aging 2006, 10 (5):377. Bourre J-M: Effects of nutrients (in food) on the structure and function of the nervous system: update on dietary requirements for brain. Part 2: macronutrients . Journal of Nutrition Health and Aging 2006, 10 (5):386. 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legend.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6908758/v1/d08fc59dbd92ac69e7d8dfb4.png"},{"id":87551096,"identity":"79d3ff91-1c0d-476d-a641-a877325ad0ce","added_by":"auto","created_at":"2025-07-25 06:20:17","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":64797,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6908758/v1/5338a60223c430d1a78eea7c.png"},{"id":87553199,"identity":"45a4abfa-a245-4245-bf86-608ffeba1756","added_by":"auto","created_at":"2025-07-25 06:36:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3510986,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6908758/v1/f700fe84-9974-4c50-a66d-69d4d3898305.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Neuroretinal and neuropsychological functional deficit in preadolescent children with stunted growth","fulltext":[{"header":"Background","content":"\u003cp\u003eOptimal nutrient intake is essential for maintaining the structural integrity and functional health of mammalian organs including the brain, the eyes and overall body composition [\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Macronutrients\u0026mdash;carbohydrates, proteins, and lipids\u0026mdash;support bioenergetics and serve distinct roles: carbohydrates fuel cellular respiration, proteins provide structural components for tissues, and lipids support enzymatic functions, membrane formation, hormone synthesis [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Micronutrients, such as vitamins, iron and zinc, function as enzyme cofactors, regulate gene expression, and play critical roles in brain health and energy metabolism [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Xanthophyll carotenoids, particularly lutein and zeaxanthin, are vital for brain and visual system development[\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Deficiencies in macro- or micronutrients disrupt cellular metabolism and homeostasis, potentially impairing growth and leading to abnormal developmental patterns in children[\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eStunting, a clinical indicator of chronic nutrient deficiency, is defined by the Centers for Disease Control and Prevention (CDC) as low height-for-age, reflecting prolonged undernutrition and impaired growth potential [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Globally, stunting remains a major public health issue, with an estimated prevalence of around 30%, and the highest burden occurring in West Africa [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The Global Nutrition Report estimates that 17.5% of children under five are stunted, compared to a regional average of 30.7% in Africa. A multilevel study similarly reported prevalence rates ranging from 8\u0026ndash;28% [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, most studies have focused on children under five, leaving a significant gap in data on stunting among preadolescent children; an age characterized by high energy demand and increase cognitive task. While the under-five period is critical for identifying stunting, assessing complex biological outcomes such as visual and cognitive function is more feasible in preadolescent children, particularly in low-resource settings. To date, there remain a paucity of studies exploring the visual and cognitive impacts of stunting in preadolescence.\u003c/p\u003e\u003cp\u003eVision and cognitive function are closely linked and play a vital role in child development, forming the basis for sensorimotor coordination and overall quality of life [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Visual input supports the development of hand-eye coordination and fine motor skills, which are essential for tasks like writing, and modulates brain pathways involved in pattern recognition, learning, and memory [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Cognitive function, in turn, supports both higher-order processes\u0026mdash;such as spatial planning, problem-solving, and self-regulation\u0026mdash;and lower-order functions like attention, psychomotor speed, and memory. Impairments in these areas can negatively affect academic performance, social interaction, emotional well-being, and overall development. The brain and eyes are particularly vulnerable to nutritional deficiencies due to their high metabolic demands. Neuroretinal biomarkers such as CFF, which reflects visual processing speed, and MPOD, which indicates retinal lutein and zeaxanthin levels, have been used to assess carotenoid status in the eyes and brain [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, their application in the context of chronic undernutrition -stunting has not been explored. Given that stunting is a key indicator of chronic undernutrition, we hypothesized that stunted children would exhibit reduced visual and cognitive function compared to non-stunted children. This study investigated the nutritional, visual, and cognitive profiles of stunted preadolescent children relative to their age-matched non-stunted children.\u003c/p\u003e\u003cp\u003eOverall, stunted children exhibited modest reductions in macro- and micronutrient levels, with more than a twofold decrease in lutein (alone and combined with zeaxanthin) and in neuroretinal function such as MPOD, along with lower foveal and perifoveal CFF. Additionally, significant declines in Stock of Cambridge scores indicated impairments in spatial planning and working memory, suggesting reduced capacity for retaining and manipulating visuospatial information. These findings highlight the potential clinical value of MPOD and CFF as early biomarkers of chronic nutritional deficiencies. We advocate for the implementation of targeted nutritional interventions to mitigate visual and cognitive deficits in children at risk of stunting.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy design, participants, and experimental design \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis was a cross-sectional study. Preadolescent Ghanaian children aged 8–13 years, attending either public or private schools in the Ashanti Region the second most populous region in Ghana—were enrolled in the study from May 2023 to August 2023.The sample included 15 chronically malnourished children, classified as stunted according to World Health Organization criteria, and 275 well-nourished children who served as healthy controls. The two groups did not differ significantly in age, sex, religion, ethnicity or grade level. All participants underwent demographic and nutritional assessments, followed by comprehensive visual evaluations, including tests of visual acuity, contrast sensitivity, critical flicker frequency, and macular pigment optical density. A subset of participants also completed neuropsychological assessments, including Delayed Matching to Sample (DMS), Paired Associates Learning (PAL), Reaction Time (RTI), Stockings of Cambridge (SOC), and Spatial Working Memory (SWM) tasks (\u003cstrong\u003eFigure 1: \u003c/strong\u003eStudy Flow chat).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipants \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStunted group \u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAnthropometric indices—including body weight and height were measured using standard procedures, Chronic undernutrition was assessed through anthropometric measurements, with stunting defined as low height-for-age based on age- and grade-appropriate norms. Classification followed the WHO anthropometric assessments following WHO Child growth standards, with stunting defined as height-for-age z-scores less than -2SD below the median of the WHO Child growth standards [22, 23]. \u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNon-Stunted children (control group) \u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNon-stunted children matched with the stunted group were selected from the same schools to control for differences in socioeconomic background, as well as home and school environments. Based on WHO Child growth standards, children with height-for-age z-scores greater or equal to -2SDs were included in this group [22, 23]. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEligibility criteria (Inclusion and exclusion)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study included children aged 7 to 13 years with best corrected visual acuity (BCVA) of ≥0.3 log MAR units, no clinical or self-reported ocular lesions, and no neurological or hearing impairments. Children were excluded if their caregivers did not provide written informed consent or if they had medical conditions that could interfere with comprehension of the clinical assessments or confound the study outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstruments and procedure \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBiographical data \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStructured questionnaire \u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eBiographical data—including age, sex, ethnicity, iris color, and medical and ocular history—were collected using a structured questionnaire.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnthropometric data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHeight and weight of the children were measured using standardized procedures outlined by the World Health Organization (WHO, 2006). Height was measured to the nearest 0.1cm using a portable stadiometer (Seca 213, 213-1821129, China) with the children standing upright without shoes, feet together, and head positioned in the Frankfurt horizontal plane. Weight was measured to the nearest 0.1kg using a calibrated digital scale (HBF-514C, 20200302714F, China), with children wearing light clothing and no shoes. Height-for-age Z-scores (HAZ) were calculated using the WHO Anthroplus software for children aged 5-19 years. Children with HAZ \u0026lt;-2 standard deviations (SD) from the median of the WHO growth standards were classified as stunted. Those with HAZ ³ -2 SD were considered non-stunted. Anthropometric measurements were taken twice, and the average value was used in the analysis to ensure accuracy and reliability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiet data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDietary questionnaire \u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eParticipants’ macronutrient, micronutrient, and carotenoid intake were assessed using a 24-hour dietary recall in triplicates with household measures. Food consumption over the past three days (two weekdays and one weekend day) was estimated using scoops, teaspoons, and food models. \u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLutein and zeaxanthin software\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIntake of lutein (L), zeaxanthin (Z), and their combined amount (L/Z) was calculated using the LZQ™ dietary estimation software [24]. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVisual function\u003c/strong\u003e\u003cstrong\u003edata \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eETDRS log MAR chart \u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eBest corrected visual acuity, a measure of spatial visual acuity was assayed using Early Treatment Diabetic Retinopathy Study (ETDRS) Logarithm of the Minimum Angle of Resolution (LogMAR) chart at 4 meters [24].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePelli Robson chart \u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eContrast sensitivity was assessed with the Pelli-Robson chart at 1 meter [24].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePhoto screener \u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA licensed optometrist determined refractive status using a Photorefractive Vision Screener, with all measurements converted to spherical equivalents for analysis [25].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMacular densitometry\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMacular carotenoids were quantified \u003cem\u003ein vivo\u003c/em\u003e as macular pigment optical density via customized heterochromatic flicker photometry (cHFP), measuring macular pigment optical density (log I\u003csub\u003ecentral\u003c/sub\u003e/I\u003csub\u003eperipheral\u003c/sub\u003e) at 1° retinal eccentricity. Participants used their best-corrected eye or, if both eyes had equal visual acuity, their dominant eye to match the peripheral green flicker with the central blue non-flicker stimulus under iso-illuminance conditions. Temporal visual acuity was measured as a function of critical flicker fusion frequency at the fovea, parafovea, and perifovea retinal regions [24].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCognition data \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCANTAB Neuropsychological performance assayed in preadolescent children \u003c/em\u003e[26].\u003c/p\u003e\n\u003cp\u003eNeuropsychological performance was assessed using the Cambridge Neuropsychological Test Automated Battery (CANTAB; www.cambridgecognition.com/cantab), as previously described [61]. Tests were administered via a touchscreen tablet and push pad. Prior to each task, examiners used standardized scripts from the CANTAB manual to instruct participants and demonstrate touchscreen use. Voice-over instructions in English guided participants throughout the ~45-minute evaluation. The following five subtests were administered:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMemory functions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e1. \u003cstrong\u003e\u003cem\u003eDelayed Matching to Sample (DMS):\u003c/em\u003e\u003c/strong\u003e Participants viewed an abstract visual pattern, followed by four similar patterns after a delay (0, 4, or 12 seconds). They selected the exact match. Outcomes included response latency, correct selections, and error probability. Desired performance: high accuracy and low error probability.\u003c/p\u003e\n\u003cp\u003e2. \u003cstrong\u003e\u003cem\u003ePaired Associates Learning (PAL):\u003c/em\u003e\u003c/strong\u003e Patterns were hidden in boxes, then presented one at a time for recall. Participants identified the original box locations. Errors and trials to correct recall were measured. Desired outcome: high correct recall, low error rate.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAttention and psychomotor speed \u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e3. \u003cstrong\u003e\u003cem\u003eReaction Time (RTI):\u003c/em\u003e\u003c/strong\u003e Participants held a button and responded to a visual cue by selecting a highlighted circle. Both simple (1-choice) and complex (5-choice) versions were used. Measures included reaction and movement times. Desired outcome: faster response and movement times.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eExecutive functions \u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e4. \u003cstrong\u003e\u003cem\u003eStockings of Cambridge (SOC):\u003c/em\u003e\u003c/strong\u003e Participants rearranged colored balls in a bottom display to match a pattern in a top display using the fewest moves possible. Outcome measures included problem difficulty, average moves, and planning time. Desired outcome: fewer moves and longer planning time.\u003c/p\u003e\n\u003cp\u003e5. \u003cstrong\u003e\u003cem\u003eSpatial Working Memory (SWM):\u003c/em\u003e\u003c/strong\u003e Participants searched colored boxes to find hidden yellow tokens, avoiding repeated selections of empty or already visited boxes. Outcome measures included error count and search strategy. Desired outcome: fewer errors and more efficient strategies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis and visualization \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRaw data were initially checked for duplicates and missing entries using Microsoft Excel. The cleaned data were then imported into SPSS version 25 (Windows 10 compatible) for analysis. Normality was assessed using the Kolmogorov-Smirnov test. Demographic, anthropometric, dietary, visual, and cognitive variables were compared by stunting using independent t-tests for normally distributed continuous data, Mann-Whitney U tests for skewed continuous data, and chi-square tests for categorical data, with corresponding Hedge’s g effect sizes reported as appropriate. Significant variables were showed graphically using Graphpad Prism version 10.4.2 compatible with MacBook, Bivariate logistic regressions examined associations between independent and outcome variables. Bivariate variables with a p≤0.05 were included in multiple linear regression models adjusting for potential confounders. Statistical significance was set at p ≤ 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWritten approval was obtained from school principals, and informed consent was secured from caregivers after explaining the study protocol. The Committee on Human Research Publication and Ethics at Kwame Nkrumah University of Science and Technology (CHRPE/AP/477/22) formally approved the study. All procedures adhered strictly to the Declaration of Helsinki.\u003c/p\u003e"},{"header":"Results ","content":"\u003cp\u003e\u003cstrong\u003eStunted children showed clinically significant reductions in micronutrient and macronutrient intake, dietary diversity, and total energy levels compared to age- and sex-matched controls\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e summarizes the biographical and nutritional characteristics of stunted children and their age (Student t-test; t = -1.112, g = 0.298; \u003cem\u003ep = 0.2670\u003c/em\u003e) and sex-matched (Chi-square test; x\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e= 0.895, V = 0.056, \u003cem\u003ep = 0.3440\u003c/em\u003e) healthy controls. \u0026nbsp;There were significantly lower anthropometric indices (p\u0026le;0.05) in stunted compared to well-nourished controls of similar age group (\u003cstrong\u003eFigure 2:\u0026nbsp;\u003c/strong\u003eshowed anthropometric characteristics between groups). Most of stunted children were female (66.7%), aged 11\u0026ndash;13 years (80%), and had no reported medical conditions (86.7%). Compared to healthy controls, stunted children showed a marked decrease in dietary carotenoid intake. Specifically, the zeaxanthin levels were similar between groups (0.10 \u0026plusmn; 0.08 vs. 0.09 \u0026plusmn; 0.07; fold change = 1.11; U = 1988.0, r = -0.014; \u003cem\u003ep = 0.8156\u003c/em\u003e), while lutein alone (1.54 \u0026plusmn; 2.46 vs. 0.90 \u0026plusmn; 1.75; fold change = 1.71, r = -0.087; \u003cem\u003ep = 0.1402\u003c/em\u003e) and combined lutein and zeaxanthin (1.64 \u0026plusmn; 2.46 vs. 0.99 \u0026plusmn; 1.73; fold change = 1.65, r = -0.076; \u003cem\u003ep = 0.1977\u003c/em\u003e) were approximately twofold lower in stunted children (\u003cem\u003ep \u0026gt; 0.05\u003c/em\u003e; see \u003cstrong\u003eFigure 3\u0026nbsp;\u003c/strong\u003edietary carotenoids and macular carotenoids measured as MPOD). Egg is a rich source of lutein and zeaxanthin and the consumption of eggs per week in the stunted children were relatively lower compared to controls (2.33 versus 2.40). Stunted children showed an overall decline in micronutrient intake (see \u003cstrong\u003eFigure 4\u0026nbsp;\u003c/strong\u003emicronutrients and macronutrient intake between groups), with similar reductions in macronutrients\u0026mdash;carbohydrates, lipids, proteins, total energy\u0026mdash;and dietary diversity scores compared to healthy controls (see \u003cstrong\u003eFigure 4\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: Biographical and nutritional markers of growth patterns\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"738\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 336px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrowth patterns\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStatistic, p-value, Effect size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthy controls (n = 275; 95%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStunted (n = 15; 5%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eBiographical characteristics\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSex\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e126 (45.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e5 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003ex\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e = 0.895, p = 0.344, V = 0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e149 (54.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e10 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003eAge (y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e10.81, 1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e11.20, 1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003et = -1.112, p = 0.267, g = 0.298\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003eAge group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003en = 275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003en = 15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003e8-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e107 (38.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e3 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003ex\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e = 2.160, p = 0.142, V = 0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003e11-13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e168 (61.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e12 (80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003eMedical condition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003en = 275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003en = 15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e22 (8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e2 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003ex\u003csup\u003e2\u003c/sup\u003e\u0026nbsp; = 0.533, p = 0.465, V = 0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e253 (92.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e13 (86.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eDietary measures\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003en = 275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003en = 15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003eLutein (mg/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e1.54 \u0026plusmn; 2.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e0.90 \u0026plusmn; 1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eU = 1594.5, p = 0.1402, r = -0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003eZeaxanthin (mg/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e0.10 \u0026plusmn; 0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e0.09 \u0026plusmn; 0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eU = 1988.0, p = 0.8156, r = -0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003eLutein + Zeaxanthin (mg/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e1.64 \u0026plusmn; 2.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e0.99 \u0026plusmn; 1.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eU = 1653.0, p = 0.1977, r = -0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003eEgg consumption/week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e2.40 \u0026plusmn; \u0026nbsp;2.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e2.33 \u0026plusmn; 1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eU = 2054.0, p = 0.9792, r = -0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003eVitamins IU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e2391.43 \u0026plusmn; 1214.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e1918.51 \u0026plusmn; 868.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eU = 1618.0, p = 0.1619, r = -0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003eRetinol (mg/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e160.43 \u0026plusmn; 193.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e121.87 \u0026plusmn; 160.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eU = 1682.0, p = 0.2318, r = -0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003eZinc (mg/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e12.13 \u0026plusmn; 1.421\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e10.67 \u0026plusmn; 3.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eU = 1779.0, p = 0.3971, r = -0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003eIron (mg/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e18.65 \u0026plusmn; 8.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e16.07 \u0026plusmn; 4.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eU = 1772.0, p = 0.3627, r = -0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003eCarbohydrates (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e377.29 \u0026plusmn; 153.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e308.76 \u0026plusmn; 83.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eU = 1476.0, p =0.0635, r = -0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003eProteins (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e80.29 \u0026nbsp;\u0026plusmn;34.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e69.45 \u0026plusmn; 22.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eU = 1715.0, p = 0.2755, \u0026nbsp; \u0026nbsp; r = -0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003eLipids (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e73.98 \u0026plusmn; 30.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e63.14 \u0026plusmn; 23.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eU = 1611.0, p = 0.2943, r = -0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003eTotal energy consumed (kcal)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e2468.27 \u0026plusmn; 905.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e2049.60 \u0026plusmn; 430.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eU = 1462.0, p = 0.0573, r = -0.112\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 186px;\"\u003e\n \u003cp\u003eDietary diversity score (counts)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 207px;\"\u003e\n \u003cp\u003e8.11 \u0026plusmn; 1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e7.93 \u0026plusmn; 1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 216px;\"\u003e\n \u003cp\u003eU = 1968.5, p = 0.7591, r = -0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eNumber of participants for this test slightly differs: Normal (139), Stunted (9). SD: Standard deviation; OD, Oculus dexter; OS, Oculus sinister; CFF, Critical Flicker Frequency; MPOD, Macular Pigment Optical Density; Statistical significance set at p\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStunted children exhibited reduced neuroretinal function\u0026mdash;reflected in lower MPOD and CFF\u0026mdash;and significant impairments in spatial planning and working memory\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e presents the neuroretinal and neuropsychological characteristics of stunted and age-matched healthy controls. Visual acuity and refractive error did not differ significantly between stunted and non-stunted children (\u003cem\u003ep \u0026gt; 0.05\u003c/em\u003e). However, contrast sensitivity was slightly better in non-stunted children by about three letters or 0.06 log units (OS: 1.53 \u0026plusmn; 0.19 vs. 1.47 \u0026plusmn; 0.27, r = -0.049, \u003cem\u003ep = 0.401\u003c/em\u003e; OD: 1.53 \u0026plusmn; 0.19 versus 1.47 \u0026plusmn; 0.27, r = -0.056, \u003cem\u003ep = 0.338\u003c/em\u003e). Neuroretinal indices such as MPOD was approximately twofold lower in stunted compared to non-stunted children (0.20\u0026plusmn;0.13 versus 0.33\u0026plusmn;0.34; fold change = 1.65, U = 1594.5, r = -0.087, \u003cem\u003ep = 0.140\u003c/em\u003e; \u003cstrong\u003eFigure 3\u003c/strong\u003e). Foveal (18.16\u0026plusmn; 3.94 versus 17.05\u0026plusmn; 4.13, r = -0.042, \u003cem\u003ep = 0.475\u003c/em\u003e) and perifoveal CFF (20.78\u0026plusmn;5.24 versus 22.61\u0026plusmn; 5.00; U = 475.0, r = -0.101, \u003cem\u003ep = 0.217\u003c/em\u003e) were also reduced in stunted relative to controls. Neurocognitive testing showed no significant differences in delayed matching to sample, paired associate learning, or reaction time (\u003cem\u003ep \u0026gt; 0.05\u003c/em\u003e). However, stunted children showed significant impairments in spatial planning (SOC Mean Moves: U = 287.50, r = -0.0317, \u003cem\u003ep = 0.040\u003c/em\u003e; see \u003cstrong\u003eFigure 5\u0026nbsp;\u003c/strong\u003eshows significant differences in specific neurocognitive task between groups) and spatial working memory (SWM Between Errors: U = 354.0, r = -0.182, \u003cem\u003ep = 0.0245\u003c/em\u003e; \u003cstrong\u003eFigure 5\u003c/strong\u003e) as seen in \u003cstrong\u003eTable 2\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Visual and neuropsychological metrics in stunted and healthy matched controls\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"792\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 450px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 210px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 264px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrowth patterns\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStatistic, p-value, Effect size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStunted group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eVision measures\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003en = 275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003en = 15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eVisual acuity (OD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.08 \u0026plusmn; 0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.10 \u0026plusmn; 0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 1811.0, p = 0.420, r = -0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eVisual acuity (OS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.08 \u0026plusmn; 0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.06 \u0026plusmn; 0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 1690.5, p = 0.234, r = -0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eContrast sensitivity (OD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.53 \u0026plusmn; 0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.47 \u0026plusmn; 0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 1758.0, p = 0.338, r = -0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eContrast sensitivity (OS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.54 \u0026plusmn;0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.47 \u0026plusmn; 0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU =1794.0, p = 0.401, r = -0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eRefractive correction in spherical equivalence (OD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e-0.02 \u0026plusmn; 0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.00 \u0026plusmn; 0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 1991.50, p = 0.822, r = -0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eRefractive correction in spherical equivalence (OS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.00 \u0026plusmn;0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.05\u0026plusmn; 0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 2016.5, p = 0.884, r = -0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eMPOD fovea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.33 \u0026plusmn; 0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.20 \u0026plusmn; 0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 1594.50, p = 0.1400, r = -0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eFovea CFF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e18.16 \u0026plusmn; 3.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e17.05 \u0026plusmn; 4.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 1422.0, p = 0.475, r = -0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eParafovea CFF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e16.53 \u0026plusmn; 5.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e17.86 \u0026plusmn; 7.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 523.0, p = 0.294, r = -0.121\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003ePerifovea CFF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e22.61 \u0026plusmn; 5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e20.78 \u0026plusmn; 5.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 475.0, p = 0.217, r = -0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eNeuropsychological measures\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eDelayed Matching to Sample (n = 150)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003en = 141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003en = 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eDMS Accuracy Covert (0 seconds delays)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e70.64 \u0026plusmn; 25.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e77.78 \u0026plusmn; 32.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 493.5, p = 0.249, r = -0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eDMS Accuracy Covert (4 seconds delays)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e64.26 \u0026plusmn; 24.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e55.56 \u0026plusmn; 37.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 560.0, p = 0.544, r = -0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eDMS Accuracy Covert (12seconds delays)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e58.30 \u0026plusmn; 26.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e55.56 \u0026plusmn;37.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 617.5, p = 0.891, r = -0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eDMS Accuracy Covert (All seconds delays)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e64.39 \u0026plusmn; 18.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e63.11 \u0026plusmn; 29.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 576.5, p = 0.644, r = -0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eDMS Accuracy Overt (Simultaneous)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e91.21 \u0026plusmn; 14.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e88.89 \u0026plusmn; 10.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 523.000, p = 0.294, r = -0.121\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eDMS Probability of an error after an incorrect response \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.24 \u0026plusmn; 0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e0.33 \u0026plusmn; 0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 475.000, p = 0.217, r = -0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003ePaired Associates Learning ( n = 150)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003en = 141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003en = 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003ePAL Accurate (Correct recall of pattern location)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e11.20 \u0026plusmn; 4.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e9.44 \u0026plusmn; 4.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 486.0, p = 0.239, r = -0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003ePAL Total Errors (Number of times to incorrectly recall a pattern location)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e19.62 \u0026plusmn; 14.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e25.44 \u0026plusmn; 15.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 467.5, p = 0.186, r = -0.108\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eReaction Time (n = 150)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003en = 141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003en = 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eRTI Median Five-Choice Movement Time\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e300.45 \u0026plusmn; 55.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e290.167 \u0026plusmn; 68.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003et = 0.528, p = 0.599, g = 0.181\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eRTI Median Five-Choice Reaction Time\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e379.14 \u0026plusmn; 46.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e389.61 \u0026plusmn; 40.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003et = -0.659, p = 0.511, g = 0.227\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eRTI Simple Median Movement Time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e276.805 \u0026plusmn; 61.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e281.44 \u0026plusmn; 80.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003et = -0.215, p = 0.830, g = 0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eRTI Simple Median Reaction Time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e341.22 \u0026plusmn; 48.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e347.28 \u0026plusmn; 42.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 580.0, p = 0.669, r = -0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eStocking of Cambridge (n = 140)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003en = 131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003en = 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eSOC Initial Thinking Time Median (5 Moves)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e2473.25 \u0026plusmn; 3069.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e2405.00 \u0026plusmn; 2237.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 570.000, p = 0.868, r = -0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eSOC Mean Moves (5 Moves)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e8.2099 \u0026plusmn; 1.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e9.89 \u0026plusmn; 1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 287.50, p = 0.040, r = -0.0317\u0026Dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eSOC Subsequent Thinking Time Median (5 Moves)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e875.93 \u0026plusmn; 1352.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e2958.01 \u0026plusmn; 4781.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 373.000, p = 0.063, r = -0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eSpatial Working Memory \u0026nbsp; \u0026nbsp; (n = 150)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003en = 141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003en = 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eSWM Between Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e20.10 \u0026plusmn; 6.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e24.78 \u0026plusmn; 5.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 354.0, p = 0.0245, r = -0.182\u0026Dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eSWM Between errors 4 boxes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.20 \u0026plusmn; 1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e1.78 \u0026plusmn; 1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 493.0, p = 0.240, r = -0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eSWM Between errors 6 boxes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e5.84 \u0026plusmn; 3.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e7.11 \u0026plusmn; 2.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 535.5, p = 0.430, r = -0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003eSWM Between errors 8 boxes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e13.06 \u0026plusmn; 4.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e15.89 \u0026plusmn; 4.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 453.5, p = 0.150, r = -0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 318px;\"\u003e\n \u003cp\u003e\u0026nbsp;SWM Strategy (6-8 boxes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e9.13 \u0026plusmn; 1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e10.11 \u0026plusmn; 1.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 210px;\"\u003e\n \u003cp\u003eU = 456.0, p = 0.152, r = -0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026Dagger;, significant difference between groups. DMS: Delayed Matching to Sample assesses both simultaneous visual matching ability and short-term visual recognition memory, for non-verbalisable patterns; PAL:\u0026nbsp;Paired Associates Learning assesses visual memory and new learning; RTI: Reaction Time (RTI) provides assessments of motor and mental response speeds, as well as measures of movement time, reaction time, response accuracy and impulsivity; SOC: Stockings of Cambridge (SOC) is a test of spatial planning that requires individuals to use problem-solving strategies to match two sets of stimuli; SWM:\u0026nbsp;Spatial Working Memory requires retention and manipulation of visuospatial information. This self-ordered test has notable executive function demands and provides a measure of strategy as well as working memory errors. OD, Oculus dexter; OS, Oculus sinister; CFF, Critical Flicker Frequency; MPOD, Macular Pigment Optical Density; Statistical significance set at p\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStunting in children was significantly associated with deficits in spatial planning\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBivariate logistic regression showed significant deficits in SOC mean moves (OR = 1.70, \u003cem\u003ep\u003c/em\u003e = 0.010), SOC thinking time (OR = 1.00, \u003cem\u003ep\u003c/em\u003e = 0.019), and SWM errors (OR = 1.18, \u003cem\u003ep\u003c/em\u003e = 0.037) in stunted children. After adjustment, SOC mean moves remained significantly associated with stunting (AOR = 1.43, \u003cem\u003ep\u003c/em\u003e = 0.049) suggestive of significant impairment in spatial planning as seen in \u003cstrong\u003eTable 3\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Bivariate and multiple regression of factors associated with stunting\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"774\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 228px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBivariate regression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 216px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultiple regression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 48px;\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 108px;\"\u003e\n \u003cp\u003e95%CI\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54px;\"\u003e\n \u003cp\u003eAOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003e95%CI\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eBiographical characteristics\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSex\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.56 - 5.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.349\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eAge (y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.83 -1.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.269\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eAge group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003e8-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003e11-13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e2.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.70 - 9.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eMedical condition: no versus yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.38 - 8.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.471\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eNutrition measures\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eLutein (mg/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.62 - 1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eZeaxanthin (mg/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.00 - 339.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.860\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eLutein + Zeaxanthin (mg/d)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.62 - 1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.331\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eEgg consumption/week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.76 - 1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.904\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eVitamins IU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.10 - 1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eRetinol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.10 - 1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eZinc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.84 - 1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eIron\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.89 - 1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.264\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eCarbohydrates (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.99 - 1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eProteins (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.97 - 1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eLipids (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.97 - 1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eEnergy consumed in kcal\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.10 - \u0026nbsp;1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eDietary diversity score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.55 - 1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eVision measures\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eVisual acuity (OD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e9.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.05 - \u0026nbsp;19.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eVisual acuity (OS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.00 - \u0026nbsp;24.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.387\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eContrast sensitivity (OD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.02 - \u0026nbsp;2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eContrast sensitivity (OS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.02 - 2.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eRefractive correction in spherical equivalence (OD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.40 - 2.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.927\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eRefractive correction in spherical equivalence (OS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.47 - 2.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.749\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eMPOD fovea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.00 - 2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eFovea CFF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.79 - 1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eParafovea CFF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.95 - \u0026nbsp;1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003ePerifovea CFF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.82 - 1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eNeuropsychological measures\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eDelayed Matching to Sample (n = 150)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eDMS Accuracy Covert (0 seconds delays)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.98 - 1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.431\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eDMS Accuracy Covert (4 seconds delays)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.96 - 1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eDMS Accuracy Covert (12seconds delays)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.97 - 1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.766\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eDMS Accuracy Covert (All seconds delays)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.96 - 1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.843\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eDMS Accuracy Overt (Simultaneous)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.95 - 1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eDMS Probability of an error after an incorrect response\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e7.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.30 \u0026ndash; 18.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.222\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003ePaired Associates Learning ( n = 150)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003ePAL Accurate (Correct recall of pattern location)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.76 \u0026nbsp;- 1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003ePAL Total Errors (Number of times to incorrectly recall a pattern location)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.98 - \u0026nbsp;1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eReaction Time (n = 150)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eRTI Median Five-Choice Movement Time\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.98 - 1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.596\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eRTI Median Five-Choice Reaction Time\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.99 - \u0026nbsp;1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.509\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eRTI Simple Median Movement Time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.99 - 1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.828\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eRTI Simple Median Reaction Time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.99 - 1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eStocking of Cambridge (n = 140)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eSOC Initial Thinking Time Median (5 Moves)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e1.00 - 1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.947\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eSOC Mean Moves (5 Moves)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e1.14 - 2.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.010\u0026Dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e1.00 \u0026ndash; 2.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.049\u0026Dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eSOC Subsequent Thinking Time Median (5 Moves)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e1.00 - 1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.019\u0026Dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e1.00- 1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.825\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eSpatial Working Memory \u0026nbsp; \u0026nbsp; (n = 150)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eSWM Between Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e1.01 - 1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.037\u0026Dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e0.97-1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eSWM Between errors 4 boxes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.85 - 2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eSWM Between errors 6 boxes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.92 - 1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eSWM Between errors 8 boxes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.98 - 1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003e\u0026nbsp;SWM Strategy (6-8 boxes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e0.90 - 2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e0.148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eDMS: Delayed Matching to Sample assesses both simultaneous visual matching ability and short-term visual recognition memory, for non-verbalisable patterns; PAL: Paired Associates Learning assesses visual memory and new learning; RTI: Reaction Time (RTI) provides assessments of motor and mental response speeds, as well as measures of movement time, reaction time, response accuracy and impulsivity; SOC: Stockings of Cambridge (SOC) is a test of spatial planning that requires individuals to use problem-solving strategies to match two sets of stimuli; SWM: Spatial Working Memory requires retention and manipulation of visuospatial information. This self-ordered test has notable executive function demands and provides a measure of strategy as well as working memory errors. OD, Oculus dexter; OS, Oculus sinister; CFF, Critical Flicker Frequency; MPOD, Macular Pigment Optical Density; OR, Odds Ratio; AOR, Adjusted Odds Ratio; CI confidence interval; Bivariate logistic regression; p-value of p\u0026lt;0.05 considered for inclusion in the multivariate model; Statistical significance set at p \u0026le; 0.05; Statistical significance set at p\u0026lt;0.05.\u003c/p\u003e"},{"header":"Discussion ","content":"\u003cp\u003eStunting, a form of chronic undernutrition characterized by reduced height-for-age (see Figure 1), \u003cs\u003eis\u003c/s\u003e resulting from prolonged inadequate intake of energy, protein and essential micronutrients, often compounded by repeated infections and poor caregiving practices. \u0026nbsp;In preadolescent children, the brain and eyes are still developing and require an adequate nutrient supply for proper function [27]. Given the high sensitivity of the brain and the eyes to nutrient deficiency and the fact that stunting is a key indicator of chronic undernutrition, reflecting long-term nutritional deprivation[1, 2, 28, 29], we hypothesized that children with stunted growth would exhibit impaired neuroretinal and neuropsychological function deficits relative to their age-matched, well-nourished controls. \u0026nbsp;Consistent with our hypothesis, we observed a marked decline in both neuroretinal and neuropsychological function among the stunted group. Specifically, stunted children demonstrated clinically significant reductions in macular pigment optical density and critical flicker fusion frequency (Table 2), as well as statistically significant deficits in spatial planning and spatial working memory compared to healthy controls (Figure 4). Moreover, stunted children were more likely to experience impaired spatial planning compared to aged-matched controls (Table 4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn our study, children with stunting exhibited reduced neuroretinal function, as reflected by decreased MPOD and CFF compared to age-matched controls (Table 2). These findings suggest diminished brain and retinal carotenoid status [30, 31] and \u0026nbsp;as well as impaired temporal visual processing. MPOD and CFF typically increase with age in premature children, but are significantly impaired in those with retinopathy of prematurity [32-35]. This suggests a link between retinal maturation and the development of these neuroretinal parameters [32-35]. This highlights the value of MPOD and CFF as objective tools for diagnosing and monitoring chronic undernutrition, particularly in resource-limited settings with a high burden of undernutrition, and their potential for assessing neural health in affected children [36].\u003c/p\u003e\n\u003cp\u003eUnlike non-stunted children, children with stunting exhibited impaired spatial planning and spatial working memory. Our observation \u0026nbsp;corroborates with previous studies that demonstrated \u0026nbsp; the impact of stunting on critical cognitive systems such as visual working memory [37]. The poor neuropsychological performance may mechanistically be due to reduced engagement of the left anterior intraparietal sulcus (a region involved in maintaining visual working memory) and greater suppression in the right temporoparietal junction (a region involved in shifting attention) [37].\u003c/p\u003e\n\u003cp\u003eFurthermore, stunted children were more likely to show an increase in the mean number of SOC moves, which indicates impaired cognition, particularly with regard to spatial planning. The findings are similar to studies by Lestari \u003cem\u003eet al\u003c/em\u003e, that showed diminished neurocognitive performance in stunted relative to non-stunted Indonesian children\u0026nbsp;[38]\u0026nbsp;as well as Sanou and coworkers that showed\u0026nbsp;poorer neuro-psychological outcomes among children in rural Burkina Faso [39]. Collectively, the findings demonstrate the functional impact of stunting on brain health and underscore the need for comprehensive cognitive evaluation in children with chronic undernutrition.\u003c/p\u003e\n\u003cp\u003eThis study presents a novel report on the deficit in neuroretinal and neurocognitive function under stunted condition and unravel the diagnostic potential of MPOD and CFF as neuroretinal biomarker to monitor chronic undernutrition. However, there are some few limitations worth mentioning. The sample size for the stunted group was relatively small, which may limit the generalizability of the findings. Nonetheless, the inclusion of a larger control group enhanced statistical power and improved the robustness of detecting subtle differences between groups. The findings have broad implications at the intersection of nutrition, ophthalmology, and neuroscience, highlighting the need for a multidisciplinary approach to addressing stunting.\u003c/p\u003e"},{"header":"Conclusion ","content":"\u003cp\u003eThis study presents data that extend beyond dietary status to examine the influence of stunting on neuroretinal and neuropsychological performance. Overall, there was a declining trend in macronutrient and micronutrient intake, including the retinal and brain carotenoids lutein and zeaxanthin (Figure 2), accompanied by clinical deficits in neuroretinal function and significant impairments in cognitive performance (Table 2 and Figure 4). The sensitivity of macular pigment optical density (MPOD) and critical flicker frequency (CFF) in identifying stunting-related changes highlights their potential as diagnostic tools for monitoring neural health in chronic undernutrition. These findings collectively support the need for targeted nutritional interventions to help mitigate visual and cognitive deficits in children at risk of stunting. \u0026nbsp;\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAOR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAdjusted Odds Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eB.M.I.\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBody Mass Index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCANTAB\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCambridge Neuropsychological Test Automated Battery\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eC.F.F.\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCritical Flicker Frequency\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eContrast Sensitivity\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eD.M.S.\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDelayed Matching to Sample\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMPOD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMacular Pigment Optical Density\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eL\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eLutein\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eO.R.\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eOdds Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eP.A.L.\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePaired Associates Learning\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eR.T.I.\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRetention Time\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eS.O.C.\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eStock of Cambridge\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eS.W.M.\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSpatial Working Memory\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eZ\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eZeaxanthin.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the school authorities and staff for their cooperation, and the caregivers and students for their participation. We also acknowledge the research assistants for their support in data collection, and Dr. Emmanuel Asamoah Agyemang for providing the iPad used for the CANTAB\u0026trade; test. Special thanks to Cambridge Cognition for supplying the CANTAB\u0026trade; test battery, financial support for travel, and expert guidance in test administration. The authors appreciate the support of Bernice Lebene Tettey of the Department of Chemistry, College of Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana for assisting in the preparation of the figure for the study workflow.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eM.A.:\u003c/strong\u003e conceptualization, methodology, project management, resources, experimental design, data curation, data validation, investigation, software, formal analysis, formatting, writing review, and editing. \u003cstrong\u003eI.O.D.J.:\u003c/strong\u003e conceptualization, methodology, project management, resources, experimental design, data curation, data validation, prepared figures, investigation, software, formal analysis, formatting, writing original draft, writing review, and editing, correspondence. \u003cstrong\u003eD.A.O:\u003c/strong\u003e methodology, project management, resources, experimental design, data collection, investigation, software, writing review, and editing. \u003cstrong\u003eF.A.A.P:\u003c/strong\u003e methodology, project management, resources, experimental design, formal analysis, writing review, and editing. \u003cstrong\u003eW.O. A:\u003c/strong\u003e methodology, project management, resources, investigation, software, formal analysis, writing review, and editing. \u003cstrong\u003eN.A.S.A:\u003c/strong\u003e methodology, project management, resources, experimental design, data collection, investigation, software, writing review, and editing. \u003cstrong\u003eE.J.J:\u003c/strong\u003e methodology, resources, data curation, data validation, investigation, software, formal analysis, writing review and editing \u003cstrong\u003eS.A.A:\u003c/strong\u003e methodology, data curation, writing reviews and editing, \u003cstrong\u003eB.A.A:\u003c/strong\u003e methodology, data visualization, writing reviews and editing, \u003cstrong\u003eJ.A.B:\u003c/strong\u003e methodology, resources, data collection, writing reviews and editing, \u003cstrong\u003eP.A.S.A:\u003c/strong\u003e methodology, writing original draft, writing reviews and editing. \u003cstrong\u003eK.O.A:\u003c/strong\u003e conceptualization, methodology, project management, resources, experimental design, data curation, data validation, investigation, software, formal analysis, writing review, and editing, supervision, correspondence.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported in part by a primary research award to N.A.S.A. from Cambridge Cognition. The CANTAB\u0026trade; research grant included a CANTAB\u0026trade; Connect license for 150 assessments, funding for site visits, and expert training in test administration. Cambridge Cognition had no role in the design, conduct, or interpretation of the study data. K.O.A. received the George Britton Early Investigator of the Year Award 2022 from the Brain and Ocular Nutrition (BON) Conference, which provided partial funding; BON likewise had no role in the study\u0026rsquo;s design, conduct, or data interpretation. K.O.A. also received partial funding through a Small Research Grant from Volunteer Optometric Services to Humanity (VOSH) International, which supported logistics and travel. VOSH had no role in the design, conduct, or interpretation of the study findings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll relevant data and materials supporting the conclusion of this article is/are available within\u003c/p\u003e\n\u003cp\u003ethe manuscript and its supporting information files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical consideration\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWritten approval was obtained from school principals, and informed consent was secured from caregivers after explaining the study protocol. The Committee on Human Research Publication and Ethics at Kwame Nkrumah University of Science and Technology (CHRPE/AP/477/22) formally approved the study. All procedures adhered strictly to the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare no competing interests.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBourre J-M: \u003cstrong\u003eEffects of nutrients (in food) on the structure and function of the nervous system: update on dietary requirements for brain. Part 1: micronutrients\u003c/strong\u003e. \u003cem\u003eJournal of nutrition health and aging\u0026nbsp;\u003c/em\u003e2006, \u003cstrong\u003e10\u003c/strong\u003e(5):377.\u003c/li\u003e\n \u003cli\u003eBourre J-M: \u003cstrong\u003eEffects of nutrients (in food) on the structure and function of the nervous system: update on dietary requirements for brain. Part 2: macronutrients\u003c/strong\u003e. \u003cem\u003eJournal of Nutrition Health and Aging\u0026nbsp;\u003c/em\u003e2006, \u003cstrong\u003e10\u003c/strong\u003e(5):386.\u003c/li\u003e\n \u003cli\u003eBartlett HE, Eperjesi F: \u003cstrong\u003eA randomised controlled trial investigating the effect of lutein and antioxidant dietary supplementation on visual function in healthy eyes\u003c/strong\u003e. \u003cem\u003eClinical Nutrition\u0026nbsp;\u003c/em\u003e2008, \u003cstrong\u003e27\u003c/strong\u003e(2):218-227.\u003c/li\u003e\n \u003cli\u003eChew EY, Clemons TE, Agr\u0026oacute;n E, Launer LJ, Grodstein F, Bernstein PS, Group A-REDSR: \u003cstrong\u003eEffect of omega-3 fatty acids, lutein/zeaxanthin, or other nutrient supplementation on cognitive function: the AREDS2 randomized clinical trial\u003c/strong\u003e. \u003cem\u003eJama\u0026nbsp;\u003c/em\u003e2015, \u003cstrong\u003e314\u003c/strong\u003e(8):791-801.\u003c/li\u003e\n \u003cli\u003eEttinger S: 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\u003cstrong\u003e30\u003c/strong\u003e(3):188-203.\u003c/li\u003e\n \u003cli\u003eVishwanathan R, Schalch W, Johnson EJ: \u003cstrong\u003eMacular pigment carotenoids in the retina and occipital cortex are related in humans\u003c/strong\u003e. \u003cem\u003eNutritional neuroscience\u0026nbsp;\u003c/em\u003e2016, \u003cstrong\u003e19\u003c/strong\u003e(3):95-101.\u003c/li\u003e\n \u003cli\u003eVishwanathan R, Neuringer M, Snodderly DM, Schalch W, Johnson EJ: \u003cstrong\u003eMacular lutein and zeaxanthin are related to brain lutein and zeaxanthin in primates\u003c/strong\u003e. \u003cem\u003eNutritional neuroscience\u0026nbsp;\u003c/em\u003e2013, \u003cstrong\u003e16\u003c/strong\u003e(1):21-29.\u003c/li\u003e\n \u003cli\u003eMcCulloch DL, Mactier H, Hamilton R: \u003cstrong\u003eFull-field flicker electroretinograms in preterm infants at risk of retinopathy of prematurity (ROP)\u003c/strong\u003e. \u003cem\u003eInvestigative Ophthalmology \u0026amp; Visual 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trends in infant temporal processing speed\u003c/strong\u003e. \u003cem\u003eVision Research\u0026nbsp;\u003c/em\u003e2017, \u003cstrong\u003e138\u003c/strong\u003e:71-77.\u003c/li\u003e\n \u003cli\u003eNagai N, Asato T, Minami S, Suzuki M, Shinoda H, Kurihara T, Sonobe H, Watanabe K, Uchida A, Ban N: \u003cstrong\u003eCorrelation between macular pigment optical density and neural thickness and volume of the retina\u003c/strong\u003e. \u003cem\u003eNutrients\u0026nbsp;\u003c/em\u003e2020, \u003cstrong\u003e12\u003c/strong\u003e(4):888.\u003c/li\u003e\n \u003cli\u003eWijeakumar S, Forbes SH, Magnotta VA, Deoni S, Jackson K, Singh VP, Tiwari M, Kumar A, Spencer JP: \u003cstrong\u003eStunting in infancy is associated with atypical activation of working memory and attention networks\u003c/strong\u003e. \u003cem\u003eNature human behaviour\u0026nbsp;\u003c/em\u003e2023, \u003cstrong\u003e7\u003c/strong\u003e(12):2199-2211.\u003c/li\u003e\n \u003cli\u003eLestari E, Siregar A, Hidayat AK, Yusuf AA: \u003cstrong\u003eStunting and its association with education and cognitive outcomes in adulthood: A longitudinal study in Indonesia\u003c/strong\u003e. \u003cem\u003ePlos one\u0026nbsp;\u003c/em\u003e2024, \u003cstrong\u003e19\u003c/strong\u003e(5):e0295380.\u003c/li\u003e\n \u003cli\u003eSanou AS, Diallo AH, Holding P, Nankabirwa V, Engebretsen IMS, Ndeezi G, Tumwine JK, Meda N, Tyllesk\u0026auml;r T, Kashala-Abotnes E: \u003cstrong\u003eAssociation between stunting and neuro-psychological outcomes among children in Burkina Faso, West Africa\u003c/strong\u003e. \u003cem\u003eChild and adolescent psychiatry and mental health\u0026nbsp;\u003c/em\u003e2018, \u003cstrong\u003e12\u003c/strong\u003e:1-10.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 4","content":"\u003cp\u003eTable 4 is not available with this version.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"chronic malnutrition, neuroretinal impairment, cognitive impairment, macular pigment optical density, critical flicker frequency, spatial planning, spatial working memory","lastPublishedDoi":"10.21203/rs.3.rs-6908758/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6908758/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiven the brain and eyes high sensitivity to nutrient deficiency, and stunting as a marker of chronic malnutrition, we hypothesized that children with stunted growth would show impaired neuroretinal and neuropsychological function compared to age-matched-well-nourished controls. This study examined the link between nutritional status, visual function, and cognitive performance in preadolescent children with stunted growth, aiming to identify early markers of malnutrition-related developmental risk.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFifteen stunted and 275 non-stunted children (ages 8–13) were assessed using dietary recall, visual tests (ETDRS LogMAR, Pelli-Robson, heterochromatic flicker photometry), and CANTAB neuropsychological assessments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStunted children consumed fewer macro- and micronutrients, including lutein and zeaxanthin, and showed reduced macular pigment optical density (MPOD) and critical flicker frequency (CFF). Cognitive testing revealed significant impairments in spatial planning, problem-solving, and visuospatial working memory. After adjusting for confounders, stunted children were more likely to show poor spatial planning on the Stockings of Cambridge (SOC) task (AOR = 1.43, 95% CI: 1.00–2.66; p = 0.049).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThese results suggest that stunting is associated with both neuroretinal and neurocognitive deficits. The findings underscore the value of visual and cognitive biomarkers in detecting early functional effects of stunting and the critical need for timely nutritional interventions in at-risk children.\u003c/p\u003e","manuscriptTitle":"Neuroretinal and neuropsychological functional deficit in preadolescent children with stunted growth","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-25 06:20:13","doi":"10.21203/rs.3.rs-6908758/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"256189291661815930351898914784677534318","date":"2025-07-21T00:30:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-20T19:49:18+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-06-24T07:17:19+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-23T12:24:57+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-23T12:23:38+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pediatrics","date":"2025-06-16T22:19:51+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9ebcef00-af65-4908-be8d-47ecbc355298","owner":[],"postedDate":"July 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-07-25T06:20:13+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-25 06:20:13","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6908758","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6908758","identity":"rs-6908758","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}