Abstract
Introduction
This study examined the association between sugar-sweetened beverage consumption before the first 24 months of life and attention-deficit/hyperactivity disorder (ADHD).
Methods
A population administrative cohort study was conducted in Korea (2008–2019) using linked national insurance data and a health screening survey. The cohort included 25,305 children in the exposed group with high sugar-sweetened beverage drinks (≥200 mL) and 339,931 in the reference groups (<200 mL) at 24 months of age. The primary outcome was the development of ADHD based on the International Classification of Disease (ICD) codes. Cox proportional model was used to identify the association between sugar-sweetened beverage consumption during early childhood and the later development of ADHD while controlling for multiple risk factors.
Results
Over a mean follow-up period of 9.2 years, the incidence rates of ADHD were 29.6 and 23.8 per 10,000 person-years in the exposed and reference groups, respectively. Compared with the reference group, children consuming high-sugar drinks were at an increased risk of ADHD (adjusted hazard ratio 1.17, 95% confidence interval [CI] 1.08–1.27). These associations remained significant even after applying alternative ADHD definitions or adjusting for confounding variables.
Conclusion
Children who consume sweetened beverages during early childhood are at increased risk of developing ADHD later in life.
Keywords: Sugar-sweetened beverage, Attention-deficit/hyperactivity disorder, Children
Introduction
Attention-deficit/hyperactivity disorder (ADHD) stands as one of the most prevalent neurodevelopmental disorders globally, affecting approximately 3.4% of children, with estimates ranging from 2.6 to 4.5% [1]. Typically emerging during childhood, ADHD interferes with various aspects of functioning and development, leading to adverse academic, social, and economic outcomes [2]. Despite its prevalence, the precise etiology of ADHD remains complex and not fully elucidated. Recognized as a condition with high heritability, numerous environmental factors have been identified as potential influencers of its onset and severity. These factors include perinatal risks such as premature birth, low birth weight, exposure to environmental pollutants, and dietary impacts [2–4].
The roles of nutrition and diet as environmental factors in ADHD have garnered significant attention; however, the impact of diet on ADHD remains a topic of debate. Both Western dietary patterns (characterized by high levels of saturated fats, refined sugars, and sodium) [5] and industrial food products, such as snacks and sugar-sweetened beverages [6–8] have been associated with ADHD. A study involving children aged 3–6 years in China revealed that a diet high in processed foods and snacks was associated with a 1.6–1.8 times higher risk of ADHD [9]. Moreover, meta-analyses of children and adolescents have indicated that the consumption of saturated fats and refined sugars is linked to an increased risk of ADHD [10, 11]. However, some studies have reported no significant association between sugar intake and ADHD among school-aged children (6–11 years) [12] and adults [13].
Sugar-sweetened beverages, a major source of added sugars in the diet, have witnessed an increase in consumption among children aged 1–5 years in South Korea. A birth cohort study conducted in Korea revealed that children who consumed a significant amount of sweet foods at age 4 were at a higher risk of displaying ADHD symptoms by age 6 [14]. The early childhood phase, from birth to 2 years of age, is considered crucial for cognitive and behavioral development [15, 16]. Therefore, investigating the relationship between diet, specifically the intake of sugar-sweetened beverages, and ADHD in children aged 18–24 months within a nationwide administrative cohort in Korea is essential. Additionally, this study aims to undertake stratified analyses to pinpoint potential modifying factors.
Materials and Methods
Study Design and Database: National Investigation of Birth Cohort in Korea Study
This was an administrative observational cohort analysis utilizing data from the Korean National Health Insurance System (NHIS) and the National Health Screening Program for Infants and Children (NHSPIC). It targets children born in Korea between January 1, 2008, and December 31, 2010, with follow-up data available up to December 31, 2018. The NHIS operates as a single insurer and provides a nationally representative database encompassing nearly the entire Korean population. It compiles comprehensive medical records for all individuals in Korea, including sociodemographic details (age, sex, and economic status) and healthcare information (International Classification of Diseases, 10th revision [ICD-10] codes, drug prescriptions, and frequency of hospital visits).
Furthermore, the NHSPIC offers seven assessment rounds for children aged 4–72 months, including a general health questionnaire, developmental screening, an oral health questionnaire and examination, anthropometric measurements, a physical examination, and age-specific anticipatory guidance. A more detailed description of these components can be found in the referenced literature [17].
Study Population
In this study, we analyzed a cohort of 1,413,994 children born in Korea between 2008 and 2010. The main cohort included children who met the following criteria: (1) underwent the 1st (at 4–6 months of age) and 3rd (at 18–24 months of age) examinations of the NHSPIC, with accessible data from both examinations (n = 738,091 and 799,909, respectively) and (2) had accurately recorded birth weights (n = 1,301,213). To minimize the influence of potential risk factors or confounders on ADHD development, we focused on healthy children and excluded those with central nervous system (CNS) diseases or other significant birth complications. The exclusion criteria were as follows: (1) death (n = 4,187); (2) birth weight below 2.5 kg or above 4 kg (n = 111,989); (3) multiple births (n = 11,137); (4) preterm births (n = 49,880); (5) ICU hospitalization for >4 days (n = 50,060); (6) general anesthesia before 1 year of age (n = 23,599); (7) diagnosed perinatal disorders related to length of gestation and fetal growth (n = 58,620), birth trauma (n = 12,955), newborn convulsions/disturbances of cerebral status (n = 5,419), or congenital malformations/chromosomal abnormalities (n = 187,547); (8) diagnosed diseases of the CNS, including inflammatory CNS diseases (n = 58,698 children), systemic atrophies primarily affecting the CNS/extrapyramidal and movement disorders (n = 6,597), demyelinating CNS diseases (n = 984), cerebral palsy (n = 8,479), or other nervous system disorders (n = 10,971); or (9) diagnosed mental and behavioral disorders before sugar-sweetened beverage consumption survey (n = 6,936). Online supplementary Table 1 (for all online suppl. material, see https://doi.org/10.1159/000539458) presents the diagnostic categories identified using ICD-10 codes. Finally, 365,236 children met the inclusion criteria for the main cohort (shown in Fig. 1).
Fig. 1.
Study participants in the main cohort.
For sensitivity analysis, additional cohorts were defined as cohorts 2 and 3 (shown in online suppl. sFig. 1). Cohort 2, which included 516,808 children, did not apply the main cohort’s exclusion criteria related to birth history, perinatal and CNS diseases, and hospital usage history and thus included a broader participant base. Cohort 3 investigated the relationship between changes in sugar-sweetened beverage consumption from 18–24 to 30–36 months of age and ADHD. This cohort included children who underwent the NHSPICs 4th examination (867,077 children) following the same inclusion criteria as in cohort 2, resulting in a total of 401,897 children being enrolled in cohort 3.
Exposure: Daily Sugar-Sweetened Beverage Consumption
The primary exposure of interest was daily sugar-sweetened beverage consumption, which was assessed in the 3rd round of the NHSPIC at 18–24 months of age. Through a self-administered general health questionnaire, parents recorded their children’s intake of fruit juices and sugary drinks such as soft drinks. They responded to the question, “How much fruit juice or sugary drinks does your child consume per day?” with the following options: (1) less than 200 mL (approximately one cup); (2) 200 mL to less than 500 mL; and (3) 500 mL or more. Due to the low number of responses for consumption of over 500 mL, the children in the main cohort were classified into two groups: the reference (or low consumption) group, consisting of children who consumed less than 200 mL of sugary drinks per day (n = 339,931) and the high consumption group, which included children consuming 200 mL or more per day (n = 25,305).
Furthermore, to investigate the potential link between changes in sugar-sweetened beverage consumption and ADHD in cohort 3, children were categorized into four distinct groups based on their reported intake at 18–24 months and 30–36 months: (1) low-to-low, for those with less than 200 mL consumption at both intervals; (2) low-to-high, for consumption increasing from less than 200 mL to more than 200 mL; (3) high-to-low, for those with a decrease in consumption from more than 200 mL to less than 200 mL; and (4) high-to-high, for children who consistently consumed more than 200 mL at both time points.
Outcomes: ADHD
The outcome of interest was the incidence of ADHD, which was predetermined. ADHD diagnosis was determined based on the ICD-10 code, with a child considered to have ADHD if they received at least one of the ICD-10 codes (F90.0, F90.1, F90.8, and F90.9) as either a primary or secondary diagnosis.
Considering that pre-school-aged children may display behaviors typical of their developmental stages, such as distractibility or high activity levels, the diagnosis of ADHD in this age group can be complex and nuanced. Consequently, to mitigate the diagnostic ambiguity associated with identifying ADHD before the age of six, we adopted alternative definitions for patients diagnosed after the age of six. Specifically, “ADHD after 6 years of age” was categorized as receiving a primary diagnosis of ADHD beyond the age of six. Additionally, “broad ADHD after 6 years of age” was defined as receiving either a primary or secondary diagnosis of ADHD after 6 years of age. This approach aims to ensure a more accurate identification of ADHD cases by accounting for the developmental context of the symptoms.
Covariates
The study collected various demographic and health-related data from the NHIS database, including sex (male or female), birth region, economic status, birth calendar year, and hospital utilization. Birth regions were categorized into Seoul/metropolitan areas, cities, and rural areas. Economic status was assessed based on insurance copayment amounts, ranked from 1 to 20, with 1 representing the lowest and 20 the highest economic status. This ranking was divided into three categories: low (1–5), medium (6–15), and high (16–20).
The critical health and developmental indicators were obtained from the NHSPIC database. This included birth weight as well as body weight and height measurements taken during early infancy and at 18–24 and 30–36 months of age. Additionally, the types of feeding during early infancy (exclusively breast milk, exclusively formula milk, mixed milk, or others) were recorded. Parents provided information on birth weight and feeding type during the first NHSPIC assessment at 4–6 months of age, whereas physicians conducted and recorded physical measurements at later stages. Body mass index (BMI) was calculated using the following formula: weight in kilograms divided by the square of height in meters. The study defined overweight as a BMI-for-age z-score of ≥1.036 but <1.645, and obesity as a BMI-for-age z-score of ≥1.645, following standardized growth chart guidelines. This comprehensive collection of data allowed for a nuanced analysis of the potential relationships between these variables and ADHD development in the cohort.
Statistical Analysis
To present the general characteristics of the study, continuous variables were described using means and standard deviations (SDs), whereas categorical variables were detailed as counts and percentages based on the categorized groups according to daily sugar-sweetened beverage consumption. The incidence of ADHD was calculated as the total number of new ADHD cases per 10,000 person years (PYs) of observation. Absolute rate differences and 95% confidence intervals (CIs) were derived from a binomial regression model using a log-link function.
To assess the relationship between sugar-sweetened beverage intake and the risk of developing ADHD, we used a Cox proportional hazard model. This model provided hazard ratios (HRs) and 95% CIs adjusted for various covariates, including sex, birth weight, BMI at 18–24 months, type of feeding during early infancy, birth region, economic status, and calendar year of birth. The follow-up period for each participant started 1 year after they completed the questionnaire on sugar-sweetened beverage consumption and continued until the occurrence of ADHD, death, or the study’s conclusion on December 31, 2018, whichever came first. Implementing a 1-year window before the follow-up period aimed to mitigate the potential for reverse causality and concerns regarding surveillance bias. The validity of the proportional hazards assumption was confirmed using the Schoenfeld residual test. Furthermore, we examined potential effect modifiers by incorporating an interaction term into the model to assess the impact of sugary drink consumption across different subgroups based on sex, birth weight, BMI at 2 years, birth calendar year, birth region, economic status, and early infancy feeding type. All statistical analyses were performed using SAS software (version 9.4, SAS Institute), with the threshold for statistical significance set at a two-sided p value of less than 0.05.
Results
General Characteristics
In the studied cohort, 6.9% of children (n = 25,305) were categorized into the high sugary drink group, defined by their consumption of ≥200 mL of sugar-sweetened beverages daily. Table 1 presents the overall characteristics of the children in the main cohort. The mean follow-up times of the children in the reference group and high sugary drinks group were 9.29 years (SD: 0.95) and 9.23 years (SD: 0.96), respectively. The high-sugar drink group had a higher percentage of boys (n = 13,242; 52.3%) compared to the reference group (n = 168,345; 49.5%). Additionally, children in the high-sugar drink group were more likely to be classified as obese (9.1% vs. 8.0%) or overweight (15.1% vs. 14.6%) at 18–24 months of age. These children were more frequently born in rural areas (7.6% vs. 6.6%) and had a higher incidence of hospitalization for any reason during early childhood (37.1% vs. 33.3%). Furthermore, the proportion of children who were exclusively breastfed was lower in the high-sugar group (43.4%) than in the reference group (46.3%).
Table 1.
Demographic and clinical characteristics
| Reference groupa (n = 339,931) | High sugary drinks groupb (n = 25,305) | |
|---|---|---|
| Sex, n (%) | ||
| Boy | 168,345 (49.52) | 13,242 (52.33) |
| Girl | 171,589 (50.48) | 12,063 (47.67) |
| Follow-up periodc, mean (SD), years | 9.29 (0.95) | 9.23 (0.96) |
| Birth weightd, mean (SD), kg | 3.23 (0.33) | 3.24 (0.33) |
| >3.2 kg (as a median value), n (%) | 199,975 (58.83) | 15,355 (60.68) |
| ≤3.2 kg, n (%) | 139,956 (41.17) | 9,950 (39.32) |
| Z score of BMI at age 18–24 monthse, mean (SD) | 0.33 (0.96) | 0.37 (0.99) |
| Obesity (1.645≤), n (%) | 27,321 (8.04) | 2,296 (9.07) |
| Overweight (1.036≤ and <1.645), n (%) | 49,456 (14.55) | 3,813 (15.07) |
| Normal (<1.036), n (%) | 261,841 (77.03) | 19,058 (75.31) |
| Region at birth, n (%) | ||
| Seoul/Metropolitan | 157,889 (46.45) | 11,224 (44.35) |
| City | 156,532 (46.05) | 11,874 (46.92) |
| Rural | 22,585 (6.64) | 1,928 (7.62) |
| Economic statusf, n (%) | ||
| Low | 34,065 (10.02) | 2,993 (11.83) |
| Middle | 213,206 (62.72) | 16,138 (63.77) |
| High | 79,969 (23.53) | 5,171 (20.43) |
| By calendar year at birth date, n (%) | ||
| 2008 | 98,273 (28.91) | 6,958 (27.50) |
| 2009 | 109,215 (32.13) | 7,829 (30.94) |
| 2010 | 132,443 (38.96) | 10,518 (41.56) |
| Feeding type during early infancyd, n (%) | ||
| Breastmilk only | 157,275 (46.27) | 10,985 (43.41) |
| Formula milk only | 113,185 (33.30) | 9,086 (35.91) |
| Mixed | 66,839 (19.66) | 5,019 (19.83) |
| The other | 1,374 (0.4) | 122 (0.48) |
| Hospitalizations for all causes from 1 month to 2 years of age, n (%) | ||
| No | 226,611 (66.66) | 15,918 (62.90) |
| Yes | 113,320 (33.34) | 9,387 (37.10) |
| Number of outpatient clinic visit for all causes from 1 month to 2 years of age, mean (SD) | 61.0 (32.5) | 61.1 (32.6) |
| <56 (as a median value), n (%) | 169,375 (49.83) | 12,604 (49.81) |
| ≥56, n (%) | 170,556 (50.17) | 12,701 (50.19) |
n, number; SD, standard deviation.
aChildren who drink less than 200 mL of sugar-sweetened beverage per day at 18–24 months of age from the questionnaire of 3rd round of National Health Screening Program for Infants and Children.
bChildren who drink 200 mL or more of sugar-sweetened beverage per day at 18–24 months of age from the questionnaire of 3rd round of National Health Screening Program for Infants and Children.
cThe follow-up was started from 1 year after the date of answering the questionnaire about the sugar-sweetened beverage consumption to ended until the outcomes occurred, died, or 2018, whatever happened first.
dObtained from the 1st round of the National Health Screening Program of Infants and Children at 4–6 months of age.
eMeasured at the 3rd round of National Health Screening Program for Infants and Children at age 18–24 months.
fEconomic status was determined by the amount of insurance co-payment, and ranged from 1 to 20 (highest), and divided into three (1–5: low, 6–15: middle, and 16–20: high).
Association between Daily Sugar-Sweetened Beverage Consumption before 2 Years of Age and Later ADHD
Table 2 shows the relationship between sugar-sweetened beverage consumption during early childhood and the subsequent risk of ADHD. The findings demonstrated a higher incidence rate of ADHD among children in the high-sugary drink group (29.6/10, 000 PY) compared to 23.8 cases per 10,000 PY in the reference group. This difference translated into an absolute rate difference of 5.77 (95% CI: 3.49–8.04). Children who consumed more than 200 mL of sugar-sweetened beverages daily before the age of 2 showed a significantly increased risk of ADHD, with an adjusted HR (aHR) of 1.17 (95% CI: 1.08–1.27), compared to those who consumed less. The study also explored the relationship between sugar-sweetened beverage intake and ADHD using alternative definitions, specifically ADHD after 6 years of age and broad ADHD after 6 years of age. The associations remained consistent, indicating an elevated risk of ADHD (aHR [95% CI]: 1.20 [1.10–1.30] and 1.20 [1.09–1.31], respectively) in children with high sugar-sweetened beverage consumption. Further analysis in cohort 2, which included a broader set of children with various birth histories, perinatal diseases, or CNS diseases, reaffirmed the association between early consumption of sugar-sweetened beverages and an increased risk of ADHD, with an aHR of 1.17 (95% CI: 1.09–1.24) (shown in Fig. 2).
Table 2.
The risk of the consumption of sugary drinks on ADHD
| Reference groupa (n = 339,931) | High sugary drinks groupb (n = 25,305) | Absolute RD/10,000 PY (95% CI) | Adjusted HR (95% CI)c | |||||
|---|---|---|---|---|---|---|---|---|
| events | n of accumulated 10,000 PY | incidence rate/10,000 PY | events | n of accumulated 10,000 PY | incidence rate/10,000 PY | |||
| ADHDd | 7,527 | 315.9 | 23.8 | 691 | 23.4 | 29.6 | 5.77 (3.49–8.04) | 1.17 (1.08–1.27) |
| Sensitivity analysis by using alternative definitions | ||||||||
| ADHD after 6 yearse | 6,754 | 316.4 | 21.4 | 631 | 23.4 | 27.0 | 5.63 (3.46–7.79) | 1.20 (1.10–1.30) |
| Broad ADHD after 6 yearsf | 5,552 | 316.6 | 17.5 | 513 | 23.4 | 22.0 | 4.51 (2.55–6.46) | 1.20 (1.09–1.31) |
n, number; PY, person-year; RD, risk difference; CI, confidence interval; HR, hazard ratio; ADHD, attention deficit hyperactive disorder.
aChildren who drink less than 200 mL of sugar-sweetened beverage per day at 18–24 months of age from the questionnaire of 3rd round of National Health Screening Program for Infants and Children.
bChildren who drink 200 mL or more of sugar-sweetened beverage per day at 18–24 months of age from the questionnaire of 3rd round of National Health Screening Program for Infants and Children.
cHRs and their 95% CIs were calculated by a Cox proportional model, adjusting for sex, birthweight, the status of BMI at 2 years of age, feeding type during early infancy, region at birth, economic status, and birth years.
dADHD was defined with at least one of the ICD-10 codes (F90.0, F90.1, F90.8, and F90.9) for the main diagnosis or sub-diagnosis.
eADHD after 6 years was defined with a main diagnosis with ADHD after 6 years of age.
fBroad ADHD after 6 years was defined when a child had a main or sub diagnosis of ADHD after 6 years’ old.
Fig. 2.
Risk of ADHD in the sensitivity analyses of the cohort 2 and cohort 3. Cohort 2 was set up without the exception of birth history, presence of perinatal diseases and CNS diseases, and history of hospital use in the main cohort, thus it included more children (n = 516,808) than in the main cohort. Cohort 3 (n = 401,897) was set up to assess the associations between the change in sugar-sweetened beverage consumption from 18–24 to 30–36 months of age and ADHD. In cohort 2, the reference group (n = 480,898) included children who drink less than 200 mL of fruit juices or sugary drinks per day and the high sugary drinks group (n = 35,910) included those who drink 200 mL or more than 200 mL of fruit juices or sugary drinks per day. In cohort 3, children were divided into four combinations based on the consumption of daily sugar-sweetened beverages (low [less than 200 mL] vs. high [200 mL or over]) from 18–24 to 30–36 months of age: (1) low to low (n = 29,441), (2) low to high (n = 345,103), (3) high to low (n = 1,911), and (4) high to high (n = 25,442). ADHD was defined with at least one of the ICD-10 codes (F90.0, F90.1, F90.8, and F90.9) for the main diagnosis or sub-diagnosis. The HRs of ADHD and their 95% CIs were calculated by using a Cox proportional hazard model, adjusted for sex, birthweight, the status of BMI at 2 years of age, feeding type during early infancy, region at birth, economic status, and birth years.
Additionally, this study investigated potential modifiers of the relationship between sugar-sweetened beverage intake and ADHD, including sex, birth weight, BMI at 2 years, birth calendar year, birth region, economic status, early infancy feeding type, and healthcare utilization during early childhood. No significant interaction effects were found (all p for interaction >0.05), suggesting that the association between sugar-sweetened beverage consumption and ADHD risk was consistent across subgroups (shown in Fig. 3).
Fig. 3.
Risk of ADHD stratified into participants’ demographic or clinical characteristics. ADHD was defined with at least one of the ICD-10 codes (F90.0, F90.1, F90.8, and F90.9) for the main diagnosis or sub-diagnosis. BMI status was divided based on the BMI for age z score. Overweight was defined as 1.036 or over and less than 1.645, and obesity was defined as 1.645 or over. The data about feeding type during early infancy was obtained from the parents-answered questionnaires of the 1st round of the National Health Screening Program of Infants and Children at their child’s age 4–6 months. The HRs of ADHD and their 95% CIs were calculated by using a Cox proportional hazard model, adjusted for sex, birthweight, the status of BMI at 2 years of age, feeding type during early infancy, region at birth, economic status, and birth years.
Risk of ADHD with the Change in Daily Sugar-Sweetened Beverage Consumption from 2 to 3 Years of Age
In cohort 3, compared to the groups of children who consumed less than 200 mL/day of sugar-sweetened beverages at 2 years of age (both the low-to-low and low-to-high groups), the group of children who consistently consumed 200 mL/day or more of sugar-sweetened beverages from ages 2 to 3 years (the high-to-high group) exhibited an increased risk of ADHD. The aHR for this group was 1.14 (95% CI: 1.05–1.23), indicating a statistically significant association between sustained high intake of sugar-sweetened beverages and the risk of developing ADHD (shown in Fig. 2).
Discussion
This nationwide administrative cohort study aimed to investigate the association between the consumption of sugar-sweetened beverages in early childhood and subsequent ADHD development, with a mean follow-up period of approximately 9 years. The findings indicated a significant association between sugar-sweetened beverage intake, evaluated at 18–24 months of age, and an increased risk of ADHD. This association persisted even after adjusting for confounding variables and remained significant across alternative definitions of ADHD, specifically for diagnoses established after age 6. Additionally, stratification analyses did not reveal any factors that modified the effect of sugar-sweetened beverage consumption on the risk of ADHD. This suggests that the association between the early consumption of sugar-sweetened beverages and ADHD is notable, underscoring the potential impact of dietary choices in early childhood on later neurodevelopmental outcomes.
Our study identified a correlation between increased intake of sugar-sweetened beverages and a higher risk of ADHD, consistent with the findings of previous research. A cross-sectional study in the USA involving middle school students with an average age of 12 years revealed that frequent consumption of high-sugar beverages was associated with a 14% higher risk of ADHD [18]. Similarly, a case-control study in Spain indicated that high consumption of sugar-sweetened beverages, such as colas or soft drinks, elevated the risk of ADHD by 3.5–3.9 times in children and adolescents aged 6–16 years [19]. A study involving Chinese children aged 6–12 years suggested a dose-response relationship between the frequency of sugar-sweetened beverage intake and ADHD risk, and a positive correlation between sugar-sweetened beverage consumption and ADHD risk [20]. Furthermore, a recent systematic review and meta-analysis reported a significant positive association between overall sugar intake, sugar-sweetened beverages and ADHD symptoms, with subgroup analysis indicating a 1.8-fold increase in the odds of ADHD symptoms associated with high sugar-sweetened beverage intake compared with the lowest intake groups [21]. However, several studies have reported conflicting results. For instance, a birth cohort study in Brazil found no association between high sugar-sweetened beverage intake and ADHD in children aged 6–11 years [12]. Additionally, a cross-sectional study involving 107 Korean children did not find a significant association between sugar intake and ADHD [22]. These discrepancies highlight the complexity of the relationship between dietary sugar and ADHD and emphasize the necessity for further research to elucidate these associations.
Several studies have investigated the association between ADHD and sugar intake, not only from sugary drinks but also through the consumption of processed snacks and other foods containing sugar. In a systematic review, healthy dietary patterns (characterized predominantly by foods of plant origin and sources of vitamins and minerals) were protective against ADHD, whereas unhealthy dietary patterns (processed food, sources of saturated or hydrogenated fat, low-quality sugars, and chemical additives) were associated with a 1.4 fold increased risk of ADHD [23]. Additionally, a sweet dietary pattern (high intake of snacks, chocolate, sweet drinks, and ice cream) in Korean children aged 4 years was associated with a higher risk of ADHD symptoms [14].
While previous studies on dietary factors and ADHD have primarily focused on children aged 4 years and older or adolescents, this study delves into the association between the intake of sugar-sweetened beverages during the first 2 years of life and ADHD in children. Investigating dietary factors preceding clinical ADHD during the initial 12–24 months of life represents a relatively unexplored area of research. Given that neurodevelopmental processes commence during pregnancy and continue throughout infancy [24], evaluating dietary habits during infancy is crucial. A Japanese study revealed that infants aged between 41 and 49 months who consumed higher amounts of sugar-sweetened beverages tended to increase their consumption of confectioneries and sugar-sweetened drinks, leading to a reduced fruit and vegetable intake [25]. Together with our findings, this trend highlights the urgent need to limit the consumption of sugar-sweetened beverages during the early years of life as a preventive measure against chronic diseases. Consequently, early dietary interventions specifically aimed at reducing sugary drink intake during infancy are crucial for promoting healthier eating habits.
The mechanisms underlying the effects of sugar-sweetened beverage intake on the development of ADHD remain incompletely understood. Glucose regulation is critical for brain physiology as it supports brain function. Excessive sugar consumption can induce fluctuations in blood glucose levels, leading to reactive hypoglycemia. This condition, defined as low blood sugar levels post-meal and subsequent hormonal responses, may disrupt normal brain function. These disruptions are associated with increased irritability and aggression, behaviors often observed in individuals with ADHD [26]. Furthermore, the dependence of the brain on external glucose sources underscores the significance of stable glucose regulation [27]. Persistent hypoglycemia, especially during critical developmental stages, may contribute to neurodevelopmental disorders, including conditions such as neuroglycopenia, in which the brain suffers from an inadequate glucose supply [28]. Additionally, ingredients present in sugar-sweetened beverages, such as sodium benzoate, have been linked to increased levels of malondialdehyde, a marker of oxidative stress, in the brain. This increase in oxidative stress could contribute to the ADHD development by damaging neural structures and interfering with neurotransmitter systems essential for attention and behavioral regulation [29]. A cohort study elucidated an inverse relationship between early intake of sugar-sweetened beverages and cognitive performance, as measured by mid-childhood scores on the Kaufman Brief Intelligence Test II, suggesting that such dietary habits could detrimentally affect cognitive development [30].
However, it is imperative to recognize that our study did not confirm a causal relationship between sugar-sweetened beverage consumption and ADHD. Children exhibiting ADHD or ADHD-like behaviors may show a tendency toward immediate gratification or struggle with self-regulation, which influences their choice of food and beverages. Sugar-sweetened beverages are often palatable and rewarding, which could potentially result in higher consumption among individuals with ADHD. To comprehensively elucidate the complexities of this relationship, additional research is warranted to determine the existence of direct causal connections.
The key strength of this study lies in its large-scale administrative cohort design, encompassing a substantial sample size providing adequate statistical power for detailed stratification analyses and a minimal rate of attrition. Furthermore, we conducted comprehensive adjustments for various covariates, including demographic factors, birth weight, breastfeeding status during infancy, and body mass index at the age of 2 years.
Nonetheless, our study has some limitations. A significant constraint is the lack of data on parental age, maternal parity, and familial ADHD history, all of which could potentially influence the risk for ADHD. Despite the robustness of our main findings in the multivariable model, we cannot dismiss the possibility of unmeasured or residual confounding factors. Moreover, our reliance on parental reports of sugar-sweetened beverage consumption may have introduced reporting inaccuracies. However, it is generally acknowledged that parents can accurately recount their children’s dietary intake [31]. The use of a multiple-choice questionnaire to collect data on juice intake means that precise consumption levels remain undetermined, precluding a thorough investigation of dose-dependent relationships. Furthermore, due to the administrative nature of our database, disease definitions relied solely on ICD-10 diagnostic codes. Although these definitions have been employed and validated in several previous studies, discrepancies may exist between these codes and the diagnoses derived from clinical symptoms and tests.
Conclusion
This extensive administrative cohort study involving Korean children demonstrated that higher consumption of sugar-sweetened beverages during early childhood is linked to an elevated risk of ADHD. This finding underscores the need for further research to understand how dietary patterns in early childhood influence neurodevelopmental issues.
Statement of Ethics
This study was conducted with ethical approval from the current National Health Insurance Act. Study participants’ consent was not required as this study was based on de-identified and publicly available data. The need for informed consent was waived by the Institutional Review Board of the Korea National Institute for Bioethics Policy. The study protocol was reviewed and approved by the Institutional Review Board of the Korea National Institute for Bioethics Policy (P01-201603-21-005).
Conflict of Interest Statement
The authors declare no competing interests.
Funding Sources
This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (Grant No. HR22C1605). The funding organization had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or the decision to submit the manuscript for publication.
Author Contributions
Man Yong Han and Ju Hee Kim had full access to all data in the study and took responsibility for the integrity of the data and accuracy of the data analysis. Concept and design: Sejin Kim and Man Yong Han. Acquisition, analysis, or interpretation of data: Jeewon Shin, Hye Ryeong Cha, and Man Yong Han. Drafting of the manuscript: Sejin Kim, Eun Kyo Ha, and Ju Hee Kim. Critical revision of the manuscript for important intellectual content: Sejin Kim, Jeewon Shin, Eun Kyo Ha, Ju Hee Kim, and Man Yong Han. Obtained funding: Man Yong Han. Administrative, technical, or material support: Hye Ryeong Cha, Man Yong Han. Supervision: Ju Hee Kim and Man Yong Han.
Funding Statement
This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (Grant No. HR22C1605). The funding organization had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or the decision to submit the manuscript for publication.
Data Availability Statement
This study was based on data from the National Health Claims Database established by the National Health Insurance Service of the Republic of Korea. Applications for using national health insurance service data are reviewed by the Inquiry Committee of Research Support. If the application is approved, raw data are provided to the applicant for a fee. We cannot provide access to the data, analytical methods, or research materials to other researchers because of the intellectual property rights of this database, which is owned by the National Health Insurance Corporation. However, investigators who wish to reproduce our results or replicate the procedure can be included in the database, which is open for research purposes (https://nhiss.nhis.or.kr). Further inquiries can be directed to the corresponding author.
Supplementary Material.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
This study was based on data from the National Health Claims Database established by the National Health Insurance Service of the Republic of Korea. Applications for using national health insurance service data are reviewed by the Inquiry Committee of Research Support. If the application is approved, raw data are provided to the applicant for a fee. We cannot provide access to the data, analytical methods, or research materials to other researchers because of the intellectual property rights of this database, which is owned by the National Health Insurance Corporation. However, investigators who wish to reproduce our results or replicate the procedure can be included in the database, which is open for research purposes (https://nhiss.nhis.or.kr). Further inquiries can be directed to the corresponding author.
