Abstract
Objectives
Falls are a leading cause of non-fatal injury in young children, but limited research has explored the characteristics and risks associated with diaper change–related falls. This study aimed to determine whether diaper change-related falls are associated with higher proportions of head injuries than other falls in young children and identify risk factors.
Methods
This cross-sectional study analyzed data from the South Korea’s Emergency Department-based Injury In-depth Surveillance Registry 2011–2022 to examine fall injuries among children aged < 3 years. Diaper change-related injuries were identified using the International Classification of Diseases, Tenth Revision codes and narrative descriptions. Clinical outcomes (emergency department disposition, injury severity, head injury diagnoses, and injury sites) were compared between diaper- and non-diaper change-related falls. Logistic regression was used to identify factors associated with traumatic brain injuries (TBIs) and skull fractures.
Results
Among 51,474 fall injuries, 298 cases (0.6%) were diaper change-related, mostly occurring at home (63.4%) and involving infants aged < 1 year (81.2%). Diaper change-related falls were associated with higher proportions of TBI (47.3% vs. 31.0%; p < 0.001) and severe injury (16.4% vs. 6.1%, p < 0.001) than non-diaper change-related falls. In multivariable analysis, diaper change-related mechanisms were independently associated with increased odds of TBI (aOR 1.31, 95% CI 1.04–1.65; p = 0.024) and skull fracture (aOR 1.62, 95% CI 1.15–2.27; p = 0.006).
Conclusion
The proportion of diaper change-related falls among ED visits for falls in children aged 0 to < 3 years is increasing, particularly at home, and are associated with greater injury severity and risk of head trauma. Targeted caregiver education and national safety standards for diaper-changing equipment are needed to prevent these injuries.
Trial registration
Clinical trial number: Not applicable.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12887-025-06473-z.
Keywords: Pediatric emergency medicine, Falls, Head injuries, Epidemiology, Diaper-changing
Introduction
Falls are the leading cause of non-fatal pediatric injuries and a major public health concern [1, 2]. In South Korea, they are the most common cause of emergency department (ED) visits among young children, primarily occurring at home [1, 3, 4]. Despite extensive research on pediatric fall injuries, little is known about diaper change-related falls [5–7]. As infants gain mobility, falls become more common, and routine caregiving tasks, such as bathing or diaper changing, can be hazardous without adequate safety precautions, particularly if caregivers are inattentive or the equipment is unstable [8].
Diaper-changing tables, designed to reduce caregiver back strain, elevate infants to adult waist height and often lack adequate safety features [9]. Additionally, certain nursery products may pose significant fall risks. For example, a United States study analyzing data from 2010 to 2013 reported that home furnishings and fixtures, specifically beds and changing tables, were the most common sources associated with fall injuries in children < 2 years [10]. In South Korea, use of changing tables has increased, with the Korean Consumer Agency’s Consumer Injury Surveillance System reporting a rise in related injuries from 2020 to 2023. This trend reflects a shift in caregiving practices from the traditional method of changing diapers on the floor to the increasing use of elevated changing tables [11].
Nevertheless, diaper change-related falls remain poorly documented in injury surveillance studies. Given infants’ anatomical vulnerabilities, such as disproportionately large heads, weaker neck muscles, and softer cranial bones, falls from elevated surfaces can result in severe head injuries, including traumatic brain injuries (TBIs) [5, 12]. TBIs in young children are associated with particularly poor outcomes, including delayed neurodevelopment, long-term cognitive impairment, and increased morbidity and mortality [13, 14]. However, the significance of TBI in this vulnerable population is often underemphasized in prior studies, leaving a substantial gap in understanding its mechanisms and severity. Therefore, this study aimed to assess whether diaper change-related fall injuries are associated with a higher risk of severe outcomes, particularly TBIs and skull fractures, compared to other fall injuries in young children by analyzing the national ED data. We also sought to identify contributing risk factors to inform caregiver practices and product safety standards.
Methods
Study design, data source and population
This cross-sectional study analyzed data from the Emergency Department-based Injury In-depth Surveillance (EDIIS) Registry in South Korea. This registry is a prospective database documenting injury visits to EDs in South Korea (20 EDs from 2011 to 2014 and 23 EDs from 2015 to 2022), including their demographic information, injury characteristics, and outcomes. The EDIIS database is based on the International Classification of External Causes of Injuries maintained by the World Health Organization. Data were collected from the electronic medical records and reviewed by a trained research coordinator. The quality management committee of the Korea Disease Control and Prevention Agency (KDCA) regularly checks and controls the data quality.
This study included cases of children aged 0 to < 3 years who sustained fall injuries recorded in the EDIIS registry between 2011 and 2022. Generally, the physical development and necessary skills for toilet training emerge between 18 and 30 months of age, with training typically completed by 36 months [15, 16]. Diaper change-related fall injuries were identified through multiple complementary criteria: the primary object of injury coded as "diaper" or "changing table", the appearance of both terms "diaper" and "change" (or their Korean equivalents) in free-text descriptions of the primary object of injury, and mentions of "diaper" and "change" (or their Korean equivalents) within the narrative fields describing the injury context. Two emergency medicine physicians thoroughly reviewed all narratives to ensure that the included cases were truly related to diaper changing.
Measures
Demographic and prehospital variables
The demographic variables included sex and age. Prehospital variables comprised the means of arrival, categorized as 119 ambulances (public emergency medical services), other ambulances (private or hospital-based ambulances), other vehicles (private cars, taxis, or public transport), walking, or unknown (missing data).
Injury-related variables
Injury-related variables included fall height, place of injury, and specific injury location. The height of the fall was categorized into five groups: < 1 m, 1–4 m, > 4 m, others, and unknown (missing data). The injury place was classified as either indoor or outdoor. Injury location was categorized into the following groups: home environments (including private residences and group living facilities), commercial facilities (e.g., supermarkets, banks, restaurants, hotels), parks, hospitals, educational facilities (e.g., schools, kindergartens, daycare centers), public transportation areas (e.g., subway, bus, train stations), and unknown (missing data).
Clinical outcome
Clinical outcomes, including ED disposition, injury severity, head injury diagnoses, and anatomical injury sites were examined. ED dispositions were categorized as discharge, transfer to another hospital, admission to the intensive care unit (ICU), admission to a general ward, death, others, or unknown (missing data). Injury severity was determined based on the excess mortality ratio-adjusted injury severity scale (EMR-ISS) [17]. The EMR-ISS score is calculated by summing the squares of the three highest EMR grades derived from the International Classification of Diseases, Tenth Revision (ICD-10) codes of a particular case: EMR-ISS = (first highest EMR grade)2 + (second highest EMR grade)2 + (third highest EMR grade)2. EMR-ISS was classified as mild (1 ≤ EMR-ISS ≤ 8), moderate (9 ≤ EMR-ISS ≤ 24), or severe (EMR-ISS ≥ 25) [18].
Head injury diagnoses were identified using ICD-10 codes [19, 20]. Skull fractures were defined by using the codes S02.0, S02.1, S02.7, S02.8, and S02.9. Intracranial injuries included codes S06–S06.9, whereas cerebral concussion were defined as S06.0. TBI was defined as the presence of at least one of the following conditions: skull fracture, intracranial injury, or cerebral concussion [21].
Anatomical injury sites were classified according to ICD-10 codes as follows: head (S00–S09), neck (S10–S19), trunk (S20–S39), upper extremities (S40–69), and lower extremities (S70–S99).
Statistical analysis
Categorical variables were expressed as frequencies and percentages. Overall comparisons between diaper change-related and non–diaper change-related falls were performed using chi-square tests (or Fisher’s exact or Monte-Carlo tests, as appropriate). For demographic characteristics, raw p-values are reported, whereas for clinical outcomes, p-values were adjusted for multiple comparisons within variable families using the Benjamini–Hochberg false discovery rate (FDR) procedure.
We calculated a visit-based proportion for children aged 0 to < 3 years, defined as the number of diaper change-related ED fall injury visits divided by all ED fall injury visits in this age group for the same year. To assess temporal trends, we estimated the annual percent change (APC) using Joinpoint regression analysis. Statistical significance for the trend was determined using the Joinpoint Regression Program, version 5.4.0.0 (National Cancer Institute, Bethesda, MD, USA).
The associations of diaper change-related mechanism and other injury-related factors (sex, age, and fall height) with TBI and skull fracture were evaluated using univariable and multivariable logistic regression analyses. Variables with p < 0.2 in the univariable analysis, along with age and sex, were included in the multivariable model [22]. In addition, variables were selected to preserve events per variable ≥ 10, avoid sparse cells and collinearity, and maintain model parsimony [23, 24].
Results were reported as odds ratios (ORs) with 95% confidence intervals (CIs). P < 0.05 was considered statistically significant. All statistical analyses were performed using R version 4.1.2 (R Foundation for Statistical Computing, Vienna, Austria).
Ethics statement
This study was approved by the Institutional Review Board of Samsung Medical Center (approval no. SMC 2025–01–081). The requirement for informed consent was waived because of the retrospective and observational design and use of anonymous data.
Results
Study population
Of 117,513 ED visits for children aged 0 to < 3 years who visited EDs in South Korea between 2011 and 2022 (Fig. 1), 51,474 (43.8%) cases involved fall injuries. Among these, 146 cases were coded with "diaper" or "changing table" as the primary injury object, 12 included the terms "diaper" and "change" (or similar expressions in Korean) within the free-text primary injury object description, and 140 referenced similar terms in the narrative section of the injury report. After review and selection, 298 (0.6%) cases of diaper change-related fall injuries and 51,176 (99.4%) cases of non-diaper change-related fall injuries were included in this study.
Fig. 1.
Study flowchart
Table 1 presents the general characteristics of the study population. Among 298 cases of diaper change-related falls, 48.3% were male, compared to 55.2% in the non-diaper change-related falls group. Infants aged < 1 year accounted for 81.2% of diaper change-related falls, substantially higher than the 40.6% observed in the non-diaper change-related group. Diaper change-related falls more often involved greater heights, with 48.0% occurring from 1–4 m compared to 18.2% in the non-diaper change-related group. Most cases in both groups arrived via other vehicles (diaper change-related, 83.2%; non-diaper change-related, 87.6%), although a higher proportion of diaper change-related falls involved arrival via 119 ambulance service (14.1% vs. 8.9%). Almost all diaper change-related falls occurred indoors (98.0%), primarily at home (63.4%), or commercial facilities (30.5%).
Table 1.
General characteristics of pediatric fall cases aged 0 to < 3 years: comparison between diaper- and non-diaper change-related falls in South Korea (2011–2022)
| Non-diaper change-related falls (N = 51,176) | Diaper change-related falls (N = 298) | p value | |
|---|---|---|---|
| Sex, N (%) | 0.02 | ||
| Male | 28,251 (55.2%) | 144 (48.3%) | |
| Female | 22,925 (44.8%) | 154 (51.7%) | |
| Age group, N (%) | < 0.001 | ||
| < 1 year | 20,783 (40.6%) | 242 (81.2%) | |
| 1 to < 2 years | 19,482 (38.1%) | 48 (16.1%) | |
| 2 to < 3 years | 10,911 (21.3%) | 8 (2.7%) | |
| Height of fall, N (%) | < 0.001 | ||
| < 1 m | 40,563 (79.3%) | 152 (51.0%) | |
| 1–4 m | 9,316 (18.2%) | 143 (48.0%) | |
| > 4 m | 407 (0.8%) | 1 (0.3%) | |
| Others | 484 (0.9%) | 2 (0.7%) | |
| Unknowna | 406 (0.8%) | 0 (0.0%) | |
| Means of arrival, N (%) | 0.005 | ||
| Other Vehicle | 44,835 (87.6%) | 248 (83.2%) | |
| 119 Ambulance | 4,542 (8.9%) | 42 (14.1%) | |
| Other Ambulance | 460 (0.9%) | 5 (1.7%) | |
| By Walk | 1,209 (2.3%) | 3 (1.0%) | |
| Unknown | 130 (0.3%) | 0 (0.0%) | |
| Injury place, N (%) | < 0.001 | ||
| Indoor | 44,567 (87.4%) | 292 (98.0%) | |
| Outdoor | 6,451 (12.6%) | 6 (2.0%) | |
| Injury location, N (%) | < 0.001 | ||
| Home | 42,619 (83.3%) | 189 (63.4%) | |
| Commercial facilities | 2,373 (4.6%) | 91 (30.5%) | |
| Park | 1,218 (2.4%) | 7 (2.3%) | |
| Hospital | 361 (0.7%) | 4 (1.3%) | |
| Educational facilities | 311 (0.6%) | 1 (0.3%) | |
| Public transportation area | 71 (0.1%) | 4 (1.3%) | |
| Unknown | 4,223 (8.3%) | 2 (0.7%) |
aThe “Unknown” category represents missing data
Annual trends in diaper change-related fall injuries
The annual proportion of diaper change-related falls per 1,000 ED fall-injury visits in children aged 0 to < 3 years remained below 2.5 from 2011 to 2018 (Fig. 2A). The increase from 2019 was driven mainly by infants < 1 year, with this group contributing the largest share of the year-over-year rise. From 2019 onward, proportions nearly doubled annually and exceeded 20 per 1,000 by 2022. Joinpoint analysis estimated an APC of 12.1% for 2011–2018 and 72.6% for 2018–2022 (p < 0.05; Supplementary Fig. 1).
Fig. 2.
Annual Trends in Diaper change-related Fall Injuries (2011–2022). A Proportions of diaper change-related falls per 1,000 fall-injured cases aged 0 to < 3 years, with age group compositions. The stacked bars show the contribution of each age group to the annual total. B Proportions of diaper change-related falls per 1,000 fall-related traumatic brain injury cases (age 0 to < 3 years)
A similar pattern was observed when restricting the analysis to fall-related TBI ED visits in children 0 to < 3 years. The proportion remained below 10 per 1,000 through 2019, then rose steeply, reaching nearly 50 per 1,000 in 2022 (Fig. 2B). Joinpoint analysis identified a modest increase from 2014 to 2020 (APC 29.60%) followed by a markedly steeper rise from 2020 onward (111.41%, p < 0.05; Supplementary Fig. 2).
Adverse clinical outcomes
In children aged 0 to < 3 years, falls from diaper-changing surfaces resulted in a substantially greater injury burden than other household falls (Table 2). Severe trauma (EMR-ISS score ≥ 25) occurred in 16.4% of diaper change-related cases compared to 6.1% of non-diaper change-related falls, whereas minor trauma (EMR-ISS score ≤ 8) was less common (4.7% vs. 13.2%). The overall difference across ISS severity categories was statistically significant (p < 0.001). The head injuries mirrored this pattern. TBIs were reported in 47.3% of diaper change-related falls compared to 31.0% of other falls (p < 0.001), driven by higher proportions of skull fracture (14.1% vs. 4.9%; p < 0.001) and cerebral concussion (33.6% vs. 25.2%; p = 0.001). The prevalence of intracranial injuries did not differ significantly between the groups (4.0% vs. 2.4%; p = 0.113). Despite differences in injury severity, ED disposition was comparable; > 94% of children in both groups were discharged home. Notably, ICU admissions, transfers, and mortality were rare. Figure 3 summarizes these disparities, showing consistently higher proportions of severe injuries and TBIs associated with diaper change-related falls.
Table 2.
Clinical outcomes of pediatric fall cases aged 0 to < 3 years: comparison between diaper- and non-diaper change-related falls
| Non-diaper change-related falls (N = 51,176) | Diaper change-related falls (N = 298) | p-adj valued | |
|---|---|---|---|
| ED outcome, N (%) | 0.52 | ||
| Discharge | 49,016 (95.8%) | 281 (94.3%) | |
| General ward admission | 1,621 (3.2%) | 13 (4.4%) | |
| ICU Admission | 334 (0.6%) | 3 (1.0%) | |
| Transfer | 152 (0.3%) | 1 (0.3%) | |
| Death | 13 (0.0%) | 0 (0.0%) | |
| Others | 39 (0.1%) | 0 (0.0%) | |
| Unknowna | 1 (0.0%) | 0 (0.0%) | |
| EMR-ISS, N (%) | < 0.001 | ||
| Score ≤ 8 | 6,754 (13.2%) | 14 (4.7%) | |
| Score 9 ~ 24 | 40,850 (79.8%) | 232 (77.9%) | |
| Score ≥ 25 | 3,132 (6.1%) | 49 (16.4%) | |
| Unknown | 440 (0.9%) | 3 (1.0%) | |
| Surgery required, N (%) | 744 (1.5%) | 3 (1.0%) | 0.805 |
| Head injury diagnosis, N (%) | |||
| Traumatic brain injuryb | 15,888 (31.0%) | 141 (47.3%) | < 0.001 |
| Cerebral concussion | 12,913 (25.2%) | 100 (33.6%) | 0.002 |
| Skull fracture | 2,524 (4.9%) | 42 (14.1%) | < 0.001 |
| Intracranial injury | 1,247 (2.4%) | 12 (4.0%) | 0.076 |
| Injury sitec, N (%) | |||
| Head | 43,864 (84.4%) | 282 (91.3%) | |
| Neck | 251 (0.5%) | 2 (0.7%) | |
| Trunk | 246 (0.5%) | 0 (0.0%) | |
| Upper extremities | 4,409 (8.5%) | 11 (3.6%) | |
| Lower extremities | 1,474 (2.8%) | 3 (1.0%) | |
| Others | 1,753 (3.4%) | 11 (3.6%) | |
ED Emergency Department, EMR-ISS Excess mortality ratio-adjusted injury severity scale, ICU Intensive Care Unit
aThe “Unknown” category represents missing data
bTraumatic brain injury (TBI) was defined as the presence of at least one of the following: a skull fracture, intracranial injury, or cerebral concussion. Note that the counts represent specific diagnoses and do not sum to the total population
cThe number of injury sites exceeds the number of cases because patients could sustain injuries to multiple anatomical sites simultaneously. Total cases: 51,997 for non-diaper change-related injuries and 309 for diaper change-related injuries
dOverall comparisons by diaper status used chi-square (Fisher’s exact/Monte-Carlo as appropriate). P -adjusted (p-adj) values are Benjamini–Hochberg false discovery rate (FDR)–adjusted within families. TBI (composite) was analyzed separately and not included in the component family
Fig. 3.
Comparison of Clinical Outcome Between Diaper- and Non-Diaper change-related Falls. EMR-ISS, excess mortality ratio–adjusted injury severity score; TBI, traumatic brain injury. Note: Positive differences (black circles) indicate outcomes more common in diaper change-related falls and negative differences (white circles) indicate outcomes more common in non-diaper change-related falls
This pattern persisted even when the analysis was restricted to infants aged < 1 year (Table 3). Severe injuries (EMR-ISS score ≥ 25) occurred in 18.6% of diaper change-related falls compared to 9.4% of non-diaper change-related falls (p < 0.001). TBIs remained more frequent in the diaper group than in the non-diaper group (49.6% vs. 42.4%; p = 0.030), with skull fractures occurring at an even higher proportion (15.7% vs. 7.8%; p < 0.001). Other outcomes, including cerebral concussion, intracranial injury, surgery, and ICU admission did not differ significantly between the groups, and most infants were discharged directly from the ED.
Table 3.
Clinical outcomes of pediatric fall cases under 1 year of age: comparison between diaper- and non-diaper change-related falls
| Non-diaper change-related falls (N = 20,783) | Diaper change-related falls (N = 242) | p-adj valued | |
|---|---|---|---|
| ED outcome, N (%) | 0.346 | ||
| Discharge | 19,798 (95.2%) | 225 (93.0%) | |
| General ward admission | 708 (3.4%) | 13 (5.4%) | |
| ICU Admission | 199 (1.0%) | 3 (1.2%) | |
| Transfer | 54 (0.3%) | 1 (0.4%) | |
| Death | 6 (0.0%) | 0 (0.0%) | |
| Others | 18 (0.1%) | 0 (0.0%) | |
| EMR-ISS, N (%) | < 0.001 | ||
| Score ≤ 8 | 1,566 (7.5%) | 10 (4.2%) | |
| Score 9 ~ 24 | 17,077 (82.2%) | 184 (76.0%) | |
| Score ≥ 25 | 1,945 (9.4%) | 45 (18.6%) | |
| Unknowna | 195 (0.9%) | 3 (1.2%) | |
| Surgery required, N (%) | 173 (0.8%) | 3 (1.2%) | 0.46 |
| Head injury diagnosis, N (%) | |||
| Traumatic brain injuryb | 8,818 (42.4%) | 120 (49.6%) | 0.025 |
| Cerebral concussion | 6,952 (33.5%) | 83 (34.3%) | 0.781 |
| Skull fracture | 1,627 (7.8%) | 38 (15.7%) | < 0.001 |
| Intracranial injury | 809 (3.9%) | 12 (5.0%) | 0.592 |
| Injury sitec, N (%) | |||
| Head | 19,477 (92.3%) | 229 (91.6%) | |
| Neck | 68 (0.3%) | 1 (0.4%) | |
| Trunk | 57 (0.3%) | 0 (0.0%) | |
| Upper extremities | 551 (2.6%) | 7 (2.8%) | |
| Lower extremities | 154 (0.7%) | 2 (0.8%) | |
| Others | 789 (3.8%) | 11 (4.4%) | |
ED Emergency Department, EMR-ISS Excess mortality ratio-adjusted injury severity scale, ICU Intensive Care Unit
aThe “Unknown” category represents missing data
bTraumatic brain injury (TBI) was defined as the presence of at least one of the following: a skull fracture, intracranial injury, or cerebral concussion. Note that the counts represent specific diagnoses and do not sum to the total population
cThe number of injury sites exceeds the number of cases because patients could sustain injuries to multiple anatomical sites simultaneously. Total cases: 21,096 for non-diaper change-related injuries and 250 for diaper change-related injuries
dOverall comparisons by diaper status used chi-square (Fisher’s exact/Monte-Carlo as appropriate). P -adjusted (p-adj) values are Benjamini–Hochberg false discovery rate (FDR)–adjusted within families. TBI (composite) was analyzed separately and not included in the component family
Associations of diaper change-related falls with TBI and skull fracture in children < 3 years
Multivariable logistic regression including pediatric fall injury < 3 years (Table 4) revealed that diaper change-related falls were independently associated with a significantly higher odds of TBI than non-diaper change-related falls (adjusted OR [aOR] 1.31, 95% CI 1.04–1.65; p = 0.024). Female sex was associated with a small increase in TBI odds versus males (aOR, 1.05; 95% CI, 1.01–1.09; p = 0.017). Compared with children aged 2 to < 3 years, TBI odds were higher in those < 1 year (aOR, 3.10; 95% CI, 2.93–3.28; p < 0.001) and 1 to < 2 years (aOR, 1.45; 95% CI, 1.36–1.53; p < 0.001). Falls from 1–4 m were associated with modest increase in TBI compared with < 1 m (aOR, 1.17; 95% CI, 1.11–1.22; p < 0.001).
Table 4.
Logistic regression analysis of factors associated with traumatic brain injury in fall injuries among children aged 0 to < 3 years
| Univariable model | Multivariable model | |||
|---|---|---|---|---|
| OR (95% CI) | p value | OR (95% CI) | p value | |
| Injury mechanism | ||||
| Non-diaper change-related falls | Reference | Reference | ||
| Diaper change-related falls | 1.99 (1.59–2.51) | < 0.001 | 1.31 (1.04–1.65) | 0.024 |
| Sex | ||||
| Male | Reference | Reference | ||
| Female | 0.93 (0.86–1.01) | 0.07 | 1.05 (1.01–1.09) | 0.017 |
| Age group | ||||
| < 1 year | 3.10 (2.94–3.28) | < 0.001 | 3.10 (2.93–3.28) | < 0.001 |
| 1 to < 2 years | 1.44 (1.36–1.53) | < 0.001 | 1.45 (1.36–1.53) | < 0.001 |
| 2 to < 3 years | Reference | Reference | ||
| Height of fall | ||||
| < 1 m | Reference | Reference | ||
| 1–4 m | 1.16 (1.10–1.21) | < 0.001 | 1.17 (1.11–1.22) | < 0.001 |
| > 4 m | 0.82 (0.66–1.03) | 0.085 | 0.84 (0.67–1.05) | 0.123 |
| Others | 0.87 (0.71–1.06) | 0.169 | 1.06 (0.86–1.30) | 0.603 |
| Unknowna | 0.64 (0.51–0.81) | < 0.001 | 0.83 (0.65–1.06) | 0.128 |
| Means of arrival | ||||
| 119 Ambulance | Reference | Reference | ||
| Other Ambulance | 1.81 (1.49–2.19) | < 0.001 | 2.03 (1.66–2.47) | < 0.001 |
| Other Vehicle | 0.74 (0.70–0.79) | < 0.001 | 0.77 (0.72–0.82) | < 0.001 |
| By Walk | 0.37 (0.32–0.44) | < 0.001 | 0.42 (0.36–0.49) | < 0.001 |
| Unknown | 0.44 (0.29–0.68) | < 0.001 | 0.42 (0.27–0.65) | < 0.001 |
| Injury place | ||||
| Indoor | Reference | Reference | ||
| Outdoor | 0.82 (0.78–0.87) | < 0.001 | 1.01 (0.95–1.07) | 0.703 |
| Injury location | ||||
| Home | Reference | |||
| Commercial facilities | 1.04 (0.95–1.14) | 0.366 | ||
| Park | 0.57 (0.50–0.65) | < 0.001 | ||
| Hospital | 1.42 (1.15–1.75) | 0.001 | ||
| Educational facilities | 0.56 (0.43–0.74) | < 0.001 | ||
| Public transportation area | 1.45 (0.91–2.30) | 0.114 | ||
| Unknown | 0.93 (0.87–1.00) | 0.043 | ||
OR odds ratio, CI confidence interval
aThe “Unknown” category represents missing data
Regarding means of arrival, other ambulance was associated with higher TBI odds (aOR, 2.03; 95% CI, 1.66–2.47; p < 0.001), whereas other vehicle (aOR, 0.77; 95% CI, 0.72–0.82; p < 0.001) and arrival by walk (aOR, 0.42; 95% CI, 0.36–0.49; p < 0.001) were associated with lower odds. Injury place (indoor vs outdoor) was not associated with TBI after adjustment (aOR, 1.01; 95% CI, 0.95–1.07; p = 0.703).
In univariable screening, several injury-location categories (e.g., hospital, park, educational facilities) showed differences relative to home. However, the multi-level factor was not retained in the final model to preserve events-per-variable, avoid sparse cells and collinearity with injury place (indoor/outdoor), and maintain parsimony.
Given clinical interest in component outcomes, we additionally fit a multivariable model for skull fracture (Supplementary Table 1). In this analysis, the diaper change-related mechanism showed a more pronounced association than for TBI (aOR 1.62, 95% CI 1.15–2.27; p = 0.006), consistent with the descriptive excess in diaper change-related falls.
Discussion
Using a 12-year, prospectively collected national registry that covers 20–23 tertiary EDs (20 sites in 2011–2014; 23 in 2015–2022), we found that diaper change-related falls represent a distinct high-severity injury mechanism for head trauma in children aged 0 to < 3 years. Notably, their prevalence increased sharply in recent years, and cases occurred predominantly indoors—often at home—with 81% of cases involving infants aged < 1 year. Compared with other falls, diaper change-related incidents occurred from greater heights (predominantly 1–4 m) and resulted in disproportionately greater trauma burden. Severe injury and TBI were significantly more common, and the adjusted odds of TBI remained elevated for diaper change-related mechanisms. Collectively, these findings establish diaper-changing surfaces as a major yet preventable source of head trauma in early childhood and highlight the urgent need for targeted indoor safety interventions.
The sharp increase in diaper change-related falls between 2019 and 2022 may reflect concurrent societal and environmental changes rather than a single causal factor. During the coronavirus disease 2019 (COVID-19) pandemic, prolonged stay-at-home measures and daycare closures increased the time infants spent under home-based care, likely heightening exposure to elevated diaper-changing surfaces [25, 26]. Pandemic-related caregiver stress and fatigue may also have contributed to brief lapses in supervision, as suggested by prior reports of increased home-based pediatric falls during lockdown periods [27]. Furthermore, consumer demand for diaper-changing tables appears to have increased in recent years, indicating broader adoption of elevated changing furniture in households and childcare settings [28]. This growing prevalence of diaper-changing tables, alongside pandemic-related lifestyle changes, may together explain the temporal rise in diaper change-related fall injuries observed after 2019.
Similar trends have been reported worldwide. In the United States, the National Electronic Injury Surveillance System reported a 23.7% increase in injuries associated with nursery products from 2003 to 2011, mainly involving baby carriers, strollers, and cribs rather than a single product such as changing tables. Although that study did not specifically demonstrate an increase in diaper change-related falls, the overall rise in nursery-related injuries may indicate greater caregiver use of elevated nursery equipment, potentially increasing the risk of diaper change-related falls. Most of these injuries involved concussions and other closed-head injuries [29]. European data, though limited, showed a similar pattern. Specifically, a Spanish multicenter study reported the involvement of nursery products in 69.4% of falls in infants aged < 1 year, and Greek surveillance identified changing-table falls as the common nursery item associated with hospitalizations [7, 30]. Korean caregivers traditionally change diapers on the floor; however, the recent rise in the use of elevated changing tables now mirrors the earlier international trends, increasing the likelihood of similar injury curves without early preventive measures.
Age-related vulnerability to TBI is well established. Biomechanical studies show that infants sustain greater intracranial strain than toddlers due to more deformable cranial bones, weaker cervical musculature, and less protective cranial vault [12, 31, 32]. These features amplify brain injury risk even from short falls, as reflected in our findings, with 83% of TBIs occurring in children aged < 1 year. Therefore, preventing head trauma requires early interventions, particularly during the first year of life when biomechanical immaturity is greatest.
Given the predominance of infant cases, we examined which head injury components were associated with excess risk. In descriptive comparisons, skull fracture and concussion were more frequent in diaper change-related falls than in other falls. Notably, skull fracture was particularly frequent among infants. To avoid overfitting in small subgroups, we focused inference on the composite TBI outcome in the full < 3 year ED fall-injury cohort, in which the diaper change-related mechanism remained independently associated with higher TBI odds than non-diaper change-related falls (aOR 1.31, 95% CI 1.04–1.65; p = 0.024, Table 4). This finding can be explained as follows: first, controlling for age and fall height attenuated associations for concussion and intracranial injury, leaving fracture as the main contributor; second, infant skulls deform and fracture at lower energy thresholds without necessarily propagating force to intracranial tissue [33]; and third, institutional variability in imaging protocols may lead to under-detection of milder concussion or occult intracranial lesions, selectively reducing the non-fracture elements of the TBI endpoint. Therefore, in clinical practice, a suspected diaper change-related fall, particularly from ≥ 1 m, should prompt a high index of suspicion for skull fracture, even when neurologic findings are subtle.
Fall height was significantly associated with TBI after adjustment. Falls from 1–4 m showed a modest but significant increase in TBI risk compared with < 1 m. This is consistent with biomechanical data from drop-tower experiments showing that even falls from 30–90 cm can generate angular head accelerations exceeding infant injury thresholds. [34] The risk is amplified by modifiable environmental features. Changing tables are typically positioned at adult waist height, yet guardrails and safety straps are often absent or ignored, and many are placed over hard, uncarpeted flooring without protective padding [9, 35]. These conditions result in routine diaper changes becoming high-energy impacts that disproportionately endanger infants with biomechanically vulnerable cranial bones.
The findings of this study have important implications for preventing injuries. Considering the high proportion of TBI cases and the age- and height-related risk factors we identified, a coordinated “3E” strategy—Education, Engineering, and Enforcement—offers the most effective approach to reduce changing-table injuries [36]. Regarding “Education”, during well-child visits, hospital discharge counselling, and home-visiting programs, clinicians should emphasize constant hands-on supervision, routine use of safety straps, and placement of cushioned mats beneath elevated changing surfaces. Randomized and quasi-experimental trials indicate that such tailored guidance improves protective behaviors and reduces fall rates [37–39]. Regarding “Engineering”, manufacturers can mitigate risk by incorporating guard-rails, non-skid bases, auto-locking restraints, and verified stability testing—features already mandated in ASTM F2388 and EN 12221 but not yet implemented in South Korea [35, 40]. Regarding “Enforcement”, adopting a national safety standard, requiring clear safety labeling, and conducting regular market surveillance would address current regulatory gaps and promote adoption of safer designs. Deploying these three elements in coordination is essential to preventing skull fractures and severe TBIs characteristic of diaper change-related falls.
Although our cross-sectional analysis could not assess outcomes beyond the ED, prior longitudinal studies have shown that TBIs in the first three years of life can disrupt brain maturation and delay cognitive and motor skill acquisition, leading to long-term physical, emotional, and financial consequences for families and society [41–43]. A complete assessment of this burden requires prospective cohorts that follow children into later childhood while accounting for potential confounders, such as caregiver supervision, household safety practices, and socioeconomic status. Future research should quantify how specific environmental and behavioral factors modulate injury risk and rigorously test the real-world effectiveness of integrated “3E” interventions. Such studies are imperative for translating the proposed preventive framework into measurable improvements in infant safety.
Limitations
Several limitations warrant consideration. First, this retrospective EDIIS registry analysis is vulnerable to missing or miscoded data—non-mandatory fields such as exact fall height, injury site, and brain CT utilization were often incomplete. The reported fall height was likely based on caregiver recollection rather than direct measurement, introducing potential recall bias. Diaper change-related cases were identified by narrative text parsing, potentially excluding events not explicitly documented as changing-table falls, although the registry is audited routinely and captures > 95% of tertiary-care ED visits nationwide. Second, key covariates were imprecise or imbalanced: age was recorded only in completed years, and fall-height distributions differed between study groups, leaving room for residual confounding despite multivariable adjustment. Third, since our dataset included only cases presenting to the ED, the number of diaper change-related fall cases may be lower than the actual incidence. In addition, we could not evaluate neurologic status at discharge or long-term neurodevelopmental outcomes. Finally, caregiving practices and housing layouts in South Korea may differ from those elsewhere, limiting direct generalizability. Prospective multicenter cohorts that capture month-level age, precise fall metrics, caregiver behavior, and post-discharge neurodevelopment are needed to define lifetime impact and to test integrated educational, engineering, and regulatory interventions [44].
Conclusion
The proportion of diaper change-related falls among ED visits for falls in children aged 0 to < 3 years is increasing, and is concentrated in infants < 1 year. Compared with non-diaper change-related falls, these incidents are associated with greater injury severity (EMR-ISS) and higher adjusted odds of TBI. Reducing this avoidable burden will require targeted caregiver education and the adoption of national safety standards for diaper-changing equipment.
Supplementary Information
Supplementary Figure 1. Joinpoint analysis of annual trends in diaper change-related fall injuries among cases aged <3 years (corresponding to Figure 2A).
Supplementary Figure 2. Joinpoint analysis of annual trends in diaper chage-related falls among fall-related TBI cases aged <3 years (corresponding to Figure 2B).
Supplementary Table 1. Logistic regression analysis of factors associated with skull fracture in fall injuries among children aged <3 years.
Acknowledgements
This work was supported by the Korea Disease Control and Prevention Agency (KDCA).
Abbreviations
- APC
Annual percent change
- ED
Emergency department
- EDIIS
Emergency Department-based Injury In-depth Surveillance
- TBI
Traumatic brain injury
- EMR-ISS
Excess mortality ratio–adjusted injury severity score
- KDCA
Korea Disease Control and Prevention Agency
- ICU
Intensive care unit
- ICD-10
International Classification of Diseases, Tenth Revision
Authors’ contributions
MK collected data, carried out the initial analyses, drafted initial manuscript, and critically reviewed and revised the manuscript. SH conceptualized and designed the study, supervised data collection, drafted initial manuscript, and critically reviewed and revised the manuscript. HY conceptualized and designed the study, supervised data collection, and critically reviewed and revised the manuscript. SJM, TK, HC, SUL, SYH, WCC critically reviewed and revised the manuscript. All authors read and approved the final manuscript.
Funding
This work was supported by the Korea Disease Control and Prevention Agency (KDCA).
Data availability
The data that support the findings of this study are available from Korea Disease Control and Prevention Agency (KDCA) but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of KDCA.
Declarations
Ethics approval and consent to participate
This study was approved by the Institutional Review Board of Samsung Medical Center (approval no. SMC 2025–01-081). The requirement for informed consent was waived because of the retrospective and observational design and use of anonymous data.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Hee Yoon and Sejin Heo contributed equally to this work.
Contributor Information
Sejin Heo, Email: silversh06@gmail.com.
Hee Yoon, Email: wildhi.yoon@gmail.com.
References
- 1.KDCA. Injury Fact Book 2024. Cheongju, South Korea: KDCA; 2024. https://www.kdca.go.kr/injury/biz/injury/recsroom/statsSmMain.do.
- 2.Centers for Disease Control and Prevention. WISQARS (Web-based Injury Statistics Query and Reporting System). National Center for Injury Prevention and Control. 2023. https://wisqars.cdc.gov/. Accessed 5 Apr 2025.
- 3.Park SH, Min JY, Cha WC, Jo IJ, Kim T. National surveillance of injury in children and adolescents in the Republic of Korea: 2011-2017. Int J Environ Res Public Health. 2020;17(23). 10.3390/ijerph17239132. [DOI] [PMC free article] [PubMed]
- 4.Lim C, Oh JH, Yoo JR, Ko SY, Kang JH, Lee SK, et al. Characteristics and trends of pediatric trauma on Jeju Island, Korea: a community-level serial cross-sectional study. Clin Exp Emerg Med. 2025;12(1):56–65. 10.15441/ceem.24.203. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Omaki E, Shields W, Rouhizadeh M, Delgado-Barroso P, Stefanos R, Gielen A. Understanding the circumstances of paediatric fall injuries: a machine learning analysis of NEISS narratives. Inj Prev. 2023;29(5):384–8. 10.1136/ip-2023-044858. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Pitone ML, Attia MW. Patterns of injury associated with routine childhood falls. Pediatr Emerg Care. 2006;22(7):470–4. 10.1097/01.pec.0000226869.41803.50. [DOI] [PubMed] [Google Scholar]
- 7.Dedoukou X, Spyridopoulos T, Kedikoglou S, Alexe DM, Dessypris N, Petridou E. Incidence and risk factors of fall injuries among infants: a study in Greece. Arch Pediatr Adolesc Med. 2004;158(10):1002–6. 10.1001/archpedi.158.10.1002. [DOI] [PubMed] [Google Scholar]
- 8.DeGeorge KC, Neltner CE, Neltner BT. Prevention of Unintentional Childhood Injury. Am Fam Physician. 2020;102(7):411–7. [PubMed] [Google Scholar]
- 9.Chaudhary S, Figueroa J, Shaikh S, Mays EW, Bayakly R, Javed M, et al. Pediatric falls ages 0–4: understanding demographics, mechanisms, and injury severities. Inj Epidemiol. 2018;5(Suppl 1):7. 10.1186/s40621-018-0147-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Ali B, Lawrence B, Miller T, Swedler D, Allison J. Consumer Products Contributing to Fall Injuries in Children Aged <1 to 19 Years Treated in US Emergency Departments, 2010 to 2013: An Observational Study. Glob Pediatr Health. 2019;6:2333794X18821941. 10.1177/2333794X18821941. [DOI] [PMC free article] [PubMed]
- 11.Korea Consumer Agency. Be cautious when using baby changing stations, as there are many accidents involving infants falling. 2023. https://www.kca.go.kr/home/board/download.do?menukey=4006&fno=10039768&bid=00000035&did=1003554553. Accessed 5 Apr 2025.
- 12.Figaji AA. Anatomical and physiological differences between children and adults relevant to traumatic brain injury and the implications for clinical assessment and care. Front Neurol. 2017;8:685. 10.3389/fneur.2017.00685. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Baum J, Entezami P, Shah K, Medhkour A. Predictors of outcomes in traumatic brain injury. World Neurosurg. 2016;90:525–9. 10.1016/j.wneu.2015.12.012. [DOI] [PubMed] [Google Scholar]
- 14.Keenan HT, Clark A, Holubkov R, Ewing-Cobbs L. Longitudinal developmental outcomes of infants and toddlers with traumatic brain injury. JAMA Netw Open. 2023;6(1):e2251195. 10.1001/jamanetworkopen.2022.51195. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Toilet Training Guidelines. Parents-the role of the parents in toilet training. Pediatrics. 1999;103(6 Pt 2):1362–3. [PubMed] [Google Scholar]
- 16.Takahashi E. Investigation of the age of release from the diaper environment. Pediatrician. 1987;14(Suppl 1):48–52. [PubMed] [Google Scholar]
- 17.Kim J, Shin SD, Im TH, Kug Jong L, Ko SB, Park JO, et al. Development and validation of the excess mortality ratio-adjusted injury severity score using the international classification of diseases 10th Edition. Acad Emerg Med. 2009;16(5):454–64. 10.1111/j.1553-2712.2009.00412.x. [DOI] [PubMed] [Google Scholar]
- 18.Kim J, Shin SD, Im TH, Lee KJ, Ko SB, Park JO, et al. Development and validation of the excess mortality ratio–adjusted injury severity score using the International Classification of Diseases 10th edition. Acad Emerg Med. 2009;16(5):454–64. 10.1111/j.1553-2712.2009.00412.x. [DOI] [PubMed] [Google Scholar]
- 19.Park HA, Lim B, Ro YS. Trends in traumatic brain injury-related emergency department visits in Korea: a report from the National Emergency Department Information System (NEDIS) 2018–2022. Clin Exp Emerg Med. 2023;10(S):S63–8. 10.15441/ceem.23.148. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Kong SY, Ro YS, Do Shin S, Song KJ, Park JH. Epidemiology of traumatic brain injury in the Republic of Korea from 2011 to 2014: based on three major data sources in the Republic of Korea. J EMS Med. 2022;1(1):13–22. 10.35616/jemsm.2019.00024. [Google Scholar]
- 21.Bazarian JJ, McClung J, Cheng YT, Flesher W, Schneider SM. Emergency department management of mild traumatic brain injury in the USA. Emerg Med J. 2005;22(7):473–7. 10.1136/emj.2004.019273. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Bursac Z, Gauss CH, Williams DK, Hosmer DW. Purposeful selection of variables in logistic regression. Source Code Biol Med. 2008;3:17. 10.1186/1751-0473-3-17. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Peduzzi P, Concato J, Kemper E, Holford TR, Feinstein AR. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol. 1996;49(12):1373–9. 10.1016/s0895-4356(96)00236-3. [DOI] [PubMed] [Google Scholar]
- 24.Westreich D, Greenland S. The table 2 fallacy: presenting and interpreting confounder and modifier coefficients. Am J Epidemiol. 2013;177(4):292–8. 10.1093/aje/kws412. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Tan Q, Wang T, Xu N, Zhang G, Luo X. Characteristics of unintentional childhood injury during COVID-19: a single-center comparative study. Transl Pediatr. 2023;12(3):405–16. 10.21037/tp-23-79. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Tomar Güneysu S, Derinöz Güleryüz O, Çolak Ö. The Home Accident Cases Applying to The Pediatric Emergency Department during the Covid-19 Pandemic: What Did the Pandemic Change? Gazi Medical Journal. 2022.
- 27.Theodorou CM, Brown EG, Jackson JE, Castle SL, Chao SD, Beres AL. Unintended consequences of COVID-19 on pediatric falls from windows: a multicenter study. J Surg Res. 2022;279:187–92. 10.1016/j.jss.2022.05.022. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Korea Consumer Agency. Consumer Injury Surveillance System: Annual Report 2023. Eumseong (KR): Korea Consumer Agency; 2024. Available from: https://www.kca.go.kr/eng/synapviewer.do?menukey=6007&fno=10040200&bid=00000005&did=1003570544. Cited 2025 Nov 13.
- 29.Gaw CE, Chounthirath T, Smith GA. Nursery product-related injuries treated in United States Emergency Departments. Pediatrics. 2017;139(4). 10.1542/peds.2016-2503 [DOI] [PubMed]
- 30.Jimenez de Domingo A, Rubio Garcia E, Maranon Pardillo R, Arias Constanti V, Frontado Haiek LA, Soriano Arola M, et al. Epidemiology and risk factors in injuries due to fall in infants under one year-old. An Pediatr. 2017;86(6):337–43. 10.1016/j.anpedi.2015.12.004. [DOI] [PubMed]
- 31.Ibrahim NG, Wood J, Margulies SS, Christian CW. Influence of age and fall type on head injuries in infants and toddlers. Int J Dev Neurosci. 2012;30(3):201–6. 10.1016/j.ijdevneu.2011.10.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Wang D, Zhao W, Wheeler K, Yang G, Xiang H. Unintentional fall injuries among US children: a study based on the National Emergency Department Sample. Int J Inj Contr Saf Promot. 2013;20(1):27–35. 10.1080/17457300.2012.656316. [DOI] [PubMed] [Google Scholar]
- 33.Margulies SS, Thibault KL. Infant skull and suture properties: measurements and implications for mechanisms of pediatric brain injury. J Biomech Eng. 2000;122(4):364–71. 10.1115/1.1287160. [DOI] [PubMed] [Google Scholar]
- 34.Ibrahim NG, Margulies SS. Biomechanics of the toddler head during low-height falls: an anthropomorphic dummy analysis. J Neurosurg Pediatr. 2010;6(1):57–68. 10.3171/2010.3.PEDS09357. [DOI] [PubMed] [Google Scholar]
- 35.U.S. Consumer Product Safety Commission. Safety Standard for Baby Changing Products. U.S. Consumer Product Safety Commission. 2016. https://www.federalregister.gov/documents/2018/06/26/2018-13556/safety-standard-for-baby-changing-products. Accessed January 26, 2025.
- 36.Pike I, Richmond S, Rothman L, Macpherson AK. Canadian Injury Prevention Resource: An Evidence-informed Guide to Injury Prevention in Canada: Parachute; 2015.
- 37.Posner JC, Hawkins LA, Garcia-Espana F, Durbin DR. A randomized, clinical trial of a home safety intervention based in an emergency department setting. Pediatrics. 2004;113(6):1603–8. 10.1542/peds.113.6.1603. [DOI] [PubMed] [Google Scholar]
- 38.Kendrick D, Young B, Mason-Jones AJ, Ilyas N, Achana FA, Cooper NJ, et al. Home safety education and provision of safety equipment for injury prevention. Cochrane Database Syst Rev. 2012;2012(9):CD005014. 10.1002/14651858.CD005014.pub3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Kendrick D, Illingworth R, Woods A, Watts K, Collier J, Dewey M, et al. Promoting child safety in primary care: a cluster randomised controlled trial to reduce baby walker use. Br J Gen Pract. 2005;55(517):582–8. [PMC free article] [PubMed] [Google Scholar]
- 40.European Committee for Standardization (CEN). Child use and care articles — Changing units for domestic use — Part 1: Safety requirements. Brussels, Belgium: European Committee for Standardization; 2014.
- 41.Dewan MC, Mummareddy N, Wellons JC 3rd, Bonfield CM. Epidemiology of Global Pediatric Traumatic Brain Injury: Qualitative Review. World Neurosurg. 2016;91(497–509):e1. 10.1016/j.wneu.2016.03.045. [DOI] [PubMed] [Google Scholar]
- 42.Rivara FP, Koepsell TD, Wang J, Temkin N, Dorsch A, Vavilala MS, et al. Incidence of disability among children 12 months after traumatic brain injury. Am J Public Health. 2012;102(11):2074–9. 10.2105/AJPH.2012.300696. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Babikian T, Merkley T, Savage RC, Giza CC, Levin H. Chronic aspects of pediatric traumatic brain injury: review of the literature. J Neurotrauma. 2015;32(23):1849–60. 10.1089/neu.2015.3971. [DOI] [PubMed] [Google Scholar]
- 44.Son D, Ahn KO, Park HA, Park JO. Factors associated with parental knowledge and attitudes toward pediatric concussions in Korea. Clin Exp Emerg Med. 2024;11(4):372–8. 10.15441/ceem.23.155. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary Figure 1. Joinpoint analysis of annual trends in diaper change-related fall injuries among cases aged <3 years (corresponding to Figure 2A).
Supplementary Figure 2. Joinpoint analysis of annual trends in diaper chage-related falls among fall-related TBI cases aged <3 years (corresponding to Figure 2B).
Supplementary Table 1. Logistic regression analysis of factors associated with skull fracture in fall injuries among children aged <3 years.
Data Availability Statement
The data that support the findings of this study are available from Korea Disease Control and Prevention Agency (KDCA) but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of KDCA.