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Abstract

Background:

Childhood injuries, particularly falls, are a significant public health concern in Low- and Middle-Income Countries (LMICs). In 2021, falls among persons less than 18 years was estimated to be approximately 350,000 with Low- and Middle-Income Countries mostly affected. This study aims to assess the risk factors associated with falls among children in Ghana using data from multiple teaching hospitals.

Design and methods:

A cross-sectional study was conducted using data from four tertiary teaching hospitals in Ghana. The study included 1555 children under 18 years who presented with unintentional injuries between January 2017 and December 2020. Generalized logistic regression was used to identify risk factors for falls.

Results:

Falls were the predominant injury mechanism, accounting for 55% of all reported injuries. Children aged 5–12 years constituted the largest proportion (47%) of fall cases, with males (69%) experiencing falls more frequently than females (31%). Urban residents accounted for 64% of fall injuries compared to rural (22%) and peri-urban (14%) areas. After adjustment for confounders, younger age groups showed significantly higher falls risk: infants (aRR = 1.16), toddlers (aRR = 1.61), and preschoolers (aRR = 1.46) compared to adolescents. Being Male (aRR = 1.16) and guardian’s tertiary education level (aRR = 1.46) were also identified as significant risk factors of fall.

Conclusions:

This study identified age, gender, and guardian’s education level as significant risk factors for childhood falls in Ghana. These findings provide insight for targeted interventions to reduce fall-related injuries among children in Ghana and similar LMICs.

Keywords

children unintentional injury falls Ghana

Introduction

Childhood injuries represent a global public health crisis, exacting a heavy toll on families and communities worldwide.¹ The Global Burden of Disease estimated falls among children and aldolescent to be approximately 350,000 in 2021,² with about one-third disproportionately affecting Low- and Middle-Income Countries (LMICs).^2–4 Children account for nearly half of the total global disability-adjusted life years (DALYs) lost due to falls.⁵ This disparity though has attracted some interventions, still requires further need for targeted interventions.

Ghana, like many sub-Saharan African countries, faces the dual challenges of inadequate injury surveillance systems and weak enforcement of child safety regulations.⁶ With children under 18 comprising approximately one-third of Ghana’s population, safeguarding their well-being is a critical area for intervention.⁷ Previous study in Ghana, although limited to household injuries among rural Ghanaian children,⁶ identified falls as the predominant causes of household unintentional injuries with a prevalence of 16.0%. A subsequent study by Gyedu et al.⁸ explored factors associated with childhood falls, revealing lower fall risks for girls compared to boys, and higher risks for children whose caregivers engaged in non-salaried work.

The existing research largely focuses on falls occurring in rural areas, leaving a gap in understanding childhood injuries by fall in peri-urban and urban settings.^6,8 Additionally, previous studies relied on single-center data limiting generalizability across Ghana’s diverse healthcare landscape⁹ and as well unexplored the influence on the education of the primary caregiver despite its influence on supervisor.¹⁰ This study aims to characterize childhood fall risk factors and examine the relationship between guardian education and fall risk in Ghana by using multi-facility injury surveillance data from four major teaching hospitals spanning diverse geographic and demographic contexts. Understanding childhood fall risk factors is essential for developing targeted interventions that can reduce injury burden, healthcare costs, and long-term disability in Ghana and similar LMICs.

Literature Review

Childhood falls represent one of the leading causes of injury-related morbidity and mortality worldwide.⁵ The burden is particularly pronounced in LMICs, where healthcare infrastructure limitations and prevention strategies are often inadequate.^4,11 Studies from various global contexts have consistently demonstrated that falls disproportionately affect younger age groups, with children under 5 years experiencing the highest rates.^12,13 Studies in high-income countries have identified several consistent risk factors for childhood falls, including age, gender, socioeconomic status, and environmental factors.^11,14 Studies from the United States and Europe have shown that boys are at higher risk than girls, attributed to behavioral differences and risk-taking tendencies.^15,16 However, the applicability of these findings to African contexts remains unclear due to different socioeconomic, cultural, and environmental factors. This is due to limited studies on childhood falls in sub-Saharan Africa.^3,17 The few existing studies from Nigeria¹⁸ and South Africa¹⁹ have shown varying patterns of childhood injuries, suggesting that contextual factors significantly influence injury epidemiology. In Ghana specifically, injury surveillance remains underdeveloped.^4,11 Findings from studies by Gyedu et al.^6,8 have provided some insights into household injuries such as falls among rural children. However, multi-center data covering diverse geographical settings remain lacking. This gap limits the development of evidence-based childhood fall injury prevention strategies tailored to the Ghanaian context.

Methods

Study design and setting

This study adopted a cross-sectional research design, which allows for the examination of relationships between variables at a specific point in time. This design was chosen because it efficiently captures prevalence data and associated factors simultaneously, making it appropriate for identifying risk factors associated with childhood falls across multiple locations. The study was conducted in Ghana, a West African country with a population of approximately 32 million people.⁷ Clinical data was obtained from four tertiary teaching hospitals in Ghana: Korle-Bu Teaching Hospital (KBTH) in Accra, the nation’s largest (2000-bed) referral center; Komfo Anokye Teaching Hospital (KATH) in Kumasi, a 1200-bed facility serving approximately 10 million people in the Ashanti Region; Tamale Teaching Hospital (TTH), the north’s sole 800-bed teaching hospital covering approximately 4 million people; and Cape Coast Teaching Hospital (CCTH), a 400-bed referral center for about 5.8 million across the Central, Western, and Western North regions.⁷ These institutions were selected due to their status as major referral centers, providing a diverse patient population from various regions of Ghana.

Study population and sampling

The study population comprised children under 18 years who presented with unintentional injuries at the selected hospitals between January 2017 and December 2020.

Inclusion and exclusion

The study included children under 18 years who presented with unintentional injuries (including falls, road traffic accidents, burns, poisoning, and other accidental injuries) at any of the four participating teaching hospitals between January 2017 and December 2020. Only cases with available primary injury diagnosis and mechanism documented in the medical records were considered for inclusion in this study.

Children with intentional injuries such as self-harm or assault, cases where the injury mechanism could not be clearly determined, and instances where the primary presenting complaint was not injury-related were excluded. Additionally, cases with incomplete data on age and injury mechanism variables were excluded to prevent misclassification in our analyses. From the initial 2196 records identified during the study period, 641 records (29.2%) were excluded due to incomplete data on age, resulting in a final sample of 1555 participant records for analysis.

Data collection

Data were extracted from the electronic medical record systems of the participating hospitals. Each hospital maintains a comprehensive database of patient information, including trauma cases. Key variables extracted for this study included demographic data, injury characteristics, clinical presentation details, and outcome measures. Data quality was ensured through regular training of hospital staff on electronic medical record data entry, periodic data quality audits conducted by hospital data management teams and cross-checking of extracted data against physical records when necessary.

Key variables definition

Injury mechanisms:

Falls: Injuries resulting from a sudden, unintentional descent from a higher height to a lower level.²⁰

Settlement types⁷:

Urban: Densely populated areas with developed infrastructure, typically cities and large towns as defined by the Ghana Statistical Service.

Rural: Sparsely populated areas characterized by agricultural landscapes and limited infrastructure as defined by the Ghana Statistical Service.

Peri-urban: Transitional zones between urban and rural areas, often experiencing rapid population growth and mixed land use as defined by the Ghana Statistical Service.

Data management and analysis

Data was downloaded, cleaned and coded from a secure electronic database with stringent quality control measures ensuring the accuracy, consistency, and integrity of the information. These measures included thorough validation checks, identifying and rectifying inconsistencies, missing values, and outliers thereby fortifying the robustness of the dataset for subsequent analyses. Statistical software, R v4.4.1 was used for data analysis. Descriptive statistics, including frequencies, proportions, means, standard deviations, and chi-square test were employed to summarize demographic and injury-related characteristics. Generalized linear mixed model using modified Poisson regression with robust standard errors.²¹ The model was run with “hospital” as random effect component, was conducted to identify risk factors of falls among children less than 18 years. Statistical significance was set at p < 0.05, and all tests were two-tailed with 95% confidence intervals.

The reporting of this study conforms to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) statement²² (See Supplemental File 1).

Ethical considerations

The Committee on Human Research Publications and Ethics (CHRPE) at Kwame Nkrumah University of Science and Technology granted ethical clearance for this study, under the reference number CHRPE/AP/290/19. Institutional management boards from each participating hospital in Ghana, including Korle-Bu Teaching Hospital, Komfo Anokye Teaching Hospital, Tamale Teaching Hospital, and Cape Coast Teaching Hospital, provided permissions prior to this approval. As this was a retrospective review of secondary data, the need for individual patient consent was waived. All data were de-identified prior to analysis to ensure patient confidentiality.

Result

Demographic characteristics

The study recorded 1555 children under 18 years. Table 1 presents the demographic and clinical characteristics of the study population. The mean age of participants was 7.8 years (SD = 4.2 years), with children aged 5–12 years constituting the largest proportion (48%) of cases of injuries reported. Injuries caused by falls comprised 55% of injuries reported.

Table 1.

Socio-demographics of Study Participants.

Variable	Frequency N = 1555 (%)
Age (years)	7.8 (4.2)^a
Infant (0–1)	70 (4.5)
Toddler (1–3)	188 (12)
Preschooler (3–5)	280 (18)
Child (5–12)	744 (48)
Adolescent (12–17)	273 (18)
Sex
Female	516 (33)
Male	1039 (67)
Guardian’s educational level
No formal education	292 (19)
Primary	207 (13)
Junior high school	406 (26)
Senior high school	330 (21)
Tertiary	320 (21)
Day category
Weekday	1094 (70)
Weekend	461 (30)
Settlement
Rural	379 (24)
Peri-urban	228 (15)
Urban	948 (61)
Falls
Yes	863 (55)
No	692 (45)

Mean (SD).

Distribution of falls

Falls were significantly associated with age (p < 0.001), with the highest incidence among children aged 5–9 years (47%), whiles infants (5.7%) had the lowest incidence (see Table 2). Males accounted for 69% of cases compared to 31% for females (p = 0.036). Falls were more common on weekdays (72%) than weekends (28%). Settlement type showed a significant influence, with urban areas having the highest incidence of falls (64%), followed by rural (22%) and peri-urban (14%) areas (p = 0.010).

Table 2.

Distribution of falls across Socio-demogrpahics.

Variable		Falls		p-Value^b
	N	Yes N = 863^a (%)	No N = 692^a (%)
Age (years)	1555			<0.001
Age group	1555
Infant (0–1 years)		49 (5.7)	21 (3.0)
Toddler (1–3 years)		129 (15)	59 (8.5)
Preschooler (3–5 years)		172 (20)	108 (16)
Child (5–12 years)		403 (47)	341 (49)
Adolescent (12–17 years)		110 (13)	163 (24)
Sex	1555			0.036
Female		267 (31)	249 (36)
Male		596 (69)	443 (64)
Guardian’s educational level	1555			<0.001
None		114 (13)	178 (26)
Primary		111 (13)	96 (14)
Junior high school		224 (26)	182 (26)
Senior high school		192 (22)	138 (20)
Tertiary		222 (26)	98 (14)
Day category	1555			0.2
Weekday		620 (72)	474 (68)
Weekend		243 (28)	218 (32)
Settlement	1555			0.010
Rural		190 (22)	189 (27)
Peri-urban		118 (14)	110 (16)
Urban		555 (64)	393 (57)

n (%).

Pearson’s Chi-squared test.

Risk factors

The analysis revealed that male children had a higher likelihood of falls compared to females, with an adjusted relative risk (aRR) of 1.16 (95% CI: 1.01, 1.35). Age was also a significant factor, with infants, toddlers, and preschoolers showing much higher adjusted relative risk of falls (aRRs of 1.69, 1.61, and 1.46, respectively) compared to adolescents. Additionally, children whose guardians had tertiary education were at the highest risk, with an aRR of 1.46 (95% CI: 1.12, 1.90) compared to those with uneducated guardians. Fall occurring on a weekday or weekday did not significantly influence the occurrence of falls (aRR = 0.99, 95% CI: 0.83, 1.12), and while urban children had higher unadjusted relative risk of falls, this association was still not significant after adjustment (aRR = 1.04, 95% CI: 0.87, 1.24). These results are summarized in Table 3.

Table 3.

Risk factors of falls among children under 18 years.

Variable	RR^a	95% CI^b	p-Value	aRR^c	95% CI^b	p-Value
Sex
Female	1			1
Male	1.14	0.99, 1.32	0.072	1.16	1.01, 1.35	0.040
Age group
Infant (0–1 years)	1.67	1.19, 2.35	0.003	1.69	1.20, 2.36	0.002
Toddler (1–3 years)	1.60	1.24, 2.07	<0.001	1.61	1.25, 2.09	<0.001
Preschooler (3–5 years)	1.47	1.15, 1.86	0.002	1.46	1.15, 1.86	0.002
Child (5–12 years)	1.32	1.07, 1.63	0.010	1.32	1.07, 1.64	0.009
Adolescent (12–17 years)	1			1
Guardian’s educational level
None	1			1
Primary	1.21	0.90, 1.63	0.2	1.22	0.91, 1.64	0.2
Junior high school	1.18	0.90, 1.54	0.2	1.20	0.91, 1.57	0.2
Senior high school	1.25	0.95, 1.63	0.11	1.25	0.95, 1.64	0.11
Tertiary	1.48	1.14, 1.92	0.004	1.46	1.12, 1.90	0.005
Day category
Weekday	1			1
Weekend	0.95	0.82, 1.11	0.5	0.97	0.83, 1.12	0.6
Settlement
Rural	1			1
Peri-urban	1.03	0.81, 1.30	0.8	1.01	0.80, 1.27	>0.9
Urban	1.11	0.94, 1.32	0.2	1.04	0.87, 1.24	0.7

RR = Relative risk.

CI = Confidence interval.

aRR = Adjusted relative risk.

Discussion

This study aimed to assess the risk factors associated with falls among children in Ghana using data from multiple teaching hospitals. In this study, infants had a much higher adjusted relative risk of experiencing falls (aRR = 1.69, 95% CI: 1.20, 2.36), as did toddlers (aRR = 1.61, 95% CI: 1.25, 2.09), and preschoolers (aRR = 1.46, 95% CI: 1.15, 1.86), compared to adolescents. The increasing risk of injuries across age groups can be attributed to a combination of physical, cognitive, and social factors during this stage of development. Physically, children have better mobility and independence compared to toddlers, but lack the maturity and coordination of adolescents.¹² Mentally, this age group is very curious and exploratory but their hazard awareness and risk perception are still developing.¹³ These findings also align with global patterns observed in high-income countries where younger children are at higher risk for falls with an incidence rate of 11.4²³ and odds of 4.6²⁴ due to their developmental stage characterized by increased mobility but limited hazard recognition.^12,13 The consistency of these patterns across diverse geographical and socioeconomic contexts suggests developmental factors are universal determinants of fall risk.

In addition, males were found to be at a higher risk of falls compared to females, with an aRR of 1.16 (95% CI: 1.01, 1.35). This corroborate findings from other studies on gender disparities in pediatric injury prevalence.^8,11,14 Girls are noted to have a 6% less risk of falling compared to boys in study conducted at the Children’s Healthcare of Atlanta of the state of Georgia.²⁵ Compared to girls, boys tend to exhibit greater impulsivity, overestimation of abilities, and attraction to risk-taking which heightens injury vulnerability¹⁵ Additionally, gender norms encourage vigorous, adventurous and competitive play among boys which raises exposure to hazards.^13,15,16

The study further identified that children whose guardians had a tertiary education compared with guardians who had no education were at the highest risk of falls, with an RR of 1.48 (95% CI: 1.14, 1.92) and an aRR of 1.46 (95% CI: 1.12, 1.90). Similar to this study, parental supervision and restrictions tend to decrease among the educated who are engaged more at work.¹⁶ In the Ghanaian setting, jobs are gender- and age-associated, with younger mothers and female guardians more likely to assume informal occupational roles or remain at home, thus providing closer supervision.^16,26 Conversely, older or male guardians are more likely to be employed in formal or physically demanding occupations, which limit their availability and attentiveness to children’s activities.^26,27

Limitations

The strength of this study lies in its multi-center design incorporating data from four major teaching hospitals across different regions of Ghana, which enhances the generalizability of findings. The large sample size (n = 1555) provides robust statistical power for identifying risk factors. Additionally, the study’s comprehensive analysis of sociodemographic and contextual factors offers valuable insights for targeted injury prevention strategies in similar LMIC settings. Again, we acknowledge potential limitations in our methodology, including the possibility of selection bias due to the tertiary hospital-based sampling, which may not fully represent community-level injury patterns. Our study also does not capture injuries treated in primary care settings or those not seeking medical attention, potentially underestimating the true burden of pediatric falls.

Conclusion

This study highlights that infants, toddlers, preschoolers are at higher risk of falls compared to adolescents. Males were found to be more susceptible to falls than females, possibly due to gender-specific behaviors and societal norms. These results underscore the need for age-specific and gender-sensitive fall prevention strategies in Ghana. Additionally, awareness programs targeting educated parents about the importance of child supervision may be beneficial.

Supplemental Material

sj-docx-1-phj-10.1177_22799036251365570 – Supplemental material for Risk factors for childhood falls in Ghana: A multi-center cross-sectional study

Supplemental material, sj-docx-1-phj-10.1177_22799036251365570 for Risk factors for childhood falls in Ghana: A multi-center cross-sectional study by Jacob Solomon Idan, Emmanuel Kweku Nakua, Shadrach Mintah, Joycelyn Serwaa Stevens and Eric Adjei-Boadu in Journal of Public Health Research

Footnotes

Acknowledgements

Authors thank all staff who made contributions to the data collection.

Author note

The study was conducted as part of the authors’ employment.

ORCID iD

Jacob Solomon Idan

Ethical considerations

Consent for publication

Not applicable.

Author contributions

J.S.I. participated in study design, conducted the data analysis, results interpretation, and drafted the manuscript. E.N. conceived the study, participated in study design, supervised data analysis, results interpretation, and reviewed the manuscript. S.M. participated in data collection, data analysis, results interpretation, and reviewed the manuscript. J.S.S. participated in study conception, data collection, results interpretation, and critically reviewed the manuscript. E.A.B supervised data analysis, results interpretation and reviewed the manuscript. All authors read and approved the final manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability statement

The datasets generated and analyzed during the current study are available.

Supplemental material

Supplemental material for this article is available online.

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