Virginia Research Day 2021

Area-Level Risk Factors for Sports and Recreational Injuries: A Systematic Review of Studies Applying Multilevel Modeling Techniques Ogunmayowa, O.* and Baker, C. Department of Population Health Sciences, Virginia Tech Problem Results Contact: olutosin@vt.edu

TAKE HOME Neighborhood/area-level socioeconomic status, street connectivity, parks/recreational facilities, and urbanization are risk factors for SR injuries.

➢ The risks of sports and recreational (SR) injuries have continued to increase as participation in SR activities have increased across age groups in the United States (U.S.). ➢ The average annual estimate of SR injury episodes in the U.S. is 8.6 million with about 4 million treated in hospital emergency departments (U.S. CDC). ➢ While this number is significant, SR injuries have been largely under- researched, and ➢ There is still less awareness on how area-level factors (e.g., physical and socioeconomic environment) in addition to individual-level factors (e.g., age, sex, body composition and physical activity) simultaneously and interactively affect SR injury outcomes. ➢ Multilevel Model (MLM) has been presented as an appropriate statistical tool that may help with this need because it enables the simultaneous examination of individual-level and area-level effects on health outcomes. ➢ Therefore, this study reviewed literatures that have examined the effect of area-level risk factors on SR injuries using MLM. ➢ Systematic search of 4 electronic databases (PubMed, CINAHL from EBSCOhost, Sports Medicine and Education Index, and Web of Science) was conducted. ➢ Screen 1510 articles and included 3 in the systematic review. ➢ Eligible Studies: 1) Participants: Studies examined people of all age groups across the world. 2) Exposures: Studies included area-level exposures e.g., physical environment, socioeconomic environment, neighborhood crime levels and safety measures, social capital and social cohesion, and urban-rural geographic location; in addition to individual-level risk factors. 3) Outcome included SR injuries. 4) Data analysis: Studies used MLM techniques. Approach

Characteristics of studies included in the review

Authors and year of publication Simpson, Janssen, Craig, & Pickett. 2005.

Title and journal

Purpose of study

Study design & type of injury data

Study population & number of data level

Age (years) & Male (%) 11-16 years. 46.4 %.

Multilevel analysis of associations between socioeconomic status (SES) and injury among Canadian adolescents. J Epidemiol Community Health . Neighbourhood street connectivity and injury in youth: a national study of built environments in Canada. Inj Prev.

How are individual and area level socioeconomic variables associated with the occurrence of medically- treated, hospitalized, fighting, and sports/recreational injuries among Canadian adoslescents? How is street connectivity associated with injuries among Canadian youths?

Cross-sectional study. Secondary data.

7,235 students. Two levels:

individual/family and school's neighborhood (N=170).

Mecredy, Janssen, & Pickett. 2012.

Cross-sectional study. Secondary data.

9,021 students. Two levels:

11-15 years. 47.5 %.

indidvidual/family and school's neighborhood (N=180).

Gropp, Janssen & Pickett. 2013.

Active transportation to school in Canadian youth: should injury be a concern? Inj Prev.

How is active transportation to school associated with injury in Canadian youth?

Cross-sectional study. Secondary data.

20,076 students in total. Two levels: individual/family and school's neighborhood (N=419).

11-15 years. 36.4 %.

Statistically significant (p < 0.05) area-level effects in final MLM models

Data type for area-level exposure variables

Reported effect estimate and 95% confidence interval OR = 0.81 (0.68, 0.97) OR = 0.80 (0.67, 0.96) OR = 1.64 (1.04, 2.61) OR = 1.64 (1.05, 2.56)

Authors and year of publication

Outcome

Area-level exposure variables with statistically significant effects Average employment income

Effect comparison

Simpson, Janssen, Craig, & Pickett. 2005.

Sport/recreational injury

Ordinal

Next-to-highest vs. highest quarter Next-to-lowest vs. highest quarter Next-to-highest vs. lowest quarter Highest vs. lowest quarter

Injury hospitalization Lone parent families

Ordinal

Less than high school education

Ordinal

OR = 2.11 (1.36, 3.28) Highest vs. lowest quarter

Mecredy, Janssen, & Pickett. 2012.

Street injury during a physical activity

Parks/recreational facilities

Ordinal

OR = 1.69 (1.05, 2.71) Next-to-lowest vs. lowest fifth

PRISMA flow diagram showing the study selection process

Biking/cycling injury Street connectivity

Ordinal

OR = 2.33 (1.28, 4.25) Low vs. high street connectivity

Gropp, Janssen & Pickett. 2013.

Active transportation injuries

Urbanization

Ordinal

OR = 1.64 (1.14, 2.36) Urban vs. rural communities

Summary of Findings

➢ Higher socioeconomic status, higher number of parks/recreational facilities, lower street connectivity, and living or attending schools in urban communities were associated with increased risk of SR injuries after adjusting for individual-level and other area-level risk factors for SR injuries. ➢ All studies were carried out in a single institution in Canada. ➢ All studies focused on adolescents, used cross-sectional study design, and secondary data. References Gropp, K., Janssen, I., & Pickett, W. (2013). Active transportation to school in Canadian youth: should injury be a concern?. Injury prevention , 19 (1), 64-67. Mecredy, G., Janssen, I., & Pickett, W. (2012). Neighbourhood street connectivity and injury in youth: a national study of built environments in Canada. Injury prevention , 18 (2), 81- 87. Simpson, K., Janssen, I., Craig, W. M., & Pickett, W. (2005). Multilevel analysis of associations between socioeconomic status and injury among Canadian adolescents. Journal of Epidemiology & Community Health , 59 (12), 1072-1077.

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