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Objective: The objective was to describe the individual items of the environmental factors and to investigate the relationship between the environmental factors to health conditions, general health and quality of life in people with SCI in South Africa., Methods: Two hundred persons with SCI participated in a cross-sectional survey design. This study formed part of the International Spinal Cord Injury (InSCI) Community Survey. Four major domains, environmental factors, health conditions, general health and quality of life of the survey questionnaire responses, were used for the analysis. Regression models were used to determine the association between the independent variable, which consisted of the specific environmental factors items, and the dependent variables comprising health conditions, general health and quality of life., Results: The commonly reported environmental barriers were public access, lack of short- and long-distance transport and finances. Environmental factors such as public access ( p < 0.001), short- ( p < 0.001) and long-distance transport ( p = 0.001), and friends' ( p = 0.003) and colleagues' ( p < 0.001) attitudes and communication ( p = 0.042) were significantly associated with the presence of secondary health conditions. Finances ( p = 0.026), family attitudes ( p = 0.037) and communication ( p = 0.039) had a significant association with worsened mental health. Services ( p = 0.022) and communication ( p = 0.042) were also significantly associated with decreased general health., Conclusion: The results provide insight into modifiable environmental factors policymakers need to consider or adapt to improve the lives of people with SCI in South Africa with respect to health (secondary health conditions), as well as general and mental health.

This study aimed to investigate the accuracy and reliability of hip and ankle worn Actigraph GT3X+ (AG) accelerometers to measure steps as a function of gait speed. Additionally, the effect of the low frequency extension filter (LFEF) on the step accuracy was determined. Thirty healthy individuals walked straight and walked with continuous turns in different gait speeds. Number of steps were recorded with a hip and ankle worn AG, and with a Stepwatch (SW) activity monitor positioned around the right ankle, which was used as a reference for step count. The percentage agreement, interclass correlation coefficients and Bland-Altmann plots were determined between the AG and the reference SW across gait speeds for the two walking conditions. The ankle worn AG with the default filter was the most sensitive for step detection at >0.6 m/s, whilst accurate step detection for gait speeds < 0.6 m/s were only observed when applying the LFEF. The hip worn AG with the default filter showed poor accuracy (12-78%) at gait speeds < 1.0 m/s whereas the accuracy increased to >87% for gait speeds < 1.0 m/s when applying the LFEF. Ankle worn AG was the most sensitive to measure steps at a vast range of gait speeds. Our results suggest that sensor placement and filter settings need to be taken into account to provide accurate estimates of step counts.