## 4 Discussion
Second, modelling of knee joint kinetics is complex leading to different normalisation techniques, making direct comparisons between studies difficult. Body mass and stature can affect joint kinetics but in a comparison between groups, if there are no differences in physical characteristics, normalisation may not be necessary. When mean values are normalised, however, coefficient of variation, indicated by standard deviation divided by mean (SD/mean), may be the more suitable measure for variability. Joint moment calculation is relative to the length of the segment (i.e., bone) but normalisation by height may cause inaccuracy. Furthermore, joint kinetics are based on 3D biomechanics and there are multiple components to be considered for comprehensive modelling, including muscle forces and contributions from surrounding connective tissues [11]. In non-invasive software simulation, however, the addition of multiple factors can often require extra assumptions for modelling. In the current study,therefore, a relatively simple approach based on inverse dynamics within Visual 3D (C-motion) has been employed to measure knee addiction moment and vertical joint force. Third, other biomechanical factors should be investigated to fully understand the role of joint kinetics in knee OA. One essential component is a sagittal plane analysis of knee joint kinetics involving flexion-extension moment and associated eccentric work and power absorption [30]. Quadriceps and other muscle groups (i.e., hamstrings, calf, plantar flexors and dorsiflexors) have been reported to help impact absorption [12; 30; 31; 32]. It is also necessary to acknowledge that knee joint loading usually has two peaks in a gait cycle, as shown in Figure 1: early and late stance for foot contact and toe-off, respectively. While the current research focused on foot contact mechanics and associated OA risk, the push-off phase of the gait cycle may be equally important, with knee flexion moment considered a key kinetic marker [33]. Connective tissues such as ligaments should also be taken into account to fully describe the causes of OA and in terms of recovery, cartilage resynthesis in addition to mechanical factors relating to OA risks should be the essential aspect [8; 34]. For the future direction of the study about biomechanical gait adaptations to control knee joint kinetics, the limitations of the current study have been addressed here. For the elimination of gender effects on obtained parameters, only the male population has been included in analysis. In future studies, it is necessary to confirm whether the findings of the current study are applicable to the female population. Comparison of healthy young and older individuals was appropriate to address the research aim of whether ageing alone influences joint kinetics associated with OA. While the current research design has identified the OA implications of knee adduction moment and vertical compression force, trailer seniors or older adults with OA symptoms may have different OA-related joint kinetics. The current research thus provides the foundation for future studies to further our biomechanical and biomedical understanding of knee OA. In conclusion, both knee adduction moment and knee joint vertical compression force were found to be larger among the older group. Increased step width and reduced toe-out angle seem to be ageing-related gait adaptations to reduce knee adduction moment. Increased step length was, in contrast, possibly a strategy to reduce knee joint vertical force, which can be attained by an increased foot contact angle. The current outcomes should be used to design future studies to propose practical intervention strategies to minimise OA risk, particularly among older adults. Conceptualization, H.N. and R.B. ; methodology, H.N. ; formal analysis, H.N. ; writing--original draft preparation, H.N. ; writing--review and editing, R.B. ; supervision, R.B. ; project administration, R.B. All authors have read and agreed to the published version of the manuscript.