To what extent does spatial variation in ill health reflect the influence of contextual factors such as differences in social trust, density of social network, and varying social support? To answer this question it is not enough to have individual and neighbourhood level data. It is also necessary to have an idea about the scale at which social influence on health are at work. In this paper we will demonstrated that changes in neighbourhood scale-that is, shifts in the number of nearest neighbours that are used to compute contextual variables-can lead to large shifts in the values for contextual variables that are assigned to different individuals. This implies that estimates of neighbourhood effects are not invariant to changes in scale. We also present results from an empirical analysis of scale dependent neighbourhood effects using Swedish longitudinal register--based data on sickness--benefit recipiency as an indicator of onset of and recovery from illness. Sickness--insurance data is used because, for confidentiality reasons, our register base data set contains limited information on health outcomes. Our first sample consists of individuals that have stayed healthy and in work for a three--year period, some of whom are affected by illness during the fourth year. Our second sample consists of those in the first group that fall ill during the fourth year, some of who return to good health in the fifth year. In order to compute the contextual variables for different scale level we use the Equipop software.