The impact of neighbourhood effects and socio-economic status on health over individual life courses
Even in an egalitarian country such as the Netherlands, the difference in life expectancy between the high and low educated is 7 years. Individual health is not only influenced by individual socio-economic status, such as education, but also by socio-economic characteristics of and social ties within the neighbourhood of somebody’s place of residence.
Traditional models in health economics usually view agents as isolated entities, ignoring the existence of social relations and interdependence. However, agents are rooted into networks of relations that provide opportunities and constraints, such as information flows, and the provision and enforcement of norms (Manski 1993; Brock & Durlauf 2001). The set of interactions between individuals or groups of individuals determines a social structure (social network) that has profound effects on individual behaviour, among which health behaviour. Due to these network effects, the geographical concentration of risk factors can lead to an emergent collective behaviour that empirically translates into a structure of correlation in the data, known as cross-sectional or spatial dependence (Elhorst 2003, 2014).
Except for education, attained in the first phase of the life course, most individual socio-economic indicators do not remain stable over time but are affected by changes in health and residential moves. In fact, health, socio-economic status and residential socio-economic status trajectories are interdependent. Poor health negatively affects socio-economic status and impedes residential moves; low socio-economic status of an individual or the residential neighbourhood tends to increase health problems (Prinz et al 2018); and low socio-economic individuals and individuals with poor health are overrepresented in low socio-economic neighbourhoods.
Despite existing empirical evidence in favour of the relation between socio-economic status and health, its causal interpretation has been challenged. A major problem is that this relation may be confounded by factors that influence both socio-economic status and health simultaneously (Fletcher 2015; Grossman 2015; Bijwaard et al 2015, 2017, 2019; Bijwaard & Jones 2019). Surprisingly little research has also explored the causal mechanism of education, or genetic, social-cultural and other early life socio-economic indicators, on health later in life when controlling for intermediate variables such as income, occupation, and health behaviour.
Even less do we know about the causal impact of residential deprivation, especially the fact that individuals self-select themselves into neighbourhoods based on individual attributes, including health (Diez-Roux 2001; Arcaya et al. 2016; Balsa & Díaz 2019). This process of social interaction between individuals at the neighbourhood level may be considered as another source of confounding. Besides, neighbourhoods may change because of policy interventions, shifts in the population composition, or macro-level social and economic developments. When examining the impact of neighbourhood effects on the relation between socio-economic status and health, we should thus be aware that neighbourhoods also change. Processes and dynamics ongoing in a neighbourhood can hinder or enhance the health impact of specific neighbourhood characteristics.
Three phases of the life course
An abundant economic literature has provided evidence that early life circumstances affects outcomes later in life, including socio-economic status and health (Currie 2009, Almond et al. 2018). Studies for the UK (Case et al. 2005) and for the US (Case & Paxson 2008) show that good health during early childhood leads to a higher economic status later in life. However, little is known on how residential social interaction affects this relation. It may have an immediate influence as children’s education choice is affected by their peers. In the long run education shapes the socio-economic and therefore health trajectories. Information on children’s health from Lifelines will be used to investigate the immediate impact of social interaction. The socioeconomic indicators of the family into which the individual was born and information around birth will allow investigating the long run impact of early life environment on health later in life.
Adverse childhood experiences in early life and current neighbourhood disadvantage have comparable associations with the co-occurrence of behavioural risk factors in mid-life. The long-term health effects of childhood experiences may be related to differences in health-promoting parenting, such as financial difficulties or parental distress. The initiation and maintenance of healthy behaviours is more difficult for people living in disadvantaged rather than affluent neighbourhoods because they are exposed to behaviours such as smoking or public drinking in their daily lives. Exposure to social class related stressors in childhood may also affect health in the long-term. For example, low safety due to high crime rates may decrease physical activity.
Employment and partnership behaviour are the two most prevalent life course transitions in mid-life. Poor health may lead to more unemployment and unemployment may lead to worse health. It has been established that health shocks have negative labour market effects. Detrimental labour market shocks also influence health (both mental and physical). Divorce and widowhood are likely to be related to both health and labour market behaviour. On the one hand, living with a partner has been shown to have a protective effect on health as married and cohabiting individuals are more likely to adopt healthier lifestyles, suffer from lower levels of psychological stress, and engage in less risky behaviour (Gardner & Oswald 2004, Murray 2000). On the other hand, poor health reduces the chance to find a partner and to remain married. Little attention has been given to the importance of early life socio-economic status, like educational attainment and, residential social interaction in shaping these relations, affecting both labour market behaviour and the health process.
Retirement is a major life course transition later in life. Just as health affects retirement, retirement also affects health. Understanding health effects of retirement is important for the evaluation of social and economic impacts of extending working lives. Due to this mutual relationship, the health effects of retirement remain unclear (Atalay & Barrett 2014; Coe & Zamarro 2011; Hessel 2016). Longitudinal studies have reported positive mental health effects of retirement, whereas findings concerning other health outcomes have been mixed (van der Heide et al. 2013). Recent studies have examined health trajectories using measurements both before and after retirement, and these suggest that retirement is followed by improved, or at least not worsening, trajectories of health. This project addresses the health-employment (labour force participation) nexus around retirement accounting for health (van der Heide et al. 2013) and residential trajectories from early life.
Mortality is another major life event later in life. Economic theories largely ignore social ties and norms as determinants of mortality, while many empirical papers suggest that peers are a key determinant of behaviours such as eating, smoking, and drinking. However, existing research rarely considers the effects of networks, or conversely isolation, on health directly, while there is empirical evidence that social and community ties and mortality are related (Holt-Lunstad et al. 2010). For example, education attained may affect the size and quality of social connections and integration into the communities in which people live. There are also important differences across gender in how ties are formed and in the type of ties they have. Men and women also appear to be differently affected by social connections. For example, the effect of marriage on mortality is very different: marriage lowers mortality more among men than among women, and widowhood increases mortality more for men than for women (Smith & Christakis 2008).
Up to now, the impact of residential socio-economic status and social interaction in shaping individual socio-economic status and health in these three life course phases are largely unexplored. All analyses will account for endogeneity due to mutual relationships of the socio-economic status and the residential area in a dynamic way.