Using a large nationally representative cohort and after accounting for several important confounders, we found that a very weak sense of community belonging increased the risk of premature death. The large sample size and complete linkage allow a detailed study of the influence of community belonging by life stage. This study uses nationally representative survey data from over 475 000 individuals linked to a complete vital statistics database, making it the largest such study. Furthermore, this focus on premature mortality as the outcome, which has not been studied in relation to community belonging, is particularly relevant for public health because such deaths are considered avoidable and reducible through preventative interventions, policy and addressing the social determinants of health. Our results did not point to a graded relationship wherein progressively weaker levels of belonging further increase the risk of premature mortality, especially among the older two age groups.

Although there are fewer studies specifically examining the impact of premature mortality, our results agree with published literature showing low sense of community belonging is associated with an increased risk in all-cause mortality33 34 and the differential findings among older ages.12 35 The findings also support the recent focus on social prescribing, which emphasises that mechanisms to increase connections and belonging have a role in the clinical setting to improve outcomes.36 There are several reasons for the observed variability across age groups. Community belonging could impact health via both behavioural and psychobiological factors. For instance, a tightly knit community network could improve access to relevant health services via increased knowledge exchange (eg, learning about local vaccination programmes or where to purchase affordable fresh produce) and via social support (eg, sharing transportation to appointments), social conformity norms could encourage positive and deter negative health behaviours (eg, quitting smoking), and improved interpersonal psychological support could reduce inflammatory stress responses related to loneliness.37–39 For example, in the case of a person dealing with cancer, a strong community network can provide additional encouragement to seek healthcare early, and a neighbourhood walking group can support the maintenance of physical activity levels.

However, not all social networks are created equal in terms of benefits conferred. Research has shown that the compositional characteristics of a social network (such as its diversity, size or degree of intimacy), can offer differential benefits in terms of type and magnitude.3 40 41 For instance, Legh-Jones and Moore42 distinguished the social networks of Canadian adults across three features: reach, range and diversity, and examined how these features were differentially associated with physical activity levels. They found that participants with a more diverse network were less likely to be physically inactive, whereas neither reach nor range components were found to be influential.42 Similarly, Li and Zhang41 found that network diversity was associated with the most positive health indicators and that friend-focused networks yielded more benefits in terms of physical health outcomes, but the same was not true for psychological health outcomes.41

Some evidence further suggests that in addition to the magnitude of the effect, network compositions can influence the direction of impact. In other words, some network features have been shown to be associated with negative health outcomes. In their study of European older adults, Litwin and Stoeckel43 defined six social networks according to their size and inclusion of proximal or distal family members, friends or other social contacts.43 Of the six network types, one was negatively associated with well-being and characterised as being larger than average, having below-average contact frequency, and mostly consisting of people living geographically close, neither friends nor family. Regarding our results, perhaps the relevance of certain network compositions to evaluations of community belonging changes as we age. For instance, having a geographically close but intimately distant network may contribute to a strong sense of community belonging in old adulthood but not in early adulthood. Additionally, given that social identities and health status do not remain static throughout life, how certain compositions impact health may also change as we age.44 However, there is limited insight into this complex dynamic, seeing as the majority of relevant studies only examine one point in time.29 30 32 Additionally, it has been proposed that in addition to positive benefits, there are some potentially negative aspects to community belonging, which possibly promote negative health outcomes. This can occur by restricting freedom due to excessive informal control, possible exclusion of out-group members, straining group members by expectations, supporting certain risky behaviours and ‘downlevelling’ norms so that individuals trying to break free from negative actions are penalised.45 46 As an illustrative example of community belonging’s dualistic nature on health outcomes, close neighbours can be a source of emotional and social support for one another. Yet, if the exchange of support occurs in contexts where there is smoking and/or excessive unhealthy food and alcohol intake, the impact of community belonging on health outcomes may be both positive and negative. These theoretical perspectives might help explain why a strong sense of community belonging was associated with an elevated risk of mortality in some age groups.

The effect of community belonging on premature mortality is likely modified by the complex interplay of different social roles with physical and psychological changes. In this way, network types that confer weaker or even negative impacts on well-being, and how relevant these are to evaluations of community belonging may be associated with specific life stages or roles, which could explain why we did not observe a consistent dose-response across the age groups. Additionally, survival bias may be contributing to these seemingly contradictory findings in older age, as well as the different causes of death. The most common causes of death differ across each life stage, and the positive effects of a strong sense of community belonging may be more potent for some causes than others. Notably, the largest magnitudes of effects were observed among the youngest age group, whose most common causes of death were considerably different from that of the older two life stages (ie, intentional self-harm and accidental poisoning compared with lung cancer and myocardial infarction). The mechanisms through which community belonging improves health are likely particularly important to mental health, which stresses the importance of strengthening community connections within the context of a growing mental health burden.

There are limitations that are important to consider. First, the observational nature of this study is such that we cannot rule out all risks of bias, particularly confounding and information bias. We did take all steps to account for these biases in our study design and statistical analyses. In addition, we were very transparent in our adjustments to ensure the reader could identify the impacts of such adjustments. Our sensitivity analysis for unmeasured confounding demonstrated that it would most likely affect the findings in the 36–55 and 56–70 age groups. Second, the findings may have been affected by selection bias; that is, people who are already sick and are at higher risk for premature death are those who may be less able to form or maintain social connections—or, conversely, may make greater efforts to seek out and develop their social connections and community belonging. To further limit the effect of poor baseline health, we conducted several sensitivity analyses, including running lag models and additionally adjusting for mental and general health, and found that the results were not affected. Third, reported community belonging is a subjective measure and was only recorded at baseline. It is possible that the sense of community belonging could have changed over the 5 years, although we have found this measure stable over time. Fourth, although we could pool twelve years of survey respondents and our models adjusted for the survey cycle, the age-stratified subsamples nonetheless came from different birth cohorts. As such, it is possible that age-graded differences can be attributed to cohort rather than age effects. Despite these limitations, this study uniquely contributes to a growing body of evidence linking community belonging with key population health and health system outcomes with the ability to adjust for a wide range of confounders. The individual-level linkage between a comprehensive health survey and reliable administrative health data allowed us to examine community belonging concerning premature mortality, a key population health indicator. Using a large nationally representative sample improved the generalisability of findings, and pooling survey cycles created a large enough sample size to meaningfully examine the association across three distinct life stages, which has been lacking in the existing literature. Compared with similar cross-sectional studies, our cohort design further clarified temporality and reduced biases seen in prior studies.