Background The goal of this thesis is to explain and examine successful ageing using disease conditions, functional capacity, life engagement, and health-related quality of life using longitudinal data, and to examine New Zealand older adults’ successful ageing trajectories. For an individual, successful ageing is defined in terms of having fewer diseases or no multimorbidity, high functional capacity, active life engagement, and good health-related quality of life. As successful ageing is on a continuum, it can be best assessed through data obtained from longitudinal studies.

Methods A secondary analysis was conducted based on data from the ongoing New Zealand Health, Work and Retirement (NZHWR) Study. In the NZHWR study, 1,433 older adults recruited at the baseline in 2006 and followed up for 12 years through seven waves of data collection were included. A metric of successful ageing was constructed through the addition of the number of disease conditions, physical functioning, role emotional, life engagement, and physical and mental component summary scores. This gave a successful ageing score ranging from zero to six. Latent growth curve modelling (LGCM) was used to assess the growth factors (intercept and rate of change (slope)) of successful ageing trajectories of older adults. Multiple indicators, multiple causes (MIMIC) models were used within the LGCM to examine the effect of age, sex, and ethnicity on the growth factors.

Results The majority of the participants were females (54.6%), New Zealand European (61.3%), and the mean age and standard deviation at the seventh wave were 72.8 years and 4.4 years. The mean successful ageing score was 3.53 in 2006 and decreased by 0.064 every year as a linear function. Those who had a higher successful ageing score at baseline had a slower decline. The mean successful ageing scores were significantly lower at baseline among females than males ( = -0.191, p = 0.013), among those in the older age group than the younger age group ( = -0.021, p = 0.017), and among M¯aori ( = -0.458, p < 0.001), Pacific Peoples ( = -1.490, p = 0.007) compared with New Zealand European. However, age was the only significant predictor in explaining the linear growth trend of successful ageing ( = -0.005, p < 0.001). The fit measures (RMSEA = 0.038, 95%CI: 0.031–0.045, CFI = 0.977, TLI/NNFI = 0.973, SRMR = 0.025) showed that the conditional model fit the data and was better than the null model.

Conclusion Young older adults, males, and New Zealand Europeans were observed to experience successful ageing more. The ethnic differences suggest the possibility of inequalities in the factors that promote successful ageing among New Zealand European and non-European. Factors that promote successful ageing among the ethnic groups in New Zealand need to be identified and culturally appropriate models of successful ageing developed. Ageing is a life-long process, and it can best be explained by taking a life-course approach to the roles policies, early and midlife experiences, and the environment play.