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Non-response is common in longitudinal surveys, reducing efficiency and introducing the potential for bias. Principled methods, such as multiple imputation, are generally required to obtain unbiased estimates in surveys subject to missingness which is not completely at random. The inclusion of predictors of non-response in such methods, for example as auxiliary variables in multiple imputation, can help improve the plausibility of the missing at random assumption underlying these methods and hence reduce bias. We present a systematic data-driven approach used to identify predictors of non-response at Wave 8 (age 25–26) of Next Steps, a UK national cohort study that follows a sample of 15,770 young people from age 13–14 years. The identified predictors of non-response were across a number of broad categories, including personal characteristics, schooling and behaviour in school, activities and behaviour outside of school, mental health and well-being, socio-economic status, and practicalities around contact and survey completion. We found that including these predictors of non-response as auxiliary variables in multiple imputation analyses allowed us to restore sample representativeness in several different settings, though we acknowledge that this is unlikely to universally be the case. We propose that these variables are considered for inclusion in future analyses using principled methods to explore and attempt to reduce bias due to non-response in Next Steps. Our data-driven approach to this issue could also be used as a model for investigations in other longitudinal studies.

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At around age 60, people are approaching late adulthood and are typically going through or anticipating life transitions such as grandparenthood, retirement, or changes in health and functioning. The timing and perception of transitions are individual and based on current circumstances and earlier life history and may link to well-being. The TRAILS (Developmental Psychological Perspectives on Transitions at Age 60: Individuals Navigating Across the Lifespan) study, which is presented in the current article, examines the diversity and underlying factors of different transitions at around age 60 and how they associate with mental well-being. It also investigates whether these transitions link to personality characteristics, contextual resources, and/or societal challenges. The role of earlier life history in the studied associations requires a prospective multiwave design where the same participants are followed over time. Only a few longitudinal studies have examined the developmental pathways from childhood to the beginning of late adulthood.

The TRAILS study continues the Jyväskylä Longitudinal Study of Personality and Social Development (JYLS). The JYLS was initiated in 1968 and includes earlier data collected from ages 8 to 50. At age 61, in 2020–21, 206 of the JYLS participants (of the initial 369 children) took part in TRAILS. The data collection included a Life Situation Questionnaire, a psychological interview, self-report inventories, a health examination and physical activity surveillance covering major areas of adult life. TRAILS extends the JYLS study to over 52 years of follow-up time and provides unique opportunities for studying individual development throughout the lifespan.

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Age at arrival is one factor that could influence the integration of humanitarian migrants, especially for children and teenagers. Previous research has focused on the influence of the age at arrival on education, employment, social and language learning outcomes, but there is limited research, especially for longitudinal study, on other important measures of integration. Moreover, young adult and adolescent refugees, and the relationship between age and integration outcomes are under-studied. To address these gaps, this study examined the relationships between age at arrival and different dimensions of integration of young refugees in Australia, using five years’ panel data from the Building a New Life in Australia (BNLA) longitudinal study from 2013 to 2018 (282 individuals). Our findings indicate that age at arrival is significantly correlated with multiple integration outcomes. Old entrants tend to have a higher probability of having a paid job but have poorer mental health and English proficiency. On the other hand, older entrants were more likely to know their rights well compared to younger entrants at arrival. However, younger entrants’ knowledge of their rights overtook older entrants four to five years after their arrival. These findings suggest that a shorter assessment process and enabling earlier entry especially among refugee youth and young adults could effectively improve their future settlement outcomes under the current humanitarian policies and system.

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Previous studies have shown that highly educated women are more likely to realise their fertility aspirations, or experience a faster progression to a higher order birth, compared to lower educated women. This is often explained by improved economic or social resources among the higher educated. However, it is unclear whether educational differences in health behaviours may also contribute to these differential fertility outcomes. In this study, we use data from Waves 1–7 of the UK Longitudinal Household Study, combined with data from the Nurse Health Assessment from Wave 2 to estimate couples’ likelihood of experiencing additional childbirth within six years. A discrete-time event history model is employed to analyse the transition to a higher order birth, while accounting for both partners’ level of education as well as smoking patterns and body mass index. We find that couples in which the female partner is highly educated are more likely to experience childbirth within six years compared to others. In addition, female smoking is negatively associated with the likelihood of childbirth, while no significant effect has been found for male health factors. Female health indicators explain some of the variation in fertility outcomes for women with lower secondary education compared to degree-educated women. However, education remains a significant predictor of the transition to higher order births, also after accounting for male and female health indicators. It is therefore important to consider both socio-economic and health factors in order to understand variations in fertility outcomes.

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This study seeks to examine how the trajectories of total cognition scores exhibited by two birth cohorts vary by race/ethnicity, gender and the level of education. The empirical work of this study is be based on the 1998–2014 Health and Retirement Study (HRS) and the HRS Cross-Wave Tracker file. The analysis is limited to individuals with available information on cognitive functioning, sex, race/ethnicity, wave, highest level of education, and the physical comorbidities associated with cognitive functioning (20,985 from the Traditionalist cohort and 11,077 from the Baby Boomer cohort). Growth curve modelling is used to assess the aims of this study.

Findings reveal that the cumulative advantage (disadvantage), persistent inequality and age-as-leveller hypotheses explain heterogeneity in total cognition scores for different race/ethnicity–sex groups, race/ethnicity–education and education–sex groups. These findings suggest that the development of an integrated treatment and screening mechanisms for physical comorbidities and cognitive functioning, and for the design of preventive strategies with the purpose of slowing or avoiding cognitive decline and maintaining healthy cognitive function should have a particular focus on females, racial ethnic minorities and those with low education.

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To assess the impact of age 15 fertility intentions on childbearing outcomes three decades later.


Evidence is mixed about the implications of teenage fertility intentions on later childbearing. Taking a prospective life course approach to assessing intentions and outcomes may help clarify these mixed findings.


A general population birth cohort (born 1972/73) was asked about their fertility intentions at age 15 and 775 of this sample (384 women, 391 men) provided data on their childbearing between ages 15 and 45.


At age 15, almost all of the sample indicated they would like to have children in the future (93%). Most (79%) reported having had a biological child by they time they were 45; but those who professed to not wanting children as teenagers were significantly less likely to have had a child three decades later.


Fertility intentions during adolescence are probably influenced by social, political and economic norms and may influence later childbearing decisions. This may be particularly true for those whose intentions counter established norms around childbearing.


A life course framework is useful for examining the relationship between hypothetical fertility intentions and outcomes.

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The consequences of the COVID-19 pandemic are still working through health systems worldwide, and further reflections about the nature of health and disease, and about how to design and implement effective public health interventions are much needed. For numerous diseases and conditions, as well as for COVID-19, our knowledge base is rich. We know a lot about the biology of the disease, and we have plenty of statistics that relate health to socio-economic factors. In this paper, we argue that we need to add a third dimension to this knowledge base, namely a thorough description of the lifeworld of health and disease, in terms of the mixed biosocial mechanisms that operate in it. We present the concepts of lifeworld and of mixed mechanisms, and then illustrate how they can be operationalised and measured through mixed methodologies that combine qualitative and quantitative approaches. Finally, we explain the complementarity of our approach with the biological and statistical dimensions of health and disease for the design of public health interventions.

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This commentary reinforces a central commitment of life course research: to make visible how social change matters in human lives. This paper captures a moderated conversation with four senior scholars about how they came to study the intersection between social change and life experience, why this intersection is so important to life course studies, and theoretical and methodological imperatives and challenges that come with it.

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