Longitudinal and Life Course Studies
An international journal

Sequencing, trajectories and patterns

View author details View Less
  • 1 Ohio State University, , USA
Full Access
Get eTOC alerts
Rights and permissions Cite this article

In my last editorial I was thinking about how COVID-19 has impacted our daily lives and the institutions that shape our societies. Some obvious examples include how children’s patterns of learning were disrupted by schools shutting down, having to wear masks and having to socially distance from their friends during developmental periods when their social, emotional, cognitive and physical growth are supposed to proceed in leaps and bounds, and when being able to be a kid with other kids can be so important. In the adult arena, disruption of work environments is also likely to have foreseen and unforeseen consequences for future working arrangements, mental health, career trajectories and so on. This is a very interesting time to be a life course researcher! Having now had COVID-19 myself, at a time when many of my friends also succumbed to the infection, my view turned inward and I began to think more about what this illness meant to me and the people I knew who were going through it. Aside from feelings of guilt that I had unwittingly passed it on to people I care about, my reactions were quite varied and wide ranging. First, I am immensely grateful to the people who worked so tirelessly to develop vaccines in record time that I know protected me from what could have been much more serious outcomes. I felt pretty lousy, I definitely couldn’t concentrate on anything work related, and losing my sense of taste and smell wasn’t great either. On the positive side, however, my waistline improved and I recovered with no known serious effects. It did disrupt my immediate plans and hence short-term work and family activities, but nothing more. I cancelled special invitations, quarantined and tried not to think of emails piling up in my inbox. This is all a long-winded way of acknowledging that sometimes things derail us and cause intended trajectories to shift, and also that my editorial this time around will be shorter as I’m still playing catch up!

There is a common theme of trajectories running through several of the papers included in this issue and reading these papers made me realise how far this type of life course research has come over the past few decades. When I was a postdoc a little over 30 years ago, my mentor, Ron Rindfuss, involved me in a project sequencing survey respondents’ lives to study patterns of work and schooling in young adulthood. Much work at this time centred on static variables measured at specific points in time that were then used to predict outcomes at later points – for example how living with both parents or only one at age 14 might impact future relationships. The dynamic nature of lives, how domains intersect, and the unfolding of the life course were relatively new concepts to be studied but they began to take on an important central focus. With methodological advances in data collection and increasingly sophisticated analytic opportunities, these were important improvements – developments that are central to many of these papers and which continue to evolve. Another reason why it is an exciting time to be a life course researcher!

The first article, ‘Regional differences in initial labour market conditions and dynamics in lifetime income trajectories’ by Kreske Ecker, Xavier de Luna and Olle Westerlund (2022) uses longitudinal register data on members of the 1954 Swedish birth cohort to examine patterns and dynamics in lifetime income trajectories, paying particular attention to the local economic conditions when people entered the labour market, along with their education, socio-economic background and gender. The authors question how lifetime income trajectories develop for individuals entering into different sized labour markets initially, how differences in income trajectories might be mediated by individual socio-economic background factors, and if the relationships they find differ by gender. Their finding that both men and women who start their working lives in a large city generally tend to have higher cumulative earned income over the period 1968–2010 highlights the importance of ‘place’ but this income measure is only one piece of the puzzle. Throughout the paper I found myself thinking of how much more expensive it can be to live in large cities than in smaller cities or rural areas. The authors mention this at the very end of the article, but future research should try and integrate this important factor throughout.

Next is an article by Chen-Hao Hsu (2022) on ‘Work and fertility in Taiwan: how do women’s and men’s career sequences associate with fertility outcomes?’ Drawing on retrospective data from the 2017 Taiwan Social Change Survey, this study examines women’s and men’s career trajectories between ages 18 and 40 using sequence analyses, and considers how career variations are associated with the timing of parenthood and number of children mothers and fathers have by age 40. Hsu’s research shows not only how career paths in Taiwan are gendered but how they are associated with various patterns of fertility timing and family size. Motherhood is delayed and women end up with lower fertility when they are stably employed in full-time jobs reflecting the intense difficulty of combining work and family in a country where traditional gender roles are entrenched and work–family policies are weak. For Taiwanese men, it is having an unstable employment history that delays the transition to fatherhood and depresses family size. Interestingly, men and women who are self-employed have children earlier and also more children by midlife, which underscores the importance of understanding the meaning of self-employment in different cultural contexts.

The third article on ‘Life course trajectories of affective symptoms and their early life predictors’ by Ellen Thompson, George Ploubidis, Marcus Richards and Darya Gaysina (2022) again looks at trajectories – this time trajectories of depression and anxiety measured over a period of more than 50 years – and asks if there are early life factors that might lead to a higher risk of certain trajectories being followed over others. Using data from the British MRC National Survey of Health and Development, this paper is a great illustration of a non-finding being important. The authors were able to identify four distinct life course profiles of affective symptoms but despite modelling 24 potential early life predictors, only four were found to be associated with their life course trajectories, and only small effect sizes were observed. As the authors note, a drawback to this study was their inability to use measures that captured the persistence of risk in early life, which we know from other research to be important. This is something that would be important to look at in future research.

The next piece by Meredith O’Connor, Shuaijun Guo, Primrose Letcher, Ann Sanson, Sharon Goldfeld and Craig Olsson (2022) is titled ‘Developmental relationships between socio-economic disadvantage and mental health across the first 30 years of life’. Drawing on data from 1,144 members of the Australian Temperament Project which followed infants recruited from the state of Victoria in 1983 until they were 27–28 years old, this study makes a nice contribution to our understanding of associations between socio-economic status and mental health by including outcome measures of mental health competences as well as mental health difficulties. Their finding that aspects of good mental health in young adulthood were related to socio-economic circumstances as far back as infancy underscores the need to promote positive aspects of mental health for disadvantaged youth. Again the notion of an unfolding life course is stressed where shifting events and circumstances create heterogeneous patterns. By differentiating the timing of exposure from the chronicity of exposure to disadvantage means this research is able to contribute to both theoretical perspectives and policy. As the COVID-19 pandemic has been linked to increased levels of mental health problems, this kind of research will become increasingly important.

Linkages between mental health and substance use are well documented and the US National Institute of Mental Health notes that about half of individuals who experience a substance use disorder during their lives will also experience a co-occurring mental disorder and vice versa.1 Cody Warner and Emily Cady’s research note ‘Does substance use play a role in gender differences in residential independence and returns to the parental home?’ focuses on the substance use part of that relationship, and ties this into an original marker of the transition to adulthood (leaving home) and the increasingly common phenomenon of young adults returning to the parental home for various reasons. Using data from the US National Longitudinal Survey of Youth 1997 Cohort these authors find that any marijuana use is associated with an increased likelihood of both home-leaving and home-returning and that these patterns vary by gender. Alcohol use, on the other hand, is not related to either and does not interact with gender. With changing laws in the US related to marijuana use, the authors note that future research should see if the legal status of marijuana in the state of residence might play a role. I would also suggest further exploration into how marijuana use is related to the use of other drugs, and how this relationship might differ by gender, could also be a fruitful avenue of research to help unpack these complex and important relationships.

The final paper in this issue is ‘New generations of respondents: assessing the representativity of the HILDA Survey’s child sample’ by Nicole Watson (2022). An important aspect of an indefinite life household panel such as HILDA (the Household, Income and Labour Dynamics in Australia survey, started in 2001) is to provide a sample of children who grow up in the study that are, as much as possible, representative of the population. When there is selective loss to follow-up of parents prior to the child becoming a part of the study themselves, selective non-response by these children even when their parents continue to participate, or when there is significant immigration or emigration causing demographic shifts in the overall population but which is not reflected in the panel, any sample of children can diverge quite significantly. As Watson clarifies, when assessing representativeness we need to know what population the sample is supposed to represent, and for what characteristics of the target population can the sample data be used. Not only does this paper provide a useful description of HILDA, but it addresses questions that are centrally important to longitudinal data collections. Some results to highlight include the importance of comparing survey estimates against multiple external sources rather than just a single source, and to be very aware of differences in questionnaire design, respondent recall, degree and patterns of missing data, and undercoverage of recent immigrants that might account for differences before drawing conclusions about one’s comparative findings.

Conflict of interest

The author declares that there is no conflict of interest.

References

  • Ecker, K., de Luna, X. and Westerlund, O. (2022) Regional differences in initial labour market conditions and dynamics in lifetime income trajectories, Longitudinal and Life Course Studies, XX(XX): 128, doi: 10.1332/175795921X16427665823284.

    • Search Google Scholar
    • Export Citation
  • Hsu, C. (2022) Work and fertility in Taiwan: how do women’s and men’s career sequences associate with fertility outcomes?, Longitudinal and Life Course Studies, XX(XX): 128, doi: 10.1332/175795921X16379265590317.

    • Search Google Scholar
    • Export Citation
  • O’Connor, M., Guo, S., Letcher, P., Sanson, A., Goldfeld, S. and Olsson, C. (2022) Developmental relationships between socio-economic disadvantage and mental health across the first 30 years of life, Longitudinal and Life Course Studies, XX(XX): 122, doi: 10.1332/175795921X16459587898770.

    • Search Google Scholar
    • Export Citation
  • Thompson, E.J., Ploubidis, G.B., Richards, M. and Gaysina, D. (2022) Life course trajectories of affective symptoms and their early life predictors, Longitudinal and Life Course Studies, XX(XX): 120, doi: 10.1332/175795921X16487298020502.

    • Search Google Scholar
    • Export Citation
  • Watson, N. (2022) New generations of respondents: assessing the representativity of the HILDA Survey’s child sample, Longitudinal and Life Course Studies, XX (XX): 122, doi: 10.1332/175795921X16349086588358.

    • Search Google Scholar
    • Export Citation
  • Ecker, K., de Luna, X. and Westerlund, O. (2022) Regional differences in initial labour market conditions and dynamics in lifetime income trajectories, Longitudinal and Life Course Studies, XX(XX): 128, doi: 10.1332/175795921X16427665823284.

    • Search Google Scholar
    • Export Citation
  • Hsu, C. (2022) Work and fertility in Taiwan: how do women’s and men’s career sequences associate with fertility outcomes?, Longitudinal and Life Course Studies, XX(XX): 128, doi: 10.1332/175795921X16379265590317.

    • Search Google Scholar
    • Export Citation
  • O’Connor, M., Guo, S., Letcher, P., Sanson, A., Goldfeld, S. and Olsson, C. (2022) Developmental relationships between socio-economic disadvantage and mental health across the first 30 years of life, Longitudinal and Life Course Studies, XX(XX): 122, doi: 10.1332/175795921X16459587898770.

    • Search Google Scholar
    • Export Citation
  • Thompson, E.J., Ploubidis, G.B., Richards, M. and Gaysina, D. (2022) Life course trajectories of affective symptoms and their early life predictors, Longitudinal and Life Course Studies, XX(XX): 120, doi: 10.1332/175795921X16487298020502.

    • Search Google Scholar
    • Export Citation
  • Watson, N. (2022) New generations of respondents: assessing the representativity of the HILDA Survey’s child sample, Longitudinal and Life Course Studies, XX (XX): 122, doi: 10.1332/175795921X16349086588358.

    • Search Google Scholar
    • Export Citation
  • 1 Ohio State University, , USA

Content Metrics

May 2022 onwards Past Year Past 30 Days
Abstract Views 2 2 2
Full Text Views 54 54 54
PDF Downloads 47 47 47

Altmetrics

Dimensions