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The long arm of childhood: Cross national comparisons using Big Cohort Data (RDF23/MPEE/PAKPAHAN)

   Faculty of Engineering and Environment

This project is no longer listed on FindAPhD.com and may not be available.

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  Dr Eduwin Pakpahan, Prof David Blane  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

Our current health and social economic status are dependent upon the experiences in early life. For example, a 65-years old male, in a healthy condition, is strongly associated with his healthy behaviours that have been consistently followed in previous years: less alcohol intake, no smoking, regular physical exercise, etc. This time span might be extended to his condition in his early life as well. This approach is the centre of the life course research. Another important background why we need life to understand the life course is because life expectancy is, on average, increasing in all countries. People live longer than previous cohort. Therefore, to understand how to reach optimum quality of life we need to understand how they survive in the beginning.

Life course research offers interdisciplinary research (health, human development and aging, sociologists, demographers, and biologist, among others). It involves all important events in someone’s life so might include gestation, childhood, adolescence, adulthood, until old age. Events in childhood might have a long-term impact, not only within the childhood years, but also in the following decades.

The question arises then, that if we know the events in the past (or if we are able to reconstruct all information from the past), are we able to predict both health and socioeconomic status in the next 20 or 30 years or more? Are we able to explain the mechanism of how these events are associated across this life span?

For example, those who were born into a poor family, do they have a chance, the future, to escape from being poor to then achieve potentially better social economic status (SES)? Or those who were born with some health problems; will they reach good health in old age? If the answers for these two questions are yes, then what and how can they do this? Is there a specific event that enables them to achieve better SES and or health, or will they remain poor or ill-conditioned throughout their life? Substantively, the life course research will examine the following topics: critical and sensitive periods, development of risk, modification of risk, and cohort effects.

We seek to disentangle the main research questions above using generalized latent variable models. Experience in programming is essential, particularly in R, Stata, and Mplus. This PhD studentship offers training in health data science using big cohort datasets (ELSA-UK, HRS-USA, IFLS-Indonesia, TILDA-Ireland, MCS-UK). These datasets provide an opportunity to examine the questions above, and interestingly they provide an opportunity for the cross-national comparisons. Additional datasets might be available in due time. The student will learn data science, epidemiology, and statistical methods through using the datasets above and produce research articles relevant to policy and practice. The PhD studentship could also develop into considering the application of and extending the causal inference methods in longitudinal studies that can be applied to assess the long-term impact of childhood experiences.

Academic Enquiries

This project is supervised by Dr. Eduwin Pakpahan. For informal queries, please contact Dr. Eduwin Pakpahan ([Email Address Removed]). For all other enquiries relating to eligibility or application process please use the email form below to contact Admissions. 

Funding Information

Home and International students (inc. EU) are welcome to apply. The studentship is available to Home and International (including EU) students and includes a full stipend at UKRI rates (for 2022/23 full-time study this is £17,668 per year) and full tuition fees. Studentships are also available for applicants who wish to study on a part-time basis over 5 years (0.6 FTE, stipend £10,600 per year and full tuition fees) in combination with work or personal responsibilities). 

Please also see further advice below of additional costs that may apply to international applicants.

Eligibility Requirements:

  • Academic excellence of the proposed student i.e. 2:1 (or equivalent GPA from non-UK universities [preference for 1st class honours]); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.
  • Appropriate IELTS score, if required.
  • Applicants cannot apply for this funding if they are already a PhD holder or if currently engaged in Doctoral study at Northumbria or elsewhere.

Please note: to be classed as a Home student, candidates must meet the following criteria:

  • Be a UK National (meeting residency requirements), or
  • have settled status, or
  • have pre-settled status (meeting residency requirements), or
  • have indefinite leave to remain or enter.

If a candidate does not meet the criteria above, they would be classed as an International student. Applicants will need to be in the UK and fully enrolled before stipend payments can commence, and be aware of the following additional costs that may be incurred, as these are not covered by the studentship.

  • Immigration Health Surcharge https://www.gov.uk/healthcare-immigration-application
  • If you need to apply for a Student Visa to enter the UK, please refer to the information on https://www.gov.uk/student-visa. It is important that you read this information very carefully as it is your responsibility to ensure that you hold the correct funds required for your visa application otherwise your visa may be refused.
  • Check what COVID-19 tests you need to take and the quarantine rules for travel to England https://www.gov.uk/guidance/travel-to-england-from-another-country-during-coronavirus-covid-19
  • Costs associated with English Language requirements which may be required for students not having completed a first degree in English, will not be borne by the university. Please see individual adverts for further details of the English Language requirements for the university you are applying to.

How to Apply

For further details of how to apply, entry requirements and the application form, see


For applications to be considered for interview, please include a research proposal of approximately 1,000 words and the advert reference (e.g. RDF23/…).

Deadline for applications: 27 January 2023

Start date of course: 1 October 2023 tbc


Pakpahan, E., Hoffmann, R., & Kröger, H. (2017). Statistical methods for causal analysis in life course research: an illustration of a cross-lagged structural equation model, a latent growth model, and an autoregressive latent trajectories model. International Journal of Social Research Methodology, 20(1), 1-19.
Pakpahan, E., Hoffmann, R., & Kröger, H. (2017). The long arm of childhood circumstances on health in old age: Evidence from SHARELIFE. Advances in Life Course Research, 31, 1-10.
Kuh, D., Ben-Shlomo, Y., Lynch, J., Hallqvist, J., & Power, C. (2003). Life course epidemiology. Journal of epidemiology and community health, 57(10), 778.

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