Early Life Social, Economic and Family Predictors of the Trajectory of Malnutrition and Cognitive Development from Childhood to Adulthood

About this project

Project description

There is substantial evidence that young people in less affluent countries have worse health, well-being, and impaired development than those who live in affluent countries. For instance, many low- to middle-income countries (LMICs) are facing a double burden of malnutrition (DBM), resulting from the coexistence of underweight and overweight individuals in a given population. Recent evidence shows that countries like India, Vietnam, Peru and Ethiopia are currently suffering such a DBM. India alone is home to one-third of the global population of malnourished children, while at the same time almost one-third of children living in urban areas are overweight/obese. This DBM is thought to have arisen due to the nutritional transition experienced by these countries, along with a rapid change in food production, dietary habits, and physical activity. Parallel to the nutritional and life style changes, social, economic and family status have changed quite rapidly. This dynamics has a huge implication for the physical and cognitive development of the young people in the LMICs like India. Unlike higher income countries, limited multi-country studies have been conducted in LMICs to understand these early life predictors of the development of childhood, adolescent and young adulthood DBM and cognitive health. Using a unique longitudinal study (see www.younglives.org.uk) of ~12000 children aged 1 to 8 years who were recruited in 2002 and subsequently followed in 2006, 2009, 2013 and 2016 (15 to 22 years) across four countries (India, Vietnam, Peru and Ethiopia), this study will determine the early life social, economic, and family predictors of DBM and cognitive development from childhood to adulthood. Life course theoretical framework and advanced statistical analyses such as multilevel structural equation modelling for causal interface will be used. Findings of this study will be useful to develop early live interventions to prevent DBM and cognitive impairments in LMICs.


  1. The PhD thesis and high impact multiple publications in peer review journals
  2. Methodological development in analysing longitudinal data within life course framework
  3. Presentation at national and international conferences on the research topics

Information for applicants

Essential capabilities

  1. Outstanding quantitative and writing skills
  2. High level of English proficiency (especially oral and writing skills).

Desireable capabilities

  1. Some experience with statistical software (such as STATA, SAS, R)
  2. Multivariable statistical skills and experience with longitudinal data analysis .

Expected qualifications (Course/Degrees etc.)

Background in statistics, economic, population studies, and psychology.

Candidate Discipline

Statistics, Economics, Population studies or Psychology.

Project supervisors

Principal supervisors

UQ Supervisor

Associate Professor Abdullah Mamun

Institute for Social Science Research
IITD Supervisor

Associate Professor Kamlesh Singh

Department of Humanities and Social Science
Additional Supervisor

Dr Nam Tran

Institute for Social Science Research