Research & Analytics

FEATURED

Advanced Population Science & Real-World Data Analytics

Leading Oxford’s Leverhulme Centre for Demographic Science, Professor Melinda Mills conducts research using high-dimensional population-scale health datasets, biosocial genetics, and geospatial analytics. Her work transforms complex, fragmented datasets into rigorous, peer-reviewed evidence on population health, human behavior, and systemic inequalities.

Google Scholar Publications

Real-World Data (RWD) & Data Governance

Real-World Data (RWD) & Biobank Governance: Strategic and fiduciary oversight of massive cohort architectures—encompassing deep phenomic, genomic, and longitudinal health records .

Advanced Biostatistics & Predictive Modeling: Architecting causal inference frameworks, statistical and AI analyses to extract scalable, actionable insights from highly complex datasets.

Data Ventures & Innovation

Global Media & Thought Leadership

Professor Melinda Mills is a prominent international commentator on demographic trends, health data, and public policy. She regularly provides expert analysis and strategic commentary across major news networks, national broadcasts, and leading international publications—including the BBC, Financial Times, and The Guardian.

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FEATURED RESEARCH

Realizing the Full Potential for Next-Generation Biobanks

Nature Genetics | Straub, Benonisdottir, Kong, & Mills

A high-impact analysis evaluating Our Future Health—the UK's flagship 5-million-participant health research cohort. This study outlines strategic frameworks for trans-biobank data linkage, federated analytics, and multi-ancestry representation to accelerate global genomic medicine and population health discovery.

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Genomics of Human Fertility, Reproductive Aging & Longevity

Tracing a decade of breakthrough discovery, Professor Mills mapped the genetic architecture of human reproduction and links to longevity. Starting with her Nature Genetics that first identified 12 genomic loci for reproductive timing, her 2023 Nature Human Behaviour study expands the analysis across 800,000 individuals to uncover 43 genetic determinants of fertility ongoing natural selection. Most recently, a 2024 study in Nature Aging connects both female and male reproductive traits—including key regulatory genes like FSHB—directly to chronic disease, psychiatric traits, and human lifespan.

Nature Genetics

Nature HB

Nature Aging

The National Conversation mass listening exercise

Mills & team are running the National Conversation - a public engagement initiative designed to measure community cohesion, public trust, and sense of belonging across the United Kingdom. Using an innovative online survey incorporating voice notes and interactive location mapping, the study gathers citizens' lived experiences to inform national policy and establish an ongoing social barometer.

See our call to action video written by playwright James Graham & narrated by Sir Ian McKellen (during the World Cup).

Fill in Survey

Optimising the Modern Workforce

Published in the journal Sleep and utilising data from the UK Biobank and wearable technology, this study reveals how individual genetic chronotypes (e.g. night owls) can protect against the health penalties of shift work—providing data-driven strategies for corporate wellness and workforce management.

Read the press release, article, or watch the film.

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Causal Inference & Policy Impact: Modeling Behavioral Interventions

Leveraging synthetic-control modelling - the gold standard for causal inference - this study evaluated the real-world impact of mandatory COVID-19 health certification on population behaviour. Published in the Lancet Public Health, the study served as key evidence for multiple national governments and featured in press release, article, FT , Guardian editorials.

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Real-Time Crisis Analytics & Geopolitical 'Nowcasting'

When crisis hits, traditional demographic data becomes obsolete instantly. Our study demonstrates how advanced, real-time data mapping and algorithmic "nowcasting" can track internal population displacement during active conflict in Ukraine. The methodology provides a blueprint for governments, NGOs and global enterprises to execute rapid, data-driven logistical and humanitarian responses in highly volatile environments. Read the press release, article.

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Recent Breakthroughs
Selected 2024-2026

Google Scholar

Straub, V.J., S. Benonisdottir, G. Scotti-Bentivoglio, N. Wary, R. Campbell, A. Kong & M.C. Mills (2026). Phenomic profiles and disease patterns of 1.9 million participants from Our Future Health, Nature Medicine (forthcoming)

An initial assessment of the UK’s flagship health research program—now exceeding 2.5 million enrolled adults and 1.9 million baseline phenotyped records. Benchmarking electronic health data, diagnoses, and lifestyle factors against national estimates and the UK Biobank, we validate the cohort’s unprecedented scale and reliability to power early disease detection, predictive analytics, and population health strategy.

Straub, V.J. & M.C. Mills. (2026). Enabling secure discovery in Trusted Research Environments with improved tooling, Nature Medicine, https://www.nature.com/articles/s41591-026-04401-x

Biobanks are introducing trusted research environments to enable secure data access, yet they can increase costs and complexity for biomedical researchers who use them. We discuss challenges and solutions and introduce the Python Phenofhy community tool for Our Future Health.

Akimova, E.T., A. Fauske, R.A. Jorgensen, A. Havdahl, E.C. Corfield, M.C. Mills, T.H. Lyngstad. (2026). When children shape their families: Evocative effects analysis of 40,000 trios from the Norwegian Mother, Father and Child Cohort Study, PNAS, 123(3); e2532642123. doi: 10.1073/pnas.2532642123.

Analyzing complex family dynamics across 40,000 parent-child trios in the Norwegian Mother, Father and Child Cohort Study. This innovative research reverses traditional demographic assumptions to quantify "evocative effects"—demonstrating how a child's genetic and behavioral traits actively shape family environments, parental behavior, and long-term socio-demographic outcomes.

Ding, X., E.T. Akimova, B. Zhao & M.C. Mills. (2025). Night shift work and sleep duration among middle and older age adults: The role of individual, social, and environmental moderators, Social Science & Medicine, 384: 118443.

Analyzing sleep deficits among night shift workers, this study reveals that sleep loss is heavily moderated by biological, environmental, and social factors. Workers with morning chronotypes, children, or those living at higher latitudes face the greatest sleep deprivation. The findings highlight distinct drivers by gender—family for women, biology for men—and show that sleep penalties are disproportionately concentrated among lower-education night shift workers.

Abdellaoui, A. et al. (2025). Socio-economic status is a social construct with heritable components and genetic consequences. Nature Human Behaviour, 9: 864-876.

This review explores how socioeconomic status and social sorting interact with human genetics to drive evolutionary selection pressures. It reveals the hidden genetic consequences of how societies are structured, providing critical insights for ethics, policy, and social fairness.

Akimova et al., F. C. Tropf, M.C. Mills (2024). Polygenic prediction of occupational status GWAS elucidates genetic and environmental interplay in intergenerational transmission, careers and health in UK Biobank, Nature Human Behaviour and FAQs

Leveraging UK Biobank data to untangle the complex interplay between genetics, environment, and career trajectories. By modeling polygenic prediction of occupational status, the research uncovers the underlying drivers of intergenerational mobility, career success, and health outcomes.

Benonisdottir et al. M.C. Mills (2024). Genetics of female and male reproductive traits and their relationship with health, longevity and consequences for offspring, Nature Aging, 4: 1745-1759. https://rdcu.be/d3tsr

This study linked male and female reproductive traits directly to overall healthspan, chronic disease, and lifespan. By analyzing cross-generational data, the research reveals how reproductive genetics shape long-term health outcomes in both parents and their offspring.

Davies, N.M. et al. (2024). The importance of family-based sampling for biobanks, Nature, 634: 795-803. https://rdcu.be/dXQ56

Advocates for integrating family-based recruitment into biobank architecture, demonstrating how sampling genetic relatives eliminates environmental confounding to isolate direct causal genetic effects.

Liu, A. et al. (2024). Evidence from Finland and Sweden on the relationship between early-life diseases and lifetime childlessness in men and women, Nature Human Behaviour, 8: 276-287.

Leverages nationwide registry data across 2.5 million individuals in Finland and Sweden to map how 414 early-life diseases—particularly mental-behavioral disorders in men and metabolic conditions in women—influence lifetime childlessness through partnership status and education.