Clustering of health, crime and social-welfare inequality in 4 million citizens from two nations

• Published in: Nature human behaviour 2020-03, Vol.4 (3), p.255-264
• Main Authors: Richmond-Rakerd, Leah S., D’Souza, Stephanie, Andersen, Signe Hald, Hogan, Sean, Houts, Renate M., Poulton, Richie, Ramrakha, Sandhya, Caspi, Avshalom, Milne, Barry J., Moffitt, Terrie E.
• Format: Article
• Language: English
• Subjects: 4014/159; 4014/4013; 4014/477; 4014/477/2811; Adolescent; Adult; Aged; Behavioral Sciences; Biomedical and Life Sciences; Child; Child, Preschool; Cluster Analysis; Clustering; Crime; Crime - economics; Crime - statistics & numerical data; Databases, Factual; Denmark - epidemiology; Drug Prescriptions - economics; Drug Prescriptions - statistics & numerical data; Educational Status; Experimental Psychology; Female; Health disparities; Health insurance; Hospitalization - economics; Hospitalization - statistics & numerical data; Hospitals, Public - economics; Hospitals, Public - statistics & numerical data; Humans; Inequality; Infant; Injuries; Insurance, Health - economics; Insurance, Health - statistics & numerical data; Life satisfaction; Life Sciences; Longitudinal Studies; Male; Mental health; Mental Health - statistics & numerical data; Microeconomics; Middle Aged; Midlife; Neurosciences; New Zealand - epidemiology; Personal Satisfaction; Personality and Social Psychology; Population; Social inequality; Social problems; Social Welfare - economics; Social Welfare - statistics & numerical data; Socioeconomic Factors; Welfare benefits; Welfare dependency; Workforce; Wounds and Injuries - economics; Wounds and Injuries - epidemiology; Young Adult; Youth
• ISSN: 2397-3374; 2397-3374
• DOI: 10.1038/s41562-019-0810-4

Health and social scientists have documented the hospital revolving-door problem, the concentration of crime, and long-term welfare dependence. Have these distinct fields identified the same citizens? Using administrative databases linked to 1.7 million New Zealanders, we quantified and monetized inequality in distributions of health and social problems and tested whether they aggregate within individuals. Marked inequality was observed: Gini coefficients equalled 0.96 for criminal convictions, 0.91 for public-hospital nights, 0.86 for welfare benefits, 0.74 for prescription-drug fills and 0.54 for injury-insurance claims. Marked aggregation was uncovered: a small population segment accounted for a disproportionate share of use-events and costs across multiple sectors. These findings were replicated in 2.3 million Danes. We then integrated the New Zealand databases with the four-decade-long Dunedin Study. The high-need/high-cost population segment experienced early-life factors that reduce workforce readiness, including low education and poor mental health. In midlife they reported low life satisfaction. Investing in young people’s education and training potential could reduce health and social inequalities and enhance population wellbeing. Using administrative data on 4 million citizens from two nations, Richmond-Rakerd et al. find that multiple health and social problems cluster in a population segment with low workforce readiness, including low education and poor early-life mental health.