To investigate the spatial distribution of self-harm incidence rates, their socioeconomic correlates and sex/age differences using data on self-harm presentations to emergency departments from The Manchester Self-Harm Project (2003–2013).

Smoothed standardised incidence ratios for index self-harm episodes (n = 14 771) and their associations with area-level socioeconomic factors across 258 small areas (median population size = 1470) in the City of Manchester municipality were estimated using Bayesian hierarchical models.

Higher numbers and rates of self-harm were found in the north, east and far southern zones of the city, in contrast to below average rates in the city centre and the inner city zone to the south of the centre. Males and females aged 10–24, 25–44 and 45–64 years showed similar geographical patterning of self-harm. In contrast, there was no clear pattern in the group aged 65 years and older. Fully adjusted analyses showed a positive association of self-harm rates with the percentage of the unemployed population, households privately renting, population with limiting long-term illness and lone-parent households, and a negative association with the percentage of ethnicity other than White British and travel distance to the nearest hospital emergency department. The area-level characteristics investigated explained a large proportion (four-fifths) of the variability in area self-harm rates. Most associations were restricted to those aged under 65 years and some associations (e.g. with unemployment) were present only in the youngest age group.

The findings have implications for allocating prevention and intervention resources targeted at high-risk groups in high incidence areas. Targets for area-based interventions might include tackling the causes and consequences of joblessness, better treatment of long-term illness and consideration of the accessibility of health services.

Population-based colorectal cancer (CRC) screening programs that use a fecal immunochemical test (FIT) are often faced with a noncompliance issue and its subsequent waiting time (WT) for those FIT positives complying with confirmatory diagnosis. We aimed to identify factors associated with both of the correlated problems in the same model.

A total of 294,469 subjects, either with positive FIT test results or having a family history, collected from 2004 to 2013 were enrolled for analysis. We applied a hurdle Poisson regression model to accommodate the hurdle of compliance and also its related WT for undergoing colonoscopy while assessing factors responsible for the mixture of the two outcomes.

The effect on compliance and WT varied with contextual factors, such as geographic areas, type of screening units, and level of urbanization. The hurdle score, representing the risk score in association with noncompliance, and the WT score, reflecting the rate of taking colonoscopy, were used to classify subjects into each of three groups representing the degree of compliance and the level of health awareness.

Our model was not only successfully applied to evaluating factors associated with the compliance and the WT distribution, but also developed into a useful assessment model for stratifying the risk and predicting whether and when screenees comply with the procedure of receiving confirmatory diagnosis given contextual factors and individual characteristics.