Health inequalities between urban and rural areas are prevalent in many countries. However, rurality is a multifaceted concept so it is important to specify which aspects of rurality are most relevant to the analysis of urban/rural health disparities. Drawing from international research, we identified four domains that are most relevant to measuring rurality:(1) access to service facilities; (2) percentage of natural space; (3) population density; and (4) percentage of people employed in farming-related occupations. For the Auckland and Northland regions of New Zealand, we calculated a score for each of the four domains and combined them into a multi-dimensional index of relative rurality for health research using network analysis and various statistical approaches. We further developed an urban/ rural typology that characterises urban and rural areas using quantitative criteria including thresholds and different combinations of domains and indicators of rurality. The rurality index, the typology and existing classifications were assessed in relation to all-cause mortality. The findings of this preliminary study provide useful insights into the potential benefits of a conceptually rigorous, granular and multi-dimensional index which incorporates characteristics that can differentiate levels of rurality in New Zealand more than existing classifications. Validation studies and assessment of associations with specific health outcomes would be useful next steps in considering the utility of this rurality index for New Zealand more generally. Keywords Rurality index • Urban/rural typology • Health research • New Zealand

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Introduction- It is being debated whether prostate-specific antigen (PSA)-based screening effectively reduces prostate cancer mortality. Some of the uncertainty could be related to deficiencies in the age-based PSA cut-off thresholds used in screening. Methods- Current study considered 2779 men with prostate cancer and 1606 men without a cancer diagnosis, recruited for various studies in New Zealand, US and Taiwan. Association of PSA with demographic, lifestyle, clinical characteristics (for cases), and the aldo-keto reductase 1C3 (AKR1C3) rs12529 genetic polymorphisms were analysed using multiple linear regression and univariate modelling.Results- Pooled multivariable analysis of cases showed that PSA was significantly associated with demographic, lifestyle and clinical data with an interaction between ethnicity and age further modifying the association. Pooled multivariable analysis of controls data also showed that demographic and lifestyle are significantly associated with PSA level. Independent case and control analyses indicated that factors associated with PSA were specific for each cohort. Univariate analyses showed a significant age and PSA correlation among all cases and controls except for the US-European cases while genetic stratification in cases showed variability of correlation. Conclusion- Data suggests that unique PSA cut-off thresholds factorized with demographics, lifestyle and genetics may be more appropriate for prostate cancer screening.