Progress Towards Using Linked Population-Based Data For Geohealth Research: Comparisons Of Aotearoa New Zealand And The United Kingdom

Evaluation of Survey Nonresponse in Measuring Cardiometabolic Health Risk Factors and Outcomes among Sexual Minority Populations: A National Data Linkage Analysis

Understanding cardiometabolic health among lesbian, gay, and bisexual (LGB) people is challenged by methodological constraints, as most studies are either based on nonprobability samples or assume that missing values in population-based samples occur at random. Linking multiple years of nationally representative surveys, hospital records, and geocoded data, we analyzed selection biases and health disparities by self-identified sexual orientation in Canada. The results from 202,560 survey respondents of working age identified 2.6% as LGB, 96.4% as heterosexual, and <1.0% with nonresponse to the sexual identity question. Those who did not disclose their sexual identity were older, less highly educated, less often working for pay, and less often residing in rural and remote communities; they also had a diagnosed cardiometabolic condition or experienced a cardiometabolic-related hospitalization more often. Among those reporting their sexual identity, LGB individuals were younger, more likely to smoke tobacco or drink alcohol regularly, more likely to have heart disease, and less likely to have a regular medical provider than heterosexual persons. This investigation highlighted the potential of leveraging linked population datasets to advance measurements of sexual minority health disparities. Our findings indicated that population health survey questions on sexual identity are not generally problematic, but cautioned that those who prefer not to state their sexual identity should neither be routinely omitted from analysis nor assumed to have been randomly distributed.

Investigating the transmission risk of infectious disease outbreaks through the Aotearoa Co-incidence Network (ACN): a population-based study

BACKGROUND

The emergence and re-emergence of infectious diseases presents a significant challenge to public health and broader society. This study utilises novel nationwide data to calculate the transmission risk and potential inequity of infectious disease outbreaks through use of network analysis.

METHODS

Nationwide employment and education microdata (∼4.7 million individuals in Aotearoa New Zealand) were used to develop the Aotearoa Co-incidence Network (ACN). The ACN considers connections generated when individuals are employed at the same workplaces or enrolled at the same schools. Through forms of network analysis, connections between geospatial areas can be established and provide proxy measures of infectious disease transmission risk. The ACN was also overlayed with nationwide population vulnerability data based on the number of older adults (>65 years) and individuals with long-term health conditions.

FINDINGS

We identify areas that have both high potential transmission risk (i.e., highly connected) and high vulnerability to infectious diseases. Community detection identified geographic boundaries that can be relevant to the application of regional restrictions for limiting infectious disease transmission.

INTERPRETATION

Integrating novel network science and geospatial analytics provides a simple way to study infectious disease transmission risk and population vulnerability to outbreaks. Our replicable method has utility for researchers globally with access to such data. It can help inform equitable preparation for, and responses to infectious disease outbreaks.

FUNDING

This project was funded by the Health Research Council of New Zealand (20/1442) and from the NZ Government via Ministry for Business Innovation and Employment and Department of Prime Minister and Cabinet.