Developing a weighting strategy to include mobile phone numbers into an ongoing population health survey using an overlapping dual-frame design with limited benchmark information

Objective: Currently, primary health care (PHC) is under-represented in health statistics due to the lack of a comprehensive PHC data collection. This research explores the utility of population health surveys to address questions relating to access to and use of PHC, using diabetes as an example. Methods: Drawing on published material relating to diabetes management, we developed a conceptual framework of access to and use of quality PHC. Using this framework we examined three recent population-based health surveys ? the 2001 National Health Survey, 2002?03 NSW Health Survey, and AusDiab ? to identify relevant information collection. Results: We identified seven domains comprising aspects of quality PHC for people with diabetes. For each domain we proposed associated indicators. In critiquing the three population health surveys in relation to these indicators, we identified strengths and weaknesses of the data collections. Conclusion: This approach could inform the development of questions and extension of population health surveys to provide a better understanding of access to and use of quality PHC in Australia. The additional information would complement other data collections with a communitybased perspective and contribute to the develop- ment of PHC policy.

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Sociodemographic factors associated with food insecurity: data from the 2003–2014 New South Wales Population Health Survey

Public Health Nutrition ◽

10.1017/s1368980019005159 ◽

2020 ◽

Vol 23 (11) ◽

pp. 1857-1867

Author(s):

Paraskevi Drakoulidou ◽

Bradley Drayton ◽

Leah Shepherd ◽

Seema Mihrshahi

Keyword(s):

Food Insecurity ◽

Population Health ◽

Health Survey ◽

Smoking Status ◽

New South ◽

New South Wales ◽

Sociodemographic Factors ◽

Factors Associated ◽

Self Rated Health ◽

South Wales

AbstractObjective:To determine the prevalence and sociodemographic factors associated with food insecurity in the state of New South Wales (NSW), Australia.Design:Cross-sectional analysis of food insecurity data collected by the NSW Population Health Survey between 2003 and 2014. Multiple logistic regression was used to examine associations with key sociodemographic variables.Setting:NSW, Australia.Participants:212 608 survey participants responded to the food insecurity survey question between 2003 and 2014. 150 767 of them were aged ≥16 years. The survey sample was randomly selected and weighted to be representative of the NSW population.Results:On average 6 % of adults aged ≥16 years experienced food insecurity in NSW. The odds of food insecurity appeared to increase from one survey year to the next by a factor of 1·05. Food insecurity was found to be independently associated with age, sex, marital status, household size, education, employment status, household income, smoking status, alcohol intake and self-rated health. The association with income, smoking status and self-rated health appeared to be the strongest among all covariates and showed a gradient effect. Food insecurity appeared to increase significantly between the age of 16 and 19 years.Conclusions:The prevalence of food insecurity appears to be rising over time. Given the negative health consequences of food insecurity, more rigorous measurement and monitoring of food insecurity in NSW and nationally is strongly recommended. The findings provide support for interventions targeting low-income and younger population groups.

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