To determine the prevalence and sociodemographic factors associated with food insecurity in the state of New South Wales (NSW), Australia.

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.

NSW, Australia.

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.

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.

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.

To compare women's diets with recommended intakes from the new Australian Dietary Guidelines (ADG 2013).

Cross-sectional study using data from the Australian Longitudinal Study on Women's Health. Diet was assessed using a validated FFQ.

Two nationally representative age cohorts of Australian women.

Women in the young cohort (born 1973–1978, aged 31–36 years) and mid-age cohort (born 1946–1951, aged 50–55 years). Women (n 18 226) were categorised into three groups: ‘young women’ (n 5760), young ‘pregnant women’ at the time or who had given birth in the 12 months prior to the survey (n 1999) and ‘mid-age women’ (n 10 467).

Less than 2 % of women in all three groups attained the ADG 2013 recommendation of five daily servings of vegetables, with the majority needing more than two additional servings. For young women, less than one-third met recommendations for fruit (32%) and meat and alternatives (28 %), while only a small minority did so for dairy (12 %) and cereals (7 %). Fifty per cent of pregnant women met guidelines for fruit, but low percentages reached guidelines for dairy (22 %), meat and alternatives (10 %) and cereals (2·5 %). For mid-age women, adherence was higher for meat and alternatives (41 %) and cereals (45 %), whereas only 1 % had the suggested dairy intake of four daily servings.

For most women to follow ADG 2013 recommendations would require substantially increased consumption of cereals, vegetables and dairy. Findings have implications for tailoring the dissemination of dietary guidelines for women in different age groups and for pregnant women.

We compared a whole-blood interferon-γ release assay (QuantiFERON-TB Gold In-Tube test, hereafter “QFT-in tube test”) with a tuberculin skin test (TST) to determine which test more accurately identified latent Mycobacterium tuberculosis infection in healthcare staff.

A total of 481 hospital staff members were recruited from 5 hospitals in Melbourne, Australia. They provided information about demographic variables and tuberculosis (TB) risk factors (ie, birth or travel in a country with a high prevalence of TB, working in an occupation likely to involve contact with M. tuberculosis or individuals with TB, or being a household contact of an individual with a proven case of pulmonary TB). The QFT-in tube test and the TST were administered in accordance with standardized protocols. Concordance between the test results and positive risk factors was analyzed using the к statistic, the McNemar test, and logistic regression.

A total of 358 participants had both a TST result and a QFT-in tube test result available for comparison. There were fewer positive QFT-in tube test results than positive TST results (6.7% vs. 33.0%; P < .001). Agreement between the tests was poor (71%; к = 0.16). A positive QFT-in tube test result was associated with birth in a country with a high prevalence of TB, the number of years an individual had lived in a country with a high prevalence of TB (ie, the effect of each additional year, treated as a continuous variable), and high-risk occupational contact. A positive TST result was associated with older age, receipt of bacille Calmette-Guérin (BCG) vaccination, and working in an occupation that involved patient contact. Receipt of BCG vaccination was most strongly associated with discordant results in instances in which the TST result was positive and the QFT-in tube test result was negative.

In a population of healthcare staff with a low prevalence of TB and a significant rate of BCG vaccination, a positive QFT-in tube test result was associated with the presence of known risk factors for TB exposure, whereas a positive TST result was more strongly associated with a prior history of BCG vaccination.

To examine statistical models that have been used to predict the cessation of breast–feeding.

In nutritional epidemiology, a knowledge of risk factors that lead to breast-feeding cessation is essential to promote optimal infant health by increasing or sustaining breast–feeding rates. However, a number of methodological issues complicate the measurement of such risk factors. It is important when building multivariate models that variables entered into the model are not intervening variables, factors on the causal pathway or surrogate outcomes. Inclusion of these types of variable can lead to inaccurate models and biased results. A factor often cited to predict breast–feeding is ‘intention to breast–feed’ prior to the birth of the infant, although this factor is directly on the causal decision–making pathway. Another factor often cited is the age of introduction of formula feeding, which is actually part of the outcome variable because formula feeding defines the difference between full, complementary and no breast-feeding. Rather than include these as risk factors in multivariate models, factors removed from the causal pathway such as influences of educational practices, including advice to complementary feed, and beliefs and attitudes of families and health-care practitioners should be measured.

The accurate quantification of modifiable risk factors is essential for designing public health education campaigns that are effective in sustaining or increasing breast–feeding duration.