Effect of voluntary Health Star Rating labels on healthier food purchasing in New Zealand: longitudinal evidence using representative household purchase data.

Front-of-pack labelling (FoPL) aims to promote healthier diets by altering consumer food purchasing behaviour. We quantify the impact of the voluntary Health Star Rating (HSR) FoPL adopted by New Zealand (NZ) in 2014, on (i) the quantity of foods purchased by HSR scores and food groups and (ii) the quantities of different nutrients purchased. We used Nielsen HomeScan household purchasing panel data over 2013-2019, linked to Nutritrack packaged food composition data. Fixed effects analyses were used to estimate the association of HSR with product and nutrient purchasing. We controlled for NZ-wide purchasing trends and potential confounding at the household and product level. In 2019, HSR-labelled products accounted for 24% (2890) of 12 040 products in the dataset and 32% of purchasing volume. Of HSR-labelled products, 1339 (46%) displayed a rating of 4.0-5.0 stars and 556 (19%) displayed a rating of 0.5-2.0 stars. We found little or no association between HSR labelling and the quantities of different foods purchased. Introduction of HSR was, however, associated with lower sodium (-9%, 95% CI -13% to -5%), lower protein (-3%, 95% CI -5% to 0%) and higher fibre (5%, 95% CI 2% to 7%) purchases when purchased products carrying an HSR were compared with the same products prior to introduction of the programme. Robust evidence of HSR labelling changing consumer purchasing behaviour was not observed. The positive effect on nutrient purchasing of HSR-labelled foods likely arises from reformulation of products to achieve a better HSR label.

The effects of self-assessed health: Dealing with and understanding misclassification bias.

Self-assessed health (SAH) is often used in health econometric models as the key explanatory variable or as a control variable. However, there is evidence questioning its test-retest reliability, with up to 30% of individuals changing their response. Building on recent advances in the econometrics of misclassification, we develop a way to consistently estimate and account for misclassification in reported SAH by using data from a large representative longitudinal survey where SAH was elicited twice. From this we gain new insights into the nature of SAH misclassification and its potential for biasing health econometric estimates. The results from applying our approach to nonlinear models of long-term mortality and chronic morbidities reveal that there is substantial heterogeneity in misclassification patterns. We find that adjusting for misclassification is important for estimating the impact of SAH. For other explanatory variables of interest, we find significant but generally small changes to their estimates when SAH misclassification is ignored.

The effect of income-based mandates on the demand for private hospital insurance and its dynamics.

We examine the effect of an income-based mandate on the demand for private hospital insurance and its dynamics in Australia. The mandate, known as the Medicare Levy Surcharge (MLS), is a levy on taxable income that applies to high-income individuals who choose not to buy private hospital insurance. Our identification strategy exploits changes in MLS liability arising from both year-to-year income fluctuations, and a reform where income thresholds were increased significantly. Using data from the Household, Income and Labour Dynamics in Australia longitudinal survey, we estimate dynamic panel data models that account for persistence in the decision to purchase insurance stemming from unobserved heterogeneity and state dependence. Our results indicate that being subject to the MLS penalty in a given year increases the probability of purchasing private hospital insurance by between 2 to 3 percent in that year. If subject to the penalty permanently, this probability grows further over the following years, reaching 13 percent after a decade. We also find evidence of a marked asymmetric effect of the MLS, where the effect of the penalty is about twice as large for individuals becoming liable compared with those going from being liable to not being liable. Our results further show that the mandate has a larger effect on individuals who are younger.

The impact of voluntary front-of-pack nutrition labelling on packaged food reformulation: A difference-in-differences analysis of the Australasian Health Star Rating scheme.

BACKGROUND: Front-of-pack nutrition labelling (FoPL) of packaged foods can promote healthier diets. Australia and New Zealand (NZ) adopted the voluntary Health Star Rating (HSR) scheme in 2014. We studied the impact of voluntary adoption of HSR on food reformulation relative to unlabelled foods and examined differential impacts for more-versus-less healthy foods. METHODS AND FINDINGS: Annual nutrition information panel data were collected for nonseasonal packaged foods sold in major supermarkets in Auckland from 2013 to 2019 and in Sydney from 2014 to 2018. The analysis sample covered 58,905 unique products over 14 major food groups. We used a difference-in-differences design to estimate reformulation associated with HSR adoption. Healthier products adopted HSR more than unhealthy products: >35% of products that achieved 4 or more stars displayed the label compared to <15% of products that achieved 2 stars or less. Products that adopted HSR were 6.5% and 10.7% more likely to increase their rating by ≥0.5 stars in Australia and NZ, respectively. Labelled products showed a -4.0% [95% confidence interval (CI): -6.4% to -1.7%, p = 0.001] relative decline in sodium content in NZ, and there was a -1.4% [95% CI: -2.7% to -0.0%, p = 0.045] sodium change in Australia. HSR adoption was associated with a -2.3% [-3.7% to -0.9%, p = 0.001] change in sugar content in NZ and a statistically insignificant -1.1% [-2.3% to 0.1%, p = 0.061] difference in Australia. Initially unhealthy products showed larger reformulation effects when adopting HSR than healthier products. No evidence of a change in protein or saturated fat content was observed. A limitation of our study is that results are not sales weighted. Thus, it is not able to assess changes in overall nutrient consumption that occur because of HSR-caused reformulation. Also, participation into labelling and reformulation is jointly determined by producers in this observational study, impacting its generalisability to settings with mandatory labelling. CONCLUSIONS: In this study, we observed that reformulation changes following voluntary HSR labelling are small, but greater for initially unhealthy products. Initially unhealthy foods were, however, less likely to adopt HSR. Our results, therefore, suggest that mandatory labelling has the greatest potential for improving the healthiness of packaged foods.

Consistent estimation of zero-inflated count models.

Applications of zero-inflated count data models have proliferated in health economics. However, zero-inflated Poisson or zero-inflated negative binomial maximum likelihood estimators are not robust to misspecification. This article proposes Poisson quasi-likelihood estimators as an alternative. These estimators are consistent in the presence of excess zeros without having to specify the full distribution. The advantages of the Poisson quasi-likelihood approach are illustrated in a series of Monte Carlo simulations and in an application to the demand for health services.