RESEARCH

Prioritizing risk factors to identify preventive interventions for economic assessment

Prioriser les facteurs de risque pour identifier les interventions préventives à évaluer économiquement

Determinación de la prioridad de los factores de riesgo con el fin de identificar las intervenciones preventivas para la evaluación económica

Nick Wilson^I,*; Tony Blakely^I; Rachel H Foster^I; David Hadorn^I; Theo Vos^II

^IDepartment of Public Health, University of Otago, Wellington, PO Box 7343, Wellington South, New Zealand
^IISchool of Population Health, University of Queensland, Herston, Australia

ABSTRACT

OBJECTIVE: To explore a risk factor approach for identifying preventive interventions that require more in-depth economic assessment, including cost-effectiveness analyses.
METHODS: A three-step approach was employed to: (i) identify the risk factors that contribute most substantially to disability-adjusted life years (DALYs); (ii) re-rank these risk factors based on the availability of effective preventive interventions warranting further cost-effectiveness analysis (and in some instances on evidence from existing cost-effectiveness analyses); and (iii) re-rank these risk factors in accordance with their relative contribution to health inequalities. Health inequalities between the Māori and non-Māori populations in New Zealand were used by way of illustration.
FINDINGS: Seven of the top 10 risk factors prioritized for research on preventive interventions in New Zealand were also among the 10 risk factors most highly ranked as contributing to DALYs in high-income countries of the World Health Organization's Western Pacific Region. The final list of priority risk factors included tobacco use; alcohol use; high blood pressure; high blood cholesterol; overweight/obesity, and physical inactivity. All of these factors contributed to health inequalities. Effective interventions for preventing all of them are available, and for each risk factor there is at least one documented cost-saving preventive intervention.
CONCLUSION: The straightforward approach to prioritizing risk factors described in this paper may be applicable in many countries, and even in those countries that lack the capacity to perform additional cost-effectiveness analyses, this approach will still make it possible to determine which cost-effective interventions should be implemented in the short run.

RÉSUMÉ

OBJECTIF: Étudier une approche fondée sur les facteurs de risque pour identifier les interventions préventives nécessitant une évaluation économique plus approfondie, y compris des analyses de rentabilité.
MÉTHODES: Une approche en trois étapes a été utilisée pour (i) identifier les facteurs de risque contribuant en grande partie aux années de vie corrigées du facteur invalidité (AVCI), (ii) reclasser ces facteurs de risque en fonction de la disponibilité des interventions préventives efficaces justifiant une analyse supplémentaire de rentabilité (et, dans certains cas, sur la base de preuves provenant d'analyses de rentabilité existantes), et (iii) reclasser ces facteurs de risque en fonction de leur contribution relative aux inégalités de santé. Les inégalités de santé entre les populations maories et non maories en Nouvelle-Zélande ont été utilisées à titre d'illustration.
RÉSULTATS: Sept des dix principaux facteurs de risque priorisés pour la recherche sur les interventions préventives en Nouvelle-Zélande figuraient également parmi les dix facteurs de risque contribuant le plus aux AVCI dans les pays à revenu élevé de la région du Pacifique occidental de l'Organisation mondiale de la Santé. La liste définitive des facteurs de risque prioritaires incluait le tabagisme, la consommation d'alcool, l'hypertension artérielle, l'hypercholestérolémie, le surpoids/l'obésité et l'inactivité physique. Tous ces facteurs contribuaient à des inégalités de santé. Des interventions efficaces pour prévenir chacun d'eux sont disponibles, et il existe au moins une intervention préventive plus économique connue pour chaque facteur de risque.
CONCLUSION: L'approche simple de priorisation des facteurs de risque décrite dans cet article peut être applicable dans de nombreux pays. Même dans les pays qui n'ont pas la capacité d'effectuer des analyses de rentabilité complémentaires, cette approche permettra de déterminer quelles interventions rentables devraient être mises en œuvre à court terme.

RESUMEN

OBJETIVO: Explorar una estrategia en relación con los factores de riesgo que permita la identificación de las intervenciones preventivas que requieran una evaluación económica de mayor profundidad, incluyendo los análisis de rentabilidad.
MÉTODOS: Se aplicó una estrategia en tres etapas con el fin de (i) identificar los factores de riesgo que contribuyen de manera más significativa a los años de vida ajustados en función de la discapacidad (AVAD); (ii) volver a clasificar estos factores de riesgo en base a la disponibilidad de intervenciones preventivas eficaces que justifiquen la realización de análisis de rentabilidad adicionales (y, en algunos casos, en base a las evidencias procedentes de los análisis de rentabilidad existentes); y (iii) volver a clasificar estos factores de riesgo de acuerdo con su contribución relativa a las desigualdades sanitarias. A modo de ilustración, se analizaron las desigualdades sanitarias entre las poblaciones maoríes y no maoríes de Nueva Zelanda.
RESULTADOS: Siete de los 10 factores de riesgo prioritarios para la investigación sobre las intervenciones preventivas en Nueva Zelanda también se encontraron entre los 10 factores de riesgo con mayor calificación en cuanto a su contribución a los AVAD en países de ingresos altos de la Región del Pacífico Occidental de la Organización Mundial de la Salud. En la lista definitiva de los factores de riesgo prioritarios se incluyeron el tabaquismo, el consumo de alcohol, la presión arterial alta, un nivel elevado de colesterol, el sobrepeso/obesidad y el sedentarismo. Todos estos factores contribuyeron a las desigualdades sanitarias. Se han desarrollado intervenciones eficaces para prevenir todos estos factores, y para cada factor de riesgo se ha documentado al menos una intervención preventiva destinada al ahorro de costes.
CONCLUSIÓN: La sencilla estrategia consistente en establecer la prioridad de los factores de riesgo descritos en este documento puede ser aplicable en muchos países, e incluso en aquellos países que carezcan de la capacidad necesaria para llevar a cabo los análisis de rentabilidad adicionales, esta estrategia también permitirá determinar qué intervenciones rentables se han de aplicar a corto plazo.

Introduction

Most countries seek to improve the health of their populations while reducing health inequalities. They must therefore deploy their health sector resources, which are often scarce, in a manner that maximizes both goals. Preventive interventions are often highly cost-effective¹ and they sometimes promote equity.^2,3 Recent work in Australia has demonstrated that many preventive interventions are cost-effective, and quite a few are actually cost-saving over the long-term. The Australian Assessing Cost-Effectiveness of Prevention (ACE-Prevention) Project reported 23 preventive interventions as being cost-saving or "dominant"; 20 as being "very cost-effective" and 31 as being simply "cost-effective" (i.e. within the range of 10000 to 50 000 Australian dollars [i.e. 9895 to 49 465 United States dollars (US$)] per disability-adjusted life year [DALY] averted).¹

In light of the above and based on the fact that many preventive interventions work through risk factor modification, we sought to develop a systematic approach for identifying those interventions that should be prioritized for more extensive cost-effectiveness analysis (CEA) based on risk factor prioritization. We implicitly sought to identify not only risk factors for which (highly) cost-effective interventions are feasible, but also risk factors that contribute substantially to the burden of disease and whose reduction through effective interventions is therefore more likely to contribute to substantial improvements in health.

We propose a three-step approach: (i) identifying the top priority risk factors, namely those that contribute the greatest number of DALYs; (ii) re-ranking these risk factors based on evidence of the availability of effective interventions that warrant CEA (and, in some instances, on evidence stemming from existing CEAs); and (iii) a final re-ranking based on the extent to which these risk factors contribute to health inequalities. By way of illustration we use health inequalities between Māori and non-Māori population groups in New Zealand.

Methods

Disease burden contributed by risk factors

Comparative risk assessment methods make it possible to compare to what extent different risk factors contribute to the disease burden. Briefly, a burden of disease study is performed to quantify the DALYs contributed by all selected disease conditions. The DALY is a composite of years of life lost due to a particular disease or disability and a morbidity component represented by the number of years lived in a state of disability (e.g. if living with stroke has a disability weight of 0.4 and the average number of years lived with stroke is 10, this amounts to a loss of 4 years of life).

With this information in hand, one can then calculate the disease burden attributable to specific risk factors. For example, in a comparative risk assessment of the burden of disease attributable to tobacco, all diseases that are caused by tobacco smoking are identified, the relative risks for the association between smoking and each disease are assembled, and the population distribution of smoking is determined from surveys. One then posits a counterfactual (but theoretically feasible) distribution for each risk factor. Such a counterfactual distribution would be nil in the case of a dichotomous variable such as smoking, but for a continuous variable such as blood pressure, the counterfactual would be a shifted and compressed distribution with a low mean that is associated with a minimal risk of disease. These data are then combined using population-attributable risk analyses to calculate the percentage of DALYs that a given factor contributes to a particular condition, for instance, the percentage of ischaemic heart disease DALYs contributed by smoking. Finally, one compares the number of DALYs attributable to various risk factors and ranks these factors accordingly.

In previous work in New Zealand, comparative risk assessment methods were used to identify and rank major risk factors for the year 1996,⁴ but rankings were based on numbers of deaths rather than DALYs. Furthermore, such work is now somewhat outdated, as more recent meta-analyses and syntheses of relative risk data have become available. We therefore used the global burden of disease data published more recently by the World Health Organization (WHO) for high-income countries in the Western Pacific Region: Australia, Brunei Darussalam, Japan, New Zealand, the Republic of Korea and Singapore.⁵

Risk factor selection criteria

As a starting point we decided that all the risk factors to be initially considered had to be among the top 15 causes of DALYs in the six aforementioned highincome countries.⁵ That is, we were interested not just in cost-effectiveness, but also in the effect of interventions on population health overall. We then assessed and re-ranked the selected risk factors in terms of: (i) current or predictable future availability of effective preventive interventions targeting the risk factor (and, in some instances, with evidence of cost-effectiveness as well); and (ii) the extent to which the factor contributes to health inequalities. For the first ranking we required the availability of at least one preventive intervention addressing the risk factor for which evidence of cost-effectiveness also existed. For our example of health inequalities drawn from New Zealand, we required that the risk factor contribute substantially to inequalities between the Māori (indigenous) and non-Māori populations (including European, Pacific peoples and Asian people), on the premise that any intervention addressing the risk factor would also reduce these inequalities. Although inequalities exist among other ethnic groups and different socioeconomic strata in New Zealand, the gap between the Māori and non-Māori populations is especially large and of particular concern to health sector policy-makers. In this paper we focus on inequalities between the Māori and non-Māori populations to illustrate how health inequalities can be incorporated into the method we have developed for prioritizing risk factors for future research on the costeffectiveness of preventive interventions.

Literature search

To inform the above process we searched Medline and Google Scholar to identify articles on interventions targeting all 15 initially selected risk factors. We also searched for reports on the New Zealand Ministry of Health web site (www.moh. govt.nz). These searches also served to identify the role played by each risk factor in the health inequalities between the Māori and non-Māori people (e.g. by comparing the hospitalization rates, the mortality rates or other disease burden estimates from epidemiological studies).

Results

The 15 risk factors initially considered from the work of the WHO on burden of disease at the regional level showed good overlap with the risk factors previously prioritized for study in New Zealand (Table 1). Of the 10 risk factors identified by WHO as being the leading contributors to lost DALYs, seven had been previously identified by the New Zealand Ministry of Health as being among the 10 most important risk factors for death in the country (i.e. albeit using a different metric from DALYs).

The last five risk factors listed in Table 1 are not likely to rank higher than the factors appearing higher on the list in terms of the potential benefits of interventions to prevent them. This is because these factors were also ranked lower in the previous burden of disease study conducted in New Zealand, and the difference between them and the top seven in terms of their contribution to DALYs is too large to be plausibly attributable to error. In light of this, we focused on the top 10 risk factors.

The preventive interventions targeting each risk factor are listed in Table 2. Cost-effective preventive interventions (some of which have also been reported as cost-saving)¹ were identified for each factor. We dropped the "occupational risk" category from further consideration because it involved a multitude of interventions specific to certain occupational settings.

It became apparent that most (8/9) of the risk factors in our revised list contributed to health inequalities between Māori and non-Māori people (Table 3). Data on DALYs were not available from previous New Zealand studies, but data on each risk factor's contribution to years-of-life-lost (YLL) in the Māori population were available for six out of nine risk factors (albeit from 1996-1997 and hence somewhat outdated). So we used these data to rank "high blood cholesterol" above "physical inactivity" in our final revisions to the ranking (Table 4). We excluded air pollution from further investigation because of lack of clarity around the importance of environmental interventions for reducing health inequalities between Māori and non-Māori populations.

Table 4 shows additional factors that we considered in the final priority ranking of the eight selected risk factors. Certain areas were assigned lower priority particularly because the strength of the evidence around intervention effectiveness and cost-effectiveness was uncertain.

Inequalities other than those between Māori and non-Māori populations should ideally be included in the risk factor priority-setting process, although not explicitly considered part of it in this paper. The six risk factors we identified as having the highest priority (Table 4) are also relevant for reducing health inequalities affecting the Pacific peoples of New Zealand, and disease burden by age group (i.e. in children or youth and older adults).³² Furthermore, four of the six risk factors are relevant to reducing health inequalities affecting socioeconomically deprived New Zealanders, given that this population group has more adverse risk factor profiles in terms of smoking, alcohol abuse, physical inactivity and overweight or obesity.³²

Discussion

Interpretation of major findings

Our study results, based on WHO regional data on DALYs by risk factor for the New Zealand setting, were fairly consistent with the findings of past work on risk factor prioritization in this country.⁴

The evidence from cost-effectiveness analyses in the literature resulted in changes in the priority ranking of some of the risk factors, but not the top three (tobacco, alcohol use and high blood pressure). From the perspective of health inequalities between the Māori and non-Māori populations, this process produced only modest changes in the rankings, since eight of the nine risk factors being considered in the revised list were found to contribute to inequality. This does not obviate the importance of explicitly considering inequalities in the prioritization process. Rather, it suggests that in New Zealand important health inequalities are present in the overall burden of disease, as measured by DALYs. Our final six top priority risk factors for New Zealand were all among the top seven contributors to DALYs as identified by WHO (Table 1).

Can the methods described in this paper be successfully applied in other countries that need to prioritize risk factors for identifying preventive interventions meriting CEA? We believe that they probably can, but this is a research question in its own right. Since global burden of disease data are available at the country level for all WHO regions and are routinely reported by country income level, there should be a reasonable choice of relevant DALY and comparative risk factor assessment data to draw upon for most countries. Also, the global burden of disease study currently in progress will draw on many additional systematic reviews and will further update burden of disease data. Admittedly, however, the quality of the data pertaining to health inequalities varies enormously across countries and will be largely country-specific.

We focused mainly on identifying those risk factors on which to concentrate for more in-depth CEA of interventions. However, a lack of capacity to undertake country-specific CEA or lack of political will may prevent CEAs from being undertaken in some countries. Nonetheless, we still believe in the usefulness of our approach, since the priority-setting exercise itself and the supporting evidence obtained through literature searches will identify those interventions that are highly likely to be cost-effective in a given country. In fact, Beaglehole et al. have essentially used this approach to recommend five priority actions - tobacco control, salt reduction, improved diets and physical activity, reduction in hazardous alcohol intake and development of essential drugs and technologies - to substantially reduce the global burden of non-communicable diseases in a cost-effective manner.⁴⁴

Strengths and limitations

One strength of our approach is its strong reliance on the DALY metric, which captures both morbidity and mortality. The use of WHO regional data has also allowed us to improve on the more limited and somewhat outdated work on disease burden formerly conducted in New Zealand and to develop an approach that other countries can potentially use in the absence of their own national burden of disease studies. Our approach is also relatively simple and hence more likely to be transparent and acceptable to policy-makers in the health sector.

However, the approach has important limitations. The WHO data on which it relies applies to the regional rather than the country level. Thus, high blood cholesterol is probably a more important risk factor in New Zealand than in other high-income countries in the Western Pacific Region because New Zealanders consume relatively large quantities of dairy products and meat.⁴⁵ Conversely, the urban air pollution is likely to be a less important risk factor than average in New Zealand, where population density and industrialization are low and where the winds are relatively strong. Furthermore, WHO data on risk factors fail to capture the potential contribution of potential upstream determinants (such as poor education, lack of employment or low socioeconomic status), to risk factors such as smoking or alcohol misuse.

Our risk factor prioritization process is further limited by the fact that only one aspect of health inequality in New Zealand was examined, namely, health inequalities between Māori and non-Māori populations. However, the distribution of risk factors in this country is such that a focus on the six top risk factors will undoubtedly benefit Pacific peoples in New Zealand as well as children and youth, older adults and socioeconomically deprived New Zealanders. Furthermore, our analysis did not take into account the potential non-health benefits of preventive interventions, which could enhance their cost-effectiveness from a societal perspective. For example, interventions targeting tobacco and alcohol use could reduce absenteeism and premature death in the workforce, and interventions targeting physical inactivity, such as walking and cycling as commuting options and reduced use of private vehicles, could reduce greenhouse gas emissions.¹⁹ Similarly, dietary interventions to reduce dairy product and meat consumption (to reduce blood cholesterol levels) would lower greenhouse gas emissions from ruminant-based agriculture (especially the greenhouse gas methane).²⁰

Our approach has tended to prioritize those risk factors having a relatively high impact on health and equity. However, other criteria should also be considered in the final process of selecting risk factors and the interventions designed to prevent them. We offer two examples. First, initial scoping of an intervention that is being actively considered for immediate implementation by policy-makers for social or political reasons may suggest that its impact and/or cost-effectiveness will be low. If so, the intervention should be prioritized for a CEA before implementation is decided. Second, policy-makers should ideally get a better sense of the tradeoffs through access to information on a wide range of interventions ranked by cost-effectiveness and by their impact on DALYs.

Implications for further work

The process of prioritizing risk factors to select preventive interventions for further CEA should include consultation with stakeholders. We have already started consulting with representatives of major health agencies, local health authorities, the primary care sector and experts in Māori health in New Zealand. We also plan to apply criteria other than the ones described herein for selecting preventive interventions for CEA, as detailed by ACE-Prevention workers in Australia.¹⁷

Additional research on public attitudes surrounding the importance of risk factors and their preventive interventions should be conducted. There is already evidence that New Zealanders support enhanced tobacco control interventions,⁴⁶ yet support can be fairly nuanced. For instance, most smokers in New Zealand support raising tobacco taxes only if the tax revenue is destined specifically to providing support for smokers wishing to quit and for health promotion.⁴⁷

In countries where important health inequalities exist, such as New Zealand, preventive interventions should also be assessed in terms of their ability to reduce health inequalities in a cost-effective way, since there may be trade-offs between achieving overall gains in population health and gains among specific population groups more heavily affected by certain risk factors. The following are possible ways of incorporating inequalities in health between the general population and ethnic minorities when conducting CEA of preventive interventions:

Although some trade-offs in the benefits afforded by a few preventive interventions are likely to occur, some interventions will result in benefits for all. For instance, higher tobacco prices tend to protect the health of all citizens as well as to reduce health inequalities.³

In summary, our risk factor approach to identifying preventive interventions for further CEA may seem somewhat simplistic. However, it is relatively straightforward and transparent and can be applied in both developed and developing countries. We encourage further research on the use of this approach internationally.

Acknowledgements

We thank NZACE-Prevention and BODE³ team colleagues, particularly Diana Sarfati, for their comments during early versions of this work.

Funding: This project receives funding support from the Health Research Council of New Zealand (Project number 10/248).

Competing interests: None declared.

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Submitted: 1 June 2011
Revised version received: 21 September 2011
Accepted: 26 September 2011
Published online: 14 October 2011

* Correspondence to Nick Wilson (e-mail: nick.wilson@otago.ac.nz).