Please use this identifier to cite or link to this item: https://repository.monashhealth.org/monashhealthjspui/handle/1/58103
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dc.contributor.authorLloyd M.-
dc.contributor.authorRodda S.-
dc.contributor.authorMorton J.-
dc.contributor.authorHu Y.-
dc.contributor.authorCallander E.-
dc.contributor.authorCookson R.-
dc.contributor.authorTeede H.-
dc.contributor.authorAdemi Z.-
dc.date.accessioned2026-04-26T23:40:49Z-
dc.date.available2026-04-26T23:40:49Z-
dc.date.copyright2026-
dc.date.issued2026-04-06en
dc.identifier.citationValue in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research. (no pagination), 2026. Date of Publication: 26 Mar 2026.-
dc.identifier.urihttps://repository.monashhealth.org/monashhealthjspui/handle/1/58103-
dc.description.abstractOBJECTIVES: To evaluate the population net health benefit and distributional health impact across socioeconomic sub-groups when considering alternative target populations for implementing antenatal lifestyle interventions in Australia. METHOD(S): Differences in the distributions of health within population sub-groups defined by Socio-Economic Index for Areas (SEIFA) quintiles were compared for standard care (no routine antenatal lifestyle intervention) versus subsidised provision to: 1) all pregnant women, 2) women with body mass index (BMI) >=25, 3) women aged >=30 years, or 4) women giving birth within the public health system. Distributional cost-effectiveness analysis of the alternative implementation strategies was conducted to model the impact on disease incidence (gestational and type-2 diabetes), direct healthcare costs, opportunity costs, mortality and quality-adjusted life years for socioeconomic sub-groups. Data were obtained from national statistics, registries and the literature. Value judgements regarding aversion to social inequality in health were captured using the Atkinson index. Extensive sensitivity analyses were conducted. RESULT(S): At an opportunity cost threshold of AU$31,157 (2024 prices), all implementation strategies improved overall population health and reduced health inequality compared with current standard care. Provision to women with a BMI>=25 generated the highest population net health benefit, while provision only within the public health system generated the greatest reduction in health inequality. Sensitivity analyses did not materially change these findings. CONCLUSION(S): Among the targeted strategies evaluated, limiting implementation to women with BMI>=25 is likely to result in the greatest incremental population net health gains and is the preferred strategy when trade-offs between efficiency and health equity are considered.Copyright © 2026. Published by Elsevier Inc.-
dc.relation.ispartofValue in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research-
dc.titleDistributional cost-effectiveness analysis of antenatal lifestyle interventions to reduce the incidence of gestational diabetes and type-2 diabetes.-
dc.typeArticle In Press-
dc.identifier.affiliationMonash University - School of Public Health and Preventative Medicine-
dc.identifier.affiliationMonash University - Monash Centre for Health Research and Implementation-
dc.identifier.doihttps://dx.doi.org/10.1016/j.jval.2026.03.005-
dc.publisher.placeUnited States-
dc.identifier.pubmedid41903800-
dc.identifier.institution(Lloyd) Health Economics and Policy Evaluation Research, Monash Institute of Pharmaceutical Sciences, Parkville, Victoria, Australia; Allergy Immunology, Murdoch Children's Research Institute, Parkville, Victoria, Australia-
dc.identifier.institution(Rodda) Health Economics and Policy Evaluation Research, Monash Institute of Pharmaceutical Sciences, Parkville, VIC, Australia-
dc.identifier.institution(Morton) Health Economics and Policy Evaluation Research, Monash Institute of Pharmaceutical Sciences, Parkville, Victoria, Australia; Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia; School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia-
dc.identifier.institution(Hu) School of Public Health, University of Technology Sydney, Sydney, NSW, Australia-
dc.identifier.institution(Callander) School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia; School of Public Health, University of Technology Sydney, Sydney, New South Wales, Australia-
dc.identifier.institution(Cookson) Centre for Health Economics, University of York, England, United Kingdom; Saw Swee Hock School of Public Health, University of Singapore, Singapore-
dc.identifier.institution(Teede) Monash Health Centre for Research and Implementation, Monash University, Clayton, VIC, Australia-
dc.identifier.institution(Ademi) Health Economics and Policy Evaluation Research, Monash Institute of Pharmaceutical Sciences, Parkville, Victoria, Australia; School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia-
dc.identifier.affiliationmh(Morton) School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australiaen
dc.identifier.affiliationmh(Callander) School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia; School of Public Healthen
dc.identifier.affiliationmh(Teede) Monash Health Centre for Research and Implementation, Monash University, Clayton, VIC, Australiaen
dc.identifier.affiliationmh(Ademi) School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australiaen
item.fulltextNo Fulltext-
item.openairetypeArticle In Press-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
crisitem.author.deptPharmacy-
crisitem.author.deptEndocrinology-
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