Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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    Dietary Patterns and Diet Quality before and/or during Pregnancy and How These Affect Birth Outcomes: A Systematic Review and Meta-analysis
    (Elsevier Inc. on behalf of American Society for Nutrition, 2025-10) Salatas C; Bronnert A; Lawrence R; Alexander T; Wall C; Bloomfield FH; Lin L
    Limited consistent evidence exists on how diet quality before and during pregnancy influences preterm birth and low birthweight risk. This study aims to assess whether diet quality based on dietary patterns before and during pregnancy affects preterm birth and low birthweight risk. We systematically searched 3 electronic databases and 4 registries for randomized controlled trials (RCTs) and quasi-RCTs without restrictions on publication date or language until 22 November, 2024. Included RCTs evaluated dietary patterns to enhance diet quality before/during pregnancy compared with a usual diet or placebo. Results were synthesized using random-effects meta-analyses with risk ratios (RRs) and 95% confidence intervals. Study quality was assessed using the Cochrane Risk of Bias 1 tool, and certainty of evidence was evaluated with the Grading of Recommendations Assessment, Development and Evaluation approach. Twenty-nine RCTs (7367 participants) were included. Improved diet quality through dietary patterns providing the recommended macronutrient intake or high unsaturated fats before and during pregnancy reduced the incidence of low birthweight (<2500 g) (7 RCTs, 2178 participants, RR 0.53 [0.37, 0.77], low certainty of evidence) and have potential benefit for reducing preterm birth (15 RCTs, 4949 participants, RR 0.79 [0.62, 1.02], low certainty of evidence) compared with usual diet. The data available support interventions starting in the first trimester (RR 0.30 [0.11, 0.80]), lasting 4–7 mo (RR 0.52 [0.37, 0.73]), with similar effects in both high-/upper-middle-income [RR 0.44 (0.19, 10.04)] and lower-middle-income (RR 0.44 [0.31, 0.63]) populations, especially in low-risk women (RR 0.52 [0.37, 0.73]). Diets providing the recommended macronutrient intake or high in unsaturated fats significantly reduced risk of low birthweight when initiated in the first trimester and maintained for 4–7 mo, regardless of country-level socioeconomic context. Healthcare providers should consider recommending dietary patterns emphasizing whole foods and high-quality fats as part of early prenatal care.
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    Making predictions under interventions: a case study from the PREDICT-CVD cohort in New Zealand primary care
    (Frontiers Media S.A., 2024-04-03) Lin L; Poppe K; Wood A; Martin GP; Peek N; Sperrin M; Piccininni M
    Background: Most existing clinical prediction models do not allow predictions under interventions. Such predictions allow predicted risk under different proposed strategies to be compared and are therefore useful to support clinical decision making. We aimed to compare methodological approaches for predicting individual level cardiovascular risk under three interventions: smoking cessation, reducing blood pressure, and reducing cholesterol. Methods: We used data from the PREDICT prospective cohort study in New Zealand to calculate cardiovascular risk in a primary care setting. We compared three strategies to estimate absolute risk under intervention: (a) conditioning on hypothetical interventions in non-causal models; (b) combining existing prediction models with causal effects estimated using observational causal inference methods; and (c) combining existing prediction models with causal effects reported in published literature. Results: The median absolute cardiovascular risk among smokers was 3.9%; our approaches predicted that smoking cessation reduced this to a median between a non-causal estimate of 2.5% and a causal estimate of 2.8%, depending on estimation methods. For reducing blood pressure, the proposed approaches estimated a reduction of absolute risk from a median of 4.9% to a median between 3.2% and 4.5% (both derived from causal estimation). Reducing cholesterol was estimated to reduce median absolute risk from 3.1% to between 2.2% (non-causal estimate) and 2.8% (causal estimate). Conclusions: Estimated absolute risk reductions based on non-causal methods were different to those based on causal methods, and there was substantial variation in estimates within the causal methods. Researchers wishing to estimate risk under intervention should be explicit about their causal modelling assumptions and conduct sensitivity analysis by considering a range of possible approaches.