Data from: Meta-analysis of variance: an illustration comparing the effects of two dietary interventions on variability in weight

Meta-analysis, which drives evidence-based practice, typically focuses on
the average response of subjects to a treatment. For instance in
nutritional research the difference in average weight of participants on
different diets is typically used to draw conclusions about the relative
efficacy of interventions. As a result of their focus on the mean,
meta-analyses largely overlook the effects of treatments on inter-subject
variability. Recent tools from the study of biological evolution, where
inter-individual variability is one of the key ingredients for evolution
by natural selection, now allow us to study inter-subject variability
using established meta-analytic models. Here we use meta-analysis to study
how low carbohydrate (LC) ad libitum diets and calorie restricted diets
affect variance in mass. We find that LC ad libitum diets may have a more
variable outcome than diets that prescribe a reduced calorie intake. Our
results suggest that whilst LC diets are effective in a large proportion
of the population, for a subset of individuals, calorie restricted diets
may be more effective. There is evidence that LC ad libitum diets rely on
appetite suppression to drive weight loss. Extending this hypothesis, we
suggest that between-individual variability in protein appetite may drive
the trends that we report. A priori identification of an individual’s
target intake for protein may help define the most effective dietary
intervention to prescribe for weight loss.

支撑循证实践的元分析（meta-analysis）通常聚焦于受试者对干预措施的平均反应。例如在营养学研究中，研究者通常通过比较不同饮食干预组受试者的平均体重差异，来推断各类干预手段的相对有效性。由于元分析聚焦于均值，其大多忽略了干预措施对受试者间变异性的影响。近年来，生物进化研究领域发展出相关工具——个体间变异性是自然选择驱动进化的关键要素之一——如今我们可借助这些工具，通过成熟的元分析模型来研究受试者间变异性。本研究借助元分析方法，探究自由进食低碳水（low carbohydrate, LC）饮食与热量限制饮食对体重变异的影响。研究结果显示，自由进食低碳水饮食的干预效果变异性可能高于热量限制饮食组。本研究结果表明，尽管低碳水饮食对绝大多数人群有效，但对于部分个体而言，热量限制饮食的减重效果可能更佳。有研究证据显示，自由进食低碳水饮食通过抑制食欲来实现减重。基于这一假说进行拓展，我们提出：个体间蛋白质食欲的变异性，或许是本研究观测到的上述趋势的驱动因素。预先识别个体的蛋白质目标摄入量，或有助于确定针对减重的最优饮食干预方案。