Population Health Innovation Lab, Department of Public Health, Environments and Society, London School of Hygiene & Tropical Medicine, London, United Kingdom.
Sciensano, Brussels, Belgium.
PLoS Med. 2020 Sep 8;17(9):e1003245. doi: 10.1371/journal.pmed.1003245. eCollection 2020 Sep.
Beverages, especially sugar-sweetened beverages (SSBs), have been increasingly subject to policies aimed at reducing their consumption as part of measures to tackle obesity. However, precision targeting of policies is difficult as information on what types of consumers they might affect, and to what degree, is missing. We fill this gap by creating a typology of beverage consumers in Great Britain (GB) based on observed beverage purchasing behaviour to determine what distinct types of beverage consumers exist, and what their socio-demographic (household) characteristics, dietary behaviours, and weight status are.
We used cross-sectional latent class analysis to characterise patterns of beverage purchases. We used data from the 2016 GB Kantar Fast-Moving Consumer Goods (FMCG) panel, a large representative household purchase panel of food and beverages brought home, and restricted our analyses to consumers who purchase beverages regularly (i.e., >52 l per household member annually) (n = 8,675). Six categories of beverages were used to classify households into latent classes: SSBs; diet beverages; fruit juices and milk-based beverages; beer and cider; wine; and bottled water. Multinomial logistic regression and linear regression were used to relate class membership to household characteristics, self-reported weight status, and other dietary behaviours, derived from GB Kantar FMCG. Seven latent classes were identified, characterised primarily by higher purchases of 1 or 2 categories of beverages: 'SSB' (18% of the sample; median SSB volume = 49.4 l/household member/year; median diet beverage volume = 38.0 l), 'Diet' (16%; median diet beverage volume = 94.4 l), 'Fruit & Milk' (6%; median fruit juice/milk-based beverage volume = 30.0 l), 'Beer & Cider' (7%; median beer and cider volume = 36.3 l; median diet beverage volume = 55.6 l), 'Wine' (18%; median wine volume = 25.5 l; median diet beverage volume = 34.3 l), 'Water' (4%; median water volume = 46.9 l), and 'Diverse' (30%; diversity of purchases, including median SSB volume = 22.4 l). Income was positively associated with being classified in the Diverse class, whereas low social grade was more likely for households in the classes SSB, Diet, and Beer & Cider. Obesity (BMI > 30 kg/m2) was more prevalent in the class Diet (41.2%, 95% CI 37.7%-44.7%) despite households obtaining little energy from beverages in that class (17.9 kcal/household member/day, 95% CI 16.2-19.7). Overweight/obesity (BMI > 25 kg/m2) was above average in the class SSB (66.8%, 95% CI 63.7%-69.9%). When looking at all groceries, households from the class SSB had higher total energy purchases (1,943.6 kcal/household member/day, 95% CI 1,901.7-1,985.6), a smaller proportion of energy from fruits and vegetables (6.0%, 95% CI 5.8%-6.3%), and a greater proportion of energy from less healthy food and beverages (54.6%, 95% CI 54.0%-55.1%) than other classes. A greater proportion of energy from sweet snacks was observed for households in the classes SSB (18.5%, 95% CI 18.1%-19.0%) and Diet (18.8%, 95% CI 18.3%-19.3%). The main limitation of our analyses, in common with other studies, is that our data do not include information on food and beverage purchases that are consumed outside the home.
Amongst households that regularly purchase beverages, those that mainly purchased high volumes of SSBs or diet beverages were at greater risk of obesity and tended to purchase less healthy foods, including a high proportion of energy from sweet snacks. These households might additionally benefit from policies targeting unhealthy foods, such as sweet snacks, as a way of reducing excess energy intake.
饮料,尤其是含糖饮料(SSB),作为解决肥胖问题措施的一部分,其消费越来越受到政策的限制。然而,由于缺乏有关政策可能影响哪些消费者以及影响程度的信息,因此难以进行精确的政策定位。我们通过在英国(GB)创建基于观察到的饮料购买行为的饮料消费者分类法来填补这一空白,以确定存在哪些不同类型的饮料消费者,以及他们的社会人口(家庭)特征、饮食行为和体重状况如何。
我们使用横断面潜在类别分析来描述饮料购买模式。我们使用了来自 2016 年 GB 坎塔尔快速消费品(FMCG)小组的数据,这是一个大型家庭购买食品和饮料的代表性样本,并且我们将分析仅限于经常购买饮料的消费者(即每年每户成员购买超过 52 升)(n = 8675)。使用 6 种饮料类别将家庭归入潜在类别:SSB;低热量饮料;果汁和牛奶饮料;啤酒和苹果酒;葡萄酒;瓶装水。使用多项逻辑回归和线性回归将类别成员资格与家庭特征、自我报告的体重状况以及从 GB 坎塔尔 FMCG 中得出的其他饮食行为相关联。确定了 7 个潜在类别,主要由更高的购买 1 或 2 种饮料类别来定义:“SSB”(占样本的 18%;中位数 SSB 量为 49.4 升/家庭成员/年;中位数低热量饮料量为 38.0 升);“低热量饮料”(16%;中位数低热量饮料量为 94.4 升);“果汁和牛奶饮料”(6%;中位数果汁/牛奶饮料量为 30.0 升);“啤酒和苹果酒”(7%;中位数啤酒和苹果酒量为 36.3 升;中位数低热量饮料量为 55.6 升);“葡萄酒”(18%;中位数葡萄酒量为 25.5 升;中位数低热量饮料量为 34.3 升);“水”(4%;中位数水量为 46.9 升);“多样化”(30%;购买的多样性,包括中位数 SSB 量为 22.4 升)。收入与被归类为多样化类别呈正相关,而低社会等级更可能是 SSB、低热量饮料和啤酒和苹果酒类别的家庭。肥胖(BMI > 30 kg/m2)在低热量饮料类别中更为普遍(41.2%,95%CI 37.7%-44.7%),尽管家庭从该类别中获得的饮料能量很少(17.9 千卡/家庭成员/天,95%CI 16.2-19.7)。超重/肥胖(BMI > 25 kg/m2)在 SSB 类别中高于平均水平(66.8%,95%CI 63.7%-69.9%)。当观察所有杂货时,来自 SSB 类别的家庭购买的总能量更高(1943.6 千卡/家庭成员/天,95%CI 1901.7-1985.6),水果和蔬菜的能量比例较低(6.0%,95%CI 5.8%-6.3%),而来自不太健康的食物和饮料的能量比例较高(54.6%,95%CI 54.0%-55.1%)。与其他类别相比,SSB(18.5%,95%CI 18.1%-19.0%)和低热量饮料(18.8%,95%CI 18.3%-19.3%)类别的家庭中来自甜零食的能量比例更高。我们分析的主要限制因素与其他研究一样,是我们的数据不包括家庭在家庭之外消费的食物和饮料购买信息。
在经常购买饮料的家庭中,那些主要购买高 volumes 的 SSB 或低热量饮料的家庭更有可能肥胖,并且往往购买不健康的食物,包括高比例的来自甜零食的能量。这些家庭可能还受益于针对不健康食品(如甜零食)的政策,以减少过量的能量摄入。