Deakin University, Institute for Physical Activity and Nutrition (IPAN), Geelong, Australia.
Deakin University, Institute for Physical Activity and Nutrition (IPAN), Geelong, Australia.
Prev Med. 2018 Jun;111:248-253. doi: 10.1016/j.ypmed.2018.03.003. Epub 2018 Mar 12.
This study examined cross-sectional and prospective associations between typologies of neighbourhood food environment and dietary patterns among 10-12 year-old children. Baseline data were collected in 2003 and follow-up data in 2006 from children in Melbourne or Geelong. Parents completed a food frequency questionnaire at both time points. 'Healthful' and 'energy-dense' dietary pattern scores were computed. A Geographic Information System was used to determine the presence or absence of food outlets (cafés/restaurant; fast food; supermarkets/grocery stores; convenience store; greengrocer; and butcher, seafood or poultry retailer) within an 800 m road network buffer of home. Three typologies were identified: 1-variety of food outlets, including those selling core/fresh foods (n = 96); 2-café/restaurant and convenience (n = 160); 3-few types of outlets (n = 208). Latent class analysis was used to identify underlying unobservable typologies of neighbourhood food outlet availability. Linear mixed models were fitted to determine cross-sectional (n = 439) and longitudinal (n = 173) associations between the three identified neighbourhood typologies and each (log-transformed) dietary pattern, accounting for clustering within families and schools. There was little evidence of cross-sectional associations. The longitudinal analyses showed that compared to those with a variety of food outlets, those with few types had 25% lower scores for the healthful dietary pattern (p < 0.05) three years later. For optimal dietary patterns, availability of a variety of food outlets close to home, particularly those where core/fresh foods are available, may be important.
本研究考察了 10-12 岁儿童的邻里食物环境类型与饮食模式之间的横断面和前瞻性关联。基线数据于 2003 年收集,随访数据于 2006 年从墨尔本或吉朗的儿童中收集。父母在两个时间点都完成了食物频率问卷。计算了“健康”和“高能量”饮食模式得分。使用地理信息系统来确定家庭 800 米道路网络缓冲区以内是否存在食物销售点(咖啡馆/餐厅;快餐店;超市/杂货店;便利店;蔬菜水果店;肉店、海鲜或家禽零售商)。确定了三种类型:1-多种食物销售点,包括销售核心/新鲜食品的销售点(n=96);2-咖啡馆/餐厅和便利店(n=160);3-几种类型的销售点(n=208)。使用潜在类别分析来识别邻里食物销售点可获得性的潜在不可观测类型。线性混合模型用于确定三种确定的邻里类型与每种(对数转换)饮食模式之间的横断面(n=439)和纵向(n=173)关联,同时考虑到家庭和学校内的聚类。几乎没有证据表明存在横断面关联。纵向分析表明,与拥有多种食物销售点的人相比,拥有较少类型的人在三年后健康饮食模式的得分低 25%(p<0.05)。对于最佳饮食模式,家庭附近有多种食物销售点,特别是有核心/新鲜食品的销售点,可能很重要。