Rurality and dietary patterns: associations in a UK cohort study of 10-year-old children

Abstract

Objective: Despite differences in obesity and ill health between urban and rural areas in the UK being well documented, very little is known about differences in dietary patterns across these areas. The present study aimed to examine whether urban/rural status is associated with dietary patterns in a population-based UK cohort study of children. Design: Dietary patterns were obtained using principal components analysis and cluster analysis of 3 d diet records collected from children at 10 years of age. Rurality was obtained from the 2001 UK Census urban/rural indicator at the time of dietary assessment. General linear models were used to examine the relationship between rurality and dietary pattern scores from principal components analysis; multinomial logistic regression was used to assess the association between rurality and dietary clusters. Setting: The Avon Longitudinal Study of Parents and Children (ALSPAC), South West England. Subjects: Children (n 5677) aged 10 years (2817 boys and 2860 girls). Results: After adjustment, increases in rurality were associated with increased scores on the 'health awareness' dietary pattern (β = 0·35; 95 % CI 0·14, 0·56; P < 0·001 for the most rural compared with the most urban group) and lower scores on the 'packed lunch/snack' dietary pattern (β = − 0·39; 95 % CI − 0·59, − 0·19; P < 0·001 for the most rural compared with the most urban group). The odds ratio for participants being in the 'healthy' compared with the 'processed' dietary cluster for the most rural areas was 1·61 (95 % CI 1·05, 2·49; P = 0·02) compared with those in the most urban areas. Conclusions: There is evidence to suggest that differences exist in dietary patterns between rural and urban areas. Similar results were found using two different methods of dietary pattern analysis, showing that children residing in rural households were more likely to consume healthier diets than those in urban households.

Diet diversity score and healthy eating index in relation to diet quality and socio-demographic factors: results from a cross-sectional national dietary survey of Swedish adolescents

“…In a Finnish national survey, children living in semi-urban areas had poorer diet quality than those in urban areas, as measured by the Finnish Children Healthy Eating Index (13) . In contrast, a regional survey in South West Britain found healthier dietary patterns in rural children compared with urban, including lower intake of snacks and processed food (14) .…”

The Association Between Dietary Pattern and Weight Status in School-Aged Children: A Cross-Sectional Study

“…The cause of differences other than similarities mentioned in the identified dietary patterns could be reported as differences between rural and urban environments, such as access to food, employment, and household income situation (27). Morris and Northstone (28) reported that rural children follow more traditional and healthier dietary patterns, while urban children follow more "fast and processed foods" dietary patterns in their study on a 10-year-old Cohort in the UK. This claim was also confirmed by mixed and traditional dietary patterns in the present study.…”

Data Resource Profile: The ALSPAC birth cohort as a platform to study the relationship of environment and health and social factors

“…Genomic investigations have identified how genetic traits have the potential to influence the domestic/personal environmental exposures, for example: where genetic propensity to armpit odour was linked to deodorant use 25 ; and an association between a single nucleotide polymorphism (SNP) in the oxytocin receptor gene to features of the maternal diet; 26 investigations assessing associations between health outcomes and workplace exposures. These indicated an association between paternal occupation and subfertility 27 and showed some weak evidence that certain maternal occupations were associated with low birth weights 28 ;investigations considering the impact of residential location and residential movement/migration on health and social outcomes, identifying associations between: residential rurality and diet; 29 the impact of underlying confounding factors to explain previously identified associations between residential movement and cannabis use, 14 residential stability and poor mental health; 30 and the impact of major life events on residential mobility; 31 investigations considering movements between places (e.g. the journey from home to school); identifying associations with fast-food consumption 32 and the role of mode of travel choices on activity levels; 33 conducting methodological work to develop environmental exposure modelling techniques within longitudinal research studies, including modelling particulate matter (PM 2.5 , PM 10 ) exposures and CO2 exposures; 12 , 34 neighbourhood measures (e.g.…”

“…investigations considering the impact of residential location and residential movement/migration on health and social outcomes, identifying associations between: residential rurality and diet; 29 the impact of underlying confounding factors to explain previously identified associations between residential movement and cannabis use, 14 residential stability and poor mental health; 30 and the impact of major life events on residential mobility; 31 …”