Associations between a home food inventory and selected noncommunicable disease risk factors in 50 year old Cantabrians

home food inventory;obesity;CVD;food environment

Grant, Emily Jane Maria ; Skidmore, Paula ; Gearry, Richard

University of Otago

关键词: home food inventory;    obesity;    CVD;    food environment;   

Others  :  https://ourarchive.otago.ac.nz/bitstream/10523/3793/1/GrantEmilyJ2013MDiet.pdf

美国|英语

来源: Otago University Research Archive

【 摘 要 】

Background: A balanced diet plays an important role in the prevention of noncommunicable chronic diseases including obesity and cardiovascular disease [CVD]. Obesity is associated with CVD risk factors, making the two disease states inextricably linked. Emerging research shows targeting food environments may be an effective strategy to improve diet, thereby reducing disease burden and risk factors. In New Zealand [NZ], the home is arguably the most important food environment and better understanding of food available in the home may inform future public health strategies. Aim: To examine whether the home food environment, measured by HFI, is associated with modifiable CVD risk factors in 151 CHALICE study participants. Methods: CHALICE is a longitudinal study examining the health and ageing of 50 year old Cantabrians. Participants attend a full day assessment and provide data on a variety of health topics. Data used in this thesis included two HFI scores (obesogenic and fruit/vegetable scores) which were compared to: nutrients from FBD (total energy [TE], total fat [TF], and saturated fat [SAFA]), lipid profile (total cholesterol [TC], low density lipoprotein [LDL], high density lipoprotein [HDL], TC:HDL ratio and triglyceride [TAG]) and body composition (body mass index [BMI], waist circumference [WC] and bio-electrical impedance analysis [BIA]). Each variable was categorised into dichotomous categories of low and high and binary logistic regression was used to predict relationships. Analyses were run separately for each HFI score with sex and ethnicity as covariates. Results: One hundred and fifty one (75.5%) participants completed the HFI and FBD and were included in analyses.Both HFI scores were associated with SAFA intake but neither was associated with energy or total fat intake. Those with a high obesogenic score were 11 times more likely to have a high SAFA intake (p < 0.001). A high fruit/vegetable score was inversely associated with SAFA intake, but the odds ratio [OR] for this was not as high (p = 0.005, OR 0.24). High obesogenic score was associated with high TC and high LDL (p < 0.001, OR 3.47 and p = 0.005, OR 3.55 respectively), but no inverse association was observed with fruit/vegetable score. Of the body composition measures, only WC was significantly associated with HFI: participants with a high obesogenic score had greater odds of having a high WC (p = 0.047, OR 2.05), but the inverse was not true for fruit/vegetable score. Ethnicity was also associated with a high WC: Maori had five times the odds of having a high WC than non-Maori (p = 0.036). Conclusions: Home food inventories have potential to reveal information about the home food environment and its relation to dietary intake and health indices. Saturated fat intake and its adverse effects on health are of particular concern in the CHALICE population, and indeed, NZ. The current study found that HFI can be linked to fat intake and selected chronic disease risk factors, but further research is required to confirm this and determine associations between HFI and other nutrients.