Dietary behaviors of adults born prematurely may explain future risk for cardiovascular disease

Abstract

Being born prematurely associates with greater cardiovascular disease (CVD) risk in adulthood. Less understood are the unique and joint associations of dietary patterns and behaviors to this elevated risk among adults who are born prematurely. We aimed to model the associations between term status, dietary and lifestyle behaviors with CVD risk factors while accounting for the longitudinal effects of family protection, and medical or environmental risks. In wave-VIII of a longitudinal study, 23-year olds born prematurely (PT-adults, n=129) and full term (FT-adults, n=38) survey-reported liking for foods/beverages and activities, constructed into indexes of dietary quality and sensation-seeking, dietary restraint and physical activity. Measured CVD risk factors included fasting serum lipids and glucose, blood pressure and adiposity. In bivariate relationships, PT-adults reported lower dietary quality (including less affinity for protein-rich foods and higher affinity for sweets), less liking for sensation-seeking foods/activities, and less restrained eating did FT-adults. In comparison to nationally-representative values and the FT-adults, PT-adults showed greater level of CVD factors for blood pressure and serum lipids. In structural equation modeling, dietary quality completely mediated the association between term status and HDL-cholesterol (higher quality, lower HDL-cholesterol) yet joined term status to explain variability in systolic blood pressure (PT-adults with lowest dietary quality had highest blood pressures). Through lower dietary quality, being born prematurely was indirectly linked to higher cholesterol/HDL, higher LDL/HDL and elevated waist/hip ratios. The relationship between dietary quality and CVD risk was strongest for PT-adults who had developed greater cumulative medical risk. Protective environments failed to attenuate relationships between dietary quality and elevated CVD risk among PT-adults. In summary, less healthy dietary behaviors contribute to elevated CVD risk among young adults who are born prematurely.

Pediatric Adapted Liking Survey: A Novel, Feasible and Reliable Dietary Screening in Clinical Practice

“…Survey-reported preferences for foods/beverages can serve as proxy of usual intake as supported by its correlation with biomarkers of nutritional status [Pallister et al, 2015;Sharafi et al, 2015Sharafi et al, , 2016. Assessing preference is cognitively easier than recalling behavior [Johnson, 1983] required of dietary assessment/screening tools.…”

“…Alternatively, asking about food/beverage preference is cognitively simpler, quicker and often less biased. Reported food preference correlates with reported intake [Lanfer et al, 2012;Sharafi et al, 2015;Tuorila et al, 2008] and biomarkers of dietary intake and/or adiposity in children and adults [Pallister et al, 2015;Sharafi et al, 2016]. Elevated preference for sweet foods is observed among children who have greater adiposity [Lanfer et al, 2012] and caries [Maciel et al, 2001].…”

Characterizing and improving the sensory and hedonic responses to polyphenol-rich aronia berry juice

“…The food items fell into major food groups (fruits, vegetables, high-fat, grains, dairy products, meats, alcoholic beverages) as well as sensory groups of sweet, salty, sour/bitter, and spicy. Survey liking serves as a proxy for dietary intake as it correlates with reported intake (Drewnowski & Hann, 1999; Duffy et al, 2007; H; Tuorila et al, 2008), biomarkers of nutritional status (Pallister et al, 2015; Scarmo et al, 2012; Sharafi et al, 2015), serum lipids (Sharafi, Duffy, Miller, Winchester, & Sullivan, 2016), and adiposity (Duffy et al, 2007; Sharafi et al, 2015). The non-food items in the survey and directions for rating the level of liking/disliking reinforce that the scale applies to all experiences (i.e., generalized) and supports the ability to compare liking/disliking ratings between individuals (Bartoshuk, Duffy, Hayes, Moskowitz, & Snyder, 2006).…”

“…A dietary quality score was formed from the food groups and overall score for the liking of healthy foods as reported previously (Sharafi et al, 2015, 2016). Liking scores were treated continuously (±100 points) and conceptually grouped, a variety score formed (# healthy foods rated as at least liked and mathematically converted to a ±100 score), and weights applied for averaging into a dietary quality index.…”

“…Liking scores were treated continuously (±100 points) and conceptually grouped, a variety score formed (# healthy foods rated as at least liked and mathematically converted to a ±100 score), and weights applied for averaging into a dietary quality index. Previous latent variable analysis (Sharafi et al, 2016) has shown adequate factor structure and internal reliability. Conceptual weights were assigned prior to averaging into a dietary quality index: fruits/vegetables (+3), protein (+1), fat (−3), sweets (−3), salty food (−3), and variety score (+2), consistent with dietary quality indices (Kourlaba & Panagiotakos, 2009).…”