title: Assessment and significance of 24-h energy intake patterns among young and aged non-affluent southern US women.
abstract: Energy intake patterns that may impact health status among non-affluent southern U.S. women from small urban communities have not been evaluated extensively. Usual intake estimates are confounded by factors such as validity of intake methods and socioeconomic status. Typical 24-h energy intakes were reported by Caucasian (CA, n=149) and African-American (AA, n=110) women; at 43% of this sub-population, AA women are appropriately and proportionately represented. Daily energy intake was examined for these non-pregnant females, 24 to 93 y of age, to define typical energy, carbohydrate, protein, and fat intake. Study groups were: 24-29 y, 30-39 y, 40-49 y, 50-59 y, 60-69 y, 70-79 y, and 80-93 y. Statistical comparisons of nutrient variables by age were made by least squares means between groups. Body mass index (BMI) calculations accounted for differences in height and relative body mass. Both races reported similar energy intakes and significant (P<0.05) decreases with age were noted. Energy intakes were 15-40% below recommended levels, similar to reported values; senior lunch programs ameliorated declines among some women >60 y. More daily calories (52-62%) were provided by carbohydrates, followed by fat (26-35%) and protein (14-17%) findings in close agreement with health recommendations. Time-of-day intake patterns suggest women >59 y consume larger noon meals. BMI for AA women was greater (P<0.05) than that of CA women between 30-59 y. At 24-29 y, AA women had lowest BMI values; BMI decreases occurred in CA women after 80 y. These factors may impact the health of non-affluent southern AA and CA women, particularly the elderly who may require guidance for diet planning and intake intervention programs.
authors.affiliation: The Bionetics Corporation, National Center for Toxicological Research, Jefferson, AR 72079, USA.
authors.forename: S M
authors.initials: SM
authors.lastname: Lewis
authors.forename: M A
authors.initials: MA
authors.lastname: Mayhugh
authors.forename: S C
authors.initials: SC
authors.lastname: Freni
authors.forename: S S
authors.initials: SS
authors.lastname: Cardoso
authors.forename: C
authors.initials: C
authors.lastname: Buffington
authors.forename: K
authors.initials: K
authors.lastname: Jairaj
authors.forename: A
authors.initials: A
authors.lastname: Turturro
authors.forename: R J
authors.initials: RJ
authors.lastname: Feuers
mesh_terms: D000328:Adult; D001741:Black or African American / Q000706:statistics & numerical data*; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000502:physiology*; D015992:Body Mass Index; D004032:Diet; D004040:Dietary Carbohydrates / Q000008:administration & dosage; D004041:Dietary Fats / Q000008:administration & dosage; D004044:Dietary Proteins / Q000008:administration & dosage; D002149:Energy Intake; D005260:Female; D005504:Food Analysis; D006801:Humans; D011939:Mental Recall; D008875:Middle Aged; D015596:Nutrition Assessment; D012959:Socioeconomic Factors; D044465:White People / Q000706:statistics & numerical data*
chemical_list: D004040:Dietary Carbohydrates; D004041:Dietary Fats; D004044:Dietary Proteins