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Gibson RS, Charrondiere UR, Bell W. Measurement Errors in Dietary Assessment Using Self-Reported 24-Hour Recalls in Low-Income Countries and Strategies for Their Prevention. Adv Nutr 2017; 8:980-991. [PMID: 29141979 PMCID: PMC5683000 DOI: 10.3945/an.117.016980] [Citation(s) in RCA: 140] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Securing accurate measurements of dietary intake across populations is challenging. Of the methods, self-reported 24-h recalls are often used in low-income countries (LICs) because they are quick, culturally sensitive, do not require high cognitive ability, and provide quantitative data on both foods and nutrients. Measuring intakes via 24-h recalls involves 1) collecting data on food intakes, 2) the appropriate use of relevant food-composition data for calculating nutrient intakes, and 3) statistically converting observed intakes to "usual intakes" for evaluating nutrient adequacy or relations between foods and nutrients and health outcomes. Like all dietary methods, 24-h recalls are subject to random errors that lower the precision and systematic errors that can reduce accuracy at each stage of the measurement protocol. Research has identified the potential sources of measurement errors in 24-h recall protocols and emphasized that sources of random error can be reduced by incorporating standardized quality-control procedures and collecting more than one 24-h recall per person, with the number depending on the study objective. Careful design of the initial 24-h recall protocol can take into account potential sources of systematic error, such as day of the week, season, age, etc. Other sources of systematic error (e.g., energy underreporting) can best be detected by including a reference measure (e.g., doubly labeled water to measure energy expenditure). Alternatively, 24-h recall intakes of energy can be compared with same-day weighed intakes. Nevertheless, very few studies in LICs have assessed the validity of 24-h recalls in their study settings or adopted recommended standardized protocols to mitigate random errors. Hence, efforts should be made to improve the assessment, analysis, and interpretation of self-reported 24-h recall data for population studies in LICs. Accurate and precise dietary intake data at the national level can play an essential role in informing food, nutrition, and agricultural policies; food fortification planning; and compliance to food-based dietary guidelines.
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Affiliation(s)
- Rosalind S Gibson
- Department of Human Nutrition, University of Otago, Dunedin, New Zealand
| | | | - Winnie Bell
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA
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Brown DL, Conley KM, Sánchez BN, Resnicow K, Cowdery JE, Sais E, Murphy J, Skolarus LE, Lisabeth LD, Morgenstern LB. A Multicomponent Behavioral Intervention to Reduce Stroke Risk Factor Behaviors: The Stroke Health and Risk Education Cluster-Randomized Controlled Trial. Stroke 2015; 46:2861-7. [PMID: 26374480 DOI: 10.1161/strokeaha.115.010678] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2015] [Accepted: 08/10/2015] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE The Stroke Health and Risk Education Project was a cluster-randomized, faith-based, culturally sensitive, theory-based multicomponent behavioral intervention trial to reduce key stroke risk factor behaviors in Hispanics/Latinos and European Americans. METHODS Ten Catholic churches were randomized to intervention or control group. The intervention group received a 1-year multicomponent intervention (with poor adherence) that included self-help materials, tailored newsletters, and motivational interviewing counseling calls. Multilevel modeling, accounting for clustering within subject pairs and parishes, was used to test treatment differences in the average change since baseline (ascertained at 6 and 12 months) in dietary sodium, fruit and vegetable intake, and physical activity, measured using standardized questionnaires. A priori, the trial was considered successful if any one of the 3 outcomes was significant at the 0.05/3 level. RESULTS Of 801 subjects who consented, 760 completed baseline data assessments, and of these, 86% completed at least one outcome assessment. The median age was 53 years; 84% subjects were Hispanic/Latino; and 64% subjects were women. The intervention group had a greater increase in fruit and vegetable intake than the control group (0.25 cups per day [95% confidence interval: 0.08, 0.42], P=0.002), a greater decrease in sodium intake (-123.17 mg/d [-194.76, -51.59], P=0.04), but no difference in change in moderate- or greater-intensity physical activity (-27 metabolic equivalent-minutes per week [-526, 471], P=0.56). CONCLUSIONS This multicomponent behavioral intervention targeting stroke risk factors in predominantly Hispanics/Latinos was effective in increasing fruit and vegetable intake, reaching its primary end point. The intervention also seemed to lower sodium intake. Church-based health promotions can be successful in primary stroke prevention efforts. CLINICAL TRIAL REGISTRATION URL: http://www.clinicaltrials.gov. Unique identifier: NCT01378780.
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Affiliation(s)
- Devin L Brown
- From the Department of Neurology, Stroke Program, University of Michigan, Ann Arbor (D.L.B., E.S., J.M., L.E.S., L.D.L., L.B.M.); Program of Health Education, School of Health Promotion and Human Performance, Eastern Michigan University, Ypsilanti (K.M.C., J.E.C.); and Departments of Biostatistics (B.N.S.), Health Behavior and Health Education (K.R.), and Epidemiology (L.D.L., L.B.M.), University of Michigan School of Public Health, Ann Arbor.
| | - Kathleen M Conley
- From the Department of Neurology, Stroke Program, University of Michigan, Ann Arbor (D.L.B., E.S., J.M., L.E.S., L.D.L., L.B.M.); Program of Health Education, School of Health Promotion and Human Performance, Eastern Michigan University, Ypsilanti (K.M.C., J.E.C.); and Departments of Biostatistics (B.N.S.), Health Behavior and Health Education (K.R.), and Epidemiology (L.D.L., L.B.M.), University of Michigan School of Public Health, Ann Arbor
| | - Brisa N Sánchez
- From the Department of Neurology, Stroke Program, University of Michigan, Ann Arbor (D.L.B., E.S., J.M., L.E.S., L.D.L., L.B.M.); Program of Health Education, School of Health Promotion and Human Performance, Eastern Michigan University, Ypsilanti (K.M.C., J.E.C.); and Departments of Biostatistics (B.N.S.), Health Behavior and Health Education (K.R.), and Epidemiology (L.D.L., L.B.M.), University of Michigan School of Public Health, Ann Arbor
| | - Kenneth Resnicow
- From the Department of Neurology, Stroke Program, University of Michigan, Ann Arbor (D.L.B., E.S., J.M., L.E.S., L.D.L., L.B.M.); Program of Health Education, School of Health Promotion and Human Performance, Eastern Michigan University, Ypsilanti (K.M.C., J.E.C.); and Departments of Biostatistics (B.N.S.), Health Behavior and Health Education (K.R.), and Epidemiology (L.D.L., L.B.M.), University of Michigan School of Public Health, Ann Arbor
| | - Joan E Cowdery
- From the Department of Neurology, Stroke Program, University of Michigan, Ann Arbor (D.L.B., E.S., J.M., L.E.S., L.D.L., L.B.M.); Program of Health Education, School of Health Promotion and Human Performance, Eastern Michigan University, Ypsilanti (K.M.C., J.E.C.); and Departments of Biostatistics (B.N.S.), Health Behavior and Health Education (K.R.), and Epidemiology (L.D.L., L.B.M.), University of Michigan School of Public Health, Ann Arbor
| | - Emma Sais
- From the Department of Neurology, Stroke Program, University of Michigan, Ann Arbor (D.L.B., E.S., J.M., L.E.S., L.D.L., L.B.M.); Program of Health Education, School of Health Promotion and Human Performance, Eastern Michigan University, Ypsilanti (K.M.C., J.E.C.); and Departments of Biostatistics (B.N.S.), Health Behavior and Health Education (K.R.), and Epidemiology (L.D.L., L.B.M.), University of Michigan School of Public Health, Ann Arbor
| | - Jillian Murphy
- From the Department of Neurology, Stroke Program, University of Michigan, Ann Arbor (D.L.B., E.S., J.M., L.E.S., L.D.L., L.B.M.); Program of Health Education, School of Health Promotion and Human Performance, Eastern Michigan University, Ypsilanti (K.M.C., J.E.C.); and Departments of Biostatistics (B.N.S.), Health Behavior and Health Education (K.R.), and Epidemiology (L.D.L., L.B.M.), University of Michigan School of Public Health, Ann Arbor
| | - Lesli E Skolarus
- From the Department of Neurology, Stroke Program, University of Michigan, Ann Arbor (D.L.B., E.S., J.M., L.E.S., L.D.L., L.B.M.); Program of Health Education, School of Health Promotion and Human Performance, Eastern Michigan University, Ypsilanti (K.M.C., J.E.C.); and Departments of Biostatistics (B.N.S.), Health Behavior and Health Education (K.R.), and Epidemiology (L.D.L., L.B.M.), University of Michigan School of Public Health, Ann Arbor
| | - Lynda D Lisabeth
- From the Department of Neurology, Stroke Program, University of Michigan, Ann Arbor (D.L.B., E.S., J.M., L.E.S., L.D.L., L.B.M.); Program of Health Education, School of Health Promotion and Human Performance, Eastern Michigan University, Ypsilanti (K.M.C., J.E.C.); and Departments of Biostatistics (B.N.S.), Health Behavior and Health Education (K.R.), and Epidemiology (L.D.L., L.B.M.), University of Michigan School of Public Health, Ann Arbor
| | - Lewis B Morgenstern
- From the Department of Neurology, Stroke Program, University of Michigan, Ann Arbor (D.L.B., E.S., J.M., L.E.S., L.D.L., L.B.M.); Program of Health Education, School of Health Promotion and Human Performance, Eastern Michigan University, Ypsilanti (K.M.C., J.E.C.); and Departments of Biostatistics (B.N.S.), Health Behavior and Health Education (K.R.), and Epidemiology (L.D.L., L.B.M.), University of Michigan School of Public Health, Ann Arbor
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Moreira MT, Oskrochi R, Foxcroft DR. Personalised normative feedback for preventing alcohol misuse in university students: Solomon three-group randomised controlled trial. PLoS One 2012; 7:e44120. [PMID: 22984466 PMCID: PMC3440433 DOI: 10.1371/journal.pone.0044120] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2012] [Accepted: 07/30/2012] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Young people tend to over-estimate peer group drinking levels. Personalised normative feedback (PNF) aims to correct this misperception by providing information about personal drinking levels and patterns compared with norms in similar aged peer groups. PNF is intended to raise motivation for behaviour change and has been highlighted for alcohol misuse prevention by the British Government Behavioural Insight Team. The objective of the trial was to assess the effectiveness of PNF with college students for the prevention of alcohol misuse. METHODOLOGY Solomon three-group randomised controlled trial. 1751 students, from 22 British Universities, allocated to a PNF group, a normal control group, or a delayed measurement control group to allow assessment of any measurement effects. PNF was provided by email. Participants completed online questionnaires at baseline, 6- and 12-months (only 12-months for the delayed measurement controls). Drinking behaviour measures were (i) alcohol disorders; (ii) frequency; (iii) typical quantity, (iv) weekly consumption; (v) alcohol-related problems; (vi) perceived drinking norms; and (vii) positive alcohol expectancies. Analyses focused on high-risk drinkers, as well as all students, because of research evidence for the prevention paradox in student drinkers. PRINCIPAL FINDINGS Follow-up rates were low, with only 50% and 40% responding at 6- and 12-months, respectively, though comparable to similar European studies. We found no evidence for any systematic attrition bias. Overall, statistical analyses with the high risk sub-sample, and for all students, showed no significant effects of the intervention, at either time-point, in a completed case analysis and a multiple imputation analysis. CONCLUSIONS We found no evidence for the effectiveness of PNF for the prevention of alcohol misuse and alcohol-related problems in a UK student population. REGISTRATION Controlled-Trials.com ISRCTN30784467.
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Affiliation(s)
- Maria T. Moreira
- Instituto Superior de Saúde do Alto Ave, Póvoa de Lanhoso, Braga, Portugal
| | - Reza Oskrochi
- Medical Statistics Programme, Oxford Brookes University, Oxford, Oxfordshire, United Kingdom
| | - David R. Foxcroft
- Department of Psychology, Social Work and Public Health, Oxford Brookes University, Oxford, Oxfordshire, United Kingdom
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Hebert JR, Hurley TG, Peterson KE, Resnicow K, Thompson FE, Yaroch AL, Ehlers M, Midthune D, Williams GC, Greene GW, Nebeling L. Social desirability trait influences on self-reported dietary measures among diverse participants in a multicenter multiple risk factor trial. J Nutr 2008; 138:226S-234S. [PMID: 18156429 DOI: 10.1093/jn/138.1.226s] [Citation(s) in RCA: 135] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Data collected at 4 Behavioral Change Consortium sites were used to assess social desirability bias in self-reports derived from a dietary fat screener (PFat), a dietary fruit and vegetable screener (FVS), and a 1-item question on fruit and vegetable intake. Comparisons were made with mean intakes derived from up to 3 24-h recall interviews at baseline and follow-up (at 12 mo in 3 sites, 6 mo in the fourth). A social-desirability-related underestimate in fat intake on the PFat relative to the 24HR (percentage energy as fat) was evident in women [baseline b = -0.56 (P = 0.005); follow-up b = -0.62 (P < 0.001)]. There was an overestimate in FVS-derived fruit and vegetable consumption (servings/week) in men enrolled in any intervention at follow-up (b = 0.39, P = 0.05) vs. baseline (b = 0.04, P = 0.75). The 1-item fruit and vegetable question was associated with an overestimate at baseline in men according to SD score (b = 0.14, P = 0.02), especially men with less than college education (b = 0.23, P = 0.01). Women with less than college education expressed a similar bias at follow-up (b = 0.13, P = 0.02). Differences in the magnitude of bias according to gender, type of instrument used, and randomization condition are comparable to what has been seen for other instruments and have important implications for both measuring change in studies of diet and health outcomes and for developing methods to control for such biases.
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Affiliation(s)
- James R Hebert
- South Carolina Statewide Cancer Prevention and Control Program, Department of Epidemiology and Biostatistics, Arnold School of Public Health University of South Carolina, Columbia, SC 29208, USA.
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