The Cardiometabolic Risk Profile of Underreporters of Energy Intake Differs from That of Adequate Reporters among Children at Risk of Obesity
Misreporting of energy intake (EI) in nutritional epidemiology is a concern because of information bias, and tends to occur differentially in obese compared with nonobese subjects. We examined characteristics of misreporters within a cohort of children with a parental history of obesity and the bias...
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Published in | The Journal of nutrition Vol. 149; no. 1; pp. 123 - 130 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Elsevier Inc
01.01.2019
Oxford University Press American Institute of Nutrition |
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Online Access | Get full text |
ISSN | 0022-3166 1541-6100 1541-6100 |
DOI | 10.1093/jn/nxy209 |
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Abstract | Misreporting of energy intake (EI) in nutritional epidemiology is a concern because of information bias, and tends to occur differentially in obese compared with nonobese subjects.
We examined characteristics of misreporters within a cohort of children with a parental history of obesity and the bias introduced by underreporting.
The QUebec Adipose and Lifestyle InvesTigation in Youth (QUALITY) cohort included 630 Caucasian children aged 8–10 y at recruitment with ≥1 obese parent [body mass index (BMI; in kg/m2) >30 or waist circumference >102 cm (men), >88 cm (women)] and free of diabetes or severe illness. Children on antihypertensive medications or following a restricted diet were excluded. Child and parent characteristics were measured directly or by questionnaire. Three 24-h dietary recalls were administered by phone by a dietitian. Goldberg's cutoff method identified underreporters (URs). Logistic regression identified correlates of URs. We compared coefficients from linear regressions of BMI after 2 y on total EI at baseline 1) in all participants; 2) in adequate reporters (ARs) (excluding URs); 3) in all participants statistically adjusted for underreporting; 4) excluding URs using individual physical activity level (PAL)-specific cutoffs; and 5) in all participants statistically adjusted for underreporting using PAL-specific cutoffs.
We identified 175 URs based on a calculated cutoff of 1.11. URs were older, had a higher BMI z score, and had poorer cardiometabolic health indicators. Parents of URs had a lower family income and higher BMI. Child BMI z score (OR: 3.07; 95% CI: 2.38, 3.97) and age (OR: 1.46/y; 95% CI: 1.14, 1.87/y) were the strongest correlates of underreporting. The association between BMI and total EI was null in all participants but became significantly positive after excluding URs (ß = 0.62/1000 kcal; 95% CI: 0.33, 0.92/1000 kcal) and after adjustment for URs (ß = 0.85/1000 kcal; 95% CI: 0.55, 1.06/1000 kcal).
URs in 8- to 10-y-old children differed from ARs. Underreporting biases measurement of nutritional exposures and the assessment of exposure-outcome relations. Identifying URs and using an appropriate correction method is essential. |
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AbstractList | Misreporting of energy intake (EI) in nutritional epidemiology is a concern because of information bias, and tends to occur differentially in obese compared with nonobese subjects.BackgroundMisreporting of energy intake (EI) in nutritional epidemiology is a concern because of information bias, and tends to occur differentially in obese compared with nonobese subjects.We examined characteristics of misreporters within a cohort of children with a parental history of obesity and the bias introduced by underreporting.ObjectiveWe examined characteristics of misreporters within a cohort of children with a parental history of obesity and the bias introduced by underreporting.The QUebec Adipose and Lifestyle InvesTigation in Youth (QUALITY) cohort included 630 Caucasian children aged 8-10 y at recruitment with ≥1 obese parent [body mass index (BMI; in kg/m2) >30 or waist circumference >102 cm (men), >88 cm (women)] and free of diabetes or severe illness. Children on antihypertensive medications or following a restricted diet were excluded. Child and parent characteristics were measured directly or by questionnaire. Three 24-h dietary recalls were administered by phone by a dietitian. Goldberg's cutoff method identified underreporters (URs). Logistic regression identified correlates of URs. We compared coefficients from linear regressions of BMI after 2 y on total EI at baseline 1) in all participants; 2) in adequate reporters (ARs) (excluding URs); 3) in all participants statistically adjusted for underreporting; 4) excluding URs using individual physical activity level (PAL)-specific cutoffs; and 5) in all participants statistically adjusted for underreporting using PAL-specific cutoffs.MethodsThe QUebec Adipose and Lifestyle InvesTigation in Youth (QUALITY) cohort included 630 Caucasian children aged 8-10 y at recruitment with ≥1 obese parent [body mass index (BMI; in kg/m2) >30 or waist circumference >102 cm (men), >88 cm (women)] and free of diabetes or severe illness. Children on antihypertensive medications or following a restricted diet were excluded. Child and parent characteristics were measured directly or by questionnaire. Three 24-h dietary recalls were administered by phone by a dietitian. Goldberg's cutoff method identified underreporters (URs). Logistic regression identified correlates of URs. We compared coefficients from linear regressions of BMI after 2 y on total EI at baseline 1) in all participants; 2) in adequate reporters (ARs) (excluding URs); 3) in all participants statistically adjusted for underreporting; 4) excluding URs using individual physical activity level (PAL)-specific cutoffs; and 5) in all participants statistically adjusted for underreporting using PAL-specific cutoffs.We identified 175 URs based on a calculated cutoff of 1.11. URs were older, had a higher BMI z score, and had poorer cardiometabolic health indicators. Parents of URs had a lower family income and higher BMI. Child BMI z score (OR: 3.07; 95% CI: 2.38, 3.97) and age (OR: 1.46/y; 95% CI: 1.14, 1.87/y) were the strongest correlates of underreporting. The association between BMI and total EI was null in all participants but became significantly positive after excluding URs (ß = 0.62/1000 kcal; 95% CI: 0.33, 0.92/1000 kcal) and after adjustment for URs (ß = 0.85/1000 kcal; 95% CI: 0.55, 1.06/1000 kcal).ResultsWe identified 175 URs based on a calculated cutoff of 1.11. URs were older, had a higher BMI z score, and had poorer cardiometabolic health indicators. Parents of URs had a lower family income and higher BMI. Child BMI z score (OR: 3.07; 95% CI: 2.38, 3.97) and age (OR: 1.46/y; 95% CI: 1.14, 1.87/y) were the strongest correlates of underreporting. The association between BMI and total EI was null in all participants but became significantly positive after excluding URs (ß = 0.62/1000 kcal; 95% CI: 0.33, 0.92/1000 kcal) and after adjustment for URs (ß = 0.85/1000 kcal; 95% CI: 0.55, 1.06/1000 kcal).URs in 8- to 10-y-old children differed from ARs. Underreporting biases measurement of nutritional exposures and the assessment of exposure-outcome relations. Identifying URs and using an appropriate correction method is essential.ConclusionsURs in 8- to 10-y-old children differed from ARs. Underreporting biases measurement of nutritional exposures and the assessment of exposure-outcome relations. Identifying URs and using an appropriate correction method is essential. Misreporting of energy intake (EI) in nutritional epidemiology is a concern because of information bias, and tends to occur differentially in obese compared with nonobese subjects. We examined characteristics of misreporters within a cohort of children with a parental history of obesity and the bias introduced by underreporting. The QUebec Adipose and Lifestyle InvesTigation in Youth (QUALITY) cohort included 630 Caucasian children aged 8-10 y at recruitment with ≥1 obese parent [body mass index (BMI; in kg/m2) >30 or waist circumference >102 cm (men), >88 cm (women)] and free of diabetes or severe illness. Children on antihypertensive medications or following a restricted diet were excluded. Child and parent characteristics were measured directly or by questionnaire. Three 24-h dietary recalls were administered by phone by a dietitian. Goldberg's cutoff method identified underreporters (URs). Logistic regression identified correlates of URs. We compared coefficients from linear regressions of BMI after 2 y on total EI at baseline 1) in all participants; 2) in adequate reporters (ARs) (excluding URs); 3) in all participants statistically adjusted for underreporting; 4) excluding URs using individual physical activity level (PAL)-specific cutoffs; and 5) in all participants statistically adjusted for underreporting using PAL-specific cutoffs. We identified 175 URs based on a calculated cutoff of 1.11. URs were older, had a higher BMI z score, and had poorer cardiometabolic health indicators. Parents of URs had a lower family income and higher BMI. Child BMI z score (OR: 3.07; 95% CI: 2.38, 3.97) and age (OR: 1.46/y; 95% CI: 1.14, 1.87/y) were the strongest correlates of underreporting. The association between BMI and total EI was null in all participants but became significantly positive after excluding URs (ß = 0.62/1000 kcal; 95% CI: 0.33, 0.92/1000 kcal) and after adjustment for URs (ß = 0.85/1000 kcal; 95% CI: 0.55, 1.06/1000 kcal). URs in 8- to 10-y-old children differed from ARs. Underreporting biases measurement of nutritional exposures and the assessment of exposure-outcome relations. Identifying URs and using an appropriate correction method is essential. Misreporting of energy intake (EI) in nutritional epidemiology is a concern because of information bias, and tends to occur differentially in obese compared with nonobese subjects. We examined characteristics of misreporters within a cohort of children with a parental history of obesity and the bias introduced by underreporting. The QUebec Adipose and Lifestyle InvesTigation in Youth (QUALITY) cohort included 630 Caucasian children aged 8–10 y at recruitment with ≥1 obese parent [body mass index (BMI; in kg/m²) >30 or waist circumference >102 cm (men), >88 cm (women)] and free of diabetes or severe illness. Children on antihypertensive medications or following a restricted diet were excluded. Child and parent characteristics were measured directly or by questionnaire. Three 24-h dietary recalls were administered by phone by a dietitian. Goldberg's cutoff method identified underreporters (URs). Logistic regression identified correlates of URs. We compared coefficients from linear regressions of BMI after 2 y on total EI at baseline 1) in all participants; 2) in adequate reporters (ARs) (excluding URs); 3) in all participants statistically adjusted for underreporting; 4) excluding URs using individual physical activity level (PAL)-specific cutoffs; and 5) in all participants statistically adjusted for underreporting using PAL-specific cutoffs. We identified 175 URs based on a calculated cutoff of 1.11. URs were older, had a higher BMI z score, and had poorer cardiometabolic health indicators. Parents of URs had a lower family income and higher BMI. Child BMI z score (OR: 3.07; 95% CI: 2.38, 3.97) and age (OR: 1.46/y; 95% CI: 1.14, 1.87/y) were the strongest correlates of underreporting. The association between BMI and total EI was null in all participants but became significantly positive after excluding URs (ß = 0.62/1000 kcal; 95% CI: 0.33, 0.92/1000 kcal) and after adjustment for URs (ß = 0.85/1000 kcal; 95% CI: 0.55, 1.06/1000 kcal). URs in 8- to 10-y-old children differed from ARs. Underreporting biases measurement of nutritional exposures and the assessment of exposure-outcome relations. Identifying URs and using an appropriate correction method is essential. ABSTRACT Background Misreporting of energy intake (EI) in nutritional epidemiology is a concern because of information bias, and tends to occur differentially in obese compared with nonobese subjects. Objective We examined characteristics of misreporters within a cohort of children with a parental history of obesity and the bias introduced by underreporting. Methods The QUebec Adipose and Lifestyle InvesTigation in Youth (QUALITY) cohort included 630 Caucasian children aged 8–10 y at recruitment with ≥1 obese parent [body mass index (BMI; in kg/m2) >30 or waist circumference >102 cm (men), >88 cm (women)] and free of diabetes or severe illness. Children on antihypertensive medications or following a restricted diet were excluded. Child and parent characteristics were measured directly or by questionnaire. Three 24-h dietary recalls were administered by phone by a dietitian. Goldberg's cutoff method identified underreporters (URs). Logistic regression identified correlates of URs. We compared coefficients from linear regressions of BMI after 2 y on total EI at baseline 1) in all participants; 2) in adequate reporters (ARs) (excluding URs); 3) in all participants statistically adjusted for underreporting; 4) excluding URs using individual physical activity level (PAL)-specific cutoffs; and 5) in all participants statistically adjusted for underreporting using PAL-specific cutoffs. Results We identified 175 URs based on a calculated cutoff of 1.11. URs were older, had a higher BMI z score, and had poorer cardiometabolic health indicators. Parents of URs had a lower family income and higher BMI. Child BMI z score (OR: 3.07; 95% CI: 2.38, 3.97) and age (OR: 1.46/y; 95% CI: 1.14, 1.87/y) were the strongest correlates of underreporting. The association between BMI and total EI was null in all participants but became significantly positive after excluding URs (ß = 0.62/1000 kcal; 95% CI: 0.33, 0.92/1000 kcal) and after adjustment for URs (ß = 0.85/1000 kcal; 95% CI: 0.55, 1.06/1000 kcal). Conclusions URs in 8- to 10-y-old children differed from ARs. Underreporting biases measurement of nutritional exposures and the assessment of exposure-outcome relations. Identifying URs and using an appropriate correction method is essential. Background Misreporting of energy intake (EI) in nutritional epidemiology is a concern because of information bias, and tends to occur differentially in obese compared with nonobese subjects. Objective We examined characteristics of misreporters within a cohort of children with a parental history of obesity and the bias introduced by underreporting. Methods The QUebec Adipose and Lifestyle InvesTigation in Youth (QUALITY) cohort included 630 Caucasian children aged 8–10 y at recruitment with ≥1 obese parent [body mass index (BMI; in kg/m2) >30 or waist circumference >102 cm (men), >88 cm (women)] and free of diabetes or severe illness. Children on antihypertensive medications or following a restricted diet were excluded. Child and parent characteristics were measured directly or by questionnaire. Three 24-h dietary recalls were administered by phone by a dietitian. Goldberg's cutoff method identified underreporters (URs). Logistic regression identified correlates of URs. We compared coefficients from linear regressions of BMI after 2 y on total EI at baseline 1) in all participants; 2) in adequate reporters (ARs) (excluding URs); 3) in all participants statistically adjusted for underreporting; 4) excluding URs using individual physical activity level (PAL)-specific cutoffs; and 5) in all participants statistically adjusted for underreporting using PAL-specific cutoffs. Results We identified 175 URs based on a calculated cutoff of 1.11. URs were older, had a higher BMI z score, and had poorer cardiometabolic health indicators. Parents of URs had a lower family income and higher BMI. Child BMI z score (OR: 3.07; 95% CI: 2.38, 3.97) and age (OR: 1.46/y; 95% CI: 1.14, 1.87/y) were the strongest correlates of underreporting. The association between BMI and total EI was null in all participants but became significantly positive after excluding URs (ß = 0.62/1000 kcal; 95% CI: 0.33, 0.92/1000 kcal) and after adjustment for URs (ß = 0.85/1000 kcal; 95% CI: 0.55, 1.06/1000 kcal). Conclusions URs in 8- to 10-y-old children differed from ARs. Underreporting biases measurement of nutritional exposures and the assessment of exposure-outcome relations. Identifying URs and using an appropriate correction method is essential. |
Author | Suissa, Karine Benedetti, Andrea Paradis, Gilles Henderson, Mélanie Gray-Donald, Katherine |
AuthorAffiliation | 3 Respiratory Epidemiology and Clinical Research Unit, McGill University Health Centre, Montreal, Quebec, Canada 1 Epidemiology, Biostatistics, and Occupational Health McGill University, Montreal, Quebec, Canada 6 School of Dietetics and Human Nutrition, McGill University, Montreal, Quebec, Canada (retired) 4 Research Center of Centre Hospitalier Universitaire Sainte-Justine, Montreal, Quebec, Canada 5 Department of Pediatrics, Faculty of Medicine, Université de Montréal, Montreal, Quebec, Canada 2 Medicine, McGill University, Montreal, Quebec, Canada |
AuthorAffiliation_xml | – name: 4 Research Center of Centre Hospitalier Universitaire Sainte-Justine, Montreal, Quebec, Canada – name: 1 Epidemiology, Biostatistics, and Occupational Health McGill University, Montreal, Quebec, Canada – name: 6 School of Dietetics and Human Nutrition, McGill University, Montreal, Quebec, Canada (retired) – name: 2 Medicine, McGill University, Montreal, Quebec, Canada – name: 5 Department of Pediatrics, Faculty of Medicine, Université de Montréal, Montreal, Quebec, Canada – name: 3 Respiratory Epidemiology and Clinical Research Unit, McGill University Health Centre, Montreal, Quebec, Canada |
Author_xml | – sequence: 1 givenname: Karine surname: Suissa fullname: Suissa, Karine organization: Epidemiology, Biostatistics, and Occupational Health McGill University, Montreal, Quebec, Canada – sequence: 2 givenname: Andrea surname: Benedetti fullname: Benedetti, Andrea organization: Epidemiology, Biostatistics, and Occupational Health McGill University, Montreal, Quebec, Canada – sequence: 3 givenname: Mélanie orcidid: 0000-0002-0102-2389 surname: Henderson fullname: Henderson, Mélanie organization: Research Center of Centre Hospitalier Universitaire Sainte-Justine, Montreal, Quebec, Canada – sequence: 4 givenname: Katherine surname: Gray-Donald fullname: Gray-Donald, Katherine organization: School of Dietetics and Human Nutrition, McGill University, Montreal, Quebec, Canada (retired) – sequence: 5 givenname: Gilles surname: Paradis fullname: Paradis, Gilles email: chair.epid@mcgill.ca organization: Epidemiology, Biostatistics, and Occupational Health McGill University, Montreal, Quebec, Canada |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30602028$$D View this record in MEDLINE/PubMed |
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CitedBy_id | crossref_primary_10_1016_j_appet_2020_104696 crossref_primary_10_1016_j_ebiom_2020_102932 crossref_primary_10_1093_jn_nxaa389 crossref_primary_10_1038_s41366_021_00958_4 |
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Keywords | energy intake glycemic index cardiometabolic risk adiposity QUALITY EI body mass index BMR misreporting glycemic load EI:BMR 24-h recall AR children underreporting PAL UR |
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Snippet | Misreporting of energy intake (EI) in nutritional epidemiology is a concern because of information bias, and tends to occur differentially in obese compared... ABSTRACT Background Misreporting of energy intake (EI) in nutritional epidemiology is a concern because of information bias, and tends to occur differentially... Background Misreporting of energy intake (EI) in nutritional epidemiology is a concern because of information bias, and tends to occur differentially in obese... |
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SubjectTerms | 24-h recall adiposity Antihypertensives Bias Body mass index Body size cardiometabolic risk Cardiovascular Diseases - etiology Child Children Children & youth children at risk Cohort Studies diabetes Diabetes mellitus Diet diet recall Diet Records Dietary restrictions dietitians disease severity Energy Intake Epidemiology Female glycemic index glycemic load Health risks household income Humans lifestyle Male men misreporting Nutrient deficiency Nutrition Obesity Original Parents Pediatric Obesity Physical activity Quebec questionnaires regression analysis Risk assessment Risk Factors risk profile Surveys and Questionnaires underreporting waist circumference Whites women youth |
Title | The Cardiometabolic Risk Profile of Underreporters of Energy Intake Differs from That of Adequate Reporters among Children at Risk of Obesity |
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