Leveraging questionnaire-based physical activity levels (PAL) to identify energy intake misreporting in the Goldberg method: A doubly-labeled water validation study Article Swipe
Heather K. Neilson
,
Shervin Asgari
,
Karen Kopciuk
,
Janet A. Tooze
,
Farah Khandwala
,
Anita Koushik
,
Rémi Rabasa‐Lhoret
,
Ilona Csizmadi
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1101/2025.04.02.25325112
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1101/2025.04.02.25325112
BACKGROUND Dietary intake misreporting is widely acknowledged in nutritional epidemiology. The Goldberg method has been proposed as an option for identifying under-reporters of energy intake (EI) in large-scale epidemiologic studies. However, its implementation remains limited by challenges associated with estimating physical activity levels (PAL), a critical component. OBJECTIVE To quantify the accuracy of the Goldberg method to classify EI misreporting using Sedentary Time and Activity Reporting Questionnaire (STAR-Q)-derived PAL STAR-Q compared with doubly-labeled water (DLW)-derived total energy expenditure (TEE DLW ). DESIGN Between 2009 and 2011, 99 weight-stable men and women (mean [SD]: 48 [8] years) completed a two-week DLW protocol, the Canadian Diet History Questionnaire I, and the STAR-Q, a comprehensive past-month activity questionnaire. TEE DLW was the criterion measure of EI to determine the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy (proportion correctly classified as under-reporters or acceptable reporters) of Goldberg cut-points based on the PAL STAR-Q . A global PAL of 1.55 frequently used in the original Goldberg method was also studied. RESULTS The Goldberg method using PAL STAR-Q classified 58% of men and women as under-reporters, compared with 60% of men and 56% of women identified with TEE DLW . Among men, values for sensitivity, specificity, PPV, NPV and accuracy of the Goldberg method and PAL STAR-Q were estimated as: 88%, 87%, 91%, 81%, and 87%, respectively. Among women, these values were: 79%, 69%, 77%, 72%, and 75%, respectively. Substituting a PAL of 1.55 for the PAL STAR-Q reduced the proportion of men and women classified as under-reporters to 35% and 19%, respectively, lowered sensitivity to 54% and 33%, and increased specificity to 93% and 100%. CONCLUSIONS Population-specific validation sub-studies using the Goldberg method and questionnaire-derived PALs can be informative for understanding EI misreporting to ultimately improve estimates of diet-disease associations in large-scale epidemiologic studies lacking in objective EI measures.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2025.04.02.25325112
- https://www.medrxiv.org/content/medrxiv/early/2025/04/04/2025.04.02.25325112.full.pdf
- OA Status
- green
- References
- 58
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4409264703
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- OpenAlex ID
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https://openalex.org/W4409264703Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2025.04.02.25325112Digital Object Identifier
- Title
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Leveraging questionnaire-based physical activity levels (PAL) to identify energy intake misreporting in the Goldberg method: A doubly-labeled water validation studyWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-04-04Full publication date if available
- Authors
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Heather K. Neilson, Shervin Asgari, Karen Kopciuk, Janet A. Tooze, Farah Khandwala, Anita Koushik, Rémi Rabasa‐Lhoret, Ilona CsizmadiList of authors in order
- Landing page
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https://doi.org/10.1101/2025.04.02.25325112Publisher landing page
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https://www.medrxiv.org/content/medrxiv/early/2025/04/04/2025.04.02.25325112.full.pdfDirect link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://www.medrxiv.org/content/medrxiv/early/2025/04/04/2025.04.02.25325112.full.pdfDirect OA link when available
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Energy (signal processing), Physical activity, Computer science, Water intake, Psychology, Environmental science, Statistics, Mathematics, Water resource management, Physical medicine and rehabilitation, MedicineTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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58Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.men | 89, 181, 190, 252 |
| abstract_inverted_index.the | 51, 54, 102, 109, 119, 126, 152, 164, 211, 245, 249, 281 |
| abstract_inverted_index.was | 118, 168 |
| abstract_inverted_index.(EI) | 26 |
| abstract_inverted_index.(TEE | 79 |
| abstract_inverted_index.1.55 | 160, 243 |
| abstract_inverted_index.19%, | 261 |
| abstract_inverted_index.2009 | 84 |
| abstract_inverted_index.33%, | 268 |
| abstract_inverted_index.69%, | 233 |
| abstract_inverted_index.72%, | 235 |
| abstract_inverted_index.75%, | 237 |
| abstract_inverted_index.77%, | 234 |
| abstract_inverted_index.79%, | 232 |
| abstract_inverted_index.81%, | 223 |
| abstract_inverted_index.87%, | 221, 225 |
| abstract_inverted_index.88%, | 220 |
| abstract_inverted_index.91%, | 222 |
| abstract_inverted_index.Diet | 104 |
| abstract_inverted_index.PALs | 286 |
| abstract_inverted_index.PPV, | 206 |
| abstract_inverted_index.Time | 63 |
| abstract_inverted_index.also | 169 |
| abstract_inverted_index.been | 15 |
| abstract_inverted_index.men, | 201 |
| abstract_inverted_index.used | 162 |
| abstract_inverted_index.were | 217 |
| abstract_inverted_index.with | 39, 72, 187, 196 |
| abstract_inverted_index.(NPV) | 136 |
| abstract_inverted_index.(mean | 92 |
| abstract_inverted_index.100%. | 275 |
| abstract_inverted_index.2011, | 86 |
| abstract_inverted_index.Among | 200, 227 |
| abstract_inverted_index.[SD]: | 93 |
| abstract_inverted_index.based | 150 |
| abstract_inverted_index.these | 229 |
| abstract_inverted_index.total | 76 |
| abstract_inverted_index.using | 61, 175, 280 |
| abstract_inverted_index.value | 131, 135 |
| abstract_inverted_index.water | 74 |
| abstract_inverted_index.were: | 231 |
| abstract_inverted_index.women | 91, 183, 194, 254 |
| abstract_inverted_index.(PAL), | 44 |
| abstract_inverted_index.(PPV), | 132 |
| abstract_inverted_index.DESIGN | 82 |
| abstract_inverted_index.STAR-Q | 70, 154, 177, 216, 247 |
| abstract_inverted_index.energy | 24, 77 |
| abstract_inverted_index.global | 157 |
| abstract_inverted_index.intake | 3, 25 |
| abstract_inverted_index.levels | 43 |
| abstract_inverted_index.method | 13, 56, 167, 174, 213, 283 |
| abstract_inverted_index.option | 19 |
| abstract_inverted_index.values | 202, 230 |
| abstract_inverted_index.widely | 6 |
| abstract_inverted_index.women, | 228 |
| abstract_inverted_index.years) | 96 |
| abstract_inverted_index.Between | 83 |
| abstract_inverted_index.Dietary | 2 |
| abstract_inverted_index.History | 105 |
| abstract_inverted_index.RESULTS | 171 |
| abstract_inverted_index.STAR-Q, | 110 |
| abstract_inverted_index.improve | 296 |
| abstract_inverted_index.lacking | 305 |
| abstract_inverted_index.limited | 35 |
| abstract_inverted_index.lowered | 263 |
| abstract_inverted_index.measure | 121 |
| abstract_inverted_index.reduced | 248 |
| abstract_inverted_index.remains | 34 |
| abstract_inverted_index.studies | 304 |
| abstract_inverted_index.ABSTRACT | 0 |
| abstract_inverted_index.Activity | 65 |
| abstract_inverted_index.Canadian | 103 |
| abstract_inverted_index.Goldberg | 12, 55, 148, 166, 173, 212, 282 |
| abstract_inverted_index.However, | 31 |
| abstract_inverted_index.accuracy | 52, 138, 209 |
| abstract_inverted_index.activity | 42, 114 |
| abstract_inverted_index.classify | 58 |
| abstract_inverted_index.compared | 71, 186 |
| abstract_inverted_index.critical | 46 |
| abstract_inverted_index.negative | 133 |
| abstract_inverted_index.original | 165 |
| abstract_inverted_index.physical | 41 |
| abstract_inverted_index.positive | 129 |
| abstract_inverted_index.proposed | 16 |
| abstract_inverted_index.quantify | 50 |
| abstract_inverted_index.studied. | 170 |
| abstract_inverted_index.studies. | 30 |
| abstract_inverted_index.two-week | 99 |
| abstract_inverted_index.OBJECTIVE | 48 |
| abstract_inverted_index.Reporting | 66 |
| abstract_inverted_index.Sedentary | 62 |
| abstract_inverted_index.completed | 97 |
| abstract_inverted_index.correctly | 140 |
| abstract_inverted_index.criterion | 120 |
| abstract_inverted_index.determine | 125 |
| abstract_inverted_index.estimated | 218 |
| abstract_inverted_index.estimates | 297 |
| abstract_inverted_index.increased | 270 |
| abstract_inverted_index.measures. | 309 |
| abstract_inverted_index.objective | 307 |
| abstract_inverted_index.protocol, | 101 |
| abstract_inverted_index.BACKGROUND | 1 |
| abstract_inverted_index.acceptable | 145 |
| abstract_inverted_index.associated | 38 |
| abstract_inverted_index.challenges | 37 |
| abstract_inverted_index.classified | 141, 178, 255 |
| abstract_inverted_index.component. | 47 |
| abstract_inverted_index.cut-points | 149 |
| abstract_inverted_index.estimating | 40 |
| abstract_inverted_index.frequently | 161 |
| abstract_inverted_index.identified | 195 |
| abstract_inverted_index.past-month | 113 |
| abstract_inverted_index.predictive | 130, 134 |
| abstract_inverted_index.proportion | 250 |
| abstract_inverted_index.reporters) | 146 |
| abstract_inverted_index.ultimately | 295 |
| abstract_inverted_index.validation | 278 |
| abstract_inverted_index.(proportion | 139 |
| abstract_inverted_index.CONCLUSIONS | 276 |
| abstract_inverted_index.expenditure | 78 |
| abstract_inverted_index.identifying | 21 |
| abstract_inverted_index.informative | 289 |
| abstract_inverted_index.large-scale | 28, 302 |
| abstract_inverted_index.nutritional | 9 |
| abstract_inverted_index.sensitivity | 264 |
| abstract_inverted_index.specificity | 271 |
| abstract_inverted_index.sub-studies | 279 |
| abstract_inverted_index.Substituting | 239 |
| abstract_inverted_index.acknowledged | 7 |
| abstract_inverted_index.associations | 300 |
| abstract_inverted_index.diet-disease | 299 |
| abstract_inverted_index.misreporting | 4, 60, 293 |
| abstract_inverted_index.sensitivity, | 127, 204 |
| abstract_inverted_index.specificity, | 128, 205 |
| abstract_inverted_index.(DLW)-derived | 75 |
| abstract_inverted_index.Questionnaire | 67, 106 |
| abstract_inverted_index.comprehensive | 112 |
| abstract_inverted_index.epidemiologic | 29, 303 |
| abstract_inverted_index.epidemiology. | 10 |
| abstract_inverted_index.respectively, | 262 |
| abstract_inverted_index.respectively. | 226, 238 |
| abstract_inverted_index.understanding | 291 |
| abstract_inverted_index.weight-stable | 88 |
| abstract_inverted_index.doubly-labeled | 73 |
| abstract_inverted_index.implementation | 33 |
| abstract_inverted_index.questionnaire. | 115 |
| abstract_inverted_index.under-reporters | 22, 143, 257 |
| abstract_inverted_index.(STAR-Q)-derived | 68 |
| abstract_inverted_index.under-reporters, | 185 |
| abstract_inverted_index.Population-specific | 277 |
| abstract_inverted_index.questionnaire-derived | 285 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 8 |
| citation_normalized_percentile.value | 0.15092326 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |