Development and testing of a quantitative food frequency questionnaire for use in Gujarat, India

Hébert, James R.; Gupta, Prakash C.; Bhonsle, R. B.; Sinor, Pesi N; Mehta, Hemali; Mehta, Fali S.

doi:10.1017/s1368980099000051

Cited by 45 publications

(53 citation statements)

References 27 publications

(45 reference statements)

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“…Despite a uniform lack of seasonal or day-of-the-week effects, there were large regional differences in the diets, as noted previously (Hebert et al, 1999b). In general, Gujaratis consumed a diet much more similar to that consumed in the West, in terms of its fat content.…”

Section: Variability In Dietary Intake In Rural Indiamentioning

confidence: 62%

“…Recipe information and data on food portion sizes were collected using methods described earlier (Hebert et al, 1998a(Hebert et al, , 1999b. Computation of nutrient scores was carried out using methods developed speci®cally for these populations, also described in earlier publications (Hebert et al, 1998a(Hebert et al, , 1999b.…”

Section: Field Methodsmentioning

confidence: 99%

“…Computation of nutrient scores was carried out using methods developed speci®cally for these populations, also described in earlier publications (Hebert et al, 1998a(Hebert et al, , 1999b.…”

Section: Field Methodsmentioning

confidence: 99%

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Sources of variability in dietary intake in two distinct regions of rural India: implications for nutrition study design and interpretation

et al. 2000

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Objective: Limited inter-person variability in nutrient intake hampers epidemiologic studies of diet ± disease relationships. Despite conjecture about non-traditional study bases providing large inter-person differences, virtually nothing is known about variations in nutrient intake outside of Europe and North America. The current study was conducted in India to determine sources of variability in the intakes of nutrients thought to be of public health importance. Design: Adult subjects in Gujarat (North India; n 60) and in Kerala (South India, n 60) were administered 24 h diet recall interviews six and eight times, respectively, over a 1 y period. To assess subject (inter-person) and residual (intra-person) contributions to variance, regression models were ®t to the data. From this, the variance ratio (VR, total within or intra-person: total between or inter-person) was computed. Setting: Rural communities in North and South India. Results: In both regions, inter-person variability was larger than that observed in the West. This was most pronounced in Gujarat, for which the VR was`1.0 for seven of the 12 energy-adjusted nutrient intakes in both men and women. In analyses of the combined data, region accounted for b 20% of variance for fat, iron, copper, zinc, b-carotene and ribo¯avin in both men and women. With the region term removed from this model, virtually all of the variability ascribed to region contributed to inter-person variability. Conclusions:The relatively large inter-person variability observed here could contribute to improved`resolution' of diet ± outcome relationships in epidemiologic studies. While this applies to data from each region, it was especially evident in analyses of the combined data.

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Section: Variability In Dietary Intake In Rural Indiamentioning

confidence: 62%

Section: Field Methodsmentioning

confidence: 99%

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Sources of variability in dietary intake in two distinct regions of rural India: implications for nutrition study design and interpretation

et al. 2000

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“…Linear regression was also used to assess the agreement between the intakes derived from FFQ1 and the average of those obtained from the 3 d of 24HR (33,34) .…”

Section: Discussionmentioning

confidence: 99%

Validation of a self-administered FFQ in adults in Argentina, Chile and Uruguay

Elorriaga

Irazola²,

Defagó³

et al. 2014

Public Health Nutr.

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Objective: To assess the reproducibility and validity among adults in the Southern Cone of Latin America (Argentina, Chile and Uruguay) of a self-administered FFQ to be used in the CESCAS I Study, an ongoing observational prospective cohort study to detect and follow up CVD and their risk factors, as well as in other epidemiological studies. Design: Relative validity of the FFQ was evaluated by comparing nutrient and selected food group intakes with those from three 24 h recalls (24HR) administered over 6 months. The FFQ was administered at baseline (FFQ1) and again after 3 months (FFQ2). Setting: Primary-care centres in Argentina, Chile and Uruguay. Subjects: Adults (n 147) aged 21-74 years. Results: Reproducibility (FFQ1 v. FFQ2): the intra-class correlation coefficients for nutrients ranged from 0?52 (potassium) to 0?74 (fat). Validity (FFQ1 v. the average of three 24HR): the Pearson correlations for energy-adjusted nutrients ranged from 0?39 (thiamin and cholesterol) to 0?59 (carbohydrate). Joint classification: overall, 66 % of participants in the lowest 24HR quintile were in the lowest one or two FFQ1 quintiles, and 62 % of those in the highest 24HR quintile were in the highest one or two FFQ1 quintiles. On average, only 4 % were misclassified into extreme quintiles. Conclusions: The FFQ version for the Southern Cone seems to present moderate to acceptable relative validity and reliability for its use in the CESCAS I Study to measure dietary exposure.Keywords FFQ Validity Reproducibility Southern Cone of Latin America CVD are increasing throughout the world and cause 16?7 million deaths each year, 80 % of which occur in lowand middle-income countries. Most cardiovascular risk in the Southern Cone of Latin America (Argentina, Chile and Uruguay) could be explained by tobacco use, abnormal lipids, abdominal obesity and high blood pressure, as shown in the INTERHEART Latin American study that included 3125 cases and controls from different Latin American countries (1) . In Argentina, recent estimates have shown that there were more than 600 000 disabilityadjusted life years and almost 400 000 years of potential life lost due to CHD and stroke in 2005. Modifiable risk factors explained 75?0 % of fatal and non-fatal acute CHD and stroke events, 75?5 % of costs for acute events and 70?7 % of disability-adjusted life years lost (2) .Nutritional exposures are considered risk factors for CVD as well as other non-communicable and infectious diseases (3,4) . FFQ are often used in epidemiological studies to investigate the relationship between diet and disease because they are easy to administer, less expensive than other methods and can, at least theoretically, assess dietary intake over an extended period of time (5) . Usually FFQ are not considered an appropriate method of estimating actual nutrient intakes of individuals, but they can be used to rank people according to their intake. This information is useful to categorize nutritional exposures for epidemiological studies (6) .FFQ may be administered by tr...

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“…Using this methodology in the context of 24HR is important per se (because it is a practicable assessment method in clinical research). It also has added relevance because the 24HR is often the referent method in validation studies of structured questionnaires including the FFQ [37][38][39], and it is reasonable to consider GI or GL as a parameter for which to test in validation.…”

Section: Discussionmentioning

confidence: 99%

Methodology for adding glycemic index and glycemic load values to 24-hour dietary recall database

Olendzki

Culver³

et al. 2006

Nutrition

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Objectives-We describe a method of adding the glycemic index (GI) and glycemic load (GL) values to the nutrient database of the 24-hour dietary recall interview (24HR), a widely used dietary assessment. We also calculated daily GI and GL values from the 24HR.Methods-Subjects were 641 healthy adults from central Massachusetts who completed 9067 24HRs. The 24HR-derived food data were matched to the International Table of Glycemic Index and Glycemic Load Values. The GI values for specific foods not in the table were estimated against similar foods according to physical and chemical factors that determine GI. Mixed foods were disaggregated into individual ingredients.Results-Of 1261 carbohydrate-containing foods in the database, GI values of 602 foods were obtained from a direct match (47.7%), accounting for 22.36% of dietary carbohydrate. GI values from 656 foods (52.1%) were estimated, contributing to 77.64% of dietary carbohydrate. The GI values from three unknown foods (0.2%) could not be assigned. The average daily GI was 84 (SD 5.1, white bread as referent) and the average GL was 196 (SD 63).Conclusion-Using this methodology for adding GI and GL values to nutrient databases, it is possible to assess associations between GI and/or GL and body weight and chronic disease outcomes (diabetes, cancer, heart disease). This method can be used in clinical and survey research settings where 24HRs are a practical means for assessing diet. The implications for using this methodology compel a broader evaluation of diet with disease outcomes.

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Development and testing of a quantitative food frequency questionnaire for use in Gujarat, India

Cited by 45 publications

References 27 publications

Sources of variability in dietary intake in two distinct regions of rural India: implications for nutrition study design and interpretation

Sources of variability in dietary intake in two distinct regions of rural India: implications for nutrition study design and interpretation

Validation of a self-administered FFQ in adults in Argentina, Chile and Uruguay

Methodology for adding glycemic index and glycemic load values to 24-hour dietary recall database

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