J Nutr Health Aging
THE JOURNAL OF NUTRITION, HEALTH & AGING©
RELATIVE VALIDITY OF A DIET HISTORY QUESTIONNAIRE AGAINST A FOUR-DAY WEIGHED FOOD RECORD AMONG OLDER MEN IN AUSTRALIA: THE CONCORD HEALTH AND AGEING IN MEN PROJECT (CHAMP) R.V.R. WAERN1,2,3, R. CUMMING2,3, T. TRAVISON4, F. BLYTH1, V. NAGANATHAN1, M. ALLMAN-FARINELLI5, V. HIRANI1 1. Centre for Education and Research on Ageing, Concord Hospital, University of Sydney, NSW, Australia; 2. School of Public Health, University of Sydney, NSW, Australia; 3. ARC Centre of Excellence in Population Ageing Research, University of Sydney, Australia; 4. Institute for Ageing Research, Hebrew Senior Life, Harvard Medical School, Boston, MA, USA; 5. School of Molecular Bioscience, University of Sydney, NSW Australia. Corresponding author: Waern Rosilene, Centre for Education and Research on Ageing, Concord Hospital, University of Sydney, NSW, Australia, [email protected]
Abstract: Objectives: To evaluate the relative validity of the diet history questionnaire (DHQ) used in the Concord Health and Ageing in Men Project (CHAMP) against a four-day weighed food record (4dWFR) as the reference method. Design and measurements: Detailed DHQ followed by a 4dWFR were completed between July 2012 and October of 2013. Setting: Burwood, Canada Bay and Strathfield in Sydney, Australia. Participants: Fifty six community- dwelling men aged 75 years and over (mean=79 years). Results: DHQ estimates of intakes were generally higher than estimates from 4dWFR. Differences between the two methods were generally less than 20% with the exception of β-carotene (37%). Fixed and proportional biases were only present for retinol, β-carotene, magnesium, phosphorus and percentage of energy from protein; however, 95% limits of agreement were in some cases wide. Pearson correlation coefficient of log-transformed unadjusted values ranged from 0.15 (zinc) to 0.70 (alcohol), and from 0.06 (iron) to 0.63 (thiamin) after energy-adjustment. Spearman’s correlation coefficients ranged from 0.16 (zinc) to 0.80 (alcohol) before energy adjustment, and from 0.15(zinc) to 0.81(alcohol) after energy adjustment. Conclusion: Our findings suggest that the DHQ used in CHAMP to measure the nutritional intake of its participants is appropriate to this age group and provides reasonably similar results to the 4dWFR for the majority of nutrients analysed. Key words: Validity, weighed food record, diet history questionnaire, elderly men.
Introduction The population is ageing rapidly in Australia and in the rest of the world (1); however, there is very little known about the dietary habits of older people. Dietary habits are one of the important modifiable factors that can affect the maintenance of health in old age (2) and therefore diet should be a key component of epidemiological studies involving older people. Although a comprehensive understanding of older peoples’ dietary habits is essential, collection of dietary intake data from older subjects can be a challenging task, particularly when it involves reliance on short-term memory (3). It is important that data are obtained through appropriate methodology to avoid misleading conclusions and potentially ineffective interventions (4, 5). However, in reviewing the literature, only a small number of validation studies of dietary intake among people aged 70 years and over were identified (6-8), moreover some studies have investigated diet-disease relationships utilising methods that were not validated. Absolute validity of a dietary method cannot be measured because absolute intake is impossible to determine (9). Typically, the tested method is compared to a method that has a greater degree of validity, and relative validity is assessed. The weighed food record is a prospective method that does not rely on participants’ memory and is considered the “gold standard” for comparisons with less detailed and demanding methods. There are three main methods for dietary measurement Received August 18, 2014 Accepted for publication September 18, 2014
1
available to epidemiological research: Diet history questionnaire, food frequency questionnaire (FFQ) and 24-hour recall. All have advantages and disadvantages (10, 11), and it is accepted that there is no ideal method valid in all situations. The best choice depends on the objectives and design of the study (8). To assess typical dietary intake, the diet history interview is thought to be a reliable approach (5, 9) that does not limit the variability of response as is the case with FFQs (9). Diet history is particularly indicated for older people because their diets tend to be consistent over long periods of time and, although this is a retrospective technique, it does not rely on short-term memory and uses a much more interactive approach than other methods (7, 12-14). Moreover, diet histories have low respondent burden, which may improve response rates among older people and they require no literacy or numeracy skills from participants (5, 15, 16), making them suitable for participants of culturally and linguistically diverse backgrounds. The Concord Health and Ageing in Men Project (CHAMP) is a longitudinal cohort study of the health of older men based in Sydney, Australia, that has followed up men aged 70 years and over since 2005(17). In 2012, collection of nutritional data using the diet history method was added to the third wave of CHAMP data collection (five-year follow-up). Despite the clear advantages of using the diet history method to collect dietary data in our study, it was important to evaluate the validity of this method (9). Therefore, the aim of the study
J Nutr Health Aging
THE CONCORD HEALTH AND AGEING IN MEN PROJECT reported in this paper was to evaluate the relative validity of the DHQ used in CHAMP compared with a 4dWFR. This is the very first paper to describe this evaluation in men aged 75 and over and it provides insights into the challenges of collecting dietary information in this age group. Materials and Methods Participants The selection of CHAMP subjects has been described in detail elsewhere (17). Briefly, 3005 men aged 70 years and over living in the suburbs of Burwood, Canada Bay and Strathfield in Sydney, Australia who were on the electoral roll were invited to participate in CHAMP. A total of 1705 men participated in the project in the baseline data collection phase in 2005-2007. The only exclusion condition was living in a residential aged care facility. Participants completed a questionnaire at home and then attended a clinic where further data were collected through interview and examination. A total of 954 participants took part in the five-year follow-up and 794 (83%) agreed to the diet history interview. Participants interviewed for DHQ between July 2012 and October of 2013 were invited to take part in the validation study. Of the eligible 361 men invited, 62 agreed to participate in the validation study, resulting in a response rate of 17%. Prior to statistical analysis, data were checked to detect potential data entry errors. Two men declined to participate after explanation of the tasks involved, two had incomplete 4dWFRs and two men were excluded from analysis due to misreporting. The final sample therefore contained 56 men aged 75 to 86 years (mean 79 years, SD 2.96), 82% of participants were born in Australia, 32% had university education and 87% were married (Table 1). All participants gave written informed consent. The study was approved by the Sydney South West Area Health Service Human Research Ethics Committee, Concord Repatriation General Hospital, Sydney, Australia. Diet History Usual dietary intake was determined through collection of diet histories (18). Upon completion of five-year CHAMP follow up clinic visit, participants were contacted and invited to answer a diet history questionnaire (DHQ), which was conducted by a trained dietitian at the participant’s residence using a standardised interview method. Participants were asked questions about their dietary intake during the previous three months, and quantities of foods consumed were ascertained by means of food models, photos (19), and household measures e.g. cup size. The diet history interview took on average 45 minutes to be administered. The diet history questionnaire form (open-ended questions on foods consumption at different meal times) used in CHAMP was adapted from the Sydney South West Area Health Service outpatient’s diet history form. Participants’ wives, carers and/or family members were encouraged to be present during interview as it has been 2
suggested to assist in participants’ recall (14). Weighed Food Record (WFR) At the end of the diet history interview, participants were invited to take part in the validation study. At that time, an invitation letter containing a summary of tasks involved was given to potential participants. Contact was then made within a week to arrange participants’ training. All the training and 4dWFR were completed within 5 weeks after diet history interview. Participants in the validation study were required to weigh and record their dietary intake for four consecutive days (including a weekend day) giving as much detail about food consumed as possible. This included brands, preparation technique, leftovers (bones, skin, core), recipes and food consumed outside of home. An electronic scale (Salter SpaceSaver Electronic Kitchen Scale) was provided along with photographic and written instructions, weighed food record booklet and dairy to record food eaten away from home. A trained dietitian demonstrated the procedure to participants. The CHAMP 4dWFR and eating out dairy were adapted from Henderson, Gregory (20). Participants were asked not to change their dietary habits during the study period, and encouraged to contact the dietitian if they had any difficulties. The dietitian contacted the participant by telephone on day 3 of the validation study to ensure that records were completed correctly and to address any problems. Upon completion of the 4dWFR, the dietitian returned to participants’ residences to collect and check diaries for accuracy and clarification. Participants were given a nutritional assessment of their diet based on the four days of the study, as a token of appreciation for their participation. We have not reported the analysis for water, vitamin and mineral supplements, as these were not specified in the 4dWFR (i.e. arbitrarily reported). Misreporting (both under- and over-reporting) is common in dietary studies and there are a number of exclusion methods to address this issue (21-24). One of these methods utilises estimates of an individual’s basal metabolic rate (BMR) and physical activity level (PAL) to estimate total energy expenditure (TEE) and compare this with reported energy intake, and implausible data are then excluded. CHAMP participants’ activity levels were measured using the Physical Activity Scale for the Elderly (PASE) (25) which uses a different scoring system to PAL. Participants’ PASE scores varied greatly (0 to 507) and it was not feasible to adjust to the standard PAL ranges (1.2 bed rest to 2.2 elite athlete). Instead, data of participants who reported energy intake above or below 2 standard deviations from the median were excluded because of probable misreporting. Dietary data analysis Participants’ daily dietary intakes were converted into nutrients using FoodWorks 7 Professional for Windows (Xyris Software (Australia) Pty Ltd, Brisbane, 2012) based
J Nutr Health Aging
THE JOURNAL OF NUTRITION, HEALTH & AGING© Correlation Pearson and Spearman’s correlation coefficients were calculated for each energy-adjusted, log-transformed and/or crude nutrient intake to determine the strength of relationship between the DHQ and 4dWFR and for comparison with other published validation studies.
upon the Australian nutrient database (AUSNUT 2007)(26), which contains the complete dataset for each food (27). A total of 27 nutrients as well as energy intake were analysed. A standardised manual was developed to assist with data entry of the diet history questionnaire, where 869 food items were identified and standardised. Recipes were entered using specific amounts as described by participants, and in cases where a food item was not available in FoodWorks, a similar food item was selected.
Results Bland-Altman, GAM smoothing splines and Bias The mean and SD of each method by nutrient, the mean difference between methods with their 95% limits of agreement, and presence of fixed and proportional bias are shown in Table 2. Mean difference between methods ranged from -18% (alcohol) to 37% (β-carotene). The 95% limits of agreement ranged from -40% to 327%. With the exception of carbohydrate (g and percentage of energy), alcohol, thiamin, retinol, sodium and percentage of energy from alcohol, diet history tended to yield higher estimates of nutrients intakes. Individual data points generally fell within the 95% limits of agreement for most nutrients. The smoothing splines showed little evidence of trends in mean differences as a function of average in selected cases (vitamin A equivalent, retinol, β-carotene, calcium, phosphorus, iron and percentage of energy from carbohydrate) that contained outliers towards the extreme intakes.
Data transformation Normality of each nutrient was assessed by the ShapiroWilk test (28). The majority of nutrients had a skewed distribution. Consequently, data of each nutrient was logtransformed and energy adjusted (nutrient values/ total energy intake (kJ) = nutrient per kJ) prior to analysis to also evaluate nutrient density of diets(9). Alcohol intakes of 0g were replaced with values of 1g before log-transformation (as log of 1=0). Analyses were performed using the R statistical environment, version 3.0.2 for windows (29). Confidence intervals were generated at the 95% level, and evidence against null hypotheses was considered statistically significant if the resulting p-values were less than 0.05. Bland-Altman method and GAM smoothing splines Bland-Altman plots are widely used in comparison analyses to evaluate the agreement between a tested and a standard method(30). The mean percentage difference between methods (DHQ-4dWFR/4dWFR) was plotted against the mean by the two methods of energy (kJ) and all nutrients (DHQ-4dWFR/2). The 95% limits of agreement (LOA) were calculated (mean % difference ±1.96*(SD of difference (%)). Additionally, using mcgv package (31) for generalized additive models (GAMs), smoothing spline of the percentage difference between methods of each individual as a function of the mean nutrient intakes was also produced. Essentially, these lines show the moving (increase or decrease) difference between methods as a function of the mean nutrient intake values of both methods (32).
Figure 1 Bland–Altman plots of the difference between total energy (kJ) and retinol (µg) intake estimated from the diet history questionnaire (DHQ) and the four-day weighed food record (4dWFR) plotted against means from the two methods for total energy (kJ) and retinol (µg)
Proportional and fixed bias detection Fixed and proportional biases are the two potential sources of systematic disagreement between methods. Fixed bias occurs when a method provides values that are consistently different (higher or lower) by a fixed amount to those provided by the compared method; proportional bias occurs when the difference is proportional to the level of the measured variable(33). To differentiate the two we utilised the standard major axis (SMA) regression analysis(34, 35). Average of 4dWFR intakes were regressed on DHQ intakes, then regression estimates of the intercept and slope were used to determine if the 95% confidence interval (CI) of the intercept did not include 0 (indicating presence of fixed bias), and if the 95% CI of the slope excluded 1 (interpreted as evidence of proportional bias). 3
J Nutr Health Aging
THE CONCORD HEALTH AND AGEING IN MEN PROJECT Discussion
Table 1 Participants’ characteristics (n=56) Characteristic
n=56
BMI (mean), kg/m2 (range)
27.15 (19 – 39)
Age (mean), years (range)
Weight (mean), kg (range)
PASE (mean), score (range)
MMSE (mean), score (range) Level of education* , %
79.2 (75 – 86)
80 (153 – 103) 147 (36 – 397) 28.7 (22 – 30)
Bachelor degree or higher
32% (n=18)
Certificate/diploma
25% (n=14)
Trade/apprenticeship No education
Source of income, % Age pension Other †
Country of birth, % Australia Other ‡
Marital status, %
18% (n=10) 23% (n=13) 43% (n=24) 57% (n=32) 82% (n=46) 18% (n=10)
Married
87% (n=49)
Never married/divorced
4% (n=2)
Widowed
To our knowledge, this study is the first to validate a diet history questionnaire against a four-day weighed food record in a group of community-dwelling men aged 75 years or older. Overall, diet history estimates of intakes tended to be higher than estimates from weighed food records. Differences between the two methods were generally less than 20% with the exception of β-carotene (37%). Fixed and proportional bias were only present for retinol, β-carotene, magnesium, phosphorus and percentage of energy from protein; however, 95% limits of agreement were in some cases wide, possibly due to the modest sample size of this study. There is very limited literature on validation of dietary methods against food records (excluding those investigating dietary patterns or one specific nutrient) in people aged 70 years and over, and no other study has focused on this topic utilising exclusively male participants’ data. Previous studies (6-8, 15, 36-38) have focused on correlation coefficients, cross classification and/or difference between the reference and tested method, without investigating the presence of systematic bias - a unique methodological aspect of our study. Correlation coefficients are widely used in validation studies to measure the degree of association between methods. Non-significant (unadjusted zinc, r=0.15, p>0.05) to very strong (unadjusted percentage of energy from alcohol, r=0.70, p
THE JOURNAL OF NUTRITION, HEALTH & AGING©
RELATIVE VALIDITY OF A DIET HISTORY QUESTIONNAIRE AGAINST A FOUR-DAY WEIGHED FOOD RECORD AMONG OLDER MEN IN AUSTRALIA: THE CONCORD HEALTH AND AGEING IN MEN PROJECT (CHAMP) R.V.R. WAERN1,2,3, R. CUMMING2,3, T. TRAVISON4, F. BLYTH1, V. NAGANATHAN1, M. ALLMAN-FARINELLI5, V. HIRANI1 1. Centre for Education and Research on Ageing, Concord Hospital, University of Sydney, NSW, Australia; 2. School of Public Health, University of Sydney, NSW, Australia; 3. ARC Centre of Excellence in Population Ageing Research, University of Sydney, Australia; 4. Institute for Ageing Research, Hebrew Senior Life, Harvard Medical School, Boston, MA, USA; 5. School of Molecular Bioscience, University of Sydney, NSW Australia. Corresponding author: Waern Rosilene, Centre for Education and Research on Ageing, Concord Hospital, University of Sydney, NSW, Australia, [email protected]
Abstract: Objectives: To evaluate the relative validity of the diet history questionnaire (DHQ) used in the Concord Health and Ageing in Men Project (CHAMP) against a four-day weighed food record (4dWFR) as the reference method. Design and measurements: Detailed DHQ followed by a 4dWFR were completed between July 2012 and October of 2013. Setting: Burwood, Canada Bay and Strathfield in Sydney, Australia. Participants: Fifty six community- dwelling men aged 75 years and over (mean=79 years). Results: DHQ estimates of intakes were generally higher than estimates from 4dWFR. Differences between the two methods were generally less than 20% with the exception of β-carotene (37%). Fixed and proportional biases were only present for retinol, β-carotene, magnesium, phosphorus and percentage of energy from protein; however, 95% limits of agreement were in some cases wide. Pearson correlation coefficient of log-transformed unadjusted values ranged from 0.15 (zinc) to 0.70 (alcohol), and from 0.06 (iron) to 0.63 (thiamin) after energy-adjustment. Spearman’s correlation coefficients ranged from 0.16 (zinc) to 0.80 (alcohol) before energy adjustment, and from 0.15(zinc) to 0.81(alcohol) after energy adjustment. Conclusion: Our findings suggest that the DHQ used in CHAMP to measure the nutritional intake of its participants is appropriate to this age group and provides reasonably similar results to the 4dWFR for the majority of nutrients analysed. Key words: Validity, weighed food record, diet history questionnaire, elderly men.
Introduction The population is ageing rapidly in Australia and in the rest of the world (1); however, there is very little known about the dietary habits of older people. Dietary habits are one of the important modifiable factors that can affect the maintenance of health in old age (2) and therefore diet should be a key component of epidemiological studies involving older people. Although a comprehensive understanding of older peoples’ dietary habits is essential, collection of dietary intake data from older subjects can be a challenging task, particularly when it involves reliance on short-term memory (3). It is important that data are obtained through appropriate methodology to avoid misleading conclusions and potentially ineffective interventions (4, 5). However, in reviewing the literature, only a small number of validation studies of dietary intake among people aged 70 years and over were identified (6-8), moreover some studies have investigated diet-disease relationships utilising methods that were not validated. Absolute validity of a dietary method cannot be measured because absolute intake is impossible to determine (9). Typically, the tested method is compared to a method that has a greater degree of validity, and relative validity is assessed. The weighed food record is a prospective method that does not rely on participants’ memory and is considered the “gold standard” for comparisons with less detailed and demanding methods. There are three main methods for dietary measurement Received August 18, 2014 Accepted for publication September 18, 2014
1
available to epidemiological research: Diet history questionnaire, food frequency questionnaire (FFQ) and 24-hour recall. All have advantages and disadvantages (10, 11), and it is accepted that there is no ideal method valid in all situations. The best choice depends on the objectives and design of the study (8). To assess typical dietary intake, the diet history interview is thought to be a reliable approach (5, 9) that does not limit the variability of response as is the case with FFQs (9). Diet history is particularly indicated for older people because their diets tend to be consistent over long periods of time and, although this is a retrospective technique, it does not rely on short-term memory and uses a much more interactive approach than other methods (7, 12-14). Moreover, diet histories have low respondent burden, which may improve response rates among older people and they require no literacy or numeracy skills from participants (5, 15, 16), making them suitable for participants of culturally and linguistically diverse backgrounds. The Concord Health and Ageing in Men Project (CHAMP) is a longitudinal cohort study of the health of older men based in Sydney, Australia, that has followed up men aged 70 years and over since 2005(17). In 2012, collection of nutritional data using the diet history method was added to the third wave of CHAMP data collection (five-year follow-up). Despite the clear advantages of using the diet history method to collect dietary data in our study, it was important to evaluate the validity of this method (9). Therefore, the aim of the study
J Nutr Health Aging
THE CONCORD HEALTH AND AGEING IN MEN PROJECT reported in this paper was to evaluate the relative validity of the DHQ used in CHAMP compared with a 4dWFR. This is the very first paper to describe this evaluation in men aged 75 and over and it provides insights into the challenges of collecting dietary information in this age group. Materials and Methods Participants The selection of CHAMP subjects has been described in detail elsewhere (17). Briefly, 3005 men aged 70 years and over living in the suburbs of Burwood, Canada Bay and Strathfield in Sydney, Australia who were on the electoral roll were invited to participate in CHAMP. A total of 1705 men participated in the project in the baseline data collection phase in 2005-2007. The only exclusion condition was living in a residential aged care facility. Participants completed a questionnaire at home and then attended a clinic where further data were collected through interview and examination. A total of 954 participants took part in the five-year follow-up and 794 (83%) agreed to the diet history interview. Participants interviewed for DHQ between July 2012 and October of 2013 were invited to take part in the validation study. Of the eligible 361 men invited, 62 agreed to participate in the validation study, resulting in a response rate of 17%. Prior to statistical analysis, data were checked to detect potential data entry errors. Two men declined to participate after explanation of the tasks involved, two had incomplete 4dWFRs and two men were excluded from analysis due to misreporting. The final sample therefore contained 56 men aged 75 to 86 years (mean 79 years, SD 2.96), 82% of participants were born in Australia, 32% had university education and 87% were married (Table 1). All participants gave written informed consent. The study was approved by the Sydney South West Area Health Service Human Research Ethics Committee, Concord Repatriation General Hospital, Sydney, Australia. Diet History Usual dietary intake was determined through collection of diet histories (18). Upon completion of five-year CHAMP follow up clinic visit, participants were contacted and invited to answer a diet history questionnaire (DHQ), which was conducted by a trained dietitian at the participant’s residence using a standardised interview method. Participants were asked questions about their dietary intake during the previous three months, and quantities of foods consumed were ascertained by means of food models, photos (19), and household measures e.g. cup size. The diet history interview took on average 45 minutes to be administered. The diet history questionnaire form (open-ended questions on foods consumption at different meal times) used in CHAMP was adapted from the Sydney South West Area Health Service outpatient’s diet history form. Participants’ wives, carers and/or family members were encouraged to be present during interview as it has been 2
suggested to assist in participants’ recall (14). Weighed Food Record (WFR) At the end of the diet history interview, participants were invited to take part in the validation study. At that time, an invitation letter containing a summary of tasks involved was given to potential participants. Contact was then made within a week to arrange participants’ training. All the training and 4dWFR were completed within 5 weeks after diet history interview. Participants in the validation study were required to weigh and record their dietary intake for four consecutive days (including a weekend day) giving as much detail about food consumed as possible. This included brands, preparation technique, leftovers (bones, skin, core), recipes and food consumed outside of home. An electronic scale (Salter SpaceSaver Electronic Kitchen Scale) was provided along with photographic and written instructions, weighed food record booklet and dairy to record food eaten away from home. A trained dietitian demonstrated the procedure to participants. The CHAMP 4dWFR and eating out dairy were adapted from Henderson, Gregory (20). Participants were asked not to change their dietary habits during the study period, and encouraged to contact the dietitian if they had any difficulties. The dietitian contacted the participant by telephone on day 3 of the validation study to ensure that records were completed correctly and to address any problems. Upon completion of the 4dWFR, the dietitian returned to participants’ residences to collect and check diaries for accuracy and clarification. Participants were given a nutritional assessment of their diet based on the four days of the study, as a token of appreciation for their participation. We have not reported the analysis for water, vitamin and mineral supplements, as these were not specified in the 4dWFR (i.e. arbitrarily reported). Misreporting (both under- and over-reporting) is common in dietary studies and there are a number of exclusion methods to address this issue (21-24). One of these methods utilises estimates of an individual’s basal metabolic rate (BMR) and physical activity level (PAL) to estimate total energy expenditure (TEE) and compare this with reported energy intake, and implausible data are then excluded. CHAMP participants’ activity levels were measured using the Physical Activity Scale for the Elderly (PASE) (25) which uses a different scoring system to PAL. Participants’ PASE scores varied greatly (0 to 507) and it was not feasible to adjust to the standard PAL ranges (1.2 bed rest to 2.2 elite athlete). Instead, data of participants who reported energy intake above or below 2 standard deviations from the median were excluded because of probable misreporting. Dietary data analysis Participants’ daily dietary intakes were converted into nutrients using FoodWorks 7 Professional for Windows (Xyris Software (Australia) Pty Ltd, Brisbane, 2012) based
J Nutr Health Aging
THE JOURNAL OF NUTRITION, HEALTH & AGING© Correlation Pearson and Spearman’s correlation coefficients were calculated for each energy-adjusted, log-transformed and/or crude nutrient intake to determine the strength of relationship between the DHQ and 4dWFR and for comparison with other published validation studies.
upon the Australian nutrient database (AUSNUT 2007)(26), which contains the complete dataset for each food (27). A total of 27 nutrients as well as energy intake were analysed. A standardised manual was developed to assist with data entry of the diet history questionnaire, where 869 food items were identified and standardised. Recipes were entered using specific amounts as described by participants, and in cases where a food item was not available in FoodWorks, a similar food item was selected.
Results Bland-Altman, GAM smoothing splines and Bias The mean and SD of each method by nutrient, the mean difference between methods with their 95% limits of agreement, and presence of fixed and proportional bias are shown in Table 2. Mean difference between methods ranged from -18% (alcohol) to 37% (β-carotene). The 95% limits of agreement ranged from -40% to 327%. With the exception of carbohydrate (g and percentage of energy), alcohol, thiamin, retinol, sodium and percentage of energy from alcohol, diet history tended to yield higher estimates of nutrients intakes. Individual data points generally fell within the 95% limits of agreement for most nutrients. The smoothing splines showed little evidence of trends in mean differences as a function of average in selected cases (vitamin A equivalent, retinol, β-carotene, calcium, phosphorus, iron and percentage of energy from carbohydrate) that contained outliers towards the extreme intakes.
Data transformation Normality of each nutrient was assessed by the ShapiroWilk test (28). The majority of nutrients had a skewed distribution. Consequently, data of each nutrient was logtransformed and energy adjusted (nutrient values/ total energy intake (kJ) = nutrient per kJ) prior to analysis to also evaluate nutrient density of diets(9). Alcohol intakes of 0g were replaced with values of 1g before log-transformation (as log of 1=0). Analyses were performed using the R statistical environment, version 3.0.2 for windows (29). Confidence intervals were generated at the 95% level, and evidence against null hypotheses was considered statistically significant if the resulting p-values were less than 0.05. Bland-Altman method and GAM smoothing splines Bland-Altman plots are widely used in comparison analyses to evaluate the agreement between a tested and a standard method(30). The mean percentage difference between methods (DHQ-4dWFR/4dWFR) was plotted against the mean by the two methods of energy (kJ) and all nutrients (DHQ-4dWFR/2). The 95% limits of agreement (LOA) were calculated (mean % difference ±1.96*(SD of difference (%)). Additionally, using mcgv package (31) for generalized additive models (GAMs), smoothing spline of the percentage difference between methods of each individual as a function of the mean nutrient intakes was also produced. Essentially, these lines show the moving (increase or decrease) difference between methods as a function of the mean nutrient intake values of both methods (32).
Figure 1 Bland–Altman plots of the difference between total energy (kJ) and retinol (µg) intake estimated from the diet history questionnaire (DHQ) and the four-day weighed food record (4dWFR) plotted against means from the two methods for total energy (kJ) and retinol (µg)
Proportional and fixed bias detection Fixed and proportional biases are the two potential sources of systematic disagreement between methods. Fixed bias occurs when a method provides values that are consistently different (higher or lower) by a fixed amount to those provided by the compared method; proportional bias occurs when the difference is proportional to the level of the measured variable(33). To differentiate the two we utilised the standard major axis (SMA) regression analysis(34, 35). Average of 4dWFR intakes were regressed on DHQ intakes, then regression estimates of the intercept and slope were used to determine if the 95% confidence interval (CI) of the intercept did not include 0 (indicating presence of fixed bias), and if the 95% CI of the slope excluded 1 (interpreted as evidence of proportional bias). 3
J Nutr Health Aging
THE CONCORD HEALTH AND AGEING IN MEN PROJECT Discussion
Table 1 Participants’ characteristics (n=56) Characteristic
n=56
BMI (mean), kg/m2 (range)
27.15 (19 – 39)
Age (mean), years (range)
Weight (mean), kg (range)
PASE (mean), score (range)
MMSE (mean), score (range) Level of education* , %
79.2 (75 – 86)
80 (153 – 103) 147 (36 – 397) 28.7 (22 – 30)
Bachelor degree or higher
32% (n=18)
Certificate/diploma
25% (n=14)
Trade/apprenticeship No education
Source of income, % Age pension Other †
Country of birth, % Australia Other ‡
Marital status, %
18% (n=10) 23% (n=13) 43% (n=24) 57% (n=32) 82% (n=46) 18% (n=10)
Married
87% (n=49)
Never married/divorced
4% (n=2)
Widowed
To our knowledge, this study is the first to validate a diet history questionnaire against a four-day weighed food record in a group of community-dwelling men aged 75 years or older. Overall, diet history estimates of intakes tended to be higher than estimates from weighed food records. Differences between the two methods were generally less than 20% with the exception of β-carotene (37%). Fixed and proportional bias were only present for retinol, β-carotene, magnesium, phosphorus and percentage of energy from protein; however, 95% limits of agreement were in some cases wide, possibly due to the modest sample size of this study. There is very limited literature on validation of dietary methods against food records (excluding those investigating dietary patterns or one specific nutrient) in people aged 70 years and over, and no other study has focused on this topic utilising exclusively male participants’ data. Previous studies (6-8, 15, 36-38) have focused on correlation coefficients, cross classification and/or difference between the reference and tested method, without investigating the presence of systematic bias - a unique methodological aspect of our study. Correlation coefficients are widely used in validation studies to measure the degree of association between methods. Non-significant (unadjusted zinc, r=0.15, p>0.05) to very strong (unadjusted percentage of energy from alcohol, r=0.70, p
