Next Article in Journal
Concepts and Controversies in Evaluating Vitamin K Status in Population-Based Studies
Next Article in Special Issue
Negative, Null and Beneficial Effects of Drinking Water on Energy Intake, Energy Expenditure, Fat Oxidation and Weight Change in Randomized Trials: A Qualitative Review
Previous Article in Journal
Magnesium Levels in Drinking Water and Coronary Heart Disease Mortality Risk: A Meta-Analysis
Previous Article in Special Issue
Hypolipidemic Effect of Tomato Juice in Hamsters in High Cholesterol Diet-Induced Hyperlipidemia
Open AccessArticle

Low Calorie Beverage Consumption Is Associated with Energy and Nutrient Intakes and Diet Quality in British Adults

1
Sig-Nurture, Guildford, Surrey GU1 2TF, UK
2
Biomathematics and Statistics Scotland, Aberdeen AB21 9SB, Scotland
3
Department of Nutritional Sciences, University of Surrey, Guildford, Surrey GU2 7XH, UK
*
Author to whom correspondence should be addressed.
Nutrients 2016, 8(1), 9; https://doi.org/10.3390/nu8010009
Received: 5 November 2015 / Revised: 8 December 2015 / Accepted: 10 December 2015 / Published: 2 January 2016
(This article belongs to the Special Issue Beverage Consumption and Human Health)

Abstract

It is unclear whether consumption of low-calorie beverages (LCB) leads to compensatory consumption of sweet foods, thus reducing benefits for weight control or diet quality. This analysis investigated associations between beverage consumption and energy intake and diet quality of adults in the UK National Diet and Nutrition Survey (NDNS) (2008–2011; n = 1590), classified into: (a) non-consumers of soft drinks (NC); (b) LCB consumers; (c) sugar-sweetened beverage (SSB) consumers; or (d) consumers of both beverages (BB), based on 4-day dietary records. Within-person data on beverage consumption on different days assessed the impact on energy intake. LCB consumers and NC consumed less energy and non-milk extrinsic sugars than other groups. Micronutrient intakes and food choices suggested higher dietary quality in NC/LCB consumers compared with SSB/BB consumers. Within individuals on different days, consumption of SSB, milk, juice, and alcohol were all associated with increased energy intake, while LCB and tea, coffee or water were associated with no change; or reduced energy intake when substituted for caloric beverages. Results indicate that NC and LCB consumers tend to have higher quality diets compared with SSB or BB consumers and do not compensate for sugar or energy deficits by consuming more sugary foods.
Keywords: low calorie; beverage; diet; energy intake; nutrient intake; soft drinks low calorie; beverage; diet; energy intake; nutrient intake; soft drinks

1. Introduction

In the latest results from the UK National Diet and Nutrition Survey [1], 44% by weight of all soft drinks consumed by adults aged 19–64 years were low-calorie beverages (LCB), a higher proportion than in other European countries [2]. In the United States, where per capita consumption of beverages is roughly double that in the UK [3], results of NHANES 2003–2010 showed that LCB constituted 32% of beverages among adults and 19% among children [4]. As a substitute for sugar-sweetened beverages (SSB), LCB offer the potential to satisfy both thirst and an innate desire for sweetness [5] with minimal caloric load [6]. Replacing an energy-containing beverage with an energy-free one may reduce energy intake, depending on the extent of compensation, both short-term and long-term [7,8,9]. The majority of randomised controlled trials (RCTs) among adults suggest that using LCB instead of caloric beverages over several weeks or months results in modest weight loss [10,11,12,13], although results vary by age, sex, ethnicity, or weight status groups [14]. Trials in overweight adolescents [15] and normal weight children [16] have found that replacing SSB with drinks like water or LCB may prevent weight gain. One adult weight loss trial found greater weight loss with LCB compared to water [17] and a recent systematic review and meta-analysis of ad libitum studies also concluded that use of low energy sweeteners (LCS) in place of sugar leads to reduced energy intake (EI) and bodyweight, possibly also when compared with water [18].
While most expert committees advise reduced consumption of SSB to reduce energy intake [19,20], they vary in advice about substituting with LCB. One reason may be a fear that LCB may encourage compensatory overeating of sweet foods or foods lower in nutrients. The impact on dietary quality should be included in assessing the overall balance of benefits and risks for LCS and LCB [21], but data are limited. In a review of the impact of LCS on weight management, Anderson et al. found that users of LCB or LCS reported higher quality diets than non-users [22], although not all studies were consistent. Using NHANES data from 1999 to 2008, Drewnowski and Rehm found that consumers of LCS, were more likely to be female, white, older, and of higher socio-economic status, to be non-smokers and more physically active than non-consumers of LCS, suggesting that LCS consumption is a marker for a healthy diet and lifestyle [23]. Moreover, users of LCB as well as LCS had significantly higher quality diets than non-users.
The effect of LCB on diet quality will depend on the way such beverages are used in the context of the overall diet. In order to target policy and advice appropriately there is a need to explore the dietary composition of those who drink LCB, SSB or no soft drinks. The NDNS rolling programme, with recent data from a representative sample of the UK population, provides an opportunity to conduct such a study. A novel aspect of our paper is the use of 4 days of data for within-person analysis of beverage consumption and energy intake.

2. Methods

2.1. Sample

The NDNS is the most authoritative source of quantitative information on the food habits and nutrient intake of the UK population. Jointly funded by the Department of Health in England (now Public Health England) and the Food Standards Agency, the results are used by Government to develop policy and monitor trends in diet and nutrient intakes [1]. Data files from 3 years (2008–2011) of the NDNS Rolling Programme [24] were obtained under license from the UK Data Archive (http://www.esds.ac.uk). Households were sampled from the UK Postcode Address File, with one adult and one child (18 months or older), or one child selected for inclusion.

2.2. Interview

Participants completed a detailed computer assisted personal interview (CAPI) to obtain background information (age, gender, ethnicity, region) and eating and lifestyle behaviours such as smoking, dieting to lose weight, medication and supplement use. Education was classified into eight categories, consolidated into two groups for analysis (any qualifications vs. none). Participants were also classified by employment status: full or part-time employment, school or college full-time, or not working at present. Their National Statistics Socio-Economic Classification (NS-SEC) was determined, based on occupation and degree of supervisory responsibility (8 categories), consolidated into four categories for analysis: (a) Higher professional/managerial; (b) Lower professional/managerial; (c) Intermediate/small employer; and (d) Routine/manual/not working. Information was also collected on household income band.

2.3. Diet Record

Following the questionnaire respondents were asked to complete a dietary record for 4 consecutive days, giving a detailed description of each item consumed, time of consumption, and amount, using household measures and photographs. Repeat visits were made by interviewers to check records and probe for missing items. Fifty-five percent of those eligible to participate completed at least 3 days of the 4 days of dietary assessment. Anthropometric measurements (weight, height, waist circumference), taken by trained nurses, were obtained for 90% of those completing a diet record. Trained diet coders entered the food intake data from completed records using an in-house dietary assessment system at MRC Human Nutrition Research, DINO (Data In, Nutrients Out) [25] and using a databank of more than 7000 foods, regularly updated and extended for the survey. Volumes of tea, coffee and concentrated soft drinks included water added as diluent. In NDNS files, tea and coffee excluded contribution from milk and sugar (except for premixed tea and coffee from takeaway/vending sources). Milk was listed separately, while discretionary sugar was treated as a food. Nutrients were calculated using the food composition databank. Sugars (nutrient) are defined in NDNS as total sugars and also as non-milk extrinsic sugars; the latter includes all sugars added by the consumer or in processing plus sugars in fruit juice and 50% of sugars in dried and processed fruit.

2.4. Classification of Beverages

Beverages were classified as:
  • Low calorie beverages (LCB): all low- and no-calorie beverages, carbonated and still, ready to drink and diluted (weight of added water included). Excludes water.
  • Sugar-sweetened beverages (SSB): beverages with a range of sugar contents, carbonated and still, ready to drink and diluted (weight of added water included).
  • 100% fruit juices (FJ), not including fruit drinks.
  • Tea, coffee and water (TCW), excluding added milk (unless takeaway/vending beverage).
  • Milk: all liquid milk, including that added to hot beverages.
  • Alcoholic beverages: beer, cider, wine, spirits, alco-pops.

2.5. Classification of Respondents

Adults aged 16 years and over were classified into four groups according to whether or not they consumed LCB, SSB, both types (BB) or neither (NC) at any time over the 4 days of survey, as shown in Table 1.
Table 1. Classification of consumers according to consumption of Low Calorie Beverages (LCB) and Sugar-sweetened Beverages (SSB).
Table 1. Classification of consumers according to consumption of Low Calorie Beverages (LCB) and Sugar-sweetened Beverages (SSB).
No LCBLCBTotal N
No SSBNon-consumer (NC)LCB only
598216814
SSBSSB onlyBoth LCB and SSB (BB)
476300776
Total N10745161590

2.6. Statistical Methods

Differences in food and nutrient intake between beverage consumer groups were evaluated using ANOVA and multiple comparison tests with Bonferroni correction. In addition, planned contrasts (based on the null hypothesis that diets of LCB consumers did not differ from others) were used to compare LCB with each of the other groups for greater power. Homogeneity of variances between beverage groups was assessed using Levene’s test. Linear models were used to estimate the mean difference in EI between beverage categories, adjusted for covariates (age, sex, BMI status, ethnicity, education, social class, income, smoking and dieting practice). Weighting (NDNS variable: wti_adY12316) was used to adjust for sampling and non-response bias. Variation within individuals between different days (n = 6328 days) was studied using fixed effects models with individual identity, day of the week and day number (day 1 to days 4) as fixed effects to evaluate the impact on EI of varying consumption of LCB from day to day, using each individual as their own control. Beverages were entered as linear covariates (g/day). Two types of models were explored: (1) an unconstrained model of the impact of each beverage on EI if all other beverages and foods were allowed to vary as they do in practice; and (2) a substitution model of the effect of replacing LCB with other beverages. All data were analysed using SPSS version22 (IBM Statistics Inc., Portsmouth, Hants, UK).

3. Results

3.1. Subject Characteristics

Non-consumers (NC) were older than other groups, BB were youngest and there was no difference in mean age between LCB consumers and SSB consumers (Table 2). There were similar proportions of men and women in each beverage group. LCB consumers were more likely to be white (Caucasian) than SSB consumers. NC were least likely to have formal educational qualifications and were more likely to be non-working/retired. There was no significant difference in socio-economic classification overall, although a slightly higher proportion of LCB consumers had higher professional and managerial occupations, compared with those consuming both LCB and SSB (BB). Similarly, there was no significant difference in household income classification but a slightly higher proportion of LCB consumers had a household income over £30K compared to SSB consumers. In regard to health behaviours reported at interview, current smoking habits did not differ but LCB consumers and NC were more likely to be ex-smokers (p = 0.001), and LCB consumers were most likely to drink some alcohol (p = 0.03). There was no significant difference in the prevalence of dieting between groups. LCB consumers had a higher mean BMI compared with SSB consumers (mean 28.4 vs. 26.3 kg/m2; p < 0.0001) and were more likely to be obese (33% vs. 22%) (p = 0.001).
Table 2. Background characteristics of beverage consumer groups.
Table 2. Background characteristics of beverage consumer groups.
CharacteristicGroup Beverage Consumer Group 1Chi-Square p Value
NCLCBSSBBBAll
n 5982164763001590
AgeAll 16+mean55 a46 b43 b37 c47<0.0001
SE1111
Age group16–24%5 a6 a24 b27 b15<0.0001
25–44%2543334634
45–64%3839272131
65+%331316720
SexMale%47485247490.25
Female%5353485351
Ethnic groupWhite%8996 a86 b91890.002
Non-white%11414911
Socio-economic groupHigher Professional‎‎/managerial%1620 a1411 b150.26
Lower Professional/managerial%2727283028
Intermediate/small employers%2017221820
Routine/manual/not working%3836374138
Educational Qualifications 2Some%72 a84 b7885 b78<0.001
None%2816221522
Economic statusIn full-time education %3 a2 a10 b15 b7<0.0001
Employed%51 a66 b5562 b56
Not working or retired%47 a32 b35 b23 c37
Household income (£)<15 K%17151813160.08
15–30 K%3427373234
>30 K%50 a,b58 a45 b55 a,b50
On a dietNot dieting%87859188880.11
Dieting%131591212
Smoking statusCurrent smoker%19252323220.001
Ex-regular smoker%27 a27 a19 b16 b22
Never regular smoker%5549586156
Drink alcoholYes%81898286830.03
No%2012181417
BMI group Under 18.5 kg/m2%11402<0.001
18.5 and below 25 kg/m2%3328 a39 b42 b36
25 and below 30 kg/m2%3738343235
30+ kg/m2%2833 a22 b2627
BMI (kg/m2) Mean27.7 a28.4 a26.3 b27.227.20.001
SE0.240.40.240.340.14
1 NC, non-consumer; LCB, Low Calorie Beverages; SSB, Sugar Sweetened Beverages; BB, both LCB and SSB 2 Educational qualifications: Any qualifications (degree/A levels/GCSE/foreign qualification/still in fulltime education) vs. no qualifications. Values sharing the same postscript (or none) are not significantly different (T-test, or Z-test of column proportions with Bonferroni correction for multiple comparisons).

3.2. Beverage Consumption

Mean consumption of LCB was 297 g/day (LCB group) and of SSB 253 g/day (SSB group), while consumers of both types drank on average 548 g/day, with almost equal amounts of LCB and SSB (Table 3). Total fluid intake from beverages (i.e., excluding water in foods) was slightly lower among NC compared with other groups (mean 1679 g/day vs. >1800 g/day; p = 0.008). NC drank more tea than SSB and BB, and less alcohol than SSB. There was no significant difference in the consumption of milk, fruit juice or plain water between the four groups.
Table 3. Beverage consumption (g/day) according to beverage consumer group.
Table 3. Beverage consumption (g/day) according to beverage consumer group.
Beverage Beverage Consumer GroupOverall ANOVAPlanned Contrasts
NCLCBSSBBBAllLCB vs. NCLCB vs. SSBLCB vs. BB
n5982164763001590
Sugar-sweetened beverages (SSB)Mean0 a0 a253 b263 b129<0.00011.0<0.0001<0.0001
SE0011176
Low calorie beverages (LCB)Mean0 a297 b0 a284 b90<0.0001<0.0001<0.00010.67
SE0240186
Tea, coffee, waterMean1245 a1070 b1041 b821 c1080<0.00010.0010.6<0.0001
SE2544293016
TeaMean490 a423 a,b359 b,c270 c399<0.00010.050.06<0.0001
SE1829191810
CoffeeMean281 a256 a238 a,b196 b2490.0050.40.500.04
SE152216189
Tap WaterMean3423103482903300.20.30.30.7
SE1931232212
Bottled WaterMean98717856800.050.10.60.3
SE1212886
Fruit Juice Mean48 a58 a,b56 b62 b550.30.30.90.8
SE49493
Alcoholic drinksMean222 a219 a,b316 b268 a,b2600.020.90.040.3
SE1636303313
MilkMean1641631541521580.51.00.50.45
SE511693
Total BeveragesMean1679 a1807 a,b1821 a,b1850 b17720.0080.050.850.6
SE3057425321
Values sharing the same postscript or none are not significantly different (multiple comparison t-test with Bonferroni correction). Planned contrasts of LCB vs. each of the other beverages as specified a priori. Tests assume equal/unequal variance based on Levene’s test.

3.3. Food Consumption

In terms of food choices, NC appeared to have the most health conscious diets and BB the least (Table 4). NC ate significantly more fruit and vegetables and fish than SSB or BB, while LCB consumers had similar intakes to NC, and ate significantly more fruit, vegetables and fish than BB. BB consumers ate significantly more meat and meat products, chips and white bread than either LCB or NC. NC ate more high-fibre breakfast cereal and less confectionery than all other groups. There were fewer significant differences between LCB and SSB consumers although LCB consumers ate less sugar and jam than SSB. However the total amount of processed sugary foods, excluding drinks, (i.e., biscuits, cakes, puddings and ice cream, confectionery, sugar and sweet spreads) was similar across all beverage groups (mean: 72, 71, 79, 75 g/day in NC, LCB consumers, SSB consumers, BB consumers, respectively; p = 0.37).
Table 4. Food consumption (g/day) according to beverage consumer group.
Table 4. Food consumption (g/day) according to beverage consumer group.
Food Group Beverage Consumer GroupPlanned Contrasts
NCLCB SSB BBAllOverall ANOVALCB vs. NCLCB vs. SSBLCB vs. BB
n5982164763001590
Meat and Meat Products Mean167 a181 a,b193 b,c211 c185<0.00010.10.20.009
SE58583
FishMean46 a42 a,b34 b31 b,c39<0.00010.40.090.03
SE2.43.92.12.71.3
FruitMean110 a105 a,b88 b,c74 c96<0.00010.60.050.001
SE57553
VegetablesMean147 a137 a,b129 b,c112 c133<0.00010.20.30.005
SE47453
PotatoesMean84 a82 a88 a,b99 b880.0040.80.30.004
SE34342
Chips, Fried and Roast PotatoesMean35 a38 a,b45 b,c52 c42<0.00010.40.10.004
SE23231
BreadMean80 a80 a88 a,b90 b840.0061.00.050.04
SE23231
White breadMean43 a42 a,b54 b,c58 c49<0.00010.80.0020.001
SE22121
Pasta, Rice & other cerealsMean65 a65 a,b80 b88 b,c74<0.00011.00.020.002
SE35452
Breakfast cerealsMean34 a23 b26 b20 b28<0.00010.0010.30.3
SE22211
High fibre breakfast cerealsMean29 a19 a,b19 b13 b,c21<0.00010.0020.80.04
SE22211
Sugary foodsMean73717873740.40.70.10.7
SE34332
Puddings, yogurt and ice creamMean50484945490.90.70.80.6
SE34332
Biscuits and cakesMean34323331330.70.50.70.8
SE22221
ConfectioneryMean6 a11 b,c12 b14 c10<0.00010.0010.50.06
SE11111
Sugar, jam and sweet spreadsMean12 a,c9 b13 a9 b,c11<0.00010.0030.0010.9
SE11111
Values sharing the same postscript or none are not significantly different (multiple comparison t-test with Bonferroni correction). Italics denote food subgroups. Planned contrasts of LCB vs. each of the other beverages as specified a priori. Tests assume equal/unequal variance based on Levene’s test. No significant differences in consumption of fats, cheese, eggs.

3.4. Energy and Macronutrient Intake

Adults consuming LCB had a mean total energy intake (TEI) identical to NC (1719, SE 21 vs. 1718 kcal/day, SE 42) and significantly lower than SSB consumers (1958 kcal/day SE 29), or BB (1986 kcal/day, SE 35) (Table 5), with a mean difference of 239 kcal, SE 51 between LCB consumers and SSB consumers (p < 0.0001). NC and LCB consumers had lower energy intakes from food as well as from beverages, compared to SSB consumers and consumers of both types (Figure 1). Overall, approximately 40%–50% of the total energy difference between groups was attributable to foods rather than beverages. NC and LCB consumers had significantly lower intakes of (non-milk extrinsic) sugars (both as g/day and % energy) compared with SSB and BB consumers (p < 0.0001) (Table 5). Intakes of fat and saturated fatty acids (SFA) were lower on an absolute basis (g/day) (p < 0.01) but not as a percentage of energy. Protein intakes were higher (as a percentage of energy) in LCB consumers than any other group.
Figure 1. Energy intake from food and beverage sources according to beverage consumer group.
Figure 1. Energy intake from food and beverage sources according to beverage consumer group.
Nutrients 08 00009 g001
Table 5. Energy and macronutrient intake according to beverage consumer group.
Table 5. Energy and macronutrient intake according to beverage consumer group.
Macronutrient Intake (per Day) Beverage Consumer GroupPlanned Contrasts
NCLCBSSBBBAllOverall ANOVALCB vs. NCLCB vs. SSBLCB vs. BB
n 5982164763001590
Energy (kcal)Mean1718 a1719 a1958 b1986 b1844<0.00011.0<0.0001<0.0001
SE2142293515
Protein (g)Mean72747577740.10.40.90.3
SE1.21.91.01.40.7
Fat (g)Mean66 a65 a72 b74 b69<0.00010.60.001<0.0001
SE1.02.01.21.60.7
Carbohydrate (g)Mean200 a200 a239 b243 b221<0.00011.0<0.0001<0.0001
SE25342
Saturated fatty acids (g)Mean24.4 a24.2 a26.7 b27.0 b25.6<0.00010.80.010.007
SE0.40.80.50.60.3
Monounsaturated fatty acids (g)Mean23.2 a22.9 a26.0 b27.1 b24.8<0.00010.7<0.0001<0.0001
SE0.40.70.50.60.3
n-6 Fatty acids (g)Mean9.5 a9.2 a10.2 a,b10.6 b9.9<0.00010.40.0090.001
SE0.20.30.20.30.1
n-3 Fatty acids (g)Mean2.11.92.12.12.10.0960.020.050.02
SE0.10.10.10.10.03
Trans fatty acids (g)Mean1.34 a1.37 a,b1.48 b1.49 b,c1.420.0040.70.10.1
SE0.030.060.030.040.02
Starch (g)Mean117 a118 a128 b138 c125<0.00010.90.007<0.0001
SE23231
Non-milk extrinsic sugars (g)Mean43 a43 a76 b71 b59<0.00011.0<0.0001<0.0001
SE12221
Non-starch polysaccharide (g)Mean13.913.913.313.313.60.2001.00.30.2
SE0.20.40.20.30.1
Macronutrients (% energy)
ProteinMean17.1 a18 b15.7 c15.7 c16.5<0.00010.03<0.0001<0.0001
SE0.20.40.20.20.1
FatMean33.933.233.033.233.40.10.30.60.9
SE0.30.50.30.30.2
CarbohydrateMean44.5 a44.1 a46.4 b46.4 b45.4<0.00010.5<0.00010.001
SE0.20.50.30.40.2
Saturated fatty acidsMean12.612.412.212.112.40.10.40.60.4
SE0.40.80.50.70.3
Monounsaturated fatty acidsMean11.911.811.912.111.90.50.60.60.1
SE0.40.70.50.60.3
n-3 Fatty acidsMean1.1 a1.0 b0.9 b1.0 b1.0<0.00010.0050.60.9
SE0.050.070.050.060.03
n-6 Fatty acidsMean4.94.84.74.84.80.20.30.61.0
SE0.190.310.190.250.11
Trans fatty acidsMean0.70.70.70.70.70.40.60.80.5
SE0.030.060.030.040.02
StarchMean26.2 a26.2 a,b25.0 b26.4 a25.90.0031.00.030.6
SE0.30.50.30.30.1
Non-milk extrinsic sugarsMean9.4 a9.2 a14.3 b13.3 b11.6<0.00010.6<0.0001<0.0001
SE0.20.30.20.30.2
Values sharing the same postscript or none are not significantly different (multiple comparison t-test with Bonferroni correction).

3.5. Micronutrient Intakes

Micronutrient intakes were mostly similar across beverage groups, although NC had lower mean sodium intake and higher vitamin A and D intakes compared with BB consumers (Table 6). LCB consumers had mean intakes intermediate between NC and SSB and not significantly different from either.
Table 6. Mean micronutrient intake and contrasts according to beverage consumption group.
Table 6. Mean micronutrient intake and contrasts according to beverage consumption group.
Micronutrient (per Day) Beverage Consumer GroupPlanned Contrasts
NCLCB SSB BBAllOverallLCB vs. nonLCB vs. SSBLCB vs. BB
n5982164763001590
Vitamin A (RE) (µg)Mean1344 a1119 a,b1012 b976 b,c1143<0.00010.040.30.2
SE5691405829
Thiamin (mg) Mean2.31.91.62.22.00.20.20.20.5
SE0.30.20.10.40.2
Riboflavin (mg) Mean2.21.81.82.12.00.30.070.90.3
SE0.20.10.10.30.1
Niacin equivalent (mg) Mean37.038.039.139.738.30.090.50.40.2
SE0.81.10.70.90.4
Vitamin B6 (mg) Mean2.82.62.63.22.80.20.40.90.1
SE0.20.10.10.40.1
Vitamin B12 (µg) Mean6.6 a5.7 a,b5.5 b5.7 a,b6.00.020.050.51.0
SE0.30.30.20.40.2
Folate (µg) Mean301.1287.4279.7300.8292.60.50.40.50.6
SE10.910.56.121.86.2
Vitamin C (mg) Mean106.699.0108.9101.2105.40.70.40.30.8
SE5.86.75.95.33.1
Vitamin D (µg) Mean4.4 a3.9 a,b3.2 b3.4 b,c3.8<0.00010.10.020.07
SE0.20.30.10.20.1
Vitamin E (mg) Mean12.510.511.410.911.60.50.080.40.7
SE1.00.60.91.00.5
Iron (mg) Mean11.811.512.211.611.90.70.70.30.9
SE0.30.50.60.30.2
Calcium (mg) Mean8248428518668420.30.50.80.4
SE132415209
Magnesium (mg) Mean2582562592542570.90.80.80.8
SE47452
Potassium (mg) Mean280628092775278627930.91.00.70.8
SE3671405122
Zinc (mg) Mean9.59.69.59.89.60.80.80.70.7
SE0.20.40.20.30.1
Selenium (µg) Mean51504849500.50.90.30.6
SE1.32.01.01.40.7
Iodine (µg) Mean180 a176 a,b173 a,b160 b1740.020.60.70.05
SE3.66.74.05.02.2
Sodium (mg) Mean2112 a2244 a,b2355 b2559 c2288<0.00010.060.1<0.0001
SE3262405022
Values sharing the same postscript or none are not significantly different (multiple comparison t-test with Bonferroni correction).

3.6. Energy Intake: Adjustment for Covariates

Lower energy intakes in LCB and NC (compared with SSB and BB consumers) remained significant after adjustment for sex, age group, ethnicity, BMI status, dieting, smoking, education, social class and income (Table 7). There were no significant interactions. Adjusted means for energy intake were 1620, 1604, 1794, 1846 kcal/day in NC, LCB, SSB and BB consumers, respectively, with a difference of 190 kcal between LCB consumers and SSB consumers (p < 0.001; Pairwise comparison test with Bonferroni correction).
Table 7. Regression model of beverages on total energy intake, adjusted for covariates.
Table 7. Regression model of beverages on total energy intake, adjusted for covariates.
ParameterBStd. ErrortSig.
Intercept15029316<0.0001
Non Consumer−22643−5<0.0001
Low Calorie Beverages−24152−5<0.0001
Sugar-Sweetened Beverages−5242−10.2
Both Beverages (ref)0
Males5152918<0.0001
Females (ref)0
Age 16–24 years95900.9
Age 25–44 years564810.2
Age 45–64 years224500.6
Age 65 + years (ref)0
BMI < 18.5 (underweight)9511010.4
BMI 18.5 < 25 (normal weight)583810.1
BMI 25 < 30 (overweight)183700.6
BMI 30+ (obese) (ref)0
Not dieting1214630.008
Dieting (ref)0
White ethnicity1614930.001
Non-white ethnicity (ref)0
Current smoker−9138−20.02
Ex-smoker103700.8
Non-smoker (ref)0...
Socioeconomic group 1 (highest)774820.1
Socioeconomic group 263800.9
Socioeconomic group 3164100.7
Socioeconomic group 4 (lowest) (ref)0
Household income 1 (lowest)−10154−20.06
Household income 2−4644−10.3
Household income 3−8541−20.04
Household income 4 (highest) (ref)0
Educational qualification (none)−11842−30.006
Educational qualification (any) (ref)0
Univariate GLM using weighted least squares. B (beta) coefficients are the difference in total energy intake associated with belonging to each group compared to the reference, after adjustment for all other factors in the model. There were no significant interactions. Adjusted difference between LCB and SSB = 190 kcal (SE 48) p = 0.001 with Bonferroni adjustment for multiple comparison.

3.7. Within- Person Analysis

Table 8 shows the coefficients estimating the impact of consuming 100 g of each beverage on total energy intake (7.1) energy from beverages (7.2) and food energy (7.3) if all other beverages and foods are allowed to vary (as they do in practice). Each 100 g of SSB was associated with an energy difference of +41 kcal (95% CI 33, 49); coefficients for other energetic beverages (milk, fruit juice, alcoholic beverages) ranged from +31 to +51 kcal. Consumption of LCB was not associated with any significant change in energy intake (0.6 kcal/100 g (p = 0.89), neither was the coefficient for tea, coffee and water significantly different from zero (−3 kcal/100 g; p = 0.073). By comparison the energy density of beverages (kcal/100 g based on total volume consumed) were as follows: LCB = 1; tea/coffee/water ≤1; SSB = 33; FJ = 37; milk = 52; alcoholic beverages = 48.
In Table 9, models 8.1, 8.2, 8.3 are substitution models of the effect on TEI, beverage energy and food energy, respectively, when replacing LCB with each of the other beverages, whilst keeping other beverage amounts constant. The coefficients can be compared with the true energy density of the beverages to estimate compensation, whether positive or negative. Consuming LCB instead of SSB (with other beverages constant) was associated with a 39 kcal reduction in total energy per 100 g substituted (8.1: TEI). In 8.2 (beverage energy) the coefficient for SSB (32 kcal/100 g) was similar to the actual energy density of all SSB consumed (33 kcal/100 g), suggesting weak or no compensation in beverage energy. 8.3 shows that food energy increased slightly by 7 kcal/100 g when consuming SSB instead of LCB (or food intake was 7 kcal lower when LCB was consumed); however this was not significant (p = 0.15).
This analysis suggests that LCB has no independent association with energy or food intake. Consuming more LCB on any one day does not appear to be associated with a lower energy intake that day. Strict 1:1 substitution of LCB in place of SSB could save an estimated 32 kcal/100 g (beverage energy model) assuming no change in intake of food or other beverages. This is equivalent to 106 kcal for a standard can of soda (330 g).
Table 8. Within-person regression models of the impact of each beverage on total energy, beverage energy and food energy intake (kcal).
Table 8. Within-person regression models of the impact of each beverage on total energy, beverage energy and food energy intake (kcal).
Model 7.1Model 7.2Model 7.3
Total EnergyBeverage EnergyFood Energy
ParameterBSEp ValueParameterBSEp ValueParameterBSEp Value
Low Calorie Beverages140.9Low Calorie Beverages−520.01Low Calorie Beverages640.1
Sugar-Sweetened Beverages414<0.0001Sugar-Sweetened Beverages282<0.0001Sugar-Sweetened Beverages143<0.0001
Tea/coffee/water−320.07Tea/coffee/water−91<0.0001Tea/coffee/water62<0.0001
Milk517<0.0001Milk393<0.0001Milk1160.05
Fruit juice317<0.0001Fruit juice213<0.0001Fruit juice1060.09
Alcoholic beverages371<0.0001Alcoholic beverages380<0.0001Alcoholic beverages−110.2
Combined results of separate models for each beverage. Coefficients (B) represent the simple (crude) effect of 100 g of beverage on energy intake (in kcals). Amounts of other beverages were allowed to vary. Models were adjusted for day of week and day number.
Table 9. Within-person regression models of the impact of substituting beverages for Low Calorie Beverages.
Table 9. Within-person regression models of the impact of substituting beverages for Low Calorie Beverages.
8.1. Total Energy8.2. Beverage Energy8.3. Food Energy
(Adjusted R Squared = 0.638)p Value(Adjusted R Squared = 0.980)p Value(Adjusted R Squared = 0.507)p Value
ParameterBSEParameterBSEParameterBSE
Intercept14402220.0001Intercept−89520.09Intercept15222150.0001
Low Calorie Beverages *- Low Calorie Beverages *- Low Calorie Beverages *-
Sugar-Sweetened Beverages3950.0001Sugar-Sweetened Beverages3210.0001Sugar-Sweetened Beverages750.2
Tea/coffee/water−940.03Tea/coffee/water−510.0001Tea/coffee/water−340.4
Milk5470.0001Milk5220.0001Milk370.7
Fruit juice3870.0001Fruit juice3320.0001Fruit juice570.5
Alcoholic beverages2440.0001Alcoholic beverages3510.0001Alcoholic beverages−1140.006
ALL BEVERAGES1640.0001ALL BEVERAGES510.0001ALL BEVERAGES1140.004
Friday67230.004Friday1350.02Friday54230.02
Saturday134240.0001Saturday2660Saturday108240.0001
Sunday39250.1Sunday160.9Sunday37240.1
Monday−18250.5Monday−360.6Monday−14240.5
Tuesday−3240.9Tuesday160.9Tuesday−4230.9
Wednesday (ref)0 Wednesday (ref)0 Wednesday (ref)0
Thursday19230.4Thursday−250.8Thursday20230.4
Day1−10160.5Day1−340.5Day1−8160.6
Day25160.8Day2041.00Day25150.8
Day316160.3Day3240.7Day315150.3
Day4 (ref)0 Day4 (ref)0 Day4 (ref)0
* Models show estimated caloric changes on consuming 100 g each beverage type instead of 100 g LCB whilst keeping total beverage intake constant (reverse sign applies for substituting LCB in place of each beverage).

4. Discussion

Our findings do not support the assertion that LCB negatively affect diet because adults who drink LCB compensate by eating more sugary or fatty foods [26,27]. Sugar intakes were lower among LCB consumers than SSB consumers owing mainly to the contribution from beverages in the SSB consumers, and there was no evidence of a reciprocal relationship with fat (or “sugar: fat see-saw”) [28] between LCB and SSB consumer groups; fat intakes were lower in LCB consumers on a g/day basis, and percentage energy from fat was not significantly different. Protein intakes (as a percentage of energy) were higher among LCB consumers than other groups, and the diets of NC and LCB consumers contained similar amounts of micronutrients for fewer calories than other groups. In all main respects (energy, macronutrient and micronutrient intakes), the diets of the LCB group were similar to those who consumed no soft drinks at all (NC), except that total fluid intakes were lower in NC. Consumption of fruit, vegetables and fish declined across the groups (NC > LCB > SSB >BB) with the reverse trend for meat; however not all differences were statistically significant. NC were significantly older than LCB and SSB consumers, while BB consumers were younger. Hence some of the observed differences may be age-related; for example older people are more likely to achieve recommendations for fruit and vegetable consumption [1].
Our conclusions are similar to those of Drewnowski and Rehm, who reported higher healthy eating index scores among users of low calorie sweeteners (LCS) and LCB compared with non-consumers, as well as healthier behaviours such as not smoking and taking more exercise [23]. The counter-intuitive observation in both studies that LCB users are more likely to be overweight despite a lower reported EI than non-users is most likely attributable to reverse causality [29]. Unlike Drewnowski and Rehm we did not find LCB consumers to have higher intakes of saturated fat and sodium. Methodological differences between our studies may explain this: LCB users may include some participants who consumed SSB in addition to LCB (our BB group), and LCB non-users may include those who consume neither LCB nor soft drinks (our NC group), whereas our classification discriminated on both classes of beverage.
Findings contrast with those of Piernas et al. who reported that overall diet quality was lower in LCB-only consumers as well as in SSB consumers, compared with non/low consumers [30] and also that purchases of either LCB or SSB were associated with more energy from food, more sugar and fat and more desserts [27]. An acknowledged limitation of purchase studies is the indirect measure of consumption and omission of unpackaged foods and out-of-home eating occasions. Furthermore, stronger evidence (from the CHOICE randomised control trial) indicated that those who replaced caloric drinks with either LCB or water also reduced their consumption of added sugar and desserts, with the LCB group sustaining a larger reduction in desserts than the water group [31].
Our within-person results show some similarities with other studies using multiple records in American populations. Wang et al. reported no significant association between LCB intake and total energy in children when LCB was added to the diet [32]. In models replacing SSB they only found a significant energy reduction with plain water and not LCB, however low numbers of children consuming diet drinks may have limited the statistical power. Stookey et al., in a study of 118 overweight women followed up for 12 months, reported that replacing SSBs by LCBs was associated with a reduction in energy intake but this was 30% smaller than if replaced by water [33]. Finally in a recent study using within-person data (2 days) from NHANES, consuming SSB was associated with an energy increment of 226 kcal/day, compared with 69 kcal associated with LCB (net difference of 157 kcal/day) [34]. Although there was a small increase in food calories this did not negate the energy saving associated with consuming LCB instead of SSB. From within-person analysis of NDNS, we found that substitution of SSB by LCB or by water/tea/coffee was associated with a reduction in total energy, and this was attributable to lower energy from beverages, with no evidence of increased food energy.

Strengths and Limitations of the Present Study

Most work on the effects of beverages on intakes and on health focuses on the adverse impacts of SSB, while less has addressed potential benefits of LCB. A major strength of this study is the NDNS data, which is nationally representative of the UK and of high quality. The 4-day diary provides a better representation of usual consumption than the more common 24-h dietary recall. Four days of records also allowed us to estimate the impact of dietary change on energy intake whilst controlling for inter-personal differences.
Causality cannot be inferred from the associations found in this analysis due to its cross-sectional design. However, the results are consistent with other data suggesting that beverages tend to supplement food choices in an independent manner, so that the benefit of LCB in terms of energy and sugars intake derives from substitution of SSB. Misreporting is a known weakness of self–reported diet records [35] and unfortunately there is no reliable means of correcting for this or reliably identifying individuals who misreport [36]. However, our conclusions regarding lower NMES intakes are based on energy-adjusted values, less susceptible to misreporting effects [37,38]. In energy intake regressions we included an adjustment for dieting, smoking, BMI and other covariates often associated with energy intake or underreporting, although residual confounding can never be ruled out. The within-person analysis further reduces distortions caused by mis-reporting because individuals tend to be consistent in this regard [39].

5. Conclusions

LCB provide a palatable source of water with minimal sugar and energy content. Their caloric benefits derive from their role as substitutes for SSB and meta-analyses have demonstrated that replacing SSB with LCB leads to reduced energy intake and modest weight loss [18]. Maintaining good diet quality during weight loss is important in order to meet nutrient requirements at a lower energy intake. In UK adults we found that LCB consumers and NC consumed less energy and sugars than consumers of SSB, or both types. NC and LCB consumers tended to have higher quality diets compared with SSB and BB consumers and did not compensate for the sugar or energy deficit by consuming more sugary foods.

Acknowledgments

UNESDA Soft Drink Europe, Rue du Trone 14-16 B-1000 Brussels, Belgium.

Author Contributions

S.G. designed the project; S.G., L.F. and A.G. performed data extraction, analysis and literature searches, G.H. provided statistical advice; S.G. wrote the manuscript with input from A.S. and G.H. S.G. holds primary responsibility for the paper. All authors approved the final version.

Conflicts of Interest

S.G. is director of Sig-Nurture Ltd, an independent consultancy, which has received research funding from food and beverage and ingredient companies, not-for-profit organisations and trade bodies. None of the other authors had a conflict of interest. The sponsors had no role in the design, analysis or interpretation of the study, or in the preparation of the manuscript. The NDNS data creators, depositors, copyright holder and the UK Data Archive bear no responsibility for further analysis or interpretation of datasets.

References

  1. Bates, B.; Lennox, A.; Prentice, A.; Bates, C.; Page, P.; Nicholson, S.; Swan, G. National Diet and Nutrition Survey: Results from Years 1 to 4 (Combined) of the Rolling Programme for 2008 and 2009 to 2011 and 2012. Available online: https://www.gov.uk/government/statistics/national-diet-and-nutrition-survey-results-from-years-1-to-4-combined-of-the-rolling-programme-for-2008-and-2009-to-2011-and-2012 (accessed on 16 December 2015).
  2. UNESDA Soft Drinks Europe. Consumption. Available online: http://www.unesda.eu/products-ingredients/consumption/ (accessed on 16 December 2015).
  3. Gibson, S.; Gunn, P.; Maughan, R.J. Hydration, water intake and beverage consumption habits among adults. Nutr. Bull. 2012, 37, 182–192. [Google Scholar] [CrossRef]
  4. Piernas, C.; Ng, S.W.; Popkin, B. Trends in purchases and intake of foods and beverages containing caloric and low-calorie sweeteners over the last decade in the united states. Pediatr. Obes. 2013, 8, 294–306. [Google Scholar] [CrossRef] [PubMed]
  5. Ventura, A.K.; Mennella, J.A. Innate and learned preferences for sweet taste during childhood. Curr. Opin. Clin. Nutr. Metab. Care 2011, 14, 379–384. [Google Scholar] [CrossRef] [PubMed]
  6. Bellisle, F.; Drewnowski, A. Intense sweeteners, energy intake and the control of body weight. Eur. J. Clin. Nutr. 2007, 61, 691–700. [Google Scholar] [CrossRef] [PubMed]
  7. Allison, D.B. Liquid calories, energy compensation and weight: What we know and what we still need to learn. Br. J. Nutr. 2014, 111, 384–386. [Google Scholar] [CrossRef] [PubMed]
  8. De la Hunty, A.; Gibson, S.; Ashwell, M. A review of the effectiveness of aspartame in helping with weight control. Nutr. Bull. 2006, 31, 115–128. [Google Scholar] [CrossRef]
  9. Mattes, R.D.; Popkin, B.M. Nonnutritive sweetener consumption in humans: Effects on appetite and food intake and their putative mechanisms. Am. J. Clin. Nutr. 2009, 89, 1–14. [Google Scholar] [CrossRef] [PubMed]
  10. Tate, D.F.; Turner-McGrievy, G.; Lyons, E.; Stevens, J.; Erickson, K.; Polzien, K.; Diamond, M.; Wang, X.; Popkin, B. Replacing caloric beverages with water or diet beverages for weight loss in adults: Main results of the choose healthy options consciously everyday (choice) randomized clinical trial. Am. J. Clin. Nutr. 2012, 95, 555–563. [Google Scholar] [CrossRef] [PubMed]
  11. Malik, V.S.; Pan, A.; Willett, W.C.; Hu, F.B. Sugar-sweetened beverages and weight gain in children and adults: A systematic review and meta-analysis. Am. J. Clin. Nutr. 2013, 98, 1084–1102. [Google Scholar] [CrossRef] [PubMed]
  12. Ebbeling, C.B. Sugar-sweetened beverages and body weight. Curr. Opin. Lipidol. 2014, 25, 1–7. [Google Scholar] [CrossRef] [PubMed]
  13. Miller, P.; Perez, V. Low-calorie sweeteners and body weight and composition: A meta-analysis of randomized controlled trials and prospective cohorts. Am. J. Clin. Nutr. 2014, 100, 765–777. [Google Scholar] [CrossRef] [PubMed]
  14. Kaiser, K.A.; Shikany, J.M.; Keating, K.D.; Allison, D.B. Will reducing sugar-sweetened beverage consumption reduce obesity? Evidence supporting conjecture is strong, but evidence when testing effect is weak. Obes. Rev. Off. J. Int. Assoc. Study Obes. 2013, 14, 620–633. [Google Scholar] [CrossRef] [PubMed]
  15. Ebbeling, C.B.; Feldman, H.A.; Chomitz, V.R.; Antonelli, T.A.; Gortmaker, S.L.; Osganian, S.K.; Ludwig, D.S. A randomized trial of sugar-sweetened beverages and adolescent body weight. New Engl. J. Med. 2012, 367, 1407–1416. [Google Scholar] [CrossRef] [PubMed]
  16. de Ruyter, J.C.; Katan, M.B.; Kuijper, L.D.; Liem, D.G.; Olthof, M.R. The effect of sugar-free versus sugar-sweetened beverages on satiety, liking and wanting: An 18 month randomized double-blind trial in children. PLoS ONE 2013, 8, e78039. [Google Scholar] [CrossRef] [PubMed]
  17. Peters, J.C.; Wyatt, H.R.; Foster, G.D.; Pan, Z.; Wojtanowski, A.C.; Vander Veur, S.S.; Herring, S.J.; Brill, C.; Hill, J.O. The effects of water and non-nutritive sweetened beverages on weight loss during a 12-week weight loss treatment program. Obesity 2014, 22, 1415–1421. [Google Scholar] [CrossRef] [PubMed]
  18. Rogers, P.J.; Hogenkamp, P.S.; de Graaf, K.; Higgs, S.; Lluch, A.; Ness, A.R.; Penfold, C.; Perry, R.; Putz, P.; Yeomans, M.R.; et al. Does low-energy sweetener consumption affect energy intake and body weight? A systematic review, including meta-analyses, of the evidence from human and animal studies. Int. J. Obes. 2015. [Google Scholar] [CrossRef] [PubMed]
  19. Scientific Advisory Committee on Nutrition (SACN). Carbohydrates and Health. Available online: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/445503/SACN_Carbohydrates_and_Health.pdf (accessed on 16 December 2015).
  20. USDA. Scientific Report of the 2015 Dietary Guidelines Advisory Committee. Available online: http://health.Gov/dietaryguidelines/2015-scientific-report/ (accessed on 16 December 2015).
  21. Gardner, C.; Wylie-Rosett, J.; Gidding, S.S.; Steffen, L.M.; Johnson, R.K.; Reader, D.; Lichtenstein, A.H. Nonnutritive sweeteners: Current use and health perspectives: A scientific statement from the american heart association and the american diabetes association. Diabetes Care 2012, 35, 1798–1808. [Google Scholar] [CrossRef] [PubMed]
  22. Anderson, G.H.; Foreyt, J.; Sigman-Grant, M.; Allison, D.B. The use of low-calorie sweeteners by adults: Impact on weight management. J. Nutr. 2012, 142, 1163S–1169S. [Google Scholar] [CrossRef] [PubMed]
  23. Drewnowski, A.; Rehm, C.D. Consumption of low-calorie sweeteners among U.S. adults is associated with higher healthy eating index (HEI 2005) scores and more physical activity. Nutrients 2014, 6, 4389–4403. [Google Scholar] [CrossRef] [PubMed]
  24. NatCen Social Research, MRC Human Nutrition Research and University College London Medical School. National Diet and Nutrition Survey Years 1–4, 2008/09–2011/12. Available online: http://dx.Doi.Org/10.5255/ukda-sn-6533-3 (accessed on 16 December 2015).
  25. Fitt, E.; Cole, D.; Ziauddeen, N.; Pell, D.; Stickley, E.; Harvey, A.; Stephen, A.M. Dino (diet in nutrients out) —An integrated dietary assessment system. Public Health Nutr. 2015, 18, 234–241. [Google Scholar] [CrossRef] [PubMed]
  26. Bleich, S.N.; Wolfson, J.A.; Vine, S.; Wang, Y.C. Diet-beverage consumption and caloric intake among us adults, overall and by body weight. Am. J. Public Health 2014, 104, e72–e78. [Google Scholar] [CrossRef] [PubMed]
  27. Piernas, C.; Ng, S.W.; Mendez, M.A.; Gordon-Larsen, P.; Popkin, B.M. A dynamic panel model of the associations of sweetened beverage purchases with dietary quality and food-purchasing patterns. Am. J. Epidemiol. 2015, 181, 661–671. [Google Scholar] [CrossRef] [PubMed]
  28. Sadler, M.J.; McNulty, H.; Gibson, S. Sugar-fat seesaw: A systematic review of the evidence. Crit. Rev. Food Sci. Nutr. 2015, 55, 338–356. [Google Scholar] [CrossRef] [PubMed]
  29. Drewnowski, A. Dietary habits and use of low-calorie sweetners: An effective tool in the prevention of obesity and diabetes. Ann. Nutr. Metab. 2013, 63, 147–148. [Google Scholar]
  30. Piernas, C.; Mendez, M.A.; Ng, S.W.; Gordon-Larsen, P.; Popkin, B.M. Low-calorie- and calorie-sweetened beverages: Diet quality, food intake, and purchase patterns of us household consumers. Am. J. Clin. Nutr. 2014, 99, 567–577. [Google Scholar] [CrossRef] [PubMed]
  31. Piernas, C.; Tate, D.F.; Wang, X.; Popkin, B.M. Does diet-beverage intake affect dietary consumption patterns? Results from the choose healthy options consciously everyday (choice) randomized clinical trial. Am. J. Clin. Nutr. 2013, 97, 604–611. [Google Scholar] [CrossRef] [PubMed]
  32. Wang, Y.C.; Ludwig, D.S.; Sonneville, K.; Gortmaker, S.L. Impact of change in sweetened caloric beverage consumption on energy intake among children and adolescents. Arch. Pediatr. Adolesc. Med. 2009, 163, 336–343. [Google Scholar] [CrossRef] [PubMed]
  33. Stookey, J.D.; Constant, F.; Gardner, C.D.; Popkin, B.M. Replacing sweetened caloric beverages with drinking water is associated with lower energy intake. Obesity 2007, 15, 3013–3022. [Google Scholar] [CrossRef] [PubMed]
  34. An, R. Beverage consumption in relation to discretionary food intake and diet quality among us adults, 2003 to 2012. J. Acad. Nutr. Dietetics 2015. [Google Scholar] [CrossRef] [PubMed]
  35. Stubbs, R.J.; O'Reilly, L.M.; Whybrow, S.; Fuller, Z.; Johnstone, A.M.; Livingstone, M.B.; Ritz, P.; Horgan, G.W. Measuring the difference between actual and reported food intakes in the context of energy balance under laboratory conditions. Br. J. Nutr. 2014, 111, 2032–2043. [Google Scholar] [CrossRef] [PubMed]
  36. Black, A.E. Critical evaluation of energy intake using the goldberg cut-off for energy intake: Basal metabolic rate. A practical guide to its calculation, use and limitations. Int. J. Obes. Relat. Metab. Disord. J. Int. Assoc. Study Obes. 2000, 24, 1119–1130. [Google Scholar] [CrossRef]
  37. Hirvonen, T.; Mannisto, S.; Roos, E.; Pietinen, P. Increasing prevalence of underreporting does not necessarily distort dietary surveys. Eur. J. Clin. Nutr. 1997, 51, 297–301. [Google Scholar] [CrossRef] [PubMed]
  38. Voss, S.; Kroke, A.; Klipstein-Grobusch, K.; Boeing, H. Is macronutrient composition of dietary intake data affected by underreporting? Results from the epic-potsdam study. European prospective investigation into cancer and nutrition. Eur. J. Clin. Nutr. 1998, 52, 119–126. [Google Scholar] [CrossRef] [PubMed]
  39. Black, A.E.; Cole, T.J. Biased over- or under-reporting is characteristic of individuals whether over time or by different assessment methods. J. Am. Dietet. Assoc. 2001, 101, 70–80. [Google Scholar] [CrossRef]
Back to TopTop