Ainsdale-on-Sea Nutrition Study: The effect of a strictly plant-based diet on measures of adiposity.

Updated: Feb 7



Abstract


Background and aims: To determine the effect of a strictly plant-based vegan diet on measures of adiposity.


Methods: Participants were assigned to a vegan diet for two weeks after first completing a two-day electronic food diary which served as a control and attended two meetings; pre- and post-intervention to provide measurements of weight and waist circumference.

Results: Overweight adults (body mass index 25-39 kg/m2; aged 18-65 years with no medical conditions) were assigned to a vegan diet which emphasised the inclusion of whole plant foods naturally low in fat. Twelve (70%) participants completed the study. At two weeks weight loss was significant compared to the control (-2.6 ± 1.3kg, P=<0.01), as was the reduction in body mass index (-0.8 ± 0.4 kg/m2 P=<0.01), waist circumference (89.4 ± 26.4cm; 84.8 ± 27.9cm, P=<0.01) and waist to height ratio (-0.02 ± 0.01, P=<0.01). A significant decrease in intake of cholesterol, protein and calcium was observed following the intervention diet, compared to control, whilst Intake of dietary fibre increased significantly.


Conclusions: Vegan diets may produce significant reduction in proxies of adiposity over a two-week period.



Introduction


A well-planned vegan diet can “support healthy living in people of all ages” (British Dietetics Association, 2017), and is associated with multiple health benefits, including a significant reduction in risk factors of chronic diseases and incidence and mortality from cardiovascular disease and cancer (Dinu, Abbate, Gensini, Casini, & Sofi, 2016). Plant-based diets have been consistently shown in observational and intervention trials to be effective in promoting and maintaining weight loss (Dreher, 2018). Plant-based diets exist on a continuum running from the most plant-based to the least; vegan>vegetarian>pesco-vegetarian>semi-vegetarian to an omnivorous diet. The link between these dietary patterns and body weight has been investigated in many studies, finding lower body mass (Tonstad et al., 2013) and lower weight gain (Rosell, Appleby, Spencer, & Key, 2006) over time amongst vegans compared to other dietary groups (Turner-McGrievy, Davidson, Wingard, Wilcox, & Frongillo, 2015). Overweight and obesity are typically assessed using body mass index, despite other measures such as waist circumference (WC) and waist to height ratio (WHtR) being shown as superior in assessing central weight, which is a better indicator of associated health risks. To date, no study has sought to investigate the effect of a vegan diet on WHtR. Therefore, the aim of this study was to determine the usefulness of a vegan diet on not only weight loss, body mass index (BMI) and WC, but WHtR.



Methods

Overweight individuals (BMI = 25-39 kg/m2) interested in reducing waist circumference and adipose tissue, were recruited from the Southport (Merseyside, UK) area, through poster advertisements in local businesses (primarily the local gym and hairdressers). To be eligible, participants were non-vegan, aged between 18-65, with a BMI >25 (kg/m2), a stable medical status, no changes to activity within 3 months and a willingness to try a plant-based vegan diet. Eligible participants were invited via email to attend a consultation to receive information about the study, provide written consent, height, weight, WC measurements and receive information about the diet. Prior to commencement, participants were invited to complete a two-day electronic food diary (one weekday and one weekend day) using the application Libro (Nutritics v5.031). This two-day pre-intervention period (omnivorous period) was used as a control. Weight was measured in light street clothing, without shoes using a calibrated digital scale (Salter 9018) accurate to 0.1kg. Height measured using a stadiometer (Seca 206), without shoes or hats. A non-stretch tape measure (Konetun AK2068) was used to assess WC, taken mid-way between the top of the hips and the lower ribs.


After baseline measurements, participants were assigned to a strictly plant-based diet for a minimum of two weeks with the option to continue for a further two weeks. Participants were given handouts providing details on the vegan diet, outlining foods to be included and others to be avoided, with information on low-fat cooking, meal ideas, recipes, sample shopping lists and links to relevant online resources. Participants were invited to a private Facebook group providing social support and a platform to share ideas and request advice. Self-monitoring and calorie restriction was not required nor emphasised; participants were free to eat at a frequency and amount of their own choosing, provided they adhere to the plant-based diet (PBD). All participants were encouraged to limit processed food and not to change alcohol or physical activity levels (PAL) during the intervention. Adherence was assessed by unannounced 24-hour dietary recall (one weekday and one weekend day) each fortnight. Adherence was measured as absence of prohibited foods (meat, dairy, eggs), recorded via the Nutritics (v5.031) application Libro.



Intervention diet

Participants were instructed to follow guidelines provided in a handout that detailed foods to try to include in their daily diet and foods that must be avoided (Table 1). Instructions to minimise processed or refined foods with added salt, oil or sugar, and advice on how to cook without oil were also provided. The handout also provided plant-based swaps or substitutes for commonly used animal ingredients, a sample meal plan and a shopping list. As well as information on the risk of deficiencies of key nutrients following a PBD, and a list of plant sources rich in the nutrients concerned. There was no recommended energy restriction, nor any limit placed on plant-foods; even high fat, energy dense foods like nuts, nut butters and avocados.


Table 1 Definitions of the intervention diet and example meals compared to control



Statistical analysis

The study sample size, 12, was powered to detect differences of 5% or greater for contrasts between two groups. Participant attrition was defined as the failure to provide body measurements at two weeks. Continuous variables were tested for normality using the Shapiro-Wilk method. Changes in parametric variables from baseline to two weeks were analysed using multiple paired t-tests to explore the effect of a PBD. Non-parametric variables were analysed using a Wilcoxon Signed Ranks Test. Data are presented as the means with standard deviations for normally distributed variables, and as medians with ranges for non-normally distributed variables. Missing data for body measurements at two weeks was excluded from analysis. All analyses were conducted using SPSS 24.0 for Windows software with a p value of 0.05 used to indicate statistically significant differences.



Results

Participants were screened in June 2018 with the trial completed through July 2018 in Ainsdale-on-sea. Of the 23 participants screened, 22 were eligible, with 17 attending the first meeting to provide baseline data and receive guidance on the plant-based vegan diet. Of the 17 participants assigned to the PBD 12 (70%) completed the study; responded to two 24-hour recall requests and provided body measurements at two weeks.


Weight loss

All participants lost weight following the intervention (Figure 1.1). The mean weight loss observed between participant weight at baseline and at day 14 following a PBD was significant (-2.6 ± 1.3kg, P=<0.01).


Body mass index

All participants exhibited a reduction in BMI (Figure 1.2), with a significant reduction in mean BMI following the two-week intervention (-0.8 ± 0.4 kg/m2, P=<0.01). With 3 participants being able to transition from the overweight range (25-29.9 kg/m2) to the healthy weight range (18.5-24.9 kg/m2) (Table 2).


Table 2 Classifications of BMI ranges according to National Institute for Health and Care Excellence guidlelines (NICE, 2014)


Waist circumference

All participants experienced a reduction in WC (Figure 1.3). The reduction in WC was significant between median WC preintervention (89.4 ± 26.4cm) and post intervention (84.8 ± 27.9cm, P=<0.01).


Waist to height ratio

All participants exhibited a reduction in WHtR (Figure 1.4) with a significant reduction in mean WHtR at 14 days compared to baseline (-0.02 ± 0.01cm/cm, P=<0.01). With 3 of the participants transitioning from an at risk (>0.50) ratio to a no increase risk ratio (<0.50).



Figure 1.1 Weight loss of participants pre- and post-intervention

Figure 1.1 Weight loss for each participant between baseline (day 0) and follow-up (day 14).



Figure 1.2 Body mass index of participants pre- and post-intervention

Figure 1.2 Changes in BMI for each participant between baseline (day 0) and follow-up (day 14).


Figure 1.3 Waist circumference of participants pre- and post-intervention

Figure 1.3 Changes in WC for each participant between baseline (day 0) and follow-up (day 14).


Figure 1.4 Waist to height ratio of participants pre- and post-intervention

Figure 1.4 Changes in WHtR for each participant between baseline (day 0) and follow-up (day 14).


Dietary intake

The data presented in Table 3 represents changes in average dietary intake between control and the vegan diet. The median energy intake of participants decreased (1724 ± 3030kcal pre-intervention, 1507 ± 1606kcal post-intervention, P=0,13), though not significantly. Participants intake of fibre increased significantly on the vegan diet (+12 ± 8g, P=<0.01). Increases in carbohydrate (CHO) vitamin A and vitamin C were observed; though increases were not significant. Dietary intake of protein, cholesterol, calcium and B12 decreased significantly. Intake of fat, saturated fat, iron and zinc decreased, though the decreases were not significant.



Table 3 Changes in intake of macronutrients, fibre, saturated fat, cholesterol, vitamins and minerals of intervention compared to control

1 Data expressed as mean ± SD 2 Data expressed as median ± range a Significant difference between control and intervention



Discussion

Changes in measures of adiposity

In assessing the subjects body composition, alternate measurements that serve as a proxy for body fat were employed, given the inaccessibility of Dual-energy X-ray absorptiometry (DEXA), considered the gold standard of body composition assessment (Madden & Smith, 2016). Body mass index is superior to weight alone as it incorporates height, describing the relationship between weight and stature (Madden & Smith, 2016). As BMI increases, there is a corresponding increase in risk of mortality, cardiovascular disease and certain cancers (Madden & Smith, 2016). Three of the participants (25%) were able to reduce their weight to within a healthy weight range for their height as determined by BMI, which may reduce their risk of diseases associated with overweight and obesity (OWO).


As BMI is calculated using body weight, it fails to discriminate between various compartments (muscle, fat etc); tall and muscular individuals are not differentiated from those with greater amounts of adipose tissue. The BMI is also unable to describe where the fat is distributed; a major limitation given there is now good evidence that central obesity carries more health risks compared with total obesity assessed by BMI (Ashwell & Gibson, 2016).


To overcome these limitations of BMI, yet still considering the entire body, other indices have been developed. The World Health Organization guidelines (WHO,2008) state that alternative measures that reflect abdominal obesity, such as WC, waist-to-hip ratio (WHR), and WHtR have been found to be superior to BMI. Waist circumference acts as an indicator of central adiposity and has been shown to be a good predictor of cardiometabolic morbidity and mortality (Madden & Smith, 2016). Whilst WC may be a superior measure compared with BMI, WHtR may be a more effective form of measurement. A recent meta-analysis of studies which sought to assess the usefulness of indices of adiposity found WHtR to be a, “better predictor of diabetes, hypertension, dyslipidaemia, metabolic syndrome and other cardiovascular outcome measures than BMI or WC in both men and women” (Ashwell & Gibson, 2016, p1.). Using a boundary of 0.5 for WHtR may be a simpler and more predictive indicator of the health risks associated with central obesity (Ashwell & Gibson, 2016). Three of the participants (25%) successfully reduced their WHtR below the 0.5 boundary which may have reduced their risk of developing diseases associated with a WHtR of greater than 0.5.


Despite being a useful indicator of adiposity and low technical error, WHR measurements were rejected in this study given the intimacy of the measurements. The use of skin fold callipers for measurement of subcutaneous fat were rejected given that the technique is more useful in the assessment of lean individuals (Madden & Smith, 2016).



The weight loss and reduction in all measures of adiposity in this study were produced without the need for dietary self-monitoring. Whilst self-monitoring is seen as an integral part of behavioural interventions for weight loss (Burke, Wang, & Sevick, 2011) the daily recording of all food and drink consumed is tedious, time-consuming and places a high burden on participants (Pendergast, Ridgers, Worsley, & McNaughton, 2017). This burden can impact adherence; which may decrease overtime (Burke et al., 2011), emphasising the importance and need for dietary strategies which do not necessitate daily self-monitoring, yet yield effective reductions in adiposity. The mean weight loss of participants at two-weeks (3.2% decrease in body weight) is significant and is approaching the 5% weight loss which has been shown to lower the risk of chronic disease (Turner-McGrievy, Mandes, & Crimarco, 2017).


The reduction in weight and waist circumference occurred without the need for calorie or carbohydrate restriction, allowing participants to eat to satiation and making the diet more appealing; high adherence (70%). Avoiding the need to track calories, record intake or restrict portions, makes this dietary approach less burdensome and easier to adhere to. Adherence to a vegan diet has been shown not to differ when compared with vegetarian, pescatarian, semi-vegetarian or an omnivorous diet (Moore, McGrievy, & Turner-McGrievy, 2015; Turner-McGrievy, Davidson, Wingard, Wilcox & Frongillo, 2015), suggesting that no one dietary pattern is easier for participants to follow.

Traditional weight loss dietary interventions tend to focus on energy-restriction, with adherence and frequency of self-reporting being positively correlated with successful weight reduction (Burke et al.,2011). This does not appear to be the case with the recommendation of plant-based diets, where even non-adherent participants experience greater weight loss compared to other less plant-based non-adherent groups (Moore et al., 2015).


The rapidity of the initial weight loss could be an important determinant of long term weight loss, with the enthusiasm and motivation garnered by early results being shown to be predictive of successful weight loss long term (Hadžiabdić et al., 2015). This early motivation may encourage dietary adherence and contribute to greater and continued weight loss, or less weight gain over time.


Weight regain is a common and persistent obstacle to weight loss, with as many as 80% of OWO individuals who lose weight, returning to or exceeding their original weight (Dreher, 2018). Future research is needed to explore the effectiveness of vegan diets to maintain weight loss beyond two weeks.



Dietary intake

The vegan diet led to favourable changes in macronutrient, fibre and cholesterol intake, consistent with the findings of other PBD interventions which also noted that the more plant-based the diet, the greater the favourable changes in dietary intake (Turner-McGrievy et al., 2015). The reduction in dietary factors known to cause disease such as saturated fat and cholesterol suggest PBDs may be of use in the treatment and prevention of obesity and its associated chronic diseases. These findings mirror those of many epidemiological studies which consistently show higher intakes of dietary fibre (Harland & Garton, 2016) and lower saturated fat intake (Farmer, 2014) of PBDs (compared to non-PBDs). This may be a major determinant in dietary quality and explain why vegan and vegetarian diets are higher in quality compared to omnivorous diets (Turner-McGrievy et al., 2008; 2015).


Whilst vegan diets contain virtually no B12, clinical symptoms are surprisingly uncommon (Mann & Truswell, 2017). Body stores of B12 are sufficient to last for 2-5 years, with some being produced by bacteria in the intestine; though bioavailability in uncertain (Mann & Truswell, 2017). Long term consumption of a vegan diet would necessitate the inclusion of a B12 supplement or consumption of B12 fortified foods (milk/meat substitutes and B12–fortified nutritional yeast).


The decrease in protein intake seen from the omnivorous to vegan diet (-28 ± 31g, P= <0.01) could have contributed to the observed weight loss, through a decrease in lean mass. The present study fails to address which compartments (adipose tissue or other) the weight loss stems from. Future studies to examine the effect of PBDs on body composition are needed.



Adopting a plant-based diet could increase the risk of calcium deficiency, given that many western countries obtain a substantial amount of total daily calcium intake from dairy products (Mann & Truswell, 2017). Both protein and calcium are key nutrients in the development and maintenance of bone (Burckhardt, 2016). The lower intakes of protein and calcium associated with a vegan diet may increase the risk of lower bone mineral density (BMD), and increased risk of fracture. A meta-analysis of nine studies by Ho-Pham, N. Nguyen and T. Nguyen (2009), demonstrated that the BMD at the femoral neck and lumbar spine, was lower in vegetarians and vegans than in omnivores. Vegans diets are however, higher in other nutrients that promote bone health compared to omnivores; magnesium, potassium, vitamin K, antioxidants, vitamins C and E and phytonutrients (Mangano & Tucker, 2017). With additional benefits to bone health arising from the alkalising effect of plant foods, which have been shown in cross-sectional and intervention trials to decrease bone resorption (Burckhardt, 2016). To decrease the risk of low BMD and fracture risk, vegans must ensure adequate consumption of protein and calcium. Plant sources of calcium from green vegetables (spinach, broccoli, peas, cabbage), legumes, nuts (almonds, walnuts), and dried figs and calcium-fortified foods, such as cereals, soy milk and tofu is essential.


Despite the non-haem iron in plants being less bioavailable than the haem iron found in meat, risk of iron deficiency is similar for plant-based individuals and omnivores (Craig, 2009). Which may result from the increased consumption of vitamin C in plant-based diets, which greatly boosts non-haem iron absorption. A well-planned vegan diet will avoid iron deficiency through inclusion of plant foods with relatively high bioavailability of non-haem iron; beetroot, broccoli, pumpkin, citrus and tomatoes.


Plant-based diets are high in phytates; a component of cereal grains, nuts and legumes which bind zinc and reduce its bioavailability (Mann & Truswell, 2017). Whilst vegans have a lower zinc intake than omnivores, they do not exhibit lower immunocompetence (Craig, 2009). To avoid deficiency, consumption of plant-based sources of zinc; pumpkin seeds, dark chocolate, garlic and chickpeas is required.


The insignificant increase in some vitamins and insignificant decrease in minerals iron and zinc seen in this study may be explained by participants reliance on processed foods, which are typically fortified with minerals but contain fewer vitamins (Carlsen et al., 2010). This may also in part be explained by the electronic food diaries being completed over a Friday-Saturday, the end of the week may lead to more hedonistic behaviours, or a disrupted routine affecting dietary intake. The improvements in proxies of adiposity seen in this study are consistent with the improvements in other metrics of health, as evidenced in studies which assessed PBDs and CVD, T2D, cancer incidence and all-cause mortality (Dinu et al., 2016).


Dietary assessment

In nutritional epidemiology, several methods exist for the assessment of dietary intake, each with inherent strengths and weaknesses (Table 4). Commonly used methods include real-time recording (food diaries) and methods of recall (food frequency questionnaires (FFQs) and 24-hour dietary recalls (24HR)) (Naska, Lagiou & Lagiou, 2017; Pendergast et al., 2017).



Table 4. Overview of dietary assessment methods


The two methods most prevalent in the scientific literature are FFQs and 24HR (Naska et al., 2017). Typically, these methods are used to describe the dietary intake of groups and not individuals (Fuller, Fong, Gerofi, Ferkh, Leung, Leung, & Caterson, 2017), with both FFQs and 24HR being prone to recall bias, given reported intake is collected retrospectively.


Food diaries use household measures to estimate the amount of food consumed, whilst weighed food diaries require each item of food to be weighed. A 7-day weighed food diary was initially considered the gold standard method of dietary intake measurement. This has been superseded by the dawn of food biomarkers, which demonstrated weighed food records over 7 days have a higher rate of under-reporting because of responder burden, and a positive correlation between under-reporting and an increase in BMI (Fuller et al., 2017). These limitations are further compounded by the high participant and researcher burden associated with weighed food diaries (Pendergast et al., 2017).

Electronic food diaries have been shown to be both an efficient and valid mode to collect data, whilst increasing dietary compliance of participants in weight-loss programmes (Fuller et al., 2017). A study by Sharp & Allman-Farinelli (2014) sought to assess the validity and feasibility of electronic food diaries compared to traditional methods (including 24HR and written food diaries), finding similar, but not superior validity between electronic and conventional assessment methods. Also noting, that participants consistently preferred electronic dietary assessment methods, compared to conventional methods. An 8-week weight loss trial by Wharton, Johnston, Cunningham and Sterner (2014), showed that the use of smart phone applications can improve dietary self-reporting.



The use of the electronic food diary Nutritics, collected via the application Libro was selected to avoid the recall bias inherent to FFQs and 24HR. The mobile application allowed food intake to be recorded in real time, improving accuracy, reducing the burden to the participant and minimising recall bias. The lack of the requirement to weigh all food, further minimised participant burden, with the Nutritics software containing visual cues to help estimate food quantity. A two-day food diary, rather than seven-day diary was used; again, to minimise the burden to the participant, reducing the likelihood that data quality would be jeopardised. Whilst all self-reported dietary assessment methods are vulnerable to misreporting, multiple 24HRs and multiple day food diaries have been shown to outperform FFQ in providing estimates for absolute dietary intake (Park et al., 2018).


Strengths and Limitations

Strengths of the present study include the low burden for both researcher and participants with minimal contact; meeting only twice with support provided via a private Facebook group and email. The minimal contact paired with participants use of guidelines to select and prepare their own meals makes the findings particularly relevant to a real-world setting. The use of a two-day electronic food diary allowed real time accounting of all foods and drinks with visual cues to enable portion size estimation; reducing the need to weigh food. The vegan intervention dietary data was collected using two unannounced 24HR recalls, which are considered an accurate measure of absolute dietary intake (Park et al., 2018). The attrition rate of the study (30%) may be considered low, given that no incentive or compensation was provided. Especially when compared to other behavioural weight loss interventions which routinely have higher rates of attrition (Castle, 2017), and in-keeping with the NICE guidelines (2014) which recommends that 60% of participants of behavioural weight management programmes complete the trial. Men and women were equally represented (6 men 6 women); atypical for weight loss studies, which typically have a higher proportion of men (Turner-McGrievy et al., 2015).


Limitations of the study include the self-reporting of dietary intake pre-intervention, the lack of physical activity level assessment and the inability to determine changes in body composition. Whilst the short period over which the study was conducted emphasises a PB vegan diets ability to quickly and effectively reduce weight and WC, it fails to address long term sustainability. The sample was of a very limited range of age, with all participants white, well-educated and recruited mainly from a gym.



Conclusion

This study provides evidence to support the notion that a plant-based vegan diet is effective at yielding short term weight loss with significant reductions in key measures of central adiposity, whilst also producing a more favourable fibre and cholesterol intake. Studies assessing the long-term impact of a vegan diet on weight loss, body composition and macro- and micronutrient intake are needed. Care must be taken when vegan diets are adopted long term to ensure nutrient deficiencies are avoided, the design of which could be the focus of future research. With careful planning and applied knowledge, vegan diets can be designed to ensure nutritional adequacy and achieve and maintain optimal weight.


References

Ashwell, M., & Gibson, S. (2016). Waist-to-height ratio as an indicator of 'early health risk': simpler and more predictive than using a 'matrix' based on BMI and waist circumference. BMJ Open, 6(3), e010159. doi:10.1136/bmjopen-2015-010159


British Dietetics Association. (2017) British Dietetic Association confirms well-planned vegan diets can support healthy living in people of all ages. Retrieved from https://www.bda.uk.com/news/view?id=179


Burckhardt, P. (2016). The role of low acid load in vegetarian diet on bone health: a narrative review. Swiss Medical Weekly, 146, w14277. doi:10.4414/smw.2016.14277

Burke, L. E., Wang, J., & Sevick, M. A. (2011). Self-monitoring in weight loss: a systematic review of the literature. J Am Diet Assoc, 111(1), 92-102. doi:10.1016/j.jada.2010.10.008


Carlsen, M. H., Halvorsen, B. L., Holte, K., Bøhn, S. K., Dragland, S., Sampson, L., . . . Blomhoff, R. (2010). The total antioxidant content of more than 3100 foods, beverages, spices, herbs and supplements used worldwide. Nutrition Journal, 9, 3. doi:10.1186/1475-2891-9-3


Castle, E. (2017) Factors Associated with Weight Status, Weight Loss and Attrition. Durham theses, Durham University. Retrieved from http://etheses.dur.ac.uk/12182/


Craig, W. J. (2009). Health effects of vegan diets. American Journal of Clinical Nutrition, 89(5), 1627S-1633S. doi:10.3945/ajcn.2009.26736N


Dinu, M., Abbate, R., Gensini, G. F., Casini, A., & Sofi, F. (2017). Vegetarian, vegan diets and multiple health outcomes: A systematic review with meta-analysis of observational studies. Critical Reviews in Food Science and Nutrition, 57 (17), 3640-3649. doi:10.1080/10408398.2016.1138447


Dreher, M.L. (2018). Whole Plant Foods in Body Weight and Composition Regulation. In: Dietary Patterns and Whole Plant Foods in Aging and Disease. Nutrition and Health. Humana Press, Cham


Farmer, B. (2014). Nutritional adequacy of plant-based diets for weight management: observations from the NHANES. American Journal of Clinical Nutrition, 100 (1), 365S-368S. doi:10.3945/ajcn.113.071308


Fuller, N. R., Fong, M., Gerofi, J., Ferkh, F., Leung, C., Leung, L., . . . Caterson, I. D. (2017). Comparison of an electronic versus traditional food diary for assessing dietary intake-A validation study. Obesity Research and Clinical Practice, 11(6), 647-654. doi:10.1016/j.orcp.2017.04.001


Hadžiabdić, M. O., Mucalo, I., Hrabač, P., Matić, T., Rahelić, D., & Božikov, V. (2015). Factors predictive of drop-out and weight loss success in weight management of obese patients. Journal of Human Nutrition and Dietetics, 28(2), 24-32. doi:10.1111/jhn.12270


Harland, J., & Garton, L. (2016) An update of the evidence relating to plant-based diets and cardiovascular disease, type 2 diabetes and overweight. British Nutrition Foundation Nutrition Bulletin, 41, 323–338. doi: 10.1111/nbu.12235


Ho-Pham, L. T., Nguyen, N. D., & Nguyen, T. V. (2009). Effect of vegetarian diets on bone mineral density: a Bayesian meta-analysis. American Journal of Clinical Nutrition, 90(4), 943-950. doi:10.3945/ajcn.2009.27521


Madden, A. M., & Smith, S. (2016). Body composition and morphological assessment of nutritional status in adults: a review of anthropometric variables. Journal of Human Nutrition and Dietetics, 29(1), 7-25. doi:10.1111/jhn.12278


Mangano, K. M., & Tucker, K. L. (2017). 17 - Bone Health and Vegan Diets. In F. Mariotti (Ed.), Vegetarian and Plant-Based Diets in Health and Disease Prevention (pp. 315-331): Academic Press.


Mann, J. & Truswell, S. (2017). Essentials of human nutrition. (5th ed.). London, United Kingdom: Oxford University Press.


Naska, A., Lagiou, A., & Lagiou, P. (2017). Dietary assessment methods in epidemiological research: current state of the art and future prospects. F1000Research, 6, 926. doi:10.12688/f1000research.10703.1


National Institute for Health and Care Excellence (2014) Obesity: identification, assessment and management Clinical guideline. Retrieved from National Institute for Health and Care Excellence website: http://nice.org.uk/guidance/cg189


Park, Y., Dodd, K. W., Kipnis, V., Thompson, F. E., Potischman, N., Schoeller, D. A., . . . Subar, A. F. (2018). Comparison of self-reported dietary intakes from the Automated Self-Administered 24-h recall, 4-d food records, and food-frequency questionnaires against recovery biomarkers. American Journal of Clinical Nutrition, 107(1), 80-93. doi:10.1093/ajcn/nqx002


Pendergast, F. J., Ridgers, N. D., Worsley, A., & McNaughton, S. A. (2017). Evaluation of a smartphone food diary application using objectively measured energy expenditure. International Journal of Behavioral Nutrition Physical Activity, 14(1), 30. doi:10.1186/s12966-017-0488-9


Rosell, M., Appleby, P., Spencer, E., & Key, T. (2006). Weight gain over 5 years in 21,966 meat-eating, fish-eating, vegetarian, and vegan men and women in EPIC-Oxford. International Journal of Obesity, 30(9), 1389-1396. doi:10.1038/sj.ijo.0803305


Sharp, D. B., & Allman-Farinelli, M. (2014). Feasibility and validity of mobile phones to assess dietary intake. Nutrition, 30(11-12), 1257-1266. doi:10.1016/j.nut.2014.02.020


Spencer, E. A., Appleby, P. N., Davey, G. K., & Key, T. J. (2003). Diet and body mass index in 38000 EPIC-Oxford meat-eaters, fish-eaters, vegetarians and vegans. International Journal of Obesity and Related Metabolic Disorders, 27(6), 728-734. doi:10.1038/sj.ijo.0802300


Tonstad, S., Stewart, K., Oda, K., Batech, M., Herring, R. P., & Fraser, G. E. (2013). Vegetarian diets and incidence of diabetes in the Adventist Health Study-2. Nutrition Metabolism and Cardiovascular Diseases, 23(4), 292-299. doi:10.1016/j.numecd.2011.07.004


Turner-McGrievy, G. M., Barnard, N. D., Cohen, J., Jenkins, D. J., Gloede, L., & Green, A. A. (2008). Changes in nutrient intake and dietary quality among participants with type 2 diabetes following a low-fat vegan diet or a conventional diabetes diet for 22 weeks. Journal of the American Dietetic Association, 108(10), 1636-1645.

doi:10.1016/j.jada.2008.07.015


Turner-McGrievy, G. M., Davidson, C. R., Wingard, E. E., Wilcox, S., & Frongillo, E. A. (2015). Comparative effectiveness of plant-based diets for weight loss: a randomized controlled trial of five different diets. Nutrition, 31(2), 350-358. doi:10.1016/j.nut.2014.09.002


Turner-McGrievy, G., Mandes, T., & Crimarco, A. (2017). A plant-based diet for overweight and obesity prevention and treatment. Journal of Geriatric Cardiology, 14(5), 369-374. doi:10.11909/j.issn.1671-5411.2017.05.002


Wharton, C. M., Johnston, C. S., Cunningham, B. K., & Sterner, D. (2014). Dietary self-monitoring, but not dietary quality, improves with use of smartphone app technology in an 8-week weight loss trial. Journal of Nutrition Education and Behavior, 46(5), 440-444. doi:10.1016/j.jneb.2014.04.291


World Health Organization. (2008). Waist Circumference and Waist-Hip Ratio. Report of WHO Expert Consultation. Retrieved from World Health Organisation website: http://www.who.int/nutrition/publications/obesity/WHO_report_waistcircumference_and_waisthip_ratio/en/