Hostname: page-component-7c8c6479df-xxrs7 Total loading time: 0 Render date: 2024-03-29T01:49:42.380Z Has data issue: false hasContentIssue false

Nutrition and physical activity interventions for the general population with and without cardiometabolic risk: a scoping review

Published online by Cambridge University Press:  25 May 2021

Mary Rozga*
Affiliation:
Evidence Analysis Center, Academy of Nutrition and Dietetics, 120 South Riverside Plaza, Suite 2190, Chicago, IL60606-6995, USA
Kelly Jones
Affiliation:
Kelly Jones Nutrition, LLC, Newtown, PA, USA
Justin Robinson
Affiliation:
Adjunct Faculty, Point Loma Nazarene University, San Diego, CA, USA
Amy Yahiro
Affiliation:
North American Spine Society, Burr Ridge, IL, USA
*
*Corresponding author: Email mrozga@eatright.org
Rights & Permissions [Opens in a new window]

Abstract

Objective:

The objective of this scoping review was to examine the research question: In the adults with or without cardiometabolic risk, what is the availability of literature examining interventions to improve or maintain nutrition and physical activity-related outcomes? Sub-topics included: (1) behaviour counseling or coaching from a dietitian/nutritionist or exercise practitioner, (2) mobile applications to improve nutrition and physical activity and (3) nutritional ergogenic aids.

Design:

The current study is a scoping review. A literature search of the Medline Complete, CINAHL Complete, Cochrane Database of Systematic Reviews and other databases was conducted to identify articles published in the English language from January 2005 until May 2020. Data were synthesised using bubble charts and heat maps.

Setting:

Out-patient, community and workplace.

Participants:

Adults with or without cardiometabolic risk factors living in economically developed countries.

Results:

Searches resulted in 19 474 unique articles and 170 articles were included in this scoping review, including one guideline, thirty systematic reviews (SR), 134 randomised controlled trials and five non-randomised trials. Mobile applications (n 37) as well as ergogenic aids (n 87) have been addressed in several recent studies, including SR. While primary research has examined the effect of individual-level nutrition and physical activity counseling or coaching from a dietitian/nutritionist and/or exercise practitioner (n 48), interventions provided by these practitioners have not been recently synthesised in SR.

Conclusion:

SR of behaviour counseling or coaching provided by a dietitian/nutritionist and/or exercise practitioner are needed and can inform practice for practitioners working with individuals who are healthy or have cardiometabolic risk.

Type
Review Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of The Nutrition Society

For individuals living in economically developed environments, rates of non-communicable diseases associated with overnutrition, such as type 2 diabetes mellitus and many forms of heart disease, are serious concerns(1). In addition to the decreasing quality of life(Reference Saboya, Bodanese and Zimmermann2) and potential lifespan(Reference Benjamin, Muntner and Alonso3), these diseases collectively contribute to extreme economic burdens to the individual and society as a whole(Reference Benjamin, Muntner and Alonso3). Nutrition and physical activity are each independent risk factors for the development of cardiometabolic diseases and associated mortality(Reference Carnethon4). Despite knowledge of the benefits of improved dietary intake and physical activity, three quarters of Americans follow an eating pattern low in fruits and vegetables(5) and only half of adults meet the minimum aerobic physical activity recommendations(6).

Population-level improvement of nutrition and physical activity behaviours may decrease development and progression of cardiometabolic disease. This may, in turn, result in improved quality of life and a decreased burden of personal and national health care costs. To improve health behaviours on a population level, evidence-based guidance is needed to inform nutrition and physical activity practitioners working with clients in the community, workplace or out-patient settings.

The aim of a scoping review is to map the availability of research, both systematic reviews (SR) and guidelines as well as controlled trials, in areas of interest to determine where resources are available to guide practice, and where evidence is still needed(Reference Peters, Godfrey, McInerney, Aromataris and Munn7). Additionally, a scoping review can identify which current topics still require SR and evidence-based practice guidelines to inform practitioners working with individuals who are healthy or who have cardiometabolic risk factors. This scoping review was conducted to determine if current evidence was available on relevant nutrition and physical activity interventions for the general population. Specific areas of interest that require clarification or are important to policy or practice were identified by practitioners currently working with clients in the field and are addressed in the individual research questions.

The objective of this scoping review is to address the overarching research question: In adults in the ‘general population’, including non-athletes or recreational athletes with or without cardiometabolic risk factors, what is the extent, range and nature of literature examining interventions to improve or maintain nutrition and physical activity and related outcomes? Specific research questions examined availability of research describing:

  • Question 1 (Q1). Individual-level nutrition and physical activity counseling or coaching provided by a dietitian/nutritionist and/or exercise practitioner;

  • Question 2 (Q2). Mobile applications (apps) and/or wearable technology;

  • Question 3 (Q3). Nutritional ergogenic aids of interest.

Methods

This scoping review was conducted with the framework introduced by Arksey and O’Malley(Reference Arksey and O’Malley8) and developed by Levac et al. (Reference Levac, Colquhoun and Brien9) and the Joanna Briggs Institute(Reference Peters, Godfrey, McInerney, Aromataris and Munn7). This scoping review was registered on Open Science Framework (osf.io/pc6sy)(Reference Rozga10) and adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist for scoping reviews(Reference Tricco, Lillie and Zarin11).

Eligibility criteria

A full description of eligibility criteria can be found in Table 1. The target population for this scoping review was adults in the ‘general’ population living in economically developed countries, such as the USA(12). The authors recognised that currently, a ‘general’ population does not imply a ‘healthy’ population, since cardiometabolic risk factors may exist in a majority of adults. Thus, this scoping review included individuals with no risk, risk for and diagnosed with cardiometabolic disease.

Table 1 Eligibility criteria for studies including in scoping review examining effect of nutrition and physical activity interventions in the general population

BCAA, branched chain amino acid; BMD, bone mineral density; BP, blood pressure; COPD, chronic obstructive pulmonary disease; CRP, C-reactive protein; FFM, fat-free mass; FM, fat mass; IBD, irritable bowel disease; PCOS, polycystic ovarian syndrome; Q1, Question 1; Q2, Question 2; Q3, Question 3; RCT, randomised controlled trial.

Three areas of nutrition and physical activity interventions were explored in this scoping review: (1) counseling or coaching, (2) mobile applications and (3) nutritional ergogenic aids. Q1 examined the efficacy of nutrition and physical activity counseling or coaching provided by a dietitian/nutritionist and/or exercise practitioner (see Table 1 for specific criteria). For Q1 inclusion, study participants must have received at least some individual-level counseling in nutrition and/or physical activity. Q2 explored the efficacy of mobile apps and other wearable technology in nutrition and physical activity interventions. For these two questions, studies were required to be controlled trials, either randomised controlled trial (RCT) or non-RCT. Q3 examined efficacy nutritional ergogenic aids deemed as commonly used in the ‘general’ population (Table 1). For Q3 only (nutritional ergogenic aids), studies were required to be placebo-controlled RCT. Additionally, for Q3, studies were limited to those reporting anthropometric, body composition and performance outcomes. For all questions, primary studies were included if they were published in 2005 or later to balance a wide breadth of evidence with relevancy of interventions to the current population. SR answering at least one of the research questions were included if published in 2015 or later, since SR published earlier than 2015 may require updated information. Included studies were limited to those published in the English language due to resource constraints.

Search plan

Search strategies were written by an Information Specialist for the following databases via the Ebsco interface: Medline Complete, CINAHL Complete, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials and Food Science Source. Searches were run on 4 and 5 May 2020. Two methodological filters were used, one for SR and meta-analyses, and another observational and other study designs. Results were limited to English language and publication year 2005 forward. Results were managed and deduplicated in Endnote Software. A sample search strategy can be found in online supplementary material, Supplemental 1.

Study selection and data extraction

Article screening was conducted in two phases. In the first phase, each title/abstract was reviewed by at least one reviewer (M.R.) and 22·4 % of title/abstracts were reviewed by a second reviewer (A.Y.) using Rayyan screening software(Reference Ouzzani, Hammady and Fedorowicz13). Any discrepancies between authors were discussed until consensus was reached. Communication between reviewers throughout the screening process solidified eligibility criteria. Included title/abstracts moved to the second phase of the full-text review. Prior to the full-text review, authors collaborated to create a template allowing for standardised data extraction and coding, including but not limited to: study design, sample size, population age group, activity level, health status, research question addressed including details specific to the research question (e.g., practitioner delivering the intervention for Q1) and outcomes reported. One of two reviewers (M.R. or A.Y.) reviewed the full text, determined eligibility and extracted data for included articles. The second reviewer confirmed reason for exclusion or checked accuracy of extracted data. Relevant SR were searched for eligible articles that may have been missed by the databases search.

Synthesis of results

The study selection process was documented using a PRISMA flow chart(Reference Moher, Liberati and Tetzlaff14). Data were analysed according to the specific research question addressed and types of studies included. A bubble chart was created to demonstrate publication trends according to the sub-question addressed. For each of the three questions, a heat map was created to demonstrate density of interventions according to the population, type of intervention and/or outcomes reported. As is customary for scoping reviews, critical appraisal of study quality and meta-analyses were not conducted.

Results

The databases and hand searches identified 19 474 unique articles. Following title/abstract screening, 657 full texts were reviewed, and 170 articles answering at least one of the research questions were included in this scoping review (Fig. 1). Eighty-three of the eighty-nine articles not meeting population criteria were specifically excluded for including participants with BMI ≥ 40 kg/m2. Of the articles included, one was an evidence-based practice guideline(Reference Lennon, DellaValle and Rodder15), thirty were SR(Reference Abdelhamid, Hooper and Sivakaran16Reference Xu, Tan and Zhang45), 134 were RCT(Reference Adachi, Yamaoka and Watanabe46Reference Zuniga, Housh and Camic179) and five were non-RCT(Reference Haruyama, Muto and Nakade180Reference Wilson, Castro Sweet and Edge184). Forty-eight of the articles were included for Q1 (counseling and coaching), thirty-seven articles were included for Q2 (mobile apps and wearables) and eighty-seven articles were included for Q3 (nutritional ergogenic aids of interest). While the rate of publication was relatively constant over the study period for articles examining nutrition and physical activity counseling and coaching (Q1), the number of primary research articles (not including SR) examining the effects of nutrition and physical activity mobile apps and/or wearables as well as nutritional ergogenic aids of interest grew considerably from approximately 2015–2020 (Fig. 2).

Fig. 1 PRISMA flow chart(Reference Moher, Liberati and Tetzlaff14) describing the study inclusion process for a scoping review examining the availability of studies with interventions including both nutrition and physical activity in the general population

Fig. 2 Bubble chart of publication trends in primary research articles published from 2005 to 2020 according to the research question addressed

Question 1: Individual-level nutrition and physical activity counseling or coaching provided by a dietitian/nutritionist or exercise practitioner

Forty-eight articles(Reference Lennon, DellaValle and Rodder15,Reference Maciejewski, Shepherd-Banigan and Raffa32,Reference Adachi, Yamaoka and Watanabe46,Reference Admiraal, Vlaar and Nierkens47,Reference Allman-Farinelli, Partridge and McGeechan49,Reference Arciero, Gentile and Martin-Pressman51,Reference Aro, Kauppinen and Kivinen52,Reference Bennett, Herring and Puleo56,Reference Colleluori, Napoli and Phadnis69,Reference Corpeleijn, Feskens and Jansen74,Reference Corpeleijn, Feskens and Jansen76,Reference Dale, Mann and McAuley78,Reference Droste, Iliescu and Vaillant83,Reference Fernández-García, Martínez-Sánchez and Bernal-López89Reference Foster-Schubert, Alfano and Duggan91,Reference Hageman, Pullen and Hertzog101Reference Haste, Adamson and McColl104,Reference Hollis, Williams and Morgan108,Reference Hurkmans, Matthys and Bogaerts109,Reference Imayama, Alfano and Kong111,Reference Kuller, Pettee Gabriel and Kinzel120,Reference Lammes, Rydwik and Akner121,Reference Magriplis, Sialvera and Papadopoulou128,Reference Maruyama, Kimura and Okumura130,Reference Nakade, Aiba and Suda133,Reference Partridge, McGeechan and Hebden138,Reference Partridge, McGeechan and Bauman139,Reference Puhkala, Kukkonen-Harjula and Aittasalo142,Reference Ross and Wing147Reference Roumen, Feskens and Corpeleijn151,Reference Salas-Salvadó, Díaz-López and Ruiz-Canela154,Reference Schrader, Panek and Temple157,Reference Sialvera, Papadopoulou and Efstathiou160Reference Smith, Bracha and Svendsen162,Reference Tanaka, Murakami and Aiba169,Reference van Wier, Ariëns and Dekkers171,Reference van Dongen, Haveman-Nies and Doets172,Reference Williams, Hollis and Collins177,Reference Haruyama, Muto and Nakade180,Reference Miller, Martz and Stoner182,Reference Wilson, Castro Sweet and Edge184) representing thirty-eight studies met inclusion criteria and examined the effect of nutrition and physical activity counseling or coaching from a dietitian/nutritionist or exercise practitioner, including one evidence-based practice guideline, one SR, thirty-three RCT and three NRCT. The populations, intervention providers and reported outcomes are shown in Table 2. Of the thirty-three primary studies, twenty-eight targeted participants with cardiometabolic risk factors, primarily individuals with overweight or obesity. Five studies met eligibility criteria that targeted participants with cardiometabolic disease (type 2 diabetes mellitus and CVD)(Reference Adachi, Yamaoka and Watanabe46,Reference Droste, Iliescu and Vaillant83,Reference Haste, Adamson and McColl104,Reference Ross and Wing147,Reference Simpson, Pajewski and Nicklas161) , and another five studies included participants with another morbidity, sarcopenia(Reference Colleluori, Napoli and Phadnis69,Reference Lammes, Rydwik and Akner121,Reference Rydwik, Lammes and Frändin149,Reference van Dongen, Haveman-Nies and Doets172) and non-severe anxiety and depression(Reference Forsyth, Deane and Williams90) in four and one study, respectively. Two trials (entitled the TXT2Bfit and 40 something trials) included participants who were both at cardiometabolic risk and who did not have cardiometabolic risk factors but were at risk of weight gain(Reference Allman-Farinelli, Partridge and McGeechan49,Reference Partridge, McGeechan and Hebden138,Reference Partridge, McGeechan and Bauman139) or were perimenopausal women(Reference Hollis, Williams and Morgan108,Reference Williams, Hollis and Collins177) . Sample sizes ranged from 28 to 11 827 participants and study durations ranged from 4 weeks to 8 years. Nutrition and physical activity counseling or coaching was provided by a dietitian/nutritionist only in fifteen studies(Reference Lennon, DellaValle and Rodder15,Reference Maciejewski, Shepherd-Banigan and Raffa32,Reference Adachi, Yamaoka and Watanabe46,Reference Admiraal, Vlaar and Nierkens47,Reference Aro, Kauppinen and Kivinen52,Reference Droste, Iliescu and Vaillant83,Reference Fernández-García, Martínez-Sánchez and Bernal-López89,Reference Hageman, Pullen and Hertzog101,Reference Magriplis, Sialvera and Papadopoulou128,Reference Partridge, McGeechan and Bauman139,Reference Ross and Wing147,Reference Roumen, Feskens and Corpeleijn151,Reference Sialvera, Papadopoulou and Efstathiou160,Reference Smith, Bracha and Svendsen162,Reference Miller, Martz and Stoner182) , an exercise practitioner only in two studies(Reference Bennett, Herring and Puleo56,Reference Wilson, Castro Sweet and Edge184) and both a dietitian/nutritionist and exercise practitioner in twenty-one studies(Reference Arciero, Gentile and Martin-Pressman51,Reference Colleluori, Napoli and Phadnis69,Reference Dale, Mann and McAuley78,Reference Forsyth, Deane and Williams90,Reference Foster-Schubert, Alfano and Duggan91,Reference Hardcastle, Taylor and Bailey102,Reference Hardcastle, Taylor and Bailey103,Reference Hollis, Williams and Morgan108,Reference Imayama, Alfano and Kong111,Reference Kuller, Pettee Gabriel and Kinzel120,Reference Lammes, Rydwik and Akner121,Reference Maruyama, Kimura and Okumura130,Reference Puhkala, Kukkonen-Harjula and Aittasalo142,Reference Rydwik, Lammes and Frändin149,Reference Simpson, Pajewski and Nicklas161,Reference Tanaka, Murakami and Aiba169,Reference van Wier, Ariëns and Dekkers171,Reference van Dongen, Haveman-Nies and Doets172,Reference Haruyama, Muto and Nakade180) . The greatest density of studies examined participants with cardiometabolic risk factors and interventions delivered by a dietitian/nutritionist and exercise practitioner or a dietitian/nutritionist only, and reporting anthropometric, glucose homoeostasis, blood pressure, lipid profile, dietary intake and physical activity outcomes. The one included SR reported the outcome of weight change(Reference Maciejewski, Shepherd-Banigan and Raffa32). Exercise practitioners providing interventions were heterogeneous and included physiotherapists (n 4), exercise physiologists (n 7), physical trainer (n 1), physical activity ‘specialist’ or ‘coach’ (n 3), exercise or physical activity instructors (n 3) and health coaches (n 2) among others.

Table 2 Primary studies examining the effect of nutrition and physical activity counseling/coaching according to the provider of intervention and outcomes reported (n 36 studies)

Red colour = >5 studies, light orange colour = 1–5 studies, light yellow colour = no available studies.

* Includes cardiovascular risk, type 2 diabetes mellitus risk, overweight and obesity and metabolic syndrome.

Simpson et al. (Reference Simpson, McNamara and Shaw191) reported frailty index, which is not reported in the table.

Includes osteopenia, osteoporosis, osteoarthritic and bone mineral density/content.

Question 2: Nutrition and physical activity mobile apps and/or wearable technology

A total of thirty-six articles(Reference Dounavi and Tsoumani18,Reference Cheatham, Stull and Fantigrassi19,Reference Kim and Seo21,Reference Flores Mateo, Granado-Font and Ferré-Grau22,Reference Lunde, Nilsson and Bergland30,Reference Milne-Ives, Lam and De Cock34,Reference Puigdomenech Puig, Robles and Saigí-Rubió35,Reference Schoeppe, Alley and Van Lippevelde37,Reference Sypes, Newton and Lewis40,Reference Veazie, Winchell and Gilbert42Reference Wu, Guo and Zhang44,Reference Aktas, Mähler and Hamm48,Reference Byrne, Meerkin and Laukkanen59,Reference Day, Jahnke and Haddock80,Reference Epton, Norman and Dadzie87,Reference Garcia-Ortiz, Recio-Rodriguez and Agudo-Conde94,Reference Gomez-Marcos, Patino-Alonso and Recio-Rodriguez95,Reference Gonzalez-Sanchez, Recio-Rodriguez and Fernandez-delRio97,Reference Greene, Sacks and Piniewski100,Reference Hebden, Cook and van der Ploeg106,Reference Hurkmans, Matthys and Bogaerts109,Reference Jakicic, Davis and Rogers113,Reference Kruger, Brennan and Strong119,Reference Lara, O’Brien and Godfrey123,Reference Lisón, Palomar and Mensorio126,Reference Martin, Miller and Thomas129,Reference Pellegrini, Verba and Otto140,Reference Polzien, Jakicic and Tate141,Reference Recio-Rodriguez, Agudo-Conde and Martin-Cantera143Reference Recio-Rodríguez, Rodriguez-Sanchez and Martin-Cantera145,Reference Ross and Wing147,Reference Wayne, Perez and Kaplan176,Reference Mailey, Irwin and Joyce181,Reference West, Monroe and Turner-McGrievy183) representing thirty studies were included for Q2, which examined the effects of nutrition and physical activity mobile apps and/or wearables. Studies included were SR (n 12), RCT (n 16) and non-RCT (n 2). The populations, study designs and reported outcomes are shown in Table 3. Ten studies included participants who were healthy(Reference Flores Mateo, Granado-Font and Ferré-Grau22,Reference Milne-Ives, Lam and De Cock34,Reference Schoeppe, Alley and Van Lippevelde37,Reference Sypes, Newton and Lewis40,Reference Day, Jahnke and Haddock80,Reference Epton, Norman and Dadzie87,Reference Garcia-Ortiz, Recio-Rodriguez and Agudo-Conde94,Reference Gonzalez-Sanchez, Recio-Rodriguez and Fernandez-delRio97,Reference Lara, O’Brien and Godfrey123,Reference Mailey, Irwin and Joyce181) and twenty-one studies included participants with cardiometabolic risk factors(Reference Dounavi and Tsoumani18,Reference Cheatham, Stull and Fantigrassi19,Reference Kim and Seo21,Reference Flores Mateo, Granado-Font and Ferré-Grau22,Reference Milne-Ives, Lam and De Cock34,Reference Puigdomenech Puig, Robles and Saigí-Rubió35,Reference Sypes, Newton and Lewis40,Reference Aktas, Mähler and Hamm48,Reference Byrne, Meerkin and Laukkanen59,Reference Garcia-Ortiz, Recio-Rodriguez and Agudo-Conde94,Reference Gomez-Marcos, Patino-Alonso and Recio-Rodriguez95,Reference Gonzalez-Sanchez, Recio-Rodriguez and Fernandez-delRio97,Reference Greene, Sacks and Piniewski100,Reference Hebden, Cook and van der Ploeg106,Reference Hurkmans, Matthys and Bogaerts109,Reference Jakicic, Davis and Rogers113,Reference Lisón, Palomar and Mensorio126,Reference Martin, Miller and Thomas129,Reference Pellegrini, Verba and Otto140,Reference Polzien, Jakicic and Tate141,Reference West, Monroe and Turner-McGrievy183) . Only six studies meeting eligibility criteria included participants with cardiometabolic diseases (type 2 diabetes mellitus and CVD)(Reference Lunde, Nilsson and Bergland30,Reference Veazie, Winchell and Gilbert42Reference Wu, Guo and Zhang44,Reference Ross and Wing147,Reference Wayne, Perez and Kaplan176) . Five studies included both participants who were both healthy and those who had cardiometabolic risk factors(Reference Flores Mateo, Granado-Font and Ferré-Grau22,Reference Milne-Ives, Lam and De Cock34,Reference Sypes, Newton and Lewis40,Reference Garcia-Ortiz, Recio-Rodriguez and Agudo-Conde94,Reference Gonzalez-Sanchez, Recio-Rodriguez and Fernandez-delRio97) . Sample sizes ranged from 34 to 1007 participants and study durations ranged from 8 to 32 weeks. There were no patient-centred health outcomes reported for studies with participants who were healthy or at cardiometabolic risk. The greatest density of primary studies and SR examined individuals with cardiometabolic risk factors and reported anthropometric, dietary intake and physical activity outcomes. Six SR addressed the efficacy of mobile apps and wearables for nutrition and physical activity and were published from 2019 until the search date of 4 May 2020(Reference Dounavi and Tsoumani18,Reference Kim and Seo21,Reference Milne-Ives, Lam and De Cock34,Reference Puigdomenech Puig, Robles and Saigí-Rubió35,Reference Sypes, Newton and Lewis40,Reference Wu, Guo and Zhang44) .

Table 3 Heat map of controlled trials examining the effect of mobile apps and/or wearable devices for nutrition and physical activity according to the target populations and reported outcomes (n 30 studies)

Red colour = >5 studies, light red colour = 1–5 studies, blue colour = no available studies.

* Includes CVD risk, type 2 diabetes mellitus risk, overweight and obesity and metabolic syndrome.

Question 3: Nutritional ergogenic aids

A total of eighty-seven articles, including seventeen SR(Reference Abdelhamid, Hooper and Sivakaran16,Reference Beaudart, Rabenda and Simmons17,Reference Chilibeck, Kaviani and Candow20,Reference Forbes, Chilibeck and Candow23Reference Lanhers, Pereira and Naughton29,Reference Zheng-Tao, Zhang and Zhu31,Reference Martínez-Arnau, Fonfría-Vivas and Cauli33,Reference Raya-González, Rendo-Urteaga and Domínguez36,Reference Southward, Rutherfurd-Markwick and Ali38,Reference Stares and Bains39,Reference Valenzuela, Morales and Castillo-García41,Reference Xu, Tan and Zhang45) and seventy placebo-controlled RCT(Reference Andersson-Hall, Pettersson and Edin50,Reference Ballard, Melby and Camus53Reference Bemben, Witten and Carter55,Reference Bernat, Candow and Gryzb57,Reference Black, Waddell and Gonglach58,Reference Burke, Candow and Chilibeck60Reference Church, Hoffman and LaMonica68,Reference Collier, Hardy and Millard-Stafford70Reference Cornish, Myrie and Bugera73,Reference Cooke, Brabham and Buford75,Reference Da Boit, Sibson and Sivasubramaniam77,Reference Dalton, Sowinski and Grubic79,Reference Demura, Yamada and Terasawa81,Reference DiLorenzo, Drager and Rankin82,Reference Del Coso, Salinero and González-Millán84Reference Eliot, Knehans and Bemben86,Reference Ferguson and Syrotuik88,Reference Fouré, Nosaka and Gastaldi92,Reference Funderburk, Beretich and Chen93,Reference Gonglach, Ade and Bemben96,Reference Graef, Smith and Kendall98,Reference Gray, Chappell and Jenkinson99,Reference Herda, Beck and Ryan105,Reference Hill, Buckley and Murphy107,Reference Hutchins-Wiese, Kleppinger and Annis110,Reference Jakeman, Lambrick and Wooley112,Reference James and Kjerulf Greer114Reference Koenig, Benardot and Cody118,Reference Lane and Byrd122,Reference Lara, Ruiz-Moreno and Salinero124,Reference Lembke, Capodice and Hebert125,Reference Logan and Spriet127,Reference Lane, Byrd and Bell131,Reference Mobley, Haun and Roberson132,Reference Nicks and Martin134Reference O’Malley, Myette-Cote and Durrer137,Reference Reule, Scholz and Schoen146,Reference Ruíz-Moreno, Lara and Brito de Souza152,Reference Sabol, Grgic and Mikulic153,Reference Salinero, Lara and Ruiz-Vicente155Reference Schrader, Panek and Temple157,Reference Shimomura, Inaguma and Watanabe159,Reference Smith, Julliand and Reeds163Reference Tallis and Yavuz168,Reference Tinsley, Gann and Huber170,Reference Verhoeven, Vanschoonbeek and Verdijk173,Reference Wallman, Goh and Guelfi175,Reference Zdzieblik, Oesser and Baumstark178,Reference Zuniga, Housh and Camic179) , examined the effect of nutritional ergogenic aids on physical activity, anthropometric and body composition outcomes. Sample sizes ranged from 10 to 118 participants and study durations ranged from 1 d to 1 year. Nearly all included articles focused on one dietary supplement of interest (branched chain amino acids, caffeine, carbohydrate replacement, collagen, creatine, exogenous ketones, multivitamins and n-3 fatty acids), with the exception of one RCT that assessed both creatine and carbohydrate supplementation(Reference Koenig, Benardot and Cody118) and one SR that assessed both creatine and the branched chain amino acid leucine(Reference Beaudart, Rabenda and Simmons17).The most frequently examined ergogenic aid was creatine (n 6 SR(Reference Beaudart, Rabenda and Simmons17,Reference Chilibeck, Kaviani and Candow20,Reference Forbes, Chilibeck and Candow23,Reference Lanhers, Pereira and Naughton28,Reference Lanhers, Pereira and Naughton29,Reference Stares and Bains39) and 22 RCT(Reference Bemben, Witten and Carter55,Reference Bernat, Candow and Gryzb57,Reference Burke, Candow and Chilibeck60Reference Chilibeck, Candow and Landeryou67,Reference Cornish, Candow and Jantz72,Reference Cooke, Brabham and Buford75,Reference Dalton, Sowinski and Grubic79,Reference Eliot, Knehans and Bemben86,Reference Ferguson and Syrotuik88,Reference Graef, Smith and Kendall98,Reference Herda, Beck and Ryan105,Reference Johannsmeyer, Candow and Brahms117,Reference Koenig, Benardot and Cody118,Reference Spillane, Schoch and Cooke164,Reference Stout, Sue Graves and Cramer165,Reference Zuniga, Housh and Camic179) ), followed by caffeine (n 5 SR(Reference Grgic25Reference Grgic, Grgic and Pickering27,Reference Raya-González, Rendo-Urteaga and Domínguez36,Reference Southward, Rutherfurd-Markwick and Ali38) and 20 RCT(Reference Bazzucchi, Felici and Montini54,Reference Black, Waddell and Gonglach58,Reference Church, Hoffman and LaMonica68,Reference Collier, Hardy and Millard-Stafford70,Reference Demura, Yamada and Terasawa81,Reference Del Coso, Salinero and González-Millán84,Reference Gonglach, Ade and Bemben96,Reference Lane and Byrd122,Reference Lara, Ruiz-Moreno and Salinero124,Reference Lane, Byrd and Bell131,Reference Nicks and Martin134,Reference Olcina, Timón and Muñoz136,Reference Ruíz-Moreno, Lara and Brito de Souza152,Reference Sabol, Grgic and Mikulic153,Reference Salinero, Lara and Ruiz-Vicente155,Reference Schrader, Panek and Temple157,Reference Tallis, Duncan and Wright166Reference Tallis and Yavuz168,Reference Wallman, Goh and Guelfi175) ). There were no SR available for carbohydrate replacement (n 4 RCT(Reference Andersson-Hall, Pettersson and Edin50,Reference Ballard, Melby and Camus53,Reference Dupuy and Tremblay85,Reference Koenig, Benardot and Cody118) ) or collagen (n 2 RCT(Reference Jendricke, Centner and Zdzieblik116,Reference Zdzieblik, Oesser and Baumstark178) ) in non- or recreational athletes. There were four SR(Reference Beaudart, Rabenda and Simmons17,Reference Fouré and Bendahan24,Reference Martínez-Arnau, Fonfría-Vivas and Cauli33,Reference Xu, Tan and Zhang45) and six RCT(Reference Fouré, Nosaka and Gastaldi92,Reference Funderburk, Beretich and Chen93,Reference Mobley, Haun and Roberson132,Reference Reule, Scholz and Schoen146,Reference Shimomura, Inaguma and Watanabe159,Reference Verhoeven, Vanschoonbeek and Verdijk173) that focused on branched chain amino acids (primarily leucine); one SR(Reference Valenzuela, Morales and Castillo-García41) and two RCT(Reference James and Kjerulf Greer114,Reference O’Malley, Myette-Cote and Durrer137) examined the effect of exogenous ketones; and two SR(Reference Abdelhamid, Hooper and Sivakaran16,Reference Zheng-Tao, Zhang and Zhu31) and fifteen RCT(Reference Corder, Newsham and McDaniel71,Reference Cornish, Myrie and Bugera73,Reference Da Boit, Sibson and Sivasubramaniam77,Reference DiLorenzo, Drager and Rankin82,Reference Gray, Chappell and Jenkinson99,Reference Hill, Buckley and Murphy107,Reference Hutchins-Wiese, Kleppinger and Annis110,Reference Jakeman, Lambrick and Wooley112,Reference Jannas-Vela, Roke and Boville115,Reference Lembke, Capodice and Hebert125,Reference Logan and Spriet127,Reference Ochi, Tsuchiya and Yanagimoto135,Reference Schattin, Baier and Mai156,Reference Smith, Julliand and Reeds163,Reference Tinsley, Gann and Huber170) examined the effect of n-3 fatty acid supplementation. There were no placebo-controlled RCT or SR identified that evaluated the effect of multivitamins in the population of interest. Table 4 displays a heat map of the distribution of outcomes assessed in RCT and SR for each ergogenic aid of interest. Of the seventy included RCT, only two did not assess exercise/performance outcomes; one examined creatine(Reference Eliot, Knehans and Bemben86) and that the other on n-3 fatty acids(Reference Hill, Buckley and Murphy107). None of the included RCT measured physical activity outcomes using metabolic equivalents of task and only two of the SRs assessed metabolic equivalents of task as an outcome measure of interest(Reference Zheng-Tao, Zhang and Zhu31,Reference Martínez-Arnau, Fonfría-Vivas and Cauli33) . For the nutritional ergogenic aids caffeine, creatine and n-3 fatty acid supplements, SR published in 2019 and 2020 were available (Fig. 3).

Table 4 Heat map of placebo-controlled randomised controlled trials and systematic reviews examining the effect of ergogenic aids according to the supplement and reported outcomes (n 87 studies)

Red colour = >5 studies identified; orange colour = 1–5 studies identified; light yellow colour = no studies identified.

Fig. 3 Bubble chart of placebo-controlled randomised controlled trials and systematic reviews published by year and by ergogenic aid. The bubble size is proportional to the number of studies published in the year for each ergogenic aid. , RCT; , SR

Discussion

This scoping review included 170 primary and secondary research articles that examined the effect of nutrition and physical activity interventions in individuals who were non-athletes or recreational athletes and who were healthy or had cardiometabolic risk. While primary research has been consistently available on the effect of individual-level nutrition and physical activity counseling or coaching from a dietitian or exercise practitioner, there has been little synthesis of these data in the 5 years of SR (2015–2020) examined. SR published prior to 2015 may be valuable for practice(Reference Johns, Hartmann-Boyce and Jebb185), but practitioners should be mindful that new evidence may shift conclusions. Additionally, newer SR may be more relevant to current circumstances (e.g., need for remote coaching/counseling during the COVID-19 pandemic). Mobile applications designed to improve nutrition and physical activity had been addressed in several primary studies over the past 5 years; these studies have been well-represented in SR. Regarding nutritional ergogenic aids of interest, recent SR were available for the supplements with relatively high publication activity (caffeine, creatine and n-3 fatty acids), particularly for the outcome of exercise performance. However, other commonly used ergogenic aids have relatively few SR available to guide practice.

Question 1: Individual-level nutrition and physical activity counseling or coaching provided by a dietitian/nutritionist or exercise practitioner

Prior education, experience, methodologies and assessment techniques can differ significantly among practitioners delivering nutrition and physical activity interventions. Studies in this scoping review included a range of practitioners providing nutrition and exercise counseling or coaching, particularly among exercise practitioners. In addition, state and federal regulations for scope of practice vary, potentially allowing less-than-qualified practitioners to provide nutrition and/or physical activity guidance. While decreasing standards may increase accessibility, there is also risk of lower quality care and, therefore, lower intervention efficacy when care is provided by non-qualified practitioners. Examining how provider qualifications impact outcomes may inform scope of practice for both dietitian/nutritionists and exercise practitioners working with different sub-groups of the ‘general’ population. For example, those with cardiometabolic disease or risk factors for cardiometabolic disease may require medical nutrition therapy provided by a Registered Dietitian, while direct coaching from an exercise practitioner may be required for individuals who are sedentary and/or have little exercise history. There were no studies included that investigated the effect on an intervention in individuals that had no cardiometabolic risk factors or disease. Most available primary studies investigated individuals with cardiometabolic risk, such as those with overweight or obesity, and investigated intermediate outcomes such as anthropometric measures, blood pressure, lab values and behavioural outcomes, which would indicate the prevention of progression towards cardiometabolic disease. A SR on the effects of nutrition and physical activity interventions in individuals with no risk factors may yield few results. However, signs and symptoms of cardiometabolic risk, such as incidence of overweight and pre-diabetic levels of fasting blood glucose, may overlap. Thus, in SR, it may be beneficial to group individuals with cardiometabolic risk factors, but without diagnosed disease.

The United States Preventative Task Force recently conducted a SR on the effect of behaviour counseling for nutrition and physical activity for individuals with cardiovascular risk on CVD outcomes(Reference O’Connor, Evans and Rushkin186). The current working version describes a beneficial effect on cardiovascular events, adiposity-related outcomes and many other health outcomes(187). The current scoping review focused on interventions delivered by nutrition and/or exercise practitioners specifically and included a broader range of participants. SR examining differences in outcomes according to the practitioner delivering the intervention can inform health care providers of the most effective methods to improve dietary intake and physical activity behaviours.

Question 2: Nutrition and physical activity mobile apps and wearable technology

Most studies examining the effectiveness of mobile apps in improving cardiometabolic risk factors have reported outcomes relating to energy intake, storage and output (dietary intake, anthropometrics and physical activity, respectively, Table 3). Fewer studies have assessed the influence of apps on treating those with cardiometabolic conditions, such as type 2 diabetes mellitus and CVD. This discrepancy may be intentional to curtail liability from self-diagnosis or self-treatment based on data or guidance from the app itself and in the absence of a qualified nutrition or exercise practitioner. However, several SR targeting individuals who are healthy or who have cardiometabolic risk factors are available to guide practitioners on the efficacy of utilising mobile apps with clients(Reference Dounavi and Tsoumani18,Reference Cheatham, Stull and Fantigrassi19,Reference Kim and Seo21,Reference Flores Mateo, Granado-Font and Ferré-Grau22,Reference Lunde, Nilsson and Bergland30,Reference Milne-Ives, Lam and De Cock34,Reference Puigdomenech Puig, Robles and Saigí-Rubió35,Reference Schoeppe, Alley and Van Lippevelde37,Reference Sypes, Newton and Lewis40,Reference Veazie, Winchell and Gilbert42Reference Wu, Guo and Zhang44) . Studies investigating individuals without cardiometabolic disease may offer valuable insights in broad-scale interventions implemented prior to individuals experiencing adverse symptoms of cardiometabolic risk and disease. Like the question investigating nutrition and physical activity counseling or coaching (Question 1), the highest density of evidence available examined individuals with cardiometabolic risk factors. These interventions most frequently reported outcomes that would indicate improved behaviours and intermediate outcomes that may indicate the prevention of cardiometabolic disease.

Use of and technology related to smartphone applications and forms of telehealth will likely continue to advance(Reference Rozga, Handu and Kelley188,189) , particularly in light of the need for remote interventions due to the COVID-19 pandemic. Thus, the number of available studies in this domain may require further synthesis including examination of effective app components, differences between apps that simply track behaviour or biomarker data compared with those which provide recommendations and differences in apps developed directly by medical providers (hospitals, insurance providers) v. third-party companies.

Question 3: Nutritional ergogenic aids

Participants were healthy individuals without cardiometabolic risk factors in all except two studies investigating the effect of ergogenic aids(Reference Hill, Buckley and Murphy107,Reference Zdzieblik, Oesser and Baumstark178) . The greatest availability of research on nutritional ergogenic aids was for creatine, caffeine and n-3 fatty acids. Individuals typically use creatine to increase strength and power and may be of particular relevance to older individuals seeking to maintain or build strength, function and potentially cognition. While primary research on creatine as an ergogenic aid has waned in recent years, several SR have been published from 2017 to 2020, including in the ageing population(Reference Beaudart, Rabenda and Simmons17,Reference Chilibeck, Kaviani and Candow20,Reference Forbes, Chilibeck and Candow23,Reference Lanhers, Pereira and Naughton28,Reference Lanhers, Pereira and Naughton29,Reference Stares and Bains39) , and these can be used as resources to guide practitioner advice on creatine supplementation. There is more availability of recent studies examining caffeine(Reference Grgic and Pickering26,Reference Grgic, Grgic and Pickering27,Reference Raya-González, Rendo-Urteaga and Domínguez36,Reference Southward, Rutherfurd-Markwick and Ali38,Reference Grgic, Trexler and Lazinica190) and n-3 fatty acids(Reference Abdelhamid, Hooper and Sivakaran16,Reference Zheng-Tao, Zhang and Zhu31) as ergogenic aids, but these have also been investigated in recent SR as recently as the year this search was conducted. When interpreting this evidence, practitioners should consider if the outcomes of interest align with the performance goals of the client including increased time spent exercising, enhanced endurance, strength or decreased pain. While little of the included research targeted individuals with cardiometabolic risk factors, the use of nutritional ergogenic aids may be common in these individuals to improve exercise endurance and capacity. Thus, when working with individuals with cardiometabolic risk factors, practitioners should consider how to appropriately interpret and modify conclusions and recommendations for clients.

Strengths and limitations

This scoping review had rigorous methods and comprehensively described interventions including both nutrition and physical activity. Another strength of this scoping review was inclusion of populations with a range of cardiometabolic risk that may be representative of the population in economically developed countries, such as the USA. This included individuals who were healthy, overweight or obese, or with cardiometabolic disease. However, the authors did set the parameter that studies would be excluded if they included participants with a BMI of ≥40 kg/m2, with the intention that this relatively arbitrary line may be a proxy for the point at which medical interventions may be necessary beyond ‘standard’ diet and exercise. This is evident in the few studies included that focused on individuals with cardiometabolic disease; most of which included some participants with BMI ≥ 40 kg/m2 and were thus excluded. Future studies may elucidate more relevant measures to stratify individuals who have therapeutic v. ‘general’ needs. Due to the wide breadth of nutrition and physical activity interventions, it was necessary to categorise populations, interventions and outcomes very broadly, thus masking heterogeneity between these studies. Future SR should consider how efficacy of interventions vary according to an individual’s cardiometabolic risk factors, diet and physical activity history and ability, and methods of data collection for dietary intake and physical activity outcomes. Improving understanding of how early interventions may prevent onset or progression of cardiometabolic risk factors prior to disease onset would allow for a development of a framework describing how interventions can be effectively individualised to specific clients but implemented on a broad scale. Increased attention to and rigor of data collection methods, including for dietary and physical activity behaviours, will improve quality of and certainty in evidence to inform practice.

Additional limitations of this scoping review were inclusion of evidence published in the English language only, which may have resulted in missing relevant studies published in other languages, and not all titles/abstracts were screened by two reviewers due to resource constraints and the wide breadth of evidence identified on the topic of interest. These limitations may have resulted in missing relevant articles published on the topics of interest. Also, while this scoping review aimed to identify primary studies published in the 15 years prior to the search and SR published in the 5 years prior to the search, as mentioned, earlier evidence may still be relevant and helpful to practitioners.

Conclusion

Interventions to improve or maintain both nutrition and physical activity can provide clients with the knowledge, skills and tools needed to prevent and treat cardiometabolic risk factors and disease. Several recent SR on the efficacy of nutrition and physical activity mobile apps and nutritional ergogenic aids can serve as evidence-based resources for health practitioners. Though consistent literature has been published examining the effect of providing nutrition and exercise counseling by practitioners in these fields, this evidence has not been synthesised. SR of these targeted interventions may inform scope of practice for dietitians and exercise practitioners working with individuals who are healthy or who have cardiometabolic risk factors. More research is needed examining the long-term effects of nutrition and physical activity interventions on patient-centred health outcomes.

Acknowledgements

Acknowledgements: The authors would like to acknowledge Janet Peterson, Dr PH, RDN, RCEP, WEMT, FACSM for her content expertise and contribution to developing the research questions and eligibility criteria. Financial support: This scoping review was supported by the Academy of Nutrition and Dietetics and the American Council on Exercise (no grant numbers). Conflicts of interest: M.R. is employed by the Academy of Nutrition and Dietetics. J.R. has provided contracting services with the American Council on Exercise. K.J. consults for US Highbush Blueberry Council, The Wonderful Company, Clif Bar & Co, Honey Stinger and NOW Foods. The authors have no other conflicts of interest to disclose. Authorship: All authors contributed to the development of the research question and sub-questions as well as eligibility criteria. M.R. and A.Y. screened article title/abstracts and full texts, extracted data and synthesised evidence. M.R., J.R. and K.J. wrote the first draft of the manuscript and all authors thoroughly reviewed and edited the manuscript and approve of the version submitted. Ethics of human subject participation: not applicable.

Supplementary material

For supplementary material accompanying this paper visit https://doi.org/10.1017/S1368980021002184

References

World Health Organization (2014) Noncommunicable Disease Country Profiles 2014. Geneva, Switzerland: World Health Organization; available at https://apps.who.int/iris/bitstream/handle/10665/128038/9789241507509_eng.pdf;jsessionid=90C284D1B7F4B79C81A3CD363C6F02E3?sequence=1 (accessed May 2021).Google Scholar
Saboya, PP, Bodanese, LC, Zimmermann, PR et al. (2016) Metabolic syndrome and quality of life: a systematic review. Rev Lat Am Enfermagem 24, e2848.CrossRefGoogle ScholarPubMed
Benjamin, EJ, Muntner, P, Alonso, A et al. (2019) Heart disease and stroke statistics-2019 update: a report from the American Heart Association. Circulation 139, e56e528.CrossRefGoogle ScholarPubMed
Carnethon, MR (2009) Physical activity and cardiovascular disease: how much is enough? Am J Lifestyle Med 3, 44s49s.CrossRefGoogle Scholar
United States Department of Agriculture (2015) Dietary Guidelines for Americans. Chapter 2: Shifts Needed To Align With Healthy Eating Patterns. https://health.gov/our-work/food-nutrition/2015-2020-dietary-guidelines/guidelines/chapter-2/current-eating-patterns-in-the-united-states/ (accessed May 2021).Google Scholar
Centers for Disease Control and Prevention (2019) QuickStats: percentage of adults who met federal guidelines for aerobic physical activity through leisure-time activity, by race/ethnicity – national health interview survey, 2008–2017. MMWR Morb Mortal Wkly Rep 68, 292. doi: 10.15585/mmwr.mm6812a6.CrossRefGoogle Scholar
Peters, MDJ, Godfrey, C, McInerney, P et al. (2020) Chapter 11: scoping Reviews (2020 version). In JBI Manual for Evidence Synthesis [Aromataris, E & Munn, Z, editors]. Adelaide, Australia: JBI.Google Scholar
Arksey, H & O’Malley, L (2005) Scoping studies: towards a methodological framework. Int J Soc Res Methodol 8, 1932.CrossRefGoogle Scholar
Levac, D, Colquhoun, HO’ & Brien, KK (2010) Scoping studies: advancing the methodology. Implement Sci 5, 69.CrossRefGoogle ScholarPubMed
Rozga, M (2020) Nutrition and Physical Activity Interventions for the General Population: an Academy of Nutrition and Dietetics and ACE Scoping Review. osf.io/pc6sy (accessed July 2020).Google Scholar
Tricco, AC, Lillie, E, Zarin, W et al. (2018) PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation. Ann Intern Med 169, 467473.CrossRefGoogle ScholarPubMed
Ouzzani, M, Hammady, H, Fedorowicz, Z et al. (2016) Rayyan-a web and mobile app for systematic reviews. Syst Rev 5, 210.CrossRefGoogle ScholarPubMed
Moher, D, Liberati, A, Tetzlaff, J et al. (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med 6, e1000097.CrossRefGoogle ScholarPubMed
Lennon, SL, DellaValle, DM, Rodder, SG et al. (2017) 2015 Evidence analysis library evidence-based nutrition practice guideline for the management of hypertension in adults. J Acad Nutr Diet 117, 1445.e14171458.e1417.CrossRefGoogle ScholarPubMed
Abdelhamid, A, Hooper, L, Sivakaran, R et al. (2019) The relationship between n-3, n-6 and total polyunsaturated fat and musculoskeletal health and functional status in adults: a systematic review and meta-analysis of RCTs. Calc Tissue Int 105, 353372.CrossRefGoogle Scholar
Beaudart, C, Rabenda, V, Simmons, M et al. (2018) Effects of protein, essential amino acids, B-hydroxy B-methylbutyrate, creatine, dehydroepiandrosterone and fatty acid supplementation on muscle mass, muscle strength and physical performance in older people aged 60 years and over. A systematic review of the literature. J Nutr Health Aging 22, 117130.CrossRefGoogle Scholar
Dounavi, K & Tsoumani, O (2019) Mobile health applications in weight management: a systematic literature review. Am J Prev Med 56, 894903.CrossRefGoogle ScholarPubMed
Cheatham, SW, Stull, KR, Fantigrassi, M et al. (2018) The efficacy of wearable activity tracking technology as part of a weight loss program: a systematic review. J Sports Med Phys Fitness 58, 534548.CrossRefGoogle ScholarPubMed
Chilibeck, PD, Kaviani, M, Candow, DG et al. (2017) Effect of creatine supplementation during resistance training on lean tissue mass and muscular strength in older adults: a meta-analysis. Open Access J Sports Med 8, 213226.CrossRefGoogle ScholarPubMed
Kim, H-N & Seo, K (2020) Smartphone-based health program for improving physical activity and tackling obesity for young adults: a systematic review and meta-analysis. Int J Environ Res Public Health 17, 15.CrossRefGoogle Scholar
Flores Mateo, G, Granado-Font, E, Ferré-Grau, C et al. (2015) Mobile phone apps to promote weight loss and increase physical activity: a systematic review and meta-analysis. J Med Internet Res 17, e253.CrossRefGoogle ScholarPubMed
Forbes, SC, Chilibeck, PD & Candow, DG (2018) Creatine supplementation during resistance training does not lead to greater bone mineral density in older humans: a brief meta-analysis. Front Nutr 5, 27.CrossRefGoogle Scholar
Fouré, A & Bendahan, D (2017) Is branched-chain amino acids supplementation an efficient nutritional strategy to alleviate skeletal muscle damage? A systematic review. Nutrients 9, 1047.CrossRefGoogle ScholarPubMed
Grgic, J (2018) Caffeine ingestion enhances Wingate performance: a meta-analysis. Eur J Sport Sci 18, 219225.CrossRefGoogle ScholarPubMed
Grgic, J & Pickering, C (2019) The effects of caffeine ingestion on isokinetic muscular strength: a meta-analysis. J Sci Med Sport 22, 353360.CrossRefGoogle ScholarPubMed
Grgic, J, Grgic, I, Pickering, C et al. (2019) Wake up and smell the coffee: caffeine supplementation and exercise performance-an umbrella review of 21 published meta-analyses. Br J Sports Med 54, 681688.CrossRefGoogle ScholarPubMed
Lanhers, C, Pereira, B, Naughton, G et al. (2015) Creatine supplementation and lower limb strength performance: a systematic review and meta-analyses. Sports Med 45, 12851294.CrossRefGoogle ScholarPubMed
Lanhers, C, Pereira, B, Naughton, G et al. (2017) Creatine supplementation and upper limb strength performance: a systematic review and meta-analysis. Sport Med 47, 163173.CrossRefGoogle ScholarPubMed
Lunde, P, Nilsson, BB, Bergland, A et al. (2018) The effectiveness of smartphone apps for lifestyle improvement in noncommunicable diseases: systematic review and meta-analyses. J Med Internet Res 20, e162.CrossRefGoogle ScholarPubMed
Zheng-Tao, L, Zhang, JM, Zhu, WT (2020) n-3 Polyunsaturated fatty acid supplementation for reducing muscle soreness after eccentric exercise: a systematic review and meta-analysis of randomized controlled trials. BioMed Res Int 2020, 116.Google Scholar
Maciejewski, ML, Shepherd-Banigan, M, Raffa, SD et al. (2018) Systematic review of behavioral weight management program move! for veterans. AmJ Prev Med 54, 704714.CrossRefGoogle ScholarPubMed
Martínez-Arnau, FM, Fonfría-Vivas, R & Cauli, O (2019) Beneficial effects of leucine supplementation on criteria for sarcopenia: a systematic review. Nutrients 11, 2504.CrossRefGoogle ScholarPubMed
Milne-Ives, M, Lam, C, De Cock, C et al. (2020) Mobile apps for health behavior change in physical activity, diet, drug and alcohol use, and mental health: systematic review. JMIR mHealth uHealth 8, e17046.CrossRefGoogle ScholarPubMed
Puigdomenech Puig, E, Robles, N, Saigí-Rubió, F et al. (2019) Assessment of the efficacy, safety, and effectiveness of weight control and obesity management mobile health interventions: systematic review. JMIR mHealth uHealth 7, e12612.CrossRefGoogle ScholarPubMed
Raya-González, J, Rendo-Urteaga, T, Domínguez, R et al. (2020) Acute effects of caffeine supplementation on movement velocity in resistance exercise: a systematic review and meta-analysis. Sports Med 50, 717729.CrossRefGoogle ScholarPubMed
Schoeppe, S, Alley, S, Van Lippevelde, W et al. (2016) Efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour: a systematic review. Int J Behav Nutr Phys Act 13, 127.CrossRefGoogle ScholarPubMed
Southward, K, Rutherfurd-Markwick, KJ & Ali, A (2018) Correction to: the effect of acute caffeine ingestion on endurance performance: a systematic review and meta-analysis. Sports Med 48, 24252441.CrossRefGoogle ScholarPubMed
Stares, A & Bains, M (2020) The additive effects of creatine supplementation and exercise training in an aging population: a systematic review of randomized controlled trials. J Geriatr Phys Ther 43, 99112.CrossRefGoogle Scholar
Sypes, EE, Newton, G & Lewis, ZH (2019) Investigating the use of an electronic activity monitor system as a component of physical activity and weight-loss interventions in nonclinical populations: a systematic review. J Phys Act Health 16, 294302.CrossRefGoogle ScholarPubMed
Valenzuela, PL, Morales, JS, Castillo-García, A et al. (2020) Acute ketone supplementation and exercise performance: a systematic review and meta-analysis of randomized controlled trials. Int J Sports Physiol Perform, 111. doi: 10.1123/ijspp.2019-0918.CrossRefGoogle ScholarPubMed
Veazie, S, Winchell, K, Gilbert, J et al. (2018) Rapid evidence review of mobile applications for self-management of diabetes. J Gen Intern Med 33, 11671176.CrossRefGoogle ScholarPubMed
Veazie, S, Winchell, K, Gilbert, J et al. (2018) Mobile applications for self-management of diabetes. J Med Syst 40, 210.Google Scholar
Wu, X, Guo, X & Zhang, Z (2019) The efficacy of mobile phone apps for lifestyle modification in diabetes: systematic review and meta-analysis. JMIR mHealth uHealth 7, e12297.CrossRefGoogle ScholarPubMed
Xu, Z-R, Tan, Z-J, Zhang, Q et al. (2015) The effectiveness of leucine on muscle protein synthesis, lean body mass and leg lean mass accretion in older people: a systematic review and meta-analysis. Br J Nutr 113, 2534.CrossRefGoogle ScholarPubMed
Adachi, M, Yamaoka, K, Watanabe, M et al. (2013) Effects of lifestyle education program for type 2 diabetes patients in clinics: a cluster randomized controlled trial. BMC Public Health 13, 467.CrossRefGoogle ScholarPubMed
Admiraal, WM, Vlaar, EM, Nierkens, V et al. (2013) Intensive lifestyle intervention in general practice to prevent type 2 diabetes among 18 to 60-year-old South Asians: 1-year effects on the weight status and metabolic profile of participants in a randomized controlled trial. PLoS One 8, e68605.CrossRefGoogle Scholar
Aktas, MF, Mähler, A, Hamm, M et al. (2019) Lifestyle interventions in Muslim patients with metabolic syndrome-a feasibility study. Eur J Clin Nutr 73, 805808.CrossRefGoogle ScholarPubMed
Allman-Farinelli, M, Partridge, SR, McGeechan, K et al. (2016) A mobile health lifestyle program for prevention of weight gain in young adults (TXT2BFiT): 9-month outcomes of a randomized controlled trial. JMIR mHealth uHealth 4, e78.CrossRefGoogle Scholar
Andersson-Hall, U, Pettersson, S, Edin, F et al. (2018) metabolism and whole-body fat oxidation following postexercise carbohydrate or protein intake. Int J Sport Nutr Exerc Metabol 28, 3745.CrossRefGoogle ScholarPubMed
Arciero, RJ, Gentile, CL, Martin-Pressman, R et al. (2006) Increased dietary protein and combined high intensity aerobic and resistance exercise improves body fat distribution and cardiovascular risk factors. Int J Sport Nutr Exerc Metab 16, 373392.CrossRefGoogle ScholarPubMed
Aro, A, Kauppinen, A, Kivinen, N et al. (2019) Life style intervention improves retinopathy status—the Finnish diabetes prevention study. Nutrients 11, 16911691.CrossRefGoogle ScholarPubMed
Ballard, TP, Melby, CL, Camus, H et al. (2009) Effect of resistance exercise, with or without carbohydrate supplementation, on plasma ghrelin concentrations and postexercise hunger and food intake. Metabolism 58, 11911199.CrossRefGoogle ScholarPubMed
Bazzucchi, I, Felici, F, Montini, M et al. (2011) Caffeine improves neuromuscular function during maximal dynamic exercise. Muscle Nerve 43, 839844.CrossRefGoogle ScholarPubMed
Bemben, MG, Witten, MS, Carter, JM et al. (2010) The effects of supplementation with creatine and protein on muscle strength following a traditional resistance training program in middle-aged and older men. J Nutr Health Aging 14, 155159.CrossRefGoogle ScholarPubMed
Bennett, GG, Herring, SJ, Puleo, E et al. (2010) Web-based weight loss in primary care: a randomized controlled trial. Obesity 18, 308313.CrossRefGoogle ScholarPubMed
Bernat, P, Candow, DG, Gryzb, K et al. (2019) Effects of high-velocity resistance training and creatine supplementation in untrained healthy aging males. Appl Physiol Nutr Metab 44, 12461253.CrossRefGoogle ScholarPubMed
Black, CD, Waddell, DE & Gonglach, AR (2015) Caffeine’s ergogenic effects on cycling: neuromuscular and perceptual factors. Med Sci Sports Exerc 47, 11451158.CrossRefGoogle ScholarPubMed
Byrne, NM, Meerkin, JD, Laukkanen, R et al. (2006) Weight loss strategies for obese adults: personalized weight management program v. standard care. Obesity 14, 17771788.CrossRefGoogle Scholar
Burke, DG, Candow, DG, Chilibeck, PD et al. (2008) Effect of creatine supplementation and resistance-exercise training on muscle insulin-like growth factor in young adults. Int J Sport Nutr Exerc Metab 18, 389398.CrossRefGoogle ScholarPubMed
Camic, CL, Housh, TJ, Zuniga, JM et al. (2014) The effects of polyethylene glycosylated creatine supplementation on anaerobic performance measures and body composition. J Strength Cond Res 28, 825833.CrossRefGoogle ScholarPubMed
Candow, DG, Little, JP, Chilibeck, PD et al. (2008) Low-dose creatine combined with protein during resistance training in older men. Med Sci Sports Exerc 40, 16451652.CrossRefGoogle ScholarPubMed
Candow, DG, Vogt, E, Johannsmeyer, S et al. (2015) Strategic creatine supplementation and resistance training in healthy older adults. Appl Physiol Nutr Metab 40, 689694.CrossRefGoogle ScholarPubMed
Carter, JM, Bemben, DA, Knehans, AW et al. (2005) Does nutritional supplementation influence adaptability of muscle to resistance training in men aged 48 to 72 years. J Geriatr Phys Ther 28, 4047.CrossRefGoogle ScholarPubMed
Chami, J & Candow, DG (2019) Effect of creatine supplementation dosing strategies on aging muscle performance. J Geriatr Phys Ther 23, 281285.Google ScholarPubMed
Chilibeck, PD, Chrusch, MJ, Chad, KE et al. (2005) Creatine monohydrate and resistance training increase bone mineral content and density in older men. J Nutr Health Aging 9, 352353.Google ScholarPubMed
Chilibeck, PD, Candow, DG, Landeryou, T et al. (2015) Effects of creatine and resistance training on bone health in postmenopausal women. Med Sci Sports Exerc 47, 15871595.CrossRefGoogle Scholar
Church, DD, Hoffman, JR, LaMonica, MB et al. (2015) The effect of an acute ingestion of Turkish coffee on reaction time and time trial performance. J Int Soc Sports Nutr 12, 111.CrossRefGoogle ScholarPubMed
Colleluori, G, Napoli, N, Phadnis, U et al. (2017) Effect of weight loss, exercise, or both on undercarboxylated osteocalcin and insulin secretion in frail, obese older adults. Oxid Med Cell Longev 2017, 48070464807046.CrossRefGoogle ScholarPubMed
Collier, NB, Hardy, MA, Millard-Stafford, ML et al. (2016) Small beneficial effect of caffeinated energy drink ingestion on strength. J Strength Condi Res 30, 18621870.CrossRefGoogle ScholarPubMed
Corder, KE, Newsham, KR, McDaniel, JL et al. (2016) Effects of short-term docosahexaenoic acid supplementation on markers of inflammation after eccentric strength exercise in women. J Sports Sci Med 15, 176183.Google Scholar
Cornish, SM, Candow, DG, Jantz, NT et al. (2009) Conjugated linoleic acid combined with creatine monohydrate and whey protein supplementation during strength training. Int J Sport Nutr Exerc Metab 19, 7996.CrossRefGoogle ScholarPubMed
Cornish, SM, Myrie, SB, Bugera, EM et al. (2018) n-3 Supplementation with resistance training does not improve body composition or lower biomarkers of inflammation more so than resistance training alone in older men. Nutr Res 60, 8795.CrossRefGoogle Scholar
Corpeleijn, E, Feskens, EJM, Jansen, EHJM et al. (2006) Improvements in glucose tolerance and insulin sensitivity after lifestyle intervention are related to changes in serum fatty acid profile and desaturase activities: the SLIM study. Diabetologia 49, 23922401.CrossRefGoogle ScholarPubMed
Cooke, MB, Brabham, B, Buford, TW et al. (2014) Creatine supplementation post-exercise does not enhance training-induced adaptations in middle to older aged males. Eur J Appl Physiol 114, 13211332.CrossRefGoogle Scholar
Corpeleijn, E, Feskens, EJM, Jansen, EHJM et al. (2007) Lifestyle intervention and adipokine levels in subjects at high risk for type 2 diabetes: the study on lifestyle intervention and impaired glucose tolerance Maastricht (SLIM). Diabetes Care 30, 31253127.CrossRefGoogle Scholar
Da Boit, M, Sibson, R, Sivasubramaniam, S et al. (2017) Sex differences in the effect of fish-oil supplementation on the adaptive response to resistance exercise training in older people: a randomized controlled trial. Am J Clin Nutr 105, 151158.CrossRefGoogle ScholarPubMed
Dale, KS, Mann, JI, McAuley, KA et al. (2009) Sustainability of lifestyle changes following an intensive lifestyle intervention in insulin resistant adults: follow-up at 2-years. Asia Pac J Clin Nutr 18, 114120.Google ScholarPubMed
Dalton, RL, Sowinski, RJ, Grubic, TJ et al. (2017) Hematological and hemodynamic responses to acute and short-term creatine nitrate supplementation. Nutrients 9, 1359.CrossRefGoogle ScholarPubMed
Day, RS, Jahnke, SA, Haddock, CK et al. (2019) Occupationally tailored, web-based, nutrition and physical activity program for firefighters: cluster randomized trial and weight outcome. J Occup Environ Med 61, 841848.CrossRefGoogle ScholarPubMed
Demura, S, Yamada, T & Terasawa, N (2007) Effect of coffee ingestion on physiological responses and ratings of perceived exertion during submaximal endurance exercise. Percept Mot Skills 105, 11091116.CrossRefGoogle ScholarPubMed
DiLorenzo, FM, Drager, CJ & Rankin, JW (2014) Docosahexaenoic acid affects markers of inflammation and muscle damage after eccentric exercise. J Strength Cond Res 28, 27682774.CrossRefGoogle Scholar
Droste, DW, Iliescu, C, Vaillant, M et al. (2013) A daily glass of red wine associated with lifestyle changes independently improves blood lipids in patients with carotid arteriosclerosis: results from a randomized controlled trial. Nutr J 12, 121.CrossRefGoogle ScholarPubMed
Del Coso, J, Salinero, JJ, González-Millán, C et al. (2012) Dose response effects of a caffeine-containing energy drink on muscle performance: a repeated measures design. J Int Soc Sports Nutr 9, 21.CrossRefGoogle ScholarPubMed
Dupuy, O & Tremblay, J (2019) Impact of carbohydrate ingestion on cognitive flexibility and cerebral oxygenation during high-intensity intermittent exercise: a comparison between maple products and usual carbohydrate solutions. Nutrients 11, 2019.CrossRefGoogle ScholarPubMed
Eliot, KA, Knehans, AW, Bemben, DA et al. (2008) The effects of creatine and whey protein supplementation on body composition in men aged 48 to 72 years during resistance training. J Nutr Health Aging 12, 208212.CrossRefGoogle ScholarPubMed
Epton, T, Norman, P, Dadzie, A-S et al. (2014) A theory-based online health behaviour intervention for new university students (U@Uni): results from a randomised controlled trial. BMC Public Health 14, 563.CrossRefGoogle ScholarPubMed
Ferguson, TB & Syrotuik, DG (2006) Effects of creatine monohydrate supplementation on body composition and strength indices in experienced resistance trained women. J Strength Cond Res 20, 939946.Google ScholarPubMed
Fernández-García, JC, Martínez-Sánchez, MA, Bernal-López, MR et al. (2020) Effect of a lifestyle intervention program with energy-restricted Mediterranean diet and exercise on the serum polyamine metabolome in individuals at high cardiovascular disease risk: a randomized clinical trial. Am J Clin Nutr, nqaa064. doi: 10.1093/ajcn/nqaa064.Google ScholarPubMed
Forsyth, A, Deane, FP & Williams, P (2015) A lifestyle intervention for primary care patients with depression and anxiety: a randomised controlled trial. Psychiatry Res 230, 537544.CrossRefGoogle ScholarPubMed
Foster-Schubert, KE, Alfano, CM, Duggan, CR et al. (2012) Effect of diet and exercise, alone or combined, on weight and body composition in overweight-to-obese postmenopausal women. Obesity 20, 16281638.CrossRefGoogle ScholarPubMed
Fouré, A, Nosaka, K, Gastaldi, M et al. (2016) Effects of branched-chain amino acids supplementation on both plasma amino acids concentration and muscle energetics changes resulting from muscle damage: a randomized placebo controlled trial. Clin Nutr 35, 8394.CrossRefGoogle ScholarPubMed
Funderburk, LK, Beretich, KN, Chen, MD et al. (2019) Efficacy of L-leucine supplementation coupled with resistance training in untrained midlife women. J Am Coll Nutr 39, 316324.CrossRefGoogle ScholarPubMed
Garcia-Ortiz, L, Recio-Rodriguez, JI, Agudo-Conde, C et al. (2018) Long-term effectiveness of a smartphone app for improving healthy lifestyles in general population in primary care: randomized controlled trial (evident II study). JMIR mHealth uHealth 6, e107.CrossRefGoogle Scholar
Gomez-Marcos, MA, Patino-Alonso, MC, Recio-Rodriguez, JI et al. (2018) Short- and long-term effectiveness of a smartphone application for improving measures of adiposity: a randomised clinical trial – EVIDENT II study. Eur J Cardiovasc Nurs 17, 552562.CrossRefGoogle Scholar
Gonglach, AR, Ade, CJ, Bemben, MG et al. (2016) Muscle pain as a regulator of cycling intensity: effect of caffeine ingestion. Med Sci Sports Exerc 48, 287296.CrossRefGoogle ScholarPubMed
Gonzalez-Sanchez, J, Recio-Rodriguez, JI, Fernandez-delRio, A et al. (2019) Using a smartphone app in changing cardiovascular risk factors: a randomized controlled trial (evident II study). Int J Med Inform 125, 1321.CrossRefGoogle Scholar
Graef, JL, Smith, AE, Kendall, KL et al. (2009) The effects of 4 weeks of creatine supplementation and high-intensity interval training on cardiorespiratory fitness: a randomized controlled trial. J Int Soc Sports Nutr 6, 18.CrossRefGoogle Scholar
Gray, P, Chappell, A, Jenkinson, AM et al. (2014) Fish oil supplementation reduces markers of oxidative stress but not muscle soreness after eccentric exercise. Int J Sport Nutr Exerc Metab 24, 206214.CrossRefGoogle Scholar
Greene, J, Sacks, R, Piniewski, B et al. (2013) The impact of an online social network with wireless monitoring devices on physical activity and weight loss. J Prim Care Community Health 4, 189194.CrossRefGoogle ScholarPubMed
Hageman, PA, Pullen, CH, Hertzog, M et al. (2014) Effectiveness of tailored lifestyle interventions, using web-based and print-mail, for reducing blood pressure among rural women with prehypertension: main results of the Wellness for Women: DASHing towards Health clinical trial. Int J Behav Nutr Phys Act 11, 132.CrossRefGoogle ScholarPubMed
Hardcastle, S, Taylor, A, Bailey, M et al. (2008) A randomised controlled trial on the effectiveness of a primary health care based counselling intervention on physical activity, diet and CHD risk factors. Patient Educ Couns 70, 3139.CrossRefGoogle ScholarPubMed
Hardcastle, SJ, Taylor, AH, Bailey, MP et al. (2013) Effectiveness of a motivational interviewing intervention on weight loss, physical activity and cardiovascular disease risk factors: a randomised controlled trial with a 12-month post-intervention follow-up. Int J Behav Nutr Phys Act 10, 4055.CrossRefGoogle ScholarPubMed
Haste, A, Adamson, AJ, McColl, E et al. (2017) Web-based weight loss intervention for men with type 2 diabetes: pilot randomized controlled trial. JMIR Diabetes 2, e14.CrossRefGoogle ScholarPubMed
Herda, TJ, Beck, TW, Ryan, ED et al. (2009) Effects of creatine monohydrate and polyethylene glycosylated creatine supplementation on muscular strength, endurance, and power output. J Strength Cond Res 23, 818826.CrossRefGoogle ScholarPubMed
Hebden, L, Cook, A, van der Ploeg, HP et al. (2014) A mobile health intervention for weight management among young adults: a pilot randomised controlled trial. J Hum Nutr Diet 27, 322332.CrossRefGoogle ScholarPubMed
Hill, AM, Buckley, JD, Murphy, KJ et al. (2007) Combining fish-oil supplements with regular aerobic exercise improves body composition and cardiovascular disease risk factors. Am J Clin Nutr 85, 12671274.CrossRefGoogle ScholarPubMed
Hollis, JL, Williams, LT, Morgan, PJ et al. (2015) The 40-Something Randomised Controlled Trial improved fruit intake and nutrient density of the diet in mid-age women. Nutr Diet 72, 316326.CrossRefGoogle Scholar
Hurkmans, E, Matthys, C, Bogaerts, A et al. (2018) Face-to-face v. mobile versus blended weight loss program: randomized clinical trial. JMIR mHealth uHealth 6, e14.CrossRefGoogle Scholar
Hutchins-Wiese, H, Kleppinger, A, Annis, K et al. (2013) The impact of supplemental N-3 long chain polyunsaturated fatty acids and dietary antioxidants on physical performance in postmenopausal women. J Nutr Health Aging 17, 7680.CrossRefGoogle ScholarPubMed
Imayama, I, Alfano, CM, Kong, A et al. (2011) Dietary weight loss and exercise interventions effects on quality of life in overweight/obese postmenopausal women: a randomized controlled trial. Int J Behav Nutr Phys Act 8, 118.CrossRefGoogle ScholarPubMed
Jakeman, JR, Lambrick, DM, Wooley, B et al. (2017) Effect of an acute dose of n-3 fish oil following exercise-induced muscle damage. Eur J Appl Physiol 117, 575582.CrossRefGoogle Scholar
Jakicic, JM, Davis, KK, Rogers, RJ et al. (2016) Effect of wearable technology combined with a lifestyle intervention on long-term weight loss: the IDEA randomized clinical trial. JAMA 316, 11611171.CrossRefGoogle ScholarPubMed
James, S & Kjerulf Greer, B (2019) Influence of exogenous β-hydroxybutyrate on walking economy and rating of perceived exertion. J J Dietary Suppl 16, 463469.CrossRefGoogle ScholarPubMed
Jannas-Vela, S, Roke, K, Boville, S et al. (2017) Lack of effects of fish oil supplementation for 12 weeks on resting metabolic rate and substrate oxidation in healthy young men: a randomized controlled trial. PLoS One 12, 114.CrossRefGoogle ScholarPubMed
Jendricke, P, Centner, C, Zdzieblik, D et al. (2019) Specific collagen peptides in combination with resistance training improve body composition and regional muscle strength in premenopausal women: a randomized controlled trial. Nutrients 11, 892.CrossRefGoogle ScholarPubMed
Johannsmeyer, S, Candow, DG, Brahms, CM et al. (2016) Effect of creatine supplementation and drop-set resistance training in untrained aging adults. Exp Gerontol 83, 112119.CrossRefGoogle ScholarPubMed
Koenig, CA, Benardot, D, Cody, M et al. (2008) Comparison of creatine monohydrate and carbohydrate supplementation on repeated jump height performance. J Strength Cond Res 22, 10811086.CrossRefGoogle ScholarPubMed
Kruger, J, Brennan, A, Strong, M et al. (2014) The cost-effectiveness of a theory-based online health behaviour intervention for new university students: an economic evaluation. BMC Public Health 14, 1011.CrossRefGoogle ScholarPubMed
Kuller, LH, Pettee Gabriel, KK, Kinzel, LS et al. (2012) The women on the move through activity and nutrition (WOMAN) study: final 48-month results. Obesity 20, 636643.CrossRefGoogle ScholarPubMed
Lammes, E, Rydwik, E & Akner, G (2012) Effects of nutritional intervention and physical training on energy intake, resting metabolic rate and body composition in frail elderly. A randomised, controlled pilot study. J Nutr Health Aging 16, 162167.CrossRefGoogle ScholarPubMed
Lane, MT & Byrd, MT (2019) Effects of pre-workout supplements on power maintenance in lower body and upper body tasks. J Funct Morphol Kinesiol 4, 18.CrossRefGoogle ScholarPubMed
Lara, J, O’Brien, N, Godfrey, A et al. (2016) Pilot randomised controlled trial of a web-based intervention to promote healthy eating, physical activity and meaningful social connections compared with usual care control in people of retirement age recruited from workplaces. PLoS One 11, 117.CrossRefGoogle ScholarPubMed
Lara, B, Ruiz-Moreno, C, Salinero, JJ et al. (2019) Time course of tolerance to the performance benefits of caffeine. PLoS One 14, 118.CrossRefGoogle ScholarPubMed
Lembke, P, Capodice, J, Hebert, K et al. (2014) Influence of n-3 (n3) index on performance and wellbeing in young adults after heavy eccentric exercise. J Sports Sci Med 13, 151156.Google Scholar
Lisón, JF, Palomar, G, Mensorio, MS et al. (2020) Impact of a web-based exercise and nutritional education intervention in patients who are obese with hypertension: randomized wait-list controlled trial. J Med Internet Res 22, e14196.CrossRefGoogle ScholarPubMed
Logan, SL & Spriet, LL (2015) n-3 Fatty acid supplementation for 12 weeks increases resting and exercise metabolic rate in healthy community-dwelling older females. PLoS One 10, 118.CrossRefGoogle ScholarPubMed
Magriplis, E, Sialvera, TE, Papadopoulou, A et al. (2019) Effectiveness and easiness of adherence to behavioural guidelines for diet and lifestyle changes for cholesterol-lowering: the increasing adherence of consumers to diet & lifestyle changes to lower (LDL) cholesterol (ACT) randomised controlled trial. J Hum Nutr Diet 32, 607618.CrossRefGoogle ScholarPubMed
Martin, CK, Miller, AC, Thomas, DM et al. (2015) Efficacy of SmartLoss, a smartphone-based weight loss intervention: results from a randomized controlled trial. Obesity 23, 935942.CrossRefGoogle ScholarPubMed
Maruyama, C, Kimura, M, Okumura, H et al. (2010) Effect of a worksite-based intervention program on metabolic parameters in middle-aged male white-collar workers: a randomized controlled trial. Prev Med 51, 1117.CrossRefGoogle ScholarPubMed
Lane, MT, Byrd, MT, Bell, Z et al. (2019) Effects of supplementation of a pre-workout on power maintenance in lower body and upper body tasks in women. J Funct Morphol Kinesiol 2, 18.CrossRefGoogle Scholar
Mobley, CB, Haun, CT, Roberson, PA et al. (2017) Effects of whey, soy or leucine supplementation with 12 weeks of resistance training on strength, body composition, and skeletal muscle and adipose tissue histological attributes in college-aged males. Nutrients 9, 972.CrossRefGoogle ScholarPubMed
Nakade, M, Aiba, N, Suda, N et al. (2012) Behavioral change during weight loss program and 1-year follow-up: Saku control obesity program (SCOP) in Japan. Asia Pac J Clin Nutr 21, 2234.Google Scholar
Nicks, CR & Martin, EH (2020) Effects of caffeine on inspiratory muscle function. Eur J Sport Sci 20, 813818.CrossRefGoogle ScholarPubMed
Ochi, E, Tsuchiya, Y & Yanagimoto, K (2017) Effect of eicosapentaenoic acids-rich fish oil supplementation on motor nerve function after eccentric contractions. J Int Soc Sports Nutr 14, 23.CrossRefGoogle ScholarPubMed
Olcina, GJ, Timón, R, Muñoz, D et al. (2008) Caffeine ingestion effects on oxidative stress in a steady-state test at 75 % VO2 max. Sci Sports 23, 8790.CrossRefGoogle Scholar
O’Malley, T, Myette-Cote, E, Durrer, C et al. (2017) Nutritional ketone salts increase fat oxidation but impair high-intensity exercise performance in healthy adult males. Appl Physiol Nutr Metab 42, 10311035.CrossRefGoogle ScholarPubMed
Partridge, SR, McGeechan, K, Hebden, L et al. (2015) Effectiveness of a mHealth lifestyle program with telephone support (TXT2BFiT) to prevent unhealthy weight gain in young adults: randomized controlled trial. JMIR mHealth uHealth 3, e66.CrossRefGoogle ScholarPubMed
Partridge, SR, McGeechan, K, Bauman, A et al. (2016) Improved eating behaviours mediate weight gain prevention of young adults: moderation and mediation results of a randomised controlled trial of TXT2BFiT, mHealth program. Int J Behav Nutr Phys Act 13, 44.CrossRefGoogle ScholarPubMed
Pellegrini, CA, Verba, SD, Otto, AD et al. (2012) The comparison of a technology-based system and an in-person behavioral weight loss intervention. Obesity 20, 356363.CrossRefGoogle Scholar
Polzien, KM, Jakicic, JM, Tate, DF et al. (2007) The efficacy of a technology-based system in a short-term behavioral weight loss intervention. Obesity 15, 825830.CrossRefGoogle Scholar
Puhkala, J, Kukkonen-Harjula, K, Aittasalo, M et al. (2016) Lifestyle counseling in overweight truck and bus drivers – effects on dietary patterns and physical activity. Prev Med Rep 4, 435440.CrossRefGoogle ScholarPubMed
Recio-Rodriguez, JI, Agudo-Conde, C, Martin-Cantera, C et al. (2016) Short-term effectiveness of a mobile phone app for increasing physical activity and adherence to the Mediterranean diet in primary care: a randomized controlled trial (evident II study). J Med Internet Res 18, 11.CrossRefGoogle Scholar
Recio-Rodriguez, JI, Agudo Conde, C, Calvo-Aponte, MJ et al. (2018) The effectiveness of a smartphone application on modifying the intakes of macro and micronutrients in primary care: a randomized controlled trial. The EVIDENT II study. Nutrients 10, 1473.CrossRefGoogle ScholarPubMed
Recio-Rodríguez, JI, Rodriguez-Sanchez, E, Martin-Cantera, C et al. (2019) Combined use of a healthy lifestyle smartphone application and usual primary care counseling to improve arterial stiffness, blood pressure and wave reflections: a randomized controlled trial (EVIDENT II Study). Hypertens Res 42, 852862.CrossRefGoogle Scholar
Reule, CA, Scholz, C, Schoen, C et al. (2017) Reduced muscular fatigue after a 12-week leucine-rich amino acid supplementation combined with moderate training in elderly: a randomised, placebo-controlled, double-blind trial. BMJ Open Sport Exerc Med 2, e000156.CrossRefGoogle ScholarPubMed
Ross, KM & Wing, RR (2016) Impact of newer self-monitoring technology and brief phone-based intervention on weight loss: a randomized pilot study. Obesity 24, 16531659.CrossRefGoogle ScholarPubMed
Roumen, C, Corpeleijn, E, Feskens, EJM et al. (2008) Impact of 3-year lifestyle intervention on postprandial glucose metabolism: the SLIM study. Diabetes Med 25, 597605.CrossRefGoogle ScholarPubMed
Rydwik, E, Lammes, E, Frändin, K et al. (2008) Effects of a physical and nutritional intervention program for frail elderly people over age 75. A randomized controlled pilot treatment trial. Aging Clin Exp Res 20, 159170.CrossRefGoogle ScholarPubMed
Roumen, C, Feskens, EJM, Jansen, EHJM et al. (2008) Changes in transferrin are related to changes in insulin resistance: the SLIM study. Diabetes Med 25, 14781482.CrossRefGoogle ScholarPubMed
Roumen, C, Feskens, EJM, Corpeleijn, E et al. (2011) Predictors of lifestyle intervention outcome and dropout: the SLIM study. Eur J Clin Nutr 65, 11411147.CrossRefGoogle ScholarPubMed
Ruíz-Moreno, C, Lara, B, Brito de Souza, D et al. (2020) Acute caffeine intake increases muscle oxygen saturation during a maximal incremental exercise test. Br J Clin Pharmacol 86, 861867.CrossRefGoogle ScholarPubMed
Sabol, F, Grgic, J & Mikulic, P (2019) The effects of 3 different doses of caffeine on jumping and throwing performance: a randomized, double-blind, crossover study. Int J Sports Physiol Perform 14, 11701177.CrossRefGoogle Scholar
Salas-Salvadó, J, Díaz-López, A, Ruiz-Canela, M et al. (2019) Effect of a lifestyle intervention program with energy-restricted Mediterranean diet and exercise on weight loss and cardiovascular risk factors: 1-year results of the PREDIMED-plus trial. Diabetes Care 42, 777788.Google Scholar
Salinero, JJ, Lara, B, Ruiz-Vicente, D et al. (2017) CYP1A2 genotype variations do not modify the benefits and drawbacks of caffeine during exercise: a pilot study. Nutrients 9, 269.CrossRefGoogle Scholar
Schattin, A, Baier, C, Mai, D et al. (2019) Effects of exergame training combined with n-3 fatty acids on the elderly brain: a randomized double-blind placebo-controlled trial. BMC Geriatr 19, 81.CrossRefGoogle ScholarPubMed
Schrader, P, Panek, LM & Temple, JL (2013) Acute and chronic caffeine administration increases physical activity in sedentary adults. Nutr Res 33, 457463.CrossRefGoogle ScholarPubMed
Schröder, H, Cárdenas-Fuentes, G, Martínez-González, MA et al. (2018) Effectiveness of the physical activity intervention program in the PREDIMED-Plus study: a randomized controlled trial. Int J Behav Nutr Phys Act 15, 110.CrossRefGoogle ScholarPubMed
Shimomura, Y, Inaguma, A, Watanabe, S et al. (2010) Branched-chain amino acid supplementation before squat exercise and delayed-onset muscle soreness. Int J Sport Nutr Exerc Metab 20, 236244.CrossRefGoogle ScholarPubMed
Sialvera, TE, Papadopoulou, A, Efstathiou, SP et al. (2018) Structured advice provided by a dietitian increases adherence of consumers to diet and lifestyle changes and lowers blood low-density lipoprotein (LDL)-cholesterol: the increasing adherence of consumers to diet & lifestyle changes to lower (LDL) cholesterol (ACT) randomised controlled trial. J Hum Nutr Diet 31, 197208.CrossRefGoogle ScholarPubMed
Simpson, FR, Pajewski, NM, Nicklas, B et al. (2019) Impact of multidomain lifestyle intervention on frailty through the lens of deficit accumulation in adults with type 2 diabetes mellitus. J Gerontol A Biol Sci Med Sci 75, 19211927.CrossRefGoogle Scholar
Smith, GD, Bracha, Y, Svendsen, KH et al. (2005) Incidence of type 2 diabetes in the randomized multiple risk factor intervention trial. Ann Intern Med 142, 313317.CrossRefGoogle Scholar
Smith, GI, Julliand, S, Reeds, DN et al. (2015) Fish oil-derived n-3 PUFA therapy increases muscle mass and function in healthy older adults. Am J Clin Nutr 102, 115122.CrossRefGoogle ScholarPubMed
Spillane, M, Schoch, R, Cooke, M et al. (2009) The effects of creatine ethyl ester supplementation combined with heavy resistance training on body composition, muscle performance, and serum and muscle creatine levels. J Int Soc Sports Nutr 6, 6.CrossRefGoogle ScholarPubMed
Stout, JR, Sue Graves, B, Cramer, JT et al. (2007) effects of creatine supplementation on the onset of neuromuscular fatigue threshold and muscle strength in elderly men and women (64–86 years). J Nutr Health Aging 11, 459464.Google Scholar
Tallis, J, Duncan, MJ, Wright, SL et al. (2013) Assessment of the ergogenic effect of caffeine supplementation on mood, anticipation timing, and muscular strength in older adults. Physiol Rep 1, e00072.CrossRefGoogle ScholarPubMed
Tallis, J, Muhammad, B, Islam, M et al. (2016) Placebo effects of caffeine on maximal voluntary concentric force of the knee flexors and extensors. Muscle Nerve 54, 479486.CrossRefGoogle ScholarPubMed
Tallis, J & Yavuz, HCM (2018) The effects of low and moderate doses of caffeine supplementation on upper and lower body maximal voluntary concentric and eccentric muscle force. Appl Physiol Nutr Metab 43, 274281.CrossRefGoogle ScholarPubMed
Tanaka, NI, Murakami, H, Aiba, N et al. (2019) Effects of 1-year weight loss intervention on abdominal skeletal muscle mass in Japanese overweight men and women. Asia Pac J Clin Nutr 28, 7278.Google ScholarPubMed
Tinsley, GM, Gann, JJ, Huber, SR et al. (2017) Effects of fish oil supplementation on postresistance exercise muscle soreness. J Dietary Suppl 14, 89100.CrossRefGoogle ScholarPubMed
van Wier, MF, Ariëns, GA, Dekkers, JC et al. (2009) Phone and e-mail counselling are effective for weight management in an overweight working population: a randomized controlled trial. BMC Public Health 9, 6.CrossRefGoogle Scholar
van Dongen, EJI, Haveman-Nies, A, Doets, EL et al. (2020) Effectiveness of a diet and resistance exercise intervention on muscle health in older adults: promuscle in practice. J Am Med Dir Assoc 21, 10651072.CrossRefGoogle ScholarPubMed
Verhoeven, S, Vanschoonbeek, K, Verdijk, LB et al. (2009) Long-term leucine supplementation does not increase muscle mass or strength in healthy elderly men. Am J Clin Nutr 89, 14681475.CrossRefGoogle ScholarPubMed
Waki, K, Fujita, H, Uchimura, Y et al. (2014) DialBetics: a novel smartphone-based self-management support system for type 2 diabetes patients. J Diabetes Sci Technol 8, 209215.CrossRefGoogle ScholarPubMed
Wallman, KE, Goh, JW & Guelfi, KJ (2010) Effects of caffeine on exercise performance in sedentary females. J Sports Sci Med 9, 183189.Google ScholarPubMed
Wayne, N, Perez, DF, Kaplan, DM et al. (2015) health coaching reduces hba1c in type 2 diabetic patients from a lower-socioeconomic status community: a randomized controlled trial. J Med Internet Res 17, e224.CrossRefGoogle ScholarPubMed
Williams, LT, Hollis, JL, Collins, CE et al. (2014) Can a relatively low-intensity intervention by health professionals prevent weight gain in mid-age women? 12-Month outcomes of the 40-Something randomised controlled trial. Nutr Diabetes 4, e116.CrossRefGoogle ScholarPubMed
Zdzieblik, D, Oesser, S, Baumstark, MW et al. (2015) Collagen peptide supplementation in combination with resistance training improves body composition and increases muscle strength in elderly sarcopenic men: a randomised controlled trial. Br J Nutr 114, 12371245.CrossRefGoogle ScholarPubMed
Zuniga, JM, Housh, TJ, Camic, CL et al. (2012) The effects of creatine monohydrate loading on anaerobic performance and one-repetition maximum strength. J Strength Cond Res 26, 16511656.CrossRefGoogle ScholarPubMed
Haruyama, Y, Muto, T, Nakade, M et al. (2009) Fifteen-month lifestyle intervention program to improve cardiovascular risk factors in a community population in Japan. Tohoku J Exp Med 217, 259269.CrossRefGoogle Scholar
Mailey, EL, Irwin, BC, Joyce, JM et al. (2019) Independent but not alone: a web-based intervention to promote physical and mental health among military spouses. Appl Psychol Health Well-Being 11, 562583.CrossRefGoogle Scholar
Miller, KE, Martz, DC, Stoner, C et al. (2018) Efficacy of a telephone-based medical nutrition program on blood lipid and lipoprotein metabolism: results of Our Healthy Heart. Nutr Diet 75, 7378.CrossRefGoogle ScholarPubMed
West, DS, Monroe, CM, Turner-McGrievy, G et al. (2016) A technology-mediated behavioral weight gain prevention intervention for college students: controlled, quasi-experimental study. J Med Internet Res 18, e133.CrossRefGoogle ScholarPubMed
Wilson, MG, Castro Sweet, CM, Edge, MD et al. (2017) evaluation of a digital behavioral counseling program for reducing risk factors for chronic disease in a workforce. J Occup Environ Med 59, e150e155.CrossRefGoogle Scholar
Johns, DJ, Hartmann-Boyce, J, Jebb, SA et al. (2014) Diet or exercise interventions vs combined behavioral weight management programs: a systematic review and meta-analysis of direct comparisons. J Acad Nutr Diet 114, 15571568.CrossRefGoogle ScholarPubMed
O’Connor, EA, Evans, CV, Rushkin, MC et al. (2020) U.S. Preventive Services Task Force Evidence Syntheses, Formerly Systematic Evidence Reviews. Rockville (MD): Agency for Healthcare Research and Quality (US).Google ScholarPubMed
U.S. Preventative Services Task Force (2020) Healthy Diet and Physical Activity to Prevent Cardiovascular Disease in Adults with Risk Factors: Behavioral Counseling Interventions. Rockville, MD: U.S. Preventative Services Task Force.Google Scholar
Rozga, M, Handu, D, Kelley, K et al. (2021) Telehealth during the COVID-19 pandemic: a cross-sectional survey of registered dietitian nutritionists. J Acad Nutr Diet S2212-2672, 00036-8.Google Scholar
Pew Research Center (2019) Mobile Fact Sheet. https://www.pewresearch.org/internet/fact-sheet/mobile/ (accessed March 2021).Google Scholar
Grgic, J, Trexler, ET, Lazinica, B et al. (2018) Effects of caffeine intake on muscle strength and power: a systematic review and meta-analysis. J Int Soc Sports Nutr 15, 11.CrossRefGoogle ScholarPubMed
Simpson, SA, McNamara, R, Shaw, C et al. (2015) A feasibility randomised controlled trial of a motivational interviewing-based intervention for weight loss maintenance in adults. Health Technol Assess 19, 1378.Google ScholarPubMed
Hill, AM, Worthley, C, Murphy, KJ et al. (2007) n-3 Fatty acid supplementation and regular moderate exercise: differential effects of a combined intervention on neutrophil function. Br J Nutr 98, 300309.CrossRefGoogle ScholarPubMed
Figure 0

Table 1 Eligibility criteria for studies including in scoping review examining effect of nutrition and physical activity interventions in the general population

Figure 1

Fig. 1 PRISMA flow chart(14) describing the study inclusion process for a scoping review examining the availability of studies with interventions including both nutrition and physical activity in the general population

Figure 2

Fig. 2 Bubble chart of publication trends in primary research articles published from 2005 to 2020 according to the research question addressed

Figure 3

Table 2 Primary studies examining the effect of nutrition and physical activity counseling/coaching according to the provider of intervention and outcomes reported (n 36 studies)

Figure 4

Table 3 Heat map of controlled trials examining the effect of mobile apps and/or wearable devices for nutrition and physical activity according to the target populations and reported outcomes (n 30 studies)

Figure 5

Table 4 Heat map of placebo-controlled randomised controlled trials and systematic reviews examining the effect of ergogenic aids according to the supplement and reported outcomes (n 87 studies)

Figure 6

Fig. 3 Bubble chart of placebo-controlled randomised controlled trials and systematic reviews published by year and by ergogenic aid. The bubble size is proportional to the number of studies published in the year for each ergogenic aid. , RCT; , SR

Supplementary material: File

Rozga et al. supplementary material

Rozga et al. supplementary material 1

Download Rozga et al. supplementary material(File)
File 109.5 KB
Supplementary material: File

Rozga et al. supplementary material

Rozga et al. supplementary material 2

Download Rozga et al. supplementary material(File)
File 30.4 KB