Software Application for Low-Sodium Diet Trial (SALT)

This a single-center prospective randomized controlled trial. Subjects will be assigned to the standard of care dietary recommendations for a low sodium diet (LSD) vs. the standard of care dietary recommendations for a low sodium diet plus a mobile application that analyzes sodium content of shopping lists that are created prior to shopping trips to the grocery store over an 8-week study period. An initial pilot phase will be done to ensure adequate percentage of subjects are completing the study in the intervention group and that adequate data is being collected.

The study will be designed as a single-center prospective randomized controlled trial. Subjects will be assigned to the standard of care dietary recommendations handout vs a mobile application that analyzes sodium content of shopping lists that are created prior to shopping trips to the grocery store. The intervention will be administered for 8 weeks. The trial will be split into two phases, 1) Pilot phase, and 2) Trial phase. Once we have enrolled 20 subjects in the intervention arm, we will analyze whether an appropriate percentage of subjects have completed the study and adequate data is being collected. At the end of the trial, outcomes will be measured as follows: Mean change in score on a Knowledge of Low Sodium Diet validated questionnaire completed at baseline and at the end of the study (primary outcome) -- The minimum and maximum scores are 0 and 26, respectively. A higher score indicates a better knowledge of LSD and we hypothesize that use of the software application will result in a higher score on the questionnaire. Mean change in urinary sodium measured on two baseline 24hr collections and two end of study 24hr collections (primary outcome) -- We hypothesize that an always-available application that helps guide subjects in grocery choices will decrease the 24hr sodium level compared to the control group Within-group assessment of how often the Healthcart application is used to create shopping carts and recording of changes in shopping cart sodium score over the study period (secondary outcome) -- Healthcare interventions delivered via mobile applications are quite novel at this time and the data regarding uptake and usage is limited. These outcome measures will add to this body of data. Clinical data (exploratory outcomes)

Subjects will be given the standard low sodium diet handout with counseling, complete a validated low sodium questionnaire, and a 24-hr urine collection.

Subjects will be given the standard low sodium diet handout with counseling, complete a validated low sodium questionnaire, and a 24-hr urine collection. Subjects will use a mobile app to build their shopping lists prior to grocery shopping.

Subjects will be given a low sodium diet handout with counseling, complete a validated questionnaire on low sodium foods, and complete a 24-hr urine collection.

Subjects will be given a low sodium diet handout with counseling, complete a validated questionnaire on low sodium foods, and complete a 24-hr urine collection. Subjects will be given a mobile app to build grocery lists where the sodium level will be recorded and tracked in the app.

Subjects will complete a low sodium diet validated questionnaire, score range from 0 to 26, higher score indicates better knowledge of role of sodium in diet and relationship of sodium to certain foods.

Urinary sodium levels measured by collecting two 24-hour urine samples at pre-study and 8 weeks. The two 24-hr samples will be averaged to get a single urinary sodium level at each time point, the change will be recorded for each subject and the mean and standard deviation for the intervention and control groups will be compared

Healthcare interventions delivered via mobile applications are quite novel at this time and the data regarding uptakes and usage is limited. These outcome measures will add to this body of data. We will record: 1. number of shopping carts created

Healthcare interventions delivered via mobile applications are quite novel at this time and the data regarding uptakes and usage is limited. These outcome measures will add to this body of data. We will record: 2. number of changes made due to suggestions offered by the application

Once 20 subjects have been enrolled in the intervention arm, we will analyze whether they are using the application and what percentage are completing the study. If 15 or more subjects have completed the trial as intended, enrollment will continue to the final number of 40 per arm. Otherwise, the trial will be terminated.

Inclusion Criteria: Male and female adults aged 18 or greater and any race/ethnicity Diagnosis of Kidney Stone Disease (KSD) within previous 6 months via: Surgical procedure for KSD -- OR Imaging demonstrating KSD (abdominal xray or CT scan) Diagnosis of hypernatriuria (elevated urinary sodium >150mmol/d) on 24-hour urine collection within previous 6 months Mobile phone with iOS Working email address Food purchased at Wegmans grocery stores in the Rochester area during the study period Willingness to participate and able to provide informed consent Exclusion Criteria: Pregnancy Current use of medications prescribed for prevention of KSD Current prescription of low sodium diet due to another medical condition Inability or unwillingness to use mobile application Do not participate in grocery shopping

Pearle MS, Goldfarb DS, Assimos DG, Curhan G, Denu-Ciocca CJ, Matlaga BR, Monga M, Penniston KL, Preminger GM, Turk TM, White JR; American Urological Assocation. Medical management of kidney stones: AUA guideline. J Urol. 2014 Aug;192(2):316-24. doi: 10.1016/j.juro.2014.05.006. Epub 2014 May 20.

Friedlander JI, Antonelli JA, Pearle MS. Diet: from food to stone. World J Urol. 2015 Feb;33(2):179-85. doi: 10.1007/s00345-014-1344-z. Epub 2014 Jun 18.

Penniston KL. The nutrition consult for recurrent stone formers. Curr Urol Rep. 2015 Jul;16(7):47. doi: 10.1007/s11934-015-0518-6.

Wertheim ML, Nakada SY, Penniston KL. Current practice patterns of urologists providing nutrition recommendations to patients with kidney stones. J Endourol. 2014 Sep;28(9):1127-31. doi: 10.1089/end.2014.0164. Epub 2014 Jun 30.

Kitchin B. Nutrition counseling for patients with osteoporosis: a personal approach. J Clin Densitom. 2013 Oct-Dec;16(4):426-31. doi: 10.1016/j.jocd.2013.08.013. Epub 2013 Sep 25.

Ravasco P, Monteiro-Grillo I, Camilo M. Individualized nutrition intervention is of major benefit to colorectal cancer patients: long-term follow-up of a randomized controlled trial of nutritional therapy. Am J Clin Nutr. 2012 Dec;96(6):1346-53. doi: 10.3945/ajcn.111.018838. Epub 2012 Nov 7.

Franz MJ, Boucher JL, Evert AB. Evidence-based diabetes nutrition therapy recommendations are effective: the key is individualization. Diabetes Metab Syndr Obes. 2014 Feb 24;7:65-72. doi: 10.2147/DMSO.S45140. eCollection 2014.

Galdas P, Fell J, Bower P, Kidd L, Blickem C, McPherson K, Hunt K, Gilbody S, Richardson G. The effectiveness of self-management support interventions for men with long-term conditions: a systematic review and meta-analysis. BMJ Open. 2015 Mar 20;5(3):e006620. doi: 10.1136/bmjopen-2014-006620.

Minich DM, Bland JS. Personalized lifestyle medicine: relevance for nutrition and lifestyle recommendations. ScientificWorldJournal. 2013 Jun 26;2013:129841. doi: 10.1155/2013/129841. Print 2013.

Murray CJ, Atkinson C, Bhalla K, Birbeck G, Burstein R, Chou D, Dellavalle R, Danaei G, Ezzati M, Fahimi A, Flaxman D, Foreman, Gabriel S, Gakidou E, Kassebaum N, Khatibzadeh S, Lim S, Lipshultz SE, London S, Lopez, MacIntyre MF, Mokdad AH, Moran A, Moran AE, Mozaffarian D, Murphy T, Naghavi M, Pope C, Roberts T, Salomon J, Schwebel DC, Shahraz S, Sleet DA, Murray, Abraham J, Ali MK, Atkinson C, Bartels DH, Bhalla K, Birbeck G, Burstein R, Chen H, Criqui MH, Dahodwala, Jarlais, Ding EL, Dorsey ER, Ebel BE, Ezzati M, Fahami, Flaxman S, Flaxman AD, Gonzalez-Medina D, Grant B, Hagan H, Hoffman H, Kassebaum N, Khatibzadeh S, Leasher JL, Lin J, Lipshultz SE, Lozano R, Lu Y, Mallinger L, McDermott MM, Micha R, Miller TR, Mokdad AA, Mokdad AH, Mozaffarian D, Naghavi M, Narayan KM, Omer SB, Pelizzari PM, Phillips D, Ranganathan D, Rivara FP, Roberts T, Sampson U, Sanman E, Sapkota A, Schwebel DC, Sharaz S, Shivakoti R, Singh GM, Singh D, Tavakkoli M, Towbin JA, Wilkinson JD, Zabetian A, Murray, Abraham J, Ali MK, Alvardo M, Atkinson C, Baddour LM, Benjamin EJ, Bhalla K, Birbeck G, Bolliger I, Burstein R, Carnahan E, Chou D, Chugh SS, Cohen A, Colson KE, Cooper LT, Couser W, Criqui MH, Dabhadkar KC, Dellavalle RP, Jarlais, Dicker D, Dorsey ER, Duber H, Ebel BE, Engell RE, Ezzati M, Felson DT, Finucane MM, Flaxman S, Flaxman AD, Fleming T, Foreman, Forouzanfar MH, Freedman G, Freeman MK, Gakidou E, Gillum RF, Gonzalez-Medina D, Gosselin R, Gutierrez HR, Hagan H, Havmoeller R, Hoffman H, Jacobsen KH, James SL, Jasrasaria R, Jayarman S, Johns N, Kassebaum N, Khatibzadeh S, Lan Q, Leasher JL, Lim S, Lipshultz SE, London S, Lopez, Lozano R, Lu Y, Mallinger L, Meltzer M, Mensah GA, Michaud C, Miller TR, Mock C, Moffitt TE, Mokdad AA, Mokdad AH, Moran A, Naghavi M, Narayan KM, Nelson RG, Olives C, Omer SB, Ortblad K, Ostro B, Pelizzari PM, Phillips D, Raju M, Razavi H, Ritz B, Roberts T, Sacco RL, Salomon J, Sampson U, Schwebel DC, Shahraz S, Shibuya K, Silberberg D, Singh JA, Steenland K, Taylor JA, Thurston GD, Vavilala MS, Vos T, Wagner GR, Weinstock MA, Weisskopf MG, Wulf S, Murray; U.S. Burden of Disease Collaborators. The state of US health, 1990-2010: burden of diseases, injuries, and risk factors. JAMA. 2013 Aug 14;310(6):591-608. doi: 10.1001/jama.2013.13805.

Slawson DL, Fitzgerald N, Morgan KT. Position of the Academy of Nutrition and Dietetics: the role of nutrition in health promotion and chronic disease prevention. J Acad Nutr Diet. 2013 Jul;113(7):972-9. doi: 10.1016/j.jand.2013.05.005.

Hall AK, Cole-Lewis H, Bernhardt JM. Mobile text messaging for health: a systematic review of reviews. Annu Rev Public Health. 2015 Mar 18;36:393-415. doi: 10.1146/annurev-publhealth-031914-122855.

Free C, Phillips G, Watson L, Galli L, Felix L, Edwards P, Patel V, Haines A. The effectiveness of mobile-health technologies to improve health care service delivery processes: a systematic review and meta-analysis. PLoS Med. 2013;10(1):e1001363. doi: 10.1371/journal.pmed.1001363. Epub 2013 Jan 15.

Eyles H, McLean R, Neal B, Jiang Y, Doughty RN, McLean R, Ni Mhurchu C. A salt-reduction smartphone app supports lower-salt food purchases for people with cardiovascular disease: Findings from the SaltSwitch randomised controlled trial. Eur J Prev Cardiol. 2017 Sep;24(13):1435-1444. doi: 10.1177/2047487317715713. Epub 2017 Jun 20.

Sarmugam R, Worsley A, Flood V. Development and validation of a salt knowledge questionnaire. Public Health Nutr. 2014 May;17(5):1061-8. doi: 10.1017/S1368980013000517. Epub 2013 Mar 18.

Claro RM, Linders H, Ricardo CZ, Legetic B, Campbell NR. Consumer attitudes, knowledge, and behavior related to salt consumption in sentinel countries of the Americas. Rev Panam Salud Publica. 2012 Oct;32(4):265-73. doi: 10.1590/s1020-49892012001000004.

Cook NR, Cutler JA, Obarzanek E, Buring JE, Rexrode KM, Kumanyika SK, Appel LJ, Whelton PK. Long term effects of dietary sodium reduction on cardiovascular disease outcomes: observational follow-up of the trials of hypertension prevention (TOHP). BMJ. 2007 Apr 28;334(7599):885-8. doi: 10.1136/bmj.39147.604896.55. Epub 2007 Apr 20.

Dorsch MP, An LC, Hummel SL. A Novel Just-in-Time Contextual Mobile App Intervention to Reduce Sodium Intake in Hypertension: Protocol and Rationale for a Randomized Controlled Trial (LowSalt4Life Trial). JMIR Res Protoc. 2018 Dec 7;7(12):e11282. doi: 10.2196/11282.