Abstract
Background
Chronic disease prevalence is increasing. Adherence to dietary guidelines is low (<50%) despite positive impacts in disease progression, clinical outcomes, and medical costs. It is important to summarize the impact of providing medically-tailored meals to patients on adherence rates, clinical outcomes, and potential economic outcomes.
Methods
A systematic review was conducted to identify, extract, and appraise food-provision studies from January 1, 2013-May 1, 2018 for heart disease, diabetes (DM), and chronic kidney disease (CKD). The key findings related to adherence and clinical outcomes were compiled. Published literature was utilized to determine the economic impact of key clinical outcomes.
Results
Across diseases, 100 articles (N = 43,175 patients) were included. Dietary adherence was considered “compliant” or ≥ 90% consistently. Significant (p < 0.05) clinical outcomes included 5–10% LDL reduction, 4-11 mmHg SBP reduction, 30% reduction in metabolic syndrome prevalence, 3–5% weight reduction, 56% lower CKD mortality rates, and increased dialysis-free time (2 years:50%, 5 years:25%, calculated cost savings of 80.6–94.3%). Literature review showed these outcomes would result in decreased: cardiovascular (CV) event risk (20–30% reduction: $5–11 billion annually), hospitalization costs ($1–8 billion), and dialysis rates (25–50% reduction: $14–29 billion annually). For heart failure patients, results include: 16% fewer readmissions (saving $234,096 per 100 patients) and a 38-day shorter length of stay (saving $79,425 per hospitalization).
Conclusion
Providing medically-tailored meals significantly increases dietary adherence above 90% and allows patients to realize significantly better chronic disease control. Through this, patients could experience fewer complications (CV events, hospital readmissions and dialysis), resulting in significant annual US healthcare cost reduction of $27–48 billion.
Keywords: Dietary adherence, Diabetes, Hypertension, Systematic review, Hyperlipidemia
1. Introduction
It is crucial to address the risk factors and modifiers associated with chronic disease to improve outcomes for patients and employers while also lowering the heavy costs of healthcare. Healthcare costs continue to rise in the United States, with $3.3 trillion spent in 2016. Projections for future spending estimate an average growth rate of 5.5% annually.1 Most spending occurs in working-age adults (54%), while the healthcare spending is three times higher in older adults (≥65 years).1 According to the Center for Disease Control (CDC), 86% of healthcare spending is for patients with chronic disease and mental health conditions, such as heart disease, diabetes, and chronic kidney disease (CKD).2 Because a bulk of this healthcare spend is associated with chronic disease, finding affordable methods for addressing chronic disease management is essential.
Additionally, these chronic diseases are the leading causes and contributors of morbidity and mortality in adults. For example, heart disease and stroke are the leading causes of death (one-third of all deaths) with over 868,000 Americans dying each year.2 In addition, over 100 million US adults have prediabetes or diabetes,2 which places them at risk for heart disease, chronic kidney disease, and vision loss. These diseases not only have impact in terms of mortality, but they produce significant morbidity, leading to a loss in work productivity and significant healthcare costs. Heart disease and diabetes alone cost employers and the healthcare system over $550 billion annually, particularly due to high hospitalization and readmission rates, which can contribute up to 61% of costs.2., 3, 4.
Important risk factors to address include: obesity, lack of dietary adherence, lack of physical activity, and smoking. Two out of every three adults are overweight or obese (70.7%),5,6 and this contributes significantly to the rising healthcare costs and places patients at risk for heart disease and diabetes.2 Patients who are overweight or obese, with or without chronic disease, cost $3559 more annually in per-patient medical expenditures.5 This becomes even more concerning when patients already have existing chronic conditions, such as heart disease and diabetes, that are exacerbated by obesity. For example, the healthcare costs of diabetic patients are 2.3 times higher than patients without diabetes, and approximately $9600 annually per patient is attributed to treatment and management of diabetes.7
Because of the effect diet can have on chronic disease, patients are often asked to adhere to a disease-specific diet via lifestyle interventions. Clinical practice guideline recommendations for preventing and treating obesity,5 heart disease,8,9 diabetes,10,11 and chronic kidney disease12 serve to address obesity and prevent or modify the risks of chronic disease. Further, in geriatrics, the nutritional needs of older adults are especially critical where approximately 10% of older adults live alone and nearly 60% in long-term care are undernourished.13 In this patient population, comorbid obesity is prominent due to low nutrient-density, sugary, and processed meals.14 It is well-documented in the literature that patients adhere to their dietary regimens less than 50% of the time.15,16 There are multiple reasons for low adherence including diet complexity,15 challenges integrating into their daily lives,10 literacy issues of reading labels,17 and uncertainty about eliminating preferred foods.16 If patients become adherent and attain healthy weights, there is potential for substantial cost savings related to improved overall health outcomes and decreased hospitalizations. For example, in diabetes, an intervention that would assist patients in becoming adherent to dietary changes could result in a minimum of $75 billion annually in savings (30 million diabetics, assuming 70% of patients are overweight or obese, and $35595 greater annual spending). Actual cost savings are likely higher due to the prevention of complications.
Culinary medicine provides medically-tailored meals which integrates evidence-based medicine and nutrition to create diet recommendations in which to prevent and assist patients with medical conditions.18 Instead of finding the perfect one-size-fits all diet (which is problematic for many patients),15,16 culinary medicine instead adapts to the individual patient's food preferences and disease states in order to improve health outcomes and prevent progression of disease.18 Once the health care provider determines the patient needs, (s)he can then work with the patient to prescribe the best diet to accomplish mutual goals.18 Investing in a prescribed/recommended diet is likely to be more beneficial for insurers, employers, and other payers, as preventing the complications and comorbidities associated with obesity and disease progression could result in significant cost savings. For example, a diabetes prevention program that costs $450 per participant could result in as much as $35,000 in annual individual savings.19,20 These cost savings can even be more substantial, as reducing sodium intake could save $26.2 billion annually.21,115
Thus, the goal of this systematic review is to assess the impact of providing focused nutritional interventions on health, clinical and economic outcomes with the intent to form recommendations that combine evidence-based literature with best clinical practices. The objective of this project was to identify the potential economic impact of culinary medicine, where patients receive ready-to-eat meals medically-tailored to their specific disease state (according to nationally published guidelines), as well as related outcomes data on dietary adherence and health outcomes for patients with heart disease, diabetes (DM), and chronic kidney disease (CKD). The authors hope to compare the improvements in health related to these nutritional interventions with the known costs of chronic disease and establish utility of these interventions as a result.
2. Methods
A systematic review was conducted according to the PRISMA statement,22 and the study protocol was generated prior to implementation and registered (PROSPERO CRD42019116570).23 The literature was systematically searched for articles where food was provided in part or whole (in person or through free access) and reviewed. All reviewers (student research assistants, fellows, and faculty) were trained on the protocol prior to beginning.
2.1. Search strategy and study selection criteria
A thorough search of electronic databases was performed to ensure all relevant studies were collected for analysis. The databases searched were: Cumulative Index to Nursing and Allied Health Literature (CINAHL), the Cochrane Central Register of Controlled Trials, Health Source (Nursing and Academic Edition), Medical Literature Analysis and Retrieval System Online (MEDLINE), and PubMed from January 1, 2013 to May 1, 2018. In the initial pilot, a 10-year span was utilized. However, the volume of articles retrieved was too great; thus, the protocol was modified to include a 5-year span.
Study selection was not limited to any particular geographic location. Full text articles were required over abstracts due to the desire for a comprehensive integration of all accessible data. The researchers obtained any full text articles when accessible. Secondary screenings were performed on the references of studies to identify additional studies for inclusion. Only non-qualitative, primary literature was included.
Electronic search terms were generated through examination of the Medical Subject Headings (MeSH) in PubMed. Once a list of potential search terms was developed, the researchers ran trial searches in the electronic databases listed above. Table 1 includes the search terms with optimal results based upon number of articles and relevance. The nutrition terms in the first column of Table 1 were searched with each of the terms in the 5 topic areas in columns 2–6.
Table 1.
Search terms.
Culinary Medicine Term | Geriatrics | Kidney Disease | Neurology | Diabetes | Heart Disease |
---|---|---|---|---|---|
Diet, Nutrition Therapy | Geriatrics, Aging, Frail Elderly | Chronic Kidney Disease, Dialysis, Kidney Function Tests, Kidney Disease | Parkinson's Disease, Alzheimer's Disease, Dementia, Neurology | Diabetes Mellitus, Diabetes Mellitus + Obesity, Ketoacidosis, Hyperglycemia | Heart Disease, Cardiovascular Function, Heart Failure (Diastolic), Heart Failure (Systolic), Hypertension |
2.2. Eligibility criteria
After searching, potential articles were screened for eligibility. Inclusion criteria were: (1) topic of interest (diabetes, heart – heart failure (HF) or hypertension (HTN), geriatrics, kidney disease, and neurology – cognition), (2) participants 18 years of age or older, (3) dietary intervention that fit with clinical guideline recommendations, and (4) meals or meal items were provided to participants at some stage of the study. The fourth eligibility item was added to determine whether culinary medicine could be of value clinically and/or economically due to less variation in patient ability to adhere. Articles also had to be in English, be published in peer-reviewed journals within the last 5 years, contain non-qualitative research data, and be available in full text.
2.3. Data extraction
Two reviewers independently examined relevant articles to determine eligibility, and a final list of articles for each topic was compiled. If there were disagreements or questions about whether an article was eligible, one author (AC) resolved discrepancies. The final article underwent data extraction to identify: duration of intervention, dietary change implemented, assessment of intervention, and findings. The data extraction items were adapted from the process outlined in the Handbook of Clinical Nutrition and Aging on nutrition systematic reviews.24 Per the protocol adapted for this review, authors were not contacted for further information in articles with partial selection criteria; rather, they were excluded from the study.
2.4. Bias and study quality assessment
All studies meeting the inclusion criteria were appraised in order to assess quality and potential bias. Two reviewers independently appraised each article using a dietary outcome tool from Lichtenstein.24 The tool includes an appraisal of: methodological quality, applicability, and overall effect. Table 8 showcases the final result of each article graded in each of the aforementioned three categories using a scoring system described in Table 8's key. Methodological quality focused on overall bias, applicability focused on target population and generalizability to a wide group, and overall effect was specifically targeted to assess clinical benefit vs. harmful effects. Any disagreements or discrepancies were resolved by a third reviewer (AC). For each topic of interest, one author (JD) randomly selected 5 studies and independently appraised them to ensure consistency and quality of the appraisal process.
Table 8.
Quality assessment of included articles.
Article | Methodical Quality | Applicability | Overall Effect |
---|---|---|---|
Anbar 2014 | A | II | ++ |
Aparicio 2013 | A | I | + |
Boespflug 2018 | B | II | + |
Brinkworth 2016 | B | I | ++ |
Camps 2017 | A | III | ++ |
Cardoso 2014 | A | II | ++ |
Casas 2014 | A | I | ++ |
Casas 2016 | A | I | ++ |
Castaner 2013 | A | II | + |
Collins 2017 | B | I | 0 |
Daly 2014 | B | II | + |
Davis and Bryan 2017 | B | II | ++ |
Davis and Hodson 2017 | B | II | + |
De Lorenzo 2017 | A | II | + |
Denissen 2017 | B | II | + |
Estruch 2018 | B | I | ++ |
Farrer 2014 | B | III | ++ |
Fito 2014 | B | I | + |
Friedman 2014 | A | III | 0 |
Goday 2016 | B | I | ++ |
Gomes-Delgado 2015 | B | I | + |
Goraya 2013 | B | III | ++ |
Gower 2015 | A | III | ++ |
Gu 2013 | B | III | + |
Haring 2014 | A | I | + |
Hikmat 2014 | A | I | ++ |
Hill 2015 | A | II | + |
Hummel 2013 | B | II | + |
Jenkins 2017 | A | II | 0 |
Johansson-Persson 2014 | A | II | + |
Juraschek 2017 | A | I | + |
Kent 2017 | B | II | ++ |
Kirwan 2016 | A | II | + |
Kitzman 2016 | B | II | + |
Martinez-Lapiscina 2013 | B | I | + |
McNamara 2018 | A | I | + |
Medina-Remon 2017 | B | I | ++ |
Mirfatahi 2016 | B | II | + |
Moorthi 2014 | B | II | + |
Ota 2016 | A | II | + |
Piccoli 2016 | B | I | ++ |
Reidlinger 2015 | A | I | + |
Richard 2013 | B | III | + |
Richard 2014 | A | II | + |
Roussel 2014 | A | II | + |
Ruscica 2016 | A | II | ++ |
Sanchez-Villegas 2013 | B | I | + |
Sayer 2015 | A | II | ++ |
Scott 2017 | B | II | + |
Tabibi 2017 | B | II | + |
Tay 2014 | B | I | ++ |
Toledo 2013 | B | I | + |
Urbanova 2017 | A | III | + |
Valls-Pedret 2015 | B | I | + |
vor Arnim 2013 | B | II | + |
Wada 2015 | A | III | 0 |
Key for Table: |
Methodological Quality |
A Least Bias; results are valid. |
B Susceptible to some bias, but not sufficient to invalidate the results |
C Significant bias that may invalidate the results |
Applicability |
I Sample is representative of the target population. It should be sufficiently large to cover both sexes, a wide age range, and other important features of the target populations (e.g., diet). |
II Sample is representative of a relevant subgroup of the target population, but not the entire population. |
III Sample is representative of a narrow subgroup of subjects only, and is of limited applicability to other subgroups. |
Overall Effect |
++ Clinically meaningful benefit demonstrated |
+ A clinically meaningful beneficial trend exists but is not conclusive. |
0 Clinically meaningful effect not demonstrated or is unlikely. |
- Harmful effect demonstrated or is likely |
2.5. Pilot test
The systematic review protocol was pilot-tested with the topic of heart disease to identify any issues with the protocol itself or protocol implementation. The research team had originally planned to pull all dietary interventions, not only ones with meals provided. They also had planned for a 10-year span of studies. However, due to the sheer volume of studies, a fourth (meals provided) and fifth (heart disease limited to the Dietary Approaches to Stop Hypertension (DASH) and Mediterranean diets) eligibility items were established and the span was limited to 5 years. At the completion of the pilot, the protocol was finalized.
2.6. Data management
All items pertaining to the systematic review were compiled and saved in a Google Team Drive folder. Google Forms that auto-populated Google Sheets based on the study protocol were used to increase consistency in reporting. Search strategies and results along with article PDFs were saved in the folder along with a copy of the article and citation in the RefWorks® (ProQuest LLC) system.
2.7. Economic impact
Since cost was not directly evaluated in these studies, and in order to contextualize the economic impact of the key clinical outcomes identified, each of the key findings from the systematic review were aggregated into ranges describing the amount of change noted across relevant studies. Then, the peer-reviewed literature and national websites with cost information were searched to identify costs associated with each positive or negative clinical outcome. These searches were performed using information available in 2019. For example, the costs of a hospitalization related to myocardial infarctions was determined and then applied when hospitalizations were reduced.
3. Results
A total of 1968 studies were identified through the literature search and hand searching process, and after applying inclusion and exclusion criteria, 57 studies (27,449 patients) remained (see Fig. 1).
Fig. 1.
PRISMA flow diagram.
3.1. Systematic review
In diabetes, articles were identified when they included low-carbohydrate or low-calorie diets, and a total of 8 articles (n = 459 patients) were included (see Table 2). Implementation of these diets resulted in weight, BMI, waist circumference, or fat reduction (8 studies); improved/reduced A1c or fasting insulin (6 studies); and improvement in cholesterol (3 studies).
Table 2.
Article summaries of low carbohydrate and low caloric diets in diabetes.
Author (Year) | N | Study Length | Diet Assignments | Outcomes Assessed | Adherence/Compliance | Key Findings |
---|---|---|---|---|---|---|
Camps (2017)69 | N = 11 Asian men | 2 days | 1 day on a high glycemic diet 1 day on a low glycemic diet |
24-h glucose iAUC Fat oxidation |
100% | Low vs high glycemic diet:
|
Farrer (2014)64 | N = 26 obese patients | 12 weeks | Randomized to:
|
Weight A1c Cholesterol |
5/17 withdrew in control 2/9 withdrew in treatment Similar rates |
VLCD vs control:
|
Goday (2016)50 | N = 89 men and women Type II DM, BMI 30–35 kg/m2 | 4 months | Randomized to:
|
Weight A1c Cholesterol |
Similar rates (Eating Self-Efficacy Scale) 92.5% rates the VLCK diet as satisfactory vs 68.5% control (p = 0.005) |
VLCK had significant reductions in:
|
Gower (2015)70 | N = 69 overweight/ obese men and women (incl. AA) | 16 weeks | Randomized to:
8 weeks hypocaloric |
Body composition Glucose metabolism |
Compliant | Low carbohydrate vs. low fat:
|
N = 30 women with PCOS | Crossover randomized to:
|
Low carbohydrate:
|
||||
Gu (2013)71 | N = 45 healthy, obese N = 30 healthy, non-obese control |
8 weeks | Very low carbohydrate diet (VLCD) | BMI Glucose metabolism |
Compliant | VLCD in obese patients reduced (at weeks 4 and 8):
|
Tay (2014)52 | N = 115 obese, Type II DM patients | 12 weeks meals provided 12 weeks (Tay) to 44 weeks (Brinkworth) on own diet with key foods provided or voucher |
Randomized to:
|
A1c Glycemic variability Antiglycemic medication changes Lipids BP Weight Adherence |
High compliance for both groups | LC vs HC:
|
Brinkworth (2016)51 – extension of Tay (2014) | Weight Mood (POMS, BDI, SAI) Diabetes emotional distress (PAID) QoL (D-39) |
LC and HC:
|
||||
Urbanova (2017)72 | N = 11 obese patients N = 16 type 2 DM obese patients N = 17 healthy non-obese controls |
3 weeks | Very low carbohydrate diet (VLCD) | Body composition Glucose metabolism Cholesterol |
Compliant | VLCD in obese DM patients reduced:
|
BP = Blood pressure, A1c = Hemoglobin A1c, TG = Triglycerides, QoL = Quality of life, POMS = Profile of Mood States, BDI = Beck Depression Inventory, SAI = Spielberger State Anxiety Inventory, PAID = Problem Areas in Diabetes Questionnaire, D-39 = QoL Diabetes-39, PCOS = Polycystic ovary syndrome, AA = African American, DM = diabetes, TC = total cholesterol.
In heart disease, articles were identified when they included the DASH diet or the Mediterranean diet, and a total of 10 DASH diet (n = 11,891) and 14 Mediterranean diet (n = 18,500) articles were included (see Table 3, Table 4, respectively). Implementation of a DASH diet resulted in improved blood pressure control, lowered blood pressure, or reduced mean arterial pressure (7 studies); weight, BMI, waist circumference, or fat reduction (3 studies); and metabolic syndrome criteria improvement (3 studies). Implementation of a Mediterranean diet resulted in improvement in cholesterol (9 studies); reduced cardiovascular risk or improved CV risk markers (6 studies); and improved blood pressure control, lowered blood pressure, or reduced mean arterial pressure (5 studies).
Table 3.
Article summaries of the DASH diet in heart disease.
Author (Year) | N | Study Length | Diet Assignments | Outcomes Assessed | Adherence/Compliance | Key Findings |
---|---|---|---|---|---|---|
Haring (2014)46 | N = 155, Caucasian and African American patients | 3-period crossover of 6 weeks each | DASH-type diet + increased carbohydrates DASH-type diet + increased protein DASH-type diet + increased unsaturated fat |
Lipoprotein A [Lp(a)] – independent risk factor for CVD | 100% - noncompliant excluded | DASH + unsaturated fat resulted in:
|
Hikmat (2014)38 DASH Trial |
N = 311 non-metabolic syndrome patients N = 99 metabolic syndrome patients |
8 weeks | Fruits and vegetables diet DASH diet Control |
Change in BP HTN Control |
DASH = 93.2% Fruit/Vegetable = 93.9% Control = 94.6% |
Metabolic syndrome patients - DASH diet resulted in:
|
Hill (2015)58 BOLD Study |
N = 62 overweight adults with metabolic syndrome | 6 months | Modified DASH diet rich in plant protein Modified DASH diet rich in animal protein (BOLD) Moderate protein diet (BOLD+) Included a meals provided phase, meals + exercise (weight-loss) and a “free-living” phase (participants made changes on their own) Healthy American diet (control) |
Change in metabolic syndrome criteria | M-DASH = 84% ± 1% BOLD = 81% ± 3% BOLD+ = 74% ± 2% |
Adherence to any one of the three diets resulted in:
Every 1% reduction in body weight was associated with a:
|
Roussel (2014)39 Secondary analysis of the BOLD Study |
N = 36 normotensive patients | 5 weeks | Weight BP Endothelial function |
93% | Adherence to the BOLD diet resulted in:
No other significnat findings. |
|
Hummel (2013)59 | N = 13 heart failure with preserved ejection fraction (HFPEF) patients | 21 days | DASH + sodium-restricted diet (SRD) | BP measurement 6-min walking test 24-h urinary collection ECHO (assessed heart function, energy, stiffness, thickness) |
“Excellent” | Adherence to the DASH + SRD diet resulted in:
|
Jenkins (2017)45 |
N = 209 men N = 710 women who were healthy & overweight |
18 months | DASH diet advice DASH weekly food provision (food basket) DASH diet advice + weekly food provision Control (Health Canada's food guide) |
Bloop panels Anthropometric measurements BP |
Highest retention with food provision vs not provided (91% vs 67% at 6 months 81% vs 57% at 18 months, p < 0.001) | Adherence to advice or diets resulted in significantly improved at 6 months:
Adherence to advice or diets resultsed in significantly improved Framingham score (−0.19 to −0.42%) at 18 months. |
Johansson-Persson (2014)73 | N = 24 overeight patients with high cholesterol | 5 weeks | High fiber (48 g) Low fiber (30.2 g) |
LDL Glucose Lipid metabolism Inflammatory markers |
High dietary fiber diet had significantly higher compliance (60.7% vs. 34.4%, p = 0.027) | Adherence to the high fiber diet resulted in:
No other significant effects |
Juraschek (2017)60 DASH Trial |
N = 412 (57% women, 57% African American) | 4 weeks (each sodium level for 30 days) | DASH groups of low (50 mmol/day), medium (100 mmol/day), and high (150 mmol/day) sodium intake Control groups of: low (50 mmol/day), medium (100 mmol/day), and high (150 mmol/day) sodium intake |
SBP DBP |
High diet adherence | Reducing sodium from high to low in control group was associated with lower SBP from baseline (p for trend = 0.004):
Reducing sodium from high to low in the DASH group was associated with lower SBP from baseline (p for trend<0.001):
The greatest impact of DASH + low sodium diet was seen in the high SBP group. |
Kirwan (2016)44 | N = 40 overweight/ obese patients | 8 weeks each (crossover) | Complete whole grain Refined grain (control) |
BP Body composition Lipids Glucose Infllamatory markers |
Adherence in both groups was similar:
|
Adherence to the whole grain diet resulted in:
Both diets resulted in significantly reduced:
|
Sayer (2015)40 | N = 19 with elevated BP | 6 weeks each (crossover) | DASH+pork DASH+chicken and fish |
SBP DBP |
≥95% for both interventions | Adherence to either DASH diet resulted in:
No significant difference between groups |
BP = Blood pressure, SBP = Systolic blood pressure, DBP = Diastolic blood pressure, A1c = Hemoglobin A1c, TG = Triglycerides, DM = diabetes, TC = total cholesterol, MD = Mediterranean Diet, HDL = high density lipoprotein.
Table 4.
Article summaries of the Mediterranean diet in heart disease.
Author (Year) | N | Study Length | Diet Assignments | Outcomes Assessed | Adherence/Compliance | Key Findings |
---|---|---|---|---|---|---|
Casas (2014)36 PREDIMED Study |
N = 164 | 1 year | MD w/EVOO MD w/nuts Low-fat diet MD Low-fat foods |
BP Lipids Markers of inflammation |
Higher in the MD arms | Adherence to a MD resulted in:
|
Casas (2016)37 PREDIMED Study |
N = 165 | 5 years | Adherence to a MD resulted in: Reduced inflammatory markers (p = 0.04) Lower SBP (p ≤ 0.05)
|
|||
Medina-Remón (2017)41 PREDIMED Study |
N = 1139 high-risk | 1 year | Adherence to a MD resulted in lower SBP and DBP and greater HDL (p < 0.05):
|
|||
Estruch (2013)74 PREDIMED Study Retracted and Republisheda: Estruch (2018)62 |
N = 7447, 1588 participants were eliminated that deviated from protocol | 4.8 years | CV event rates (MI, stroke, death) | Adherence to a MD resulted in:
No other significant differences |
||
Castaner (2013)47 PREDIMED Study |
N = 34 patients with CVD risk factors | 3 months | Lipids (TC, HDL, TG) Gene transcription |
Adherence to a MD resulted in:
No significant difference in lipids. |
||
Fito (2014)48 PREDIMED Study |
N = 930 patients at high CV risk | 1 year | HF Biomarkers: NT-pro BNP, OxLDL, Lp(A) | Adherence to a MD resulted in:
Adherence to the MD + EVOO resulted in:
|
||
Toledo (2013)42 PREDIMED Study |
N = 7447 | 4 years | BP | Adherence to a MD resulted in:
Dietary adherence overall resulted in a greater percentage of patients with controlled BP (p < 0.001):
|
||
Davis and Hodgson (2017)43 MedLey study |
N = 166 older adults | 6 months | MD Habitual diet (control) |
BP Flow-mediated dilation (FMD) |
MD significant improvement in adherence from med to high vs. control (p < 0.001) | Adherence to a MD resulted in (vs control):
|
Davis and Bryan (2017)49 MedLey study |
Lipids (TG) F2-isoprostanes |
“Good” | Adherence to a MD resulted in (vs control):
|
|||
De Lorenzo (2017)75 | N = 25 patients with metabolic syndrome | 1 day | MD Western, high fat diet (control) |
Ox-LDL | 100% | Adherence to a MD resulted in:
|
Gomez-Delgado (2015)76 | N = 897 patients with the “CLOCK” gene and CHD | 1 year | MD Low-fat foods (control) |
C-reactive protein levels (CRP) HDL levels |
Not listed | Adherence to a MD resulted in:
|
Ruscica (2016)61 | N = 26 with MetS | 12 weeks | MD + soy protein MD + animal protein |
Metabolic syndrome features Biomarkers associated with CV risk |
>95% to both diets | Adherence to a MD + soy protein resulted in (p < 0.05):
|
Richard (2013)63 | N = 26 males with MetS (19 males for last phase) | 35 weeks | 5 weeks normal American diet – isocaloric (control) 5 weeks MD – isocaloric 20 weeks free-living (no food provided) For those that lost ≥5% of body weight: 5 weeks MD - isocaloric |
Body composition Biomarkers associated with CV risk |
Only adherent to the MD when food was provided | Adherence to a MD resulted in (p < 0.05) vs control period:
|
Richard (2014)77 | Apolipoprotein B100 (apoB100) metabolism | Adherence to a MD resulted in:
|
BP = Blood pressure, SBP = Systolic blood pressure, DBP = Diastolic blood pressure, A1c = Hemoglobin A1c, TG = Triglycerides, DM = diabetes, TC = total cholesterol, MD = Mediterranean Diet, HDL = high density lipoprotein, EVOO = extra virgin olive oil, CV = cardiovascular, CVD = cardiovascular disease.
Due to retraction, the 2013 article was eliminated and replaced with the republished version in June 2018.
In geriatrics, articles were identified when they included dietary interventions for geriatric patients, and a total of 7 articles (n = 714) were included (see Table 5). Implementation of a broad range of diets that included more fresh fruits and vegetables, increased protein, and higher energy intake, often in collaboration with resistance training or other exercise, resulted in improved weight, fat-free mass, or muscle mass (3 studies). Other results related to geriatrics were varied among studies.
Table 5.
Geriatrics article summaries.
Author (Year) | N | Study Length | Diet Assignments | Outcomes Assessed | Adherence/Compliance | Key Findings |
---|---|---|---|---|---|---|
Anbar (2014)78 | N = 50 geriatric patients | ≥14 days | Caloric restriction with oral nutritional supplements (based on energy goal) Control |
Resting energy expenditures Length of hospital stay Complication incidence |
Compliant | Caloric restriction resulted in:
|
Aparicio (2013)81 | N = 140 institutionalized elderly from Madrid, Spain | 7 days | Glycemic Index (GI) and glycemic load (GL) via food provided by nursing home | Depression (GDS) – separated into non-depressed and depressed | Compliant | Patients with a higher GL were:
There were no differences in GI between depressed and non-depressed. |
Collins (2017)80 | N = 122 subacute ward patients | 14 days | High energy and protein diet Control |
Weight Hand grip strength Patient satisfaction Cost |
Compliant | No significant differences between groups in outcomes. Intervention group had:
|
Daly (2014)84 | N = 100 elderly women | 4 months | Progressive resistance training + lean red meat (160 g 6 days/week) Control: progressive resistance training +1 serving pasta or rice/day |
Muscle mass and composition Inflammatory markers Blood pressure Lipids |
81% meat compliance 100% carbohydrate compliance 92% VitD supplement compliance |
Allocation to the lean red meat group resulted in:
|
Denissen (2017)82 | N = 40 functionally disabled home-dwelling elderly | 12 weeks | Home meal delivery service of a high quality dinner with fresh ingredients using the Netherlands Nutrition Centre Foundation guidelines (which includes low sodium) Control |
Satisfaction with service Body composition QoL |
Compliant | Intervention group:
|
Kitzman (2016)79 | N = 100 older obese men and women | 20 weeks | Exercise alone Diet alone (caloric restriction, ~400 kcal/day deficit) Diet (~350 kcal/day deficit) Control |
Exercise capacity QoL (MLHF) |
Dietary compliance was 99 ± 1% for both diet groups. | All intervention groups had significant improvements in exercise capacity (p < 0.001). No change in quality of life |
Reidlinger (2015)83 | N = 162 nonsmoking men and women | 12 weeks | United Kingdom dietary guidelines (low sodium, low fat, low sugar while increasing fish, fruits, vegetables, and whole grains) Control (traditional British diet) |
SBP TC HDL Weight |
Compliant | Adherence to dietary guidelines resulted in:
Diets were “well accepted and did not differ in cost.” |
QoL = Quality of life, MLHF = Minnesota Living with Heart Failure Questionnaire, GDS = Geriatric Depression Scale, SBP = Systolic blood pressure, TC = Total cholesterol.
In chronic kidney disease, articles were identified when they included dietary interventions for chronic kidney disease patients, and a total of 7 articles (n = 637) were included (see Table 6). Commonly utilized diets within these studies were fixed protein, oral NaHCO3, and daily addition of flaxseed oil. Implementation of protein-controlled or nutrient-specific controlled diets resulted in: improved GFR or dialysis-free time (2 studies). Other factors considered in these studies were inflammation markers, urine phosphorus, SBP, and CrCL; however these were not consistent across all articles.
Table 6.
Chronic kidney disease / kidney article summaries.
Author (Year) | N | Study Length | Diet Assignments | Outcomes Assessed | Adherence/Compliance | Key Findings |
---|---|---|---|---|---|---|
Friedman (2014)55 | N = 8 severely obese patients with normal kidney function | 7 days | Fixed protein (50 g/day) | Glomerular filtration rate (GFR) | 100% compliance | GFR was statistically lower after surgery (p < 0.01). Low protein diet did not alter GFR (p = 0.07) |
Goraya (2013)85 | N = 71 Stage 4 CKD patients | 1 year | Oral NaHCO3 daily Base-producing fruits and vegetables |
eGFR PTCO2 Kidney injury Weight SBP |
Not listed | Adherence to base-producing fruits and vegetables resulted in:
|
Moorthi (2014)54 | N = 13 patients with CKD | 4 weeks | 70% plant protein omnivorous diet | Changes in 24 h urine phosphorus | Median = 95% compliance (94% in first two weeks, 97% in last two weeks) | Urine phosphorus significantly decreased by 215 ± 232 mg/day (p < 0.001) |
Piccoli (2016)53 | N = 449 CKD patients | 847 patient-years of observation | Moderately-restricted low protein diet (0.6 g/kg/day of protein) | Dialysis-free time Mortality rates Cost savings |
Compliant | Dialysis-free time for patients with low GFR (≤15 mL/min):
Lower mortality rates than for patients on dialysis:
Calculated cost savings:
|
Tabibi (2017)56 | N = 38 hemodialysis patients | 8 weeks | Flaxseed oil (6 g/day) Control |
Hematologic factors Serum hepcidin concentration |
90% compliance | Adherence to flaxseed oil resulted in:
|
Mirfatahi (2016)86 | N = 34 hemodialysis patients | Inflammation markers Oxidative stress |
Adherence to flaxseed oil:
|
|||
Wada (2015)57 | N = 24 patients with IgA nephropathy | 4–5 days | Hospital diet: 120 mEq sodium, 65 g protein, 1800 kcal of energy Control: home diet |
Differences in creatinine clearance (CrCl) and glomerular filtration rate (GFR) | 100% compliance | Changes in dietary protein intake were correlated with changes in glomerular filtration rate (r = 0.726, p < 0.001) and associated with CrCl |
PTCO2 = Plasma total CO2.
In neurology/cognition, articles were identified when they included dietary interventions for neurologic issues, which included cognition and depression, and a total of 10 articles (n = 5182) were included (see Table 7). Implementation of nutrient-specific diets (often antioxidant or flavonoid-related) resulted in improved cognition (7 articles). Other results varied among studies with benchmarks such as constructional praxis, long-term memory, memory discrimination, and depression, but these were not consistent across all articles.
Table 7.
Cognition article summaries.
Author (Year) | N | Study Length | Diet Assignments | Outcomes Assessed | Adherence/Compliance | Key Findings |
---|---|---|---|---|---|---|
Boespflug (2018)96 | N = 21 adults ages 68 or older with age-related memory decline | 16 weeks | Freeze-dried whole fruit blueberry powder (flavonoids) Placebo powder |
Functional magnetic resonance imaging during a working memory task to examine blood oxygen level-dependent (BOLD) signaling | Assessed but actual rates not provided | Adherence to blueberries resulted in:
There was no impact on working memory enhancement. |
Cardoso (2014)91 | N = 20 older adults with mild cognitive impairment | 6 months | Brazil nuts (selenium) – one Brazil nut daily Control |
Blood selenium concentrations Antioxidant enzymes (erythrocyte glutathione peroxidase (GPx) activity, oxygen radical absorbance capacity, and malondialdehyde) Change in cognition: CERAD neuropsychological battery (animal naming, Boston naming, word list learning, constructional praxis, word list recall, recognition) |
All but 3 patients had ≥85% compliance. | Adherence to the brazil nut diet resulted in:
|
Kent (2017)87 | N = 49 adults ≥70 years with mild-to-moderate dementia | 12 weeks | Cherry Juice 200 mL/day (flavonoid-rich food = anthocyanis) Control (apple juice) |
BP Inflammatory markers (CRP and IL-6) Change in cognition:
|
Unknown | Adherence to the cherry juice resulted in:
Inflammatory markers were not changed. |
McNamara (2018)95 | N = 94 adults ages 62–80 years with mild cognitive decline | 24 weeks | Daily fish oil Daily blueberry (flavonoids) Fish oil + blueberry |
Change in cognition:
|
Assessed but actual rates not provided | Combined had no cognitive improvement. Adherence to fish oil resulted in:
Adherence to blueberries resulted in:
|
Ota (2016)88 | N = 19 adults ≥60 years with no dementia | 1 meal | Ketogenic meal (20 g of medium chain TGs) Control (isocaloric meal) |
Global cognitive score from 3 tests:
|
Compliant | Adherence to the ketogenic meal resulted in:
|
Scott (2017)90 | N = 48 | 6 months | Avocado (Lutein): 135 g/day (approximately 1.33 avocado per day) Control (Potato/chickpeas) |
Serum lutein Macular pigment density Change in cognition:
|
98% compliance | Adherence to the avocado diet resulted in:
|
von Arnim (2013)89 | N = 39 adults 61–87 years with mild/moderate cognitive impairment | 2 months | Micronutrient Supplement (antioxidant, zinc, B vitamin) | Blood levels of vitamins Nutritional status (Mini Nutritional Assessment) |
99% compliance | Adherence to the vitamins resulted in:
|
Martinez-Lapisncina (2013)92 PREDIMED Study |
N = 522 adults at high vascular risk | 6.5 years | Mediterranean diet with EVOO Mediterranean diet with nuts Control (low-fat diet) Mediterranean diet with EVOO Mediterranean diet with nuts Control (low-fat diet) |
Global cognitive performance:
|
Good Good, with Mediterranean diet groups having greater adherence |
Adherence to the Mediterranean diet + EVOO resulted in:
Adherence to the Mediterranean diet + nuts resulted in:
|
Valls-Pedret (2015)93 PREDIMED Study |
N = 447 cognitively healthy older adults | Median = 4.1 years | Change in cognition:
|
Control group:
Adherence to the Mediterranean diet + EVOO resulted in:
Adherence to the Mediterranean diet + nuts resulted in:
|
||
Sáchez-Villegas (2013)94 PREDIMED Study |
N = 3923 adults | Median = 5.4 years |
|
224 new cases of depression Adherence to a MD resulted in no significant association with the risk of developing depression. Adherence to a MD in patients with type 2 diabetes resulted in a significant inverse association with the risk of developing depression (HR = 0.59, 95% CI: 0.36–0.98). |
BP = Blood pressure, TG = triglyceride, RAVLT = Rey Auditory Verbal Learning Test, SOPT = self-ordered pointing task, TMT = trail making test, CRT = Choice Reaction Time, RVIP = Rapid Visual Information Processing, DMS = Delayed Match to Sample, PAL = Paired Associates Learning, SSP = Spatial Span, SSP-R = Spatial Span Reverse, SWM = Spatial Working Memory, SOC = Stocking of Cambridge, CERAD = Consortium to Establish a Registry for Alzheimer's Disease, EVOO = Extra Virgin Olive Oil, MMSE = Mini Mental Status Exam, CDT = Clock Drawing Test, DEX = Dysexecutive Questionnaire.
All included articles had Level A or B methodological quality, indicating that the bias did not invalidate the results. There was a broad range of applicability of the studies, and no studies had a harmful effect. Table 8 breaks down articles by their overall effect in column 4, where there were mostly studies that were clinically meaningful but not conclusive (58.9%, n = 33), and second most clinical meaningful benefit fully demonstrated (33.9%, n = 19).
3.2. Economic impact
After the systematic review was completed, a compilation of changes in clinical outcomes was compiled with ranges of impact (see Table 9). Key findings from the systematic review indicated that providing food to patients resulted in high rates of dietary adherence in heart disease (HTN, HF), diabetes, and CKD. With dietary guidelines adherence, it was observed that HTN was improved through SBP reduction, DBP reduction, and greater control achievement. CV events also were reduced, and patients had improvements in lipids, A1c, and weight loss. Many patients also had resolution of or reduction of the metabolic syndrome criteria.
Table 9.
The economic impact of food provision studies.
Systematic Review Clinical Outcome | Clinical Impact from the Literature | Cost from the Literature | Projected Cost Savings |
---|---|---|---|
Improvement in HTN through the DASH and MD diet adherence |
|
Cost of High BP:
|
More patients are likely to achieve the HTN control. A 21% reduction in CV events97 could result in:
A 30.5% reduction in strokes could result in:
Cost savings over 10 years with adherence to DASH98:
Cost savings by reducing prevalence of HTN:
|
CV event reduction with MD adherence | |||
Adherence to dietary recommendations in heart disease | |||
Lipid improvements with DASH and MD adherence |
|
||
Weight loss or resolution of MetS with DASH or MD diet adherence |
|
Cost of MetS:
|
Resolution of MetS saves $7863 per patient per year. With 111 million patients diagnosed, decreasing MetS by 39% could result in:
|
A1c reduction with low carbohydrate and low calorie diet adherence50, 51, 52,64
Adherence to diets in DM50, 51, 52
|
|
Costs of DM:
|
More patients are likely to lower A1c, particularly below 9% Improving A1c control to <9%65 would result in:
Assuming a 1.5% reduction in A1c,111 the cost savings would be:
If 58 million Americans are prevented from progressing to DM2, lifetime cost savings would range from $480–723 billion |
Adherence to the DASH diet in HF
|
|
Heart Failure Hospitalization Costs:
|
More patients are likely to be >90% adherent. Reducing HF readmissions by 16%,68 would result in cost savings of:
Reducing length of stay from 55 days to 17 days,68 would result in cost savings of:
|
Adherence to recommended dietary intake in CKD |
|
CKD costs per person (Medicare)114:
|
25–50% of ESRD patients are likely to be free from dialysis. Reducing the number of patients on dialysis would result in:
|
BP = Blood pressure, SBP = Systolic blood pressure, HTN = Hypertension, HF = Heart failure, MetS = Metabolic syndrome, A1c = Hemoglobin A1c, DM = Diabetes, CKD = Chronic kidney diease, ESRD = End stage renal disease.
DASH = Dietary Approaches to Stop Hypertension diet, MD = Mediterranean diet.
These findings were then examined in context of the literature. Each of these findings had substantial implications for patient disease progression, morbidity, and mortality as well as healthcare system resource utilization and costs. Literature review showed these outcomes would result in: lower CV event risk (20–30% reduction: $5–11 billion annually), decreased hospitalization costs ($1–8 billion), and lower dialysis rates (25–50% reduction: $14–29 billion annually). For heart failure patients, results include: 16% fewer readmissions and a 38-day shorter length of stay, resulting in a savings of $234,096 per 100 patients (decreased readmissions) and $79,425 per hospitalization. For diabetes, patients were compliant and reduced their A1c (0.9–2.6%). Reducing A1c by 1.5% could result in $11.6–20 billion in savings to the US healthcare system. Further, these reductions often brought A1c levels under 9%, which would result in $1.8 billion in annual savings. In CKD, 25–50% of ESRD patients became dialysis-free, which could lead to $14.7–29.4 billion in annual savings.
4. Discussion
The studies presented within this review indicate that provision of medically-tailored meals may indeed provide a novel strategy to helping patients meet their nutrition goals and thereby improving numerous health outcomes. Patient adherence was high when food or meal items were provided, and patients often experienced reduction in key clinical outcomes, such as decreased weight and BMI, improved A1c, lowered blood pressure, and improved renal function. Dietary modification is a key component of medical therapy in the treatment of many chronic diseases, including diabetes, cardiovascular disease, and chronic kidney disease. Treatment guidelines for these prominent chronic diseases prioritize dietary changes including reduced salt intake, increase fruit and vegetable consumption, and reduced consumption of processed carbohydrates and saturated fats.25, 26., 27, 28 However, the required dietary changes are often complex and inconvenient, especially when multiple comorbidities are present. Additionally, patients are often not equipped with the required knowledge, skills, time, and resources to adequately plan, cook and eat meals that adhere to the recommended diet. Patients in one study with end stage renal disease found that patients' knowledge of their dietary recommendations was often limited, and most patients followed the dietary patterns of their surrounding family members, rather than following guideline-based dietary advice.29 Similar studies have indicated that many patients with diabetes or cardiovascular disease also have limited knowledge of the impact of diet on their conditions.30, 31, 32
As patients experience many barriers to dietary adherence, including limitations in knowledge, health beliefs, and required resources, adherence to dietary recommendations remains low. In a study evaluating the dietary patterns of patients with diabetes, only 22% of sampled patients with type 1 and type 2 diabetes reported adhering to dietary recommendations.33 Other studies have indicated that adherence to dietary recommendations in kidney disease may be as low as 20%.34,35 However, this review indicated that provision of medically-tailored meals (MTM) greatly improves adherence, providing another important tool to influence the treatment of chronic disease, in addition to addressing clinical and economic outcomes. Numerous studies have reported that provision of medically-tailored meals improved adherence to dietary recommendations in heart disease to greater than 90% of included patients.36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49 Similarly, 100% of patients with diabetes who received medically-tailored nutrition were found to be adequately compliant, and 93% reported dietary satisfaction.50, 51, 52 Findings among patients with chronic kidney disease were also similar.53, 54, 55, 56, 57 Clearly, the provision of medically-tailored meals aids in adherence to dietary recommendations, helping patients overcome the barriers they face in adhering to complex dietary recommendations.
Improved adherence to dietary recommendations leads to numerous beneficial health outcomes which has been well documented by the literature presented in this review. Guidelines for the treatment of hypertension and heart failure recommend a reduced sodium diet, often referred to as the DASH diet.8,27 Additionally, the Mediterranean diet has also shown benefit in cardiovascular risk reduction. Both Hikmet et al. and Davis et al. indicated that provision of medically-tailored meals following these dietary recommendations resulted in higher rates of controlled hypertension.38,43 These interventions resulted in significant reductions in both systolic (3.3-12 mmHg reduction) and diastolic blood pressure (1.9–7.8 mmHg reduction).36, 37, 38, 39, 40, 41, 42, 43, 44,58, 59, 60 In some cases, the prevalence of hypertension was reduced by 30%,38 which is substantial considering 73 million Americans are diagnosed with hypertension.
These dietary interventions also resulted in impressive improvements in overall lipid panels, including reductions in LDL and total cholesterol as well as increases in HDL.36,37,41,58,61 The impact of adherence to provided diets reduced lab values and resulted in reduced cardiovascular events, including stroke. These results illustrate the profound impact of adherence to dietary recommendations. As patients were enabled to follow guideline-directed dietary interventions, patients experienced improvements in key risk factors for cardiac complications, including improvements in blood pressure and lipid control. While previous literature has documented the benefits of blood pressure and lipid reductions, the impact of dietary adherence is illustrated in the significant reduction of cardiovascular events.
Dietary adherence also is challenging in diabetes management. Recommended diabetes self-care practices nearly always include dietary recommendations with current guidelines recommending all diabetic patients be referred for personalized nutrition therapy..26 A key goal of nutrition therapy is achieving and maintaining an appropriate body weight. Medically-tailored meals resulted in significant reductions in weight, waist circumference, BMI and body fat percentage.37,44,45,63 Of note, these dietary changes also resulted in reduced severity of metabolic syndrome as well as increased odds of resolution of this common condition. Additionally, provision of low carbohydrate and low calorie diets resulted in A1c reductions comparable to many prominent medication therapies, reducing A1c by 0.9–2.6%.50, 51, 52,64 Improvements in A1c control impact many health outcomes including reductions in hospitalizations as well as microvascular and macrovascular complications.65,66 This novel approach to nutrition where healthcare professionals provide meals to patients is promising with documented improvements in A1c and weight control, offering a new mode of treatment to prevent and/or minimize progression and complications of diabetes.
Patients with chronic kidney disease are often asked to follow complex dietary restrictions, including reduced salt and protein intake. In addition, these patients often suffer from other comorbidities including hypertension and diabetes, complicating their dietary needs even further. This review indicated that provision of medically-tailored meals can overcome this barrier and ultimately delay progression of disease. Piccoli et al. indicated that providing nutrition that followed dietary recommendations aided in delay of progression to dialysis even in patients with GFR less than 15. In this study, 50% of patients remained dialysis-free after 2 years, and further, 25% were still dialysis free after five years.53 This finding is significant, as dialysis imposes a heavy burden on both the patient and the healthcare system. The benefit of meal provision is further demonstrated in this study by significant decreases in mortality rates in patients receiving medically-tailored nutrition.
While the benefit of medically-tailored meals is clear in terms of health outcomes, the economic implications are harder to quantify. Improvements in key health markers, such as decreases in blood pressure and A1c, most often lead to improvements in health outcomes, including decreases in cardiovascular events or other complications. Costs of these complications are high with the average three-year cost of an MI or stroke ranging from $71,600–$73,300.67 The cost savings associated with reduction in cardiovascular events and strokes can range from $3.8 – $4.9 billion annually. While it cannot be assumed that medically-tailored meals will directly result in these cost savings, these costs certainly illustrate the potential economic impact of simple lifestyle improvements.
Meal provision represents a novel approach to chronic disease therapy with the potential for impressive implications for health outcomes and economic savings. Just as evidence-based medications and therapies are selected and covered by both commercial and private insurance, medically-tailored meals could be considered as a reimbursable service for patients with chronic disease, as further evidence builds regarding the impact of nutrition on health outcomes. In addition, the coverage of these services may represent an avenue for cost savings for insurance companies as healthcare costs continue to increase due to the burden of chronic disease.
When patients adhere to lifestyle changes, there are substantial patient clinical benefits as well as economic benefits. With costs in the healthcare system still rising, how do we position patients for better adherence and observe better clinical and economic outcomes? An excellent example from the literature that was published after the closure of the systematic review time period illustrates this point. Hummel and colleagues (2018) randomly distributed HF patients at discharge to usual care or HF-appropriate delivered meals. Even though the differences between groups were not significant, at 12 weeks, patients who received meals had improved cardiomyopathy clinical summary scores, fewer HF readmissions (11% vs 27% in the control group), and fewer days of rehospitalization (17 vs 55 days for the control group).68 While limited inferences can be done from this short-term study due to its non-significance, this could be an area for further exploration.
5. Limitations
This review does have several limitations. While all included studies did provide some element of the subjects' diets, studies regarding complete meal delivery are rare. Many of these studies required patients to prepare their own meals and measured dietary intake based on dietary recall. This indicates that actual dietary intake may have varied from that which was reported. Secondly, many potentially relevant studies were excluded because meals were not directly provided by the researchers. Many other studies investigating the impact of diet and nutrition on economic and health outcomes were not included due to the observational nature of their design. Additionally, only studies written in the English language were included in the review, which could introduce bias, as key studies with positive or negative findings could be missed. Lastly, cost was not directly evaluated in the included studies. To date, there are few studies that quantify the costs associated with medically-tailored meals compared to the financial implications of nutrition on health outcomes. This review sought to investigate the economic impact of meal provision by comparing the improvements in health to the known costs of chronic disease. While this is not a direct representation of the true cost of meal delivery versus cost-savings in terms of health outcomes, it illustrates the potential benefit of medically-tailored meals and the need for further study in this area.
6. Conclusion
It is easier and less costly to prevent disease-based complications and progression than to manage acute issues. The healthcare system and healthcare professionals need to consider evolving strategies to empower patients to be part of the solution. Many Medicare Advantage and private insurance plans are beginning to cover medically-tailored meals, and with expanded access and a consistent structure, more data will be available to study the impact of dietary adherence on patient clinical and economic outcomes. What is clear is that providing medically-tailored meals to patients with chronic disease needs results in improved adherence, and when patients are adherence, clinical outcomes improve.
Disclosures
Aleda M. H. Chen and Juanita Draime received no funding for this project. Sarah Berman and Julia Gardner were funded as student research assistants through this project. At the time of writing, Joe Martinez was the President of Healthy Meals Supreme, LLC.
Contributor Information
Aleda M.H. Chen, Email: amchen@cedarville.edu.
Juanita A. Draime, Email: juanitaadraime@cedarville.edu.
Sarah Berman, Email: sberman@cedarville.edu.
Julia Gardner, Email: jcgardner@cedarville.edu.
Zach Krauss, Email: amchen@cedarville.edu.
References
- 1.Center for Medicare and Medicaid Services NHE Fact Sheet. 2018. https://www.cms.gov/research-statistics-data-and-systems/statistics-trends-and-reports/nationalhealthexpenddata/nhe-fact-sheet.html Accessed October 2, 2020.
- 2.Centers for Disease Control Heath and Economic Costs of Chronic Diseases. 2018. https://www.cdc.gov/chronicdisease/about/costs/index.htm Accessed October 2, 2020.
- 3.Tarride J.-E., Lim M., DesMeules M., et al. A review of the cost of cardiovascular disease. Can J Cardiol. 2009;25(6):e195–e202. doi: 10.1016/s0828-282x(09)70098-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.American Heart Association Cardiovascular Disease: A Costly Burden for America. Projections Through 2035. 2017. http://www.heart.org/idc/groups/heart-public/@wcm/@adv/documents/downloadable/ucm_491543.pdf Accessed October 2, 2020.
- 5.Garvey W.T., Mechanick J.I., Brett E.M., et al. American Association of Clinical Endocrinologist and American College of endocrinology comprehensive clinical practice guidelines for medical care of patients with obesity. Endocr Pract. 2016;22(S3):1–203. doi: 10.4158/EP161365.GL. [DOI] [PubMed] [Google Scholar]
- 6.Centers for Disease Control Obesity and Overweight. 2017. https://www.cdc.gov/nchs/fastats/obesity-overweight.htm Accessed October 2, 2020.
- 7.American Diabetes Association The Cost of Diabetes. 2018. http://www.diabetes.org/advocacy/news-events/cost-of-diabetes.html Accessed October 2, 2020.
- 8.Yancy C.W., Jessup M., Bozkurt B., et al. 2017 ACC/AHA/HFSA focused update of the 2013 ACCF/AHA guideline for the management of heart failure: a report of the American College of Cardiology/American Heart Association task force on clinical practice guidelines and the Heart Failure Society of America. J Am Coll Cardiol. 2017;70(6):776–803. doi: 10.1016/j.jacc.2017.04.025. [DOI] [PubMed] [Google Scholar]
- 9.Whelton P.K., Appel L.J., Sacco R.L., et al. Sodium, blood pressure, and cardiovascular disease: further evidence supporting the American Heart Association sodium reduction recommendations. Circulation. 2012;126(24):2880–2889. doi: 10.1161/CIR.0b013e318279acbf. [DOI] [PubMed] [Google Scholar]
- 10.American Diabetes Association 4. Lifestyle management: Standards of medical care in diabetes—2018. Diabetes Care. 2018;41(Supplement 1):S38–S50. doi: 10.2337/dc18-S004. [DOI] [PubMed] [Google Scholar]
- 11.Garber A.J., Abrahamson M.J., Barzilay J.I., et al. Consensus statement by the American Association of Clinical Endocrinologists and American College of endocrinology on the comprehensive type 2 diabetes management algorithm - 2018 executive summary. Endocr Pract. 2018;24(1):91–120. doi: 10.4158/CS-2017-0153. [DOI] [PubMed] [Google Scholar]
- 12.Academy of Nutrition and Dietetics Chronic Kidney Disease (CKD) Guideline. 2010. https://www.andeal.org/topic.cfm?menu=5303&cat=3927 Accessed October 2, 2020.
- 13.Best Practice Advocacy Centre New Zealand Strategies to Improve Nutrition in Elderly People. 2011. https://bpac.org.nz/bpj/2011/may/elderly.aspx
- 14.Fakhouri T.H., Ogden C.L., Carroll M.D., et al. National Center for Health Statistics; Hyattsville, MD: 2012. Prevalence of Obesity Among Older Adults in the United States, 2007–2010. NCHS Data Brief, no 106. [PubMed] [Google Scholar]
- 15.Dansinger M.L., Gleason J., Griffith J.L., Selker H.P., Schaefer E.J. Comparison of the Atkins, Ornish, weight watchers, and zone diets for weight loss and heart disease risk reduction: a randomized trial. J Am Med Assoc. 2005;293(1):43–53. doi: 10.1001/jama.293.1.43. [DOI] [PubMed] [Google Scholar]
- 16.Middleton K.R., Anton S.D., Perri M.G. Long-term adherence to health behavior change. Am J Lifestyle Med. 2013;7(6):395–404. doi: 10.1177/1559827613488867. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Cha E., Kim K.H., Lerner H.M., et al. Health literacy, self-efficacy, food label use, and diet in young adults. Am J Health Behav. 2014;38(3):331–339. doi: 10.5993/AJHB.38.3.2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.La Puma J. What is culinary medicine and what does it do? Popul Health Manag. 2016;19(1):1–3. doi: 10.1089/pop.2015.0003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Khan T., Tsipas S., Wozniak G. Medical care expenditures for individuals with prediabetes: the potential cost savings in reducing the risk of developing diabetes. Popul Health Manag. 2017;20(5):389–396. doi: 10.1089/pop.2016.0134. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.American Medical Association AMA DPP Cost Calculator. 2015. https://ama-roi-calculator.appspot.com/ Accessed October 2, 2020.
- 21.Weintraub W.S., Daniels S.R., Burke L.E., et al. Value of primordial and primary prevention for cardiovascular disease. Circulation. 2011;124(8):967–990. doi: 10.1161/CIR.0b013e3182285a81. [DOI] [PubMed] [Google Scholar]
- 22.Moher D., Liberati A., Tetlaff J., Altman D., The PRISMA Group Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Med. 2009;6(7) doi: 10.1371/journal.pmed.1000097. e1000097. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Chen A.M.H., Draime J.A., Gardner J., Berman S., Martinez J.B. PROSPERO 2019 CRD42019116570. 2019. A systematic review of the clinical and economic outcomes associated with guideline-recommended food provision studies in heart disease, diabetes, chronic kidney disease, Alzheimer’s disease, and older adults.http://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42019116570 [Google Scholar]
- 24.Lichtenstein A.H. In: Handbook of Clinical Nutrition and Aging. 3rd ed. Bales C.W., Locher J.L., Saltzman E., editors. Humana Press; New York: 2015. Systematic reviews in the field of nutrition; pp. 21–35. [Google Scholar]
- 25.Yancy C.W., Jessup M., Bozkurt B., et al. 2017 ACC/AHA/HFSA focused update of the 2013 ACCF/AHA guideline for the management of heart failure. J Card Fail. 2017;23(8):628–651. doi: 10.1016/j.cardfail.2017.04.014. [DOI] [PubMed] [Google Scholar]
- 26.American Diabetes Association 5. Lifestyle management: Standards of medical care in diabetes—2019. Diabetes Care. 2019;42(Supplement 1):S46–S60. doi: 10.2337/dc19-S005. [DOI] [PubMed] [Google Scholar]
- 27.Whelton P.K., Carey R.M., Aronow W.S., et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: a report of the American College of Cardiology/American Heart Association task force on clinical practice guidelines. J Am Coll Cardiol. 2018;71(19):e127–e248. doi: 10.1016/j.jacc.2017.11.006. [DOI] [PubMed] [Google Scholar]
- 28.Kopple J.D. National kidney foundation K/DOQI clinical practice guidelines for nutrition in chronic renal failure. Am J Kidney Dis. 2001;37(1 Suppl 2):S66–S70. doi: 10.1053/ajkd.2001.20748. [DOI] [PubMed] [Google Scholar]
- 29.Dulal S.L., Thakurathi M.T., Dulal R.K., Karki S., Raut K.B. Dietary practice among the patients with end stage renal disease undergoing maintenance haemodialysis. J Nepal Med Assoc. 2018;56(213):830–836. doi: 10.31729/jnma.3723. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Breen C., Ryan M., Gibney M.J., O’Shea D. Diabetes-related nutrition knowledge and dietary intake among adults with type 2 diabetes. Br J Nutr. 2015;114(3):439–447. doi: 10.1017/S0007114515002068. [DOI] [PubMed] [Google Scholar]
- 31.Ni H., Nauman D., Burgess D., Wise K., Crispell K., Hershberger R.E. Factors influencing knowledge of and adherence to self-care among patients with heart failure. Arch Intern Med. 1999;159(14):1613–1619. doi: 10.1001/archinte.159.14.1613. [DOI] [PubMed] [Google Scholar]
- 32.Heo S., Lennie T.A., Moser D.K., Okoli C. Heart failure patients’ perceptions on nutrition and dietary adherence. Eur J Cardiovasc Nurs. 2009;8(5):323–328. doi: 10.1016/j.ejcnurse.2009.05.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Broadbent E., Donkin L., Stroh J.C. Illness and treatment perceptions are associated with adherence to medications, diet, and exercise in diabetic patients. Diabetes Care. 2011;34(2):338–340. doi: 10.2337/dc10-1779. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Paes-Barreto J.G., Silva M.I., Qureshi A.R., et al. Can renal nutrition education improve adherence to a low-protein diet in patients with stages 3 to 5 chronic kidney disease? J Ren Nutr. 2013;23(3):164–171. doi: 10.1053/j.jrn.2012.10.004. [DOI] [PubMed] [Google Scholar]
- 35.Cianciaruso B., Pota A., Pisani A., et al. Metabolic effects of two low protein diets in chronic kidney disease stage 4–5--a randomized controlled trial. Nephrol Dial Transplant. 2008;23(2):636–644. doi: 10.1093/ndt/gfm576. [DOI] [PubMed] [Google Scholar]
- 36.Casas R., Sacanella E., Urpi-Sarda M., et al. The effects of the Mediterranean diet on biomarkers of vascular wall inflammation and plaque vulnerability in subjects with high risk for cardiovascular disease. A randomized trial. PLoS One. 2014;9(6) doi: 10.1371/journal.pone.0100084. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Casas R., Sacanella E., Urpi-Sarda M., et al. Long-term immunomodulatory effects of a Mediterranean diet in adults at high risk of cardiovascular disease in the PREvencion con DIeta MEDiterranea (PREDIMED) randomized controlled trial. J Nutr. 2016;146(9):1684–1693. doi: 10.3945/jn.115.229476. [DOI] [PubMed] [Google Scholar]
- 38.Hikmat F., Appel L.J. Effects of the DASH diet on blood pressure in patients with and without metabolic syndrome: results from the DASH trial. J Hum Hypertens. 2014;28(3):170–175. doi: 10.1038/jhh.2013.52. [DOI] [PubMed] [Google Scholar]
- 39.Roussell M.A., Hill A.M., Gaugler T.L., et al. Effects of a DASH-like diet containing lean beef on vascular health. J Hum Hypertens. 2014;28(10):600–605. doi: 10.1038/jhh.2014.34. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Sayer R.D., Wright A.J., Chen N., Campbell W.W. Dietary approaches to stop hypertension diet retains effectiveness to reduce blood pressure when lean pork is substituted for chicken and fish as the predominant source of protein. Am J Clin Nutr. 2015;102(2):302–308. doi: 10.3945/ajcn.115.111757. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Medina-Remon A., Casas R., Tressserra-Rimbau A., et al. Polyphenol intake from a Mediterranean diet decreases inflammatory biomarkers related to atherosclerosis: a substudy of the PREDIMED trial. Br J Clin Pharmacol. 2017;83(1):114–128. doi: 10.1111/bcp.12986. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Toledo E., Hu F.B., Estruch R., et al. Effect of the Mediterranean diet on blood pressure in the PREDIMED trial: results from a randomized controlled trial. BMC Med. 2013;11:207. doi: 10.1186/1741-7015-11-207. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Davis C.R., Hodgson J.M., Woodman R., Bryan J., Wilson C., Murphy K.J. A Mediterranean diet lowers blood pressure and improves endothelial function: results from the MedLey randomized intervention trial. Am J Clin Nutr. 2017;105(6):1305–1313. doi: 10.3945/ajcn.116.146803. [DOI] [PubMed] [Google Scholar]
- 44.Kirwan J.P., Malin S.K., Scelsi A.R., et al. A whole-grain diet reduces cardiovascular risk factors in overweight and obese adults: a randomized controlled trial. J Nutr. 2016;146(11):2244–2251. doi: 10.3945/jn.116.230508. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Jenkins D.J.A., Boucher B.A., Ashbury F.D., et al. Effect of current dietary recommendations on weight loss and cardiovascular risk factors. J Am Coll Cardiol. 2017;69(9):1103–1112. doi: 10.1016/j.jacc.2016.10.089. [DOI] [PubMed] [Google Scholar]
- 46.Haring B., Wyler von Ballmoos M.C., Appel L.J., Sacks F.M. Healthy dietary interventions and lipoprotein (a) plasma levels: results from the Omni heart trial. PLoS One. 2014;9(12):e114859. doi: 10.1371/journal.pone.0114859. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Castaner O., Corella D., Covas M.I., et al. In vivo transcriptomic profile after a Mediterranean diet in high-cardiovascular risk patients: a randomized controlled trial. Am J Clin Nutr. 2013;98(3):845–853. doi: 10.3945/ajcn.113.060582. [DOI] [PubMed] [Google Scholar]
- 48.Fito M., Estruch R., Salas-Salvado J., et al. Effect of the Mediterranean diet on heart failure biomarkers: a randomized sample from the PREDIMED trial. Eur J Heart Fail. 2014;16(5):543–550. doi: 10.1002/ejhf.61. [DOI] [PubMed] [Google Scholar]
- 49.Davis C.R., Bryan J., Hodgson J.M., Woodman R., Murphy K.J. A Mediterranean diet reduces F2-isoprostanes and triglycerides among older Australian men and women after 6 months. J Nutr. 2017;147(7):1348–1355. doi: 10.3945/jn.117.248419. [DOI] [PubMed] [Google Scholar]
- 50.Goday A., Bellido D., Sajoux I., et al. Short-term safety, tolerability and efficacy of a very low-calorie-ketogenic diet interventional weight loss program versus hypocaloric diet in patients with type 2 diabetes mellitus. Nutrition & diabetes. 2016;6(9) doi: 10.1038/nutd.2016.36. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Brinkworth G.D., Wycherley T.P., Noakes M., Buckley J.D., Clifton P.M. Long-term effects of a very-low-carbohydrate weight-loss diet and an isocaloric low-fat diet on bone health in obese adults. Nutrition. 2016;32(9):1033–1036. doi: 10.1016/j.nut.2016.03.003. [DOI] [PubMed] [Google Scholar]
- 52.Tay J., Luscombe-Marsh N.D., Thompson C.H., et al. A very low-carbohydrate, low–saturated fat diet for type 2 diabetes management: a randomized trial. Diabetes Care. 2014;37(11):2909–2918. doi: 10.2337/dc14-0845. [DOI] [PubMed] [Google Scholar]
- 53.Piccoli G.B., Nazha M., Capizzi I., et al. Patient survival and costs on moderately restricted low-protein diets in advanced CKD: equivalent survival at lower costs? Nutrients. 2016;8(12):758. doi: 10.3390/nu8120758. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Moorthi R.N., Armstrong C.L., Janda K., Ponsler-Sipes K., Asplin J.R., Moe S.M. The effect of a diet containing 70% protein from plants on mineral metabolism and musculoskeletal health in chronic kidney disease. Am J Nephrol. 2014;40(6):582–591. doi: 10.1159/000371498. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Friedman A.N., Quinney S.K., Inman M., Mattar S.G., Shihabi Z., Moe S. Influence of dietary protein on glomerular filtration before and after bariatric surgery: a cohort study. Am J Kidney Dis. 2014;63(4):598–603. doi: 10.1053/j.ajkd.2013.11.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56.Tabibi H., Mirfatahi M., Hedayati M., Nasrollahi A. Effects of flaxseed oil on blood hepcidin and hematologic factors in hemodialysis patients. Hemodial Int. 2017;21(4):549–556. doi: 10.1111/hdi.12516. [DOI] [PubMed] [Google Scholar]
- 57.Wada T., Nakao T., Matsumoto H., et al. Relationship between dietary protein intake and the changes in creatinine clearance and glomerular cross-sectional area in patients with IgA nephropathy. Clin Exp Nephrol. 2015;19(4):661–668. doi: 10.1007/s10157-014-1055-1. [DOI] [PubMed] [Google Scholar]
- 58.Hill A.M., Harris Jackson K.A., Roussell M.A., West S.G., Kris-Etherton P.M. Type and amount of dietary protein in the treatment of metabolic syndrome: a randomized controlled trial. Am J Clin Nutr. 2015;102(4):757–770. doi: 10.3945/ajcn.114.104026. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 59.Hummel S.L., Seymour E.M., Brook R.D., et al. Low-sodium DASH diet improves diastolic function and ventricular-arterial coupling in hypertensive heart failure with preserved ejection fraction. Circ Heart Fail. 2013;6(6):1165–1171. doi: 10.1161/CIRCHEARTFAILURE.113.000481. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60.Juraschek S.P., Miller E.R., 3rd, Weaver C.M., Appel L.J. Effects of sodium reduction and the DASH diet in relation to baseline blood pressure. J Am Coll Cardiol. 2017;70(23):2841–2848. doi: 10.1016/j.jacc.2017.10.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 61.Ruscica M., Pavanello C., Gandini S., et al. Effect of soy on metabolic syndrome and cardiovascular risk factors: a randomized controlled trial. Eur J Nutr. 2018;57(2):499–511. doi: 10.1007/s00394-016-1333-7. [DOI] [PubMed] [Google Scholar]
- 62.Estruch R., Ros E., Salas-Salvadó J., et al. Primary prevention of cardiovascular disease with a Mediterranean diet supplemented with extra-virgin olive oil or nuts. New Engl J Med. 2018;378(25) doi: 10.1056/NEJMoa1800389. [DOI] [PubMed] [Google Scholar]
- 63.Richard C., Couture P., Desroches S., Lamarche B. Effect of the Mediterranean diet with and without weight loss on markers of inflammation in men with metabolic syndrome. Obesity (Silver Spring, Md) 2013;21(1):51–57. doi: 10.1002/oby.20239. [DOI] [PubMed] [Google Scholar]
- 64.Farrer O., Golley R. Feasibility study for efficacy of group weight management programmes achieving therapeutic weight loss in people with type 2 diabetes. Nutrition & Dietetics. 2014;71(1):16–21. [Google Scholar]
- 65.Wilf-Miron R., Bolotin A., Gordon N., Porath A., Peled R. The association between improved quality diabetes indicators, health outcomes and costs: towards constructing a “business case” for quality of diabetes care--a time series study. BMC Endocr Disord. 2014;14:92. doi: 10.1186/1472-6823-14-92. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66.Nathan D.M., Group DER The diabetes control and complications trial/epidemiology of diabetes interventions and complications study at 30 years: overview. Diabetes Care. 2014;37(1):9–16. doi: 10.2337/dc13-2112. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 67.O’Sullivan A.K., Rubin J., Nyambose J., Kuznik A., Cohen D.J., Thompson D. Cost estimation of cardiovascular disease events in the US. Pharmacoeconomics. 2011;29(8):693–704. doi: 10.2165/11584620-000000000-00000. [DOI] [PubMed] [Google Scholar]
- 68.Hummel S.L., Karmally W., Gillespie B.W., et al. Home-delivered meals postdischarge from heart failure hospitalization: the GOURMET-HF pilot study. Circulation. Heart Failure. 2018;11(8):e004886. doi: 10.1161/CIRCHEARTFAILURE.117.004886. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 69.Camps S.G., Kaur B., Quek R.Y.C., Henry C.J. Does the ingestion of a 24 hour low glycaemic index Asian mixed meal diet improve glycaemic response and promote fat oxidation? A controlled, randomized cross-over study. Nutr J. 2017;16(1):43. doi: 10.1186/s12937-017-0258-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 70.Gower B.A., Goss A.M. A lower-carbohydrate, higher-fat diet reduces abdominal and intermuscular fat and increases insulin sensitivity in adults at risk of type 2 diabetes. J Nutr. 2015;145(1):177S–183S. doi: 10.3945/jn.114.195065. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 71.Gu Y., Zhao A., Huang F., et al. Very low carbohydrate diet significantly alters the serum metabolic profiles in obese subjects. J Proteome Res. 2013;12(12):5801–5811. doi: 10.1021/pr4008199. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 72.Urbanova M., Mraz M., Durovcova V., et al. The effect of very-low-calorie diet on mitochondrial dysfunction in subcutaneous adipose tissue and peripheral monocytes of obese subjects with type 2 diabetes mellitus. Physiol Res. 2017;66(5):811–822. doi: 10.33549/physiolres.933469. [DOI] [PubMed] [Google Scholar]
- 73.Johansson-Persson A., Ulmius M., Cloetens L., Karhu T., Herzig K.H., Onning G. A high intake of dietary fiber influences C-reactive protein and fibrinogen, but not glucose and lipid metabolism, in mildly hypercholesterolemic subjects. Eur J Nutr. 2014;53(1):39–48. doi: 10.1007/s00394-013-0496-8. [DOI] [PubMed] [Google Scholar]
- 74.Estruch R., Ros E., Salas-Salvado J., et al. Primary prevention of cardiovascular disease with a Mediterranean diet. N Engl J Med. 2013;368(14):1279–1290. doi: 10.1056/NEJMoa1200303. [DOI] [PubMed] [Google Scholar]
- 75.De Lorenzo A., Bernardini S., Gualtieri P., et al. Mediterranean meal versus Western meal effects on postprandial ox-LDL, oxidative and inflammatory gene expression in healthy subjects: a randomized controlled trial for nutrigenomic approach in cardiometabolic risk. Acta Diabetol. 2017;54(2):141–149. doi: 10.1007/s00592-016-0917-2. [DOI] [PubMed] [Google Scholar]
- 76.Gomez-Delgado F., Garcia-Rios A., Alcala-Diaz J.F., et al. Chronic consumption of a low-fat diet improves cardiometabolic risk factors according to the CLOCK gene in patients with coronary heart disease. Mol Nutr Food Res. 2015;59(12):2556–2564. doi: 10.1002/mnfr.201500375. [DOI] [PubMed] [Google Scholar]
- 77.Richard C., Couture P., Ooi E.M., et al. Effect of Mediterranean diet with and without weight loss on apolipoprotein B100 metabolism in men with metabolic syndrome. Arterioscler Thromb Vasc Biol. 2014;34(2):433–438. doi: 10.1161/ATVBAHA.113.302185. [DOI] [PubMed] [Google Scholar]
- 78.Anbar R., Beloosesky Y., Cohen J., et al. Tight calorie control in geriatric patients following hip fracture decreases complications: a randomized, controlled study. Clinical Nutrition (Edinburgh, Scotland) 2014;33(1):23–28. doi: 10.1016/j.clnu.2013.03.005. [DOI] [PubMed] [Google Scholar]
- 79.Kitzman D.W., Brubaker P., Morgan T., et al. Effect of caloric restriction or aerobic exercise training on peak oxygen consumption and quality of life in obese older patients with heart failure with preserved ejection fraction: a randomized clinical trial. J Am Med Assoc. 2016;315(1):36–46. doi: 10.1001/jama.2015.17346. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 80.Collins J., Porter J., Truby H., Huggins C.E. A foodservice approach to enhance energy intake of elderly subacute patients: a pilot study to assess impact on patient outcomes and cost. Age Ageing. 2017;46(3):486–493. doi: 10.1093/ageing/afw238. [DOI] [PubMed] [Google Scholar]
- 81.Aparicio A., Robles F., Lopez-Sobaler A.M., Ortega R.M. Dietary glycaemic load and odds of depression in a group of institutionalized elderly people without antidepressant treatment. Eur J Nutr. 2013;52(3):1059–1066. doi: 10.1007/s00394-012-0412-7. [DOI] [PubMed] [Google Scholar]
- 82.Denissen K.F., Janssen L.M., Eussen S.J., et al. Delivery of nutritious meals to elderly receiving home care: feasibility and effectiveness. J Nutr Health Aging. 2017;21(4):370–380. doi: 10.1007/s12603-016-0790-2. [DOI] [PubMed] [Google Scholar]
- 83.Reidlinger D.P., Darzi J., Hall W.L., Seed P.T., Chowienczyk P.J., Sanders T.A. How effective are current dietary guidelines for cardiovascular disease prevention in healthy middle-aged and older men and women? A randomized controlled trial. Am J Clin Nutr. 2015;101(5):922–930. doi: 10.3945/ajcn.114.097352. [DOI] [PubMed] [Google Scholar]
- 84.Daly R.M., O’Connell S.L., Mundell N.L., Grimes C.A., Dunstan D.W., Nowson C.A. Protein-enriched diet, with the use of lean red meat, combined with progressive resistance training enhances lean tissue mass and muscle strength and reduces circulating IL-6 concentrations in elderly women: a cluster randomized controlled trial. Am J Clin Nutr. 2014;99(4):899–910. doi: 10.3945/ajcn.113.064154. [DOI] [PubMed] [Google Scholar]
- 85.Goraya N., Simoni J., Jo C.H., Wesson D.E. A comparison of treating metabolic acidosis in CKD stage 4 hypertensive kidney disease with fruits and vegetables or sodium bicarbonate. Clinical Journal of the American Society of Nephrology : CJASN. 2013;8(3):371–381. doi: 10.2215/CJN.02430312. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 86.Mirfatahi M., Tabibi H., Nasrollahi A., Hedayati M., Taghizadeh M. Effect of flaxseed oil on serum systemic and vascular inflammation markers and oxidative stress in hemodialysis patients: a randomized controlled trial. Int Urol Nephrol. 2016;48(8):1335–1341. doi: 10.1007/s11255-016-1300-5. [DOI] [PubMed] [Google Scholar]
- 87.Kent K., Charlton K., Roodenrys S., et al. Consumption of anthocyanin-rich cherry juice for 12 weeks improves memory and cognition in older adults with mild-to-moderate dementia. Eur J Nutr. 2017;56(1):333–341. doi: 10.1007/s00394-015-1083-y. [DOI] [PubMed] [Google Scholar]
- 88.Ota M., Matsuo J., Ishida I., et al. Effect of a ketogenic meal on cognitive function in elderly adults: potential for cognitive enhancement. Psychopharmacology. 2016;233(21−22):3797–3802. doi: 10.1007/s00213-016-4414-7. [DOI] [PubMed] [Google Scholar]
- 89.von Arnim C.A., Dismar S., Ott-Renzer C.S., Noeth N., Ludolph A.C., Biesalski H.K. Micronutrients supplementation and nutritional status in cognitively impaired elderly persons: a two-month open label pilot study. Nutr J. 2013;12(1):148. doi: 10.1186/1475-2891-12-148. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 90.Scott T.M., Rasmussen H.M., Chen O., Johnson E.J. Avocado consumption increases macular pigment density in older adults: a randomized, controlled trial. Nutrients. 2017;9(9):919. doi: 10.3390/nu9090919. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 91.Rita Cardoso B., Apolinario D., da Silva Bandeira V., et al. Effects of Brazil nut consumption on selenium status and cognitive performance in older adults with mild cognitive impairment: a randomized controlled pilot trial. Eur J Nutr. 2016;55(1):107–116. doi: 10.1007/s00394-014-0829-2. [DOI] [PubMed] [Google Scholar]
- 92.Martinez-Lapiscina E.H., Clavero P., Toledo E., et al. Mediterranean diet improves cognition: the PREDIMED-NAVARRA randomised trial. J Neurol Neurosurg Psychiatry. 2013;84(12):1318–1325. doi: 10.1136/jnnp-2012-304792. [DOI] [PubMed] [Google Scholar]
- 93.Valls-Pedret C., Sala-Vila A., Serra-Mir M., et al. Mediterranean diet and age-related cognitive decline: a randomized clinical trial. JAMA Intern Med. 2015;175(7):1094–1103. doi: 10.1001/jamainternmed.2015.1668. [DOI] [PubMed] [Google Scholar]
- 94.Sánchez-Villegas A., Martínez-González M.A., Estruch R., et al. Mediterranean dietary pattern and depression: the PREDIMED randomized trial. BMC Med. 2013;11(1):208. doi: 10.1186/1741-7015-11-208. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 95.McNamara R.K., Kalt W., Shidler M.D., et al. Cognitive response to fish oil, blueberry, and combined supplementation in older adults with subjective cognitive impairment. Neurobiol Aging. 2018;64:147–156. doi: 10.1016/j.neurobiolaging.2017.12.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 96.Boespflug E.L., Eliassen J.C., Dudley J.A., et al. Enhanced neural activation with blueberry supplementation in mild cognitive impairment. Nutr Neurosci. 2018;21(4):297–305. doi: 10.1080/1028415X.2017.1287833. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 97.Lee J.H., Kim S.-H., Kang S.-H., et al. Blood pressure control and cardiovascular outcomes: real-world implications of the 2017 ACC/AHA hypertension guideline. Nat Sci Rep. 2018;8(1) doi: 10.1038/s41598-018-31549-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 98.Erlinger T.P., Vollmer W.M., Svetkey L.P., Appel L.J. The potential impact of nonpharmacologic population-wide blood pressure reduction on coronary heart disease events: pronounced benefits in African-Americans and hypertensives. Prev Med. 2003;37(4):327–333. doi: 10.1016/s0091-7435(03)00140-3. [DOI] [PubMed] [Google Scholar]
- 99.Palar K., Sturm R. Potential societal savings from reduced sodium consumption in the U.S. adult population. Am J Health Promot. 2009;24(1):49–57. doi: 10.4278/ajhp.080826-QUAN-164. [DOI] [PubMed] [Google Scholar]
- 100.Goetzel R.Z., Pei X., Tabrizi M.J., et al. Ten modifiable health risk factors are linked to more than one-fifth of employer-employee health care spending. Health Aff. 2012;31(11):2474–2484. doi: 10.1377/hlthaff.2011.0819. [DOI] [PubMed] [Google Scholar]
- 101.Torio C.M., Moore B.J. 2013. Statistical Brief #204. National Inpatient Hospital Costs: The Most Expensive Conditions by Payer. Rockville, Maryland 2016. [PubMed] [Google Scholar]
- 102.Vernon S. How Much Would a Heart Attack Cost you? 2010. https://www.cbsnews.com/news/how-much-would-a-heart-attack-cost-you/
- 103.Dunlay S.M., Shah N.D., Shi Q., et al. Lifetime costs of medical care after heart failure diagnosis. Circulation: Cardiovascular Quality and Outcomes. 2011;4(1):68–75. doi: 10.1161/CIRCOUTCOMES.110.957225. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 104.Wang G., Zhang Z., Ayala C., Dunet D.O., Fang J., George M.G. Costs of hospitalization for stroke patients aged 18-64 years in the United States. J Stroke Cerebrovasc Dis. 2014;23(5):861–868. doi: 10.1016/j.jstrokecerebrovasdis.2013.07.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 105.Cardoso R., Vaishnav J., Martin S.S., Blumenthal R.S. How Low Should we Decrease LDL-Cholesterol in a Cost-Effective Manner? 2018. https://www.acc.org/latest-in-cardiology/articles/2018/02/16/09/31/how-low-should-we-decrease-ldl-cholesterol-in-a-cost-effective-manner
- 106.Moore J.X., Chaudhary N., Akinyemiju T. Metabolic syndrome prevalence by race/ethnicity and sex in the United States, National Health and nutrition examination survey, 1988-2012. Prev Chronic Dis. 2017;14:E24. doi: 10.5888/pcd14.160287. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 107.Curtis L.H., Hammill B.G., Bethel M.A., Anstrom K.J., Gottdiener J.S., Schulman K.A. Costs of the metabolic syndrome in elderly individuals: findings from the cardiovascular health study. Diabetes Care. 2007;30(10):2553–2558. doi: 10.2337/dc07-0460. [DOI] [PubMed] [Google Scholar]
- 108.Courtemanche T., Mansueto G., Hodach R., Handmaker K. Population health approach for diabetic patients with poor A1c control. Am J Manag Care. 2013;19(6):465–472. [PubMed] [Google Scholar]
- 109.Liese A.D., Nichols M., Sun X., D’Agostino R.B., Haffner S.M. Adherence to the DASH diet is inversely associated with incidence of type 2 diabetes: the insulin resistance atherosclerosis study. Diabetes Care. 2009;32(8):1434–1436. doi: 10.2337/dc09-0228. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 110.Centers for Disease Control and Prevention Calculate What Diabetes Costs your Business. 2018. https://www.cdc.gov/diabetes/diabetesatwork/plan/costs.html Accessed September 28, 2018.
- 111.Baxter M., Hudson R., Mahon J., et al. Estimating the impact of better management of glycaemic control in adults with Type 1 and Type 2 diabetes on the number of clinical complications and the associated financial benefit. Diabet Med. 2016;33(11):1575–1581. doi: 10.1111/dme.13062. [DOI] [PubMed] [Google Scholar]
- 112.Kilgore M., Patel H.K., Kielhorn A., Maya J.F., Sharma P. Economic burden of hospitalizations of Medicare beneficiaries with heart failure. Risk Manag Healthc Policy. 2017;10:63–70. doi: 10.2147/RMHP.S130341. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 113.National Kidney Foundation End Stage Renal Disease in the United States. 2017. https://www.kidney.org/news/newsroom/factsheets/End-Stage-Renal-Disease-in-the-US Accessed March 3, 2019.
- 114.Honeycutt A.A., Segel J.E., Zhuo X., Hoerger T.J., Imai K., Williams D. Medical costs of CKD in the Medicare population. J Am Soc Nephrol. 2013;24(9):1478–1483. doi: 10.1681/ASN.2012040392. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 115.Dall T.M., Fulgoni V.L., Zhang Y., Reimers K.J., Packard P.T., Astwood J.D. Potential health benefits and medical cost savings from calorie, sodium, and saturated fat reductions in the American diet. Am J Health Promot. 2009;23:412–422. doi: 10.4278/ajhp.080930-QUAN-226. [DOI] [PubMed] [Google Scholar]