Original Research
An Evaluation of Alternative Technology-Supported Counseling Approaches to Promote Multiple Lifestyle Behavior Changes in Patients With Type 2 Diabetes and Chronic Kidney Disease

https://doi.org/10.1053/j.jrn.2022.05.006Get rights and content

Objectives

Although technology-supported interventions are effective for reducing chronic disease risk, little is known about the relative and combined efficacy of mobile health strategies aimed at multiple lifestyle factors. The purpose of this clinical trial is to evaluate the efficacy of technology-supported behavioral intervention strategies for managing multiple lifestyle-related health outcomes in overweight adults with type 2 diabetes (T2D) and chronic kidney disease (CKD).

Design and Methods

Using a 2 × 2 factorial design, adults with excess body weight (body mass index ≥27 kg/m2, age ≥40 years), T2D, and CKD stages 2-4 were randomized to an advice control group, or remotely delivered programs consisting of synchronous group-based education (all groups), plus (1) Social Cognitive Theory–based behavioral counseling and/or (2) mobile self-monitoring of diet and physical activity. All programs targeted weight loss, greater physical activity, and lower intakes of sodium and phosphorus-containing food additives.

Results

Of 256 randomized participants, 186 (73%) completed 6-month assessments. Compared to the ADVICE group, mHealth interventions did not result in significant changes in weight loss, or urinary sodium and phosphorus excretion. In aggregate analyses, groups receiving mobile self-monitoring had greater weight loss at 3 months (P = .02), but between 3 and 6 months, weight losses plateaued, and by 6 months, the differences were no longer statistically significant.

Conclusions

When engaging patients with T2D and CKD in multiple behavior changes, self-monitoring diet and physical activity demonstrated significantly larger short-term weight losses. Theory-based behavioral counseling alone was no better than baseline advice and demonstrated no interaction effect with self-monitoring.

Introduction

Type 2 diabetes (T2D) is a chronic, progressive condition associated with a variety of complications.1, 2, 3, 4, 5, 6, 7, 8 Chronic kidney disease (CKD) is a common complication, affecting ∼40%-50% of T2D patients.9,10 In 2016, Medicare spending exceeded $79 billion for CKD and $35 billion for kidney failure.11 The United States Renal Data System Annual Data Report notes that reduction in expenditures could be achieved by reducing progression to kidney failure and preventing the development of related cardiovascular disease.11

Multiple modifiable factors appear to be involved in the development and progression of CKD to kidney failure, including obesity,12, 13, 14, 15, 16, 17, 18 lack of physical activity and sedentary behavior,19, 20, 21, 22, 23 and excess dietary sodium intake.24, 25, 26 Hyperphosphatemia, a well-recognized problem in patients with kidney failure, also may contribute to vascular calcification in earlier stages of CKD.27, 28, 29, 30, 31, 32 Lifestyle interventions have the potential to slow CKD progression by reducing obesity, increasing physical activity, and decreasing dietary sodium and phosphorus intake, but the effectiveness of this approach depends on the ability to produce sustained behavior change. Behavioral methods that target psychosocial determinants (e.g., attitudes, social influence, risk perceptions, and self-efficacy) are generally considered essential components of lifestyle and self-management interventions. However, theory-based behavior change research has traditionally targeted one behavior at a time and provided little guidance on best approaches for targeting multiple behaviors.33 We assert that behavioral methods alone may be insufficient for engaging patients in multiple behavior changes, due to the cognitive burden of paying attention to multiple aspects of one’s lifestyle,34,35 and the complexity of information required to make informed self-management decisions.36,37

The purpose of the Diabetes Healthy Hearts and Kidneys (HHK) Study is to evaluate alternative remotely delivered, technology-supported intervention approaches for engaging patients with T2D and concurrent CKD in multiple lifestyle behavior changes (weight loss, physical activity, and dietary restriction of sodium and phosphate additives). We compared the main effects of Social Cognitive Theory–based38 Behavioral Group Counseling (hereafter SCT), technology-based self-monitoring (to reduce vigilance and information burden, hereafter MONITORING), and their interaction (hereafter COMBINED), to baseline advice about weight loss, physical activity, and dietary intake of sodium and phosphate additives (hereafter ADVICE): We hypothesized that the magnitude of the effect of the interventions on the proportion of participants demonstrating ≥5% baseline body weight loss, and reductions in urinary excretion of sodium and phosphorus (primary outcomes) would be COMBINED > SCT > ADVICE. In exploratory analyses, we proposed to describe the impact of MONITORING on primary outcomes. We also proposed exploratory analyses of the impact of randomization assignment on hemoglobin A1c, serum lipids, blood pressure, and vascular stiffness.

Section snippets

Design

We previously published the study rationale, design, and pretrial pilot activities related to this study.39 In brief, HHK was a 2 × 2 factorial, randomized controlled trial of adults who were overweight or obese and had T2D and concurrent CKD. Using computer-generated permuted blocks, participants were randomized first to SCT or no-SCT and, within these groups, re-randomized to MONITORING or no-MONITORING. The 4 resulting groups were ADVICE, MONITORING, SCT, and COMBINED. Measurements were

Results

Participants were recruited from NYULH between January 2016 and April 2019. Of the 3,575 individuals who self-referred and were screened, 372 were interested and eligible, 256 were randomized, and 186 of randomized participants (73%) completed 6-month assessments. The CONSORT diagram is shown in Figure 1. As shown in Table 1, randomized participants tended to be older, obese, White individuals who were married or partnered and had a high school or greater education, health insurance, and

Discussion

Cardiovascular disease, rather than kidney failure, is the leading cause of death in patients with CKD, making obesity an important treatment target.46 While the 2020 update of the Kidney Disease Outcomes Quality Initiative (KDOQI) Clinical Practice Guideline for Nutrition in CKD does not recommend weight loss, neither does it prohibit it.47 A lifestyle intervention that includes weight loss may be beneficial for Stage 1-4 CKD patients, as it reduces the proteinuria and glomerular

Practical Applications

Managing information burden appears to be essential for engaging patients with T2D and concurrent CKD in multiple behavior changes. Behavioral counseling alone was no better than baseline advice, and demonstrated no interaction effect with self-monitoring. Behavioral counseling may be important for sustaining longer term behavior change (e.g., beyond 6 months), but must be confirmed with additional research. Future studies would be strengthened by selecting participants who are obese, have more

CrediT Authorship Contribution Statement

David E. St-Jules: Methodology, Validation, Data curation, Writing – original draft. Lu Hu: Methodology, Validation, Data curation, Writing – review & editing. Kathleen Woolf: Conceptualization, Funding acquisition, Methodology, Software, Validation, Data curation, Writing – review & editing. Chan Wang: Software, Data curation, Formal analysis, Data curation, Writing – review & editing. David S. Goldfarb: Conceptualization, Funding acquisition, Data curation, Writing – review & editing. Stuart

References (64)

  • J.H. Fuller et al.

    Mortality from coronary heart disease and stroke in relation to degree of glycaemia: the Whitehall study

    Br Med J (Clin Res Ed)

    (1983)
  • R. Klein

    Hyperglycemia and microvascular and macrovascular disease in diabetes

    Diabetes Care

    (1995)
  • M. Hanefeld et al.

    Risk Factors for myocardial infarction and death in newly detected NIDDM: the Diabetes Intervention Study, 11-year follow-up

    Diabetologia

    (1996)
  • E. Standl et al.

    Predictors of 10-year macrovascular and overall mortality in patients with NIDDM: the Munich general Practitioner Project

    Diabetologia

    (1996)
  • A.I. Adler et al.

    Risk factors for diabetic peripheral sensory neuropathy. Results of the Seattle prospective diabetic Foot study

    Diabetes Care

    (1997)
  • R.C. Turner et al.

    Risk factors for coronary artery disease in non-insulin dependent diabetes mellitus: United Kingdom Prospective Diabetes Study (UKPDS: 23)

    BMJ

    (1998)
  • M. Wei et al.

    Effects of diabetes and level of glycemia on all- cause and cardiovascular mortality. The San Antonio Heart Study

    Diabetes Care

    (1998)
  • M.C. Thomas et al.

    Changing epidemiology of type 2 diabetes mellitus and associated chronic kidney disease

    Nat Rev Nephrol

    (2016)
  • R.Z. Alicic et al.

    Diabetic kidney disease challenges, progress, and possibilities

    Clin J Am Soc Nephrol

    (2017)
  • 2019 USRDS Annual Data Report: Epidemiology of kidney disease in the United States

    (2019)
  • E. Ejerblad et al.

    Obesity and risk for chronic renal failure

    J Am Soc Nephrol

    (2006)
  • C.Y. Hsu et al.

    Body mass index and risk for end- stage renal disease

    Ann Int Med

    (2006)
  • M. Praga et al.

    Obesity, proteinuria, and progression of renal failure

    Curr Opin Nephrol Hypertens

    (2006)
  • H. Kramer et al.

    Obesity and albuminuria among adults with type 2 diabetes: the Look AHEAD (action for health in diabetes) study

    Diabetes Care

    (2009)
  • M. Madero et al.

    Comparison between different measures of body fat with kidney function decline and incident CKD

    Clin J Am Soc Nephrol

    (2017)
  • C. Robinson-Cohen et al.

    Physical activity and rapid decline in kidney function among older adults

    Arch Intern Med

    (2009)
  • B.M. Lynch et al.

    Television viewing time and risk of chronic kidney disease in adults: the AusDiab Study

    Ann Behav Med

    (2010)
  • M.S. Hawkins et al.

    Association of physical activity and kidney function: national health and nutrition Examination Survey

    Med Sci Sports Exerc

    (2011)
  • M.S. Hawkins et al.

    TV Watching but not physical activity is associated with change in kidney function in older adults

    J Phys Act Health

    (2015)
  • R.J.H. Martens et al.

    Amount and pattern of physical activity and sedentary behavior are associated with kidney function and kidney damage: the Maastricht Study

    PLoS ONE

    (2018)
  • F.B. Nerbass et al.

    High sodium intake is associated with important risk factors in a large cohort of chronic kidney disease patients

    Eur J Clin Nutr

    (2015)
  • M. Kuwabara et al.

    Increased serum sodium and serum osmolarity are independent risk factors for developing chronic kidney disease; 5 year cohort study

    PLoS ONE

    (2018)
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    Financial Disclosure: The authors declare that they have no relevant financial disclosures.

    Support: The study was supported by the National Institutes of Health Grant R01-DK100492. We also acknowledge the support of New York University Langone’s Clinical and Translational Science Institute, which is supported by the National Center for Advancing Translational Sciences through Grant Award Number UL1TR001445. National Institutes of Health played no role in study design; collection, analysis, and interpretation of data; writing the report; or the decision to submit the report for publication.

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