Clinical trial NCT05400005: Impact of Different Types of Higher Dietary Protein Intake on Sleep Quality in Singapore Older Adults
Official title: Impact of Different Types of Higher Dietary Protein Intake on Sleep Quality in Singapore Older Adults
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Sleep
Gut Microbiome
Cardiometabolic Risk
Keywords: Dietary protein
Lead sponsor: National University of Singapore
Sponsor class: OTHER
First posted: 2022-06-01
Enrollment: 54
Sex: ALL
Minimum age (years): 60
Maximum age (years): 85
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: FACTORIAL
Intervention model description: This is a 16-week factorial study design with subjects randomly assigned to consume normal-protein diet, higher-protein diet with micellar casein protein isolates or higher-protein diet with soy protein isolates. Subjects' sleep quality will also be evaluated and screened using the PSQI questionnaire (GSS ≤5 \[good sleepers\] vs. GSS \>5 \[poor sleepers\]).

Sixty-eight older men and women (aged 60-85y, approximately half men and half women) will be recruited with the expectation that ≥ 54 subjects (≥ 18 subjects per group) will complete the study (≤ 20% dropout rate). The 18 subjects recruited for each of the intervention group were further classified into poor (n=9) and good sleepers (n=9).
Primary purpose: BASIC_SCIENCE

Brief summary: Today, insufficient sleep has become a growing global problem. Sleep is essential to health and changes in sleep patterns are a part of the aging process. Inadequate and low-quality sleep also increases the risk for age-related cognitive decline and disease conditions. More importantly, due to COVID-19 health emergency, there is a significant increase of psychological distress and symptoms of mental illness and a worsening of quality of sleep. Therefore, there is an urgent need to investigate the way of improving sleep quality, in particular during and post COVID-19 period, in older adults.

One of the possible strategies in improving sleep quality with lifestyle modification is having higher-protein diet. However, this effect has not been fully elucidated in older adults. In addition, the effect of type of dietary protein on sleep quality is inconclusive and there is no clinical trial which assessed the differential response in sleep quality between animal-sourced protein vs. plant-sourced protein. Therefore, the purpose of this research project is to assess the impact of different types of higher dietary protein intake on sleep quality in Singapore older adults.

Findings from the proposed research will provide the scientific evidence of the beneficial effects of regularly consuming higher-protein diet on sleep quality in Singapore older adults. In addition, this research may validate the differential effect of different type of dietary protein on sleep quality. The results from the proposed research will also assist a practical guidance of nutritional behaviour changes providing sleep promoting effects to a large proportion of the Singapore population.

Detailed description: During the 16-week intervention, subjects will be randomly assigned to 1 of 3 groups including consuming normal-protein diet, higher-protein diet supplemented with micellar casein protein or higher-protein diet supplemented with soy protein. Recommended Dietary Allowances for healthy Singaporean. Normal-protein diet will be designed following a healthy eating pattern diet, referred to as the "My Healthy Plate" launched by Health Promotion Board and subjects will consume 3 servings of dietary protein. Higher-protein diet will also follow a healthy eating pattern diet while subjects will additionally take either 20 g micellar casein protein isolate or 20 g soy protein isolate. One-on-one dietary counselling and written instructions for each subject will be provided by a research dietitian and trained research staff. Compliance with the diet interventions will be promoted by frequent online and in-person contact and dietary assessment. Blood amino acid concentration will also be assessed as an indicator of compliance to the protein intake.

Eligibility criteria: Inclusion Criteria:

1. Adults 60-85 years old
2. Not following HPB diet

Exclusion Criteria:

1. Weight change \> 3kg in the past 3 months
2. Exercise vigorously over the past 3 months
3. Drinking more than 2 alcoholic drinks per day
4. (if applicable) Pre-menopausal women
5. Taking dietary supplements or medications which may impact sleep outcomes (e.g. Nutritional Shakes (e.g. Ensure), Trp, 5-HTP or melatonin supplementations) the past 1 month
6. Taking dietary supplements which may impact the gut microbiota (e.g. antibiotics, prebiotics, probiotics) the past 2 months (a list of fermented foods)
7. Impaired renal function (normal values: estimated glomerular filtration rate ≥ 90 mL/min/1.73 m2 calculated by chronic kidney disease epidemiology collaboration equation; CKD EPI)
8. Soy intolerance and/or allergy or any medical conditions that may be affected by consumption of soy products (e.g. gout)
9. Prescribed and taking antihypertensive/cholesterol-lowering/ type-2 diabetic medication or Chinese medicine herb which started less than 3 years prior to the intervention participation
10. Diagnosed with gut/gastrointestinal issues such as lactose intolerance and irritable bowel syndrome (IBS)

Primary outcomes:
measure: Change in sleep quality assessed by validated sleep questionnaires
timeFrame: Every 4 weeks (week 0, week 4, week 8, week 12 and week 16)
measure: Change in sleep quality assessed by electronic equipment
timeFrame: Every 4 weeks (week 0, week 4, week 8, week 12 and week 16)
measure: Change in blood amino acid concentration
timeFrame: Every 8 weeks (week 0 , week 8 and week 16)
measure: Change in blood serotonin concentration
timeFrame: Every 8 weeks (week 0 , week 8 and week 16)
measure: Change in urinary 6-sulfatoxymelatonin (aMT6s) concentration
timeFrame: Every 8 weeks (week 0 , week 8 and week 16)
Secondary outcomes:
measure: Change in fecal microbiome composition
timeFrame: Every 8 weeks (week 0 , week 8 and week 16)
measure: Change in fecal short chain fatty acid (SCFA) concentration
timeFrame: Every 8 weeks (week 0 , week 8 and week 16)
measure: Change in serum lipopolysaccharide binding protein (LBP) concentration
timeFrame: Every 8 weeks (week 0 , week 8 and week 16)
measure: Change in blood short chain fatty acid (SCFA) concentration
timeFrame: Every 8 weeks (week 0 , week 8 and week 16)
measure: Change in fecal bile acids
timeFrame: Every 8 weeks (week 0 , week 8 and week 16)
measure: Change in fecal zonulin
timeFrame: Every 8 weeks (week 0 , week 8 and week 16)
measure: Change in fecal calprotectin
timeFrame: Every 8 weeks (week 0 , week 8 and week 16)
measure: Change in urinary creatinine concentration
timeFrame: Every 8 weeks (week 0 , week 8 and week 16)
measure: Change in Estimated Glomerular Filtration Rate (eGFR)
timeFrame: Every 8 weeks (week 0 , week 8 and week 16)
measure: Change in Trimethylamine N-oxide (TMAO)
timeFrame: Every 8 weeks (week 0 , week 8 and week 16)
measure: Change in Blood Glucose
timeFrame: Every 8 weeks (week 0 , week 8 and week 16)
measure: Change in Blood Triglyceride
timeFrame: Every 8 weeks (week 0 , week 8 and week 16)
measure: Change in Blood Cholesterol
timeFrame: Every 8 weeks (week 0 , week 8 and week 16)
measure: Change in Blood Low-density Lipoprotein-cholesterol (LDL)
timeFrame: Every 8 weeks (week 0 , week 8 and week 16)
measure: Change in Blood High-density Lipoprotein-cholesterol (LDL)
timeFrame: Every 8 weeks (week 0 , week 8 and week 16)
measure: Change in Blood Advanced Glycation End-product (AGEs)
timeFrame: Every 8 weeks (week 0 , week 8 and week 16)
measure: Change in Skin Advanced Glycation End-product (AGEs)
timeFrame: Every 8 weeks (week 0 , week 8 and week 16)
measure: Change in Blood Interleukin-6 (IL-6)
timeFrame: Every 8 weeks (week 0 , week 8 and week 16)
measure: Change in Endothelial Function
timeFrame: Baseline and Post-intervention (week 0 and week 16)
measure: Change in Flow Mediate Dilation
timeFrame: Baseline and Post-intervention (week 0 and week 16)
measure: Change in weight and height
timeFrame: Every 4 weeks (week 0, week 4, week 8, week 12 and week 16)
measure: Change in waist circumference
timeFrame: Every 4 weeks (week 0, week 4, week 8, week 12 and week 16)
measure: Change in blood pressure
timeFrame: Every 4 weeks (week 0, week 4, week 8, week 12 and week 16)
measure: Dietary assessment
timeFrame: Every 4 weeks (week 0, week 4, week 8, week 12 and week 16)
measure: Change in mood (stress)
timeFrame: Every 4 weeks (week 0, week 4, week 8, week 12 and week 16)
measure: Change in mood (depression)
timeFrame: Every 4 weeks (week 0, week 4, week 8, week 12 and week 16)
measure: Change in mood (anxiety)
timeFrame: Every 4 weeks (week 0, week 4, week 8, week 12 and week 16)
Other outcomes:
Locations:
city: Singapore
country: Singapore
facility: National University of Singapore
Study officials:
affiliation: National University of Singapore
name: Jung Eun Kim, PhD
role: PRINCIPAL_INVESTIGATOR
References:
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citation: Zhou J, Kim JE, Armstrong CL, Chen N, Campbell WW. Higher-protein diets improve indexes of sleep in energy-restricted overweight and obese adults: results from 2 randomized controlled trials. Am J Clin Nutr. 2016 Mar;103(3):766-74. doi: 10.3945/ajcn.115.124669. Epub 2016 Feb 10.
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citation: St-Onge MP, Crawford A, Aggarwal B. Plant-based diets: Reducing cardiovascular risk by improving sleep quality? Curr Sleep Med Rep. 2018 Mar;4(1):74-78. Epub 2018 Feb 5.