Protein and Polycystic Ovary Syndrome (PCOS)

Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexFemale
Age18-50
SponsorUniversity of Arkansas, Fayetteville

About this trial

Polycystic ovary syndrome (PCOS) is a significant public health problem and is one of the most common hormonal disturbances affecting women of reproductive age. Women with PCOS are often insulin resistant, increasing their risk for cardiometabolic health problems (e.g., type 2 diabetes, heart disease, high blood pressure, sleep apnea, anxiety, depression, and stroke) especially if they are overweight. Lifestyle modifications, including dietary changes and regular physical activity, may alleviate metabolic dysfunction in women with PCOS and are often the first line of management for patients with PCOS. Several studies have identified protein as a key nutrient for regulation of energy balance, maintenance of skeletal muscle mass, and improving cardiometabolic health across the lifespan. However, the effect of increased protein intake (30% of total energy intake) on cardiometabolic health in women with PCOS has not been well-defined and mechanisms for these effects have not been identified.

There is an evident need for well-designed, randomized controlled trials evaluating the efficacy of increased protein intake in women with PCOS on markers of cardiometabolic health. Preliminary data from collaborative projects with the investigators on this proposal suggest that increasing protein in the diet has the potential to improve markers of cardiometabolic health, potentially through improvements in body composition and/or changes in cortisol, energy metabolism, inflammation, and neurological regulators

Eligibility criteria

This trial accepts healthy volunteers

Qualifiers

Females ages 18-50 years

Confirmed diagnosis of PCOS

Body mass index (BMI) between 18.5 and 35 kg/m2

Stable body weight for at least 3 months (+ 5 pounds)

Disqualifiers

Smoking or use of nicotine products

Smoking, vaping, and/or use of marijuana products

More than 4 alcoholic beverages per week

Food allergies or dietary restrictions incompatible with test meals

Trial design

Design model

Parallel

Treatments tested in this trial

  • Higher protein dietary pattern

    Other intervention

    Follow energy-restricted (10% calorie reduction), higher protein dietary pattern (1.6 g protein/kg body weight)

  • Calorie restriction

    Other intervention

    Follow energy-restricted (10% calorie reduction) dietary pattern for 16 weeks. No restrictions on macronutrient content.

Treatment groups

60 Participants
are divided into 4 treatment groups
Group A: Calorie restricted controlActive comparator 1 intervention
Group B: Control and ProteinActive comparator 1 intervention
Group C: Calorie restricted PCOSActive comparator 1 intervention
Group D: PCOS ProteinActive comparator 1 intervention

Trial outcomes

Primary outcomes

1

Lean body mass

Lean body mass will be measured using dual x-ray absorptiometry.

Time frame
0 and 16 weeks.

Secondary outcomes

1

Body fat mass

Total body fat and body fat distribution will measured using dual x-ray absorptiometry.

Time frame
0 and 16 weeks
2

Sleep Duration

Sleep quality and duration will be assessed objectively via an ActiGraph triaxial wrist accelerometer GT3X+, ActiGraph, LLC, Pensacola, FL, USA), a validated method of sleep assessment. Each participant will wear an ActiGraph monitor on the non-dominant wrist for 24-hour per day for seven days (except when bathing or involved in water activities) prior to the start of the intervention, 8-, and 16-weeks. Actigraphs will be fitted securely on each participants wrist. Participants will receive sleep diaries to define "time in bed" and "time out of bed". Researchers will use the indicated "start" and "end" points to define a sleep region to be analyzed within the ActiGraph software. Sleep outcomes will be calculated based on epoch-to-epoch sleep/wake algorithms within the defined sleep period. Data were processed by using the ActiLife Version 6.9.2 software (Pensacola, FL, USA) and sleep will be scored via the Cole-Kripke algorithm.

Time frame
Sleep will be measured every 8 weeks (0, 8, and 16 weeks)
3

Mood

The Profile of Mood States (POMS) questionnaire consists of 65 questions containing a one-word adjective of mood to measure and identify six affective states. The six identifiable mood/affective states are tension-anxiety, depression-dejection, anger-hostility, vigor-activity, fatigue/-inertia, and confusion-bewilderment. Participants will be instructed to define their mood on a 5-point Likert scale ranging from 0 to 4. The numbers refer to the following descriptive phrases: 0 = Not at all, 1 = A little, 2 = Moderately, 3 = Quite a bit, 4 = Extremely. To obtain the score for reach identifiable mood/affective state subscale, the sum of the responses for each adjective is calculated. The subscale scores range from 0 up to 36, 60, 48, 32, 28, and 28 for tension-anxiety depression-dejection, anger-hostility, vigor-activity, fatigue/-inertia, and confusion-bewilderment respectively. Higher subscale scores for all affect states, but the vigor domain represent poorer mood.

Time frame
Every 4 weeks (0, 4, 8, 12, 16 weeks)
4

Quality of Life perception

Health-related quality of life will be assessed using the 36-Item Short Form Health Survey (SF-36). The instrument consists of 36 items grouped into eight domains: physical functioning, role limitations due to physical health, bodily pain, general health perceptions, vitality, social functioning, role limitations due to emotional problems, and mental health. Items will be scored using standard Likert-type response scales and coded according to established procedures. Raw scores for each domain were summed and linearly transformed to a 0-100 scale, with higher scores indicating better health status.

Time frame
Every 4 weeks (0, 4, 8, 12, and 16 weeks)

Other outcomes

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

University of Arkansas, Fayetteville

Lead sponsor

Arkansas Biosciences Institute

Collaborator