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. Author manuscript; available in PMC: 2022 Oct 15.
Published in final edited form as: Exp Gerontol. 2021 Aug 31;154:111545. doi: 10.1016/j.exger.2021.111545

Changes in body weight and metabolic risk during time restricted feeding in premenopausal versus postmenopausal women

Sofia Cienfuegos 1, Kelsey Gabel 1, Faiza Kalam 1, Mark Ezpeleta 1, Shuhao Lin 1, Krista A Varady 1
PMCID: PMC8464526  NIHMSID: NIHMS1737919  PMID: 34478825

Abstract

Background:

Time restricted feeding (TRF) involves confining the eating window to a specific number of hours, and fasting for the remaining hours of the day.

Objective:

This study examined if changes in body weight and metabolic risk factors during TRF, differ between premenopausal and postmenopausal women.

Methods:

This is a secondary analysis of an 8-week TRF study (4–6 h eating window, 18–20 h fasting window daily) conducted in adults with obesity. Male participants were excluded, and female subjects were classified in two groups based on menstrual status: premenopausal (n = 13), or postmenopausal (n = 19). Perimenopausal women were excluded from the original study.

Results:

Body weight decreased by week 8 in premenopausal women (−3.3 ± 0.4%) and postmenopausal women (−3.3 ± 0.5%) (main effect of time, P < 0.001), with no difference between groups (no group × time interaction). Adherence was excellent in both groups, with premenopausal women adhering to their prescribed eating window on 6.2 ± 0.1 d/week, and postmenopausal women adhering to their window on 6.2 ± 0.2 d/week. Fat mass, lean mass, fasting insulin, insulin resistance, and 8-isoprostane (marker of oxidative stress) were reduced similarly in both groups (main effect of time, P < 0.05 for all comparisons). Visceral fat mass, relative skeletal muscle index (RSMI), blood pressure, LDL cholesterol, HDL cholesterol, triglycerides, fasting glucose, HbA1c, TNF-alpha and IL-6 remained unchanged in both groups by week 8.

Conclusion:

These findings suggest that the weight loss and metabolic benefits of TRF do not differ between premenopausal and postmenopausal women with obesity.

Keywords: Intermittent fasting, time restricted feeding, women, menopause, metabolic disease, obesity

Introduction

Time restricted feeding (TRF) has emerged as one of the most popular weight loss diets in recent years (de Cabo and Mattson 2019; Patterson and Sears 2017). TRF involves confining the eating window to a specified number of hours per day (typically 4 to 10 h), and fasting with water or calorie-free beverages for the remaining hours of the day. TRF is unique in that it does not require individuals to monitor energy intake or count calories during the eating window. Recent findings suggest that subjects are not able consume all of their energy needs for the day within the prescribed window, resulting in an unintentional energy restriction of 300–500 kcal/d (Cienfuegos and others 2020; Gabel and others 2018; Wilkinson and others 2020). As a result, individuals with obesity lose mild amounts of weight (1–4%) during short periods of TRF (Chow and others 2020; Cienfuegos and others 2020; Gabel and others 2018; Wilkinson and others 2020). Improvements in metabolic disease risk factors have also been observed. For instance, reductions in blood pressure, triglycerides, fasting insulin and insulin resistance are routinely demonstrated with TRF in men and women with obesity (Chow and others 2020; Cienfuegos and others 2020; Gabel and others 2018; Moro and others 2016; Sutton and others 2018; Tinsley and others 2019; Wilkinson and others 2020).

While these preliminary findings are promising, these studies are limited in that they pooled the findings for men, premenopausal women and postmenopausal women into one group. A key question that remains unresolved is whether the weight loss efficacy of TRF varies according to menopausal status. In a recent trial of alternate day fasting (Barnosky and others 2017), it was shown that postmenopausal women lost almost twice as much weight (12%) as premenopausal women (6%) after 24-weeks. Whether this same effect holds true for TRF, has never been assessed, but is of great interest.

Accordingly, this study was undertaken to examine if diet compliance, weight loss and metabolic risk factor improvements with TRF, differ between premenopausal and postmenopausal women. We hypothesized that postmenopausal women would be more compliant with TRF which would lead to greater reductions in body weight and insulin resistance, when compared to premenopausal women.

Methods

Subject selection

This is a secondary analysis of an 8-week randomized parallel-arm trial comparing the effects of 4-h and 6-h TRF on body weight and metabolic risk variables in adults with obesity (Cienfuegos and others 2020). For the original study, independently living subjects were recruited from the Chicago area by flyers. Participants were included in the original study if they were female or male; 18–65 years old; BMI 30.0–49.9 kg/m2; and previously sedentary (light exercise less than 1 h per week) or moderately active (moderate exercise 1 to 2 h per week). Individuals were excluded if they had a history of type 1 or type 2 diabetes, cardiovascular disease, were taking weight loss medications, were not weight stable for 3 months prior to the beginning of the study (> 4 kg weight loss or gain), were pregnant, lactating, shift-workers, or smokers. Perimenopausal women (defined as having irregular menses, with differences on cycle length over seven days or amenorrhea until one year) were excluded from the original study since this stage of menopause is associated with metabolic disturbances (Solomon and others 2001). The University of Illinois Chicago Office for the Protection of Research Subjects approved the experimental protocol, and all research participants gave their written informed consent to participate in the trial.

Results from our original study (Cienfuegos and others 2020) show that 4-h and 6-h TRF produce nearly identical changes in weight (−3%), energy intake (−550 kcal/d) and metabolic risk factors, including fasting insulin, insulin resistance and oxidative stress. In the original study, n = 19 were randomized to the 4-h TRF group and n = 20 were randomized to the 6-h TRF group (Figure 1). Three subjects dropped out of the 4-h TRF group, and n = 1 subject dropped out of the 6-h TRF group. For the present analysis, we combined completers from the 4-h TRF group (n = 16) and the 6-h TRF group (n = 19) into one cohort (n = 35). We then removed the male participants (n = 3), leaving a total sample of n = 32. Women from this larger cohort were then classified in two groups based on self-reported menstruation pattern per the Stages of Reproductive Aging Workshop classification (Harlow and others 2012): premenopausal (regular menses; n = 13), or postmenopausal (absence of menses for over one year; n = 19).

Figure 1.

Figure 1.

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Study flow diagram

Time restricted feeding protocol

The full protocol has been published previously (Cienfuegos and others 2020). Briefly, during the 8-week intervention, the 4-h TRF group was instructed to eat ad libitum from 3 to 7 pm daily (4-h eating window), and fast from 7 pm to 3 pm (20-h fast). The 6-h TRF group was instructed to eat ad libitum from 1 to 7 pm daily (6-h eating window), and fast from 7 pm to 1 pm (18-h fast). During the eating windows, TRF participants were not required to monitor energy intake and there were no restrictions on types or quantities of foods consumed. During the fasting window, TRF participants were encouraged to drink plenty of water and were permitted to consume energy-free beverages, such as black tea, coffee, and diet sodas, in moderation.

Body weight and body composition

Body weight was assessed every week at the research center without shoes and in light clothing using a digital scale (HealthOMeter, Boca Raton, FL). Body composition (fat mass, lean mass, visceral fat mass) was measured at baseline and at week 8 using dual x-ray absorptiometry (DXA; iDXA, General Electric Inc). Relative skeletal muscle index (RSMI) represents the relative amount of muscle in the arms and legs relative to height. RSMI was calculated using the Baumgartner equation: RSMI = [(lean mass of arms (kg) + lean mass of legs (kg)] / (height (m2)) (Baumgartner and others 1998).

Diet adherence and physical activity

Energy intake at baseline (pre-intervention) and week 8 was assessed by a 7-d food record. The total daily intake of energy was calculated using the food analysis program, Nutritionist Pro (Axxya Systems, Stafford, TX). Adherence to the TRF window was measured using a daily adherence log, which recorded the times each subject started and stopped eating each day. If the log indicated that the subject ate within the appropriate window, that day was labeled “adherent”. If the log indicated that the subject consumed food outside of the prescribed feeding window, that day was labeled as “non-adherent”. Adherence to the TRF diet was assessed as the number of adherent days per week. All subjects were asked to maintain their level of physical activity throughout the entire trial. Activity level (steps/d) was measured over a 7-d period during baseline (pre-intervention) and at week 8 by Fitbit Alta HR (Fitbit, San Francisco, CA). In the group of postmenopausal women, compliance was excellent and all of these women (n = 19) wore the activity monitor for the 7-day wear period. On the other hand, in the group of premenopausal women, n = 2 women wore the monitor for only 5-days, while the other women (n = 11) wore the activity monitor for the 7-day wear period.

Metabolic disease risk factor assessment

All metabolic disease risk variables were measured at baseline (pre-intervention) and week 8. Post-treatment measurements were made within 24–48 h of the cessation of the intervention. Twelve-hour fasting blood samples were collected between 6 am and 9 am. The subjects were instructed to avoid exercise, alcohol, and coffee for 24 h before each visit. Blood pressure was measured in triplicate using a digital automatic monitor (Omron HEM 705 LP, Kyoto, Japan) with the subject in a seated position after a 10-min rest. Fasting plasma LDL cholesterol, HDL-cholesterol, triglyceride, HbA1c concentrations were measured by a commercial lab (Medstar, Chicago, IL). Fasting glucose concentrations were measured with a hexokinase reagent kit (Abbott, South Pasadena, CA). Fasting insulin was assessed as total immunoreactive insulin (Coat-A-Count Insulin, Los Angeles, CA). Insulin resistance (IR) was calculated using the HOMA (Homeostasis Model Assessment) method, by applying the following formula: [HOMA-IR = Fasting insulin (μlU/ml) × Fasting glucose (mg/dL) / 405]. Circulating inflammatory cytokines, TNF-alpha and IL-6, and the oxidative stress marker, 8-isoprostane, were measured by ELISA (R&D Systems, Minneapolis, MN; Cayman Chemical Company; Ann Arbor, MI, respectively) on a Bio Rad Microplate reader (Bio-Rad Laboratories; Hercules, CA).

Statistical analyses

All data are presented as means ± SEM. Tests for normality were included in the model, and all data were found to be normally distributed. We performed both an intention-to-treat analysis (with last observation carried forward) and a completers analysis. At baseline, differences between premenopausal versus postmenopausal women were tested by an independent samples t-test (continuous variables) or McNemar test (categorical variables). Repeated measures ANOVA with groups (premenopausal women and postmenopausal women) as the between-subject factor and time (baseline and week 8) as the within-subject factor was used to compare changes in dependent variables between the groups over time. When there was a significant main effect but no interaction, post hoc comparisons were performed using Bonferroni’s correction to determine differences between group means. Cohen’s d effect sizes (the difference between means divided by pooled standard deviation) were calculated for dependent variables. Pearson correlations were performed to assess relationships between outcome measures. Differences were considered significant at P < 0.05. All data was analyzed using SPSS software (version 27, SPSS Inc, Chicago, IL).

Results

Baseline characteristics

In the original study, n = 19 participants were randomized to the 4-h TRF group, and n = 20 were randomized to the 6-h TRF group. A total n = 16 subjects completed the 4-h TRF intervention and n = 19 completed the 6-h TRF intervention (Figure 1). The proportion of premenopausal and postmenopausal women from the 4-h TRF group (43%; 57% respectively; P = 0.87) and 6-h TRF group (39%; 61% respectively, P = 0.49) were not significantly different.

At baseline, postmenopausal women were significantly older than premenopausal women (P < 0.001). However, there were no significant differences between premenopausal and postmenopausal women for any other parameter at baseline, including: race, ethnicity, BMI, body weight, body composition, energy intake, physical activity (steps/d) or any metabolic disease risk variable.

Body weight and body composition

Changes in body weight and body composition for the subjects who completed the trial are displayed in Figure 2 and Table 1. Body weight significantly decreased from baseline in premenopausal women (−3.3 ± 0.4%) and postmenopausal women (−3.3 ± 0.5%) by week 8 (main effect of time, P < 0.001). There were no significant differences between groups for weight loss (no group × time interaction; effect size: 0). Fat mass and lean mass significantly decreased from baseline to week 8 for premenopausal and postmenopausal women (main effect of time, P = 0.01 for both comparisons), with no differences between groups (no group × time interaction; effect size: 0.1). Visceral fat mass, BMI, and relative skeletal muscle index (RSMI) remained unchanged over the course of the trial in both groups. Weight loss was related to reductions in fat mass in the total sample (r = 0.27, P = 0.04). In addition, decreases in fat mass were related to lower visceral fat mass in the total sample (r = 0.41, P = 0.04). Results from our intention-to-treat analysis yielded nearly identical findings for body weight and body composition as our completers analysis (data not shown).

Figure 2. Weight loss during 8-weeks of time restricted feeding in premenopausal versus postmenopausal women.

Figure 2.

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Values are expressed as means ± SEM. Premenopausal women (n = 13); postmenopausal women (n = 19). Body weight significantly decreased from baseline to week 8 in premenopausal women (−3.3 ± 0.4%) and postmenopausal women (−3.3 ± 0.5%) (main effect of time, P < 0.001). There were no significant differences between groups for weight loss (no group × time interaction).

Table 1.

Body weight, body composition, energy intake and physical activity during 8-weeks of time restricted feeding in premenopausal versus postmenopausal women

Variables Premenopausal women (n = 13) Postmenopausal women (n =19) P-value
Baseline Week 8 Change Baseline Week 8 Change Time Group × Time
Age (y) 40 ± 2 56 ± 1 -- < 0.001
Race or ethnic group -- 0.88
 White 2 2
 Black 11 13
 Asian 2 0
 Hispanic 2 0
Body composition
 Body weight (kg) 99.9 ± 3.8 96.6 ± 3.6 −3.3 ± 0.5 102.2 ± 5.0 98.9 ± 4.8 −3.3 ± 0.5 < 0.001 0.99
 Height (cm) 164.2 ± 1.9 164.2 ± 1.9 0 ± 0 163.5 ± 1.9 163.5 ± 1.9 0 ± 0 0.99 0.41
 BMI (kg/m2) 37.1 ± 1.2 35.8 ± 1.1 −1.3 ± 0.9 38.2 ± 1.2 37.0 ± 1.3 −1.2 ± 0.8 0.37 0.96
 Fat mass (kg) 47.2 ± 2.4 45.3 ± 2.4 −1.9 ± 0.5 50.0 ± 3.6 47.9 ± 3.4 −2.1± 0.5 0.01 0.49
 Lean mass (kg) 51.1 ± 2.5 49.8 ± 2.5 −1.3 ± 0.5 49.7 ± 1.9 48.7 ± 1.8 −1.0 ± 0.4 0.01 0.83
 Visceral fat (kg) 1.1 ± 0.1 1.0 ± 0.1 −0.1 ± 0.1 1.4 ± 0.1 1.2 ± 0.1 −0.2 ± 0.1 0.11 0.13
 RSMI (kg/m2) 7.5 ± 1.0 7.4 ± 1.0 −0.1 ± 0.1 7.8 ± 0.8 7.5 ± 0.8 −0.3 ± 0.1 0.42 0.77
Diet and activity
 Energy intake (kcal/d) 1553± 169 1325± 186 −228 ± 165 1662± 205 1203± 155 −459 ± 190 0.03 0.52
 Adherence (d/week) 6.2 ± 0.1 6.2 ± 0.2 -- 0.93
 Activity (steps/d) 6828± 786 6805± 772 −23 ± 611 8163± 773 7905± 786 −258± 590 0.88 0.78
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Values are expressed as means ± SEM. RSMI: Relative skeletal muscle index.

P-value: Repeated measures ANOVA with groups (premenopausal women and postmenopausal women) as the between subject factor and time (baseline and week 8) as the within-subject factor.

Energy intake and physical activity

Energy intake for the completers significantly decreased from baseline to week 8 for premenopausal women (−228 ± 165 kcal/d) and postmenopausal women (−459 ± 190 kcal/d) (main effect of time, P = 0.03), with no differences between groups (no group × time interaction; effect size: 0.3) (Table 1). Adherence was excellent in both groups, with premenopausal women adhering to their prescribed eating window on 6.2 ± 0.1 d/week, and postmenopausal women adhering to their window on 6.2 ± 0.2 d/week (Table 1). Adherence level was not significantly different between groups (no group × time interaction). Activity level (assessed as steps/d) did not change during the study in either group of women (Table 1). Findings from our intention-to-treat analysis yielded the same results for energy intake, adherence, and activity level as our completers analysis (data not shown).

Metabolic risk factors

Changes in metabolic disease risk factors for the completers are shown in Table 2. Blood pressure did not change in either premenopausal or postmenopausal women after 8-weeks of TRF. Likewise, LDL cholesterol, HDL cholesterol, and triglycerides remained unchanged in both groups by the end of the study. Fasting insulin and HOMA-IR (measure of insulin resistance) significantly decreased (main effect of time, P = 0.04 for both comparisons) in premenopausal and postmenopausal women, with no differences between groups (no group × time interaction; effect size: 0.2). Fasting glucose and HbA1c remained unchanged over the course of the trial in both groups. The inflammatory cytokines, TNF-alpha and IL-6, did not change from baseline to post-treatment in either group of women. However, 8-isoprostane (a marker of oxidative stress to lipids) significantly decreased from baseline to week 8 in premenopausal and postmenopausal women (main effect of time, P = 0.03), with no differences between groups (no group × time interaction; effect size: 1.1). Results from our intention-to-treat analysis yielded the same results for each of these metabolic risk variables as our completers analysis (data not shown).

Table 2.

Metabolic risk factors during 8-weeks of TRF in premenopausal versus postmenopausal women

Variables Premenopausal women (n = 13) Postmenopausal women (n = 19) P-value
Baseline Week 8 Change Baseline Week 8 Change Time Group × Time
Blood pressure
 Systolic BP (mm Hg) 126 ± 4 124 ± 3 −2 ± 2 133 ± 3 126 ± 3 −7 ± 3 0.37 0.14
 Diastolic BP (mm Hg) 86 ± 3 83 ± 2 −3 ± 1 88 ± 2 84 ± 2 −4 ± 2 0.10 0.43
Plasma lipids
 LDL cholesterol (mg/dl) 105 ± 7 102 ± 6 −3 ± 3 110 ± 8 102 ± 6 −8 ± 7 0.34 0.51
 HDL cholesterol (mg/dl) 57 ± 4 56 ± 4 −1 ± 2 61 ± 5 59 ± 5 −2 ± 2 0.56 0.64
 Triglycerides (mg/dl) 90 ± 11 91 ± 11 1 ± 4 87 ± 7 90 ± 9 3 ± 8 0.94 0.77
Glucoregulatory
 Glucose (mg/dl) 90 ± 3 85 ± 3 −5 ± 2 99 ± 2 93 ± 3 −6 ± 3 0.12 0.70
 Insulin (μlU/mL) 15 ± 4 13 ± 3 −2 ± 2 14 ± 2 12 ± 1 −2 ± 1 0.04 0.72
 HOMA-IR 3.4 ± 0.9 2.8 ± 0.8 −0.6 ± 0.4 3.5 ± 0.5 2.7 ± 0.4 −0.8 ± 0.4 0.04 0.63
 HbA1c (%) 5.7 ± 0.1 5.6 ± 0.1 −0.1 ± 0.1 5.9 ± 0.1 5.7 ± 0.1 −0.2 ± 0.1 0.19 0.29
Inflammation
 TNF-alpha (pg/ml) 10 ± 2 11 ± 3 1 ± 2 12 ± 2 11 ± 3 −1 ± 3 0.63 0.36
 IL-6 (pg/ml) 5 ± 2 5 ± 1 0 ± 2 3 ± 1 6 ± 2 3 ± 1 0.98 0.28
Oxidative stress
 8-isoprostane (pg/ml) 39 ± 4 18 ± 2 −21 ± 3 28 ± 4 22 ± 5 −6 ± 3 0.03 0.13
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Values are expressed as means ± SEM. BP: Blood pressure, HOMA-IR: Homeostatic Model Assessment for Insulin Resistance.

P-value: Repeated measures ANOVA with groups (premenopausal women and postmenopausal women) as the between subject factor and time (baseline and week 8) as the within-subject factor.

We also performed an analysis to see if the results for each outcome measure (body weight, body composition, diet, physical activity, and metabolic disease risk factors) differed when the TRF intervention was statistically controlled for. Our results show that the menopause groups responded similarly when the TRF regimen was controlled (data not shown).

Discussion

Findings from this secondary analysis show that premenopausal and postmenopausal women lose similar amounts of weight (3.3%) during 8-weeks of TRF (4–6 h eating window). Compliance was excellent, with both groups adhering to their prescribed eating window on 6.2 days per week. Fat mass, lean mass, fasting insulin, insulin resistance, and 8-isoprostane were reduced after 8-weeks of TRF, but these decreases did not vary according to menopausal status. Other metabolic risk factors, such as visceral fat mass, blood pressure, LDL cholesterol, triglycerides, fasting glucose, HbA1c, and inflammatory cytokines remained unchanged in both groups.

Contrary to our hypothesis, postmenopausal women did not lose greater amounts of weight with TRF when compared to premenopausal women. This hypothesis was formulated based on a recent intermittent fasting trial (Barnosky and others 2017) showing that postmenopausal women lose almost twice as much weight as premenopausal women after 24-weeks of alternate day fasting. Several reasons may explain why these effects were not noted here. First, our study implemented a different form of intermittent fasting (i.e. TRF instead of alternate day fasting). Second, our trial was much shorter than this previous study. It is possible that differences between groups would only become apparent with longer intervention durations (>24 weeks). It will be of interest to compare changes in body weight between premenopausal and postmenopausal women during longer periods of TRF to see if one of these groups of women benefit more from this diet than the other.

Changes in body composition were also nearly identical between premenopausal and postmenopausal women. Fat mass was reduced by ~2kg and lean mass was reduced by ~1 kg in both groups, with no changes reported for visceral fat mass. Accumulating evidence suggests that adipose tissue is redistributed from subcutaneous to visceral fat depots during menopause (Chopra and others 2019; Kozakowski and others 2017). These body composition changes are in part due to the rapid decline in levels of estrogen and sex-hormone binding globulin (SHBG) (Chopra and others 2019; Kozakowski and others 2017). In view of these hormonal changes that occur during menopause, it has been postulated that postmenopausal women may react differently to weight loss interventions, versus premenopausal women. To our surprise, no study to date has directly compared the weight loss efficacy of any dietary intervention in postmenopausal versus premenopausal women. While several trials have been conducted in either premenopausal (Gardner and others 2007; Harvie and others 2011; Simkin-Silverman and others 2003) or postmenopausal women (Imayama and others 2012; Seimon and others 2019; van Gemert and others 2019), a head-to-head comparison yet to be performed. Due to the paucity of data in this area, it remains unknown if changes in fat mass, lean mass, and visceral fat mass, vary according to menopausal status during periods of dietary restriction. Larger and longer-term studies that specifically examine whether menopausal status influences body composition during dietary weight loss interventions, will be required to answer this important question.

We were also interested in seeing if diet adherence and energy intake varied according to menopausal status. Our findings reveal that premenopausal and postmenopausal women both reported excellent compliance to TRF over 8-weeks. Energy intake was reduced in both groups, with no significant differences observed between groups. Interestingly, the daily energy deficit reported by postmenopausal women was numerically much higher (~460 kcal/d) than what was reported in premenopausal women (~230 kcal/d). However, since the degree of weight loss achieved was the same by both groups, it is likely that our energy intake data, assessed via food records, is inaccurate (Scagliusi and others 2009). It will be important for future trials in this area to assess energy expenditure and dietary restriction by gold-standard methods, such as the doubly labeled water technique (de Jonge and others 2007; Ravussin and others 1991). Findings from trials implementing this more robust technique, could help to clarify if dietary adherence and energy intake truly do vary according to menopausal status.

Level of physical activity, measured as steps per day, did not change significantly from baseline to post-treatment in either group of women. However, minor numerical reductions in activity were noted in both premenopausal (−0.3%) and postmenopausal women (−3.2%). This is somewhat surprising as weight loss generally improves mobility and makes walking easier (Creasy and others 2018; Swift and others 2014). It is possible, however, that activity level may have decreased slightly during the fasting window due to the absence of food intake. It will be of interest for future trials of TRF measure changes in activity during the eating window versus the fasting window, to clarify how this diet regimen impacts exercise habits.

Improvements in metabolic disease risk factors with TRF also did not differ between premenopausal and postmenopausal women. For instance, fasting insulin, insulin resistance, and oxidative stress (8-isoprostane) decreased similarly in both groups, with no significant differences between groups. Menopause has been purported to coincide with an increase in insulin resistance in women with obesity (Carr 2003; Chu and others 2006). Interestingly, in the present study, both premenopausal and postmenopausal women displayed similar degrees of insulin resistance at baseline (HOMA-IR - premenopausal women: 3.4; postmenopausal: 3.5; with values >2.7 indicating insulin resistance (Gayoso-Diz and others 2013; Sumner and Cowie 2008)). Our findings also show that reductions in insulin resistance were comparable between groups by the end of the study (−0.6 for premenopausal women, and −0.8 for postmenopausal women). Thus, premenopausal and postmenopausal women may experience similar improvements in insulin resistance when the same degree of weight loss is achieved. No changes were noted in other metabolic risk indicators, such as blood pressure, LDL cholesterol, HDL cholesterol, triglycerides, fasting, glucose or HbA1c. This lack of effect could be due to the small reductions in body weight observed here. It is likely that clinically significant weight loss (>5% from baseline) would be needed for improvements in these indicators to be observed (Williamson and others 2015). In addition, it should be noted that the values for blood pressure, plasma lipids, fasting glucose and HbA1c were already in the normal range at baseline, which may explain why no additional benefit was demonstrated.

This secondary analysis has several limitations. First, the sample size was small (n = 32). Menopause has a significant impact on body composition and cardiometabolic markers (Lovejoy and others 2008; Sowers and others 2007). Since our sample size was limited, our trial may have been underpowered to detect significant differences between groups for these key outcome measures at baseline and post-treatment. Second, the trial ran for a short duration (8-weeks). It is possible that if the study ran for longer (>24 weeks), significant differences in adherence and weight loss between groups may have been detected. Third, we did not assess other key determinants of weight loss, including marriage status, employment status, education level, or income level, etc. Fourth, we used adherence logs and food records to assess compliance to the TRF intervention. It is well known that individuals with obesity underreport energy intake by 20–40% in food logs (Kretsch and others 1999). Thus, our compliance and energy intake data are most likely inaccurate. Fifth, it is possible that we did not see any differences between these two groups of women because they were too close in age (40 y versus 56 y). Future work should aim to recruit women in these two menopause categories that are more disparate in age (e.g., 30-y versus 60-y old women) and control for the confounder of age. Sixth, menopausal status was determined via self-report. The study would have benefited from a sex hormone assessment (e.g. FSH > 30 mIU/mL) to help confirm menopause. Lastly, we did not control for medication use. Certain drugs, such as anti-psychotic medications, β-receptor antagonists, corticosteroids, and neurotropic drugs, can lead to significant body composition changes (Verhaegen and Van Gaal 2021), and therefore should be controlled for in future studies.

Conclusion

Results from this secondary analysis show that premenopausal and postmenopausal women lose equivalent amounts of weight (~3% from baseline) and experience similar body composition changes during TRF. Our findings also show that key metabolic risk factors, such as fasting insulin, insulin resistance, and 8-isoprostane (marker of oxidative stress), improve similarly in these groups of women. Taken together, these data suggest that the weight loss and metabolic benefits of TRF do not vary according to menopausal status. These preliminary findings warrant confirmation by a well-powered clinical trial that specifically aims to assess how menopausal status impacts changes in body weight and metabolic risk factors during TRF.

Acknowledgments

We would like to thank the participants for their time and effort in participating in the clinical trial.

Funding:

National Institutes of Health, NIDDK, R01DK119783

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Disclosure: The authors have no conflicts of interest to disclose.

Trial registration: Clinicaltrials.gov NCT03867773

References

  1. Barnosky A; Kroeger CM; Trepanowski JF; Klempel MC; Bhutani S; Hoddy KK; Gabel K; Shapses SA; Varady KA Effect of alternate day fasting on markers of bone metabolism: An exploratory analysis of a 6-month randomized controlled trial. Nutr Healthy Aging. 4:255–263; 2017 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Baumgartner RN; Koehler KM; Gallagher D; Romero L; Heymsfield SB; Ross RR; Garry PJ; Lindeman RD Epidemiology of sarcopenia among the elderly in New Mexico. Am J Epidemiol. 147:755–763; 1998 [DOI] [PubMed] [Google Scholar]
  3. Carr MC The emergence of the metabolic syndrome with menopause. J Clin Endocrinol Metab. 88:2404–2411; 2003 [DOI] [PubMed] [Google Scholar]
  4. Chopra S; Sharma KA; Ranjan P; Malhotra A; Vikram NK; Kumari A Weight Management Module for Perimenopausal Women: A Practical Guide for Gynecologists. J Midlife Health. 10:165–172; 2019 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Chow LS; Manoogian ENC; Alvear A; Fleischer JG; Thor H; Dietsche K; Wang Q; Hodges JS; Esch N; Malaeb S; Harindhanavudhi T; Nair KS; Panda S; Mashek DG Time-Restricted Eating Effects on Body Composition and Metabolic Measures in Humans who are Overweight: A Feasibility Study. Obesity (Silver Spring). 28:860–869; 2020 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Chu MC; Cosper P; Orio F; Carmina E; Lobo RA Insulin resistance in postmenopausal women with metabolic syndrome and the measurements of adiponectin, leptin, resistin, and ghrelin. Am J Obstet Gynecol. 194:100–104; 2006 [DOI] [PubMed] [Google Scholar]
  7. Cienfuegos S; Gabel K; Kalam F; Ezpeleta M; Wiseman E; Pavlou V; Lin S; Oliveira ML; Varady KA Effects of 4- and 6-h Time-Restricted Feeding on Weight and Cardiometabolic Health: A Randomized Controlled Trial in Adults with Obesity. Cell Metab; 2020 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Creasy SA; Lang W; Tate DF; Davis KK; Jakicic JM Pattern of Daily Steps is Associated with Weight Loss: Secondary Analysis from the Step-Up Randomized Trial. Obesity (Silver Spring). 26:977–984; 2018 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. de Cabo R; Mattson MP Effects of Intermittent Fasting on Health, Aging, and Disease. N Engl J Med. 381:2541–2551; 2019 [DOI] [PubMed] [Google Scholar]
  10. de Jonge L; DeLany JP; Nguyen T; Howard J; Hadley EC; Redman LM; Ravussin E Validation study of energy expenditure and intake during calorie restriction using doubly labeled water and changes in body composition. Am J Clin Nutr. 85:73–79; 2007 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Gabel K; Hoddy KK; Haggerty N; Song J; Kroeger CM; Trepanowski JF; Panda S; Varady KA Effects of 8-hour time restricted feeding on body weight and metabolic disease risk factors in obese adults: A pilot study. Nutr Healthy Aging. 4:345–353; 2018 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Gardner CD; Kiazand A; Alhassan S; Kim S; Stafford RS; Balise RR; Kraemer HC; King AC Comparison of the Atkins, Zone, Ornish, and LEARN diets for change in weight and related risk factors among overweight premenopausal women: the A TO Z Weight Loss Study: a randomized trial. JAMA. 297:969–977; 2007 [DOI] [PubMed] [Google Scholar]
  13. Gayoso-Diz P; Otero-Gonzalez A; Rodriguez-Alvarez MX; Gude F; Garcia F; De Francisco A; Quintela AG Insulin resistance (HOMA-IR) cut-off values and the metabolic syndrome in a general adult population: effect of gender and age: EPIRCE cross-sectional study. BMC Endocr Disord. 13:47; 2013 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Harlow SD; Gass M; Hall JE; Lobo R; Maki P; Rebar RW; Sherman S; Sluss PM; de Villiers TJ; Group SC Executive summary of the Stages of Reproductive Aging Workshop + 10: addressing the unfinished agenda of staging reproductive aging. J Clin Endocrinol Metab. 97:1159–1168; 2012 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Harvie MN; Pegington M; Mattson MP; Frystyk J; Dillon B; Evans G; Cuzick J; Jebb SA; Martin B; Cutler RG; Son TG; Maudsley S; Carlson OD; Egan JM; Flyvbjerg A; Howell A The effects of intermittent or continuous energy restriction on weight loss and metabolic disease risk markers: a randomized trial in young overweight women. Int J Obes (Lond). 35:714–727; 2011 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Imayama I; Ulrich CM; Alfano CM; Wang C; Xiao L; Wener MH; Campbell KL; Duggan C; Foster-Schubert KE; Kong A; Mason CE; Wang CY; Blackburn GL; Bain CE; Thompson HJ; McTiernan A Effects of a caloric restriction weight loss diet and exercise on inflammatory biomarkers in overweight/obese postmenopausal women: a randomized controlled trial. Cancer Res. 72:2314–2326; 2012 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Kozakowski J; Gietka-Czernel M; Leszczynska D; Majos A Obesity in menopause - our negligence or an unfortunate inevitability? Prz Menopauzalny. 16:61–65; 2017 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Kretsch MJ; Fong AK; Green MW Behavioral and body size correlates of energy intake underreporting by obese and normal-weight women. J Am Diet Assoc. 99:300–306; quiz 307–308; 1999 [DOI] [PubMed] [Google Scholar]
  19. Lovejoy JC; Champagne CM; de Jonge L; Xie H; Smith SR Increased visceral fat and decreased energy expenditure during the menopausal transition. Int J Obes (Lond). 32:949–958; 2008 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Moro T; Tinsley G; Bianco A; Marcolin G; Pacelli QF; Battaglia G; Palma A; Gentil P; Neri M; Paoli A Effects of eight weeks of time-restricted feeding (16/8) on basal metabolism, maximal strength, body composition, inflammation, and cardiovascular risk factors in resistance-trained males. J Transl Med. 14:290; 2016 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Patterson RE; Sears DD Metabolic Effects of Intermittent Fasting. Annu Rev Nutr. 37:371–393; 2017 [DOI] [PubMed] [Google Scholar]
  22. Ravussin E; Harper IT; Rising R; Bogardus C Energy expenditure by doubly labeled water: validation in lean and obese subjects. Am J Physiol. 261:E402–409; 1991 [DOI] [PubMed] [Google Scholar]
  23. Scagliusi FB; Ferriolli E; Pfrimer K; Laureano C; Cunha CS; Gualano B; Lourenco BH; Lancha AH Jr. Characteristics of women who frequently under report their energy intake: a doubly labelled water study. Eur J Clin Nutr. 63:1192–1199; 2009 [DOI] [PubMed] [Google Scholar]
  24. Seimon RV; Wild-Taylor AL; Keating SE; McClintock S; Harper C; Gibson AA; Johnson NA; Fernando HA; Markovic TP; Center JR; Franklin J; Liu PY; Grieve SM; Lagopoulos J; Caterson ID; Byrne NM; Sainsbury A Effect of Weight Loss via Severe vs Moderate Energy Restriction on Lean Mass and Body Composition Among Postmenopausal Women With Obesity: The TEMPO Diet Randomized Clinical Trial. JAMA Netw Open. 2:e1913733; 2019 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Simkin-Silverman LR; Wing RR; Boraz MA; Kuller LH Lifestyle intervention can prevent weight gain during menopause: results from a 5-year randomized clinical trial. Ann Behav Med. 26:212–220; 2003 [DOI] [PubMed] [Google Scholar]
  26. Solomon CG; Hu FB; Dunaif A; Rich-Edwards J; Willett WC; Hunter DJ; Colditz GA; Speizer FE; Manson JE Long or highly irregular menstrual cycles as a marker for risk of type 2 diabetes mellitus. JAMA. 286:2421–2426; 2001 [DOI] [PubMed] [Google Scholar]
  27. Sowers M; Zheng H; Tomey K; Karvonen-Gutierrez C; Jannausch M; Li X; Yosef M; Symons J Changes in body composition in women over six years at midlife: ovarian and chronological aging. J Clin Endocrinol Metab. 92:895–901; 2007 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Sumner AE; Cowie CC Ethnic differences in the ability of triglyceride levels to identify insulin resistance. Atherosclerosis. 196:696–703; 2008 [DOI] [PubMed] [Google Scholar]
  29. Sutton EF; Beyl R; Early KS; Cefalu WT; Ravussin E; Peterson CM Early Time-Restricted Feeding Improves Insulin Sensitivity, Blood Pressure, and Oxidative Stress Even without Weight Loss in Men with Prediabetes. Cell Metab. 27:1212–1221 e1213; 2018 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Swift DL; Johannsen NM; Lavie CJ; Earnest CP; Church TS The role of exercise and physical activity in weight loss and maintenance. Prog Cardiovasc Dis. 56:441–447; 2014 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Tinsley GM; Moore ML; Graybeal AJ; Paoli A; Kim Y; Gonzales JU; Harry JR; VanDusseldorp TA; Kennedy DN; Cruz MR Time-restricted feeding plus resistance training in active females: a randomized trial. Am J Clin Nutr. 110:628–640; 2019 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. van Gemert WA; Peeters PH; May AM; Doornbos AJH; Elias SG; van der Palen J; Veldhuis W; Stapper M; Schuit JA; Monninkhof EM Effect of diet with or without exercise on abdominal fat in postmenopausal women - a randomised trial. BMC Public Health. 19:174; 2019 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Verhaegen AA; Van Gaal LF Drugs Affecting Body Weight, Body Fat Distribution, and Metabolic Function-Mechanisms and Possible Therapeutic or Preventive Measures: an Update. Curr Obes Rep. 10:1–13; 2021 [DOI] [PubMed] [Google Scholar]
  34. Wilkinson MJ; Manoogian ENC; Zadourian A; Lo H; Fakhouri S; Shoghi A; Wang X; Fleischer JG; Navlakha S; Panda S; Taub PR Ten-Hour Time-Restricted Eating Reduces Weight, Blood Pressure, and Atherogenic Lipids in Patients with Metabolic Syndrome. Cell Metab. 31:92–104 e105; 2020 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Williamson DA; Bray GA; Ryan DH Is 5% weight loss a satisfactory criterion to define clinically significant weight loss? Obesity (Silver Spring). 23:2319–2320; 2015 [DOI] [PubMed] [Google Scholar]

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