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Published in final edited form as: J Behav Med. 2015 Dec 10;39(3):465–471. doi: 10.1007/s10865-015-9704-8

Successful weight loss maintenance associated with morning chronotype and better sleep quality

Kathryn M Ross 1, J Graham Thomas 1, Rena R Wing 1
PMCID: PMC4854772  NIHMSID: NIHMS744234  PMID: 26660638

Abstract

It is not known whether individuals successful at long term weight loss maintenance differ in chronotype (i.e., being a “morning” or “evening” person) or sleep habits compared to those who are overweight and obese. We compared Morningness-Eveningness Questionnaire (MEQ) and Pittsburgh Sleep Quality Index (PSQI) scores of 690 National Weight Control Registry (NWCR) members (73%female, 93%white, age=51.7±12.5, BMI=26.4±5.1) to 75 enrollees in two behavioral weight loss interventions (INT; 77%female, 88%white, age=55.7±10.4, BMI=36.2±4.7). Controlling for age, MEQ scores were higher in NWCR than INT, p=.004, such that more NWCR than INT were morning-types and fewer were evening types, p=.014. Further, NWCR participants reported better sleep quality, longer sleep duration, and shorter latency to sleep onset compared to INT, ps<.05, and fewer NWCR participants reported <6 or <7 hours of sleep, ps<.01. Future studies should examine if these factors change as a result of weight loss or are predictors of weight outcome.

Keywords: Obesity, Weight Loss Maintenance, Sleep, Chronotype, Morningness/Eveningness

Introduction

The difficulty experienced by many individuals in maintaining weight loss long-term (Jeffery et al., 2000; Kraschnewski et al., 2010) suggests the need for increased research on the factors associated with successful maintenance. Although prior studies have focused on the eating and physical activity patterns of successful weight loss maintainers, there has been no research to date on the chronotype or sleep habits of these individuals. This is surprising given the increasing emphasis on the impact of both chronotype (i.e., whether someone is a “morning” or an “evening” person) and sleep habits (e.g., sleep duration and quality) on health behaviors and health risks, including obesity.

Obesity has been associated with both shorter sleep duration (Cappuccio et al., 2008; Gangwisch et al., 2005) and poor sleep quality (Quick et al., 2013; Taheri et al., 2004; Tworoger et al., 2005). While the direction of this association remains unclear, some evidence suggests that there may be a reciprocal influence between sleep and obesity. Shorter sleep duration has been shown to lead to decreased levels of leptin (a protein hormone that signals satiety) and increased levels of ghrelin (a gut peptide associated with the sensation of hunger; Copinschi et al., 2014; Spiegel et al., 2004; Taheri et al., 2004), increased appetite for high-calorie, high-carbohydrate food (Spiegel et al., 2004), stimulation of brain regions sensitive to food stimuli (Copinschi et al., 2014), and insulin resistance (Broussard et al., 2012). Conversely, obesity has been associated with higher prevalence of sleep related problems, such as obstructive sleep apnea (Vgontzas et al., 1994), and weight loss in obese individuals has been shown to lead to clinically-relevant improvements in both sleep apnea (Foster et al, 2009) and overall sleep quality (Toor et al., 2012). It remains unknown whether sleep quality and duration differ between successful weight loss maintainers and overweight/obese individuals.

Compared to the research on sleep and obesity, relatively little research has investigated the association between chronotype and obesity. While a direct link between chronotype and weight status has yet to be demonstrated, evening-type chronotype has been associated with a wide variety of negative health outcomes, from behavioral dysregulation (Caci et al., 2004; Tonetti et al., 2010) to drug addiction (Adan, 1994), depression (Levandovski et al., 2011), and eating disorders (Natale et al., 2008) and evening-type individuals have been shown to be more likely to engage in eating behaviors that may negatively impact weight, such as increased fast food and soda consumption (Fleig & Randler, 2009). Similarly, morning-type individuals report higher dietary restraint and lower dietary disinhibition (Schubert & Randler, 2008), factors which have been demonstrated to differentiate obese and overweight individuals from normal weight individuals (Lindroos et al., 1997).

Despite increased research on long-term maintenance of weight loss, successful maintenance remains a challenge for many individuals (Kraschnewski et al., 2010); investigating the behaviors that differ between those who are successful at weight loss and maintenance and those who are overweight and obese may provide clues to understanding this challenge. Findings from the National Weight Control Registry (NWCR), a registry of individuals who have lost at least 13.6 kg and have maintained this weight loss for at least 1 year, have provided insight into the characteristics and behaviors of highly successful weight loss maintainers (Klem et al., 1997). For example, studies from the NWCR have demonstrated that individuals successful at weight loss maintenance report continued consumption of a reduced calorie, low fat diet, regular engagement in high levels of physical activity, and frequent self-weighing (Klem et al., 1997; McGuire et al., 1999). The current study focused on identifying chronotype and characterizing sleep habits in a group of successful weight loss maintainers (NWCR), and compared them to overweight and obese individuals enrolling in two behavioral weight loss interventions (INT). Compared to INT participants, we hypothesized that more NWCR would be categorized as morning-type chronotype. Further, we hypothesized that NWCR participants would have better sleep quality and longer sleep duration compared to INT participants.

Methods and Procedures

Participants

Participants were recruited for the NWCR through national and local television, radio, magazine, and newspaper advertisements. Eligibility requirements for participation in the NWCR included weight loss of ≥ 13.6 kg and duration of weight loss maintenance ≥ 1 year. Those interested in joining the NWCR were mailed a consent form and questionnaire packet and asked to report their maximum weight, current weight, and weight loss and to provide verification of their weight loss by photographs, physician report, or collateral testimony. There was no compensation for participation in the registry. For the present study, 1,000 NWCR participants who had consented to complete on-line questionnaires and had completed their most recent year’s follow-up questions were emailed a link to use for this study.

INT participants were recruited from two behavioral weight management programs at the Weight Control and Diabetes Research Center in Providence, RI. For each study, participants responded to newspaper or Internet advertisements and were screened by phone for basic eligibility criteria (BMIs > 25 kg/m2, no current medical conditions affecting safety of the program, not using any medications that affect weight, and not currently enrolled in another weight management program). Participants who met basic eligibility criteria were invited to attend an in-person orientation visit, where they completed informed consent and baseline study measures. Participants were not compensated for completion of this assessment.

Measures

Demographics

Age, gender, race/ethnicity, marital status, and educational attainment were assessed via self-report questionnaire.

Height and weight

Height and weight were collected from NWCR participants using a self-report questionnaire; previous studies have demonstrated good accuracy of the self-report weight data in the NWCR.(McGuire et al., 1999) Height and weight were measured for INT participants at an in-person assessment. Height was measured using a wall-mounted stadiometer, without shoes, to the nearest .1 cm. Weight was measured in one layer of light indoor clothing, without shoes, to the nearest .1 kg using a calibrated digital scale. Height and weight for each participant were used to calculate body mass index (BMI).

Morningness/Eveningness

Chronotype was assessed using the Morningness-Eveningness Questionnaire (MEQ), a 19-item questionnaire developed by Horne and Ostberg (1975) to assess chronotype via self-reported habitual bed and wake times, alertness at waking and bedtimes, and preferred times of physical and mental performance. The MEQ has acceptable internal reliability (Smith et al., 1989), and chronotype categorization from the MEQ has been validated by objectively measured sleep/wake times in adults (Carrier et al., 1997), physiological indicators such as body temperature (Kerkhof et al., 1980; Kerkhof & Van Dongen, 1996) and electrocortical activity (Ishihara et al., 1987; Kerkhof et al., 1980), and cognitive measure such as alertness (Natale & Cicogna, 2002) and performance tasks (Horne et al., 1980; Kerkhof et al., 1980).

Sleep Quality

Sleep quality and duration were measured using the Pittsburgh Sleep Quality Index (PSQI; Buysse et al., 1989). This measure has been demonstrated to have high reliability and good validity for assessing impaired sleep (Backhaus et al., 2002). Both the PSQI total score and subscale scores were used, including the subscales assessing duration of sleep, sleep disturbance, sleep latency, day dysfunction due to sleepiness, sleep efficiency, and need for sleep medications.

Statistical Analyses

All analyses were conducted using SAS v9.3 for Windows (SAS Institute Inc., 2011). Of the 797 NWCR participants who completed the online questionnaire, 67 were excluded from analyses for no longer meeting registry entry requirements (no longer maintaining a weight loss ≥ 13.6 kg), and 40 were excluded due to missing items on the chronotype and sleep measures that prevented calculation of scale and total summary scores, leaving a total sample of 690. Data from four INT participants were excluded due to missing items on the sleep measures, leaving a total sample of 75. Participants in both INT studies were asked to complete the PSQI at their first study assessment, but only those in the second study (N=52) were asked to complete the MEQ.

Demographic differences between the NWCR and INT samples were assessed using independent samples t-tests and chi-square analyses. As morningness/eveningness scores have been shown to increase with age (Carrier et al., 1997; Monk & Kupfer, 2007), age was controlled as a covariate in the primary analyses for morningness/eveningness and sleep.

Morningness/Eveningness

An ANCOVA using SAS proc GLM was used to investigate differences in total MEQ scores by group (NWCR vs. INT) after controlling for participant age. The original cut-offs recommended by Horne & Ostberg (1975) were developed using data from college students and have been criticized for misclassifying chronotype in middle-aged adults; thus, in our analyses we used cut-offs for morningness/eveningness that were developed specifically for use with middle-aged adults (Taillard et al., 2004), participants who scored above 69 on the MEQ were categorized as ‘definitely morning type,’ those who scored 65–69 as ‘moderately morning type,’ those who scored 53–64 as ‘neither type,’ those who scored 52–47 as ‘moderately evening type,’ and those who scored less than 47 as ‘definitely evening type.’ A chi-square analysis was used to investigate differences in MEQ categorization between the NWCR and INT groups. To investigate significant differences following this analysis, ‘definitely morning type’ and ‘moderately morning type’ were collapsed into a general ‘morning type’ category, and ‘definitely evening type’ and ‘moderately evening type’ were collapsed into ‘evening type’(Horne et al., 1980; Horne & Ostberg, 1975). We further replicated this analysis using the cut-offs originally developed by Horne and Ostberg (1975).

Sleep Quality

Analyses of covariance (ANCOVAs; using SAS proc GLM) were used to investigate differences in PSQI total score and subscale scores between NWCR and INT, after adjusting for age. Two chi-square analyses were used to assess differences between NWCR and INT in proportion of participants reporting less than six hours and less than seven hours of sleep each night. Finally, participants were categorized using established cut-offs for “good sleep quality” (total PSQI score ≤ 5) and “poor sleep quality” (total PSQI score > 5; Buysse et al., 1989) and differences in categorization were assessed using a chi-square analysis.

Results

The NWCR participants reported an average weight loss of −33.91 ± 17.21 kg at the time the questionnaire was administered (representing a −29.93 ± 9.63% reduction from maximum lifetime weight), and reported maintaining this loss for an average of 7.26 ± 6.05 years. Demographic data, by study, are presented in Table 1. There were no significant differences between the NWCR and INT samples in terms of gender or marital status, all ps > .05. As anticipated, the NWCR participants had lower BMIs compared to INT participants, t(763) = 15.94, p < .0001. NWCR participants were significantly younger than INT participants, t(763) = 2.63, p = .009, and there was a significant difference between samples in terms of race/ethnicity, Fisher’s exact p = .04, and education, χ2(4) = 42.16, p < .001, such that the NWCR participants were more likely identify as non-Hispanic Caucasian and to report a college or graduate/professional degree compared to INT participants.

Table 1.

Baseline demographic characteristics of NWCR and INT participants.

NWCR
INT
n = 690 n = 75
Age (SD), years 51.72 (12.54) 55.67 (10.43)a
BMI (SD), kg/m2 26.37 (5.07) 36.19 (4.66)a
Gender (%)
 Female 72.61 77.33
 Male 27.39 22.67
Ethnicity (%)
 African American 2.0% 4.0%b
 Asian 1.5% 0.0%
 Caucasian 92.7% 88.0%
 Hispanic 2.8% 1.3%
 Other/Multiple 1.6% 6.7%
Marital Status (%)
 Single 14.8% 17.3%
 Married or living with a partner 72.3% 62.7%
 Separated/Divorced 13.0% 20.0%
Education (%)
 High school or less 2.6% 10.7%a
 Vocational Training 1.9% 5.3%
 Some college 11.2% 29.3%
 College or university degree 35.1% 26.7%
 Graduate degree 49.1% 28.0%
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a

p < .01

b

p< .05

Morningness/Eveningness

After controlling for age, NWCR participants had significantly higher MEQ scores than INT participants (see Table 2), suggesting that NWCR participants were more likely to be “morning type” compared to INT, Cohen’s d = .38. Adjusting for education did not affect the results. Using the “morning-type” and “evening-type” categorizations developed for middle aged adults (Taillard et al., 2004), there was a significant difference between NWCR and INT, Fisher’s exact p = .014 (see Figure 1), such that more NWCR participants were categorized as morning type (definitely or moderately) compared to INT (33.8% compared to 25.0%) and less as evening types (19.7% vs. 30.8%). Analyses completed using the original cut-offs developed by Horne and Ostberg (1975) demonstrated the same pattern of results.

Table 2.

PSQI total and subscale scores and MEQ total scores, by group.

NWCR
INT
p
M SE M SE
PSQI Total1 5.02 0.11 6.05 0.34 .005
PSQI Subscales
 Duration 0.37 0.03 0.67 0.08 < .001
 Sleep Disturbance 1.21 0.02 1.31 0.06 .073
 Sleep Latency 0.80 0.03 1.19 0.10 < .001
 Day Dysfunction 0.75 0.03 0.81 0.08 .503
 Sleep Efficiency 0.33 0.03 0.48 0.08 .069
 Sleep Quality 0.93 0.03 1.13 0.08 .015
 Need Meds to Sleep 0.63 0.04 0.47 0.13 .232
MEQ Total2 59.82 0.35 56.00 1.27 .004
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1

Lower scores = Better sleep.

2

Higher scores = Higher morningness tendencies

Figure 1.

Figure 1

Open in a new tab

Morningness/Eveningness categorization by group, using cut-offs developed for middle-aged adults.

Sleep Quality and Duration

PSQI total scores and subscale scores are presented by group in Table 2. After adjusting for age, the NWCR participants had significantly lower total PSQI scores compared to INT participants, indicating that they reported better overall sleep quality than INT participants, Cohen’s d = .35. Further, on the PSQI subscales, NWCR participants reported significantly better duration of sleep, less sleep latency (time to fall asleep), and better self-reported sleep quality. There were no differences between the NWCR and INT groups in terms of sleep disturbance, day dysfunction due to sleepiness, sleep efficiency, or needing medications to sleep.

On average, NWCR participants reported taking approximately (mean ± SE) 17.4 ± 0.7 minutes to fall asleep, compared to 23.6 ± 2.0 minutes reported by INT participants, F(1,763) = 8.80, p = .003, ȵ2partial = .011. Significantly fewer participants in the NWCR group reported <6 hours (7.0% for NWCR compared to 18.7% of INT χ2(1) = 12.46, p < .001) or <7 hours of sleep each night (29.6% for NWCR compared to 45.3% INT, χ2(1) = 7.85, p = .005). Using established cut-offs for assessing “good sleep quality” compared to “poor sleep quality,” NWCR participants were significantly more likely to report “good sleep quality,” (66.4% NWCR compared to 52.0% INT), χ2(1) = 6.14, p = .013.

Discussion

Results from the current study demonstrated that individuals who have been highly successful at both weight loss and long-term maintenance were more likely to be categorized as a “morning type” chronotype and reported longer sleep duration and better sleep quality compared to treatment-seeking overweight and obese participants. Further, these NWCR participants were more likely to report shorter sleep latency (time required to fall asleep) and were less likely to report short sleep, defined as either <6 or <7 hours of sleep per night, than INT participants. Effect sizes for differences between total MEQ and PSQI scores indicate small to moderate effect of group on chronotype and sleep quality.

A previous population study of morningness/eveningness found that approximately 24.7% of middle-aged adults were categorized as morning-type (Taillard et al., 2004); Categorization of MEQ scores in the INT participants closely mirrored these population estimates, at 25.0%, whereas 33.8% of the NWCR sample were categorized as morning type. These results suggest that individuals who are successful at long-term weight maintenance may be especially likely to morning-type chronotype. In addition, NWCR members were far less likely to be short sleepers, with only 7% reporting sleep duration of <6 hours compared to 19% of INT. What remains unknown is the direction of these associations. Does morning chronotype or better sleep predict success at long-term maintenance, or does success at weight loss maintenance alter chronotype and sleep? Previous studies with NWCR participants suggest several health behaviors that could feasibly impact both chronotype and sleep, such as high levels of physical activity (Klem et al., 1997) and regular breakfast consumption (Wyatt et al., 2002), and weight loss has been shown to lead to improvements in both sleep apnea (Foster et al., 2009) and sleep quality and duration (Toor et al., 2012). Conversely, both genetic markers for evening-type chronotype (Garaulet et al., 2012) and short sleep duration/poor sleep quality (Thomson et al., 2012) have been shown to predict smaller weight losses following intervention. Indeed, although the correlational nature of the current study precludes causal inferences, they are interesting in relation to results by Thomson and colleagues (2012), who demonstrated that better sleep quality increased the likelihood of weight loss success by 33%. A third possibility may be that there is a reciprocal relationship between these factors. While it is unknown whether intervention can affect chronotype, effective interventions for improving sleep quality exist (Edinger et al., 2001; Sivertsen et al., 2006; Vitiello et al., 2009); thus, future research should focus on measuring both chronotype and sleep before, during, and after weight loss to examine the direction of these effects and to examine whether attempts to intervene on these factors may impact success at weight loss and maintenance.

The current study represents the first investigation into the chronotype classification and sleep habits of successful weight loss maintainers. Strengths of the current study included the examination of novel correlates of weight loss maintenance, the collection of data from a large sample of successful weight loss maintainers, and the comparison of these data from successful weight loss maintainers to treatment-seeking obese and overweight individuals at enrollment for a weight management program.

Despite these strengths, the current study had several limitations. First, all sleep data (from both NWCR and INT) were self-reported, which may introduce bias. The methods of data collection utilized were not suited to the use of actigraphy to measure sleep; however, the PSQI has been widely used to assess sleep in both population and intervention studies, and has demonstrated validity for assessing impaired sleep (Backhaus et al., 2002). As discussed previously, the cross-sectional nature of the current data prevents causal interpretation of the results. Further, it is unknown whether individuals without a lifetime history of overweight/obesity differ in chronotype or sleep from individuals successful at long-term weight loss maintenance. Future studies should compare successful weight loss maintainers to normal weight individuals to assess whether these differences may be associated with current weight status rather than history of weight loss/maintenance. Finally, the current study did not assess nor adjust for sleep apnea. As prevalence of sleep apnea is associated with obesity (Vgontzas et al., 1994), future research should investigate symptoms of sleep apnea when investigating sleep quality and duration.

Conclusion

In summary, the current results establish an association between successful weight loss maintenance and morning-type chronotype. Further, we demonstrated that successful weight loss maintainers were more likely to report longer sleep duration and improved sleep quality compared to treatment-seeking overweight and obese adults. Future research should investigate whether chronotype categorization and sleep quality change as a result of weight loss, or if morning-type chronotype and better sleep quality predict later success at weight loss and long-term maintenance.

Acknowledgments

Funding: This study was funded by the National Cancer Institute (National Institutes of Health) under award number 5U01CA150387 awarded to RRW, and by the National Institute of Diabetes Digestive and Kidney Diseases (National Institutes of Health) under award number F32DK100069 awarded to KMR. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

Conflict of Interest: The authors declare that they have no conflict of interest.

Ethical approval: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study.

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