Self-reported body silhouette trajectories across the lifespan and excessive daytime sleepiness in adulthood: a retrospective analysis. The Paris Prospective Study III

Quentin Lisan, Muriel Tafflet, Marie-Aline Charles, Frédérique Thomas, Pierre Boutouyrie, Catherine Guibout, José Haba-Rubio, Marie Cécile Périer, Bruno Pannier, Pedro Marques-Vidal, Xavier Jouven, Jean-Philippe Empana, Quentin Lisan, Muriel Tafflet, Marie-Aline Charles, Frédérique Thomas, Pierre Boutouyrie, Catherine Guibout, José Haba-Rubio, Marie Cécile Périer, Bruno Pannier, Pedro Marques-Vidal, Xavier Jouven, Jean-Philippe Empana

Abstract

Objectives: Excessive daytime sleepiness (EDS) is a common sleep complaint in the population and is increasingly recognised as deleterious for health. Simple and sensitive tools allowing identifying individuals at greater risk of EDS would be of public health importance. Hence, we determined trajectories of body silhouette from early childhood to adulthood and evaluated their association with EDS in adulthood.

Design: A retrospective analysis in a prospective community-based study.

Participants: 6820 men and women self-reported their silhouette at ages 8, 15, 25, 35 and 45 using the body silhouettes proposed by Stunkard et al. EDS was defined by an Epworth Sleepiness Scale score ≥11.

Main outcome measure: Presence of EDS in adulthood.

Results: The study population comprised 6820 participants (mean age 59.8 years, 61.1% men). Five distinct body silhouettes trajectories over the lifespan were identified: 31.9% 'lean stable', 11.1% 'lean increase', 16.1% 'lean-marked increase', 32.5% 'moderate stable' and 8.4% 'heavy stable'. Subjects with a 'heavy-stable' trajectory (OR 1.24, 95% CI 0.94 to 1.62) and those with a 'lean-marked increase' trajectory (OR 1.46, 95% CI 1.18 to 1.81) were more likely to have EDS when compared with the 'lean-stable' group after adjusting for confounding. Further adjustment for birth weight strengthened the magnitude of the ORs.

Conclusion: Increasing body silhouette and to a lesser extent constantly high body silhouette trajectory from childhood to adulthood are associated with increased likelihood of EDS, independently of major confounding variables.

Trial registration number: NCT00741728; Pre-results.

Keywords: body silhouette; excessive daytime sleepiness; obesity; sleep; trajectory.

Conflict of interest statement

Competing interests: None declared.

© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Figures

Figure 1
Figure 1
Body silhouettes in (A) children and (B) adults, adapted from Stunkard et al.
Figure 2
Figure 2
Trajectories of body silhouette. Note: percentages represent the proportion of the population according to each trajectory.

References

    1. Johns M, Hocking B. Daytime sleepiness and sleep habits of Australian workers. Sleep 1997;20:844–7. 10.1093/sleep/20.10.844
    1. Whitney CW, Enright PL, Newman AB, et al. . Correlates of daytime sleepiness in 4578 elderly persons: the Cardiovascular Health Study. Sleep 1998;21:27–36. 10.1093/sleep/21.1.27
    1. Walsleben JA, Kapur VK, Newman AB, et al. . Sleep and reported daytime sleepiness in normal subjects: the Sleep Heart Health Study. Sleep 2004;27:293–8. 10.1093/sleep/27.2.293
    1. Boden-Albala B, Roberts ET, Bazil C, et al. . Daytime sleepiness and risk of stroke and vascular disease: findings from the Northern Manhattan Study (NOMAS). Circ Cardiovasc Qual Outcomes 2012;5:500–7. 10.1161/CIRCOUTCOMES.111.963801
    1. Ford ES, Cunningham TJ, Giles WH, et al. . Trends in insomnia and excessive daytime sleepiness among U.S. adults from 2002 to 2012. Sleep Med 2015;16:372–8. 10.1016/j.sleep.2014.12.008
    1. Melamed S, Oksenberg A. Excessive daytime sleepiness and risk of occupational injuries in non-shift daytime workers. Sleep 2002;25:315–22. 10.1093/sleep/25.3.315
    1. Empana JP, Dauvilliers Y, Dartigues JF, et al. . Excessive daytime sleepiness is an independent risk indicator for cardiovascular mortality in community-dwelling elderly: the three city study. Stroke 2009;40:1219–24. 10.1161/STROKEAHA.108.530824
    1. Baskin ML, Ard J, Franklin F, et al. . Prevalence of obesity in the United States. Obes Rev 2005;6:5–7. 10.1111/j.1467-789X.2005.00165.x
    1. Hayley AC, Williams LJ, Kennedy GA, et al. . Excessive daytime sleepiness and body composition: a population-based study of adults. PLoS One 2014;9:e112238 10.1371/journal.pone.0112238
    1. Vgontzas AN, Bixler EO, Tan TL, et al. . Obesity without sleep apnea is associated with daytime sleepiness. Arch Intern Med 1998;158:1333–7. 10.1001/archinte.158.12.1333
    1. Bixler EO, Vgontzas AN, Lin HM, et al. . Excessive daytime sleepiness in a general population sample: the role of sleep apnea, age, obesity, diabetes, and depression. J Clin Endocrinol Metab 2005;90:4510–5. 10.1210/jc.2005-0035
    1. Fernandez-Mendoza J, Vgontzas AN, Kritikou I, et al. . Natural history of excessive daytime sleepiness: role of obesity, weight loss, depression, and sleep propensity. Sleep 2015;38:351–60. 10.5665/sleep.4488
    1. Tsuno N, Jaussent I, Dauvilliers Y, et al. . Determinants of excessive daytime sleepiness in a French community-dwelling elderly population. J Sleep Res 2007;16:364–71. 10.1111/j.1365-2869.2007.00606.x
    1. Hayley AC, Williams LJ, Kennedy GA, et al. . Excessive daytime sleepiness and metabolic syndrome: a cross-sectional study. Metabolism 2015;64:244–52. 10.1016/j.metabol.2014.09.011
    1. Theorell-Haglöw J, Åkerstedt T, Schwarz J, et al. . Predictors for Development of Excessive Daytime Sleepiness in Women: A Population-Based 10-Year Follow-Up. Sleep 2015;38:1995–2003. 10.5665/sleep.5258
    1. Stettler N, Zemel BS, Kumanyika S, et al. . Infant weight gain and childhood overweight status in a multicenter, cohort study. Pediatrics 2002;109:194–9. 10.1542/peds.109.2.194
    1. Must A, Strauss RS. Risks and consequences of childhood and adolescent obesity. Int J Obes Relat Metab Disord 1999;23(Suppl 2):S2–11. 10.1038/sj.ijo.0800852
    1. Must A, Willett WC, Dietz WH. Remote recall of childhood height, weight, and body build by elderly subjects. Am J Epidemiol 1993;138:56–64. 10.1093/oxfordjournals.aje.a116777
    1. Tehard B, van Liere MJ, Com Nougué C, et al. . Anthropometric measurements and body silhouette of women: validity and perception. J Am Diet Assoc 2002;102:1779–84.
    1. Song M, Hu FB, Wu K, et al. . Trajectory of body shape in early and middle life and all cause and cause specific mortality: results from two prospective US cohort studies. BMJ 2016;353:i2195 10.1136/bmj.i2195
    1. Song M, Willett WC, Hu FB, Fb H, et al. . Trajectory of body shape across the lifespan and cancer risk. Int J Cancer 2016;138:2383–95. 10.1002/ijc.29981
    1. Fagherazzi G, Vilier A, Affret A, et al. . The association of body shape trajectories over the life course with type 2 diabetes risk in adulthood: a group-based modeling approach. Ann Epidemiol 2015;25:785–7. 10.1016/j.annepidem.2015.06.002
    1. Fagherazzi G, Guillas G, Boutron-Ruault MC, et al. . Body shape throughout life and the risk for breast cancer at adulthood in the French E3N cohort. Eur J Cancer Prev 2013;22:29–37. 10.1097/CEJ.0b013e328355ec04
    1. Empana JP, Bean K, Guibout C, et al. . Paris Prospective Study III: a study of novel heart rate parameters, baroreflex sensitivity and risk of sudden death. Eur J Epidemiol 2011;26:887–92. 10.1007/s10654-011-9618-x
    1. Johns MW. A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep 1991;14:540–5. 10.1093/sleep/14.6.540
    1. Stunkard AJ, Sørensen T, Schulsinger F. Use of the Danish Adoption Register for the study of obesity and thinness. Res Publ Assoc Res Nerv Ment Dis 1983;60:115–20.
    1. Pichot P. A self-report inventory on depressive symptomatology (QD2) and its abridged form (QD2) Assessment of depression: Springer, 1986:108–22.
    1. Baecke JA, Burema J, Frijters JE. A short questionnaire for the measurement of habitual physical activity in epidemiological studies. Am J Clin Nutr 1982;36:936–42. 10.1093/ajcn/36.5.936
    1. Thomas F, Pannier B, Safar ME. Impact of country of birth on arterial function in subjects living in France. J Am Soc Hypertens 2012;6:405–13. 10.1016/j.jash.2012.10.003
    1. Jones BL, Nagin DS. Advances in group-based trajectory modeling and an SAS procedure for estimating them. Sociol Methods Res 2007;35:542–71. 10.1177/0049124106292364
    1. Genolini C, Falissard B. KmL: a package to cluster longitudinal data. Comput Methods Programs Biomed 2011;104:e112–e121. 10.1016/j.cmpb.2011.05.008
    1. Buuren Svan, Groothuis-Oudshoorn K. mice: multivariate imputation by chained equations in R . J Stat Softw 2011;45:1–67. 10.18637/jss.v045.i03
    1. Miller AL, Lumeng JC, LeBourgeois MK. Sleep patterns and obesity in childhood. Curr Opin Endocrinol Diabetes Obes 2015;22:41–7. 10.1097/MED.0000000000000125
    1. Lee JM, Pilli S, Gebremariam A, et al. . Getting heavier, younger: trajectories of obesity over the life course. Int J Obes 2010;34:614–23. 10.1038/ijo.2009.235
    1. Ng WL, Orellana L, Shaw JE, et al. . The relationship between weight change and daytime sleepiness: the Sleep Heart Health Study. Sleep Med 2017;36:109–18. 10.1016/j.sleep.2017.05.004
    1. Barker DJ, Osmond C, Forsén TJ, et al. . Trajectories of growth among children who have coronary events as adults. N Engl J Med 2005;353:1802–9. 10.1056/NEJMoa044160
    1. Forsén T, Eriksson J, Tuomilehto J, et al. . The fetal and childhood growth of persons who develop type 2 diabetes. Ann Intern Med 2000;133:176–82. 10.7326/0003-4819-133-3-200008010-00008
    1. Power C, Thomas C. Changes in BMI, duration of overweight and obesity, and glucose metabolism: 45 years of follow-up of a birth cohort. Diabetes Care 2011;34:1986–91. 10.2337/dc10-1482
    1. Elks CE, Loos RJ, Sharp SJ, et al. . Genetic markers of adult obesity risk are associated with greater early infancy weight gain and growth. PLoS Med 2010;7:e1000284 10.1371/journal.pmed.1000284
    1. Elks CE, Heude B, de Zegher F, et al. . Associations between genetic obesity susceptibility and early postnatal fat and lean mass: an individual participant meta-analysis. JAMA Pediatr 2014;168:1122–30. 10.1001/jamapediatrics.2014.1619

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