Various psychosocial factors may mediate how sleep is disrupted during pregnancy. These factors include the age of the mother, her initial and subsequent BMI, ethnicity, and health behaviors such as nutritional practices, exercise practices, smoking or consumption of alcohol. Unfortunately, few studies examining sleep in general have reported on these factors, and only one study assessing sleep during pregnancy has commented on any of these variables. Studies considering gender and/or age differences have provided some of the information. Increasing age, for instance, was found to be associated with less time asleep, poorer sleep efficiency, and more minutes awake in the last 2 h of sleep (Carrier, Land, Buysse, Kupfer, and Monk 2001). Similarly, women between the ages of 30 and 40 had less SWS percentage compared to women between 20 and 30 years of age (Ehlers and Kupfer 1997). The only study assessing how age influenced sleep during pregnancy supported the previous study: older pregnant women had less total sleep than younger pregnant women (Hedman et al. 2002). Extrapolation and comparison from most of the studies examining gender and/or age is difficult because a majority of the individuals in these studies are beyond childbearing years and subsequently may have age-associated sleep changes, such as hormonal changes.
There have been several studies that have considered sleep in women of childbearing years and variables that may affect sleep patterns. In a study of employed women, Lee (1992) found influences of age on how women self-reported their sleep disturbances. Younger women reported having poorer sleep quality, while older women stated less sleep quantity, increased difficulty initiating sleep, more midsleep awakenings and increased sleepiness during the day. A study evaluating a sleep restriction protocol in women and how age modulates its effects showed that younger women (~23 years) had more SWS than older women (~60 years), and had increased sleepiness as depicted by the Stanford Sleepiness Scale and the Maintenance of Wakefulness Test (MWT); furthermore, the percentage of SWS was well preserved in the older sample (Stenuit and Kerkhofs 2005). Recently, Tworoger, Davis, Vitiello, Lentz, and McTiernan (2005) considered various factors associated with sleep reported objectively and subjectively in a sample of young, normally cycling women (~30 years). They found that increased BMI was associated with poorer sleep efficiency and more wake time, although the sample was lean (~24 ± 3.8). No correlations were observed between alcohol consumption or exercise and physiologically recorded or subjectively reported sleep.
Another factor that has been considered to be sleep disrupting with and without a relationship to age/gender is smoking. Data stemming from the past 25 years have linked smoking with shorter sleep duration (Palmer, Harrison, and Hiorns 1980), and chronic insomnia, including difficulty initiating and maintaining sleep (Phillips and Danner 1995). It has been suggested that nocturnal nicotine withdrawals are one of the subsequent causes for nocturnal awakenings (Colrain, Trinder, and Swan 2004). These frequent nocturnal awakenings may contribute to the findings that smokers have higher complaints of excessive daytime sleepiness, more reports of minor accidents, higher reported depression and greater impairment in daytime functioning than nonsmokers (Phillips et al. 1995). There are no reports considering the relationship between smoking and sleep disturbance during pregnancy, even though various studies have assessed smoking during pregnancy (Burguet et al. 2004; Kaneita et al. 2005; Narahara and Johnston 1993; Simhan, Caritis, Hillier, and Krohn 2005).
The importance of understanding the synergistic relationship among the psychosocial variables and sleep has been a more recent trend. Stepnowsky, Moore, and Dimsdale (2003) studied the effects of ethnicity on sleep and found that both in the laboratory and at home, Blacks had less SWS than Caucasians. Considering additional factors, Redline, Kirchner, Quan, Gottlieb, Kapur, and Newman (2004) evaluated sex, age, obesity and ethnicity on sleep architecture in a cohort from the Sleep Heart Health study. Although not fully applicable to women of childbearing age as the age range was from 37 to 92, they were able to show that parameters of sleep architecture differed in individuals who were older than 61 years of age compared to those <54 years old. Specifically, sleep was comprised of an increased amount of lighter sleep stages, 1 and 2, in the older subjects. Sleep was also shown to vary with ethnicity. American Indians had more Stage 1 sleep than Caucasians or Blacks, more Stage 2 and less SWS than Caucasians, Blacks, Hispanics, or Asian Americans. Similarly, Blacks had greater percentage Stage 2 sleep than Caucasians or Hispanics. The authors also considered how BMI related to sleep architecture. They showed that as BMI increased lighter stages of sleep, i.e., Stages 1 and 2, dominated the architecture and SWS diminished. Finally, due to the large sample size, the authors were able to evaluate how smoking status affected sleep architecture. They reported that people who smoked or were ex-smokers had more Stage 1 and 2 sleep compared to those who never smoked; and SWS was highest in those who never smoked, while lowest in those who currently smoked. Percent REM sleep was highest in current smokers compared to ex-smokers. Hong, Mills, Loredo, Adler, and Dimsdale (2005) evaluated similar demographic variables and visually scored sleep parameters in a large sample of men and women. Results indicate that being older was associated with increased percentage of Stage 1 and less SWS. The range of ages was 25 to 50. Furthermore, ethnicity, in particular being African-American, was associated with reduced percentage of SWS. No relationship was observed between sleep and BMI or smoking; this is likely a result of a fairly fit sample (average BMI 25.4 ± 4.1) and few smokers (7/63). In a large cohort sample of Japanese men and women, Sekine, Chandola, Martikainen, Marmot, and Kagamimori (2006) suggested that SES did not affect self-reported sleep quality, but being unmarried was associated with poor subjective sleep quality. Several psychosocial and behavioral factors have been considered in relation to sleep patterns, but clearly no definitive answers have been derived.
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