Prevalence of excessive daytime sleepiness and associated factors in women aged 35-49 years from the "Pindamonhangaba Health Project" (PROSAPIN)

Abstracts

OBJETIVO: Estimar a prevalência da sonolência diurna excessiva (SDE) e identificar os fatores associados em mulheres de 35 a 49 anos de idade do "Projeto de Saúde de Pindamonhangaba" (PROSAPIN). MÉTODOS: O estudo foi observacional transversal com 372 mulheres com idade entre 35 e 49 anos selecionadas aleatoriamente da Estratégia Saúde da Família (ESF) do município de Pindamonhangaba, São Paulo, onde é desenvolvido o "Projeto de Saúde de Pindamonhangaba" (PROSAPIN). A SDE foi avaliada por entrevista utilizando a Escala de Sonolência de Epworth e os fatores associados por meio de questões que investigaram as características sócio-demográficas, a história ginecológica, a presença de comorbidades, o estilo de vida, a rotina de sono e o uso de medicamentos capazes de alterar o estado de alerta, além de mensuradas as variáveis antropométricas. Estimou-se a prevalência da SDE com intervalo de confiança de 95% (IC 95%) e foram identificados os fatores associados por meio de um modelo de regressão logística múltipla realizado no Programa Stata, versão 10.0. RESULTADOS: A prevalência da SDE foi de 18,5% (IC 95%: 14,7- 22,9) e os fatores associados foram: profissão relacionada a serviços domésticos (OR = 2,2; IC 95%: 1,1-4,3), nível de atividade física acima da média da população estudada (OR = 1,9; IC 95%: 1,1-3,4); e a presença de características sugestivas de ansiedade (OR = 1,9; IC 95%: 1,1-3,4). CONCLUSÃO: A prevalência da SDE em mulheres de 35 a 49 anos do PROSAPIN foi elevada e associada à característica sociodemográfica, à presença de comorbidades e ao estilo de vida.

Distúrbios do sono por sonolência excessiva; mulheres; saúde pública

ORIGINAL ARTICLE

^IMSc in Public Health; Professor at Fundação Universitária Vida Cristã (FUNVIC), São Paulo, SP, Brazil

^IIPhD in Public Health; Professor of the Department of Physical Therapy, Speech Therapy and Occupational Therapy, Faculdade de Medicina, Universidade de São Paulo (FMUSP), São Paulo, SP, Brazil

^IIIAssociate Professors, Faculdade de Saúde Pública, Universidade de São Paulo (FSP/USP), São Paulo, SP, Brazil

^IVMSc; Professor, Universidade de Taubaté (UNITAU), Taubaté, SP, Brazil

^VDirector of the Sleep Laboratory, Instituto do Coração (INCOR), São Paulo, SP, Brazil

^VIPhD; Professor, Faculdade de Medicina, Universidade do Chile, Santiago, Chile

Correspondence to

SUMMARY

OBJECTIVE: To estimate the prevalence of excessive daytime sleepiness (EDS) and to identify associated factors in women aged 35 to 49 years from the "Pindamonhangaba Health Project" (PROSAPIN).

METHODS: This was a cross-sectional observational study of 372 women aged 35 to 49 years, randomly selected from the Family Health Strategy (FHS) program of the city of Pindamonhangaba, SP, Brazil, where the "Pindamonhangaba Health Project" (PROSAPIN) is being developed. EDS was assessed through interviews using the Epworth Sleepiness Scale and the associated factors through questions that investigated sociodemographic characteristics, gynecological history, presence of comorbidities, lifestyle, sleep routine, and use of drugs capable of altering the state of alertness; anthropometric variables were also measured. The prevalence of EDS was estimated with a 95% confidence interval (95% CI) and the associated factors were identified through a multiple logistic regression model performed with the Stata software, release 10.0.

RESULTS: EDS prevalence was 18.5% (95% CI: 14.7-22.9) and the associated factors were: profession related to domestic services (OR = 2.2, 95% CI: 1.1-4.3), physical activity level above the mean of the study population (OR = 1.9, 95% CI: 1.1-3.4), and presence of features suggestive of anxiety (OR = 1.9, 95% CI: 1.1-3.4).

CONCLUSION: The prevalence of EDS in women aged 35-49 years from PROSAPIN was high and associated with sociodemographic characteristics, presence of comorbidities, and lifestyle.

Keywords: Disorders of excessive sleepiness; women; public health.

INTRODUCTION

Excessive daytime sleepiness (EDS) is a frequent complaint in the population and can result from diseases such as obstructive sleep apnea syndrome (OSAS)^1,2; depression; anxiety;use of drugs for heart disease, hypertension, diabetes, allergies, muscle contractures³; and habits such as alcoholism, sedentary lifestyle⁴, and insufficient sleep^5,6.

It compromises quality of life due to the impairment it causes in work performance, interpersonal relations, and cognitive and neuropsychological functions⁷, in addition to causing a higher risk of car accidents⁵, and metabolic⁸ and cardiovascular⁹ diseases.

Its prevalence is higher in individuals aged between 20 and 49 years, that is, during the most productive phase in life^5,10-14. It is known that high demands at work and the incessant quest for professional development are sources of physical exhaustion; this, associated with nonrestorative sleep, either due to the small number of hours slept or the poor quality of sleep, result in EDS¹⁵.

In females, excessive sleepiness is further aggravated by the accumulation of domestic responsibilities such as taking care of home and children¹⁶; apart from the fact that, after the age of 37, women suffer from hormonal fluctuations that lead to symptoms such as anxiety or depression, hot flashes, and night sweats that also interfere with sleep, making it lighter, intermittent, and shorter¹⁷.

It is essential that health professionals know the triggers of this condition and develop primary care strategies to prevent its occurrence or to minimize its negative effects on quality of life. Thus, this study aimed to estimate the prevalence of EDS in women aged 35 to 49 years treated by the "Pindamonhangaba Health Project" (PROSAPIN), and to identify possible anthropometric, sociodemographic, clinical, and lifestyle-related factors that may be associated with its occurrence.

METHODS

POPULATION

This is a cross-sectional study conducted in the municipality of Pindamonhangaba, in the countryside of the state of São Paulo, with women aged 35 to 65 years enrolled in the Family Health Strategy (FHS). At the time of the study, the municipality had a primary health care network consisting of 18 family health teams covering 34% of the population (45,537 individuals)¹⁸.

The reference population consisted of 7,212 women who were in the age group of interest and were registered in the FHS. Of these, 875 were randomly selected by systematic sampling with stratification by age and health unit. To calculate the sample size, the lowest prevalence of all variables studied in PROSAPIN were considered: 20% of metabolic syndrome¹⁹, a maximum error of 3% in 95% of the possible samples, and possible losses.

Of the 875 women, 126 did not participate in the study for the following reasons: two had cognitive deficit, 121 refused to participate or had changed address, one was unable to stand during the anthropometric measurements, and two were hospitalized during the data collection period. Thus, 749 women (85.6%) participated in the study.

The present article corresponds to an arm of PROSAPIN that studies EDS only in women younger than 50 years, i.e. from 35 to 49 years, thus providing a sample of 372 individuals.

PROSAPIN was authorized by the Health Secretariat of Pindamonhangaba and approved by the Ethics Committee of the School of Public Health, Universidade de São Paulo (FSP/USP) under protocol No. 1324.

DEPENDENT VARIABLE: EXCESSIVE DAYTIME SLEEPINESS

For the investigation, the Epworth Sleepiness Scale was used, which quantifies the propensity of the individual to fall asleep in the following routine situations: sitting and reading; watching TV; sitting in a public place, without activity (waiting room, meeting, movie theater); as a train, car, or bus passenger, riding for an hour without stopping; laying to rest in the afternoon when circumstances permit; sitting and talking to someone; sitting quietly after lunch without alcohol ingestion; and in the car while stopped for a few minutes in heavy traffic. This scale attributes a value to each question that corresponds to the chance of falling asleep: 0 = no, 1 = small, 2 = moderate, and 3 = high chance. Together, they generate a maximum score of 24 and a minimum of 0, identifying sleepy individuals as those with scores greater than 10²⁰.

INDEPENDENT VARIABLES

Anthropometric measurements were obtained (weight, height, and hip and abdomen circumferences) and interviews were conducted in order to obtain information on sleep (latency and number of hours slept), sociodemographic characteristics, gynecological history, and use of medications that can alter alertness. Furthermore, comorbidities and lifestyle were also assessed in the interview using validated instruments for: depression (Beck Depression Inventory)²¹, anxiety (Beck Anxiety Inventory)²², obesity (World Health Organization's Classification of Obesity)²³, obstructive sleep apnea (Berlin Questionnaire)²⁴, usual physical activity (Baecke Questionnaire)²⁵, and smoking and drinking (I National Survey on patterns of alcohol consumption and smoking in the Brazilian population)^26,27.

To ensure quality and prevent systematic errors, data collection was monitored daily and at the end of the study it was submitted to a re-check, by randomly selecting 10% the studied women for a re-interview by phone.

DATA ANALYSIS

The prevalence of EDS was estimated with 95% CI. Bivariate analyses were performed to identify possible associations between EDS and independent variables. A multiple logistic regression model was designed, initially including all variables that were associated with EDS in the bivariate analyses, and later testing the remaining variables. All analyses were performed using the software Stata, release 10.0.

RESULTS

372 women aged 35 to 49 years with a mean age of 41.5 ± 4.0 years were studied. The prevalence of EDS was 18.5% with 95% CI of 14.7% to 22.8%.

Table 1 shows the sociodemographic characteristics of the studied women, who were mostly married (81%), white (51%), Catholic (66%), and who attended school until the 8^th grade (72%). 48% had no paid work. Among those who worked, 22% had occupations related to domestic services (housekeepers, maids, cooks, etc.), and 83% had a per capita income of up to one minimum wage.

Table 2 describes the clinical characteristics reported by participants, of whom 68% menstruated regularly, 29% had systemic arterial hypertension (SAH), 5% had diabetes mellitus (DM), 8% had heart diseases, 19% had polycystic ovary syndrome (PCOS), and 8% had hyperuricemia. The measurement of anthropometric variables identified 65% of women with body mass index (BMI) > 25.52, i.e., overweight or obese, 70% with waist circumference (WC) > 88 cm, and 84% with a waist/hip ratio (WHR) > 0.80.

Table 2

Regarding lifestyle, a questionnaire that quantifies the level of usual physical activity, i.e., occupational energy expenditure in physical exercise or leisure activities and during locomotion, with the total physical activity being the sum of all these energy expenditures, was used for the assessment of physical activity. This instrument has no cutoff point, as it compares an individual only with other individuals belonging to the same population. Its analysis is based on through the mean value of energy expenditure in the population, indicating that some people are above or below the mean of this population. Thus, 55% of the women studied had a level of total physical activity up to the mean of the studied population.

Additionally regarding lifestyle, 24% were smokers, 25% drank alcohol, 37% reported the habit of sleeping fewer than six hours per night, and 27% reported using drugs that interfered with the state of alertness.

When the bivariate analyses were performed, associations between EDS and the level of occupational physical activity, leisure, and locomotion above the mean of that of the studied population (OR = 2.2, 95%

CI: 1.3-3.7); professions related to domestic services (OR = 2.5, 95% CI: 1.3-4.8); presence of PCOS (OR = 1.9, 95% CI: 1.0-3.5); and fewer than six hours of sleep per night (OR = 1.8, 95% CI: 1.1-3.2) were identified.

The final multiple logistic regression model identified the following factors as independently associated with EDS in the study population: level of occupational physical activity, leisure and locomotion above the mean of that of the study population; professional services related to domestic services; and features suggestive of anxiety²⁸ (Table 3).

This model also included the participants' menstrual regularity, and menstrual irregularity was not associated with the occurrence of EDS (OR = 1.2, 95% CI: 0.7-2.1).

DISCUSSION

Although no studies that investigated EDS exclusively in women aged 35-49 years were identified, the existing ones showed that part of their sample consisted of women in this age range^10,29-35.

In Brazil, only two population studies were found with a random sample that investigated exclusively EDS, with the inclusion of individuals of both genders older than 18 years. The first, conducted in the countryside of the state of Bahia, reported a prevalence of 21.5%²⁹.The second, conducted in the capital of the state of Mato Grosso do Sul, found a prevalence of 18.9%¹⁰. Both studies showed no prevalence stratified by gender and age, which makes it difficult to compare them with the present results.

The prevalence of EDS in other countries also shows variation. In Thailand, 19.5% of the population has excessive sleepiness symptoms³⁰; in Norway, 17.7%³¹; in Latin America (Mexico, Chile, Venezuela, and Uruguay), 16.4%³²; in Korea, 12.2%³³; in Spain, 11.6%³⁴;and in Japan, 2.5%³⁵. Although all of these studies included individuals of both genders aged > 18 years, only two showed the prevalence of EDS separated by gender, but not by age. Thus, in Korea excessive sleepiness is present in 13.7% of women³¹ and in Japan, in 2.2% of the women³⁵.

Some studies report that EDS is more prevalent among the elderly^36,2. However, other studies demonstrate that the frequency of the condition is higher in individuals aged 20 to 49 years^5,10-14. Corroborating these findings, this study found a high prevalence of EDS (18.5%) among women aged 35 to 49 years.

The present study showed three other high prevalence rates: depression (30%), anxiety (50%), and PCOS (19%). The first two rates corroborate the results of other Brazilian studies that investigated emotional disorders in women^37,38. However, the prevalence of PCOS is high when compared to the only study conducted in Brazil, in which the proportion of women with PCOS in Bahia was 8.5%³⁹.

The first hypothesis for the difference between the two studies refers to the type of instrument used for data collection. Fernandes³⁹ assessed the prevalence of PCOS using ultrasound equipment, while the present study's prevalence was assessed through a questionnaire, in which self-reporting of this disease included the woman in the group of affected individuals.

At first glance, the divergence suggests overestimation of the present study's PCOS prevalence. However, when comparing the prevalence of SAH reported by the present study's participants (29%) with the prevalence of hypertension measured by the anthropometry team (28%) the quality of the reported data is observed. Thus, a second hypothesis, that there actually is a difference between the prevalence of PCOS between the Northeast and Southeast regions, becomes more relevant. The similarity between the reported and measured data reinforces the validity of the present study, mainly related to the high prevalence of EDS in women aged 35-49 years.

EDS may derive from several factors, but the endocrine system appears to be of particular importance. Gracia et al.¹⁷ found that in the presence of progressive hormonal fluctuations of early menopausal transition, from 37 years of age onward, significant changes occur in sleep architecture, caused by the insufficiency of progesterone in the premenstrual phase.

In fact, difficulty in falling asleep or recurrent nocturnal awakenings are common premenstrual symptoms, affecting 20% to 40% of women in the menopausal transition, which, by reducing the number of hours of sleep, allow the onset of EDS⁴⁰.

In the bivariate analysis, there was a clear association between EDS and sleeping fewer than six hours a night, a fact already well-documented in the young population, for which there was an increased prevalence of EDS from 15.6% in 1960 to 37.1% in 2001⁴¹. It seems that the main reason for this increase is professional, as the young individual, concerned about earning an income, starts working early and often has more than one job¹⁵. In the case of women, the situation becomes even more complex due to the accumulation of responsibilities for the care of children and home¹⁶.

However, the association between sleeping fewer than six hours a night and the presence of EDS lost part of its statistical significance in the multivariate analysis. A possible explanation is that the interviewees were questioned regarding the number of hours slept during the night, without any questions about the habit of sleeping during the day. Considering that 47.7% of participants did not work outside the home, the habit of daytime sleep may have been a confounding factor, not fully controlled in the analysis.

Another significant risk factor for the development of EDS in the present study was the domestic nature of work (maids, housekeepers, cooks, washerwomen or cleaning aid) possibly due to the long working hours inherent to these activities, which include little or no rest intervals⁴².

According to the physical activity questionnaire used (Baecke)²⁵, it was observed that participants who had a level of physical activity with intensity and frequency greater than the mean of the studied sample had a higher risk of developing EDS. Although some studies have reported that physical activity reduces or eliminates EDS, in a more refined analysis, all studies that reported reduction of EDS had the bias of including only physical activity programs, without considering usual physical activities originating from daily activities^4,36, which prevents comparison with the present results.

Therefore, it is believed that a level of physical activity above the average for a specific population may mean an activity overload, favoring an increase in EDS.

It was also observed that the presence of features suggestive of anxiety was another risk factor for EDS, a result that is similar to that obtained by Kravitz et al.⁴³, in which 35% of women in menopausal transition who had this emotional disorder had difficulty falling sleep.

Other possible factors responsible for EDS are the concerns of everyday life, such as little help from the spouse regarding household chores, lack of social strategies to ensure the education and care of children, and fear of not providing adequate care for children and of not dedicating appropriately to one's career¹⁶.

Any type of worry may be a triggering agent of the process: difficulties in falling asleep, fewer hours of sleep, malaise, fatigue, and EDS on the following day.

Obesity and WC > 88 cm are other risk factors for the development of EDS. However, the latter has been more involved in the onset of OSA syndrome, characterized by repeated pauses in breathing, lasting > 10 seconds, followed by transiently waking or superficial sleep throughout the night, which results in sleep fragmentation or deprivation, of which the main clinical manifestation is EDS^1,2,44.

The study found no association between EDS, waist circumference, and OSA, possibly because the women classified as overweight or obese (BMI > 25), or with waist circumference > 88 cm, had a homogenous distribution of fat in the hip and abdomen regions (gynecoid shape).

The results of this study reflect the profile of the studied population, as the Pindamonhangaba FHS treats most often the poorer population, with the vast majority being women with low educational level and income.

The professional activities related to domestic services may have been associated with EDS due to the fact that many participants were not employed during the study period (some lived on welfare provided by the federal government) and the low level of schooling may not have allowed other types of work rather than domestic ones. However, it is important to emphasize that professions like those require great physical effort, and consequently cause fatigue.

Finally, some information about the present study must be considered. First, as it is an epidemiological study, the focus was to screen for features suggestive of some diseases and not to perform diagnoses.

Second, as this is a transversal study, it does not allow for conclusions regarding causality. Another point to be taken into account that the data were obtained through interviews, thus important information may have been omitted. In spite of the use of validated tools, the multiple sleep latency test was not performed to confirm EDS.

CONCLUSION

The prevalence of EDS in women aged 35-49 years from PROSAPIN was high and among the main risk factors for its occurrence, a level of physical activity greater than the mean observed in the studied population a profession associated to housework and characteristics suggestive of anxiety must be emphasized; these results are relevant in terms of public health.

REFERENCES

• 1. Bixler EO, Vgontzas AN, Lin HM, Calhoun SL, Vela-Bueno A, Kales A. 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.
• 2. Tsuno N, Jaussent I, Dauvilliers Y, Touchon J, Ritchie K, Besset A. Determinants of excessive daytime sleepiness in a French community-dwelling elderly population. J Sleep Res. 2007;16:364-71.
• 3. Gooneratne NS, Weaver TE, Cater JR, Pack FM, Arner HM, Greenberg AS et al. Functional outcomes of excessive daytime sleepiness in older adults. J Am Geriatr Soc. 2003;51:642-9.
• 4. Toledo Guimarães CLH, Carvalho LB, Yanaguibashi G, Prado GF. Physically active elderly women sleep more and better than sedentary women. Sleep Med. 2008;9:488-93.
• 5. Kim H, Young T. Subjective daytime sleepiness: dimensions and correlates in the general population. Sleep. 2005;5:625-34.
• 6. Kezirian EJ, Harrison SL, Ancoli-Israel S, Redline S, Ensrud S, Claman DM et al; Study of Osteoporotic Fractures Research Group. Behavioral correlates of sleep-disordered breathing in older women. Sleep. 2007;30:1181-8.
• 7. Bittencourt LR, Silva RS, Santos RF, Pires ML, Mello MT. Excessive daytime sleepiness. Rev Bras Psiquiatr. 2005;27(Suppl I):16-21.
• 8. Aloia MS, Arnedt JT, Smith L, Skrekas J, Stanchina M, Millman RP. Examining the construct of depression in obstructive sleep apnea syndrome. Sleep Med. 2005;6:115-21.
• 9. Davies DP, Rodgers H, Walshaw D, James OF, Gibson GJ. Snoring, daytime sleepiness and stroke: a case-control study of first-ever stroke. J Sleep Res. 2003;12:313-8.
• 10. Souza JC, Magna LA, Reimão R. Excessive daytime sleepiness in the Campo Grande general population, Brazil. Arq Neuropsiquiatr. 2002;60:558-62.
• 11. Liu X, Uchiyama M, Klim K, Okawa M, Shibui K, Kudo Y et al. Sleep loss and daytime sleepiness in the general adult population of Japan. Psychiatry Res. 2002;93:1-11.
• 12. Doi Y, Minowa M. Gender differences in excessive daytime sleepiness among Japanese workers. Soc Sci Med. 2003;56:883-94.
• 13. Hasler G, Buysse DJ, Gamma A, Adjacic V, Eich D, Rössler W et al. Excessive daytime sleepiness in young adults: a 20-year prospective community study. J Clin Psychiatr. 2005;66:521-9.
• 14. Gander PH, Marshall NS, Harris R, Reid P. The Epworth Sleepiness Scale: influence of age, ethnicity, and socioeconomic deprivation. Epworth Sleepiness scores of adults in New Zealand. Sleep. 2005;28:249-53.
• 15. Young TB. Epidemiology of daytime sleepiness: definitions, symptomatology and prevalence. J Clin Psychiatr. 2004;65(Suppl 16):12-6.
• 16. Spindola T, Santos RS. Mujer y trabajo - La historia de vida de madres trabajadoras en enfermería. Rev Latinoam Enferm. 2003;11:593-600.
• 17. Gracia CR, Sammel MD, Freeman EW, Lin H, Langan E, Kapoor S et al. Defining menopause status: creation of a new definition to identify the early changes of the menopausal transition. Menopause. 2005;12:128-35.
• ¹⁸
  Brasil. Ministério da Saúde: Sistema de Informação da Atenção Básica. [citado 21 jun 2007]. Disponível em: http://www.datasus.gov.br
  » link
• 19. Royer M, Castelo-Branco C, Blümel JE, Chedraui PA, Danckers L, Bencosme A et al. The US National Cholesterol Education Programme Adult Treatment Panel III (NCEP ATP III): prevalence of the metabolic syndrome in postmenopausal Latin American women. Climacteric. 2007;10(2):164-70.
• 20. Johns MW. A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep. 1991;14:540-5.
• 21. Beck AT, Rial WY, Rickels K. Short form of depression inventory: cross-validation. Psychol Rep. 1974;34:1184-6.
• 22. Beck AT, Steer RA, Brown G. Beck anxiety checklist. University Pensylvania; 1985.
• 23. World Health Organization (WHO). Physical status: the use and interpretation of anthropometry. Geneve; 1996. A compilation of twenty-two essays delivered in America between, 1996.
• 24. Netzer NC, Stoohs RA, Netzer CM, Clark K, Strohl KP. Using the Berlin Questionnaire to identify patients at risk for the sleep apnea syndrome. Ann Intern Med. 1999;131:485-91.
• 25. Florindo AA, Latorre MR. Validation and reliability of the Baecke questionnaire for the evaluation of habitual physical activity in adult men. Rev Bras Med Esporte. 2003;9:129-15.
• 26. Marques ACPR, Zaleski M, Caetano R, Laranjeira R, Pinsky I, Gigliotti A et al. Estudo da prevalência de fumantes em uma amostra probabilística da população brasileira em 2006. São Paulo; 2006.
• 27. Castro-Costa E, Ferri CP, Lima-Costa MF, Zaleski M, Pinsky I, Caetano R, Laranjeira R. Alcohol consumption in late-life--the first Brazilian National Alcohol Survey (BNAS). Addict Behav. 2008;33(12):1598-601.
• 28. Cunha JA. Manual da versão em português das Escalas de Beck. São Paulo: Casa do Psicólogo; 2001.
• 29. Souza JC, Magna LA, Aiache S, Magna NS. Excessive daytime sleepiness in the general population of a Brazilian city. J Bras Psiquiatr. 2008;57:34-7.
• 30. Tubtimtes S, Sukying C, Prueksaritanond S. Sleep problems in out-patient of primary care unit. J Med Assoc Thai. 2009;92:273-8.
• 31. Pallesen S, Nordhus IH, Omvik S, Sivertsen B, Tell GS, Bjorvatn B. Prevalence and risk factors of subjective sleepiness in the general adult population. Sleep. 2007;30:619-24.
• 32. Bouscoulet LT, Vázquez-García JC, Muiño A, Márquz M, López MV, Oca MM et al. Prevalence of sleep related symptoms in four Latin American cities. J Clin Sleep Med. 2008;4:579-85.
• 33. Joo S, Baik I, Yi H, Jung K, Kim J, Shin C. Prevalence of excessive daytime sleepiness and associated factors in the adult population of Korea. Sleep Med. 2009;10:182-8.
• 34. Vela-Bueno A, De Iceta M, Fernández C. Prevalence of sleep disorders in Madrid, Spain. Gac Sanit. 1999;13:441-8.
• 35. Kaneita Y, Ohida T, Uchiyama M, Takemura S, Kawahara K, Yokoyama E et al. Excessive daytime sleepiness among the Japanese general population. J Epidemiol. 2005;15:1-8.
• 36. Whitney CW, Enright PL, Newman AB, Bonekat W, Foley D, Quan SF. Correlates of daytime sleepiness in 4578 elderly persons: the Cardiovascular Health Study. Sleep. 1998;21:27-36.
• 37. Fernandes RCL, Rozental M. Avaliação da sintomatologia depressiva de mulheres no climatério com escala de rastreamento populacional para depressão CES-D. Rev Psiquiatr Rio Gd Sul. 2008;30:192-200.
• 38. Polissen AF, Araújo DAC, Polissen F, Mourão Junior CA, Polissen J, Fernandes ES et al. Depressão e ansiedade em mulheres climatéricas: fatores associados. Rev Bras Ginecol Obstet. 2009;31:28-34.
• 39. Fernandes LG. Síndrome dos ovários policísticos em Salvador, Brasil: um estudo de prevalência na atenção primária de saúde [dissertação]. Bahia: Instituto de Saúde Coletiva, Universidade Federal da Bahia; 2009.
• 40. Lee KA, Baker FC, Newton KM, Ancoli-Israel S. The influence of reproductive status and age on women's sleep. J Womens Health. 2008;17:1209-14.
• 41. Crispim CA, Zalcman I, Dáttilo M, Padilha HG, Tufik S, Mello MT. Relation between sleep and obesity: a literature review. Arq Bras Endocrinol Metab. 2007;51:1041-9.
• 42. Diogo MF. Significance in cleaning and conservation activities. Psicol Estudo. 2007;12:483-92.
• 43. Kravitz HM, Ganz PA, Bromberger J, Powell LH, Sutton-Tyrrell K, Meyer PM. Sleep difficulty in women at midlife: a community survey of sleep and the menopausal transition. Menopause. 2003;10:19-28.
• 44. Martins AB, Tufik S, Moura SM. Physiopathology of obstructive sleep apneahypopnea syndrome. J Bras Pneumol. 2007;33:93-100.

Prevalence of excessive daytime sleepiness and associated factors in women aged 35-49 years from the "Pindamonhangaba Health Project" (PROSAPIN)

Elaine Cristina Alves Pereira^I; Ana Carolina Basso Schmitt^II; Maria Regina Alves Cardoso^III; Wendry Maria Paixão Pereira^IV; Geraldo Lorenzi-Filho^V; Juan Enrique Blumel^VI; José Mendes Aldrighi^III

Publication Dates

• Publication in this collection
  24 Aug 2012
• Date of issue
  Aug 2012

History

• Received
  14 Mar 2011
• Accepted
  28 Mar 2012