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Original Article
ARTICLE IN PRESS
doi:
10.25259/JNRP_357_2024

Prevalence of restless legs syndrome and associated factors in rural West African country

Department of Neurology, Hubert Koutoukou MAGA National University Hospital Center, Cotonou, Gabon.
Department of Neurology, University Hospital of Parakou, Parakou, Benin.
Department of Neurology, University Hospital of Libreville, Libreville, Gabon.

*Corresponding author: Jennifer Nyangui Mapaga, Department of Neurology, Hubert Koutoukou MAGA National University Hospital Center, Cotonou, Benin. jenica45@yahoo.fr

Licence
This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-Share Alike 4.0 License, which allows others to remix, transform, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.

How to cite this article: Nyangui Mapaga J, Agbetou M, Gnigone P, Sowanou A, Mambila Matsalou G, Kouna Ndouongo P, et al. Prevalence of restless legs syndrome and associated factors in rural West African country. J Neurosci Rural Pract. doi: 10.25259/JNRP_357_2024

Abstract

Objectives:

This study aimed to assess the prevalence of restless legs syndrome (RLS) within the rural population of Adjohoun.

Materials and Methods:

A cross-sectional analytical study was conducted, with data collected from March 25 to April 10, 2019. RLS was diagnosed when participants met the four diagnostic criteria defined by the International RLS Study Group. Data analysis was performed using R software version 3.5.1. Factors associated with RLS were assessed through logistic regression, with statistical significance set at P < 0.05.

Results:

A total of 1655 subjects were interviewed. The prevalence of RLS was 0.97%, with a 95% confidence interval (CI) from 0.50 to 1.44. Abdominal obesity was identified as an associated factor, with an odds ratio of 2.9 and a 95% CI of 1.1–8.1.

Conclusion:

RLS is uncommon in the rural population of Benin, consistent with findings from other studies conducted across Africa. Further research may enhance our understanding of this condition within the people of African descent.

Keywords

Adjohoun
African population
Prevalence
Restless legs syndrome
Rural area

INTRODUCTION

Restless legs syndrome (RLS) is characterized by uncomfortable sensations in the legs, particularly during sleep or rest, causing an urge to move the legs.[1] In subSaharan Africa, RLS is often under-recognized and underestimated by non-neurologists. This chronic sensory-motor disorder was first described by Ekbom and Ulfberg.[1] The prevalence of RLS ranges from 0.013% to 23% with most studies conducted on Caucasian populations, showing higher rates in North America and Western Europe.[2-4] In Africa, few studies have investigated the prevalence of RLS in rural areas or even in hospital settings.[3,5]

The pathophysiology of primary RLS remains unclear. Three main contributing factors have been proposed although they are not independent[6] dysfunction of the nigrostriatal dopaminergic system, iron and ferritin, and genetic predisposition.[7] Women are affected twice as often as men. Risk factors for RLS include female gender, pregnancy, lower socioeconomic status, poor health, low iron levels, advanced age, comorbidities such as Parkinson’s disease or psychiatric disorders, and family history of similar conditions.[6,7] Given the impact of RLS on quality of life and its potential cardiovascular risk, studying the conduct, prevalence, and associated factors of RLS in rural areas of Benin is warranted.

MATERIALS AND METHODS

Study design

This study was cross-sectional and prospective with both descriptive and analytical aims and objectives.

Setting

The study was conducted in Adjohoun, a rural area in Benin with a population of 50,000 residents aged over 18. Data collection occurred from March 25 to April 10, 2019, using a two-stage sampling technique. A representative sample was randomly selected from a list of the 8 arrondissements in the Adjohoun commune, with four arrondissements chosen: Akpadanou, Adjohoun, Azowlissè, and Togbota. Lots were drawn to randomly select half the villages in each arrondissement. Within each selected village, participants were identified through door-to-door surveys. Interviewers positioned themselves in the center of each village and randomly determined a direction to begin (by tossing a pen in the air, with the tip indicating the starting direction). They interviewed all households in this direction until the required number was reached. If the target was not met, they returned to the center and repeated the process in a new direction until the goal was achieved. A standardized questionnaire was developed for the study, and incorporated into a digital data collection tool called Kobo Collect. This questionnaire comprises two sections: Sociodemographic information and data for diagnosing RLS. Before the survey, interviewers received 3 days of training on both the questionnaire and the Kobo Collect software. All interviewers were healthcare professionals, including a neurologist and neurology interns or students. The survey was conducted over 15 days, with groups of 1–4 interviewers assigned to various study sites based on each village’s population size. Arrondissements were numbered from 1 to 4, villages from 01 to 05, and individuals aged 18 and over were assigned numbers starting from 001. These individuals were interviewed in their homes, often in the presence of their families, for a minimum of 15 min. RLS cases were confirmed by a neurologist according to the diagnostic criteria set by the International RLS Study Group (IRLSSG).

Participants

We included subjects aged 18 and over, who had lived in Adjohoun for at least 6 months, were present at home during the survey, and had provided informed verbal consent.

Variables

Data were collected through a structured individual interview. For each, participant, we gathered sociodemographic information (age, sex, occupation, marital status, education level, religion), medical history (high blood pressure (HBP), diabetes, alcohol abuse, tobacco use, chronic kidney failure, peripheral neuropathy, neuropathic pain using the DN4 score, hepatitis C, iron deficiency), physical measurements (blood pressure, weight, height, waist circumference), and biological data (glycemia, human immunodeficiency virus [HIV] Rapid Diagnostic Test ). Participants were verbally informed about the HIV test procedure. The RLS questionnaire was translated to ensure data clarity and consistency. The dependent variable was RLS, characterized by a binary yes/no. RLS diagnosis was confirmed if participants met the four criteria established by the IRLSSG.[8]

Bias

Information bias

In a largely illiterate setting, age was self-reported; to reduce inaccuracies, birth certificates or identity cards were requested when available.

Selection bias

Although some individuals refused to participate, the sample size chosen for our study minimized the impact of non-respondents.

Confounding bias

This was minimized through univariate and multivariate analysis, allowing us to identify factors directly associated with RLS.

Study size

The sample size was calculated using the Schwartz formula based on a previous study in France by Tison et al. in 2005,[8] with an estimated prevalence of 8.5% and a desired precision of 1.5%, and the minimum required sample size was calculated to be of 1294 participants.

Statistical methods

Data analysis was performed using R 3.5.1 software. Descriptive statistics were produced for the study variables. Quantitative variables were presented as mean with standard deviation for normally distributed data (assessed by Shapiro’s test) and as median with interquartile range for non-normal distribution. Qualitative variables were expressed as percentages. The analysis of factors associated with RLS included both univariate and multivariate approaches. In the univariate analysis, prevalence was compared across independent variables using Pearson’s uncorrected Chi-square test (for expected counts >5) and Fisher’s exact test (for expected counts <5). For the multivariate analysis, a stepwise logistic regression model was used to identify variables independently associated with RLS. The initial model included variables associated with RLS at a threshold of 5% or 20% in the univariate analysis. Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to quantify the strength of associations, with significance set at P < 0.05.

Ethics

The administrative authorities of the Adjohoun commune were informed about the study and its significance. Each participant, along with any immediate family members present during household visits, was provided with an explanation of the study. Free and informed consent was obtained from all participants, and anonymity and confidentiality were assured.

RESULTS

Although the survey was initially planned for 1294 participants, 1655 individuals were ultimately enrolled and completed the IRLSSG questionnaire. The mean age was 41.44 ± 16.71 years, with ages ranging from 18 to 93 years. The sex ratio was 0.5, with uneducated individuals comprising 53.5% of the sample. The most common occupations were craftsmen (38.7%), retailers (23.1%), and farmers (21.4%). Among participants, 18 were diabetic and 101 reported neuropathic pain. The mean body mass index (BMI) was 23.7 ± 4.8 ranging from 13.0 to 49.8 and abdominal circumferences ranged from 56 to 151 cm, with an average of 82.1 ± 10.9 cm. HBP was diagnosed in 728 participants (44%; 95% CI: 41.6–46.4%) and Table 1 provides a summary of participants characteristics. HIV rapid diagnostic tests and glycemia measurements were performed on 1339 (80.9%) and 1088 (65.7%) of participants, respectively. The frequency of HIV was 1.2% (16 participants), and 6.1% (66 participants) had hyperglycemia (>1.26 g/L).

Table 1: Characteristics of the study population, Adjohoun, Benin 2019.
Number (n) Frequency (%)
Age in years
  <50 1,111 67.1
  ≥50 544 32.9
Sex
  Male 582 35.2
  Female 1,073 64.8
Instruction level
  Schooled 770 46.5
  No schooled 885 53.5
Marital status
  Single 414 25.0
  In couple 1,241 75.0
Profession
  Craftsman/manufacturers 640 38.7
  Retailers 382 23.1
  Farmers 354 21.4
  Employees 93 5.5
  Students 77 4.7
  Housewives 65 3.9
  Retired persons 44 2.7
Antecedent
  High blood pressure 355 21,5
  alcohol 273 16,5
  Peripheral neuropathy 114 6,9
  Neuropathic pain 101 6,1
  Diabetes 18 1,1
Body mass index
  Obesity 170 10.3
  Overweight 346 20.9
  Normal 971 58.7
  Emaciation 168 10.2
Waist obesity
  Yes 602 36.4
  No 1,053 63.6
High blood pressure*
  Yes 728 44.0
  No 927 56.0

n: Number of subjects, *High blood pressure at the time of survey or antihypertensive treatment before survey

The prevalence of RLS was 0.97% (95% CI: 0.50–1.44%) with 16 cases out of 1655 participants, including 7 moderate cases, 5 severe cases, 3 mild cases, and 1 very severe case. Of those with RLS, 56.25% were under the age of 50. There were 9 men and 7 women with RLS, resulting in a sex ratio of 1.29. Among RLS cases, 56.25% had a BMI ≥25, and 62.5% had abdominal obesity.

In the bivariate analysis, RLS was significantly associated with abdominal obesity (OR = 2.9, 95% CI: 1.1–8.2, P = 0.029) and obesity (BMI ≥25) (OR = 2.9, 95% CI 1.1–7.8, P = 0.030), as shown in Table 2. In the multivariate analysis, after adjusting for other characteristics, abdominal obesity remained significantly associated with RLS (ORa = 2.9, 95% CI 1.1– 8.1). Table 3 provides a summary of the multivariate analysis.

Table 2: Prevalence of RLS according to general characteristics; Adjohoun, Benin 2019.
Total (n) RLS OR CI 95% P-value
Yes % No
Age (years) 0.352
  <50 1,111 9 (0.8) 1,102 1
  ≥50 544 7 (1.3) 537 1.6 0.6–4.3
Sex 0.352
  Male 582 5 (0.9) 577 1
  Female 1,073 11 (1.0) 1,062 1.2 0.4–3.4
Instruction 0.467
  Schooled 770 6 (0.8) 764 1
  No schooled 885 10 (1.1) 875
Marital status 0.999
  Single 414 4 (1.0) 410 1
  In couple 1,241 12 (1.0) 1,229 1.6 0.5–4.0
Profession 0.769
  Craftsman/manufacturers 640 7 (1.1) 633 1
  Retailers 382 4 (1.0) 378 0.9 0.3–3.3 0.944
  Farmers 354 4 (1.1) 350 1.0 0.3–3.6 0.958
  Employees 93 0 (0.0) 93 - - 0.311
  Students 77 0 (0.0) 77 - - 0.356
  Housewives 65 0 (0.0) 65 - - 0.397
  Retired persons 44 1 (2.3) 43 2.1 0.3–17.5 0.482
High blood pressure 0.127
  Yes 355 6 (1.7) 349 2.2 0.8–6.1
  No 1300 10 (0.8) 1,290 1 -
Diabetes 0.161
  Yes 18 1 (5.6) 17 6.4 0.8–50.9
  No 1637 15 (0.9) 1,622 1 -
Peripheral neuropathy 1.000
  Yes 114 1 (0.9) 113 0.9 0.1–6.9
  No 1541 15 (1.0) 1,526 1 -
Neuropathic pain 0.618
  Yes 101 1 (1.0) 100 1 1.0-1.1
  No 1554 15 (1.0) 1,539 1 -
Alcoholism 0.495
  Yes 273 1 (0.4) 272 0.3 0.1–2.5
  No 1382 15 (1.1) 1,367 1 -
BMI (kg/m2) 0.030
  ≥25 516 9 (1.7) 507 2.9 (1.1–7.8)
  <25 1139 7 (0.6) 1,132 1 -
Waist obesity 0.029
  Yes 602 10 (1.7) 592 2.9 (1.1–8.2)
  No 1053 6 (0.6) 1,047 1 -
HBP 0.626
  Yes 728 8 (1.1) 720 1.3 (0.5–3.4)
  No 927 8 (0.9) 919 1 -
HIV 1.000
  Yes 16 0 (0.0) 16 - -
  No 1323 16 (1.2) 1,307
Glycemia (g/L) 1.000
  >1.26 66 0 (0.0) 66 - -
  ≤1.26 1,022 16 (1.6) 1,006 - -

RLS: Restless legs syndrome, CI: Confidence interval, OR: Odds ratio, BMI: Body mass index, HIV: Human immunodeficiency virus, HBP: High blood pressure

Table 3: Associated factors to RLS in multivariate analysis in Adjohoun, Bénin 2019.
OR adjusted CI 95% P-value
Age (≥50/<50 years) 1.2 0.4–3.5 0.716
Sex (female/male) 0.7 0.2–2.4 0.575
High blood pressure (yes/no) 1.6 0.6–4.6 0.379
Diabetes (yes/no) 5.6 0.7–45.3 0.108
BMI (≥25/< 25 kg/m2) 1.9 0.6–6.3 0.289
Waist obesity (yes/no) 2.9 1.1–8.1 0.037

RLS: Restless legs syndrome, BMI: Body mass index, CI: Confidence interval, OR: Odds ratio

DISCUSSION

The prevalence of RLS in our study was 0.97%, based on the IRLSSG criteria. Ekbom and Ulfberg estimated prevalence rates between 1 and 5%.[1,4] Since 1995, several epidemiological studies using the IRSSLG criteria have reported higher prevalence rates of 5–15% in population studies and predominantly conducted in Caucasian populations, with noted variations across geographic regions.[4]

In Africa, few studies have examined RLS prevalence. The first published study by Winkler et al., in a rural population in northern Tanzania, included 7654 individuals and found a low prevalence of 0.013%.[3] More recently, a study in Tanzania’s urban area (Dar es Salaam, Kinondoni) involving a sample of 35,008 participants reported a prevalence of 0.037%,[5] using the IRLSSG criteria with an adaptation of the first question.

In Europe, RLS prevalence ranges from 3.19% to 25%.[8-14] In the United States, several population studies using a single-question telephone survey found a prevalence of approximately 9.4%.[15] Asian populations show a lower prevalence, from 0.1% to −0.6%.[16-21] However, prevalence rates in South Korea vary significantly due to methodological differences. In 2008, it was based on IRLSSG criteria, compared to 0.9% in 2009 using diagnostic and statistical manual of mental disorders, 4th ed. criteria.[21,22] A study by Kim et al. in 2005, which used a single question (“Have you ever felt the need to move your legs or an unpleasant feeling like scary sensations in your legs before sleeping?”) reported a high prevalence using,[23] but this method may overestimate RLS as it does not rule out other conditions.

Overall, RLS has a low prevalence in African countries, India, and several Asian countries, with higher rates observed in Northern Europe.[24] The north-south gradient in prevalence may be due to genetic and methodological factors as well as environmental influences such as climate and ecology.

Several studies, including ours, have found a higher RLS prevalence in females and individuals over 50 years old. Tison et al. reported RLS in 10.8% of women and 5.8% of men, with prevalence increasing until 64 years before declining in both sexes.[8] Allen et al. and Berger et al. also observed that RLS is twice as frequent in women, with a peak in prevalence up to age 79 before decreasing.[25,26] This female predominance is likely linked to estrogen, with an increase in RLS during the third trimester of pregnancy, coinciding with an estrogen peak. Iron deficiency, which plays a well-known role in RLS pathogenesis and is common during pregnancy and menstruation, may also contribute.[27,28] In addition, literature reviews show that, in addition to elderly subjects, RLS can affect children and adolescents though many studies, including ours, have not included these age groups.[28]

RLS may also complicate diabetes mellitus,[29,30] affecting 18% of diabetics, compared to 5.5% of non-diabetics.[29] The risk of RLS was 1.79 times higher in diabetics,[30] with a significative association between the syndrome and the diabète. Cho et al. found that diabetic individuals have a fourfold higher risk, which may be partly due to diabetic neuropathy.[31] Some researchers suggest a link between RLS and cardiovascular disease, citing sleep disruption, sympathetic hyperactivity in RLS, and underlying periodic limb movements, all of which can contribute to HBP. The majority of RLS patients report 200–300 periodic limb movements per night.[32] However, Elwood and Winter found this cardiovascular risk low.[33,34] Gao et al. observed that the RLS prevalence increases with BMI and waist circumference,[35] with an adjusted OR of 2.9 in our study. A separate cross-sectional study on 1803 individuals aged 18 and older found that each 5 kg/m2 increase in BMI raised the likelihood of RLS by 31%.[15] Obesity may contribute to RLS by reducing dopaminergic receptor sensitivity and the development of type 2 diabetes.[36] In addition, both obesity and RLS share metabolic risk factors, and obese patients often suffer from vascular damage, further increasing RLS risk.[34] HIV was not associated with RLS in this study. The relationship between HIV-associated neurodegeneration in central nervous system (CNS) sensorimotor modulation areas and RLS symptoms remains unclear, though longer HIV duration may lead to chronic CNS inflammation, iron deficiency in the CNS, and loss of myelin integrity.[37]

A primary limitation of our study is that age was self-reported by illiterate participants, which could. introduce bias. As one of the first studies of its kind in Benin and West Africa, this study employed rigorous methodology based on validated criteria and random sampling.

Data availability statement

All data generated or analyzed during this study are included in this published article and its online supplementary material. Further information can be specified to the corresponding author.

CONCLUSION

RLS remains a rare neurological condition in rural areas of Benin, with abdominal obesity as the main associated factor. RLS should be considered in individuals presenting symptoms, as understanding and managing RLS could play a role in addressing cardiovascular health.

Authors’ contributions

JNM and DDG: Designed the project. TAA and PMG: Extracted the data and performed the analysis. JNM, MA, AS: Wrote the manuscript. GAMM, PKN, TAA: Revised the content. All authors refined the manuscript and revised it critically to improve valuable intellectual content. All authors approved the final manuscript.

Ethical approval

The ethical approval has been regularized under number: 0350/CLERB-UP/P/SP/R/SA by the Local Ethics Committee for Biomedical Research of the University of Parakou, dated February 27, 2019.

Declaration of patient consent

The authors certify that they have obtained all appropriate patient consent.

Conflicts of interest

There are no conflicts of interest.

Use of artificial intelligence (AI)-assisted technology for manuscript preparation

The authors confirm that there was no use of artificial intelligence (AI)-assisted technology for assisting in the writing or editing of the manuscript and no images were manipulated using AI.

Financial support and sponsorship: Nil.

References

  1. , . Restless legs syndrome. J Intern Med. 2009;266:419-31.
    [CrossRef] [PubMed] [Google Scholar]
  2. , , . Epidemiology of restless legs syndrome: A synthesis of the literature. Sleep Med Rev. 2012;16:283-95.
    [CrossRef] [PubMed] [Google Scholar]
  3. , , , , , . Restless legs syndrome in a population of Northern Tanzania: A community-based study. Mov Disord. 2010;25:596-601.
    [CrossRef] [PubMed] [Google Scholar]
  4. , . Epidemiology and clinical findings of restless legs syndrome. Sleep Med. 2004;5:293-9.
    [CrossRef] [PubMed] [Google Scholar]
  5. , , , , , , et al. Prevalence of restless legs syndrome in an urban population of eastern Africa (Tanzania) J Neurol Sci. 2014;346:121-7.
    [CrossRef] [PubMed] [Google Scholar]
  6. , , , , . Restless legs syndrome: An overview of pathophysiology, comorbidities and therapeutic approaches (review) Exp Ther Med. 2022;23:185.
    [CrossRef] [PubMed] [Google Scholar]
  7. , , , , , , et al. Prevalence of restless legs syndrome and associated factors in an otherwise healthy population: Results from the Danish blood donor study. Sleep Med. 2017;36:55-61.
    [CrossRef] [PubMed] [Google Scholar]
  8. , , , , , . Epidemiology of restless legs syndrome in French adults: A nationwide survey: The INSTANT study. Neurology. 2005;65:239-46.
    [CrossRef] [PubMed] [Google Scholar]
  9. , , , . Treatment wish of individuals with known and unknown restless legs syndrome in the community. J Neurol. 2008;255:1365-71.
    [CrossRef] [PubMed] [Google Scholar]
  10. , , , , . Prevalence and risk factors of RLS in an elderly population: The MEMO study. Memory and morbidity in Augsburg elderly. Neurology. 2000;54:1064-8.
    [CrossRef] [PubMed] [Google Scholar]
  11. , , , , , , et al. Unexpectedly low prevalence and unusual characteristics of RLS in Mersin, Turkey. Neurology. 2003;61:1562-9.
    [CrossRef] [PubMed] [Google Scholar]
  12. , , , , , . Correlation of anxiety and depression symptoms in patients with restless legs syndrome: A population based survey. J Neurol Neurosurg Psychiatry. 2004;75:226-30.
    [Google Scholar]
  13. , , , . Prevalence and correlates of restless legs syndrome in adolescents. Dev Med Child Neurol. 2011;53:40-7.
    [CrossRef] [PubMed] [Google Scholar]
  14. , , , , , , et al. Prevalence and clinical correlates of restless legs syndrome in an elderly French population: The synapse study. J Gerontol A Biol Sci Med Sci. 2010;65:167-73.
    [CrossRef] [PubMed] [Google Scholar]
  15. , , , , , . Epidemiology of restless legs symptoms in adults. Arch Intern Med. 2000;160:2137-41.
    [CrossRef] [PubMed] [Google Scholar]
  16. , , , , , . Restless legs syndrome in an Asian population: A study in Singapore. Mov Disord. 2001;16:577-9.
    [CrossRef] [PubMed] [Google Scholar]
  17. , , , . Prevalence of restless legs syndrome in non-institutionalized Japanese elderly. Psychiatry Clin Neurosci. 2005;59:461-5.
    [CrossRef] [PubMed] [Google Scholar]
  18. , , , , . Prevalence of restless legs syndrome in a rural community in Japan. Mov Disord. 2008;23:2363-9.
    [CrossRef] [PubMed] [Google Scholar]
  19. , , , , , . Prevalence and risk factors of restless legs syndrome among Chinese adults in a rural community of Shanghai in China. PLoS One. 2015;10:e0121215.
    [CrossRef] [PubMed] [Google Scholar]
  20. , , , , , , et al. The prevalence of restless legs syndrome in Taiwanese adults. Psychiatry Clin Neurosci. 2010;64:170-8.
    [CrossRef] [PubMed] [Google Scholar]
  21. , , , , , , et al. Epidemiology of restless legs syndrome in Korean adults. Sleep. 2008;31:219-23.
    [CrossRef] [PubMed] [Google Scholar]
  22. , , , , , , et al. Restless legs syndrome in a community sample of Korean adults: Prevalence, impact on quality of life, and association with DSM-IV psychiatric disorders. Sleep. 2009;32:1069-76.
    [Google Scholar]
  23. , , , , , , et al. Prevalence of restless legs syndrome and associated factors in the Korean adult population: The Korean health and genome study. Psychiatry Clin Neurosci. 2005;59:350-3.
    [CrossRef] [PubMed] [Google Scholar]
  24. , , . Restless legs syndrome in an Indian Urban population. Sleep Med. 2007;9:88-93.
    [CrossRef] [PubMed] [Google Scholar]
  25. , , , , , , et al. Restless legs syndrome prevalence and impact: REST general population study. Arch Intern Med. 2005;165:1286-92.
    [CrossRef] [PubMed] [Google Scholar]
  26. , , , , . Sex and the risk of restless legs syndrome in the general population. Arch Intern Med. 2004;164:196-202.
    [CrossRef] [PubMed] [Google Scholar]
  27. , , . Restless legs syndrome: A comprehensive overview on its epidemiology, risk factors, and treatment. Sleep Breath. 2012;16:987-1007.
    [CrossRef] [PubMed] [Google Scholar]
  28. , , , . Elevated estradiol plasma levels in women with restless legs during pregnancy. Sleep. 2009;32:169-74.
    [CrossRef] [PubMed] [Google Scholar]
  29. , , , . Restless legs syndrome in patients with hypertension and diabetes mellitus. Med Arch. 2016;70:116-8.
    [CrossRef] [PubMed] [Google Scholar]
  30. , , , , . The relationship between frequency of restless legs syndrome and type 2 diabetes. Iran J Diabetes Obes. 2017;9:40-4.
    [Google Scholar]
  31. , , , , , , et al. Prevalence and clinical characteristics of restless legs syndrome in diabetic peripheral neuropathy: Comparison with chronic osteoarthritis. Sleep Med. 2013;14:1387-92.
    [CrossRef] [PubMed] [Google Scholar]
  32. , , , , , . Prospective study of restless legs syndrome and coronary heart disease among women. Circulation. 2012;126:1689-94.
    [CrossRef] [PubMed] [Google Scholar]
  33. , , , , . Sleep disturbance, stroke, and heart disease events: Evidence from the Caerphilly cohort. J Epidemiol Community Health. 2006;60:69-73.
    [CrossRef] [PubMed] [Google Scholar]
  34. , , , , , , et al. Restless legs syndrome and risk of incident cardiovascular disease in women and men: Prospective cohort study. BMJ Open. 2012;2:e000866.
    [CrossRef] [PubMed] [Google Scholar]
  35. , , , . Obesity and restless legs syndrome in men and women. Neurology. 2009;72:1255-61.
    [CrossRef] [PubMed] [Google Scholar]
  36. , , , , , , et al. Brain dopamine and obesity. Lancet. 2001;357(9253):354-7.
    [CrossRef] [PubMed] [Google Scholar]
  37. , , , , , , et al. HIV-associated neurocognitive disorder--pathogenesis and prospects for treatment. Nat Rev Neurol. 2016;12:234-48.
    [CrossRef] [PubMed] [Google Scholar]
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