Aims

Currently, there is no data available assessing the association between body mass index (BMI) and periodontitis among women living with HIV (WLWH). This study aims to investigate this association among WLWH and women at risk for HIV (WRH) in the United States.

Methods and results

Data from 351 WLWH and 52 WRH participants from the Women's Interagency HIV Study having pocket depths and clinical periodontal attachment loss assessments in 2003-2004 were included. Multinomial logistic regression analyses in the full sample assessed the relationship between BMI (underweight/normal, overweight, or obese) and periodontitis by severity (mild, moderate, severe), adjusting for study sites, age, education, annual household income, smoking, alcohol consumption, and diabetes. Overall, 75.2% women (76.0% WLWH; 69.0% WRH) had periodontitis. Moreover, 75.0% obese and 75.3% overweight women were affected by periodontitis. In the full sample, adjusted odds ratio (aOR) of having mild, moderate, and severe periodontitis in obese women were: 1.14 (95% confidence interval [CI]: 0.51-2.52), 1.02 (95% CI: 0.46-2.29), and 0.24 (95% CI: 0.06-1.07), respectively, and in overweight women: 0.70 (95% CI: 0.31-1.58), 0.85 (95% CI: 0.38-1.90), and 0.31 (95% CI: 0.08-1.15), respectively.

Conclusions

Even with high prevalence of periodontitis among women with or without HIV infection in this cohort, this study does not provide evidence of an association between BMI and periodontitis.

Background

Data on the prevalence and correlates of restless legs syndrome (RLS) in people with HIV are limited. This study sought to determine the prevalence of RLS, associated clinical correlates, and characterize sleep-related differences in men with and without HIV.

Methods

Sleep-related data were collected in men who have sex with men participating in the Multicenter AIDS Cohort Study (MACS). Demographic, health behaviors, HIV status, comorbidities, and serological data were obtained from the MACS visit coinciding with sleep assessments. Participants completed questionnaires, home polysomnography, and wrist actigraphy. RLS status was determined with the Cambridge-Hopkins RLS questionnaire. RLS prevalence was compared in men with and without HIV. Multinomial logistic regression was used to examine correlates of RLS among all participants and men with HIV alone. Sleep-related differences were examined in men with and without HIV by RLS status.

Results

The sample consisted of 942 men (56% HIV+; mean age 57 years; 69% white). The prevalence of definite RLS was comparable in men with and without HIV (9.1% vs 8.7%). In multinomial regression, HIV status was not associated with RLS prevalence. However, white race, anemia, depression, and antidepressant use were each independently associated with RLS. HIV disease duration was also associated with RLS. Men with HIV and RLS reported poorer sleep quality, greater sleepiness, and had worse objective sleep efficiency/fragmentation than men without HIV/RLS.

Conclusions

The prevalence of RLS in men with and without HIV was similar. Screening for RLS may be considered among people with HIV with insomnia and with long-standing disease.