Demographic Differences in Periodic Limb Movement Index and Apnea–Hypopnea Index in a Diverse Clinical Cohort

This study investigated how age, sex, and ethnicity relate to the severity of periodic limb movement index (PLMI) and obstructive sleep apnea (OSA) in a diverse clinical population. A retrospective analysis was conducted on 711 adults who underwent diagnostic polysomnography between June 2022 and July 2024. The mean age was 57.2 years; 55.6% were female, and the sample was ethnically diverse (53.7% White, 31.6% Hispanic, 6.8% Asian, 6.1% Black, 1.8% Other). PLMI was significantly higher in older adults, males, and White participants. AHI was higher in males and peaked in middle-aged adults (44-62 years). Multivariable regression models showed that male sex independently predicted higher PLMI and AHI, while increasing age was associated with higher PLMI only. Black ethnicity was linked to lower PLMI, and Hispanic ethnicity to higher AHI. These findings emphasize the role of demographic factors in the presentation of sleep disorders and support the need for personalized approaches in screening and diagnosis. Recognizing at-risk subgroups may improve early detection and targeted interventions for both PLMS and OSA in diverse populations.

Authors

Institutions

Publication Details

Journal
International Journal of Environmental Research and Public Health
Published
2025-09-24
DOI
https://doi.org/10.3390/ijerph22101476
Citations
1
Primary Topic
Obstructive Sleep Apnea Research
Type
article
Field-Weighted Citation Impact
1.16
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Demographic Differences in Periodic Limb Movement Index and Apnea–Hypopnea Index in a Diverse Clinical Cohort

Preetinder Sandhu, Lourdes M. DelRosso, Viraj Jain, Alec M. Chan‐Golston et al.
1 citations
International Journal of Environmental Research and Public Health
Obstructive Sleep Apnea Research
1.16
article

Demographic Differences in Periodic Limb Movement Index and Apnea–Hypopnea Index in a Diverse Clinical Cohort

Preetinder Sandhu, Lourdes M. DelRosso, Viraj Jain, Alec M. Chan‐Golston, Moon Park, Harshil Modi
article en
1 citations

Abstract

This study investigated how age, sex, and ethnicity relate to the severity of periodic limb movement index (PLMI) and obstructive sleep apnea (OSA) in a diverse clinical population. A retrospective analysis was conducted on 711 adults who underwent diagnostic polysomnography between June 2022 and July 2024. The mean age was 57.2 years; 55.6% were female, and the sample was ethnically diverse (53.7% White, 31.6% Hispanic, 6.8% Asian, 6.1% Black, 1.8% Other). PLMI was significantly higher in older adults, males, and White participants. AHI was higher in males and peaked in middle-aged adults (44-62 years). Multivariable regression models showed that male sex independently predicted higher PLMI and AHI, while increasing age was associated with higher PLMI only. Black ethnicity was linked to lower PLMI, and Hispanic ethnicity to higher AHI. These findings emphasize the role of demographic factors in the presentation of sleep disorders and support the need for personalized approaches in screening and diagnosis. Recognizing at-risk subgroups may improve early detection and targeted interventions for both PLMS and OSA in diverse populations.

International Journal of Environmental Research and Public HealthVol. 22(10)
University of California, Merced (US), University of California, San Francisco (US), Loyola Marymount University (US), California State University, Fresno (US)
Openalex Percentile: Top 18%
Obstructive Sleep Apnea Research
1.16
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.