ABSTRACT
Background and Objectives: Acanthosis nigricans is characterized by hyperpigmentation and velvet-like thickening of the skin. It symmetrically involves the neck, axilla, groins, antecubital and popliteal fossae, umbilical, and perianal areas. Acanthosis nigricans is a marker for insulin resistance and is increasingly found to be associated with metabolic syndrome. We conducted this study to estimate the frequency of metabolic syndrome in acanthosis nigricans. Methods: In this hospital-based, cross-sectional study, we evaluated 60 patients with acanthosis nigricans with neck involvement. They were examined for other areas of involvement by acanthosis nigricans. Axillary and neck severity was graded based on the scale described by Burke et al. Insulin resistance was interpreted using homeostatic model assessment (HOMA-IR). Metabolic syndrome was diagnosed according to the SAM-NCEP criteria. Collected data were analyzed using IBM SPSS Statistics, Version 22 (Armonk, NY: IBM Corp). Results: Axilla was the most common site involved in 51 patients (85%) followed by knuckles (55%). Metabolic syndrome was found in 78.3% of our patients, and 56.66% had insulin resistance. A statistically significant association of severity grading of axillary acanthosis nigricans with both metabolic syndrome (P = 0.001) and insulin resistance (P = 0.03) was noted. However, no meaningful association was found between the severity grading of neck acanthosis nigricans with both metabolic syndrome (P = 0.4) and insulin resistance (P = 0.08). The association of neck texture grading of acanthosis nigricans with insulin resistance was statistically significant (P = 0.005). Conclusions: Metabolic syndrome was seen in 78.3% of acanthosis nigricans. Axillary severity grading was associated with metabolic syndrome.
ABSTRACT
OBJECTIVES: To estimate the occurrence of obstructive sleep apnea (OSA) and its risk factors in a rural Indian population using screening questionnaire and Level III sleep study. To determine the feasibility to train community health workers to administer Level III sleep study in the high-risk population. MATERIALS AND METHODS: The study was conducted from seven villages with adult population of 2247, in Mugalur, near Bengaluru, from January to April 2014. Berlin questionnaire was used to screen 321 participants chosen by stratified random sampling. A total of 26 out of 321 patients underwent Level III sleep study at home, administered by the health workers, who were trained in three sessions to hook up the machine. Data were verified by a certified sleep physician. RESULTS: The mean age was 39.43 ± 15.6 years with the M:F ratio of 0.98:1. Prevalence of risk of OSA by Berlin questionnaire was 8.72% (95% confidence interval [CI] 5.63, 11.81) in the total population, 7.4% in males and 11.7% in females. Older age (odds ratio [OR] 3.97; CI 1.63, 9.6), hypertension (OR 11; CI 4.3, 28.2), obesity (OR 2.35; CI 1, 5.5), and higher Mallampati score (OR 3.78; CI 1.7, 8.4) were significantly associated with high risk of OSA (P = 0.0001-0.04). Twenty-six patients underwent Level III sleep study and OSA was diagnosed in 12 patients. The mean apnea-hypopnea index (AHI) of this group was 9.7/h. The prevalence of OSA by AHI criteria was 3.74%. CONCLUSIONS: OSA is underdiagnosed in rural populations, although risk factors are present. Training community health workers to administer Level III sleep study is a feasible and cost-effective strategy.
