Sex-Specific Prediction Models for Sleep Apnea from the Hispanic Community Health Study/Study of Latinos This article has been presented in abstract form (Shah NA, Hanna DB, Teng Y, et al. Epidemiol Genet Sleep Disordered Breathing. 2014: A5334).

Neomi Shah, David B. Hanna, Yanping Teng, Daniela Sotres-Alvarez, Martica Hall, Jose S. Loredo, Phyllis Zee, Mimi Kim, H. Klar Yaggi, Susan Redline, Robert C. Kaplan

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Objective We developed and validated the first-ever sleep apnea (SA) risk calculator in a large population-based cohort of Hispanic/Latino subjects. Methods Cross-sectional data on adults from the Hispanic Community Health Study/Study of Latinos (2008-2011) were analyzed. Subjective and objective sleep measurements were obtained. Clinically significant SA was defined as an apnea-hypopnea index ≥ 15 events per hour. Using logistic regression, four prediction models were created: three sex-specific models (female-only, male-only, and a sex × covariate interaction model to allow differential predictor effects), and one overall model with sex included as a main effect only. Models underwent 10-fold cross-validation and were assessed by using the C statistic. SA and its predictive variables; a total of 17 variables were considered. Results A total of 12,158 participants had complete sleep data available; 7,363 (61%) were women. The population-weighted prevalence of SA (apnea-hypopnea index ≥ 15 events per hour) was 6.1% in female subjects and 13.5% in male subjects. Male-only (C statistic, 0.808) and female-only (C statistic, 0.836) prediction models had the same predictor variables (ie, age, BMI, self-reported snoring). The sex-interaction model (C statistic, 0.836) contained sex, age, age × sex, BMI, BMI × sex, and self-reported snoring. The final overall model (C statistic, 0.832) contained age, BMI, snoring, and sex. We developed two websites for our SA risk calculator: one in English (https://www.montefiore.org/sleepapneariskcalc.HTML) and another in Spanish (http://www.montefiore.org/sleepapneariskcalc-es.HTML). Conclusions We created an internally validated, highly discriminating, well-calibrated, and parsimonious prediction model for SA. Contrary to the study hypothesis, the variables did not have different predictive magnitudes in male and female subjects.

Original languageEnglish (US)
Pages (from-to)1409-1418
Number of pages10
JournalChest
Volume149
Issue number6
DOIs
StatePublished - Jun 1 2016

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Viverridae
Sleep Apnea Syndromes
Hispanic Americans
Health
Snoring
Apnea
Sleep
Population
Logistic Models

Keywords

  • clinical decision-making
  • community health
  • epidemiology (pulmonary)
  • sex-specific prediction
  • sleep apnea

ASJC Scopus subject areas

  • Pulmonary and Respiratory Medicine
  • Critical Care and Intensive Care Medicine
  • Cardiology and Cardiovascular Medicine

Cite this

Sex-Specific Prediction Models for Sleep Apnea from the Hispanic Community Health Study/Study of Latinos This article has been presented in abstract form (Shah NA, Hanna DB, Teng Y, et al. Epidemiol Genet Sleep Disordered Breathing. 2014 : A5334). / Shah, Neomi; Hanna, David B.; Teng, Yanping; Sotres-Alvarez, Daniela; Hall, Martica; Loredo, Jose S.; Zee, Phyllis; Kim, Mimi; Yaggi, H. Klar; Redline, Susan; Kaplan, Robert C.

In: Chest, Vol. 149, No. 6, 01.06.2016, p. 1409-1418.

Research output: Contribution to journalArticle

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title = "Sex-Specific Prediction Models for Sleep Apnea from the Hispanic Community Health Study/Study of Latinos This article has been presented in abstract form (Shah NA, Hanna DB, Teng Y, et al. Epidemiol Genet Sleep Disordered Breathing. 2014: A5334).",
abstract = "Objective We developed and validated the first-ever sleep apnea (SA) risk calculator in a large population-based cohort of Hispanic/Latino subjects. Methods Cross-sectional data on adults from the Hispanic Community Health Study/Study of Latinos (2008-2011) were analyzed. Subjective and objective sleep measurements were obtained. Clinically significant SA was defined as an apnea-hypopnea index ≥ 15 events per hour. Using logistic regression, four prediction models were created: three sex-specific models (female-only, male-only, and a sex × covariate interaction model to allow differential predictor effects), and one overall model with sex included as a main effect only. Models underwent 10-fold cross-validation and were assessed by using the C statistic. SA and its predictive variables; a total of 17 variables were considered. Results A total of 12,158 participants had complete sleep data available; 7,363 (61{\%}) were women. The population-weighted prevalence of SA (apnea-hypopnea index ≥ 15 events per hour) was 6.1{\%} in female subjects and 13.5{\%} in male subjects. Male-only (C statistic, 0.808) and female-only (C statistic, 0.836) prediction models had the same predictor variables (ie, age, BMI, self-reported snoring). The sex-interaction model (C statistic, 0.836) contained sex, age, age × sex, BMI, BMI × sex, and self-reported snoring. The final overall model (C statistic, 0.832) contained age, BMI, snoring, and sex. We developed two websites for our SA risk calculator: one in English (https://www.montefiore.org/sleepapneariskcalc.HTML) and another in Spanish (http://www.montefiore.org/sleepapneariskcalc-es.HTML). Conclusions We created an internally validated, highly discriminating, well-calibrated, and parsimonious prediction model for SA. Contrary to the study hypothesis, the variables did not have different predictive magnitudes in male and female subjects.",
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AU - Shah, Neomi

AU - Hanna, David B.

AU - Teng, Yanping

AU - Sotres-Alvarez, Daniela

AU - Hall, Martica

AU - Loredo, Jose S.

AU - Zee, Phyllis

AU - Kim, Mimi

AU - Yaggi, H. Klar

AU - Redline, Susan

AU - Kaplan, Robert C.

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N2 - Objective We developed and validated the first-ever sleep apnea (SA) risk calculator in a large population-based cohort of Hispanic/Latino subjects. Methods Cross-sectional data on adults from the Hispanic Community Health Study/Study of Latinos (2008-2011) were analyzed. Subjective and objective sleep measurements were obtained. Clinically significant SA was defined as an apnea-hypopnea index ≥ 15 events per hour. Using logistic regression, four prediction models were created: three sex-specific models (female-only, male-only, and a sex × covariate interaction model to allow differential predictor effects), and one overall model with sex included as a main effect only. Models underwent 10-fold cross-validation and were assessed by using the C statistic. SA and its predictive variables; a total of 17 variables were considered. Results A total of 12,158 participants had complete sleep data available; 7,363 (61%) were women. The population-weighted prevalence of SA (apnea-hypopnea index ≥ 15 events per hour) was 6.1% in female subjects and 13.5% in male subjects. Male-only (C statistic, 0.808) and female-only (C statistic, 0.836) prediction models had the same predictor variables (ie, age, BMI, self-reported snoring). The sex-interaction model (C statistic, 0.836) contained sex, age, age × sex, BMI, BMI × sex, and self-reported snoring. The final overall model (C statistic, 0.832) contained age, BMI, snoring, and sex. We developed two websites for our SA risk calculator: one in English (https://www.montefiore.org/sleepapneariskcalc.HTML) and another in Spanish (http://www.montefiore.org/sleepapneariskcalc-es.HTML). Conclusions We created an internally validated, highly discriminating, well-calibrated, and parsimonious prediction model for SA. Contrary to the study hypothesis, the variables did not have different predictive magnitudes in male and female subjects.

AB - Objective We developed and validated the first-ever sleep apnea (SA) risk calculator in a large population-based cohort of Hispanic/Latino subjects. Methods Cross-sectional data on adults from the Hispanic Community Health Study/Study of Latinos (2008-2011) were analyzed. Subjective and objective sleep measurements were obtained. Clinically significant SA was defined as an apnea-hypopnea index ≥ 15 events per hour. Using logistic regression, four prediction models were created: three sex-specific models (female-only, male-only, and a sex × covariate interaction model to allow differential predictor effects), and one overall model with sex included as a main effect only. Models underwent 10-fold cross-validation and were assessed by using the C statistic. SA and its predictive variables; a total of 17 variables were considered. Results A total of 12,158 participants had complete sleep data available; 7,363 (61%) were women. The population-weighted prevalence of SA (apnea-hypopnea index ≥ 15 events per hour) was 6.1% in female subjects and 13.5% in male subjects. Male-only (C statistic, 0.808) and female-only (C statistic, 0.836) prediction models had the same predictor variables (ie, age, BMI, self-reported snoring). The sex-interaction model (C statistic, 0.836) contained sex, age, age × sex, BMI, BMI × sex, and self-reported snoring. The final overall model (C statistic, 0.832) contained age, BMI, snoring, and sex. We developed two websites for our SA risk calculator: one in English (https://www.montefiore.org/sleepapneariskcalc.HTML) and another in Spanish (http://www.montefiore.org/sleepapneariskcalc-es.HTML). Conclusions We created an internally validated, highly discriminating, well-calibrated, and parsimonious prediction model for SA. Contrary to the study hypothesis, the variables did not have different predictive magnitudes in male and female subjects.

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