# Maximal Respiratory Muscle Strength in Singaporean Adults: Normative Reference Values and Predictive Models from a Cross-Sectional Study

## TL;DR

This study establishes reference values for respiratory muscle strength in Singaporean adults and identifies factors influencing these values.

## Contribution

The study provides updated normative reference values and predictive models for respiratory muscle strength in Singaporean adults.

## Key findings

- Males had significantly higher MIP and MEP values than females.
- Regression models explained 27.5% and 32.1% of the variance in MIP and MEP, respectively.
- Variables like age, gender, height, and weight were significant predictors of respiratory muscle strength.

## Abstract

Maximal inspiratory pressure (MIP) and maximal expiratory pressure (MEP) are commonly used proxies to measure respiratory muscle strength. Current literature lacks recent large-scale normative reference values (NRV) for these pressures in healthy Singaporean adults. Moreover, no consensus exists on the variables that could influence MIP and MEP. This cross-sectional study aims to: (1) establish the NRV of MIP and MEP; (2) determine the correlations of variables that could influence these pressures; and (3) develop regression equations using non-spirometry variables to estimate reference values for MIP and MEP in the healthy Singaporean population aged 21 to 80 years. MIP and MEP were measured alongside demographic and anthropometric data collected from 391 participants (202 females, 189 males) recruited via convenience sampling. Median MIP and MEP values were significantly higher in males (112 and 85 cmH2O) than in females (83 and 64 cmH2O). Spearman correlations revealed significant associations between MIP/MEP and gender, height, weight, body mass index (BMI), waist–hip ratio, and spirometric variables. Regression models using age, gender, height, and weight explained 27.5% and 32.1% of the variance in MIP and MEP, respectively. This study updated the NRV of MIP and MEP and provided practical predictive equations for assessing respiratory muscle strength in Singapore.