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Fulltext The use of quantile regression to forecast higher than expected respiratory deaths in a daily time series: a study of New York City data 1987-2000

Soyiri IN, Reidpath DD

PLoS One, 2013;8(10):e78215.
PMID: 24147122 DOI: 10.1371/journal.pone.0078215

Forecasting higher than expected numbers of health events provides potentially valuable insights in its own right, and may contribute to health services management and syndromic surveillance. This study investigates the use of quantile regression to predict higher than expected respiratory deaths. Data taken from 70,830 deaths occurring in New York were used. Temporal, weather and air quality measures were fitted using quantile regression at the 90th-percentile with half the data (in-sample). Four QR models were fitted: an unconditional model predicting the 90th-percentile of deaths (Model 1), a seasonal/temporal (Model 2), a seasonal, temporal plus lags of weather and air quality (Model 3), and a seasonal, temporal model with 7-day moving averages of weather and air quality. Models were cross-validated with the out of sample data. Performance was measured as proportionate reduction in weighted sum of absolute deviations by a conditional, over unconditional models; i.e., the coefficient of determination (R1). The coefficient of determination showed an improvement over the unconditional model between 0.16 and 0.19. The greatest improvement in predictive and forecasting accuracy of daily mortality was associated with the inclusion of seasonal and temporal predictors (Model 2). No gains were made in the predictive models with the addition of weather and air quality predictors (Models 3 and 4). However, forecasting models that included weather and air quality predictors performed slightly better than the seasonal and temporal model alone (i.e., Model 3 > Model 4 > Model 2) This study provided a new approach to predict higher than expected numbers of respiratory related-deaths. The approach, while promising, has limitations and should be treated at this stage as a proof of concept.

Matched MeSH terms: Respiratory Tract Diseases/mortality*
Prognostic value of grip strength: findings from the Prospective Urban Rural Epidemiology (PURE) study

Leong DP, Teo KK, Rangarajan S, Lopez-Jaramillo P, Avezum A, Orlandini A, et al.

Lancet, 2015 Jul 18;386(9990):266-73.
PMID: 25982160 DOI: 10.1016/S0140-6736(14)62000-6

Reduced muscular strength, as measured by grip strength, has been associated with an increased risk of all-cause and cardiovascular mortality. Grip strength is appealing as a simple, quick, and inexpensive means of stratifying an individual's risk of cardiovascular death. However, the prognostic value of grip strength with respect to the number and range of populations and confounders is unknown. The aim of this study was to assess the independent prognostic importance of grip strength measurement in socioculturally and economically diverse countries.

Matched MeSH terms: Respiratory Tract Diseases/mortality
Fulltext Mortality and cardiovascular and respiratory morbidity in individuals with impaired FEV1 (PURE): an international, community-based cohort study

Duong M, Islam S, Rangarajan S, Leong D, Kurmi O, Teo K, et al.

Lancet Glob Health, 2019 05;7(5):e613-e623.
PMID: 31000131 DOI: 10.1016/S2214-109X(19)30070-1

BACKGROUND: The associations between the extent of forced expiratory volume in 1 s (FEV1) impairment and mortality, incident cardiovascular disease, and respiratory hospitalisations are unclear, and how these associations might vary across populations is unknown.
METHODS: In this international, community-based cohort study, we prospectively enrolled adults aged 35-70 years who had no intention of moving residences for 4 years from rural and urban communities across 17 countries. A portable spirometer was used to assess FEV1. FEV1 values were standardised within countries for height, age, and sex, and expressed as a percentage of the country-specific predicted FEV1 value (FEV1%). FEV1% was categorised as no impairment (FEV1% ≥0 SD from country-specific mean), mild impairment (FEV1% <0 SD to -1 SD), moderate impairment (FEV1%

Matched MeSH terms: Respiratory Tract Diseases/mortality*
Fulltext FEV1 and total Cardiovascular mortality and morbidity over an 18 years follow-up Population-Based Prospective EPIC-NORFOLK Study

Ching SM, Chia YC, Lentjes MAH, Luben R, Wareham N, Khaw KT

BMC Public Health, 2019 May 03;19(1):501.
PMID: 31053065 DOI: 10.1186/s12889-019-6818-x

BACKGROUND: Our study aimed to determine the association between forced expiratory volume in one second (FEV1) and subsequent fatal and non-fatal events in a general population.
METHODS: The Norfolk (UK) based European Prospective Investigation into Cancer (EPIC-Norfolk) recruited 25,639 participants between 1993 and 1997. FEV1 measured by portable spirometry, was categorized into sex-specific quintiles. Mortality and morbidity from all causes, cardiovascular disease (CVD) and respiratory disease were collected from 1997 up to 2015. Cox proportional hazard regression analysis was used with adjustment for socio-economic factors, physical activity and co-morbidities.
RESULTS: Mean age of the population was 58.7 ± 9.3 years, mean FEV1 for men was 294± 74 cL/s and 214± 52 cL/s for women. The adjusted hazard ratios for all-cause mortality for participants in the highest fifth of the FEV1 category was 0.63 (0.52, 0.76) for men and 0.62 (0.51, 0.76) for women compared to the lowest quintile. Adjusted HRs for every 70 cL/s increase in FEV1 among men and women were 0.77 (p < 0.001) and 0.68 (p < 0.001) for total mortality, 0.85 (p<0.001) and 0.77 (p<0.001) for CVD and 0.52 (p <0.001) and 0.42 (p <0.001) for respiratory disease.
CONCLUSIONS: Participants with higher FEV1 levels had a lower risk of CVD and all-cause mortality. Measuring the FEV1 with a portable handheld spirometry measurement may be used as a surrogate marker for cardiovascular risk. Every effort should be made to identify those with poorer lung function even in the absence of cardiovascular disease as they are at greater risk of total and CV mortality.

Matched MeSH terms: Respiratory Tract Diseases/mortality*