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Armstrong, Ben

doi:10.1097/00001648-200307000-00016

Cited by 7 publications

(9 citation statements)

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“…In this study special attention has been paid to control for time varying confounding factors in that several time dependent covariates including daily averages of temperature, humidity, solar radiation, wind speed and air pollutant concentrations were controlled for so that residual confounding in daily mortality was minimized. The case-only logistic regression is specially designed for assessing interaction between personal and environmental factors on individual case-only data, and the estimation would not be affected by any modeling assumptions for adjustment of the time independent personal and environmental confounding covariates [43].…”

Section: Discussionmentioning

confidence: 99%

“…Then odds ratios for E 1 or E 2 against E 0 were computed and they were termed as the “crude odds ratios”, which were then further stratified to “group specific odds ratios” by gender, age group, smoking, drinking, job nature, educational attainment, population density of the decedent's living district, housing type, and the duration of illness before death to assess the association between frequency of exercise and death in influenza epidemics to different personal characteristics and risk factors. For the difference in excess risks (ER) of mortality associated with influenza epidemics between exercise groups (between E 1 and E 0 , or E 2 and E 0 ), multinomial logistic regression under the case-only approach [43], [48] was applied by using the variable that indicated the three exercise groups as the categorical dependent variable and the influenza epidemic indicator as the independent variable (X).where p = probability that one is having a particular exercise habit. The influenza effect which may be modified by an exercise habit is estimated by (exp( β )−1)×100%.…”

Section: Methodsmentioning

confidence: 99%

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Is Exercise Protective Against Influenza-Associated Mortality?

Wong

Lai

et al. 2008

PLoS ONE

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BackgroundLittle is known about the effect of physical exercise on influenza-associated mortality.Methods and FindingsWe collected information about exercise habits and other lifestyles, and socioeconomic and demographic status, the underlying cause of death of 24,656 adults (21% aged 30–64, 79% aged 65 or above) who died in 1998 in Hong Kong, and the weekly proportion of specimens positive for influenza A (H3N1 and H1N1) and B isolations during the same period. We assessed the excess risks (ER) of influenza-associated mortality due to all-natural causes, cardiovascular diseases, or respiratory disease among different levels of exercise: never/seldom (less than once per month), low/moderate (once per month to three times per week), and frequent (four times or more per week) by Poisson regression. We also assessed the differences in ER between exercise groups by case-only logistic regression. For all the mortality outcomes under study in relation to each 10% increase in weekly proportion of specimens positive for influenza A+B, never/seldom exercise (as reference) was associated with 5.8% to 8.5% excess risks (ER) of mortality (P<0.0001), while low/moderate exercise was associated with ER which were 4.2% to 6.4% lower than those of the reference (P<0.001 for all-natural causes; P = 0.001 for cardiovascular; and P = 0.07 for respiratory mortality). Frequent exercise was not different from the reference (change in ER −0.8% to 1.7%, P = 0.30 to 0.73).ConclusionWhen compared with never or seldom exercise, exercising at low to moderate frequency is beneficial with lower influenza-associated mortality.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Is Exercise Protective Against Influenza-Associated Mortality?

Wong

Lai

et al. 2008

PLoS ONE

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“…The case-only approach with logistic regression was originally proposed for studying the gene–environment interaction and has been widely used in this field of study (Fallin et al 2003; Fracanzani et al 2005). Armstrong (2003) has pointed out that this method can be extended for evaluating the interaction between time-varying variables and individual factors. Subsequently, Schwartz (2005) gave a more detailed description of this method and applied it to examine whether medical conditions modify the mortality effects of extreme temperature.…”

Section: Methodsmentioning

confidence: 99%

The Effects of Air Pollution on Mortality in Socially Deprived Urban Areas in Hong Kong, China

Wong

Chen

Chan

et al. 2008

Environ Health Perspect

123

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BackgroundPoverty is a major determinant of population health, but little is known about its role in modifying air pollution effects.ObjectivesWe set out to examine whether people residing in socially deprived communities are at higher mortality risk from ambient air pollution.MethodsThis study included 209 tertiary planning units (TPUs), the smallest units for town planning in the Special Administrative Region of Hong Kong, China. The socioeconomic status of each TPU was measured by a social deprivation index (SDI) derived from the proportions of the population with a) unemployment, b) monthly household income < US$250, c) no schooling at all, d) one-person household, e) never-married status, and f ) subtenancy, from the 2001 Population Census. TPUs were classified into three levels of SDI: low, middle, and high. We performed time-series analysis with Poisson regression to examine the association between changes in daily concentrations of ambient air pollution and daily number of deaths in each SDI group for the period from January 1996 to December 2002. We evaluated the differences in pollution effects between different SDI groups using a case-only approach with logistic regression.ResultsWe found significant associations of nitrogen dioxide, sulfur dioxide, particulate matter with aerodynamic diameter < 10 μm, and ozone with all nonaccidental and cardiovascular mortality in areas of middle or high SDI (p < 0.05). Health outcomes, measured as all nonaccidental, cardiovascular, and respiratory mortality, in people residing in high SDI areas were more strongly associated with SO2 and NO2 compared with those in middle or low SDI areas.ConclusionsNeighborhood socioeconomic deprivation increases mortality risks associated with air pollution.

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“…Several investigators (Armstrong 2003; Medina-Ramon and Schwartz 2008; Medina-Ramon et al 2006a; Schwartz 2005) pointed out that this approach was suitable to analyze how the effect of a time-varying exposure (e.g. PM 10 concentration) is modified by some individual characteristics that do not vary over time (e.g.…”

Section: Methodsmentioning

confidence: 99%

Cardiorespiratory treatments as modifiers of the relationship between particulate matter and health: A case-only analysis on hospitalized patients in Italy

Conti

Lafranconi

Zanobetti³

et al. 2015

Environmental Research

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Background A few panel and toxicological studies suggest that health effects of particulate matter (PM) might be modified by medication intake, but whether this modification is confirmed in the general population or for more serious outcomes is still unknown. Objectives We carried out a population-based pilot study in order to assess how pre-hospitalization medical treatments modify the relationship between PM < 10 µm in aerodynamic diameter (PM10) and the risk of cardiorespiratory admission. Methods We gathered information on hospitalizations for cardiorespiratory causes, together with pre-admission pharmacological treatments, that occurred during 2005 in seven cities located in Lombardy (Northern Italy). City-specific PM10 concentrations were measured at fixed monitoring stations. Each treatment of interest was analyzed separately through a case-only approach, using generalized additive models accounting for sex, age, comorbidities, temperature and simultaneous intake of other drugs. Analyses were stratified by season and, if useful, by age and sex. Results Our results showed a higher effect size for PM10 on respiratory admissions in subjects treated with theophylline (Odds Ratio (OR) of treatment for an increment of 10 µg/m3 in PM10 concentration: 1.119; 95% Confidence Interval (CI), 1.013 – 1.237), while for cardiovascular admissions treatment with cardiac therapy (OR: 0.967, 95% CI, 0.940 – 0.995) and lipid modifying agents (OR: 0.962, 95% CI, 0.931 – 0.995) emerged as a protective factor, especially during the warm season. Evidence of a protective effect against the pollutant was found for glucocorticoids and respiratory admissions. Conclusions Our study showed that the treatment with cardiac therapy and lipid modifying agents might mitigate the effect of PM10 on cardiovascular health, while the use of theophylline seems to enhance the effect of the pollutant, possibly due to confounding by indication. It is desirable to extend the analyses to a larger population.

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Abstract: The simplicity and reduced assumptions of the case-only approach provide an advantage over conventional analysis, although the approach gives information only on modification, not main effects.

Cited by 7 publications

References 0 publications

Is Exercise Protective Against Influenza-Associated Mortality?

Is Exercise Protective Against Influenza-Associated Mortality?

The Effects of Air Pollution on Mortality in Socially Deprived Urban Areas in Hong Kong, China

Cardiorespiratory treatments as modifiers of the relationship between particulate matter and health: A case-only analysis on hospitalized patients in Italy

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