Regional similarities in seasonal mortality across the United States: an examination of 28 metropolitan statistical areas

The Impact of Winter Months on Venous Thromboembolism (VTE) Patients: A Retrospective Analysis of Hospital Outcomes in the United States

Objective: We aimed to analyze the Health Care Utilization Project’s (HCUP) Nationwide Inpatient Sample (NIS) and compare mortality rates in hospitals by month to determine if there is seasonal variability in outcomes associated with venous thromboembolism (VTE).

Methods: The Nationwide Inpatient Sample database was queried from 1998 to 2011. Inclusion criteria were a diagnosis of deep vein thrombosis (DVT) (ICD-9 {International Classification of Diseases, Ninth Revision, Clinical Modification} 453.4, 453.8) and/or VTE (ICD-9 415.1) in patients aged 18 years or more. Admission data was then analyzed to compare mortality rates in teaching and non-teaching hospitals over that time and by month. Demographics, Charlson Comorbidity Index, length of stay (LOS), hospital region, and admission types (emergent/urgent versus elective admissions) were assessed. Linear and logistic models were generated for complex survey design to analyze predictors of mortality and LOS.

Results: A total of 1,449,113 DVT/VTE cases were identified in the Nationwide Inpatient Sample (weighted n= 7,150,613), 54.7% female, 56.38% white, 49% in teaching hospitals. Higher mortality was found in the months of November 6.52%, December 6.9%, January 6.94%, and February 6.93% versus overall mortality of 6.4% over 12 months. Higher mortality was noted in these winter months in all regions, along with a significantly increased LOS. Mortality in the total cohort was found to be higher in January, with odds ratio (OR) 1.11 (1.08-1.15), p<0.0001; February, OR 1.11 (1.07-1.15), p<0.0001; and December, OR 1.10 (1.06-1.14), p<0.0001 compared to June. Mortality was significantly lower in the Midwest or North Central regions (OR 0.78 {0.72-0.83}, p<0.0001) and West (OR 0.80 {0.73-0.87}, p<0.0001) compared to the Northeast. Mortality was also significantly higher in teaching hospitals than in non-teaching hospitals (OR 1.16 {1.10-1.22}, p<0.0001), with mortality trending higher in teaching hospitals each month. Emergent/urgent admission, larger hospital size, female sex, age, and urban location were also significantly associated with increased mortality.

Conclusions: This national study identified an increased risk of mortality associated with hospitalizations for DVT/VTE in the winter months, independent of hospital teaching status or region.

Effects of seasonal and climate variations on in-hospital mortality and length of stay in patients with type A aortic dissection

Objective

To investigate the effects of seasonal and climatic changes on postoperative in-hospital mortality and length of stay (LOS) in patients with type A acute aortic dissection (AAD).

Methods

Patients undergoing implantation of the modified triple-branched stent graft to replace the descending aorta in addition to aortic root reconstruction for type A AAD in our hospital from January 2016 to December 2019 were included. Relevant data were retrospectively collected and analyzed.

Results

A total of 404 patients were included in our analyses. The multivariate unconditional logistic regression analysis showed that patients admitted in autumn (OR 4.027, 95% CI 1.023–17.301, P = 0.039) or with coronary heart disease (OR 8.938, 95% CI 1.991–29.560, P = 0.049) were independently associated with an increased risk of postoperative in-hospital mortality. Furthermore, patients admitted in autumn (OR 5.956, 95% CI 2.719–7.921, P = 0.041) or with hypertension (OR 3.486, 95% CI 1.192–5.106, P = 0.035) were independently associated with an increased risk of longer LOS.

Conclusion

Patients admitted in autumn or with coronary heart disease are at higher risk of in-hospital mortality following surgery for type A AAD. Also, patients admitted in autumn or with hypertension have a longer hospital LOS. In the autumn of the temperature transition, we may need to strengthen the management of medical quality after surgery for type A AAD.

Monthly variance in UK renal transplantation activity: a national retrospective cohort study

OBJECTIVE

To identify whether renal transplant activity varies in a reproducible manner across the year.

DESIGN

Retrospective cohort study using NHS Blood and Transplant data.

SETTING

All renal transplant centres in the UK.

PARTICIPANTS

A total of 24 270 patients who underwent renal transplantation between 2005 and 2014.

PRIMARY OUTCOME

Monthly transplant activity was analysed to see if transplant activity showed variation during the year.

SECONDARY OUTCOME

The number of organs rejected due to healthcare capacity was analysed to see if this affected transplantation rates.

RESULTS

Analysis of national transplant data revealed a reproducible yearly variance in transplant activity. This activity increased in late autumn and early winter (p=0.05) and could be attributed to increased rates of living (October and November) and deceased organ donation (November and December). An increase in deceased donation was attributed to a rise in donors following cerebrovascular accidents and hypoxic brain injury. Other causes of death (infections and road traffic accidents) were more seasonal in nature peaking in the winter or summer, respectively. Only 1.4% of transplants to intended recipients were redirected due to a lack of healthcare capacity, suggesting that capacity pressures in the National Health Service did not significantly affect transplant activity.

CONCLUSION

UK renal transplant activity peaks in late autumn/winter in contrast to other countries. Currently, healthcare capacity, though under strain, does not affect transplant activity; however, this may change if transplantation activity increases in line with national strategies as the spike in transplant activity coincides with peak activity in the national healthcare system.

National and regional seasonal dynamics of all-cause and cause-specific mortality in the USA from 1980 to 2016

In temperate climates, winter deaths exceed summer ones. However, there is limited information on the timing and the relative magnitudes of maximum and minimum mortality, by local climate, age group, sex and medical cause of death. We used geo-coded mortality data and wavelets to analyse the seasonality of mortality by age group and sex from 1980 to 2016 in the USA and its subnational climatic regions. Death rates in men and women ≥ 45 years peaked in December to February and were lowest in June to August, driven by cardiorespiratory diseases and injuries. In these ages, percent difference in death rates between peak and minimum months did not vary across climate regions, nor changed from 1980 to 2016. Under five years, seasonality of all-cause mortality largely disappeared after the 1990s. In adolescents and young adults, especially in males, death rates peaked in June/July and were lowest in December/January, driven by injury deaths.

In the USA, more deaths happen in the winter than the summer. But when deaths occur varies greatly by sex, age, cause of death, and possibly region. Seasonal differences in death rates can change over time due to changes in factors that cause disease or affect treatment.

Analyzing the seasonality of deaths can help scientists determine whether interventions to minimize deaths during a certain time of year are needed, or whether existing ones are effective. Scrutinizing seasonal patterns in death over time can also help scientists determine whether large-scale weather or climate changes are affecting the seasonality of death.

Now, Parks et al. show that there are age and sex differences in which times of year most deaths occur. Parks et al. analyzed data on US deaths between 1980 and 2016. While overall deaths in a year were highest in winter and lowest in summer, a greater number of young men died during summer – mainly due to injuries – than during winter. Seasonal differences in deaths among young children have largely disappeared and seasonal differences in the deaths of older children and young adults have become smaller. Deaths among women and men aged 45 or older peaked between December and February – largely caused by respiratory and heart diseases, or injuries. Deaths in this older age group were lowest during the summer months. Death patterns in older people changed little over time. No regional differences were found in seasonal death patterns, despite large climate variation across the USA.

The analysis by Parks et al. suggests public health and medical interventions have been successful in reducing seasonal deaths among many groups. But more needs to be done to address seasonal differences in deaths among older adults. For example, by boosting flu vaccination rates, providing warnings about severe weather and better insulation for homes. Using technology like hands-free communication devices or home visits to help keep vulnerable elderly people connected during the winter months may also help.

Assessing Effect Modification of Excess Winter Death by Causes of Death and Individual Characteristics in Zhejiang Province, China: A Multi-Community Case-Only Analysis

Mortality in many parts of the world has a seasonal pattern, with a marked excess of deaths during winter. To date, however, there is very little published evidence on the nature of this wintertime excess in low- and middle-income countries. In this study, we aimed to quantify the extent of the death peak in winter and to assess effect modification on excess winter death (EWD) by individual characteristics and cause of deaths in China. We used a Cosinor model to examine seasonal patterns for specific causes of deaths and a case-only analysis of deaths in winter compared with other seasons to assess effect modification by individual characteristics. A total of 398,529 deaths were investigated between January 2010 and December 2013 in Zhejiang Province, China. Deaths peaked in winter, and overall mortality was around 30% higher in winter than in summer. Although diseases of the respiratory and circulatory systems were highly seasonal, surprisingly we observed that deaths from mental and behavioral disorders exhibited greater fluctuation. Males, the elderly and illiterate individuals suffered high EWD. EWDs were also particularly common in emergency rooms, at home, on the way to hospitals, and in nursing homes/family wards. This study highlighted the high EWD in some previously unreported groups, indicating new information to facilitate the targeting of necessary preventive measures to those at greatest risk in order to mitigate wintertime death burdens.

Respiratory hospital admissions and weather changes: a retrospective study in Charlottesville, Virginia, USA

In most midlatitude locations, human morbidity and mortality are highly seasonal, with winter peaks driven by respiratory disease and associated comorbidities. But the transition between high and low mortality/morbidity months varies spatially. We use a measure of the thermal biophysical strain imposed on the respiratory system-the Acclimatization Thermal Strain Index (ATSI)-to examine respiratory hospital admissions in Charlottesville, VA. Daily respiratory admissions to the University of Virginia over a 19-year period are compared to ATSI values derived from hourly surface weather data acquired from the Charlottesville airport. Negative ATSI values (associated with transitions from warm (and humid) to cold (and dry) conditions) are related to admission peaks at seasonal and weekly timescales, whereas positive ATSI values (cold to warm) exhibit weaker relationships. This research marks the first application of the ATSI to human morbidity, and results suggest that respiratory strain may account for how people who are acclimated to different climates respond to short-term weather changes.

Heat/mortality sensitivities in Los Angeles during winter: a unique phenomenon in the United States

BACKGROUND

Extreme heat is often associated with elevated levels of human mortality, particularly across the mid-latitudes. Los Angeles, CA exhibits a unique, highly variable winter climate, with brief periods of intense heat caused by downsloping winds commonly known as Santa Ana winds. The goal is to determine if Los Angeles County is susceptible to heat-related mortality during the winter season. This is the first study to specifically evaluate heat-related mortality during the winter for a U.S. city.

METHODS

Utilizing the Spatial Synoptic Classification system in Los Angeles County from 1979 through 2010, we first relate daily human mortality to synoptic air mass type during the winter season (December, January, February) using Welch's t-tests. However, this methodology is only somewhat effective at controlling for important inter- and intra-annual trends in human mortality unrelated to heat such as influenza outbreaks. As a result, we use distributed lag nonlinear modeling (DLNM) to evaluate if the relative risk of human mortality increases during higher temperatures in Los Angeles, as the DLNM is more effective at controlling for variability at multiple temporal scales within the human mortality dataset.

RESULTS

Significantly higher human mortality is uncovered in winter when dry tropical air is present in Los Angeles, particularly among those 65 years and older (p < 0.001). The DLNM reveals the relative risk of human mortality increases when above average temperatures are present. Results are especially pronounced for maximum and mean temperatures, along with total mortality and those 65 + .

CONCLUSIONS

The discovery of heat-related mortality in winter is a unique finding in the United States, and we recommend stakeholders consider warning and intervention techniques to mitigate the role of winter heat on human health in the County.

Time series models of environmental exposures: Good predictions or good understanding

Time series data are popular in environmental epidemiology as they make use of the natural experiment of how changes in exposure over time might impact on disease. Many published time series papers have used parameter-heavy models that fully explained the second order patterns in disease to give residuals that have no short-term autocorrelation or seasonality. This is often achieved by including predictors of past disease counts (autoregression) or seasonal splines with many degrees of freedom. These approaches give great residuals, but add little to our understanding of cause and effect. We argue that modelling approaches should rely more on good epidemiology and less on statistical tests. This includes thinking about causal pathways, making potential confounders explicit, fitting a limited number of models, and not over-fitting at the cost of under-estimating the true association between exposure and disease.

Onset seasons and clinical outcomes in patients with Stanford type A acute aortic dissection: an observational retrospective study

OBJECTIVES

To evaluate the association of onset season with clinical outcome in type A acute aortic dissection (AAD).

DESIGN

A single-centre, observational retrospective study.

SETTING

The study was conducted in Fuwai Hospital, the National Centre for Cardiovascular Disease, Beijing, China.

PARTICIPANTS

From 2008 to 2010, a set of consecutive patients with type A AAD, confirmed by CT scanning, were enrolled and divided into four groups according to onset season: winter (December, January and February), spring (March, April and May), summer (June, July and August) and autumn (September, October and November). The primary end points were in-hospital death and all-cause mortality during follow-up.

RESULTS

Of the 492 cases in this study, 129 occurred in winter (26.2%), 147 in spring (29.9%), 92 in summer (18.7%), and 124 in autumn (25.2%). After a median follow-up of 20.4 months (IQR 9.7-38.9), the in-hospital mortality in cases occurring in autumn was higher than in the other three seasons (23.4% vs 8.4%, p<0.01). Long-term mortality was comparable among the four seasonal groups (p=0.63). After adjustment for age, gender and other risk factors, onset in autumn was still an independent factor associated with increased risk of in-hospital mortality (HR 2.05; 95% CI 1.15 to 3.64, p=0.02) in addition to surgical treatment. Further analysis showed that the seasonal effect on in-hospital mortality (autumn vs other seasons: 57.4% vs 27.3%, p<0.01) was only significant in patients who did not receive surgical treatment. No seasonal effect on long-term clinical outcomes was found in this cohort.

CONCLUSIONS

Onset in autumn may be a factor that increases the risk of in-hospital death from type A AAD, especially in patients who receive conservative treatment. Immediate surgery improves the short-term and long-term outcomes regardless of onset season.

Role of Acclimatization in Weather-Related Human Mortality During the Transition Seasons of Autumn and Spring in a Thermally Extreme Mid-Latitude Continental Climate

Human mortality is closely related to natural climate-determined levels of thermal environmental stress and the resulting thermophysiological strain. Most climate-mortality research has focused on seasonal extremes during winter and summer when mortality is the highest, while relatively little attention has been paid to mortality during the transitional seasons of autumn and spring. The body acclimatizes to heat in the summer and cold in winter and readjusts through acclimatization during the transitions between the two during which time the body experiences the thermophysiological strain of readjustment. To better understand the influences of weather on mortality through the acclimatization process, the aim here is to examine the periods that link very cold and very warms seasons. The study uses the Acclimatization Thermal Strain Index (ATSI), which is a comparative measure of short-term thermophysiological impact on the body. ATSI centers on heat exchange with the body’s core via the respiratory system, which cannot be protected. The analysis is based on data for a major city in the climatic region of the Russian Far East characterized by very hot summers and extremely cold winters. The results show that although mortality peaks in winter (January) and is at its lowest in summer (August), there is not a smooth rise through autumn nor a smooth decline through spring. A secondary peak occurs in autumn (October) with a smaller jump in May. This suggests the acclimatization from warm-to-cold produces more thermophysiological strain than the transition from cold-to-warm. The study shows that ATSI is a useful metric for quantifying the extent to which biophysical adaptation plays a role in increased strain on the body during re-acclimatization and for this reason is a more appropriate climatic indictor than air temperature alone. The work gives useful bioclimatic information on risks involved in transitional seasons in regions characterized by climatic extremes. This could be handy in planning and managing health services to the public and measures that might be used to help mitigate impacts.

Seasonal variations in mortality and clinical indicators in international hemodialysis populations from the MONDO registry

Background

Seasonal mortality differences have been reported in US hemodialysis (HD) patients. Here we examine the effect of seasons on mortality, clinical and laboratory parameters on a global scale.

Methods

Databases from the international Monitoring Dialysis Outcomes (MONDO) consortium were queried to identify patients who received in-center HD for at least 1 year. Clinics were stratified by hemisphere and climate zone (tropical or temperate). We recorded mortality and computed averages of pre-dialysis systolic blood pressure (pre-SBP), interdialytic weight gain (IDWG), serum albumin, and log C-reactive protein (CRP). We explored seasonal effects using cosinor analysis and adjusted linear mixed models globally, and after stratification.

Results

Data from 87,399 patients were included (northern temperate: 63,671; northern tropical: 7,159; southern temperate: 13,917; southern tropical: 2,652 patients). Globally, mortality was highest in winter. Following stratification, mortality was significantly lower in spring and summer compared to winter in temperate, but not in tropical zones. Globally, pre-SBP and IDWG were lower in summer and spring as compared to winter, although less pronounced in tropical zones. Except for southern temperate zone, serum albumin levels were higher in winter. CRP levels were highest in winter.

Conclusion

Significant global seasonal variations in mortality, pre-SBP, IDWG, albumin and CRP were observed. Seasonal variations in mortality were most pronounced in temperate climate zones.

Electronic supplementary material

The online version of this article (doi:10.1186/s12882-015-0129-y) contains supplementary material, which is available to authorized users.

Regional and seasonal variation in Clostridium difficile infections among hospitalized patients in the United States, 2001-2010

BACKGROUND

This study identified national regional and seasonal variations in Clostridium difficile infection (CDI) incidence and mortality among hospitalized patients in the United States over a 10-year period.

METHODS

This was a retrospective cohort study of the U.S. National Hospital Discharge Survey from 2001-2010. Eligible cases had an ICD-9-CM discharge diagnosis code for CDI (008.45). Data weights were used to derive national estimates. CDI incidence and mortality were presented descriptively. Regions were as defined by the U.S. Census Bureau. Seasons included the following: winter (December-February), spring (March-May), summer (June-August), and fall (September-November).

RESULTS

These data represent 2.3 million CDI discharges. Overall, CDI incidence was highest in the Northeast (8.0 CDIs/1,000 discharges) and spring (6.2 CDIs/1,000 discharges). CDI incidence was lowest in the West (4.8 CDIs/1,000 discharges) and fall (5.6 CDIs/1,000 discharges). Peak CDI incidence among children occurred in the West (1.7 CDI/1,000 discharges) and winter (1.5 CDI/1,000 discharges). Mortality among all CDI patients was highest in the Midwest (7.3%) and during the winter (7.9%).

CONCLUSION

The region and season with the highest CDI incidence rates among patients hospitalized in U.S. hospitals were the Northeast and spring, respectively. The highest CDI mortality rates were seen in the Midwest and winter. Children exhibited different regional and seasonal CDI variations compared with adults and older adults.

Unusually cold and dry winters increase mortality in Australia

Seasonal patterns in mortality have been recognised for decades, with a marked excess of deaths in winter, yet our understanding of the causes of this phenomenon is not yet complete. Research has shown that low and high temperatures are associated with increased mortality independently of season; however, the impact of unseasonal weather on mortality has been less studied. In this study, we aimed to determine if unseasonal patterns in weather were associated with unseasonal patterns in mortality. We obtained daily temperature, humidity and mortality data from 1988 to 2009 for five major Australian cities with a range of climates. We split the seasonal patterns in temperature, humidity and mortality into their stationary and non-stationary parts. A stationary seasonal pattern is consistent from year-to-year, and a non-stationary pattern varies from year-to-year. We used Poisson regression to investigate associations between unseasonal weather and an unusual number of deaths. We found that deaths rates in Australia were 20-30% higher in winter than summer. The seasonal pattern of mortality was non-stationary, with much larger peaks in some winters. Winters that were colder or drier than a typical winter had significantly increased death risks in most cities. Conversely summers that were warmer or more humid than average showed no increase in death risks. Better understanding the occurrence and cause of seasonal variations in mortality will help with disease prevention and save lives.