Factors associated with out-of-hospital coronary heart disease death: the national longitudinal mortality study☆
Introduction
With the rapid implementation of effective treatments of acute myocardial infarction in the hospital setting, it is critical that symptoms of a heart attack be recognized early and a medical response be initiated as soon as possible. While death can happen within minutes of the first onset of symptoms, there is often sufficient warning to enable a life-saving response. The overall delay in arrival at the hospital includes the actual travel time, in addition to delays in any of the following: 1) recognition of symptoms, 2) realization of need for medical care, 3) decision to seek medical care, and 4) obtaining transportation (1). Death may occur at any time along this sequence of delay.
There have been many studies which have sought to identify reasons for delay and ways to reduce the time between symptom onset and hospital arrival. The Rapid Early Action for Coronary Treatment (REACT) trial was a large community intervention study designed to apply community-wide education and information to reduce delay, and to investigate reasons why delay occurs (1). A Medicare-based study, the Cooperative Cardiovascular Project, investigated factors affecting delay in over 100,000 hospitalizations for myocardial infarction (2). Other systematic reviews of hospital records have investigated causes and trends in hospital delay 3., 4., 5.. All of these studies investigate factors related to delay times among those who successfully arrived at the hospital, that is, in those who arrived alive at the emergency room. However, these studies miss the substantial portion that dies prior to admittance to the emergency room.
Characterization of the reasons why deaths occur outside of the hospital is difficult, since there need to be extensive interviews with next-of-kin and the death may have been unwitnessed. Information about the decedent is difficult to obtain retrospectively. Using a large national cohort study [National Longitudinal Mortality Study (NLMS)], deaths which occurred over the follow-up period between 1979 and 1989 have been characterized by cause and by place of death. Additionally, and most importantly, decedents can be characterized by their demographic, social, and economic status at the time of their baseline interview. Thus, features which distinguish out-of-hospital CHD death from in-hospital CHD death can be identified, providing an additional resource to identify factors related to delay times and possibly survival.
Section snippets
Methods
The US National Longitudinal Mortality Study is a prospective study of mortality occurring in combined samples of the non-institutionalized United States population drawn from the Current Population Survey (CPS) 6., 7.. Each CPS conducted by the Census Bureau is a complex, national, probability sample of households surveyed monthly to obtain demographic, economic, and social information about the US population. The surveys, which are conducted by personal and telephone interview, have a
Results
The distribution of all deaths in this study categorized by the general place of death is shown in Table 1. In the 11 NLMS cohorts described above, there were 82,679 deaths available for this study. As described in the Methods section, some states did not include information for the more detailed hospital place of death. The second column in Table 1 shows the distribution of deaths excluding those states with missing information, resulting in a remaining total of 59,034 deaths. Since the focus
Discussion
From a sample of the US population followed for mortality outcome (excluding states with missing data) we identified several demographic and socioeconomic characteristics that are significantly associated with an increased risk that a CHD death will occur out of the hospital. While there are weak relationships with geography, income, and education, there is a moderate relationship with race and a strong relationship with living alone or not being married. This strongly suggests that having a
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Cited by (24)
Breathing new life into death certificates: Extracting handwritten cause of death in the LIFE-M project
2023, Explorations in Economic HistoryCitation Excerpt :For example, research using cause of death in the NLMS finds racial differences in breast cancer mortality by education attainment (Kim et al., 2005; Akinyemiju et al., 2013), differences in brain cancer mortality by occupation (Van Wijngaarden and Dosemeci 2006), male-female differences in lung cancer by education level (Limin et al. 2009), and differences in longevity by socioeconomic status (Du et al., 2011; Chetty et al., 2016). Similar analyses identify key differences in demographic, economic, and geographic factors associated with stroke mortality (Howard et al., 1995; Howard et al., 1997), injury mortality (Hussey 1997), suicide (Kposowa 1999; Kposowa 2001; Kposowa 2013), and heart disease (Mackenbach et al., 2000; Muntaner et al., 2001; Sorlie et al., 2004; Cooper et al., 2009; Coady et al., 2014). Because the relationship between socioeconomic factors and mortality is not stable over time (Bengtsson et al., 2020) or even across places (Bengtsson and van Poppel, 2011), documenting variation in the cause-specific antecedents of mortality in the United States is an important research focus.
Living arrangements as determinants of myocardial infarction incidence and survival: A prospective register study of over 300,000 Finnish men and women
2015, Social Science and MedicineCitation Excerpt :Instrumental support from a partner can also lead to better early detection and care of both early atherosclerosis and later of more complicated forms of CHD such as MI (Atzema et al., 2011). However, when CHD manifests as an acute heart attack, survival often critically depends on reaching hospital quickly, which is likely to be an important contributor to the greater risks of out-of-hospital CHD deaths observed in the unmarried (Empana et al., 2008; Lammintausta et al., 2014; Sorlie et al., 2004). Living alone can dispose to a particularly strong risk for mortality, because it may translate to severe and potentially fatal delays to obtaining acute care (Lammintausta et al., 2014; Schmaltz et al., 2007).
The impact of National Death Index linkages on population-based cancer survival rates in the United States
2013, Cancer EpidemiologyCitation Excerpt :Cancer registries are encouraged to link their incidence records with both state death records and the NDI for the purpose of ascertaining deaths and updating date and cause of death information [9]. Record linkage with the NDI has been used with both adult and pediatric cohort studies [12–17]. The present study uses secondary data from the Accuracy of Cancer Mortality Statistics Based on Death Certificates (ACM) study [18].
Place of death in metropolitan regions: Metropolitan versus non-metropolitan variation in place of death in Belgium, The Netherlands and England
2010, Health and PlaceCitation Excerpt :These motives have incited public health policy to support more people in dying at home where that is their wish (House of Commons Health Committee, 2004). Previous research revealed that residents of urban areas had less chance than their rural counterparts of dying in their own homes (Catalan-Fernandez et al., 1991; Cohen et al., 2006; Costantini et al., 2000; Gomes and Higginson, 2006; Sorlie et al., 2004), particularly if they live in a metropolitan region. Death seemed to occur substantially more often in hospitals and in care homes and less often at home in the metropolitan population of Brussels (Houttekier et al., 2009) than in the more rural population of Flanders, the northern part of Belgium (Cohen et al., 2006).
Neighborhood Disparities in Incident Hospitalized Myocardial Infarction in Four U.S. Communities: The ARIC Surveillance Study
2009, Annals of EpidemiologyCitation Excerpt :However, the patterns of socioeconomic and racial disparities seen in hospitalized MI events may differ from other CHD events, including silent MIs and fatal CHD. Previous reports suggested that blacks are proportionately more likely to have an out-of-hospital fatal CHD event than are whites (50) and that inverse socioeconomic gradients are stronger for out-of-hospital CHD events than for all incident MI events (8). We are currently linking neighborhood socioeconomic data to fatal CHD events in ARIC surveillance communities, which will allow us to examine this issue in a subsequent report.
Marital status and long-term cardiovascular risk in general population (Gubbio, Italy)
2023, Scientific Reports
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This study was funded though an interagency agreement between the National Heart, Lung, and Blood Institute and the Bureau of the Census.