Age-adjusted All-cause Mortality Rates Research Articles

Associations of Medical Debt With Health Status, Premature Death, and Mortality in the US

Medical debt is increasingly common in the US. Little is known regarding its association with population health. To examine the associations of medical debt with health status, premature death, and mortality at the county level in the US. This cross-sectional study was conducted at the US county level using 2018 medical debt data from the Urban Institute Debt in America project linked with 2018 data on self-reported health status and premature death from the County Health Rankings & Roadmaps and with 2015 to 2019 mortality data from the National Center for Health Statistics. Data analysis was performed from August 2022 to May 2023. Share of population with any medical debt in collections and median amount of medical debt. Health status was measured as (1) the mean number of physically and mentally unhealthy days in the past 30 days per 1000 people, (2) the mean number of premature deaths measured as years of life lost before age 75 years per 1000 people, and (3) age-adjusted all-cause and 18 cause-specific mortality rates (eg, malignant cancers, heart disease, and suicide) per 100 000 person-years. Multivariable linear models were fitted to estimate the associations between medical debt and health outcomes. A total of 2943 counties were included in this analysis. The median percentage of the county population aged 65 years or older was 18.3% (IQR, 15.8%-20.9%). Across counties, a median 3.0% (IQR, 1.2%-11.9%) of the population were Black residents, 4.3% (IQR, 2.3%-9.7%) were Hispanic residents, and 84.5% (IQR, 65.7%-93.3%) were White residents. On average, 19.8% (range, 0%-53.6%) of the population had medical debt. After adjusting for county-level sociodemographic characteristics, a 1-percentage point increase in the population with medical debt was associated with 18.3 (95% CI, 16.3-20.2) more physically unhealthy days and 17.9 (95% CI, 16.1-19.8) more mentally unhealthy days per 1000 people during the past month, 1.12 (95% CI, 1.03-1.21) years of life lost per 1000 people, and an increase of 7.51 (95% CI, 6.99-8.04) per 100 000 person-years in age-adjusted all-cause mortality rate. Associations of medical debt and elevated mortality rates were consistent for all leading causes of death, including cancer (1.12 [95% CI, 1.02-1.22]), heart disease (1.39 [95% CI, 1.21-1.57]), and suicide (0.09 [95% CI, 0.06-0.11]) per 100 000 person-years. Similar patterns were observed for associations between the median amount of medical debt and the aforementioned health outcomes. These findings suggest that medical debt is associated with worse health status, more premature deaths, and higher mortality rates at the county level in the US. Therefore, policies increasing access to affordable health care, such as expanding health insurance coverage, may improve population health.

Association Between Partisan Affiliation of State Governments and State Mortality Rates Before and During the COVID-19 Pandemic.

Increasing polarization of states reached a high point during the COVID-19 pandemic, when the party affiliation of elected officials often predicted their policy response. The health consequences of these divisions are unclear. Prior studies compared mortality rates based on presidential voting patterns, but few considered the partisan orientation of state officials. This study examined whether the partisan orientation of governors or legislatures was associated with mortality outcomes during the COVID-19 pandemic. Data on deaths and the partisan orientation of governors and legislators were obtained from the Centers for Disease Control and Prevention and the National Conference of State Legislatures, respectively. Linear regression was used to measure the association between Republican representation (percentage of seats held) in legislatures and (1) age-adjusted, all-cause mortality rates (AAMRs) in 2015-2021 and (2) excess death rates during three phases of the COVID-19 pandemic, controlling for median household income, the prevalence of four risk factors (obesity, chronic obstructive pulmonary disease, heart attack, stroke), and state policy orientation. Associations between excess death rates and the governor's party were also examined. States with Republican governors or greater Republican representation in legislatures experienced higher AAMRs during 2015-2021, lower excess death rates during Phase 1 of the COVID-19 pandemic (weeks ending March 28, 2020, through June 13, 2020), and higher excess death rates in Phases 2 and 3 (weeks ending June 20, 2020, through April 30, 2022; p < 0.05). Most associations lost statistical significance after adjustment for control variables. Mortality was higher in states with Republican governors and greater Republican legislative representation before and during much of the pandemic. Observed associations could be explained by the adverse effects of policy choices, reverse causality (e.g., popularity of Republican candidates in states with lower socioeconomic and health status), or unmeasured factors that predominate in states with Republican leaders.

Comorbidities and Outcomes among Females with Non-Alcoholic Fatty Liver Disease Compared to Males.

Sex-based medicine is an important emerging discipline within medicine. We investigated the clinical characteristics, complications, and outcomes of Nonalcoholic Fatty Liver Disease (NAFLD) in females compared to males. Demographics, comorbidities, malignancy, complications, outcomes, and all-cause mortality of NAFLD patients older than 18 years were analyzed. The data were extracted using the MDClone platform from "Clalit" in Israel. A total of 111,993 (52.8%) of the study subjects were females with an average age of 44.4 ± 14.7 years compared to 39.62 ± 14.9 years in males, p &lt; 0.001. Significantly higher rates of hypertension, diabetes mellitus, obesity, dementia, and thyroid cancer and lower rates of ischemic heart disease (22.3% vs. 27.3%, p &lt; 0.001) were found among females. Females had a higher rate of cirrhosis, 2.3% vs. 1.9%, p &lt; 0.001, and a lower rate of hepatocellular carcinoma, 0.4% vs. 0.5%, p &lt; 0.001. In the multivariate analysis, a relationship between age, diabetes mellitus, and cirrhosis development were found among males and females. A lower age-adjusted mortality rate was found among females, 94.5/1000 vs. 116/1000 among males. In conclusion, older age at diagnosis, higher rates of hypertension, diabetes mellitus, obesity, cirrhosis, and a lower age-adjusted all-cause mortality rate were found among females with NAFLD.

846. Trend Analysis of Cause-Specific Mortality among HIV-Infected Veterans: A 35-Year Study

BackgroundThe aims are to estimate the rates for, and examine the trends of, all-cause and cause-specific mortality since the beginning of the epidemic, in an effort to better forecast future mortality patterns and potentially prevent premature death.MethodsAll patients in the HIV Atlanta VA Cohort Study (HAVACS), an ongoing, open cohort of all HIV-infected veterans who ever sought or are seeking care at the Atlanta VA Medical Center, with a documented HIV diagnosis between January 1982 and December 2016 are included. All-cause and cause-specific mortality rates are calculated annually and for the study period, and age-adjusted to the 2000 U.S. standard population. Join-point regression analyses are performed to calculate annual percent changes (APC) and 95% CIs during periods of time when significant changes in trends are observed.ResultsThe analytic sample consisted of 4,674 patients; of whom 1,752 (36.8%) died. The age-adjusted all-cause mortality rate per 100 PY (95% CI) is 19.0 (9.9, 28.2); this rate decreased 45.2% annually from 1983 to 1987, and thereafter became relatively stable. The age-adjusted mortality rates for AIDS–opportunistic infection (aIR=19.0, 95% CI=17.0, 21.0), cardiovascular (aIR=16.2, 95% CI=9.2, 23.1; APC=-2.0), infection (aIR=20.7, 95% CI=10.3, 31.1), liver (aIR=13.8, 95% CI=9.7, 18.0; APC=-0.6), pulmonary (aIR=24.6, 95% CI=3.4, 45.8; APC=-0.3), renal (aIR=17.6, 95% CI=11.1, 24.1; APC=-1.3), and violence (aIR=14.7, 95% CI=9.2, 20.2; APC=-2.8) have all decreased since the beginning of the epidemic, most markedly for AIDS–opportunistic infection (APC=-18.0; 95% CI=-31.9, -1.4) and infection (APC=-3.4; 95% CI=-6.5, -0.3). In contrast, the age-adjusted mortality rates for AIDS–opportunistic malignancy (aIR=32.4, 95% CI=15.9, 48.9; APC=1.5), malignancy (aIR=13.2, 95% CI=6.2, 20.2; APC=1.1), and sudden death (aIR=9.6, 95% CI=6.1, 13.1; APC=32.2) have increased since the beginning of the epidemic.Figure 1. Joinpoint regression analysis of age-adjusted mortality rates in the HAVACS cohort, 1982-2016 (n=4,674). AIDS, acquired immune deficiency syndrome; APC, annual percent change; HAVACS, HIV Atlanta VA Cohort Study; HIV, human immunodeficiency virus; PY, person-years. *Statistically significant at α=0.05. 1. 2000 U.S. standard population; excludes deaths for which the date is unknown (n=46). 2. Coding Causes of Death in HIV (CoDe) protocol adapted to classify causes of death; AIDS-related illnesses refers to an appended list of AIDS-defining illnesses (1993 definition). 3. Pulmonary infections included in pulmonary, not infection. 4. Hepatocellular carcinoma included in liver, not malignancy.ConclusionHIV-infected veterans are experiencing decreasing mortality rates due to almost all causes of death, principally infections; however, increasing mortality rates due to malignancies and sudden death are observed. Identifying risk factors for those causes on the rise may help realign resources and mitigate disease burden in this population.Disclosures All Authors: No reported disclosures

Assessment of Racial Disparities in Mortality Rates Among Older Adults Living in US Rural vs Urban Counties From 1968 to 2016

Population-based mortality rates are important indicators of overall health status. Mortality rates may reflect underlying disparities in access to health care, quality of care, racial and geographical variations, and other socioeconomic factors associated with health. However, there is limited information on historical trends in mortality rates between older Black and White adults living in urban compared with rural communities. To examine historical trends of mortality rates among White adults compared with Black adults and among rural residents compared with urban residents by comparing sex-specific age-adjusted all-cause mortality rates between older adults of both races who reside in rural and urban counties in the US. In this county-level cross-sectional longitudinal study of US counties from January 1, 1968, to December 31, 2016, mortality data were obtained from the CDC WONDER database of the Centers for Disease Control and Prevention, and socioeconomic characteristics were obtained from the Area Health Resources Files of the US Health Resources and Services Administration. The study population included older adults (≥65 years) of Black and White ancestry living in 3131 rural and urban counties in the US. Using ordinary least squares regression analyses, race- and sex-specific trends in mortality rates with 95% CIs were examined, and trends adjusted by county-level socioeconomic characteristics using year and county fixed-effects were calculated. Data were analyzed from March 24 to May 10, 2020. Three geographic regions were examined: urban counties, rural counties adjacent to an urban county (rural-adjacent counties), and rural counties not adjacent to an urban county (rural-nonadjacent counties). All-cause age-adjusted mortality rates of Black and White adults 65 years and older. For 1968, a total of 3076 counties (19 240 437 adults ≥65 years; 11 100 000 women [57.69%]; 1 484 747 Black individuals [7.74%]) were identified; of those, 1138 counties were urban, 1018 counties were rural adjacent, and 922 counties were rural nonadjacent. For 2016, a total of 3087 counties (46 400 000 adults ≥65 years; 25 800 000 women [55.72%]; 4 447 733 Black individuals [9.60%]) were identified; of those, 1163 counties were urban, 1020 counties were rural adjacent, and 904 counties were rural nonadjacent. Between 1968 and 2016, mortality rates per 100 000 persons decreased from 9063 to 4896 deaths (46%) among White men and from 6175 to 3760 deaths (39%) among White women. During the same period, mortality rates decreased from 8801 to 5477 deaths (38%) among Black men and from 6380 to 3960 deaths (38%) among Black women. However, the racial mortality gap increased among men living in rural counties after 1980. From 1968 to 2016, the mortality rate among White men decreased from 9063 to 4751 deaths (48%) in urban counties, from 9113 to 5338 deaths (41%) in rural-adjacent counties, and from 8971 to 5229 deaths (42%) in rural-nonadjacent counties. The mortality rate among Black men during the same period decreased from 8715 to 5368 deaths (38%) in urban counties, from 8924 to 6458 deaths (28%) in rural-adjacent counties, and from 9500 to 6941 deaths (27%) in rural-nonadjacent counties. Rural and urban socioeconomic differences were associated with mortality rate disparities among both White and Black women. However, rural vs urban disparities in mortality rates among men remained significant, especially among Black men living in rural counties. Notably, the current mortality rate of Black men living in rural areas is similar to that of White men living in urban and rural areas in the mid-1980s. Understanding the intersectional factors associated with health disparities may help to inform public health and clinical interventions.

All-Cause Mortality After the Great East Japan Earthquake in Fukushima Prefecture: Trends From 2009 to 2016 and Variation by Displacement.

On March 11, 2011, a magnitude 9 earthquake (the Great East Japan Earthquake) occurred off the east coast of Japan. After the Fukushima Daiichi Nuclear Power Plant accidents, as of 2016, people were not allowed to live in the 6 districts (Tomioka, Okuma, Futaba, Namie, Katsurao, Iidate) in Fukushima Prefecture. In the present study, we aimed to evaluate the long-term effects of displacement on all-cause mortality in Fukushima Prefecture. Data regarding population and deaths from 2009 to 2016 in Fukushima Prefecture were obtained from the governmental statistics. The age-adjusted all-cause mortality were compared among the 4 areas in Fukushima Prefecture; the Eastern, Middle, Western, and Displacement areas. The age-adjusted all-cause mortality rates in the Eastern and Displacement areas were higher than in the other 2 areas from 2009 to 2011. During the period from 2012 to 2016, all-cause mortality in the Displacement area decreased to the lowest, while the morality in the Eastern area remained the highest. Against all expectations, after the earthquake, all-cause mortality in the Displacement area was continuously lower than in the rest of the Fukushima Prefecture. Following disasters, long-term monitoring should be organized to meet local health-care needs.

Mortality Rate and Causes of Death Among Refugees Resettled in Washington State, 2006-2016.

Cause of death among refugees resettled in the United States is not well documented. This evaluation determined cause of death among refugees who resettled to and died in Washington State. Records of refugees who arrived in Washington State from 2006 to 2016 were linked to state death records for the same period. Rates and proportions of death were calculated and compared to those for all Washingtonians. From 2006 to 2016, 171 of 30,243 refugees (0.6%) resettled to and died in Washington. The age-adjusted all-cause mortality rate was 3.93 (95% CI 3.12-4.75) per 1000 refugees, compared to 6.98 (95% CI 6.96-7.00) per 1000 Washingtonians. Malignant neoplasms and heart disease were the leading causes of death for both refugees and Washingtonians. Determining cause of death among refugee populations can identify emerging trends in mortality. This information can be used to help inform disease and injury prevention interventions for refugee communities.

Temporal Trends in Mortality Rates among Kaiser Permanente Southern California Health Plan Enrollees, 2001-2016.

Temporal analyses of death rates in the US have found a decreasing trend in all-cause and major cause-specific mortality rates. To determine mortality trends in Kaiser Permanente Southern California (KPSC), a large insured population, and whether they differ from those of California and the US. Trends in age-adjusted all-cause and cause-specific mortality rates from 2001 to 2016 were determined using data collected in KPSC and those derived through linkage with California State death files and were compared with trends in the US and California. Trends of race/ethnicity-specific all-cause and cause-specific mortality rates were also examined. Average annual percent changes (AAPC) and 95% confidence intervals (CI) were calculated. From 2001 to 2016, the age-adjusted all-cause mortality rate per 100,000 person-years decreased significantly in KPSC (AAPC = -1.84, 95% CI = -2.95 to -0.71), California (AAPC = -1.60, 95% CI = -2.51 to -0.69) and the US (AAPC = -1.10, 95% CI = -1.78 to -0.42). Rates of 2 major causes of death, cancer and heart disease, also decreased significantly in the 3 populations. Differences in trends of age-adjusted all-cause mortality rates and the top 10 cause-specific mortality rates between KPSC and California or the US were not statistically significant at the 95% level. No significant difference was found in the trends of race/ethnicity-specific, sex-specific, or race/ethnicity- and sex-specific all-cause mortality rates between KPSC and California or the US. Trends in age-adjusted mortality rates in this insured population were comparable to those of the US and California.

Mortality by skin color/race, urbanicity, and metropolitan region in Brazil

This study investigated the mortality rate distribution in Brazilian cities based on skin color/race and according to level of urbanicity and aggregation into metropolitan region (MR) in 2010. The age-adjusted all-cause mortality rate (AMR) was calculated according to skin color/race (white, brown, or black). Municipalities were used as analysis units and classified into six categories: Rural within MR; Rural outside MR; ‘Rurbano’ within MR; ‘Rurbano’ outside MR; Urban within MR and Urban outside MR. Racial inequality intensified in line with increasing urbanicity level, from rural to urban areas. However, these differences depended on how the city was aggregated to MR, thus suggesting that the mortality spatial structure was based on skin color or race in these locations. The black population presented the worst AMR risk, mainly in cities outside MR. In addition, it was found that there was an excess mortality in the black population as compared with white people. Mortality-related racial inequalities were associated with urbanicity and MR level. They were also dependent on a complex combination of risk factors in these areas. City categorization may serve as an intervention point to reduce racial inequalities in health among populations in Brazilian cities.

Racial segregation, income inequality, and mortality in US metropolitan areas.

Evidence of the association between income inequality and mortality has been mixed. Studies indicate that growing income inequalities reflect inequalities between, rather than within, racial groups. Racial segregation may play a role. We examine the role of racial segregation on the relationship between income inequality and mortality in a cross-section of US metropolitan areas. Metropolitan areas were included if they had a population of at least 100,000 and were at least 10% black (N = 107). Deaths for the time period 1991–1999 were used to calculate age-adjusted all-cause mortality rates for each metropolitan statistical area (MSA) using direct age-adjustment techniques. Multivariate least squares regression was used to examine associations for the total sample and for blacks and whites separately. Income inequality was associated with lower mortality rates among whites and higher mortality rates among blacks. There was a significant interaction between income inequality and racial segregation. A significant graded inverse income inequality/mortality association was found for MSAs with higher versus lower levels of black–white racial segregation. Effects were stronger among whites than among blacks. A positive income inequality/mortality association was found in MSAs with higher versus lower levels of Hispanic–white segregation. Uncertainty regarding the income inequality/mortality association found in previous studies may be related to the omission of important variables such as racial segregation that modify associations differently between groups. Research is needed to further elucidate the risk and protective effects of racial segregation across groups.

Short report. Variation in mortality rates in Australia: correlation with indigenous status, remoteness and socio-economic deprivation

The aim of this study was to study ecological correlations between age-adjusted all-cause mortality rates in Australian statistical divisions and (1) the proportion of residents that self-identify as Indigenous, (2) remoteness, and (3) socio-economic deprivation. All-cause mortality rates for 57 statistical divisions were calculated and directly standardized to the 1997 Australian population in 5-year age groups using Australian Bureau of Statistics (ABS) data. The proportion of residents who self-identified as Indigenous was obtained from the 1996 Census. Remoteness was measured using ARIA (Accessibility and Remoteness Index for Australia) values. Socioeconomic deprivation was measured using SEIFA (Socio-Economic Index for Australia) values from the ABS. Age-standardized all-cause mortality varies two-fold from 5.7 to 11.3 per 1,000 across Australian statistical divisions. Strongest correlation was between Indigenous status and mortality (r = 0.69, p < 0.001). Correlation between remoteness and mortality was modest (r = 0.39, p = 0.002) as was correlation between socio-economic deprivation and mortality (r = -0.42, p = 0.001). Excluding the three divisions with the highest mortality, a multiple regression model using the logarithm of the adjusted mortality rate as the dependent variable showed that the partial correlation (and hence proportion of the variance explained) for Indigenous status was 0.03 (9 per cent; p = 0.03), for SEIFA score was -0.17 (3 per cent; p = 0.22); and for remoteness was -0.22 (5 per cent; p = 0.13). Collectively, the three variables studied explain 13 per cent of the variability in mortality. Ecological correlation exists between all-cause mortality, Indigenous status, remoteness and disadvantage across Australia. The strongest correlation is with Indigenous status, and correlation with all three characteristics is weak when the three statistical divisions with the highest mortality rates are excluded. Intervention targeted at these three statistical divisions could reduce much of the variability in mortality in Australia.

Postmenopausal estrogen use and mortality. Results from a prospective study in a defined, homogeneous community.

The authors studied the association between postmenopausal estrogen use and mortality from cardiovascular disease, coronary heart disease, cancer, and all causes in a cohort of 1,868 women aged 50-79 years residing in a planned community. After 12 years, the age-adjusted all-cause mortality rate was lower in the 734 postmenopausal estrogen users (14.9/100 women) compared with the 1,134 nonusers (21.5/100 women) (relative risk (RR) = 0.69, 95% confidence interval (Cl) 0.55-0.87). After adjustment for age, systolic blood pressure, social class, fasting plasma cholesterol, fasting plasma glucose, Quetelet index (weight (lbs)/height (in)2 x 100), and cigarette smoking by the Cox model, the relative risk increased to 0.79 (95% Cl 0.62-1.01). Because a postmenopausal estrogen-smoking interaction term was significant (p = 0.025), separate Cox models were run for never, past, and current smokers. In never and current smokers, estrogen was protective for all-cause mortality, with relative risks of 0.67 (95% Cl 0.45-0.99) and 0.62 (95% Cl 0.39-0.98), respectively. However, past smokers were not protected by postmenopausal estrogen use (RR = 1.32, 95% Cl 0.84-2.08). Cause-specific models revealed differences in the association of postmenopausal estrogen use with cardiovascular disease mortality and coronary heart disease mortality that were dependent on smoking status. Postmenopausal estrogen use was strongly protective in current smokers but was associated with increased risk in past smokers. As expected, cancer mortality was increased in smokers. The confidence intervals for the relative risk estimate of postmenopausal estrogen use for cancer mortality in each smoking category included one. Finally, a separate analysis of subsequent three-year mortality in women surviving the first nine years of follow-up revealed reduced death rates only for women using estrogen at both baseline and nine years of follow-up, suggesting both a conservative bias in our data introduced by the large reduction in postmenopausal estrogen use during the study period and the possibility of a stronger protective effect for recent postmenopausal estrogen use.