Dataset Information

Educational level, ethnicity and mortality rates in Israel: national data linkage study.

ABSTRACT:

Background

Many studies have shown significant gaps in mortality, and cause specific mortality by educational status. This study investigated these measures in Israel by educational and ethnic status in recent decades.

Method

A mortality follow-up till 2017 was done of a cohort of Israeli residents aged 25-64 in 2000 who remained in Israel and had available educational data, grouped into under 8, 9-11, 12, 13-15 and 16 and above years of education. Indirect age adjustment was used to calculate Standard Mortality Ratios (SMRs) by sex and educational group, and a Cox regression model to assess relative risk of total and cause specific mortality controlling for age and ethnic group (Jews and Others and Arabs).The analysis was repeated for each ethnic group separately.

Results

2,776,422 persons were included of whom 174,792 (6.3%) died till 2017. SMR's for total mortality of males and females with less than 8 years of education compared to 16 and over were 2.2 and 1.8, respectively. Corresponding HR were 2.13 (95% CI 2.08-2.18) and 1.77 (95% CI 1.72-1.82), respectively. The highest cause specific hazard ratios in males were for homicide, 4.40 (95% CI 3.19-6.07), respiratory diseases, 4.01 (95% CI 3.61-4.44), infectious diseases, 3.55 (95% CI 3.15-3.19) and diabetes 3.41 (95% CI 3.06-3.79) and in females for diabetes, 4.41 (95% CI 3.76-5.16), infectious diseases, 4.16 (95% CI 3.52-4.91), respiratory diseases, 4.13 (95% CI 3.55-4.81), and heart disease, 2.96 (95% CI 2.66-3.29). Education-adjusted risk of all-cause mortality for Arab males was 1.07 (1.05-1.09) times that of Jews and Others and non-significant in females. High mortality risk was found for Arab males and females compared to Jews and Others for homicide, diabetes, heart and cerebrovascular disease and for respiratory disease in males. Lower risk was found for suicide and infectious diseases in both sexes and cancer in females.

Conclusion

We found significant effect of educational level on all-cause and cause specific mortality, particularly respiratory diseases, infectious diseases, diabetes and homicide. Our results highlight the importance of increasing the educational level of all groups in the population and of encouraging healthy behavior in the lower educated.

SUBMITTER: Goldberger NF

PROVIDER: S-EPMC8364056 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundRegional variation in clinical practice may identify differences in care, reveal inequity in access, and explain inequality in outcomes. The study aim was to measure geographical variation in Scotland for adjuvant chemotherapy use and mortality in early-stage breast cancer.Patients and methodsIn this retrospective cohort study using population cancer registry-based data linkage, patients with surgically treated early breast cancer between 2001 and 2018 were identified from the Scottish Cancer Registry. Geographical regions considered were based on NHS Scotland organisational structure including 14 territorial Health Boards as well as three regional Cancer Networks. Regional variation in the proportion receiving chemotherapy, breast cancer mortality and all-cause mortality was investigated. Inter-regional comparisons of chemotherapy use were adjusted for differences in case mix using logistic regression. Comparison of breast cancer-specific mortality and all-cause mortality used regression with a parametric survival model. Time trends were assessed using moving average plots.ResultsChemotherapy use ranged from 35% to 46% of patients across Health Boards without adjustment. Variation reduced between 2001 and 2018. Following adjustment for clinical case mix, variation between cancer networks was within 3 percentage points, but up to 10 percentage points from the national average in some Health Boards. Differences in breast cancer mortality and all-cause mortality between cancer networks were modest, with hazard ratios of between 0.933 (95% confidence interval 0.893-0.975) and 1.041 (1.002-1.082) compared with the national average. Survival improved over the time period studied.ConclusionWith adequate case mix adjustment, variation in adjuvant chemotherapy use for early breast cancer in Scotland is small, with a trend towards greater convergence in practice and improved mortality outcomes in more recent cohorts. This suggests very limited regional inequity in access and convergence of clinical practice towards risk-stratified treatment recommendations. Outliers require assessment to understand the reasons for variance.

Project description:BackgroundMigrant and ethnic minority groups are often assumed to have poor health relative to the majority population. Few countries have the capacity to study a key indicator, mortality, by ethnicity and country of birth. We hypothesized at least 10% differences in mortality by ethnic group in Scotland that would not be wholly attenuated by adjustment for socio-economic factors or country of birth.Methods and findingsWe linked the Scottish 2001 Census to mortality data (2001-2013) in 4.62 million people (91% of estimated population), calculating age-adjusted mortality rate ratios (RRs; multiplied by 100 as percentages) with 95% confidence intervals (CIs) for 13 ethnic groups, with the White Scottish group as reference (ethnic group classification follows the Scottish 2001 Census). The Scottish Index of Multiple Deprivation, education status, and household tenure were socio-economic status (SES) confounding variables and born in the UK or Republic of Ireland (UK/RoI) an interacting and confounding variable. Smoking and diabetes data were from a primary care sub-sample (about 53,000 people). Males and females in most minority groups had lower age-adjusted mortality RRs than the White Scottish group. The 95% CIs provided good evidence that the RR was more than 10% lower in the following ethnic groups: Other White British (72.3 [95% CI 64.2, 81.3] in males and 75.2 [68.0, 83.2] in females); Other White (80.8 [72.8, 89.8] in males and 76.2 [68.6, 84.7] in females); Indian (62.6 [51.6, 76.0] in males and 60.7 [50.4, 73.1] in females); Pakistani (66.1 [57.4, 76.2] in males and 73.8 [63.7, 85.5] in females); Bangladeshi males (50.7 [32.5, 79.1]); Caribbean females (57.5 [38.5, 85.9]); and Chinese (52.2 [43.7, 62.5] in males and 65.8 [55.3, 78.2] in females). The differences were diminished but not eliminated after adjusting for UK/RoI birth and SES variables. A mortality advantage was evident in all 12 minority groups for those born abroad, but in only 6/12 male groups and 5/12 female groups of those born in the UK/RoI. In the primary care sub-sample, after adjustment for age, UK/RoI born, SES, smoking, and diabetes, the RR was not lower in Indian males (114.7 [95% CI 78.3, 167.9]) and Pakistani females (103.9 [73.9, 145.9]) than in White Scottish males and females, respectively. The main limitations were the inability to include deaths abroad and the small number of deaths in some ethnic minority groups, especially for people born in the UK/RoI.ConclusionsThere was relatively low mortality for many ethnic minority groups compared to the White Scottish majority. The mortality advantage was less clear in UK/RoI-born minority group offspring than in immigrants. These differences need explaining, and health-related behaviours seem important. Similar analyses are required internationally to fulfil agreed goals for monitoring, understanding, and improving health in ethnically diverse societies and to apply to health policy, especially on health inequalities and inequities.

Project description:BackgroundRecently, studies have examined the underlying patient and practice factors for missed appointments, but less is known about the impact on patient health. People with one or more long-term conditions who fail to attend appointments may be at risk of premature death. This is the first study to examine the effect of missed primary healthcare appointments on all-cause mortality in those with long-term mental and physical health conditions.MethodsWe used a large, nationwide retrospective cohort (n = 824,374) extracted from routinely collected general practice data across Scotland over a 3-year period from September 2013 until September 2016. This data encompasses appointment history for approximately 15% of the Scottish population, and was linked to Scottish deaths records for patients who had died within a 16-month follow-up period. We generated appointment attendance history, number of long-term conditions and prescriptions data for patients. These factors were used in negative binomial and Cox's proportional hazards modelling to examine the risk of missing appointments and all-cause mortality.ResultsPatients with a greater number of long-term conditions had an increased risk of missing general practice appointments despite controlling for number of appointments made, particularly among patients with mental health conditions. These patients were at significantly greater risk of all-cause mortality, and showed a dose-based response with increasing number of missed appointments. Patients with long-term mental health conditions who missed more than two appointments per year had a greater than 8-fold increase in risk of all-cause mortality compared with those who missed no appointments. These patients died prematurely, commonly from non-natural external factors such as suicide.ConclusionsMissed appointments represent a significant risk marker for all-cause mortality, particularly in patients with mental health conditions. For these patients, existing primary healthcare appointment systems are ineffective. Future interventions should be developed with a particular focus on increasing attendance by these patients.

Project description:ObjectiveTo examine county level associations between the prevalence of medical and recreational cannabis stores (referred to as dispensaries) and opioid related mortality rates.DesignPanel regression methods.Setting812 counties in the United States in the 23 states that allowed legal forms of cannabis dispensaries to operate by the end of 2017.ParticipantsThe study used US mortality data from the Centers for Disease Control and Prevention combined with US census data and data from Weedmaps.com on storefront dispensary operations. Data were analyzed at the county level by using panel regression methods.Main outcome measureThe main outcome measures were the log transformed, age adjusted mortality rates associated with all opioid types combined, and with subcategories of prescription opioids, heroin, and synthetic opioids other than methadone. The associations of medical dispensary and recreational dispensary counts with age adjusted mortality rates were also analyzed.ResultsCounty level dispensary count (natural logarithm) is negatively related to the log transformed, age adjusted mortality rate associated with all opioid types (β=-0.17, 95% confidence interval -0.23 to -0.11). According to this estimate, an increase from one to two storefront dispensaries in a county is associated with an estimated 17% reduction in all opioid related mortality rates. Dispensary count has a particularly strong negative association with deaths caused by synthetic opioids other than methadone (β=-0.21, 95% confidence interval -0.27 to -0.14), with an estimated 21% reduction in mortality rates associated with an increase from one to two dispensaries. Similar associations were found for medical versus recreational storefront dispensary counts on synthetic (non-methadone) opioid related mortality rates.ConclusionsHigher medical and recreational storefront dispensary counts are associated with reduced opioid related death rates, particularly deaths associated with synthetic opioids such as fentanyl. While the associations documented cannot be assumed to be causal, they suggest a potential association between increased prevalence of medical and recreational cannabis dispensaries and reduced opioid related mortality rates. This study highlights the importance of considering the complex supply side of related drug markets and how this shapes opioid use and misuse.

Project description:Background Persistent racial/ethnic disparities in cardiovascular disease (CVD) mortality are partially explained by healthcare access and socioeconomic, demographic, and behavioral factors. Little is known about the association between race/ethnicity-specific CVD mortality and county-level factors. Methods and Results Using 2017 county-level data, we studied the association between race/ethnicity-specific CVD age-adjusted mortality rate (AAMR) and county-level factors (demographics, census region, socioeconomics, CVD risk factors, and healthcare access). Univariate and multivariable linear regressions were used to estimate the association between these factors; R2 values were used to assess the factors that accounted for the greatest variation in CVD AAMR by race/ethnicity (non-Hispanic White, non-Hispanic Black, and Hispanic/Latinx individuals). There were 659 740 CVD deaths among non-Hispanic White individuals in 2698 counties; 100 475 deaths among non-Hispanic Black individuals in 717 counties; and 49 493 deaths among Hispanic/Latinx individuals across 267 counties. Non-Hispanic Black individuals had the highest mean CVD AAMR (320.04 deaths per 100 000 individuals), whereas Hispanic/Latinx individuals had the lowest (168.42 deaths per 100 000 individuals). The highest CVD AAMRs across all racial/ethnic groups were observed in the South. In unadjusted analyses, the greatest variation (R2) in CVD AAMR was explained by physical inactivity for non-Hispanic White individuals (32.3%), median household income for non-Hispanic Black individuals (24.7%), and population size for Hispanic/Latinx individuals (28.4%). In multivariable regressions using county-level factor categories, the greatest variation in CVD AAMR was explained by CVD risk factors for non-Hispanic White individuals (35.3%), socioeconomic factors for non-Hispanic Black (25.8%), and demographic factors for Hispanic/Latinx individuals (34.9%). Conclusions The associations between race/ethnicity-specific age-adjusted CVD mortality and county-level factors differ significantly. Interventions to reduce disparities may benefit from being designed accordingly.