Are we really all in this together? The social patterning of mortality during the first wave of the COVID-19 pandemic in Belgium

Abstract Background Belgium was one of the countries that was struck hard by COVID-19. Initially, the belief was that we were ‘all in it together’. Emerging evidence showed however that deprived socioeconomic groups suffered disproportionally. Yet, few studies are available for Belgium. The main question addressed in this paper is whether excess mortality during the first COVID-19 wave followed a social gradient and whether the classic mortality gradient was reproduced. Methods We used nationwide individually linked data from the Belgian National Register and the Census 2011. Age-standardized all-cause mortality rates were calculated during the first COVID-19 wave in weeks 11-20 in 2020 and compared with the rates during weeks 11-20 in 2015-2019 to calculate absolute and relative excess mortality by socioeconomic and -demographic characteristics. For both periods, relative inequalities in total mortality between socioeconomic and -demographic groups were calculated using Poisson regression. Analyses were stratified by age, gender and care home residence. Results Excess mortality during the first COVID-19 wave was high in collective households, with care homes hit extremely hard by the pandemic. The social patterning of excess mortality was rather inconsistent and deviated from the usual gradient, mainly through higher mortality excesses among higher socioeconomic groups classes in specific age-sex groups. Overall, the first COVID-19 wave did not change the social patterning of mortality, however. Differences in relative inequalities between both periods were generally small and insignificant, except by household living arrangement. Conclusion The social patterning during the first COVID-19 wave was exceptional as excess mortality did not follow the classic lines of higher mortality in lower classes and patterns were not always consistent. Relative mortality inequalities did not change substantially during the first COVID-19 wave compared to the reference period.

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EXCESS MORTALITY FROM COVID-19. WEEKLY EXCESS DEATH RATES BY AGE AND SEX FOR SWEDEN.

10.1101/2020.05.10.20096909 ◽

2020 ◽

Cited By ~ 1

Author(s):

Karin Modig ◽

Marcus Ebeling

Keyword(s):

Life Expectancy ◽

Excess Mortality ◽

Total Population ◽

Total Mortality ◽

Death Rates ◽

Excess Death ◽

Relative Risks ◽

All Cause Mortality ◽

The Difference ◽

Age And Sex

Objectives: Mortality from Covid-19 is monitored in detail both within as well as between countries with different strategies against the virus. However, death counts and relative risks based on crude numbers can be misleading. Instead, age specific death rates should be used for comparability. Given the difficulty of ascertainment of Covid-19 specific deaths, excess all-cause mortality is currently more appropriate for comparisons. By estimating age- and sex-specific death rates we aim to get more accurate estimates of the excess mortality attributed to Covid-19, as well as the difference between men and women in Sweden. Design: We make use of Swedish register data about total weekly deaths, total population at risk, and estimate age- and sex-specific weekly death rates for 2020 and the 5 previous years. The data is provided by Statistics Sweden. Results: From the first week of April and onwards, the death rates at all ages above 60 are higher than those in previous years in Sweden. Persons above age 80 are dis-proportionally more affected, and men suffer higher levels of excess mortality than women at all ages with 75% higher death rates for males and 50% higher for females. Current excess mortality corresponds to a decline in remaining life expectancy of 3 years for men and 2 years for women. Conclusion: The Covid-19 pandemic has so far had a clear and consistent effect on total mortality in Sweden, with male death rates being comparably more affected. What consequences the pandemic will eventually have on mortality and life expectancy will depend on the progression of the pandemic, the extent that some of the deaths would have occurred in the absence of the pandemic, only somewhat later, the consequences for other health conditions, as well as the health care sector at large.

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All-cause excess mortality in the State of Gujarat, India, during the COVID-19 pandemic (March 2020-April 2021)

10.1101/2021.08.22.21262432 ◽

2021 ◽

Cited By ~ 1

Author(s):

Rolando J. Acosta ◽

Biraj Patnaik ◽

Caroline Buckee ◽

Satchit Balsari ◽

Ayesha Mahmud

Keyword(s):

Excess Mortality ◽

Age Groups ◽

Total Mortality ◽

The State ◽

Demographic Groups ◽

Mortality Estimate ◽

Baseline Mortality ◽

Diagnostic Capacity ◽

The Impact ◽

Civil Death

AbstractOfficial COVID-19 mortality statistics are strongly influenced by the local diagnostic capacity, strength of the healthcare system, and the recording and reporting capacities on causes of death. This can result in significant undercounting of COVID-19 attributable deaths, making it challenging to understand the total mortality burden of the pandemic. Excess mortality, which is defined as the increase in observed death counts compared to a baseline expectation, provides an alternate measure of the mortality shock of the COVID-19 pandemic. Here, we use data from civil death registers for 54 municipalities across the state of Gujarat, India, to estimate the impact of the COVID-19 pandemic on all-cause mortality. Using a model fit to monthly data from January 2019 to February 2020, we estimate excess mortality over the course of the pandemic from March 2020 to April 2021. We estimated 16,000 [95% CI: 14,000, 18,000] excess deaths across these municipalities since March 2020. The sharpest increase in deaths was observed in April 2021, with an estimated 480% [95% CI: 390%, 580%] increase in mortality from expected counts for the same period. Females and the 40 to 60 age groups experienced a greater increase from baseline mortality compared to other demographic groups. Our excess mortality estimate for these 54 municipalities, representing approximately 5% of the state population, exceeds the official COVID-19 death count for the entire state of Gujarat.

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Excess mortality during the COVID-19 pandemic in Israel, March–November 2020: when, where, and for whom?

Israel Journal of Health Policy Research ◽

10.1186/s13584-021-00450-4 ◽

2021 ◽

Vol 10 (1) ◽

Author(s):

Ziona Haklai ◽

Miriam Aburbeh ◽

Nehama Goldberger ◽

Ethel-Sherry Gordon

Keyword(s):

Excess Mortality ◽

Average Rate ◽

Total Mortality ◽

Mortality Rates ◽

Significant Excess ◽

Arab Population ◽

Susceptible Population ◽

Demographic Groups ◽

Arab Sector ◽

Official Data

Abstract Background Excess all-cause mortality has been used in many countries as an estimate of mortality effects from COVID-19. What was the excess mortality in Israel in 2020 and when, where and for whom was this excess? Methods Mortality rates between March to November 2020 for various demographic groups, cities, month and week were compared with the average rate during 2017–2019 for the same groups or periods. Results Total mortality rates for March–November were significantly higher by 6% in 2020, than the average of 2017–2019, 14% higher among the Arab population and 5% among Jews and Others. Significantly higher monthly mortality rates were found in August, September and October by 11%, 13% and 19%, respectively, among Jews and Others, and by 19%, 64% and 40% in the Arab population. Excess mortality was significant only at older ages, 7% higher rates at ages 65–74 and 75–84 and 8% at ages 85 and above, and greater for males than females in all ages and population groups. Interestingly, mortality rates decreased significantly among the younger population aged under 25. The cities with most significant excess mortality were Ramla (25% higher), Bene Beraq (24%), Bat Yam (15%) and Jerusalem (8%). Conclusion Israel has seen significant excess mortality in August–October 2020, particularly in the Arab sector. The excess mortality in March–November was statistically significant only at older ages, over 65. It is very important to protect this susceptible population from exposure and prioritize them for inoculations. Lockdowns were successful in lowering the excess mortality. The excess mortality is similar to official data on COVID-19 deaths.

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Risk factors for excess all-cause mortality during the first wave of the COVID-19 pandemic in England: A retrospective cohort study of primary care data

PLoS ONE ◽

10.1371/journal.pone.0260381 ◽

2021 ◽

Vol 16 (12) ◽

pp. e0260381

Author(s):

Iain M. Carey ◽

Derek G. Cook ◽

Tess Harris ◽

Stephen DeWilde ◽

Umar A. R. Chaudhry ◽

...

Keyword(s):

Risk Factors ◽

Primary Care ◽

Excess Mortality ◽

Total Mortality ◽

Individual Risk ◽

Mortality Data ◽

All Cause Mortality ◽

Specific Mortality ◽

Mortality Ratio ◽

The Impact

Background The COVID-19 pandemic’s first wave in England during spring 2020 resulted in an approximate 50% increase in all-cause mortality. Previously, risk factors such as age and ethnicity, were identified by studying COVID-related deaths only, but these were under-recorded during this period. Objective To use a large electronic primary care database to estimate the impact of risk factors (RFs) on excess mortality in England during the first wave, compared with the impact on total mortality during 2015–19. Methods Medical history, ethnicity, area-based deprivation and vital status data were extracted for an average of 4.8 million patients aged 30–104 years, for each year between 18-March and 19-May over a 6-year period (2015–2020). We used Poisson regression to model total mortality adjusting for age and sex, with interactions between each RF and period (pandemic vs. 2015–19). Total mortality during the pandemic was partitioned into "usual" and "excess" components, assuming 2015–19 rates represented "usual" mortality. The association of each RF with the 2020 "excess" component was derived as the excess mortality ratio (EMR), and compared with the usual mortality ratio (UMR). Results RFs where excess mortality was greatest and notably higher than usual were age >80, non-white ethnicity (e.g., black vs. white EMR = 2.50, 95%CI 1.97–3.18; compared to UMR = 0.92, 95%CI 0.85–1.00), BMI>40, dementia, learning disability, severe mental illness, place of residence (London, care-home, most deprived). By contrast, EMRs were comparable to UMRs for sex. Although some co-morbidities such as cancer produced EMRs significantly below their UMRs, the EMRs were still >1. In contrast current smoking has an EMR below 1 (EMR = 0.80, 95%CI 0.65–0.98) compared to its UMR = 1.64. Conclusions Studying risk factors for excess mortality during the pandemic highlighted differences from studying cause-specific mortality. Our approach illustrates a novel methodology for evaluating a pandemic’s impact by individual risk factor without requiring cause-specific mortality data.

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1034All-cause mortality in Australia: impact of social isolation and living alone

International Journal of Epidemiology ◽

10.1093/ije/dyab168.060 ◽

2021 ◽

Vol 50 (Supplement_1) ◽

Author(s):

Margo Barr ◽

Alamgir Kabir ◽

Ben Harris-Roxas ◽

Elizabeth Comino ◽

Tony Jackson ◽

...

Keyword(s):

Social Isolation ◽

Record Linkage ◽

Linear Models ◽

Meta Analysis ◽

Total Mortality ◽

Linkage Study ◽

Living Alone ◽

The Social ◽

All Cause Mortality ◽

Rate Ratios

Abstract Background The prevalence of social isolation (SI), living alone (LA) and loneliness among older people in Australia is 17%, 25% and 19% respectively. In a meta-analysis of 70 prospective studies undertaken by Holt-Lunstad et al (2015)1 they found, after controlling for covariates, a 29% increased all-cause mortality for SI, 32% for LA, and 26% for loneliness. But how accurate is this evidence for Australia considering that the meta-analysis only included three Australian studies; all only reporting on LA, and only one reported a significant effect of LA on total mortality. Methods We conducted a record linkage study in NSW using the Social Economic and Environmental Factors sub-study questionnaire data (n = 60,399) from the 45 and Up Study (n = 267,153) and death registrations (Centre for Health Record Linkage). Overall, 20% were SI and 18% were LA. Univariate and multivariable generalised linear models were used to estimate crude and adjusted 7-year all-cause mortality rate ratios (MRR). Results Crude MRR were 28% higher for SI and 98% higher for LA. When adjusted by age and sex they were still significantly higher (28% and 23% respectively). However, when controlled for covariates, SI was 9% higher [AdjRR(95%CI):1.09(1.01-1.18)] and LA had no effect on mortality [AdjRR(95%CI):1.05(0.94-1.18)]. Conclusions As was the case for the Australian studies used in the meta-analysis we found no association between LA and all-cause mortality. We did however find a small significant effect for SI. Key messages Applying the overall meta-analysis results to Australia overestimates the effect of SI and LA on increased all-cause mortality.

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Estimation of Excess Mortality and Years of Life Lost to COVID-19 in Norway and Sweden between March and November 2020

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18083913 ◽

2021 ◽

Vol 18 (8) ◽

pp. 3913

Author(s):

Martin Rypdal ◽

Kristoffer Rypdal ◽

Ola Løvsletten ◽

Sigrunn Holbek Sørbye ◽

Elinor Ytterstad ◽

...

Keyword(s):

Excess Mortality ◽

Age Groups ◽

Years Of Life Lost ◽

Regressive Model ◽

Epidemic Period ◽

All Cause Mortality ◽

Auto Regressive ◽

Expected Mortality ◽

Auto Regressive Model ◽

Excess Deaths

We estimate the weekly excess all-cause mortality in Norway and Sweden, the years of life lost (YLL) attributed to COVID-19 in Sweden, and the significance of mortality displacement. We computed the expected mortality by taking into account the declining trend and the seasonality in mortality in the two countries over the past 20 years. From the excess mortality in Sweden in 2019/20, we estimated the YLL attributed to COVID-19 using the life expectancy in different age groups. We adjusted this estimate for possible displacement using an auto-regressive model for the year-to-year variations in excess mortality. We found that excess all-cause mortality over the epidemic year, July 2019 to July 2020, was 517 (95%CI = (12, 1074)) in Norway and 4329 [3331, 5325] in Sweden. There were 255 COVID-19 related deaths reported in Norway, and 5741 in Sweden, that year. During the epidemic period of 11 March–11 November, there were 6247 reported COVID-19 deaths and 5517 (4701, 6330) excess deaths in Sweden. We estimated that the number of YLL attributed to COVID-19 in Sweden was 45,850 [13,915, 80,276] without adjusting for mortality displacement and 43,073 (12,160, 85,451) after adjusting for the displacement accounted for by the auto-regressive model. In conclusion, we find good agreement between officially recorded COVID-19 related deaths and all-cause excess deaths in both countries during the first epidemic wave and no significant mortality displacement that can explain those deaths.

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Fruit and Vegetable Intake and All-Cause Mortality in a Chinese Population: The China Health and Nutrition Survey

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18010342 ◽

2021 ◽

Vol 18 (1) ◽

pp. 342

Author(s):

Yuxuan Gu ◽

Yansu He ◽

Shahmir H. Ali ◽

Kaitlyn Harper ◽

Hengjin Dong ◽

...

Keyword(s):

Vegetable Intake ◽

Total Mortality ◽

Negative Association ◽

Mortality Data ◽

Sample Population ◽

Fruit And Vegetable ◽

Nutrition Survey ◽

Related Factors ◽

Health And Nutrition ◽

All Cause Mortality

This study was to investigate the association of long-term fruit and vegetable (FV) intake with all-cause mortality. We utilized data from the China Health and Nutrition Survey (CHNS), a prospective cohort study conducted in China. The sample population included 19,542 adult respondents with complete mortality data up to 31 December 2011. Cumulative FV intake was assessed by 3 day 24 h dietary recalls. Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of all-cause mortality. Covariates included sociodemographic characteristics, lifestyle factors, health-related factors, and urban index. A total of 1409 deaths were observed during follow-up (median: 14 years). In the fully adjusted model, vegetable intake of the fourth quintile (327~408 g/day) had the greatest negative association with death compared to the lowest quintile (HR = 0.63, 95% CI: 0.53–0.76). Fruit intake of the fifth quintile (more than 126 g/day) had the highest negative association (HR = 0.24, 95% CI: 0.15–0.40) and increasing general FV intake were also negatively associated with all-cause mortality which demonstrated the greatest negative association in the amount of fourth quintile (HR = 0.59, 95% CI: 0.49–0.70) compared to the lowest quintile. To conclude, greater FV intake is associated with a reduced risk of total mortality for Chinese adults. High intake of fruit has a stronger negative association with mortality than differences in intake of vegetables. Our findings support recommendations to increase the intake of FV to promote overall longevity.

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Dietary patterns related to total mortality and cancer mortality in the United States

Cancer Causes & Control ◽

10.1007/s10552-021-01478-2 ◽

2021 ◽

Author(s):

Marcela R. Entwistle ◽

Donald Schweizer ◽

Ricardo Cisneros

Keyword(s):

United States ◽

Dietary Patterns ◽

Cancer Mortality ◽

Cox Regression ◽

Total Mortality ◽

Principal Component ◽

The United States ◽

Red Meat ◽

Increased Risk ◽

All Cause Mortality

Abstract Purpose This study investigated the association between dietary patterns, total mortality, and cancer mortality in the United States. Methods We identified the four major dietary patterns at baseline from 13,466 participants of the NHANES III cohort using principal component analysis (PCA). Dietary patterns were categorized into ‘prudent’ (fruits and vegetables), ‘western’ (red meat, sweets, pastries, oils), ‘traditional’ (red meat, legumes, potatoes, bread), and ‘fish and alcohol’. We estimated hazard ratios for total mortality, and cancer mortality using Cox regression models. Results A total of 4,963 deaths were documented after a mean follow-up of 19.59 years. Higher adherence to the ‘prudent’ pattern was associated with the lowest risk of total mortality (5th vs. 1st quintile HR 0.90, 95% CI 0.82–0.98), with evidence that all-cause mortality decreased as consumption of the pattern increased. No evidence was found that the ‘prudent’ pattern reduced cancer mortality. The ‘western’ and the ‘traditional’ patterns were associated with up to 22% and 16% increased risk for total mortality (5th vs. 1st quintile HR 1.22, 95% CI 1.11–1.34; and 5th vs. 1st quintile HR 1.16, 95% CI 1.06–1.27, respectively), and up to 33% and 15% increased risk for cancer mortality (5th vs. 1st quintile HR 1.33, 95% CI 1.10–1.62; and 5th vs. 1st quintile HR 1.15, 95% CI 1.06–1.24, respectively). The associations between adherence to the ‘fish and alcohol’ pattern and total mortality, and cancer mortality were not statistically significant. Conclusion Higher adherence to the ‘prudent’ diet decreased the risk of all-cause mortality but did not affect cancer mortality. Greater adherence to the ‘western’ and ‘traditional’ diet increased the risk of total mortality and mortality due to cancer.

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Association of mushroom consumption with all-cause and cause-specific mortality among American adults: prospective cohort study findings from NHANES III

Nutrition Journal ◽

10.1186/s12937-021-00691-8 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Djibril M. Ba ◽

Xiang Gao ◽

Joshua Muscat ◽

Laila Al-Shaar ◽

Vernon Chinchilli ◽

...

Keyword(s):

Lower Risk ◽

Proportional Hazards ◽

Total Mortality ◽

Cox Proportional Hazards ◽

Dietary Factors ◽

Mortality Data ◽

Nhanes Iii ◽

Dietary Recall ◽

All Cause Mortality ◽

Specific Mortality

Abstract Background Whether mushroom consumption, which is rich in several bioactive compounds, including the crucial antioxidants ergothioneine and glutathione, is inversely associated with low all-cause and cause-specific mortality remains uncertain. This study aimed to prospectively investigate the association between mushroom consumption and all-cause and cause-specific mortality risk. Methods Longitudinal analyses of participants from the Third National Health and Nutrition Examination Survey (NHANES III) extant data (1988–1994). Mushroom intake was assessed by a single 24-h dietary recall using the US Department of Agriculture food codes for recipe foods. All-cause and cause-specific mortality were assessed in all participants linked to the National Death Index mortality data (1988–2015). We used Cox proportional hazards regression models to calculate multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (95% CIs) for all-cause and cause-specific mortality. Results Among 15,546 participants included in the current analysis, the mean (SE) age was 44.3 (0.5) years. During a mean (SD) follow-up duration of 19.5 (7.4) years , a total of 5826 deaths were documented. Participants who reported consuming mushrooms had lower risk of all-cause mortality compared with those without mushroom intake (adjusted hazard ratio (HR) = 0.84; 95% CI: 0.73–0.98) after adjusting for demographic, major lifestyle factors, overall diet quality, and other dietary factors including total energy. When cause-specific mortality was examined, we did not observe any statistically significant associations with mushroom consumption. Consuming 1-serving of mushrooms per day instead of 1-serving of processed or red meats was associated with lower risk of all-cause mortality (adjusted HR = 0.65; 95% CI: 0.50–0.84). We also observed a dose-response relationship between higher mushroom consumption and lower risk of all-cause mortality (P-trend = 0.03). Conclusion Mushroom consumption was associated with a lower risk of total mortality in this nationally representative sample of US adults.

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Disparity and Dynamics of Social Distancing Behaviors in Japan: An Investigation of mobile phone mobility data (Preprint)

10.2196/preprints.31557 ◽

2021 ◽

Author(s):

Zeyu Lyu ◽

Hiroki Takikawa

Keyword(s):

Large Scale ◽

Age Groups ◽

Mitigation Strategies ◽

Social Distancing ◽

Demographic Groups ◽

Fine Grained ◽

Mobility Data ◽

The Social ◽

The Government ◽

Over Time

BACKGROUND The availability of large-scale and fine-grained aggregated mobility data has allowed researchers to observe the dynamic of social distancing behaviors at high spatial and temporal resolutions. Despite the increasing attentions paid to this research agenda, limited studies have focused on the demographic factors related to mobility and the dynamics of social distancing behaviors has not been fully investigated. OBJECTIVE This study aims to assist in the design and implementation of public health policies by exploring the social distancing behaviors among various demographic groups over time. METHODS We combined several data sources, including mobile tracking data and geographical statistics, to estimate visiting population of entertainment venues across demographic groups, which can be considered as the proxy of social distancing behaviors. Then, we employed time series analyze methods to investigate how voluntary and policy-induced social distancing behaviors shift over time across demographic groups. RESULTS Our findings demonstrate distinct patterns of social distancing behaviors and their dynamics across age groups. The population in the entertainment venues comprised mainly of individuals aged 20–40 years, while according to the dynamics of the mobility index and the policy-induced behavior, among the age groups, the extent of reduction of the frequency of visiting entertainment venues during the pandemic was generally the highest among younger individuals. Also, our results indicate the importance of implementing the social distancing policy promptly to limit the spread of the COVID-19 infection. However, it should be noticed that although the policy intervention during the second wave in Japan appeared to increase the awareness of the severity of the pandemic and concerns regarding COVID-19, its direct impact has been largely decreased could only last for a short time. CONCLUSIONS At the time we wrote this paper, in Japan, the number of daily confirmed cases was continuously increasing. Thus, this study provides a timely reference for decision makers about the current situation of policy-induced compliance behaviors. On the one hand, age-dependent disparity requires target mitigation strategies to increase the intention of elderly individuals to adopt mobility restriction behaviors. On the other hand, considering the decreasing impact of self-restriction recommendations, the government should employ policy interventions that limit the resurgence of cases, especially by imposing stronger, stricter social distancing interventions, as they are necessary to promote social distancing behaviors and mitigate the transmission of COVID-19. CLINICALTRIAL None

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