Dimensionality reduction model based on integer planning for the analysis of key indicators affecting life expectancy

Purpose:Exploring a dimensionality reduction model that can adeptly eliminate outliers and select the appropriate number of clusters is of profound theoretical and practical importance.Additionally,the interpretability of these models presents a persistent challenge.Design/methodology/approach:This paper proposes two innovative dimensionality reduction models based on integer programming(DRMBIP).These models assess compactness through the correlation of each indicator with its class center,while separation is evaluated by the correlation between different class centers.In contrast to DRMBIP-p,the DRMBIP-v considers the threshold parameter as a variable aiming to optimally balances both compactness and separation.Findings:This study,getting data from the Global Health Observatory(GHO),investigates 141 indicators that influence life expectancy.The findings reveal that DRMBIP-p effectively reduces the dimensionality of data,ensuring compactness.It also maintains compatibility with other models.Additionally,DRMBIP-v finds the optimal result,showing exceptional separation.Visualization of the results reveals that all classes have a high compactness.Research limitations:The DRMBIP-p requires the input of the correlation threshold parameter,which plays a pivotal role in the effectiveness of the final dimensionality reduction results.In the DRMBIP-v,modifying the threshold parameter to variable potentially emphasizes either separation or compactness.This necessitates an artificial adjustment to the overflow component within the objective function.Practical implications:The DRMBIP presented in this paper is adept at uncovering the primary geometric structures within high-dimensional indicators.Validated by life expectancy data,this paper demonstrates potential to assist data miners with the reduction of data dimensions.Originality/value:To our knowledge,this is the first time that integer programming has been used to build a dimensionality reduction model with indicator filtering.It not only has applications in life expectancy,but also has obvious advantages in data mining work that requires precise class centers.

New Characteristics of Active Life Expectancy of the Elderly in China

Life expectancy of the elderly is a significant problem in China, and it changes not only the health care, but also the pension. This study used tracking data from the Chinese Urban and Rural Elderly Population Survey to calculate the age-specific Active Life Expectancy (ALE) of the Chinese elderly population aged 60 years and over. For analysis, this population was divided into different sub-populations according to gender, census register and region. The main conclusions of our study are as follows: 1) The quality of life for elderly males may be greater than that for elderly females;2) There were significant differences in Active Life Expectancy (ALE) and Inactive Life Expectancy (ILE) between urban and rural elderly;3) The differences in ALE between the eastern, central and western regions of China were not significant;and 4) The increased remaining life expectancy of the elderly was mainly attributed to the extended ALE in the lower age group and the expanded ILE in the higher age group. This study expands the knowledge of Chinese elderly’s life expectancy in different health status.

Impact of Cardiovascular Disease Deaths on Life Expectancy in Chinese Population

Objective We aimed to analyze the impact of cardiovascular disease （CVD） deaths on life expectancy （LE） in Chinese population and estimate the percentage reduction in CVD mortality needed to increase LE by 1 year from the current level, a national target of health improvement. Methods We used life tables, cause-elimination life tables, and age decomposition of LE with corrected mortality data from the National Disease Surveillance System in 2010. Results LE at birth of Chinese people was 73.24 years in 2010. Women had a longer LE than men, and urban population had a longer LE than rural population. CVD deaths resulted in a 4.79-year LE loss and premature deaths in people aged 25 to 64 years were responsible for a substantial part of LE loss from CVD. Death from ischemic heart disease and cerebrovascular diseases accounted for 69.2% of LE loss from CVD deaths and death from cerebrovascular diseases was the largest contributor. In rural men, 51.1% LE loss from CVD deaths was caused by cerebrovascular diseases. If there were no changes in mortality rates for all other diseases, a 27.4% reduction in CVD mortality would increase LE by i year in Chinese population. Conclusion There is a considerable impact of CVD deaths on LE. A 1-year LE increase in the future requires at least a 27.4% reduction in CVD mortality from the current level. Targeting the rural population and tackling cerebrovascular diseases are important for reaching the national goal of health improvement.

Evaluation of Impact of Major Causes of Death on Life Expectancy Changes in China,1990-2005

Objective To evaluate the impact of major causes of death on changes of life expectancy in China. Methods Life expectancy was calculated by standard life table techniques using mortality data from the national censuses in 1990 and 2000 and the 1% National Population Sampling Surveys in 1995 and 2005, Mortality data about the major causes of death from VR-MOH were used as reference values to estimate their death proportions of the specific age groups by sex and regions, as well as all-cause mortality and age-specific mortality rates of major causes of death. Decomposition method was used to quantitatively evaluate the impact. Results Three key findings were identified in our study. First, China's health challenge was shifted from diseases related to living conditions to those related to behavior and lifestyle, with rural areas relatively lagged behind urban areas, Second, the impacts of cardiovascular diseases and neoplasm on the middle aged and elderly population were stressed. Third, compared to the urban population, the rural population tended to have increasing mortality of neoplasm and cardiovascular diseases, especially in adults at the age of 15-39 years. Conclusion Further efforts should be made to reduce the incidence of neoplasm and cardiovascular diseases, especially in rural areas, by promoting healthy behavior and lifestyle and providing appropriate therapies for all patients in need.

Impact of Cerebrovascular Disease Mortality on Life Expectancy in China

Objective To evaluate the impact of cerebrovascular disease mortality on life expectancy （LE） in China in 2010 compared with 2005, and to identify the high-risk population （age, sex, and region） where cerebrovascular disease mortality has had a major impact on LE. Methods LE and cause-eliminated LE were calculated by using standard life tables which used adjusted mortality data from the Death Surveillance Data Sets in 2005 and 2010 from the National Disease Surveillance System. Decomposition was used to quantitate the impact of cerebrovascular disease in different age groups. Results LE in China was 73.24 years in 2010, which was higher in women and urban residents compared with men and rural residents. The loss of LE caused by cerebrovascular disease mortality was 2.26 years, which was higher in men and rural residents compared with women and urban residents. More than 30% of the loss of LE were attributed to premature death from cerebrovascular disease in people aged 〈65 years. Compared with 2005, LE in 2010 increased by 0.92 years. The reduction of cerebrovascular disease mortality in urban residents contributed 0.45 years to the increase of LE, but the increase of cerebrovascular disease mortality caused a 0.12-year loss of LE in rural residents. Conclusion Cerebrovascular disease mortality had a major impact on LE in China, with a significant difference between urban and rural residents. LE is likely to be further increased by reducing cerebrovascular disease mortality, and special attention should be paid to reducing premature deaths in people aged 〈65 years.

Nurse staffing and life expectancy at birth and at 65 years old:Evidence from 35 OECD countries

Objective: To measure the possible magnitude of the role nurse staffing has on increasing life expectancy at birth and at 65 years old.Methods: The statistical technique of panel data analysis was applied to investigate the relationship from the number of practicing nurses' density per 1000 population to life expectancy at birth and at 65 years old.Five control variables were used as the proxies for the levels of medical staffing,health care financial and physical resources,and medical technology.The observations of 35 member countries of Organization for Economic Co-operation and Development (OECD) were collected from OECD Health Statistics over 2000-2016 period.Results: There were meaningful relationships from nurse staffing to life expectancy at birth and at 65 years with the long-run elasticities of 0.02 and 0.08,respectively.Overall,the role of nursing characteristics in increasing life expectancy indicators varied among different health care systems of OECD countries and in average were determined at the highest level in Japan (0.25),followed by Iceland (0.24),Belgium (0.21),Czech Republic (0.21),Slovenia (0.20) and Sweden (0.18).Conclusion: A higher proportion of nursing staff is associated with higher life expectancy in OECD countries and the dependency of life expectancy to nursing staff would increase by aging.Hence,the findings of this study warn health policy makers about ignoring the effects nursing shortages create e.g.increasing the risk of actual age-specific mortality,especially in care of elderly people.

The Nationwide Impact of Injury-related Deaths on Average Life Expectancy in China

To expand the evidence base to inform future public policy aimed at accident prevention, we investigated the impact of different categories of injury on average life expectancy in China. We used data from the National Death Cause Registration Information System and National Maternity and Children Health Surveillance databases, as well as 2010 population data from the National Bureau of Statistics. We then calculated the average life expectancy of the Chinese population, in addition to life expectancy after eliminating injury-related mortality. The average life expectancy of the Chinese population in 2010 was 74.93 years. After eliminating deaths due to injuries, the fourth leading cause of mortality in China, average life expectancy increased by 1.36 years. When this was broken down by population sub-groups, these gains were 1.76 and 0.79 years in men and women, 0.94 and 1.56 years in urban and rural residents, and 1.11, 1.30, and 1.67 years for residents in the Eastern, Central and Western regions respectively. After eliminating all categories of injury, the average life expectancy of the Chinese population was found to increase by 1.36 years. This figure was higher for males and residents of rural areas and Western China.

Key Social Determinants to Narrow the Gap between Health-adjusted Life Expectancy and Life Expectancy in Megacities

Objective Improvement in the quality of life is reflected in the narrowing of the gap between healthadjusted life expectancy(HALE)and life expectancy(LE).The effect of megacity expansion on narrowing the gap is rarely reported.This study aimed to disclose this potential relationship.Methods Annual life tables were constructed from identified death records and population counts from multiple administrative sources in Guangzhou,China,from 2010 to 2020.Joinpoint regression was used to evaluate the temporal trend.Generalized principal component analysis and multilevel models were applied to examine the county-level association between the gap and social determinants.Results Although LE and HALE in megacities are increasing steadily,their gap is widening.Socioeconomic and health services are guaranteed to narrow this gap.Increasing personal wealth,a growing number of newborns and healthy immigrants,high urbanization,and healthy aging have helped in narrowing this gap.Conclusion In megacities,parallel LE and HALE growth should be highly considered to narrow their gap.Multiple social determinants need to be integrated as a whole to formulate public health plans.

Impact of Long-term Exposure to Air Particulate Matter on Life Expectancy and Survival Rate of Shanghai Residents

Objective To evaluate the impact of long-term air particulate matter exposure on the life expectancy and survival rate of Shanghai residents. Methods Epidemiology - based exposure-response function was used for the calculation of attributable deaths to air particulate matter in Shanghai, and the effect of long-term exposure to particulate matter on life expectancy and survival rate was estimated using the life table of Shanghai residents in 1999. Results It was shown that in 1999, the long-term air particulate matter exposure caused 1.34-1.69 years reduction of life expectancy and a decrease of survival rate for each age group of Shanghai residents. Conclusion The effect of long-term exposure to air particulate matter on life expectancy is substantial in Shanghai.

Progress in Research of Nutrition and Life Expectancy

Life expectancy is an important indicator to evaluate the social development of a country. Health and longevity can not only improve people＇s life quality but also ensure them to have more time to pursue their life goal. A one-year increase in life expectancy during ＇China＇s Twelfth Five-Year Economic and Social Development Plan＇ period has been used as an indicator to evaluate whether the goal of improving people＇s living standards continuously is met. Nutrition is one of the important factors affecting people＇s health. Both malnutrition and overnutrition are risk factors for disease and death. Many studies of the relationship between nutrition and life expectancy have been conducted in the world, and the results of them are quite valuable for China to improve people＇s life expectancy by targeted nutrition intervention strategy. This paper summarizes the progress in research of nutrition and life expectancy in the world.

Reduced Life Expectancy Model Analyses of Exposure Time Effects of Endocrine Disruptors to Teleost Fishes Based on Effect Concentration of Hepatic Biomarkers

In this current paper, the exposure time effects on four endocrine disruptors and teleost fishes were evaluated using the reduced life expectancy (RLE) model based on the effect concentration (EC50) of available literature published. The result on the regression analysis over different exposure times has demonstrated that the EC50 of hepatic biomarkers falls with increasing exposure times in a predictable manner. The slopes of the regression equations reflect the strength of the toxic effects on the various teleost fish. The EC50 reduction over time can be interpreted based on the bioconcentration process, which can be used to understand transfer routes of the compounds from water to fish body. RLE model also provides useful information in assessing the toxic effects on fish life expectancy as a result of the occurrence of compounds.

Test of Ordered Multivariate Discrete Selection Model for Average Life Expectancy

At present, there are significant regional differences in average life expectancy among countries in the world. Not only is there a great disparity in average life expectancy, but also the gender difference is positive and negative, and is distributed in a bipolar distribution of “long life in rich countries and short life in poor countries”. This paper analyzes the factors affecting the life grade by using the ordered multivariate discrete selection model and combined with the average life expectancy data of countries all over the world in 2017. The test results show that: 1) The growth of per capita GDP, elderly dependency ratio and the proportion of people using at least basic drinking water services can effectively improve the level of life expectancy;2) The birth rate has an inhibitory effect on the average life expectancy;3) Through model comparison, probit model is more suitable for the analysis of this kind of problems than logit model, and the properties of the obtained model are better.

Dynamic prediction of landslide life expectancy using ensemble system incorporating classical prediction models and machine learning

With the development of landslide monitoring system,many attempts have been made to predict landslide failure-time utilizing monitoring data of displacements.Classical models(e.g.,Verhulst,GM(1,1),and Saito models)that consider the characteristics of landslide displacement to determine the failuretime have been investigated extensively.In practice,monitoring is continuously implemented with monitoring data-set updated,meaning that the predicted landslide life expectancy(i.e.,the lag between the predicted failure-time and time node at each instant of conducting the prediction)should be re-evaluated with time.This manner is termed“dynamic prediction”.However,the performances of the classical models have not been discussed in the context of the dynamic prediction yet.In this study,such performances are investigated firstly,and disadvantages of the classical models are then reported,incorporating the monitoring data from four real landslides.Subsequently,a more qualified ensemble model is proposed,where the individual classical models are integrated by machine learning(ML)-based meta-model.To evaluate the quality of the models under the dynamic prediction,a novel indicator termed“discredit index(b)”is proposed,and a higher value of b indicates lower prediction quality.It is found that Verhulst and Saito models would produce predicted results with significantly higher b,while GM(1,1)model would indicate results with the highest mean absolute error.Meanwhile,the ensemble models are found to be more accurate and qualified than the classical models.Here,the performance of decision tree regression-based ensemble model is the best among the various ML-based ensemble models.

Contributions by age and cause to life expectancy gap between China and South Korea,1990-2019:a decomposition analysis

In the past 30 years,the life expectancy in China continues to rise yet at a slower pace because of,in large part,the heavy burden of chronic diseases on older age groups.Based on data obtained from the United Nations World Population Prospects 2019 and the Global Burden of Disease Study 2019,this study applies Arriaga’s decomposition method to decompose the age/cause-specific contributions to life expectancy gap between China and South Korea during 1990-2019,which could provide understanding on mortality patterns and heavy burden by chronic disease resulting from an aging society.The study has found that the life expectancy gap between these two countries for females has remained constant,while that of males has been increasing during the same period.Another finding is that non-communicable diseases,like cardiovascular diseases among the elderly(aged 60+),explain a large and enlarging part of the life expectancy gap between China and South Korea,especially among males.In addition,maternal and neonatal disorders among children(age group 1-4ys)contribute less and less to life expectancy gap.Those observations suggest a convergence of mortality pattern among younger age groups as well as the continued existence of substantial gaps among older age groups.Additionally,given the precedent of South Korea,China should also take suicide as another issue with greater attention in the future.Finally,this study concludes by suggesting targeted public health policies to reduce mortality in certain age groups and save more lives from certain diseases.

The impact of stomach cancer mortality on life expectancy at birth:a decomposition analysis in east Asian countries from 1990 to 2019

From 1990 to 2019,stomach cancer posed a significant health burden in East Asia.The impact of stomach cancer deaths on life expectancy at birth in East Asian countries remains underexplored.This study quantifies the impact of stomach cancer on life expectancy(LE)and decomposes the age-specific contributions of this impact from 1990 to 2019 for East Asian countries.Using Global Burden of Disease data,we utilize potential gains in life expectancy(PGLEs)at birth to assess the impact by building cause-deleted life tables.The research decomposed age-specific contributions to the impact using Arriaga’s method.The findings reveal that stomach cancer deaths reduced approximately 0.35 to 1.02 years in LE at birth for males and 0.24 to 0.66 years for females in East Asian countries over the decades.The impact of stomach cancer on life expectancy in China,Japan,and South Korea converged before 2004 and then declined.A sudden drop characterized North Korea between 1995 and 2003.Notably,the patterns of age-specific contributions to the impact were heterogeneous.In China,Japan,and South Korea,the most impactful contribution in the PGLEs at birth shifted towards older age groups,while the pattern in North Korea showed limited changes.Focusing on consistent stomach cancer prevention policies could yield greater life expectancy gains,especially for older males.Despite rising life expectancy,nations with slower declines in stomach cancer mortality may face a more pronounced impact in the future.

Average life expectancy of the Chinese population in 1949-2019: trends, contributors and prospects

This paper provided an overview of literature on life expectancy of Chinese popu-lation,elaborated the characteristics of the significant increase in the average life expectancy(ALE)of Chinese population over the past 70 years since the founding of PRC,analyzed the major factors contributing to the improvement in the ALE,and highlight the needs to put greater emphasize to increase average healthy life expectancy(AHLE),to narrow the regional differences in AHLE,to advocate and promote healthy lifestyles,and to prevent and control pollution persistently and effectively.

Interactions between life expectancy and the incidence and mortality rates of cancer in China: a population-based cluster analysis

Background:The relationship between cancer and life expectancy is well established in both developed and developing countries.China is a vast country with significant geographical differences in population structure and healthcare,and thus provides a unique opportunity to analyze the complex relationship between life expectancy and cancer incidence and mortality rates.Methods:Cancer data were extracted for a total of 255 units(cities or counties)from the 2013 National Central Cancer Registry.Life expectancy data at the unit level were obtained from the National Centers for Disease Control and Prevention.Linear regression analysis was used to analyze the relationship between life expectancy and crude incidence and mortality rates of cancer.In a separate analysis,life expectancy was rated as low(<76.0 years),middle(76-80 years),or high(>80 years).Results:Overall,the cancer incidence and mortality rates positively correlated with life expectancy in both sexes(R at 0.37 and 0.50,P<0.001).The correlation was significant for the following cancers:lung,colorectal,prostate,blad-der and pancreas,as well as for lymphoma in men(R 0.36-0.58,P<0.001),lung,breast,colorectal,thyroid,uterus,and ovary in women(R 0.18-0.51,P<0.001).We failed to observe an association between upper gastrointestinal cancer and life expectancy.The number of cities/counties with low,middle and high life expectancy levels were 110,101 and 44,respectively.The highest age-standardized cancer incidence rate was observed in areas with a high life expec-tancy level(192.83/100,000).The highest age-standardized mortality rate was in areas with the lowest life expectancy(118.44/100,000).Cancers of the stomach,liver and esophagus are major cancer types in areas with low and middle life expectancy.In contrast,areas with high life expectancy had high incidence and mortality rates of colorectal can-cer,breast cancer in women and prostate cancer in men.Conclusions:Longer life expectancy is associated with higher overall cancer incidence and mortality in China.The cancer pattern also varies substantially across areas with different life expectancy levels.Life expectancy levels must be considered when developing strategies to prevent and treat cancers.

Temporal trend in mortality of cardiovascular diseases and its contribution to life expectancy increase in China, 2013 to 2018

Backgrounds::Cardiovascular disease(CVD)remains the leading cause of deaths nationwide.However,little is understood about its temporal trend and corresponding influence on longevity improvements.We aimed to describe the updated tendency in CVD mortality and to quantify its impact on life expectancy(LE)increase in China.Methods::All-cause mortality rates were calculated with population sizes from the National Bureau of Statistics and death counts from the National Health Commission.We estimated CVD mortality rates by allocating age-and sex-based mortality envelopes to each CVD subtype based on its proportion derived from the Disease Surveillance Points system.The probability of CVD premature deaths and LE were calculated with life tables and we adopted Arriaga’s method to quantitate age-and cause-specific contributions to LE gains.Results::During 2013 to 2018,the age-standardized mortality rate of CVD decreased from 289.69(95%confidence interval[CI]:289.03,290.35)/100,000 to 272.37(95%CI:271.81,272.94)/100,000,along with a decline in probability of CVD premature deaths from 9.05%(95%CI:9.02%,9.09%)to 8.13%(95%CI:8.10%,8.16%).The gap in CVD mortality across sexes expanded with more remarkable declines in females,especially for those aged 15 to 64 years.Among major subtypes,the probability of premature deaths from hemorrhage stroke declined fastest,while improvements of ischemic stroke and ischemic heart disease were limited,and there was an increase in stroke sequelae.LE in China reached 77.04(95%CI:76.96,77.12)years in 2018 with an increase of 1.38 years from 2013.Of the total LE gains,21.15%(0.29 years)were attributed to reductions of CVD mortality in the overall population,mostly driven by those aged>65 years.Conclusions::The general process in reducing CVD mortality has contributed to longevity improvements in China.More attention should be paid to prevention and control of atherosclerotic CVD and stroke sequelae,especially for the elderly.Working-age males also deserve additional attention due to inadequate improvements.

Does Life Expectancy Affect Private Educational Investment in China?

In this paper, we emphasize the interactive effect between life expectancy and human capital accumulation, and test the positive feedback of longevity to educational investment in China. This is very important for understanding the pressure from the aging population and the increase in private educational investment in China. We first show in an extended human eapital investment model that life expectancy growth acts as a driving force for educational investment. We then build a difference-in-difference-in-differences empirieal framework and use cross-province data to examine the effect in China. We use the maternal mortality rate （MMR） to identify the difference in life expectancy between genders, and the illiteracy rate or average years of education by gender for educational investment. The empirical results comply with the theory, in that increases in life expectancy significantly lower illiteracy rates and improve the average schooling years in China. This content of the present paper is closely related to crucial issues like population aging, human capital accumulation and gender discrimination. Policy implications are discussed based on the empirical results.

Increasing life expectancy in China by achieving its 2025 air quality target

China is striving to build a“Beautiful China”characterized by clean air.The country has committed to further reducing its national mean fine particle(PM_(2.5))concentration by 10%from 2020 to 2025,following the substantial improvements in its air quality during the past decade.Meanwhile,the“Healthy China”mission has pledged to increase the national mean life expectancy by one year during the same period.Yet,to what extent will the“Beautiful China”mission contribute to the“Healthy China”vision by reducing the levels of the detrimental PM_(2.5) is still unclear.Here,by coupling the life table approach and an epidemiological concentration-response model,this study quantifies the potential benefits of achieving China's 2025 air quality target on the national life expectancy.The analysis reveals that the Chinese citizen could expect to extend the average life expectancy by 42.5 days by 2025 due to improved air quality.In addition,if the Chinese government outperforms the planned air quality target,as it usually does,the gains would increase to 65.4 days,~18% of the“Healthy China”life expectancy increment task.Further reductions in PM_(2.5) concentration would lead to accelerated gains in life expectancy both nationally and at the city level,providing strong incentives for the authorities to keep improving air quality.This study reveals the notable benefits on individual life that could be expected from air quality improvement in China and suggests that longer life expectancy is achievable by implementing a health-prioritized air quality management mechanism.