Article Text

Original research
Temporal trend of population structure, burden of diseases, healthcare resources and expenditure in China, 2000–2019
  1. Zhenguo Liang1,
  2. Dongze Wu1,2,
  3. Cui Guo3,4,
  4. Jieruo Gu1
  1. 1Department of Rheumatology, Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China
  2. 2Department of Rheumatology and Immunology, Sichuan Provincial People's Hospital, Chengdu, Sichuan, China
  3. 3Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China
  4. 4Department of Urban Planning and Design, Faculty of Architecture, The University of Hong Kong, Hong Kong SAR, China
  1. Correspondence to Dr Jieruo Gu; gujieruo{at}mail.sysu.edu.cn

Abstract

Objectives To explore the evolutionary trend of population structure, disease burden, healthcare resources and expenditure in China, and to identify key domains that are most in need of intervention.

Design A cross-sectional and longitudinal analysis.

Data source Population and healthcare data from China Statistical Yearbook, and disease burden attributable to causes and risk factors from the Global Burden of Diseases between 2000 and 2019.

Measures and methods We used the Joinpoint Regression Program to measure trends in population composition, population change, dependency ratio, healthcare institution, personnel, expenditure and disease burden from 2000 to 2019.

Results Regarding the population in China between 2000 and 2019, a decreasing trend was observed among youth aged 0–14 years (average annual percent change (AAPC): −1.17), a slow rising trend was observed among individuals aged 15–64 years (AAPC: 1.10) and a rapidly increasing trend was observed among individuals older than 65 years (AAPC: 3.67). Astonishing increasing trends in healthcare institutions (AAPC: 3.97), medical personnel (AAPC: 3.26) and healthcare expenditures (AAPC: 15.28) were also observed. Among individuals younger than 70 years, neoplasms (AAPC: 0.54) and cardiovascular diseases (AAPC: 0.67) remained among the top three causes, while tobacco (AAPC: 0.22) remained a top three risk factor. However, while musculoskeletal disorders (AAPC: 1.88) were not a top three cause in 2000, they are a top three cause in 2019.

Conclusion Comprehensive age/cause/risk factor-specific strategies are key to reconcile the tension among the triad of population ageing, disease burden and healthcare expenditure. The disease burden from cardiometabolic diseases, neoplasms and musculoskeletal disorders was identified as key domains that require intervention to reduce an increasing disease burden among individuals currently older than 70 years, as well as those approaching this age group.

  • Health economics
  • Health policy
  • Health & safety

Data availability statement

Data are available in a public, open access repository. Data used for the analyses are publicly available from the Institute of Health Metrics and Evaluation (https://ghdx.healthdata.org/gbd-2019;https://ghdx.healthdata.org/gbd-2019/data-input-sources) and the National Bureau of Statistics of China (https://data.stats.gov.cn/english/index.htm;http://www.stats.gov.cn/tjsj/ndsj/2020/indexeh.htm).

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STRENGTHS AND LIMITATIONS OF THIS STUDY

  • This study is the first to comprehensively characterise the patterns and temporal trends in population structure and composition, health resources and expenditures, life expectancy and disease burden in China from 2000 to 2019.

  • This study does not only provide an overview of population, healthcare and disease burden in China, but also inform the policymakers to pay more attention to the increasing age-driven disease burden in older population.

  • Although data from the Global Burden of Disease and China Statistical Yearbook are well refined, the quality of the data source needs to be further improved.

  • The principal limitations of this study are the unavailability of provincial-level data in disease burden, population and healthcare, and inability to provide granular policy recommendation.

Introduction

Together with the world’s population, people in China struggle against cancer and ageing despite efforts to extend lifespan and maximise healthspan.1 2 Since 1950, the lifespan at birth has been extended to 26 years in China, while the total fertility rate has decreased from 5.91 to 1.43.3 Between 2000 and 2019, the life expectancy for males has increased from 69.1 to 74.4 years, while the life expectancy for females has increased from 73.9 to 80.8 years.3 It has been forecasted that China will become the largest economy by 2035, and that the population in China will decline by 48.0% from 2017 to 2100.4 Moreover, in the next 20 years, the universal two-to-three-child policy may not reverse a shrinking workforce and rapid population ageing, especially in rural areas.5 6 In 2009, China expanded its social health insurance coverage to its entire population and reformed its healthcare delivery system.7 8

Healthcare systems coordinate complex inter-relationships among individuals who receive and provide medical financial support.9 It would have been difficult for China to rigorously control the two pandemics that occurred in 2003 and 2019 without a healthcare system. In particular, an increasing number of modernised medical institutions and well-educated personnel have been established over the past two decades in China.10 11 Accelerating rural-to-urban migration and corresponding increases in urban populations have also both led to improved access to healthcare, although substantial health risks can accompany changes in human activities, diets and social structures.12 Although two Global Burden of Diseases (GBD) studies have assessed the disease burden and risk factor at provincial level in China,13 14 this study further evaluates healthcare professionals and expenditure and identifies key domains to mitigate the age-driven disease burden.

The ageing society in China continues to exacerbate the burden borne by current family and public healthcare systems, which make it necessary to make long-term strategic plans to respond to the pressures of an ageing society at the governmental, individual and technological level.15 There are very low spatial and temporal matching degrees between the ageing population rate and the number of medical resources per thousand residents in China, and the geographical pattern of the temporal matching between them exhibited a feature of north–south differentiation.16 China does not have a typical disease characteristic of an ageing society comparing the characteristics of the ageing population in China with those in the world.17 Namely, China faces the dual threat of non-communicable diseases (NCDs) and communicable diseases, and the former account for most of the age-related disease burden. Although there are a great number of studies centring on trend of population, burden of disease and healthcare in China, they failed to dissect the implication of a central tension among three mutually conflicting forces: intractable disease burden, population ageing and upsurging healthcare expenditure. This study tries to find a solution to reconcile the three contradictory forces, achieving longer healthy lifespan in the ageing society at high-cost performance of health expenditure. Possible driving forces of disease burden among ageing populations were also examined to provide a basis for targeted interventions, such as early disease prevention and health management among older populations.

Methods

Data sources

The National Bureau of Statistics (NBS) of China annually publishes the China Statistical Yearbook (CSY).18 The Department of Population and Employment Statistics of the NBS conducts statistical population surveys as follows. A national population census is conducted in years ending with 0; a national 1% population sample survey is conducted in years ending with 5 and sample surveys on population changes are conducted in the remaining years. The latter covers about one per thousand of the total population of China. The sample surveys on population change take the entire nation of China as the population, while each province, autonomous region or municipality represents a subpopulation. A stratified multistage systematic probability-proportional-to-size cluster sampling scheme is used. Data regarding population, healthcare institutions, personnel, beds and health expenditures are described in detail in the online supplemental appendix (including a glossary).

The GBD 2019 study assessed life expectancy, disease burden, risk factor, aetiology and impairment.3 19 20 All-cause incidence, prevalence, death, years lived with disability, years of life lost, disability-adjusted life years (DALYs) and attributable risk factors were assessed between 1990 and 2019. The study identified 22 level 2 leading causes and 20 level 2 leading risk factors. Both causes and risk factors were assessed according to number, rate and age-standardised rate of DALYs. The estimation methods and data for burden of disease published in GBD 2019 were used to assess disease burden in China between 2000 and 2019 for the present study.

Aggregated data of population and healthcare from CSY and aggregated data of life expectancy, disease burden attributable to 22 causes or 20 risk factors from GBD between 2000 and 2019 were used to quantify temporal trend of population structure, burden of diseases, healthcare resources and expenditure in China.

Outcomes of measurements

The primary outcomes are temporal trend in population (population composition, population change, dependency ratio), healthcare (number of healthcare institutions, number of health personnel, healthcare expenditure), life expectancy (healthy and total), disease burden attributable to 22 causes or 20 risk factors (DALYs) from 2000 to 2019. The secondary outcomes are (1) the main drivers of disease burden from 22 causes or 20 risk factors in individuals younger and older than 70 years; and (2) temporal trend in population, healthcare and disease burden attributable to 22 causes or 20 risk factors from 2000 to 2009, and from 2010 to 2019. Driver refers to the cause or risk factor that has the greatest impact on the total disease burden attributable to 22 causes or 20 risk factors from 2000 to 2019.

Age groups of population and disease burden

Two sets of age group were used to specifically assess the trend of population composition and disease burden. Population composition (0–14, 15–64, 65+ years) and dependency ratio (gross, children, old) were used to reflect the trend of working population and population ageing as age 0–14, 15–64 and 65+ group were younger population, working population, post-working population, respectively. The analysis of disease burden in population younger and older than 70 years aimed to identify the cause or risk factor (driver) which has the greatest impact on the trend of disease burden attributable to 22 causes and 20 risk factors from 2000 to 2019. The cut-off point of age 70 years was chosen because women in 164 and men in 165 of 186 countries and territories had a higher probability of dying before 70 years of age from an NCD than from communicable, maternal, perinatal and nutritional conditions combined according to NCD Countdown 2030.19 21

Statistical analysis

The population composition, change, dependency ratio, healthcare institution, personnel, and expenditures in terms of number, disease burden and risk factors in terms of number and rate were assessed by using a Joinpoint regression model. The disease burden and risk factor in individuals younger and older than 70 years in terms of number and rate were also assessed to identify the driving causes and risk factors. Average annual per cent change (AAPC) and associated 95% CIs were calculated for the study period. Temporal increasing and decreasing trends were defined according to the statistical significance of the AAPC compared with 0. AAPC values with 95% CIs overlapping with 0 were considered stable. Two segmented line regressions with joinpoint of 2000, 2009, and 2019 were calculated to show the temporal trend from 2000 to 2009, and from 2010 to 2019. All statistical analyses were performed by using the Joinpoint Regression Program (V.4.8.0.1, Statistical Methodology and Applications Branch, Surveillance Research Program, National Cancer Institute, Bethesda, Maryland, USA). P values less than 0.05 were considered statistically significant at a two-tailed level.

Patient and public involvement

Patients and the public were not involved in any way in this research.

Results

Population trends between 2000 and 2019

Initially, temporal trends of the population structure in China were examined based on CSY data in terms of gender and age composition, birth rate and dependency ratio. From 2000 through 2019, an increasing trend in total population (AAPC: 0.52, 95% CI: 0.51 to 0.54), male population (AAPC: 0.47, 95% CI: 0.44 to 0.51) and female population (AAPC: 0.59, 95% CI: 0.56 to 0.62) was observed. As expected, a strikingly contrasting trend in urban population (AAPC: 3.28, 95% CI: 3.18 to 3.38) and rural population (AAPC: −1.98, 95% CI: −2.02 to −1.95) was observed. We further identified that an increasing trend in urban population was attenuated, while a decreasing trend in rural population was aggravated, during 2010–2019 compared with 2000–2009 (figure 1A and table 1).

Figure 1

Temporal trends of population in China between 2000 and 2019. Temporal trends of population composition are presented according to gender and area (A), age group (B), birth rate, death rate, and natural growth rate (C), and gross ratio, children ratio, and old dependency ratio (D).

Table 1

The average annual per cent change (AAPC) in population composition, change and dependency ratio between 2000 and 2019

A clear decreasing trend in the younger population (ages 0–14 years) was observed in 2000–2019 (AAPC: −1.17, 95% CI: −1.78 to −0.55), especially in 2000–2009. An increasing trend in the working population (ages 15–64 years) was observed in 2000–2009 (AAPC: 1.10, 95% CI: 1.03 to 1.18), and then it gradually disappeared over 2010–2019. In contrast, an increasing trend in the post-working population (65+ years) that was observed in 2000–2019 (AAPC: 3.67, 95% CI: 3.51 to 3.82) gradually intensified from 2000–2009 to 2010–2019 (figure 1B and table 1).

From 2000 to 2019, the birth rate (AAPC: −1.53, 95% CI: −2.31 to −0.75) and natural growth rate (AAPC: −4.20, 95% CI: −5.52 to −2.87) continued to decrease. Conversely, from 2000 to 2009, the death rate continued to increase (AAPC: 1.10, 95% CI: 0.75 to 1.46), yet from 2010 to 2019, it remained stable (AAPC: 0.03, 95% CI: −0.06 to 0.13) (figure 1C and table 1). The past two decades also exhibited a reverse trend in gross dependency ratio from 2010 to 2019, a muted decreasing trend in children dependency ratio from 2000–2009 to 2010–2019, and a strengthened increasing trend in old dependency ratio from 2000–2009 to 2010–2019 (figure 1D and table 1).

Health resources and expenditure between 2000 and 2019

Temporal trends in health sources, including institutions, personnel and expenditures, were examined based on CSY data. A consistent increasing trend in number of hospitals (AAPC: 3.97, 95% CI: 3.69 to 4.24), including general hospitals, hospitals that specialise in traditional Chinese medicine and specialised hospitals, was observed. The number of medical personnel (AAPC: 3.26, 95% CI: 2.76 to 3.77), including medical technical personnel, licensed assistant doctors, licensed doctors and registered nurses, also continued to increase in 2000–2019. Moreover, the rate of increasing number of medical personnel was higher in 2010–2019 than in 2000–2009. The number of beds in healthcare institutions (AAPC: 5.54, 95% CI: 5.20 to 5.88), including hospitals, township health service centres, specialised public health institutions, and women and children care agencies, also increased in 2000–2019. Like medical personnel, the rate increase for beds in healthcare institutions was greater in 2010–2019 than in 2000–2009 (table 2).

Table 2

The average annual per cent change (AAPC) in healthcare institution, personnel and expenditures between 2000 and 2019

Total healthcare expenditure increased from ¥458.66 billion (US$55.40 billion) in 2000 to ¥6584.14 billion (US$954.68 billion) in 2019, with an AAPC of 15.28 (95% CI: 14.64 to 15.91). The per capita health expenditure increased from ¥361.88 in 2000 to ¥4702.79 in 2019, with an AAPC of 14.67 (95% CI: 14.04 to 15.30). Striking increasing trends in government health expenditure (AAPC: 18.95, 95% CI: 16.72 to 21.22), social health expenditure (AAPC: 19.03, 95% CI: 17.56 to 20.52) and out-of-pocket health expenditure (AAPC: 10.62, 95% CI: 9.24 to 12.02) were also observed in 2000–2019 (table 2).

Population health, disease burden and risk factors between 2000 and 2019

According to data from GBD 2019, life expectancy at birth and at 60–64 years was estimated to increase (AAPC: 0.44, 95% CI: 0.43 to 0.46; AAPC: 0.76, 95% CI: 0.60 to 0.91, respectively). In addition, the percentage of healthy life expectancy within total life expectancy at birth and at 60–64 years decreased from 88.90 to 88.32, and from 77.12 to 76.36, respectively (online supplemental figure 1 and tables 1–3). Overall, the number of all-cause DALYs was stable during 2000–2019 (AAPC: 0.08, 95% CI −0.06 to 0.22). However, it decreased between 2000 and 2009 (AAPC: −0.44, 95% CI: −0.58 to −0.31), and it increased between 2010 and 2019 (AAPC: 0.60, 95% CI: 0.39 to 0.82) (online supplemental table 4).

In 2000, the top three causes of DALYs were cardiovascular diseases, neoplasms and chronic respiratory diseases. In 2019, they were cardiovascular diseases, neoplasms and musculoskeletal disorders. From 2000 to 2019, the top three drivers of increasing number of DALYs were HIV/AIDS and sexually transmitted infections (AAPC: 3.47, 95% CI: 2.72 to 4.22), diabetes and kidney diseases (AAPC: 2.30, 95% CI: 2.09 to 2.51), and sense organ diseases (AAPC: 2.14, 95% CI: 1.98 to 2.30). The top two drivers of increasing age-standardised rate of DALYs were HIV/AIDS and sexually transmitted infections (AAPC: 2.02, 95% CI: 1.50 to 2.53) and musculoskeletal disorders (AAPC: 0.16, 95% CI: 0.10 to 0.23) (online supplemental table 5).

In 2000, the top three risk factors were tobacco, air pollution and high systolic blood pressure. In 2019, they were tobacco, high systolic blood pressure and dietary risks. Between 2000 and 2019, the top three leading risk factors with the largest increasing number of DALYs were high body mass index (AAPC: 4.02, 95% CI: 3.74 to 4.29), low physical activity (AAPC: 3.54, 95% CI: 2.70 to 4.38) and low bone mineral density (AAPC: 3.39, 95% CI: 3.12 to 3.67). The top three leading factors with the largest increase in age-standardised rate of DALYs were unsafe sex (AAPC: 1.47, 95% CI: 0.88 to 2.06), high body mass index (AAPC: 1.28, 95% CI: 0.95 to 1.60) and low bone mineral density (AAPC: 0.40, 95% CI: 0.27 to 0.54) (online supplemental table 6).

Trends in disease burden between younger individuals and those older than 70 years

Finally, trends in causes and risk factors for the population with a cut-off point of 70 years were examined for 2000–2019. Among individuals younger than 70 years, musculoskeletal disorders replaced other NCDs as one of the top three causes from 2000 to 2019. In contrast, the top three causes remained the same among individuals older than 70 years, and included cardiovascular diseases, neoplasms and chronic respiratory disease (table 3). Among the population younger than 70 years, the causes with the largest increment in number of DALYs were HIV/AIDS and sexually transmitted infections (AAPC: 3.33, 95% CI: 2.58 to 4.08), musculoskeletal disorders (AAPC: 1.88, 95% CI: 1.84 to 1.92) and sense organ diseases (AAPC: 1.71, 95% CI: 1.43 to 2.00). In the same population, the largest increments in rate of DALYs were HIV/AIDS and sexually transmitted infections (AAPC: 3.42, 95% CI: 2.76 to 4.09), musculoskeletal disorders (AAPC: 2.04, 95% CI: 2.00 to 2.08), and diabetes and kidney diseases (AAPC: 1.88, 95% CI: 1.58 to 2.18). In comparison, the causes among individuals older than 70 years that had the largest increment in both number and rate of DALYs were maternal and neonatal disorders (AAPC: 10.64, 95% CI: 10.47 to 10.82; AAPC: 6.84, 95% CI: 6.69 to 6.98, respectively), HIV/AIDS and sexually transmitted infections (AAPC: 8.17, 95% CI: 6.93 to 9.43; AAPC:4.39, 95% CI: 3.26 to 3.53, respectively) and unintentional injuries (AAPC: 4.66, 95% CI: 3.90 to 5.43; AAPC: 1.01, 95% CI: 0.46 to 1.56, respectively) (table 3).

Table 3

The average annual per cent change (AAPC) of 22 causes in people younger and older than 70 years of age presented in disability-adjusted life years

Among the population younger than 70 years, dietary risks (AAPC: 1.02, 95% CI: 0.85 to 1.19) and high systolic blood pressure (AAPC: 1.55, 95% CI: 1.29 to 1.81) replaced air pollution and child and maternal malnutrition in the top three risk factors from 2000 to 2019. In contrast, the top three risk factors remained the same between 2000 and 2019 for the population older than 70 years, and they include: high systolic blood pressure, tobacco and air pollution (table 3). Regarding risk factors among the population younger than 70 years, the largest increments in number and rate of DALYs were high body mass index (AAPC: 3.70, 95% CI: 3.59 to 3.82; AAPC: 3.88, 95% CI: 3.69 to 4.07, respectively), unsafe sex (AAPC: 3.11, 95% CI: 2.80 to 3.42; AAPC: 3.28, 95% CI: 2.96 to 3.60, respectively) and low physical activity (AAPC: 2.75, 95% CI: 2.34 to 3.15; AAPC: 2.91, 95% CI: 2.46 to 3.36, respectively). In contrast, the risk factors with the largest increment in number of DALYs among those older than 70 years were high body mass index (AAPC: 5.22, 95% CI: 4.79 to 5.65), low bone mineral density (AAPC: 5.22, 95% CI: 4.98 to 5.46) and high low-density lipoprotein (LDL) cholesterol (AAPC: 5.02, 95% CI: 4.62 to 5.41). Furthermore, the same risk factors with different rankings were observed in terms of rate of DALYs for the same population: low bone mineral density (AAPC: 1.62, 95% CI: 1.38 to 1.86), high body mass index (AAPC: 1.50, 95% CI: 1.01 to 2.00) and high LDL cholesterol (AAPC: 1.44, 95% CI: 1.04 to 1.84), respectively (table 4).

Table 4

The average annual per cent change (AAPC) of 20 risk factors in people younger and older than 70 years of age

Discussion

In the past two decades, although China invested hugely on health institution, personnel and expenditures to extend life expectancy and improve healthy life expectancy, population structure deteriorated, the total disease burden remained largely unchanged and age-driven disease burden continuously intensified. The trends we observed in the population structure of China highlight the potential for an irreversible population decline to occur before the household wealth of G7 nations is achieved in China. Despite easing of birth limits in China, couples have been put off by high costs of living, expensive childcare, career choices and maternity leave. In addition, the post-working population has been increasing at an accelerating rate, suggesting a clear deterioration in population structure and ageing.19 Thus, the ability of China to ease strains on its ageing population in the next 30 years is a pressing concern.22

On the one hand, continuous effort is needed to address the top three causes and risk factors which have been identified among the population in China between 2000 and 2019. Our findings show that neoplasms and cardiovascular diseases remain among the top three causes, and tobacco remains among the top three risk factors for individuals younger than 70 years. Comprehensive regional-specific strategies, including effective tobacco control policy, recommendations for healthier lifestyles and control of chronic infections, are needed as the cancer spectrum in China is changing from that of a developing country to that of a developed country.23 24 Regulatory reforms also need to further reduce the lag between approval of new cancer drugs by the US Food and Drug Administration and their subsequent approval in China, and they need to facilitate the development and registration of drugs that may have clinical superiority over existing drugs.25 Turning the inverted pyramid of the healthcare system is essential for the battle against cardiovascular diseases due to the increasing number of older patients, the high proportion of out-of-hospital deaths, and the gaps in lifestyle indicators between what is preferred and what is currently observed.26 27 All provinces in mainland China have made great progress in increasing life expectancy at birth. Life course management of disease across the entire spectrum of healthcare services has led to a shift from a patient-centred and treatment-dominated model to a people-centred and health-centred model. It is hypothesised that the latter may help to integrate preventive and treatment measures for cardiovascular disease.28 Tobacco sales have also increased despite a tight anti-smoking policy in China. Potential interference from the tobacco industry and the social currency of tobacco are suspected to be factors.29–31 Therefore, great efforts should be taken not only to minimise these practices, but also to slow tobacco production.32

On the other hand, it is crucial to focus on incremental driving causes and risk factors in the early stages to mitigate future age-driven disease burden. Our data show that musculoskeletal disorders, dietary risks and high systolic blood pressure are among the top three causes and risk factors in people younger than 70 years. Split analyses were performed to examine variations according to age, and a cut-off point of 70 years was used because ischaemic heart disease and stroke were the top-ranked causes of DALYs in the population aged 70 years and older.19 A previous study quantified the temporal trends in disease burden of musculoskeletal disorders which could be attributed to changes in risk factors.27 The results obtained support population-wide initiatives which target high body mass index to help mitigate the burden of musculoskeletal disorders.33 Changes in diets to correct for urbanisation-driven dietary shifts to higher consumption of refined sugars, refined fats, oils and meats may also help prevent diet-related and chronic NCDs.34 With resources available to control high systolic blood pressure and reduce the burden of hypertension, efforts are needed to improve access to better antihypertensive medications and to implement artificial intelligence-based digital health.35 36

We identified key domains that require intervention in order to reduce an increasing disease burden among individuals older than 70 years. Most importantly, the top three causes and risk factors for this age group remained unchanged. Thus, our findings indicate that greater effort is needed to tackle the rapidly increasing age-standardised rate of DALYs due to traditional major risk factors, including high body mass index, low bone mineral density and high LDL cholesterol. Moreover, the increasing burden of maternal and neonatal disorders, HIV/AIDS and sexually transmitted infections, and unintentional injuries needs to be highlighted as well.

Healthcare for older individuals is undergoing unprecedented challenges due to underprepared geriatric hospitals and nursing homes, an unbalanced healthcare insurance system between urban and rural areas, and an absence of education on national ageing and post-working health.22 Consequently, there is an urgent need to identify traits in older people who experience short healthspan. By identifying healthy behaviours and casual genetic and metabolic factors of the latter, it may be possible to decrease the burden of late-life diseases and extend healthspan.37 The development of long-term health systems to meet the needs of older individuals in an age-friendly environment is fundamental to fostering healthy ageing and maximising the functional abilities of older individuals.38

Healthcare has experienced an upsurge regarding medical institutions, personnel, beds and expenditures. Our findings clearly demonstrate that China has increased its health spending much faster than its economic growth. In 2018, China provided $644.7 million for the development of health assistance.39 This trend in increasing healthcare expenditures will be further aggravated considering the high costs related to chronic illnesses, population growth and ageing in the USA.9 40 While China has reformed its primary healthcare system to insure its population,7 41 improving the quality of primary healthcare and increasing reimbursement for chronic NCDs are key steps to alleviating national disease burden.42 43 In addition, the cost-effectiveness of health expenditures on disease burden and targeting the poor should be primary considerations in public health policy given the limited financial resources for health.44

Limitation of this study

It must also be noted that there were several limitations associated with the present study. First, our findings might be biased by changes in the age structure of the population and different populations over a specified period because temporal trends in population and healthcare utilisation were not quantified in terms of age-standardised rate. Second, population and healthcare data from CSY 2020 were combined with modelled disease burden data from GBD 2019 based on an assumption that these two sources of data are consistent. Third, the most recent trends could not be captured due to time lags in data release by the NBS of China and GBD studies. Fourth, all the limitations of the GBD methodology described elsewhere3 19 20 could have potentially affected the present study. Fifth, owing to the nature of the data and methods from CSY, we are currently unable to parse population estimates into more narrow age groups and provide deflator-adjusted health expenditure data. National-level data were collected and analysed, and therefore, within-country variations were not considered.

Conclusion

Comprehensive age/cause/risk factor-specific strategies are key to reconcile the tension among the triad of population ageing, disease burden and healthcare expenditure. The disease burden from cardiometabolic diseases, neoplasms and musculoskeletal disorders was identified as key domains that require intervention to reduce an increasing disease burden among individuals currently older than 70 years, as well as those approaching this age group.

Data availability statement

Data are available in a public, open access repository. Data used for the analyses are publicly available from the Institute of Health Metrics and Evaluation (https://ghdx.healthdata.org/gbd-2019;https://ghdx.healthdata.org/gbd-2019/data-input-sources) and the National Bureau of Statistics of China (https://data.stats.gov.cn/english/index.htm;http://www.stats.gov.cn/tjsj/ndsj/2020/indexeh.htm).

Ethics statements

Patient consent for publication

Ethics approval

Data released from the Global Health Data Exchange query and the China Statistical Yearbook did not require informed patient consent. This study used an anonymised publicly available dataset with no identifiable information of the survey participants. Thus, ethics approval was not required for this study.

References

Supplementary materials

  • Supplementary Data

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Footnotes

  • ZL, DW and CG contributed equally.

  • Contributors Prof. JG is the guarantor of the study and had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. ZL, DW, CG and JG conceived and designed the study, performed the analysis, and wrote the paper. All authors read and commented on the manuscript and approved the final version of the manuscript. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

  • Funding Project funded by China Postdoctoral Science Foundation (2020TQ0380) and Guangdong Clinical Research Center of Immune Disease (2020B1111170008). The Global Burden of Disease Study is funded by the Bill and Melinda Gates Foundation.

  • Disclaimer The funder was not involved in the preparation of this manuscript.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.