JPH JMIR Public Health Surveill JMIR Public Health and Surveillance 2369-2960 JMIR Publications Toronto, Canada v8i11e35785 36394944 10.2196/35785 Original Paper Original Paper Patterns of HIV or AIDS Mortality Among Older People From 1990 to 2019 in China: Age-Period-Cohort Analysis Eysenbach Gunther Qin Qianqian Park Jun Ren Ningjun MPH 1 https://orcid.org/0000-0003-3339-0511 Li Yuansheng MPH 1 https://orcid.org/0000-0002-1174-3374 Wan Zhengwei PhD 2 https://orcid.org/0000-0002-4239-0882 Wang Ruolan MPH 1 https://orcid.org/0000-0002-3948-4220 Zhang Wenxin MPH 1 https://orcid.org/0000-0001-8249-382X Dzakah Emmanuel Enoch PhD 3 https://orcid.org/0000-0002-7475-6420 Zhang Junhui PhD 1 https://orcid.org/0000-0001-6166-1601 Li Ailing MSc 1 https://orcid.org/0000-0001-9650-8236 Fan Song PhD 1
School of Public Health Southwest Medical University No.1, Section 1, Xianglin Road Longmatan District Luzhou, 64600 China 86 8303175813 fansong@swmu.edu.cn
https://orcid.org/0000-0002-2228-5401 School of Public Health Southwest Medical University Luzhou China Department of Health Management Center & Institute of Health Management, Sichuan Provincial People's Hospital University of Electronic Science and Technology of China Chengdu China Department of Molecular Biology and Biotechnology, School of Biological Sciences College of Agriculture and Natural Sciences University of Cape Coast Cape Coast Ghana Corresponding Author: Song Fan fansong@swmu.edu.cn 11 2022 17 11 2022 8 11 e35785 21 12 2021 10 5 2022 29 5 2022 23 10 2022 ©Ningjun Ren, Yuansheng Li, Zhengwei Wan, Ruolan Wang, Wenxin Zhang, Emmanuel Enoch Dzakah, Junhui Zhang, Ailing Li, Song Fan. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 17.11.2022. 2022

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on https://publichealth.jmir.org, as well as this copyright and license information must be included.

 Background

With the increasing effectiveness of antiretroviral therapy and shifting demographics, the problem of older people with HIV or AIDS is increasingly grim in China, and neglecting infection among them may cause more serious social problems, exacerbate the difficulty of controlling HIV or AIDS transmission, and increase the risk of death.

 Objective

We investigated the variations in the trends of Chinese mortality by age, period, and cohort, from 1990 to 2019, to reveal the relationship between age, period, cohort, and HIV burden, as well as providing guidance for resource allocation to prevent HIV-related deaths in vulnerable target populations.

 Methods

We extracted the HIV or AIDS mortality data from the Global Burden of Disease. The joinpoint regression model was applied to detect changes in HIV or AIDS trends. The age-period-cohort model was used to explore the age, period, and cohort effects.

 Results

The trends in age-standardized mortality rates in HIV or AIDS were increased in both genders, from 0.50 to 4.54/105 individuals for males, and from 0.19 to 1.43/105 individuals for females. Joinpoint regression model showed the average annual percentage change of age-standardized mortality rates was 7.0 for male and 6.4 for female individuals, showing an increasing trend. The age effect of male HIV or AIDS mortality showed a net increase of 0.59 (–0.21 to 0.38) from the ages 50-79 years. There is a gradual upward trend in the change in risk of death from HIV or AIDS for the period effect among the older population, lowest at ages 50-54 years (–0.80 for male and –0.78 for female individuals) and highest at ages 75-79 years (0.86 for male and 0.69 for female individuals). The variation of cohort effects was complex, but both genders had a nearly consistent tendency; people born in 1920-1929 had the lowest cohort effect, and those born in 1950-1954 had the highest values.

 Conclusions

Our study showed a marked rise in HIV mortality for both genders in China from 1990 to 2019. Aging is an important issue in current HIV prevention and control. There is an urgent need to promote HIV testing and health education. Our findings will help predict future HIV or AIDS mortality changes and identify age-specific priority populations for intervention.

 HIV AIDS aging mortality trends age-period-cohort model APC Introduction

HIV and AIDS have been prevalent in China for more than 30 years since the first case of HIV was reported in 1985 [1]. Due to the substantial number of deaths attributed to the virus, HIV or AIDS has become the most severe notifiable infectious disease accounting for the most deaths, over 18,819, in 2020 in China [2]. With the increasing effectiveness of antiretroviral therapy (ART), people with HIV are living longer [3], and HIV or AIDS has transformed from a near-uniformly fatal infection to a chronic condition [4]. As a result, some estimates indicate that nearly 50% of persons with HIV in the United States are aged 50 years and older [5]. The situation of AIDS among older people in Europe is far from satisfactory, with estimates from some European countries predicting a “silver tsunami” within the HIV community, mirroring that of the general population, with those aged 50 years or older accounting for nearly 70% of people with HIV by 2030 [6-8]. Overlooking the risk of HIV or AIDS infection among older people is a mistake. The public perception that older people were not susceptible to HIV or AIDS infection, coupled with the lack of proper sexual education [9], exacerbates HIV among the older people. This problem is increasingly grim in China.

Furthermore, previous studies mainly focused on the age distribution of morbidity or mortality, with few studies considering both time and cohort effects [10,11]. However, period effects are also crucial in influencing the onset of disease. Period effects can also be understood as the role of social and epidemiological conditions in influencing some events, including policies, medical technology, screening tools, and even disease classification criteria. Tarone et al [12] found that the rise in the incidence of breast cancer in North America in the 1980s was due to the mass use of diagnostic mammography techniques, which increased diagnostic accuracy and thus the incidence of breast cancer. Ma et al [13] and Zhang et al [11] noted that the “Four Free and One Care” policy enacted in mainland China, which expanded HIV or AIDS screening and increased attention to HIV or AIDS, led to an increase in the incidence of HIV or AIDS and a decrease in the death rate.

Moreover, the cohort effect is because people in the same birth cohort will experience the same events at the same age. Birth cohorts that experience different events at different stages of their life course have different levels of exposure to economic, behavioral, policy, and environmental risks. Nevertheless, trends in Chinese HIV or AIDS deaths by age, among older people, remain unclear, as does the relative risk due to time and cohort effects [14]. The age-period-cohort (APC) model analyzes the age, period, and cohort effect for a comprehensive analysis to clarify the answers to these questions. This study examined elderly HIV or AIDS mortality trends by age, period, and cohort. A statistical analysis of the HIV or AIDS mortality of 50-79 years old in China from 1990 to 2019 was performed. Those effects were estimated by the APC model combined with the Intrinsic Estimator (IE) algorithm [15].

Studying HIV or AIDS mortality trends in older Chinese may reveal new information about the risk factors associated with HIV or AIDS. The finding reveals the relationship between age-period-cohort, on the one hand, and HIV or AIDS burden, on the other. It also provides guidance for resource allocation to prevent HIV-related deaths in vulnerable target populations.

 Methods

China’s HIV or AIDS mortality data were extracted from the Institute for Health Metrics and Evaluation. To examine temporal trends in HIV (coded in the International Classification of Diseases, 10th Revision) mortality over the past 30 years, we used data from the Institute for Health Metrics and Evaluation, an independent global health research center at the University of Washington in the United States. Many scientists from dozens of countries around the world wrote the Global Burden of Diseases (GBD) Injuries and Risk Factor Study (GBD 2019 [16]), which used the Bayesian disease modeling meta-regression to collect data comprehensively and accurately [17]. To standardize the mortality of different observation ages, we collected the population data of each age group from the Statistical Yearbook of Population and Employment of China from 1990 to 2019. Elderly HIV or AIDS was defined according to the United Nations program on HIV or AIDS (UNAIDS) “AIDS and aging” standards [18,19].

For the requirements of the APC model, we divided the age range of 50-79 years into 6 age groups at intervals of 5 years. Individuals younger than 50 years and older than 80 years were ruled out (>80 years old already exceeds life expectancy per capita in China, and the inclusion of a population with a complex cause of death and high mortality from reduced resistance may affect the accuracy of the model). Since the purpose of our study was aimed at older patients with HIV or AIDS, after excluding Chinese patients with HIV or AIDS who are younger than 50 years and older than 79 years, the data used in our study were from the age groups of 50-54 years old to 75-79 years old. The time range of data was from 1990-2019 (with 5 years per period) for computing the age-standardized mortality rates (ASMR) and period mortality rates.

The APC models represent a classic epidemiological approach for extracting historical morbidity and mortality risk changes from cross-sectional data, termed the cohort effect [20]. As there is a linear relationship between the age, period, and cohort, it is difficult to estimate the unique setting for every age, period, and cohort effect, referred to as the unidentification problem [21,22]. Many statistical analysis algorithms were designed to solve the unidentification problem [23-26]. Fu [15,27] applied the estimable functions and the singular value decomposition of matrices to approach the estimator of the APC model, which is the most effective for the unidentification problem, named the IE.

Finally, we described the magnitude of the rates as a function of age (a), period (p), and birth cohort (c) using a log-linear model, with Poisson distribution and with the log of the person-years at risk defined as an offset of the IE method. Dap indicates the number of incidences in the “a” age group in the “p” period; Pap denotes the total number of persons in the age group “a” in period “p.”

In this paper, the joinpoint regression models were performed by the Joinpoint Regression Program (version 4.3.1.0), and the age-period-cohort model analyses and graphs were conducted using APC fit in R, version 3.6.0 (R foundation for Statistical Computing). Fitting deviance, R2, and adjust R2 were used to evaluate the model; the closer the value to 1, the better the test performance.

 Results Mortality of HIV or AIDS in Older Chinese People

In Figure 1, ASMR for HIV or AIDS by gender from 1990 to 2019 was shown. HIV or AIDS ASMRs showed increasing trends from 0.50 to 4.51/105 individuals for male and 0.19/105 to 1.45/105 for female populations, slightly decreasing after 2018. ASMR increased 8.91-fold for male and 7.31-fold for female populations over the past 30 years. Our results also indicated that the gap between the mortality rates for older male and female individuals was enormous, with a maximum of 3.36 times that of female individuals in 2013.

Trends in the HIV age-standardized mortality rates per 100,000 population by gender from 1990 to 2019 using the Statistical Yearbook of Population and Employment of China from 1990 to 2019 for the age-standardized population.

 HIV or AIDS Mortality Trend Variation in the Age, Period, and Cohort

The HIV or AIDS mortality trend variation among 50-79 years age groups of different genders in China between 1990 and 2019 is shown in Figure 2. Regardless of the period, almost all groups had insignificant changes, especially females. Only males between 2010-2014 and 2015-2019 groups showed increased HIV or AIDS mortality with age.

The variations in the HIV or AIDS mortality rates of different age groups during the decades from 1990-2019 are shown in Figure 3. There was a significant increase in HIV or AIDS mortality regardless of age or gender. The 75-79 years age groups showed the highest mortality rate (5.66/105) in males, and all groups of older males with AIDS had higher mortality rates than female groups. The male ASMR (5.66/105) was over 5 times more than that of the female groups（1.08/105）at ages 75-79 years from 2015-2019.

The effect of birth cohort on ASMR of HIV or AIDS among Chinese of different age groups is shown in Figure 4. The earlier the birth cohort, the higher the HIV or AIDS mortality rate. Across all cohorts, HIV mortality fluctuated more with the birth cohort, especially for males.

HIV mortality rates of different age groups (50-54 years old to 75-79 years old) in each period (1990-1994, 1995-1999, 2000-2004, 2005-2009, 2010-2014, and 2015-2019) are shown (male populations represented by blue lines and female populations by red).

Age-adjusted mortality rates of HIV-infected persons per 100,000 person-years among men and women by age groups, 1990-2019 (adjusted to the data of the 6th population census of China in 2010 as the standard population).

Age-specific HIV mortality in different Chinese cohorts aged over 50 years (per 100,000 people): HIV mortality rates of different age groups (50-54 to 75-79 years old) in each cohort (1915-1919, 1920-1924, 1925-1929, 1930-1934, 1935-1939, 1940-1944, 1945-1949, 1950-1954, 1955-1959, 1960-1964, and 1965-1969).

 Trends in the Joinpoint Regression Analysis Result

Table 1 shows the joinpoint regression analysis results of the changing trend of the death rate of patients with HIV or AIDS in China, whose age was older than 50 years in different genders, by age group during the observation period. The trends, size, and statistical significance of the mortality of HIV or AIDS in different age groups during different observation periods are described.

Over the monitoring period, trends in mortality in different age groups can be broadly divided by gender into 2 categories. Older male HIV or AIDS mortality increased over time in all age groups, with slight differences in the rate of increase between periods and mortality rates stabilizing after 2016 in most groups. All age groups saw the most significant increase from 2012 to 2016, with the 70-74 years age group exhibiting the highest APC of 30.3%, whereas the trend for older female individuals increased, then decreased, and increased again.

The first period of growth was roughly 1990-2004 with an APC of around 10%, whereas the 70-79 years age group grew by more than 15%. From 2004 to 2013, the HIV or AIDS mortality rate for older female groups decreased with an APC of around –4%. The second segment grew more significantly than the first. Similar to male groups, all APC was greater than 18% over the period 2013-2016, particularly among the 65-74 years age group, where the average annual percentage change was significant, more than 35%.

The trend in HIV mortality age-standardized mortality rates for the age>50 years in all genders during 1990-2019.

Cohort and age range Joinpoint regression analysis
Trend 1 Trend 2 Trend 3 Trend 4 Trend 5 AAPCa
year APCb year APC year APC year APC year APC (%) 95% CI
Male
adjusted 1990~2005 7.8c 2005~2013 2.2c 2013~2016 23.4c 2016~2019 0.4 —d — 7.0c (5.9~8.0)
50-54 years 1990~2002 10.7c 2002~2012 1.1 2012~2016 20.9c 2016~2019 2.4 — — 7.8c （6.6~8.9）
55-59 years 1990~2006 8.8c 2006~2013 –0.6 2013~2016 17.8c 2016~2019 4.3c — — 6.9c （5.7~8.0）
60-64 years 1990~2013 5.7c 2013~2016 20.1c 2016~2019 –4.0 — — — — 6.1c （4.9~7.2）
65-69 years 1990~2012 4.5c 2012~2016 23.6c 2016~2019 0.1 — — — — 6.5c （5.4~7.7）
70-74 years 1990~2001 12.2c 2001~2013 1.6c 2013~2016 30.3c 2016~2019 2.0 — — 8.3c （6.9~9.8）
75-79 years 1990~2010 8.3c 2010~2013 –3.3 2013~2016 18.1c 2016~2019 –3.3 — — 6.7c （5.1~8.4）
Female
adjusted 1990~2004 10.4c 2004~2013 –3.4c 2013~2016 25.9c 2016~2019 1.5 — — 6.4c (5.2~7.6)
50-54 years 1990~2004 10.8c 2004~2012 –4.9c 2012~2016 18.9c 2016~2019 2.3 — — 6.4c （5.2~7.5）
55-59 years 1990~2005 10.4c 2005~2013 –6.0c 2013~2016 19.4c 2016~2019 2.9 — — 5.7c （4.0~7.4）
60-64 years 1990~2005 9.0c 2005~2012 –4.2c 2012~2016 19.5c 2016~2019 –2.9 — — 5.8c （5.0~6.6）
65-69 years 1990~2002 9.8c 2002~2013 –1.0 2013~2016 35.7c 2016~2019 2.2 — — 7.1c （5.5~8.7）
70-74 years 1990~2001 16.9c 2001~2013 –2.8c 2013~2016 36.1c 2016~2019 7.4c — — 9.0c （7.0~11.2）
75-79 years 1990~1996 1.6 1996~2005 15.6c 2005~2013 –4.1c 2013~2016 18.6c 2016~2019 2.7 5.9c （3.7~8.1）

aAAPC: average annual percentage change.

bAPC: annual percentage change.

cIndicates that the APC and AAPC are significantly different from zero at the alpha=.05 level.

dNot applicable.

 APC Model Analysis Results of HIV or AIDS Mortality

In this study, by fitting the age-period-cohort model, the IE algorithm was used for quantitative analysis of China’s 1990-2019 elderly HIV or AIDS deaths among different age groups and periods. The result of the analysis of HIV or AIDS mortality is shown in Table 2 and Figure 5.

The age effect of male HIV or AIDS mortality showed a net increase of 0.59 (–0.21 to 0.38), from the age of 50-79 years; using the lowest value (55-59 years age group) of the male age effect as a reference, the highest value (75-79 years age group) is 1.81 times higher. The female population’s effect was more complex than that of males, with the maximum occurring in the 65-69 years age group, and the minimum in the 70-74 years age group with less fluctuation.

According to period effects, there is a significant upward trend in the risk of death from HIV or AIDS among older people of both genders. Female groups had a slight decline after 2005 and then an increase. The risk of death is lowest at ages 50-54 years (male: –0.80; female: –0.78) and highest at ages 75-79 years (male: 0.86; female: 0.69). If the 1990 male period group is used as a reference, the period effect of HIV or AIDS mortality in 2015 increased by 5.23. This shows that the risk of HIV or AIDS deaths among older Chinese males increased by 522.61% over 30 years. Meanwhile, using the 1990 female population as the reference group, the period risk of HIV or AIDS deaths among older Chinese female individuals increased by 441.83% over 30 years.

According to the analysis of cohort effects, the mortality rates of male and female individuals living with HIV or AIDS have almost identical trends with complex and fluctuating variations similar to waves. The 1920-1924 period had the lowest cohort effect (male: –0.29; female: –0.38) on mortality risk from HIV or AIDS. Using the male population’s lowest cohort effect (1920-1924) as a reference, the highest cohort effect risk (1950-1954) of death was 1.35. The female cohort effect has 2 peaks, occurring in cohorts 1950-1954 and 1965-1969. However, the cohort effects were not statistically different (P>.05; Table 2).

The age-period-cohort model analysis results of HIV mortality.

Cohort and age range Coefficient SE Pvalue Period Coefficient SE Pvalue Cohort Coefficient SE Pvalue
Malea
50-54b years –0.0798 0.0226 .003 1990-1994b –0.7965 0.0203 <.001 1915-1919b –0.1228 0.0466 .02
55-59b years –0.2136 0.0211 <.001 1995-1999b –0.3831 0.0218 <.001 1920-1924b –0.2915 0.0366 <.001
60-64b years –0.1692 0.0218 <.001 2000-2004b –0.1217 0.022 <.001 1925-1929 –0.0307 0.0328 .36
65-69 years –0.0264 0.0219 .25 2005-2009b 0.1332 0.0217 <.001 1930-1934b 0.0644 0.0302 .049
70-74b years 0.1067 0.0215 <.001 2010-2014b 0.3109 0.0208 <.001 1935-1939 –0.0146 0.0275 .60
75-79b years 0.3824 0.0213 <.001 2015-2019b 0.8572 0.0235 <.001 1940-1944b –0.076 0.0238 .006
—c — — — — — — — 1945-1949b 0.0779 0.0261 .009
— — — — — — — — 1950-1954b 0.1764 0.0278 <.001
— — — — — — — — 1955-1959 0.056 0.0299 .08
— — — — — — — — 1960-1964 0.013 0.0338 .71
— — — — — — — — 1965-1969b 0.148 0.0595 .02
Femaled
50-54b years 0.1007 0.0316 .006 1990-1994b –0.776 0.0284 <.001 1915-1919b –0.17 0.0651 .02
55-59 years –0.0206 0.0295 .496 1995-1999b –0.2952 0.0304 <.001 1920-1924b –0.3801 0.0512 <.001
60-64 years 0.0561 0.0304 .08 2000-2004b 0.0971 0.0308 .006 1925-1929 –0.0048 0.0458 .92
65-69b years 0.0799 0.0306 .019 2005-2009b 0.1991 0.0303 <.001 1930-1934b 0.0929 0.0422 .04
70-74b years –0.1227 0.0300 <.001 2010-2014b 0.0857 0.0291 .01 1935-1939 0.0125 0.0384 .75
75-79b years –0.0934 0.0297 .006 2015-2019b 0.6893 0.0328 <.001 1940-1944 –0.0124 0.0333 .72
—c — — — — — — — 1945-1949b 0.1271 0.0365 .003
— — — — — — — — 1950-1954b 0.2084 0.0389 <.001
— — — — — — — — 1955-1959 0.0722 0.0417 .10
— — — — — — — — 1960-1964 0.0022 0.0473 .96
— — — — — — — — 1965-1969 0.052 0.0832 .54

aR2=0.9981; adjusted R2=0.9957.

bIndicates that age, period, and cohort effects are significantly different from zero at the alpha=.05 level.

cNot applicable.

dR2=0.9941; adjusted R2=0.9867.

The age-period-cohort effect and 95% CI.

 Discussion Principal Findings

Due to the increased effectiveness of ART, life expectancy has increased for people with HIV. Although disparities in life expectancy among people with HIV continue to persist, there is an increasing prevalence of people with HIV at 50 years of age and older [28]. However, this study showed that elderly HIV or AIDS mortality rates in China increased from 1990 to 2019, with ASMR ranging from 0.50/105 to 4.54/105 for male and 0.19/105 to 1.43/105 for female individuals. In addition to the aging population, a proportion of HIV infections occurs in older persons [4,29,30], exacerbating the severity of the HIV epidemic in the older people. Our results indicated that elderly HIV mortality in China increased rapidly, especially in male individuals (average annual percentage change=7.0). Furthermore, the ASMR showed that the mortality rate was more pronounced for male individuals as they get older, especially at 75-79 years old, but for female individuals, it peaked at 65-69 years old. It may be because with the increasing efficiency of antiretroviral therapy, the age of survival of patients who have AIDS can reach 77.3 years, which is the average life expectancy of the Chinese population [31] regardless of whether they die of diseases or natural causes.

The mortality rate of older male individuals was 2-4 times that of the older female individuals [32], both in crude rates and in ASMR, which indicated a significant gender difference in the mortality of the older people with AIDS. Possible reasons for this are that the physiological functions of people older than 50 years of age have not declined, and the physical condition and sexual needs of older male individuals are still at a high level; the standard of living of mainland Chinese residents has improved in the early 21st century [9], whereas in older female individuals, incidences are mainly due to spousal transmission [33]. However, owing to the lack of sex education, these people did not have the most basic reproductive health education and had a low perception of risk, leading to the frequent occurrence of high-risk sexual behaviors [8]. Unprotected commercial sex is the main route of HIV transmission among older males [33]. Therefore, long-term, in-depth, comprehensive HIV or AIDS health education for older male individuals is essential for critical groups.

The joinpoint regression analysis showed that the mortality rates for older male individuals have continued to increase over time (at different rates per period), while for female individuals, there was a downward trend compared with male individuals from 2003 to 2013. However, HIV or AIDS mortality rates also increased more slowly during this period compared with other periods. In 2004, the Chinese government announced its “Four Frees and One Care” policy [1], which may reduce HIV- or AIDS-related mortality or a reduction in the rate of increase. The policy has increased ART facilities from 671 in 2004 to 3733 in 2013, facilitating access to standardized ART for the HIV or AIDS population. It also strengthens the cooperation between medical institutions and the Centers for Disease Control and Prevention, continuously adjusts the types of antiviral drugs and treatment standards according to the actual ART needs of each region, and operates and establishes a system for the procurement, supply, and funding of relevant drugs.

To present more realistic results, the APC model was used to divide the influencing factors into age, period, and cohort. Age is one of the most important demographic factors affecting HIV mortality, and many surveys have shown that ages older than 40 years are strongly associated with mortality from AIDS-related diseases [34,35]. The age effect in the change of HIV or AIDS mortality among Chinese older male individuals reflects a quantitative relationship that the higher the age, the larger the effect coefficient, with the most significant age effect coefficient of 0.38 for the 75-79 years group, indicating that the high-risk group for death among Chinese older men with HIV is still people in the higher age group. In contrast to male individuals, the risk of death among older female individuals with HIV is generally decreasing. However, there is a slight increase between 55 and 69 years. Therefore, prevention and control for female populations should focus on the 50-69 years age group.

According to the analysis of the period effect on HIV mortality, there was a net increase of 1.653 from 1990-1994 to 2015-2019. Such rapid growth may suggest that the period effect is an essential factor influencing HIV- or AIDS-related deaths in older people. The continuous improvement of the quality of life and the neglect of the sexual needs of older people by their families will lead to unsafe sexual behaviors [6,36]. At the same time, due to the lack of sexual knowledge, older males often have the mentality of not being afraid or not caring. More unprotected commercial behaviors [37,38] increase HIV mortality risk during these periods. Hence, in this era of increasing material abundance, the trend will continue to affect older people living with HIV. Therefore, at a time of continuous economic and social progress, openness to sexuality, and significance of aging [39,40], we should use multidisciplinary approaches to curb the growing severity of HIV- or AIDS-related problems.

The cohort effect is a comprehensive indicator, and it is impacted by age and period effects. Only by fundamentally solving the above problems can we effectively reduce the mortality rate of HIV in older people. Community organizations should be focused on carrying out more sex education, especially among older male populations, enriching the cultural life of older people and promoting healthy and safe sexual attitudes [41]. More attention must be paid to HIV or AIDS education in low-income and rural areas, raising awareness about its health risks and impact on families and society in an acceptable manner [42-44]. In particular, maintaining a single sexual partner and the correct use of condoms must be the focus of education. Moreover, continuously carrying out voluntary counseling and testing, actively mobilizing the older population for HIV testing for early detection of elderly HIV, and providing timely care and effective treatment [45] are required.

 Limitations

This study also has some limitations. First, this paper only provides a descriptive analysis of the GBD 2019 database without etiological and attribution analyses. Second, we could not discuss China’s provinces and the differences between regions due to data inadequacy. Third, the results of GBD 2019 are mainly estimates obtained from calculations by combining a system dynamics model with a statistical model, which may differ from the actual observed data and cannot avoid distortion of the results. Finally, our study has ecological fallacies and unique limitations associated with the APC model (including identifiability issues and the uncertainty principle). Therefore, future large-scale cohort studies are needed to confirm the relevant hypotheses in this study.

 Conclusion

In conclusion, our study shows a marked increase in HIV mortality for both sexes in China from 1990 to 2019. These trends may be due to changes in socioeconomic growth and lifestyle in the population. The aging trend of the population is still a significant problem for HIV prevention and treatment in older people. It is essential to carry out early HIV screening and health education for people aged 50 years and older, as is urging infected individuals to receive ART as soon as possible to prevent HIV infection and reduce mortality rate. These findings may help predict future changes in HIV mortality and identify priority populations.

 Abbreviations APC

age-period-cohort

 ART

antiretroviral therapy

 ASMR

age-standardized mortality rates

 GBD

Global Burden of Disease

 IE

Intrinsic Estimator

This paper was supported by Sichuan Research Centre for Sociology of Sexuality and Sexuality Education, Sichuan Key Research Base of Philosophy and Social Sciences Project (grant number: SXJYB2004), and the Luzhou Social Science Union (grant LZ21A079). The funders had no role in study design, data collection, data analysis, data interpretation, writing the manuscript, and decision to publish.

 Data Availability

The data set supporting the conclusions of this article are available in the GBD Data Tool repository [46].

Demographic data were collected from the Statistical Yearbook of Population and Employment of China by the National Bureau of Statistics for the calendar years 1990 to 2019 [47].

SF, NR, and YL participated in the study conception and design, literature search, and statistical analysis. NR, YL, RW, and WZ participated in gathering data, tabulating the table, and plotting the graphic. NR drafted and wrote the report. SF, AL, ZW, and EED participated in language polishing and provided comments on the manuscript. All authors participated in interpreting data and study findings as well as critically reviewing and substantively revising the manuscript. All authors have approved the final version of the manuscript to be published. All authors agreed to be accountable for all aspects of the work and ensure that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

None declared.

 Wu Z Chen J Scott SR McGoogan JM History of the HIV epidemic in China Curr HIV/AIDS Rep 2019 12 26 16 6 458 466 10.1007/s11904-019-00471-4 31773405 10.1007/s11904-019-00471-4 PMC7088640 National epidemiological profile of statutory infectious diseases in 2020 Chinese Centers for Disease Control and Prevention 2021 2022-11-07 http://www.nhc.gov.cn/jkj/s3578/202103/f1a448b7df7d4760976fea6d55834966.shtml Shiau S Bender AA O'Halloran JA Sundermann E Aggarwal J Althoff KN Baker JV Deeks S Fried LP Karpiak S Karris MY Marcotte TD Nachega JB Margolick JB Erlandson KM Moore DJ The current state of HIV and aging: Findings presented at the 10th international workshop on HIV and aging AIDS Res Hum Retroviruses 2020 12 36 12 973 981 10.1089/AID.2020.0128 32847368 PMC7703090 Erlandson KM Karris MY HIV and aging: Reconsidering the approach to management of comorbidities Infect Dis Clin North Am 2019 09 33 3 769 786 10.1016/j.idc.2019.04.005 31395144 S0891-5520(19)30034-0 PMC6690376 Aging with HIV Centers for Disease Control and Prevention 2018 11 14 2022-11-07 https://www.cdc.gov/hiv/group/age/olderamericans/index.html Smit M Brinkman K Geerlings S Smit C Thyagarajan K Sighem AV de Wolf F Hallett TB ATHENA observational cohort Future challenges for clinical care of an ageing population infected with HIV: a modelling study Lancet Infect Dis 2015 07 15 7 810 8 10.1016/S1473-3099(15)00056-0 26070969 S1473-3099(15)00056-0 PMC4528076 Wing EJ HIV and aging Int J Infect Dis 2016 12 53 61 68 10.1016/j.ijid.2016.10.004 27756678 S1201-9712(16)31187-0 Autenrieth CS Beck EJ Stelzle D Mallouris C Mahy M Ghys P Global and regional trends of people living with HIV aged 50 and over: Estimates and projections for 2000-2020 PLoS One 2018 13 11 e0207005 10.1371/journal.pone.0207005 30496302 PONE-D-18-19731 PMC6264840 Abel T Werner M HIV risk behaviour of older persons Eur J Public Health 2003 12 13 4 350 2 10.1093/eurpub/13.4.350 14703323 Wang LY Qin QQ Ge L Ding ZW Cai C Guo W Cui Y [Characteristics of HIV infections among over 50-year-olds population in China] Zhonghua Liu Xing Bing Xue Za Zhi 2016 02 37 2 222 6 10.3760/cma.j.issn.0254-6450.2016.02.015 26917520 Zhang HX Han MJ Zhou Y Xiu XF Xu F Wang L [Interrupted time series analysis for influence on HIV related fatality of implementation of 'Four Free Services One Care' policy in China] Zhonghua Liu Xing Bing Xue Za Zhi 2020 03 10 41 3 406 411 10.3760/cma.j.issn.0254-6450.2020.03.024 32294844 Tarone RE Chu KC Gaudette LA Birth cohort and calendar period trends in breast cancer mortality in the United States and Canada J Natl Cancer Inst 1997 02 05 89 3 251 6 10.1093/jnci/89.3.251 9017006 Ma Y Cui Y Hu Q Mubarik S Yang D Jiang Y Yao Y Yu C Long-term changes of HIV/AIDS incidence rate in China and the U.S. population from 1994 to 2019: A join-point and age-period-cohort analysis Front Public Health 2021 9 652868 10.3389/fpubh.2021.652868 34869132 PMC8634360 Gao D Zou Z Zhang W Chen T Cui W Ma Y Age-period-cohort analysis of HIV mortality in China: Data from the Global Burden of Disease Study 2016 Sci Rep 2020 04 27 10 1 7065 10.1038/s41598-020-63141-1 32341364 10.1038/s41598-020-63141-1 PMC7184615 Fu W Preliminary analysis of age-period-cohort data—Basic models The Identification Problem and Beyond 2018 Boca Raton, Florida, US CRC Press GBD 2017 DiseaseInjury Incidence Prevalence Collaborators Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017 Lancet 2018 11 10 392 10159 1789 1858 10.1016/S0140-6736(18)32279-7 30496104 S0140-6736(18)32279-7 PMC6227754 Jia Z Ruan Y Lu Z HIV incidence and mortality in China Lancet 2015 04 18 385 9977 1510 10.1016/S0140-6736(15)60753-X 25933281 S0140-6736(15)60753-X Adler WH Baskar PV Chrest FJ Dorsey-Cooper B Winchurch RA Nagel JE HIV infection and aging: mechanisms to explain the accelerated rate of progression in the older patient Mech Ageing Dev 1997 06 96 1-3 137 55 10.1016/s0047-6374(97)01888-5 9223117 S0047-6374(97)01888-5 UNAID report on global AIDS epidemic UNAIDS 2021-11-09 https://aids2020.unaids.org/report/ Glenn ND Mason WM Fienberg SE Cohort analysis in social research: Beyond the identification problem Journal of the American Statistical Association 1986 09 81 395 870 10.2307/2289041 Mason KO Mason WM Winsborough HH Poole WK Some methodological issues in cohort analysis of archival data American Sociological Review 1973 04 38 2 242 10.2307/2094398 O'Brien R Age-Period-Cohort Models: Approaches and Analyses with Aggregate Data 2014 New York, US Chapman and Hall/CRC Osmond C Gardner MJ Age, period and cohort models applied to cancer mortality rates Stat Med 1982 1 3 245 59 10.1002/sim.4780010306 7187097 James IR Segal MR On a method of mortality analysis incorporating age--year interaction, with application to prostate cancer mortality Biometrics 1982 06 38 2 433 43 7115872 Holford TR The estimation of age, period and cohort effects for vital rates Biometrics 1983 06 39 2 311 24 6626659 Yang Y Land KC Age-Period-Cohort Analysis: New Models, Methods, and Empirical Applications 2013 New York, US Chapman and Hall/CRC 9781466507524 Fu W A Practical Guide to Age-Period Cohort Analysis Using R: The Identification Problem and Beyond 2017 New York, US Chapman and Hall/CRC Althoff KN Chandran A Zhang J Arevalo WM Gange SJ Sterling TR Gill MJ Justice AC Palella FJ Rebeiro PF Silverberg MJ Mayor AM Horberg MA Thorne JE Rabkin CS Mathews WC Klein MB Humes E Lee J Hogg R Moore RD North American AIDS Cohort Collaboration on ResearchDesign (NA-ACCORD) of IeDEA Life-expectancy disparities among adults with HIV in the United States and Canada: The impact of a reduction in drug- and alcohol-related deaths using the Lives Saved simulation model Am J Epidemiol 2019 12 31 188 12 2097 2109 10.1093/aje/kwz232 31602475 5583226 PMC7036649 Sundermann EE Erlandson KM Pope CN Rubtsova A Montoya J Moore AA Marzolini C O'Brien KK Pahwa S Payne BAI Rubin LH Walmsley S Haughey NJ Montano M Karris MY Margolick JB Moore DJ Current challenges and solutions in research and clinical care of older persons living with HIV: Findings presented at the 9th international workshop on HIV and aging AIDS Res Hum Retroviruses 2019 35 11-12 985 998 10.1089/AID.2019.0100 31373216 PMC6862962 Antiretroviral Therapy Cohort Collaboration Survival of HIV-positive patients starting antiretroviral therapy between 1996 and 2013: a collaborative analysis of cohort studies Lancet HIV 2017 08 4 8 e349 e356 10.1016/S2352-3018(17)30066-8 28501495 S2352-3018(17)30066-8 PMC5555438 Statistical bulletin on the development of health care in China in 2019 Committee Health and Wellness 2020 2022-11-07 http://www.gov.cn/guoqing/2021-04/09/content_5598657.htm Wu Z Sullivan SG Wang Y Rotheram-Borus MJ Detels R Evolution of China's response to HIV/AIDS Lancet 2007 02 24 369 9562 679 90 10.1016/S0140-6736(07)60315-8 17321313 S0140-6736(07)60315-8 PMC7137740 Chen X Li X Qin B Zheng J He J Wang L Wang N Hsu A Khoshnood K Older HIV-positive adults in Xiangxi, China: infection modes and associated risk factors Sex Transm Dis 2012 09 39 9 716 9 10.1097/OLQ.0b013e31825af361 22902669 00007435-201209000-00011 Zhang F Dou Z Ma Y Zhang Y Zhao Y Zhao D Zhou S Bulterys M Zhu H Chen RY Effect of earlier initiation of antiretroviral treatment and increased treatment coverage on HIV-related mortality in China: a national observational cohort study Lancet Infect Dis 2011 07 11 7 516 24 10.1016/S1473-3099(11)70097-4 21600849 S1473-3099(11)70097-4 Chen L Pan X Ma Q Yang J Xu Y Zheng J Wang H Zhou X Jiang T Jiang J He L Jiang J HIV cause-specific deaths, mortality, risk factors, and the combined influence of HAART and late diagnosis in Zhejiang, China, 2006-2013 Sci Rep 2017 02 15 7 42366 10.1038/srep42366 28198390 srep42366 PMC5309804 Lindau ST Schumm LP Laumann EO Levinson W O'Muircheartaigh CA Waite LJ A study of sexuality and health among older adults in the United States N Engl J Med 2007 08 23 357 8 762 74 10.1056/NEJMoa067423 17715410 357/8/762 PMC2426743 Xie T Wu N Epidemiological and mortality analysis of older adults with HIV in eastern China Clin Interv Aging 2013 8 1519 25 10.2147/CIA.S53657 24277983 cia-8-1519 PMC3838474 Cheng S Siankam B The impacts of the HIV/AIDS pandemic and socioeconomic development on the living arrangements of older persons in sub-Saharan Africa: a country-level analysis Am J Community Psychol 2009 09 44 1-2 136 47 10.1007/s10464-009-9243-y 19543825 Zeng Y Fan J Zhang Q Wang PC Tang DJ Zhon SC Zheng XW Liu DP Detection of antibody to LAV/HTLV-III in sera from hemophiliacs in China AIDS Res 1986 12 2 Suppl 1 S147 9 3103638 Lu H Liu Y Dahiya K Qian H Fan W Zhang L Ma J Ruan Y Shao Y Vermund SH Yin L Effectiveness of HIV risk reduction interventions among men who have sex with men in China: a systematic review and meta-analysis PLoS One 2013 8 8 e72747 10.1371/journal.pone.0072747 24137497 PONE-D-13-10216 PMC3796948 Shippy RA Karpiak SE The aging HIV/AIDS population: fragile social networks Aging Ment Health 2005 05 9 3 246 54 10.1080/13607860412331336850 16019278 P25G486181M06267 Nogueira JDA Silva AO de Sá LR Almeida SAD Monroe AA Villa TCS AIDS in adults 50 years of age and over: characteristics, trends and spatial distribution of the risk Rev Lat Am Enfermagem 2014 22 3 355 63 10.1590/0104-1169.3327.2424 25029044 S0104-11692014000300355 PMC4292626 Sabin CA Reiss P Epidemiology of ageing with HIV: what can we learn from cohorts? AIDS 2017 06 01 31 Suppl 2 S121 S128 10.1097/QAD.0000000000001374 28471942 00002030-201706002-00003 Puhr R Kumarasamy N Ly PS Ng OT Van Nguyen K Merati TP Pham TT Lee MP Choi JY Ross JL Law MG HIV and aging: Demographic change in the Asia-Pacific region J Acquir Immune Defic Syndr 2017 04 15 74 5 e146 e148 10.1097/QAI.0000000000001258 28267699 00126334-201704150-00019 PMC5341141 Ren N Li Y Zhang W Wang R Fan S Li A Disease burden and trend of HIV/AIDs among the elderly in China during 1990-2019 Chin J Dis Prev. 2022 2022 26 06 639 44 10.16462/j.cnki.zhjbkz.2022.06.004 GBD Results Institute for Health Metrics and Evaluation 2022-11-07 http://ghdx.healthdata.org/gbd-results-tool Statistical Yearbook of Population and Employment of China, 1990-2019 National Bureau of Statistics 2022-11-07 https://data.cnki.net/Trade/yearbook/single/N2020020031?z=Z001