Urgent need for inclusion of male infertility in global health strategies: insights from the GBD 2021 Study

Abstract

This study examines the global burden and prevalence of male infertility using data from the Global Burden of Disease Study 2021 (GBD 2021 Study), encompassing 204 countries from 1990 to 2021. By analyzing disability-adjusted life years (DALYs) and prevalence trends, alongside lifestyle, environmental, and disease-related factors, including the impact of coronavirus disease 2019 (COVID-19), we identified significant temporal and regional disparities. Using joinpoint regression, decomposition analysis, and Bayesian age-period-cohort models, the results revealed a rising global burden, with DALYs increasing from 15.8 to 18.6 per 100 000 and the age-standardized prevalence rising from 2752.5 to 3218.9 per 100 000 over three decades. Low- and middle-sociodemographic index (SDI) regions presented the highest burden, driven by demographic shifts and epidemiological challenges. The COVID-19 pandemic further exacerbated healthcare disparities, particularly in resource-limited settings. These findings underscore the urgent need to integrate male infertility into global health agendas, emphasizing tailored interventions and policy reforms to address socioeconomic impacts and mitigate rising burdens, especially in low- and middle-SDI regions.

INTRODUCTION

Male infertility is a widespread issue, affecting approximately 70 million individuals globally and approximately 9% of couples.1 One in eight couples encounters difficulties conceiving their first child, while one in six experiences challenges with subsequent pregnancies.2,3 Male factor infertility is identified in approximately 50% of infertile couples, with approximately 20% of these cases attributed solely to male factors.4,5 These findings underscore the substantial contribution of male infertility to the overall infertility burden.

Male infertility is a multifactorial condition, encompassing genital tract infections, ejaculatory disorders related to the urogenital tract, endocrine disorders leading to testosterone imbalances, testicular spermatogenesis disorders, and various adverse lifestyle factors, including smoking, excessive alcohol consumption, and high body mass index (BMI). Infection is a significant cause of male infertility, with 13%–15% of male infertility cases associated with infections.6 Pathogens, including viruses, Chlamydia trachomatis, Ureaplasma, Staphylococcus aureus, Pseudomonas aeruginosa, and Mycoplasma spp., can cause a range of urogenital infections, including bacterial prostatitis, acute epididymitis, viral orchitis, and obstructive azoospermia.7 These infections can directly impair spermatogenesis, hinder sperm maturation and function, cause partial obstruction of the sperm ducts, and lead to accessory gland dysfunction, ultimately resulting in genetic or epigenetic changes.

In low-income countries, urogenital infections remain a significant challenge, with prevalence rates reaching as high as 60% in some regions of Africa. Additionally, the interplay of inadequate healthcare systems exacerbates male infertility in these areas. In contrast, middle- and high-income countries generally exhibit lower infection rates, supported by better healthcare systems that play a crucial role in prevention and treatment. The vicious cycle driven by economic disparities calls for future policy adjustments and resource allocation to address this pressing issue more effectively.7,8 Furthermore, prolonged exposure to environmental toxins can directly affect sperm parameters.9,10

Socioeconomic disparities exacerbate this issue, as many individuals living near industrial areas, farms, construction sites, highways, or railways have limited options for improving their living conditions to reduce exposure to these harmful factors. Moreover, chemical pollution levels in everyday products vary across countries with different economic conditions, further contributing to disparities in fertility levels among populations.10 Clinical evaluation of male infertility includes semen parameters (sperm concentration, motility, morphology, and DNA fragmentation index [DFI]), medical history, hormonal evaluation, testicular ultrasound, and physical partner assessment. This process requires significant time, effort, and financial resources. Although assisted reproductive technologies (ART) have been available for over 30 years and enabled the birth of millions of children, they remain underutilized or inaccessible in many low- and middle-income regions, where economic challenges render them unaffordable.11 As a result, pharmacological interventions become a more accessible option for many patients. Drug treatment strategies primarily consist of three components: (1) endocrine therapy, including human chorionic gonadotropin (hCG), human menopausal gonadotropin (hMG), follicle-stimulating hormone (FSH), aromatase inhibitors, and testosterone replacement therapy; (2) nutritional support, such as zinc, selenium, and L-carnitine supplements; and (3) antioxidant therapy, which includes vitamin C, vitamin E, and coenzyme Q10. However, these treatments are only effective for specific patient groups.

Most previous epidemiological studies on male infertility have relied on data from the Global Burden of Disease Study 2019 (GBD 2019 Study).12,13 Research exploring the relationships between male infertility, economic status, and regional distribution is relatively limited. The recent GBD update, released in May 2024, provides valuable data that support epidemiological research, significantly contributing to public health analysis and prediction.14 This paper leverages the latest GBD data to analyze and predict male infertility trends, offering insights that can inform the development and refinement of public health policies.

MATERIALS AND METHODS

Data sources and overview

The data for this study were sourced from the Global Burden of Disease Study 2021 (GBD 2021 Study), which analyzed 371 diseases and injuries across 100 983 relevant datasets from 9 super-regions, 21 regions, 204 countries (including 21 countries with subnational locations), and 811 subnational locations from 1990 to 2021.14

We primarily used data on disability-adjusted life years (DALYs) and the prevalence of male infertility, focusing on individuals aged 20–49 years. All data included corresponding 95% uncertainty intervals. The study encompassed 204 countries, 6 sociodemographic index (SDI) regions, and 4 continents, with a particular emphasis on cause or risk rankings in India and China by 1990, 2010 and 2021. Changes in rankings were visually represented using connecting lines.14,15

Socioeconomic development status was assessed using the SDI, a quantifiable indicator reflecting a country or region’s development level. The SDI incorporates key dimensions, such as per capita gross domestic product (GDP), educational attainment, and life expectancy, providing a comprehensive evaluation of a region’s social progress.

Data analysis

We employed the joinpoint regression model, a statistical method widely used in epidemiology to analyze trend changes over time.16 This method identifies overall trend changes, inflection points, and annual percent changes (APC) within each segment and determines the overall average annual percent change (AAPC).17

To quantify trends in male infertility, we calculated the average annual percent change (AAPC) in the age-standardized DALYs rate (ASDR) and age-standardized prevalence rate (ASPR), along with the 95% confidence interval (CI) to assess statistical precision. Additionally, 95% uncertainty interval (UI) were provided to illustrate ASDR and ASPR to reflect the overall accuracy.

Decomposition analysis is a method that breaks down complex issues or systems into smaller, relatively independent components or factors to separate and quantify the contributions of these driving factors. We used decomposition analysis to assess the impacts of age, epidemiological changes, and population in different SDI regions. The decomposition analysis was conducted using the Hyers-Graves-Quinn (HGQ) formula15:

This multifactorial decomposition analysis method enables a simultaneous assessment of the contributions of multiple variables to overall changes. This approach allows us to quantify the impact of different factors on the burden of male infertility over time.

Finally, we used GBD visualization to display DALYs trends for male infertility from 1990 to 2021 in the top ten Asian countries. We also compared environmental exposure-related factors influencing DALYs rankings in India and China between 1990 and 2021. The data covered rankings, rates of change, and the percentage of total DALYs.

Data analysis was performed using R software version 4.3.3 (R Foundation for Statistical Computing, Vienna, Austria). Figures were edited and visually optimized using Canva (Canva Pty. Ltd., Sydney, Australia).

RESULTS

Global burden and prevalence of male infertility

The global burden of male infertility has been steadily increasing. It is estimated that male factors contribute to 30–50% of infertility cases.4 Among men aged 20–49 years, the global burden of disease (per 100 000) for male infertility rose from 15.8 (95% UI: 4.6–40.9) in 1990 to 18.6 (95% UI: 5.2–48.6) in 2021, with an AAPC of 0.5 (95% CI: 0.4–0.6, P < 0.05; Table 1). The age-standardized prevalence (per 100 000 people) increased from 2752.5 (95% UI: 1162.9–5557.3) in 1990 to 3218.9 (95% UI: 1293.1–6569.9) in 2021, with an AAPC of 0.5 (95% CI: 0.4–0.6, P < 0.05; Table 1). We also analyzed the disease burden and age-standardized prevalence across five SDI regions. Notably, in the low–middle SDI region, the ASDRs’ AAPC were 1.1 (95% CI: 0.8–1.4, P < 0.05), and the age-standardized prevalence’ AAPC was 1.1 (95% CI: 0.9–1.4, P < 0.05; Table 1). The age-standardized prevalence of male infertility exhibited marked geographic variation, with the lowest interval below 1725.9 cases per 100 000 people and the highest reaching 7710.9 cases per 100 000. The prevalence was most concentrated in the Caribbean and Central America, Russia, China, India, the Persian Gulf, the Balkan Peninsula, Southeast Asia, West Africa, the Eastern Mediterranean, and Northern Europe. The highest prevalence interval (more than 3695.0 cases per 100 000) was predominantly observed across these high-incidence regions, peaking at approximately 7710.9 cases per 100 000.

Table 1.

Trends in the prevalence and disability-adjusted life years of male infertility globally and by sociodemographic index from 1990 to 2021

Disease burden by location	1990 rate		2021 rate		1990–2021 rate
	ASR	95% UI	ASR	95% UI	AAPC	95% CI
Global
DALYs	15.8	4.6–40.9	18.6	5.2–48.6	0.5	0.4–0.6*
Prevalence	2752.5	1162.9–5557.3	3218.9	1293.1–6569.9	0.5	0.4–0.6*
High-middle SDI
DALYs	18.8	5.2–50.8	19.9	5.4–53.5	0.2	0.2–0.2*
Prevalence	3351.0	1318.7–6927.8	3517.8	1340.3–7429.3	0.2	0.1–0.2*
High SDI
DALYs	13.1	3.8–34.0	15.4	4.1–40.5	0.5	0.5–0.6*
Prevalence	2192.0	899.4–4484.5	2571.0	978.6–5450.1	0.6	0.5–0.6*
Low–middle SDI
DALYs	14.0	4.2–35.3	19.3	5.4–49.4	1.1	0.8–1.4*
Prevalence	2392.5	1098.8-4749.8	3299.4	1368.7–6793.5	1.1	0.9–1.4*
Low SDI
DALYs	16.7	5.3–40.2	17.2	5.1–42.9	0.1	0–0.3*
Prevalence	2934.6	1471.9–5407.3	3004.6	1346.7–5889.7	0.1	0–0.3*
Middle SDI
DALYs	15.9	4.4–42.3	19.0	5.2–50.1	0.6	0.5–0.7*
Prevalence	2832.6	1117.0–5837.7	3305.2	1279.9–6810.5	0.5	0.4–0.6*

*P<0.05. DALYs: disability-adjusted life years; UI: uncertainty interval; CI: confidence interval; SDI: sociodemographic index; AAPC: average annual percent change; ASR: age-standardized rate

The corresponding burden of ASDRs likewise displayed a bipolar distribution, ranging from <10.0 years to 44.3 years per 100 000 people. High-prevalence regions corresponded to areas with elevated ASDRs, exceeding 21.4 years per 100 000 people and reaching a maximum of 44.3 years per 100 000 people. Conversely, the low-burden regions (<10.0 years per 100 000 people) were clustered in countries and regions with relatively favorable geographic or socioeconomic conditions.

Trends in male infertility over time

From 1990 to 2021, overall trends in ASDRs and ASPRs for male infertility, as analyzed using the joinpoint model, exhibited fluctuations. Prior to 2010, trends remained relatively stable. For ASDRs, the APC was −0.28 from 1990 to 2001, 0.92 from 2001 to 2005, and −0.40 from 2005 to 2010. For ASPRs, the APC was −0.31 from 1990 to 2001, 0.86 from 2001 to 2005, and −0.37 from 2005 to 2010. However, after 2010, a significant exponential increase was observed, with APCs of 2.2 from 2010 to 2014 and 1.4 from 2014 to 2021 for ASDRs and APCs of 2.3 from 2010 to 2014 and 1.29 from 2014 to 2021 for ASPRs. The AAPCs for ASDRs and ASPRs both reached 0.5 (Figure 1).

Figure 1.

Global prevalence and the DALYs joinpoint model. (a) The prevalence rate (age-standardized prevalence rate) per 100 000 people. (b) The ASDRs per 100 000 people of male infertility. ^*P < 0.05. APC: annual percent change; DALYs: disability-adjusted life years; ASDR: age-standardized incidence rate.

Relationship between SDI regions and male infertility

According to the Bayesian age-period-cohort (BAPC) model, the overall trends in ASPRs over time have increased. The high-SDI and middle-SDI regions exhibit slight upward trends, with minimal overall changes. The high–middle SDI region shows negligible variation, with changes approaching zero. In contrast, the low-SDI regions primarily exhibit negative values, although a gradual upward trend, approaching 1, was observed by 2021. Notably, the rapid increase in the low–middle SDI region after 2010 warrants further investigation (Figure 2).

Figure 2.

Changes in ASPRs over time in each SDI region based on BAPC model. ASPR: age-standardized prevalence rate; SDI: sociodemographic index; BAPC: Bayesian age-period-cohort.

Burden of male infertility in Asia

From a global perspective, when factors such as age, population, and epidemiological changes are combined, population and epidemiological changes emerge as the primary drivers of the increasing burden of male infertility and prevalence. Among these, population changes are the most critical (Figure 3). Supplementary Figure 1 ^{(637.3KB, tif)} illustrates that Asia has consistently maintained a high burden of male infertility, with this trend continuing to rise. Additionally, the impact of the coronavirus disease 2019 (COVID-19) pandemic, an ongoing concern since its emergence in 2019, is crucial in the context of male infertility.18 Significant increases in male infertility rates were observed in Africa and Europe in 2020. As shown in Supplementary Table 1, the AAPC of male infertility attributable to COVID-19 across the four continents exhibited varying upward trends. Africa experienced the highest increase (AAPC = 54.6), followed by Europe (AAPC = 36.4), while China showed the lowest increase (AAPC = 31.9). With a population of 1 447 301 400 people, China is the most populous country in Asia, followed by India, which has a population of 1 403 018 576 people. Other notable countries include Indonesia, Pakistan, Bangladesh, Japan, the Philippines, Vietnam, and Iran.19 Interestingly, while India and China rank highest in terms of the burden of male infertility, China has exhibited a declining trend. In contrast, India has shown an increasing trend, with a crossover occurring in approximately 2015 (Supplementary Figure 2 ^{(446.5KB, tif)} ).

Figure 3.

Three-factor analysis of the DALYs and prevalence. The three-factor analysis about (a) prevalence and (b) DALYs between 1990 and 2021. DALYs: disability-adjusted life years.

Supplementary Table 1.

Age-standardized prevalence across four continents

Location	Year	Value	95% UI	AAPC
Africa	2020	4678.7	4386.1–5012.0	54.6
	2021	7662.1	7217.5–8178.7
America	2020	3472.9	3235.5–3706.1	35.7
	2021	4747.4	4423.7–5136.3
Asia	2020	1298.9	1194.2–1452.4	31.9
	2021	2316.4	2125.5–2632.7
Europe	2020	1686.1	1538.5–1839.9	36.4
	2021	3008.80	2689.21–3374.31

AAPC: average annual percent change; UI: uncertainty interval

National burden of male infertility

The exponential rise in male infertility observed in approximately 2010 (Figure 3) prompted an analysis of exposure risks contributing to the disease burden in China and India for 1990, 2010, and 2021. We examined environmental, behavioral, and metabolic risk factors. Heatmap comparisons from these three years revealed that in China, smoking, hypertension, ambient particulate matter pollution, diabetes, and high BMI have all increased. In contrast, indoor air pollution, low birth weight, preterm birth, and low child weight have decreased. In contrast, India has experienced a decline in low birth weight, preterm birth, and indoor air pollution, although these factors remain at high levels. Additionally, hypertension, diabetes, and outdoor air pollution continue to increase annually (Supplementary Figure 3 ^{(673.8KB, tif)} and 4 ^{(683.7KB, tif)} ).

DISCUSSION

The United Nations’ Sustainable Development Goals (SDGs) envision a promising future for humanity, aiming to achieve all targets by 2030. Goal 3 specifically underscores the importance of ensuring healthy lives and promoting well-being for all age groups. This goal explicitly advocates for the promotion and universal accessibility of health and reproductive health services, including household reproductive self-determination (HRSD). It emphasizes integrating reproductive health into national strategies and programs. In summary, HRSD refers to the ability of families to maintain individual reproductive choices through planning and scheduling. It involves consideration of factors such as economic status, life goals, and personal preferences when determining the number of children, spacing of births, and approaches to education and parenting. Fertility preservation refers to protecting and intervening in male reproductive capacity, emphasizing male reproductive health. These two aspects contribute differently to achieving multiple SDGs, each highlighting different dimensions of global health and development. Both significantly contribute to SDG3, “Good Health and Well-being,” by ensuring maternal and infant health, preventing disease transmission, and protecting reproductive health.

Additionally, the “Quality Education” SDG4 facilitates the rational allocation of educational resources and supports educational planning. Furthermore, it aims to significantly reduce the prevalence of diseases caused by hazardous chemicals and air, water, and soil pollution.20 Environmental pollutants, due to their extreme stability and nonbiodegradable nature, are pervasive and persistent in the environment, potentially disrupting the human reproductive system. They may lead to reduced sperm motility, increased DNA damage, oxidative stress induction, and mitochondrial dysfunction.21,22,23 These findings highlight the importance of reproductive health in global health, elevating it to a national strategic priority. However, male factors contribute to 30%–50% of infertility cases among couples with regular sexual activity, with 20% of these cases attributed solely to male factors.24 However, male infertility is often overlooked due to gender inequality. Although it affects the quality of life for both partners, research on male infertility remains limited compared to other health issues.4 Male fertility is not only an individual health issue but also impacts the overall health of the male population, subsequently affecting societal health. Therefore, enhancing male fertility can be considered a critical objective for improving the overall health of the male population, contributing to societal health and sustainable development in the long term.

Additionally, male reproductive health is directly linked to human reproduction and societal continuity. High-quality fertility ensures reproductive health, infant well-being, and the prosperity of future societies. Consequently, investigating, diagnosing, and treating male infertility are urgent priorities. We believe that updating and strengthening the global burden of disease and prevalence data on male infertility is crucial.

This study, based on the latest data from the GBD 2021 update in May 2024, focuses on comparing the national burden of disease and associated risk factors for male infertility in two of the world’s most populous countries. The main differences between GBD 2021 and GBD 2019 include updated data, inclusion of COVID-19 impacts, updates to risk factors, methodological improvements, and adjustments to health metrics. GBD 2021 utilized more recent data sources, offering a more accurate reflection of global health, particularly in light of the impact of COVID-19. Furthermore, it included a reassessment and enhancement of risk factors and health indicators. We hope that our research will contribute to formulating relevant policies and support achieving the 2030 global sustainable development goals.

The global burden of disease and the age-standardized prevalence of male infertility are increasing. Worldwide, fertility rates are declining, with over half of the countries and regions reporting fertility rates below replacement levels in 2021.25 Male infertility trends vary across regions and countries and do not fully correlate with the SDI. Among the five SDI regions, male fertility rates have steadily increased in low-SDI regions, although a reversal of this trend is observed approaching 2021. Moreover, ASDRs and ASPRs in the other four SDI regions have shown an increasing trend. Of particular concern is the low–middle-SDI region, which may be a key target for interventions aimed at improving global male infertility outcomes.

Oxidative stress is widely regarded as a core mechanism of male infertility, potentially leading to poor embryo development, miscarriage, and infertility.26,27 According to the Italian Society of Andrology and Sexual Medicine (SIAMS), negative lifestyle behaviors such as alcohol consumption, high BMI, and occupational exposure to heavy metals, organic solvents, and ionizing radiation adversely affect sperm morphology, motility, and oxidative stress. These factors, whether acting together or independently, may contribute to pregnancy failure. The incidence of obesity-related complications increases exponentially with visceral obesity. Male infertility is one of the primary comorbidities associated with obesity-induced systemic inflammation. The physiological changes induced by obesity that adversely affect the male reproductive endocrine system are mediated primarily through the hypothalamic-pituitary-gonadal (HPG) axis. Obesity-related inflammatory responses may disrupt the endocrine regulation of reproductive function by affecting the HPG axis and its crosstalk with other hormones.

Diabetes impacts the reproductive system at multiple levels, contributing to HPG axis dysfunction and testicular dysfunction. Testicular dysfunction appears to be the most common underlying mechanism of male infertility in diabetic men. Diabetes induces histological changes in the testicular veins and cell diameter, leading to reduced tissue perfusion and impaired testicular function. Under diabetic conditions, sperm glucose metabolism is disrupted, resulting in reduced fertility or even infertility. Additionally, elevated reactive oxygen species (ROS) levels induced by hyperglycemia and the associated oxidative stress are key contributors to diabetes-induced male infertility.28,29,30 A healthy lifestyle can potentially improve fertility and maximize the effectiveness of fertility treatments.31 Lifestyle interventions are widely recognized as the first step toward overall, reproductive, and sexual health. Many unhealthy lifestyle habits, such as smoking, alcohol consumption, and generally sedentary behavior, are key factors affecting reproductive health. Long-term ethanol exposure induces oxidative stress, increases enzymatic antioxidant levels, and causes a prolonged oxidant/antioxidant ratio imbalance. Moreover, chronic alcohol consumption is increasingly linked to epigenetic regulation and the inheritance of these modifications by the next generation, with altered paternal DNA methylation emerging as a critical factor in alcohol-related fetal growth defects.32,33

Similarly, the 2021 European Urology Association guidelines on male sexual and reproductive health emphasize that lifestyle changes, such as weight loss, exercise, and smoking cessation, can improve sperm parameters and should be recommended, as they can enhance the overall health of male partners.34 Therefore, interventions targeting high-risk factors may help reduce DNA fragmentation, improve sperm quality, and decrease the incidence of male infertility.35 However, according to our statistical analysis of the data, rapid economic globalization has exacerbated modifiable risk factors for male infertility, such as alcohol use, smoking, hyperglycemia, and high BMI, particularly in countries with relatively high levels of economic development. In contrast, countries with lower economic levels face more severe external factors (e.g., occupational hazards, environmental pollution, and lifestyle factors such as heat exposure, low birth weight, and preterm birth).36 Therefore, we believe that policies for reproductive-age men in high-income countries should focus on smoking cessation, controlling excessive alcohol consumption, and promoting targeted physical activity interventions. Environmental management and intervention are critical for restoring male fertility in economically underdeveloped regions. In these areas, greater efforts should be made to address issues such as treating toxic and harmful gas emissions, secondary processing of pollutants, and focused remediation of heavy metal contamination.

The COVID-19 pandemic has had a devastating impact on male fertility.37 The virus primarily targets the angiotensin converting enzyme (ACE-2) receptor, which is abundantly expressed in spermatogonia, testicular stroma, and Sertoli cells within the testes.38 Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been detected in significant amounts in the semen of male COVID-19 patients.39 This could lead to reduced semen volume, decreased motility, sperm deformities, lower sperm concentration, and a decline in sperm count, potentially resulting in long-lasting effects.40,41,42 SARS-CoV-2 infection induces a series of hormonal changes that threaten the HPG axis, leading to its dysfunction. In addition, complications such as fever can independently damage the male reproductive system. Acute respiratory distress syndrome (ARDS) and impaired gas exchange cause systemic hypoxia in patients with COVID-19, leading to histopathological changes in testicular tissue.43,44 Our observations indicate a significant increase in the burden of male infertility in Africa from 2019 to 2021, with the most pronounced rise occurring in this region. We attribute this to a combination of factors. Compared with other regions, many African countries have an underdeveloped healthcare infrastructure, making it challenging to control the spread of COVID-19.45 Additionally, their public health policies are inadequately developed, hindering their response to public health emergencies and leading to widespread outbreaks.46,47

In contrast, this trend is less evident in Asia, possibly due to stringent government policies effectively curbing the spread of the virus, resulting in a more stable male infertility burden. Therefore, focusing on regions with underdeveloped public health systems and implementing preemptive risk management strategies are crucial. This approach could help control or even reduce the burden of male infertility, a challenge that extends globally.45

Countries around the world face varying fertility burdens. Since 1950, fertility rates have steadily declined globally and in nearly all countries and regions, with projections indicating that this trend may continue until 2100.25 For example, Finland’s fertility rate is far below the replacement level required for population maintenance.48 Among the 204 countries and regions, only 6 are expected to have fertility rates above replacement levels by 2100, and only 26 will maintain a natural growth rate.25 Moreover, male fertility has significantly declined in recent decades, with notable increases in cases of hypogonadism, other etiologies, and idiopathic cases during this period.49 Asia carries the highest burden of male infertility which mainly contributed by India and China. Despite leading the world in male infertility ASDRs and ASPRs, China and India exhibit differing trend patterns. Understanding these trends may provide insights for refining policies.

In China, factors such as smoking, hypertension, particulate air pollution, diabetes, and high BMI significantly contribute to the increased risk of male infertility. Although the burden in China has somewhat declined in recent years, its significant population results in a substantial overall burden. Implementing detailed policies addressing environmental pollution control and treating metabolic-related diseases in China may help reduce the male infertility burden.50,51

In India, where neonatal and infant mortality rates remain high, preterm birth and low birth weight are major contributing factors. These infants face higher risks of hospitalization and mortality due to underdeveloped immune systems, and some conditions may be predetermined at birth.52 Addressing these issues through tailored public policies is essential for low- and middle-income countries,53 where early detection, prevention, and management of infertility are crucial for early identification and intervention among reproductive-aged men.54 However, only a small number of men opt to consult with urologists at a young age. Despite ongoing debate, combining urology consultations with physical exams, semen analysis, and laboratory evaluations may be beneficial and improve male health.55 Additionally, there should be more awareness campaigns regarding the risks of male infertility due to poor lifestyle behaviors.31 Cultivating specialized healthcare professionals, such as male reproductive health officers, for infertile couples should also be prioritized, alongside public health initiatives promoting healthy living. Historically, male factors contributing to infertility have been marginalized in infertility research. Notably, an analysis of 6357 articles on male infertility revealed a significant increase in publications between 1995 and 2014;56 however, a dedicated public database for andrology is still lacking. We believe that with the ongoing changes in global industrialization and economic globalization, and against the backdrop of uneven economic development worldwide, the disease burden of male infertility is likely to continue rising. However, this trend remains uncertain due to the influence of various potential factors, such as policy changes and unexpected public health events. In the future, strengthening epidemiological data collection on male infertility and establishing multicenter andrology-specific databases would significantly benefit research. We hope our study will encourage more researchers and funding initiatives to focus on andrology and address male infertility and related health issues.

LIMITATIONS

First, our extensive research is primarily based on descriptive studies and lacks experimental validation. Second, although the low–middle SDI region is particularly noteworthy, we did not conduct in-depth investigations into this region, representing a significant opportunity for future research on male infertility. We did not explore the mechanisms underlying several key risk exposures or provide detailed strategies to address them. Tailoring prevention strategies to different regions, countries, and even smaller administrative units is essential. Given the wide variation in national conditions and development levels, detailed policy improvements and recommendations must be made according to local conditions. Finally, due to sociological and related statistical survey limitations, the population we selected was 18–49 years old, which has a certain degree of research bias.

AUTHOR CONTRIBUTIONS

LZ and JXG provided conceptualization, analyzed the data, and wrote the paper. JXG, CL, and LCN contributed to the review and editing of the study. SLS, YD, MJC, and YL acquired the data. YY designed the research study. All authors read and approved the final manuscript.

COMPETING INTERESTS

All authors declared no competing interests.

Supplementary Figure 1

The changes in age-standardized disease burden across four continents.

Supplementary Figure 2

DALYs values by 10 countries from Asia over years. DALYs: disability-adjusted life years.

Supplementary Figure 3

Changes in risk factors causing the burden of disease in China.

Supplementary Figure 4

Changes in risk factors causing the burden of disease in India.