Inequalities and changes in mortality from leading causes in pre-pandemic and during COVID-19 pandemic in Lithuania

Abstract

Background

The COVID-19 pandemic has profoundly disrupted global health systems, contributing to significant shifts in mortality patterns. Beyond the direct impact of the virus, the pandemic has exacerbated existing health inequalities and introduced new inequalities in mortality from leading causes of death in Lithuania. The aim of this study was to investigate inequalities and trends in mortality from leading causes of death based on residential location, comparing the period prior to the COVID-19 pandemic with the period during the pandemic in Lithuania.

Methods

This study analyzed mortality data from 2017 to 2023 (pre-pandemic period 2017–2019, pandemic period 2020–2023) by gender, age group (< 65/65+), and place of residence (urban/rural), using data from the State Register of Death Cases and Their Causes and the Statistics Department of Lithuania. Mortality was assessed for three major causes of death: cardiovascular diseases, cancer, and respiratory diseases. The Mann–Whitney U test was used to compare groups, and Join point regression analysis was applied to evaluate trends in mortality inequalities.

Results

Among individuals aged 65+, respiratory system-related mortality rates were significantly higher during the pandemic in both urban and rural populations compared to pre-pandemic period (p = 0.001 and p = 0.003). The mortality due to respiratory system diseases showed a notable increase, particularly among females aged 65+. In urban areas, mortality increased from 17.06 to 80.68 per 100,000, while in rural areas, it rose from 25.20 to 110.40 per 100,000 (p = 0.001). Mortality from malignant neoplasms of the rectum significantly declined in rural males (AAC = -6.71, p = 0.01). Pneumonia mortality significantly declined in urban males (AAC = -7.96, p = 0.001), while rural females exhibited a significant decline in chronic obstructive pulmonary disease mortality (AAC = -25.22, p = 0.043).

Conclusions

The study reveals urban–rural and gender differences in mortality during the COVID-19 pandemic in Lithuania, with older adults—especially rural males and urban females—experiencing increased deaths from respiratory diseases, including COVID-19. These findings may also support broader discussions on reducing health inequalities and strengthening health system resilience to better prepare for future public health challenges.

Key Message

The COVID-19 pandemic disproportionately affected older adults, with significant increases in respiratory system disease-related mortality among rural males and urban females aged 65 and older, highlighting urban–rural and gender inequalities in health outcomes.

These findings emphasize the need to strengthen healthcare system resilience through improved primary care, telemedicine, and crisis preparedness to reduce health inequalities and better respond to future public health crises.

Background

The COVID-19 pandemic has profoundly disrupted global health systems, contributing to significant shifts in mortality patterns. Beyond the direct impact of the virus, the pandemic has exacerbated existing health inequalities and introduced new inequalities in mortality from leading causes of death. For instance, conditions such as cardiovascular diseases, cancer, and chronic respiratory diseases experienced variable trends, influenced by delayed diagnoses, as well as shifts in healthcare priorities. The COVID-19 pandemic has posed a serious and persistent threat to global public health and has brought significant changes to daily life. Moreover, the unprecedented scope of the worldwide pandemic has led to extraordinary demands on the healthcare system, resulting in critical shortages of medical resources and serious reductions in social capital [1].

Healthcare inequalities remain a significant issue in Lithuania. While the most recent data is limited, the 2023 European Union health report highlighted that both the overall health indicators and the efficiency of the healthcare system in Lithuania still lag significantly behind the EU average [1]. The analysis from 1990 to 2019 reveals that rural residents, both males and females, consistently experienced higher amenable mortality rates compared to urban populations throughout the study period. Although overall amenable mortality declined, the reduction was more significant among females, particularly in rural areas. However, the persistent disparities highlight the need for targeted health interventions, with a special emphasis on addressing the elevated risks faced by rural inhabitants and developing gender-specific strategies to reduce inequalities further [2]. Additionally, data from the Lithuanian Institute of Hygiene indicates persistent health inequalities among different population groups, particularly by gender, age, education, socioeconomic status, and place of residence [3]. To address these inequalities, the Lithuanian government developed the Action Plan for Reduction of Health Inequalities 2014–2023. However, the outcomes of its implementation have yet to be comprehensively evaluated. Moreover, geographic inequalities remain pronounced, with rural and lower-educated populations often experiencing worse health outcomes. This underscores the need for targeted interventions and sustained monitoring to close the health equity gap [4].

In 2018, Lithuanian treatable mortality rates were already double the EU average, indicating challenges in the effectiveness of primary and hospital care. The pandemic further disrupted disease prevention programs targeting cardiovascular diseases and treatable cancers, as well as planned specialist care, potentially worsening these pre-existing inequalities [5]. Additionally, the pandemic led to lifestyle changes, which may have long-term health implications. A study assessing sociodemographic differences in nutrition, physical activity, and body weight during the quarantine found that up to 34.9% of respondents reported changes in eating habits, mostly increased consumption, and 29.5% indicated reduced physical activity. These lifestyle changes were associated with weight gain in nearly a third of the participants, potentially increasing the risk of chronic diseases [6]. Given these factors, it is crucial to evaluate inequalities and changes in mortality from leading causes during the pre-pandemic period and the COVID-19 pandemic in Lithuania. Existing studies on health inequalities largely focus on earlier periods and do not encompass the pandemic’s timeframe. Such an analysis is essential to understanding the broader impact of the pandemic on health inequalities and to inform future policies aimed at mitigating inequalities during health crises.

Such studies are critical for examining the resilience of healthcare systems as they provide valuable insights into how well the system can adapt to, and recover from, crises such as the COVID-19 pandemic. Health system resilience is defined by its ability to maintain essential functions, deliver equitable care, and minimize disparities, even under stress. Through the analysis of health inequalities, variations in mortality rates from major causes, and disruptions in healthcare access, this study aims to identify the populations most impacted during crises and to elucidate the underlying vulnerabilities within the healthcare system. According to a study on healthcare system resilience during the COVID-19 pandemic, the crisis caused significant disruptions to healthcare services globally, with older adults experiencing the greatest challenges in accessing healthcare, which led to increased vulnerability and higher mortality rates. The authors emphasize that strengthening healthcare system resilience is crucial to ensure a more effective response to future crises [7].

Research on pre-pandemic and pandemic health outcomes sheds light on the system’s capacity to address chronic conditions, provide timely and effective care, and prevent avoidable deaths during times of strain. Moreover, these findings highlight areas where targeted interventions, resource allocations, and structural reforms are needed to enhance the system’s ability to withstand future challenges.

Incorporating these studies into resilience assessments ensures a comprehensive approach, focusing not only on immediate crisis management but also on long-term equity and sustainability in healthcare delivery. This evidence-based understanding is fundamental for building a robust and adaptable health system that prioritizes both equity and efficiency.

Pre-existing socioeconomic and regional inequalities have further shaped these outcomes, with marginalized populations bearing the brunt of the pandemic’s indirect health impact. Disparities in mortality trends across different demographic groups, healthcare systems, and geographic regions underscore the urgent need for a nuanced understanding of how the pandemic disrupted healthcare delivery and outcomes. Social determinants of health — including the accessibility and quality of healthcare and education, social and community context, economic stability, and neighborhood and built environments [3] — have had a profound influence on health inequalities not only before, but also during the COVID-19 pandemic era [2].

The aim of this study is to investigate inequalities and trends in mortality from leading causes of death based on residential location, comparing the period prior to the COVID-19 pandemic with the period during the pandemic in Lithuania.

Methods

Design of the study

The study applied a quantitative, retrospective observational design, using secondary national mortality data. Trends and inequalities in cause-specific mortality were analyzed by comparing the pre-pandemic (2017–2019) and pandemic (2020–2023) periods in Lithuania.

Data sources

Information on deaths among males and females in urban and rural areas of Lithuania was obtained from the State Register of Death Cases and Their Causes. The size of the average annual population during 2017–2023 was obtained from the Database of Indicators of Statistics Lithuania [8].

Data analysis

The data were analyzed by the place of residence (urban and rural), gender, and age group (< 65 and 65+). Urban and rural populations were categorized on the basis of the Lithuanian classification supplied by Statistics Lithuania, the categorization being as follows: (1) “urban population” refers to those persons who live in cities and towns, i.e., in the population areas with closely built permanent dwellings and with a resident population of more than 3000; (2) “rural population” refers to those persons who live in population areas without any sign of a town or city (villages, small towns, and steadings) [9]. The analysis for this study included mortality from three major causes of death in Lithuania during the period between 2017 and 2023 (pre-pandemic period 2017–2019 and pandemic period 2020–2023): cardiovascular diseases, cancer, and respiratory system diseases as well as all causes mortality [10–16]. Deaths were classified according to the underlying cause of death as recorded in the national mortality database. Mortality from cardiovascular diseases (ICD-10-I00-I99) was assessed by analyzing deaths attributed to atherosclerotic cardiovascular diseases (ICD-10-I25.0), chronic ischemic heart diseases (ICD-10-I25.9), and atherosclerotic heart diseases (ICD-10-I25.10). Mortality from cancer (ICD-10-C00-C96) was assessed by analyzing deaths attributed to malignant neoplasm of the bronchus and lung (ICD-10-C34.8), malignant neoplasm of the rectum (ICD-10-C20), and malignant neoplasm of the prostate gland (ICD-10-C61). These cancer sites were selected because they are among the leading causes of cancer-related deaths in Lithuania and reflect the main contributors to the national cancer mortality burden. Lung and colorectal cancers are consistently the most common causes of cancer mortality in both genders, while prostate cancer represents one of the predominant causes of death among men [10–16]. Focusing on these specific cancer sites allows for a more representative overview of the most relevant oncological mortality trends of the Lithuanian population.

Analysis of mortality from respiratory diseases (ICD-10-J00-J99) showed that prior to 2020, the main causes of death in this group were pneumonia (ICD-10-J18.9) and chronic obstructive pulmonary disease (ICD-10-J44). From 2020 onwards, deaths from COVID-19 (ICD-10-U07.1) were included in the analysis of respiratory mortality due to the virus’s predominant impact on the respiratory system, although it is classified under special-purpose codes in the ICD-10 [10–16]. Cases where COVID-19 (ICD-10 code U07.1 or U07.2) was identified as the underlying cause of death were included in the COVID-19–related mortality category. Deaths in which COVID-19 was listed as a contributing or associated cause, but not as the underlying cause, were excluded from this analysis. This approach was applied to ensure consistency and comparability of cause-specific mortality trends, particularly in distinguishing deaths directly attributed to COVID-19 from those resulting from comorbid conditions such as pneumonia or cardiovascular diseases. Mortality from all causes of death (ICD-10: A00–Z99) was calculated.

Mortality rates from the analyzed causes were calculated by the place of residence (urban or rural) among males and females per 100,000 population. Mortality rates were age-standardized using the European Union Standard Population (based on the EU and EFTA 2011-30 population projections) 2013 as recommended by the WHO [17].

The Mann-Whitney U test was used to compare mortality rates between different groups (before COVID-19/during COVID-19 and urban/rural areas). This non-parametric test was chosen to assess whether there were significant differences in mortality distributions, particularly for cardiovascular diseases, cancer, respiratory system diseases and all causes of death. The overall level of significance was set at p = 0.05.

For the assessment of inequality trends during 2017–2023, Join point regression analysis was applied. The three main causes of death in each mortality group were analyzed for this period. In this analysis, the best fitting points, where the rate changes significantly (increase or decrease), were chosen. Coefficients of regression multiplied by 100 were presented as average annual changes (AAC), which were considered to be statistically significant at p < 0.05.

Results

Table 1 compares the age-standardized mortality rates (ASMR) per 100,000 population among males and females in Lithuania from major causes of death in urban and rural areas between two periods - before and during the COVID-19 pandemic. The table categorizes mortality rates by cardiovascular diseases, cancer, and respiratory system diseases, further stratified by two age groups (< 65 and 65 + years).

Table 1.

Age-standardized mortality of males and females from major causes before and during pandemic in urban/rural areas in Lithuania

Cause of Death	Urban areas			Rural areas
	Before pandemic (2017–2019)	During pandemic (2020–2023)	p-value	Before pandemic (2017–2019)	During pandemic (2020–2023)	p-value
Cardiovascular diseases
Males
< 65	130.73	125.95	0.917	166.93	173.68	0.618
65+	811.99	740.25	0.610	1057.92	974.75	0.479
Females
< 65	32.00	31.16	0.819	44.96	45.41	0.507
65+	537.16	518.99	0.908	703.12	786.36	0.705
Cancers
Males
< 65	85.00	80.69	0.738	114.94	108.96	0.639
65+	331.23	299.23	0.064	360.46	336.89	0.254
Females
< 65	55.69	51.68	0.508	63.65	58.85	0.913
65+	135.66	136.26	0.856	138.48	135.51	0.681
Respiratory system diseases
Males
< 65	14.42	34.70	0.392	18.91	40.68	0.265
65+	63.23	174.48	0.001	102.79	246.89	0.003
Females
< 65	3.33	14.07	0.001	5.45	18.80	0.053
65+	17.06	80.68	0.001	25.20	110.40	0.001
All causes
Males
< 65	413.90	418.73	0.752	522.90	534.05	0.758
65+	1417.36	1431.34	0.564	1750.89	1747.19	0.283
Females
< 65	149.16	157.79	0.755	179.11	190.20	0.963
65+	817.41	872.15	0.587	999.59	1220.86	0.587

* Mortality rates calculated per 100 000 population; ** The category “Respiratory system diseases” includes COVID-19

For cardiovascular diseases, mortality rates among males remained relatively stable between the pre-pandemic (2017–2019) and pandemic (2020–2023) periods in both urban and rural populations. No statistically significant differences were observed (p > 0.05). Cancer-related mortality rates also did not show significant changes over time in either urban or rural settings. Although a slight decline is observed in cancer mortality among males aged 65 + in both areas, however, the changes were not statistically significant. In contrast, mortality due to respiratory system diseases exhibited notable differences. Among males aged 65 and older, mortality rates were significantly higher during the pandemic in both urban and rural populations, with p-values of 0.001 and 0.003. This finding suggests that the impact of COVID-19 on respiratory-related deaths was particularly pronounced among older individuals, especially in rural areas where mortality rate more than doubled. All-cause mortality among males did not demonstrate statistically significant differences (p > 0.05) between the pre-pandemic (2017–2019) and pandemic (2020–2023) periods in either urban or rural areas.

For cardiovascular diseases, mortality rates among females remained relatively stable between the pre-pandemic and pandemic periods in both urban and rural populations. No statistically significant differences were observed (p > 0.05), suggesting that the pandemic had no substantial impact on cardiovascular diseases mortality in these groups. Regarding cancer mortality, a slight but non-significant decrease was observed in both urban and rural populations for individuals aged < 65 and 65+. The p-values indicate no statistically significant differences between the two periods (p > 0.05), implying that female cancer-related mortality was not significantly affected by the COVID-19 pandemic. In contrast, mortality due to respiratory system diseases showed a notable increase. Among females younger than 65 years, mortality rose from 3.33 to 14.07 per 100,000 in urban areas (p = 0.001). A similar pattern was observed among women aged 65 and older: in urban areas, mortality increased from 17.06 to 80.68 per 100,000, while in rural areas it rose from 25.20 to 110.40 per 100,000 (p = 0.001). These differences were statistically significant (p = 0.001), indicating a substantial impact of the COVID-19 pandemic on respiratory-related deaths among older females. All-cause mortality among females did not show statistically significant differences (p > 0.05) between the pre-pandemic (2017–2019) and pandemic (2020–2023) periods in either urban or rural areas.

The analysis of ASMR for males and females reveals key differences in mortality trends before and during the COVID-19 pandemic. In both genders, cardiovascular and cancer mortality remained relatively stable, with no significant changes observed. However, respiratory system disease mortality increased significantly during the pandemic period, particularly among individuals aged 65 and older. This increase was more pronounced in males than in females, especially in rural areas, suggesting a higher vulnerability of older males to COVID-19-related respiratory complications.

Figure 1 presents AAC, years of cut-off points indicating significant trend shifts, and p-values for males and females in urban and rural areas during 2017–2023. Significant changes in mortality trends were observed for atherosclerotic cardiovascular disease (ASCVD), chronic ischemic heart disease, and atherosclerotic heart disease across different population groups. ASCVD mortality significantly increased in urban males, (AAC = 11.57, cut-off year 2020, p = 0.001), while in rural males, it decreased (AAC = -15.92, cut-off year 2023, p = 0.01). Among females, ASCVD mortality increased significantly in both urban (AAC = 7.74, cut-off year 2021, p = 0.001) and rural populations (AAC = 8.08, cut-off year 2021, p = 0.001). Chronic ischemic heart disease showed a notable decline in mortality across all groups, with statistically significant reductions in urban (AAC = -10.59, cut-off year 2023, p = 0.001) and rural males (AAC = -9.07, cut-off year 2023, p = 0.001), as well as urban (AAC = -10.95, cut-off year 2023, p = 0.001) and rural females (AAC = -11.80, cut-off year 2023, p = 0.001). Atherosclerotic heart disease mortality demonstrated a consistent downward trajectory across all population groups, with the magnitude and statistical robustness of these reductions varying by gender and place of residence. In urban areas, mortality declined significantly among males (AAC = − 12.36, cut-off year 2021, p = 0.03), while females experienced an even sharper decrease (AAC = − 14.35, cut-off year 2021, p = 0.001). Similar patterns were observed in rural areas: males showed a more moderate but still statistically significant reduction (AAC = − 9.08, cut-off year 2020, p = 0.04), whereas females exhibited one of the steepest declines (AAC = − 12.86, cut-off year 2021, p = 0.002). Trends in cancer-related mortality varied by cancer type and population group. Mortality from malignant neoplasm of the bronchi and lung showed a modest but statistically significant decline among urban males (AAC = − 3.67, cut-off year 2019, p = 0.04), while no significant changes were observed in other subgroups. However, mortality from malignant neoplasms of the rectum significantly declined among urban males (AAC = -8.32, cut-off year 2019, p = 0.001) and rural males (AAC = -6.71, cut-off year 2017, p = 0.002), while no significant changes were detected in other groups. The COVID-19 mortality trend showed no statistically significant changes across any group. However, pneumonia mortality significantly declined in urban males (AAC = -7.96, p = 0.001), while rural females exhibited a significant decline in chronic obstructive pulmonary disease (COPD) mortality (AAC = -25.22, cut-off year 2021, p = 0.043). All-cause mortality demonstrated a consistent decline across all demographic groups. Significant reductions were observed among urban males (AAC = − 2.85, cut-off year 2021, p = 0.022), urban females (AAC = − 2.30, cut-off year 2021, p = 0.001), rural males (AAC = − 1.60, cut-off year 2023, p = 0.106), and rural females (AAC = − 3.70, cut-off year 2021, p = 0.23).

Fig. 1.

Annual changes in age-standardized cause-specific mortality in urban and rural areas during the 2017–2023 period in Lithuania. Note: * – years at which significant trend shifts were identified (p < 0.05)

Table 2 shows age-standardized mortality rates per 100,000 population of males and females from major causes of death in urban and rural areas before and after the COVID-19 pandemic in Lithuania. Prior to the COVID-19 pandemic (2017–2019), both age groups (< 65 and 65+) of males had higher cardiovascular diseases mortality in rural areas than in urban areas. In the 65 + age group, the mortality rate for the rural population (1057.92) was statistically significantly higher than that for the urban population (811.99) (p = 0.008). During the pandemic (2020–2023), males mortality from cardiovascular diseases was higher in rural areas. In the age group of 65+, mortality was significantly higher in rural areas (974.75) than in urban areas (740.25) (p = 0.014). Cancer-related mortality among males showed one statistically significant difference during the pandemic period. While no significant urban–rural disparities were observed among males younger than 65 years, mortality among those aged 65 and older was significantly higher in rural areas compared with urban areas during the pandemic (p = 0.015). Prior to the pandemic, mortality for respiratory diseases was slightly higher, with a significant difference in the 65 + age group (p = 0.029) in rural areas rather than in urban areas. During the pandemic, the mortality rate in both age groups increased, but the rural population still had a higher mortality rate. However, this difference was not statistically significant during the pandemic. Statistically significant differences in all-cause mortality were observed only among males aged 65 and older. Before the pandemic, mortality in rural areas was significantly higher than in urban areas (p = 0.029). This disparity persisted during the pandemic, with rural males aged 65 and older again experiencing significantly higher all-cause mortality compared with urban males (p = 0.017).

Table 2.

Age-standardized mortality rates per 100,000 population of males and females from major causes of death in urban and rural areas before and during the pandemic in Lithuania

Cause of Death	Before pandemic (2017–2019)			During pandemic (2020–2023)
	Urban areas	Rural areas	p-value	Urban areas	Rural areas	p-value
Cardiovascular diseases
Males
< 65	130.73	166.93	0.406	125.95	173.68	0.733
65+	811.99	1057.92	0.008	740.25	974.75	0.014
Females
< 65	32.00	44.96	0.596	31.16	45.41	0.943
65+	537.16	703.12	0.148	518.99	786.36	0.031
Cancers
Males
< 65	85.00	114.94	0.993	80.69	108.96	0.826
65+	331.23	360.46	0.217	299.23	336.89	0.015
Females
< 65	55.69	63.65	0.989	51.68	58.85	0.734
65+	135.66	138.48	0.935	136.26	135.51	0.883
Respiratory system diseases
Males
< 65	14.42	18.91	0.652	34.70	40.68	0.617
65+	63.23	102.79	0.029	174.48	246.89	0.174
Females
< 65	3.33	5.45	0.840	14.07	18.80	0.603
65+	17.06	25.20	0.038	80.68	110.40	0.369
All causes
Males
< 65	413.90	522.90	0.421	418.73	534.05	0.347
65+	1417.36	1750.89	0.029	1431.34	1747.19	0.017
Females
< 65	149.16	157.79	0.869	179.11	190.20	0.592
65+	817.41	872.15	0.217	999.59	1220.86	0.121

*Mortality rates calculated per 100 000 population; ** The category “Respiratory system diseases” includes COVID-19

During the COVID-19 pandemic, among females 65 years and older, the mortality rate for the rural population (786.36) was higher than that for the urban population (518.99) (p = 0.031). In terms of cancer mortality, there was no statistically significant difference between urban and rural areas in both age groups before or during the COVID-19 pandemic. Before the COVID-19 pandemic, females’ mortality from respiratory system diseases was significantly higher in the 65 + age group (p = 0.038) in rural areas than in urban areas. There was no significant difference in respiratory system diseases mortality between urban and rural population in the age group of 65 + during the COVID-19 pandemic. No statistically significant urban–rural differences in all-cause mortality were observed among females in either age group, before or during the pandemic. All p-values for both < 65 and 65 + age groups exceeded 0.05, indicating that overall mortality did not differ meaningfully between urban and rural areas during either period.

In summary, the results highlight the differential impact of the pandemic on patients with different chronic diseases, with the highest mortality occurring in patients with respiratory diseases and some cardiovascular diseases. The findings underline the need for continuous monitoring of mortality trends, especially among vulnerable groups such as the elderly, and the importance of building health system resilience to mitigate the impact of future health crises.

Discussion

The COVID-19 pandemic is arguably the worst global public health crisis in our lifetime. Efforts to control its impact on public health and on the economy are still overwhelming governments across the world. At the time of writing this paper, the virus-related death toll exceeds over 7 million lives worldwide [18].

For many years, the structure of the causes of death of the Lithuanian population has been dominated by three main causes of death, which have remained unchanged – cardiovascular diseases, cancer, and external causes of death [19], however, instead of external causes of death, we analyzed respiratory diseases, specifically due to COVID-19.

Analysis of the results shows that there were no statistically significant differences in mortality before COVID-19 and during the COVID-19 pandemic from cardiovascular diseases and cancer between urban and rural populations, for both males and females. However, we found statistically significant differences when analyzing deaths from respiratory system diseases. Most of these deaths are known to be caused by the COVID-19 disease.

When interpreting mortality from respiratory system diseases during the COVID-19 pandemic, potential shifts in cause-of-death classification should be considered. COVID-19 frequently involves severe respiratory complications, including pneumonia, and some deaths that might previously have been attributed to respiratory diseases may have been recorded as COVID-19 during the pandemic period. In particular, pneumonia is often part of the causal pathway in COVID-19–related deaths and is commonly recorded as an intermediate rather than the underlying cause of death. As a result, pneumonia mortality based on underlying cause data may underestimate its contribution to respiratory-related mortality during 2020–2023. Therefore, changes in respiratory system disease mortality during the pandemic likely reflect both true changes in disease burden and differences in cause-of-death classification, and should be interpreted with caution.

The observed urban-rural differences in mortality from respiratory system diseases among both genders were largely explained by the factor of older age (≥ 65 years). Similar results were found in studies by other authors [20, 21]. Other authors noted that the gender differences observed in COVID-19-related deaths are not a feature of the COVID-19 pandemic but are associated with higher overall mortality [22]. Studies by other authors have shown that, while urban areas may have had a higher number of cases initially, rural areas had a higher mortality rate from COVID-19 over time. Due to delays in access to treatment and pre-existing health inequalities (e.g. higher incidence of comorbidities, such as diabetes and cardiovascular diseases), rural populations had higher mortality during the pandemic [23–25]. In our study, mortality trends during the COVID-19 pandemic differed between males and females. While cardiovascular and cancer mortality remained largely unchanged in both genders, mortality from respiratory system diseases increased markedly during the pandemic, particularly among individuals aged 65 years and older. This increase was observed in both urban and rural areas, with especially pronounced rises in rural populations. Across the 2020–2023 period, mortality among females increased more consistently, whereas among males changes were more modest. In 2023, mortality declined more clearly among males than among females, suggesting a stronger post-pandemic recovery in the male population. These differences may partly reflect higher COVID-19–related mortality among males earlier in the pandemic and the more sustained impact of health care disruptions on older women. These findings underline the importance of considering gender-specific mortality patterns when assessing the population-level effects of the COVID-19 pandemic.

Several European studies have examined differences in COVID-19 mortality between urban and rural areas, highlighting factors such as delayed access to healthcare, pre-existing health conditions, and vaccination hesitancy, which have led to higher mortality in rural areas. A population-based study analyzing national surveillance data from Germany and Italy found that while urban areas initially had higher rates of COVID-19, rural areas faced significant problems over time. The study highlights that, together with demographic characteristics such as age, hospitalization was the most important factor in the differences in COVID-19 mortality between urban and rural areas, even after controlling for other individual and regional factors, including population density and the proportion of the population over 60 years of age [26]. Several studies have shown that during the COVID-19 pandemic, older people experienced significant disruptions in access to healthcare services. The pandemic has had a significant impact on older people, especially those suffering from a range of chronic diseases, as closures, social isolation, and overcrowded health systems have limited access to basic healthcare services. These impairments have led to a deterioration in physical and mental health and exacerbated existing vulnerabilities. Research shows that health systems need to strengthen infrastructure and ensure that older people receive continuous and specialized healthcare, not only in times of crisis, but also during the recovery phase. In addition, both studies highlighted the importance of building health system resilience to better withstand future health disruptions and to reduce the negative consequences for vulnerable populations [27, 28]. Although most COVID-19 cases were initially reported in urban areas, rural areas eventually experienced higher mortality rates due to problems with access to healthcare, pre-existing health inequalities, and reluctance to vaccinate. Studies in both the US and Europe show that rural populations were particularly vulnerable due to higher rates of comorbidities, limited medical infrastructure, and socio-demographic factors such as multi-generational living. Addressing these disparities requires targeted public health interventions, better access to healthcare, and increased community outreach to reduce vaccine resistance and mitigate future health crises in rural areas.

Understanding factors which may contribute to such differences is vital, not only in addressing the continuing fallout from the current pandemic but also in preparing countries around the world for future pandemics. Factors such as health status, lifestyle, nutrition, health infrastructure, and access to healthcare services that shape life expectancy in a given region in “normal” times (i.e., health capital) may also have a crucial role in determining vulnerability to a pandemic [29]. 53.9% of respondents aged 65 and over experienced difficulties when trying to schedule an appointment with a specialist during the COVID-19 pandemic. This was the most commonly reported organizational barrier and was significantly more prevalent among individuals with lower income, lower educational attainment, and poorer self-rated health. These access issues highlight systemic inequalities that may have contributed to delayed diagnoses and poorer health outcomes in vulnerable older populations [30].

The increase in mortality from cardiovascular and respiratory diseases among elderly individuals suggests that rural populations may be facing greater health-related challenges, including difficulties in accessing healthcare services, a shortage of medical professionals, and delays in receiving significant care. Significant increase in respiratory diseases mortality, particularly in urban areas, underscores the direct impact of COVID-19 on vulnerable populations and highlights the importance of building a more resilient healthcare system capable of withstanding future health crises.

Results of this study emphasize the importance of the flexibility of the healthcare system – maintaining essential services, as well as the ability to prepare, react, and recover. A flexible healthcare system can ensure similar access to care and reduce the effect of a pandemic by maintaining continuity in treatment for chronic conditions and effectively allocating resources in times of crisis. Inequalities in mortality have shown that the healthcare system of Lithuania faced significant challenges with the adaptation of increased demands, especially in rural areas where healthcare inequalities existed before. Several critical issues must be addressed for the healthcare system to strengthen its resilience and be better prepared for pandemics and other crisis situations. To ensure hospitals can cope with sudden increases in demand, especially during emergencies, it is crucial to enhance healthcare infrastructure by expanding the workforce, enhancing medical equipment, and increasing the ongoing education of healthcare workers. Enhancing primary healthcare services is also essential as it can alleviate the strain on hospitals and deliver prompt care, particularly in isolated regions, while improving emergency response capabilities is an important strategy to increase the flexibility of the healthcare system and reduce mortality inequalities in any future public health crises. Continuous education in crisis management, including the application of telemedicine and health monitoring technologies, should also be accessible to healthcare personnel. Investment in digital technologies, such as electronic health records and telemedicine, enhances the system’s responsiveness and efficiency. To ensure prompt information dissemination and proper resource allocation during emergencies, effective intersectoral collaboration among healthcare organizations, governments, local authorities, and NGOs is critical. In addition, providing access to healthcare services is crucial for diminishing health inequalities in both distant and rural locations. Lastly, health policies should be continuously reviewed and adapted to meet changing demographic, social, and economic conditions. By addressing these areas, the healthcare system can become more resilient, responsive, and capable of providing equitable and high-quality services to all citizens, particularly to vulnerable populations.

However, several limitations of this study should be acknowledged. First, the analysis is based on routine mortality data, which do not allow for the assessment of individual-level risk factors such as comorbidities, socio-economic circumstances, or people’s actual access to healthcare services. In addition, variations in how causes of death were determined and classified during the pandemic may have influenced the observed trends in cause-specific mortality. Despite these limitations, the study offers important insights for policymakers seeking to reduce health inequalities and to strengthen the preparedness of the public health system for future challenges.

Conclusions

This study reveals differences in mortality patterns between males and females during the COVID-19 pandemic, particularly in relation to respiratory system diseases among older adults. Mortality from cardiovascular diseases and cancer remained statistically unchanged across genders and urban–rural areas. However, an increase in deaths from respiratory system diseases was observed among older age groups, with the most notable changes among rural males and urban females aged 65 years and older. The findings also suggest urban–rural differences in mortality related to respiratory system diseases, including COVID-19, with older adults appearing to be the most affected group. These patterns are broadly consistent with observations from other European and international studies. Although the study does not allow for conclusions about individual-level risk factors or causal pathways, the results add to the growing body of evidence on population-level mortality changes during the pandemic. They may also support broader discussions on reducing health inequalities and strengthening the resilience of health systems to better prepare for potential future public health challenges.

Author contributions

A.G. was responsible for drafting the introduction and methods sections, conducting the initial data processing, and compiling the relevant literature. S.S., as the academic supervisor of A.G., contributed to the statistical analysis, supported the interpretation of the results, and provided methodological and conceptual guidance throughout the research process. Both A.G. and S.S. collaboratively developed the discussion section and critically revised the manuscript. All authors reviewed and approved the final version of the manuscript for publication.

Funding

No funding was provided for this study, which was conducted as a part of the authors’ routine work.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Competing interests

The authors declare no competing interests.