Post-earthquake health-related quality of life in Afghanistan: a cross- sectional study

Post-earthquake health-related quality of life in Afghanistan: a cross- sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Post-earthquake health-related quality of life in Afghanistan: a cross- sectional study Ahmad Neyazi, Mehrab Neyazi, Mehran Neyazi, Nosaibah Razaqi, Farida Razaqi, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8863086/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 12 You are reading this latest preprint version Abstract Background: Earthquakes are among the most destructive natural disasters, causing severe physical, psychological, and social disruption. Assessing health-related quality of life (HRQoL) among survivors is essential for evidence-based recovery planning, particularly in resource-limited settings such as Afghanistan. This study evaluated HRQoL and its sociodemographic and clinical determinants among survivors of the 2023 Herat earthquake. Methods: A community-based cross-sectional study was conducted among 902 adult survivors in five earthquake-affected districts of Herat Province. Data were collected through structured face-to-face interviews between February and March 2024. HRQoL was assessed using the WHOQOL-BREF, and associations between HRQoL domains (physical, psychological, social, environmental) and independent variables were analyzed using chi-square tests. Results: Low HRQoL was reported by 38.3% of participants in the physical domain, 36.7% in the psychological domain, 28.3% in the environmental domain, and 25.7% in the social domain. Women reported significantly lower physical (44.2% vs. 30.3%; p = 0.002) and psychological (42.4% vs. 29.5%; p = 0.006) HRQoL compared with men. Widowed/divorced individuals had the highest prevalence of low HRQoL (physical: 51.5%; psychological: 48.5%; p 10 members reported nearly double the prevalence of low physical HRQoL compared with those from ≤5-member households (49.2% vs. 26.8%; p < 0.001). Low monthly income (<10,000 AFN), unemployment, chronic illness (physical: 56.8% vs. 33.5%; p < 0.001), and earthquake-related injuries (52.3% vs. 34.1%; p < 0.01) were also significantly associated with impaired HRQoL. Conclusion: Survivors of the Herat earthquake experienced substantial impairments in physical and psychological well-being. Women, widowed/divorced individuals, low-income households, and those with injuries or chronic illnesses were disproportionately affected. Targeted psychosocial support, economic assistance, and long-term rehabilitation strategies are urgently required to improve HRQoL and strengthen community resilience in earthquake-affected regions. Earthquake Afghanistan HRQoL WHOQOL-BREF Mental health Disaster recovery Introduction Earthquakes are natural disasters that occur with significant frequency and magnitude globally, posing substantial threats to human life and well-being, particularly in low- and middle-income countries (LMICs) .( 1 , 2 ) These seismic events often lead to immediate public health crises, characterized by widespread injuries, fatalities, and critical disruptions to essential health services. Beyond the immediate aftermath, earthquakes also inflict profound long-term public health consequences, including severe mental health impacts such as post-traumatic stress disorder (PTSD), anxiety, and depression, as well as mass displacement and significant compromise of health-related quality of life (HRQoL) among survivors .( 3 , 4 , 5 , 6 ). HRQoL is a multidimensional construct that encompasses an individual's subjective perception of their physical, psychological, social, and environmental well-being, extending beyond mere survival to capture the broader impact of health conditions and life circumstances on daily functioning and overall satisfaction.( 7 ) It is a crucial outcome measure in disaster contexts because it reflects the enduring challenges faced by affected populations in regaining normalcy and achieving a satisfactory standard of living ( 8 )( 9 ). Evidence from diverse post-earthquake settings consistently shows that HRQoL is substantially compromised. Studies in Turkey, Pakistan, India, Iran, and China have demonstrated that physical and psychological domains are often the most severely affected, frequently intertwined with PTSD and other mental-health conditions. ( 3 , 4 , 5 , 6 , 10 ). For instance, a study two years after the Jiuzhaigou earthquake in a minority area of China revealed significant HRQoL impairments, with mental health domains particularly affected due to high prevalence of PTSD ( 5 ), and similarly, a study conducted 10 years after the Wenchuan earthquake in China indicated that post-traumatic status, particularly PTSD, significantly influenced HRQoL ( 6 ). In Iran, older survivors of the Bam earthquake had compromised HRQoL five years after the disaster, underscoring age-related vulnerability and the need for tailored recovery policies.( 10 ) Similarly, among older adults who experienced the 2017 Pohang earthquake in South Korea, HRQoL was significantly impacted, with associated factors including age, sex, and socioeconomic status ( 4 ). This is further supported by findings from a multi-country study in South Asia, which, while focusing on severe mental illness, underscores how socioeconomic and health-related factors critically interact to shape HRQoL in LMICs. Factors such as low socioeconomic status, illiteracy, insufficient healthcare providers, and lack of effective drugs contribute to lower HRQoL in vulnerable populations ( 8 ). The study by Liang and Lu (2014) in Sichuan Province, China, highlighted the role of adaptation to harsh conditions in post-earthquake HRQoL, emphasizing the importance of social support and community resilience ( 11 ). Furthermore, Liang and Wang also demonstrated that post-earthquake rescue policies in Sichuan, China, positively influenced survivors’ HRQoL, underscoring the role of government interventions in recovery. ( 12 ) Afghanistan, a country frequently affected by earthquakes, presents a unique and particularly vulnerable context for studying HRQoL. The nation experiences frequent seismic activity, often leading to devastating consequences. For example, the recent series of earthquakes in Herat province, beginning in October 2023, caused widespread destruction, claiming thousands of lives and displacing entire communities, exacerbating an already dire humanitarian situation.( 13 , 14 , 15 ) Another significant event was the 2022 earthquake in Paktika and Khost provinces, which resulted in over 1,000 fatalities and left tens of thousands homeless, highlighting the immense and repetitive impact of these disasters( 16 ). The country's protracted conflict, weak healthcare infrastructure, and ongoing humanitarian crises further compound the vulnerabilities of its population to natural disasters ( 17 ). Displaced populations, such as Afghan refugees in Quetta, Pakistan, also experience compromised HRQoL influenced by socio-demographic factors, underscoring the broader regional challenges ( 18 ). Women and children are disproportionately affected in such crises, facing heightened risks and barriers to recovery. Despite the high frequency and severe impact of earthquakes in Afghanistan, there is a notable dearth of published evidence specifically examining post-earthquake HRQoL within this context. Given these critical gaps, this study aims to assess the HRQoL among individuals affected by recent earthquakes in Herat, Afghanistan, this research will also investigate the socio-demographic factors associated with HRQoL in this highly vulnerable population, providing crucial insights to inform humanitarian response and long-term recovery efforts. Materials and Methods Participants, Study Design, and Procedure This cross-sectional study was conducted in 2024 and involved 902 participants aged between 15 and 78 years. The participants were recruited from Herat province, Afghanistan. Data collection was carried out through face-to-face interviews conducted by five trained data collectors. A cluster convenience sampling method was employed, whereby 1,500 individuals residing in Herat province were approached near their residential or workplace areas. Out of these, 902 individuals consented to participate in the study. Participants were required to meet specific eligibility criteria: they had to be (i) residents of Afghanistan, (ii) proficient in either Dari or Pashto, and (iii) capable of providing informed consent, either in written or verbal form. Instruments The study utilized a structured survey divided into two sections. The first section gathered socio-demographic information, including age, marital status, education level, number of children, residency, and monthly family income. Additionally, participants were asked if they had experienced a "bad event" in the past month, defined as any incident that made them feel down or distressed; the interpretation of what constituted a “bad event” was left to the participants' discretion. The second section assessed participants' quality of life using the 26-item Dari version of the World Health Organization's Quality of Life-Bref (WHOQOL-Bref 26) instrument. This tool evaluates four domains of quality of life: physical health, psychological health, social relationships, and environment. Each item (e.g., “To what extent do you feel that physical pain prevents you from doing what you need to do?”) was rated on a five-point Likert scale ranging from 1 (“not at all”) to 5 (“an extreme amount”). Raw scores were subsequently converted to a 0–100 scale for consistency with the WHOQOL-100. Scores below 46 were classified as indicating low quality of life, scores between 46 and 65 indicated moderate quality of life, and scores above 65 reflected high quality of life. Analysis Data entry was conducted using Microsoft Excel 2016, while statistical analyses were performed using IBM SPSS version 27.0 for Windows. Descriptive statistics such as means, standard deviations, frequencies, and percentages were used to summarize the data. Chi-square tests were employed to assess associations between variables, and multiple regression analysis was conducted to identify independent socio-demographic factors associated with sleep disturbances and quality of life. Statistical significance was determined using a two-tailed p-value of less than 0.05. Results The study sample consisted of 902 participants, with a majority aged 15–34 years (53.9%), while 46.1% were aged 35–78 years. Females comprised 69.1% of the sample, whereas males accounted for 30.9%. Regarding marital status, most participants were married (71.6%), followed by single individuals (19.1%) and those who were widowed or divorced (9.3%). The number of children varied, with 50.1% having 1–5 children, 25.9% having none, and 23.9% reporting more than five children. Residency distribution indicated that 60.5% lived in Herat city, while 39.5% resided in the epicenter. Educational attainment showed that 44.1% were illiterate, 13.7% had completed primary school, 14.1% secondary school, 20.1% high school, and 8.0% had university education. Most participants reported low family income (71.7%), while 22.9% had middle income and only 5.3% reported high income. Additionally, 93.0% of the sample experienced a bad event in the past month, with only 7.0% reporting no such event. [Table 1] The association between participants' characteristics and their physical domain of quality of life revealed several significant findings. Age group showed a strong correlation, with older participants (35–78 years) having a higher proportion of low physical quality of life (30.5%) compared to younger participants (15–34 years) at only 5.8% (p < .001). Gender differences were also evident, with females experiencing a higher prevalence of low (19.6%) and medium (25.8%) physical quality of life compared to males (11.8% and 12.9%, respectively; p < .001). Marital status significantly influenced outcomes, as widowed/divorced individuals had the highest proportion of low physical quality of life (42.9%) compared to married (17.8%) and single participants (2.3%) (p < .001). Participants with more than five children reported notably higher rates of low (43.5%) and medium (32.4%) physical quality of life (p < .001). Education was also a significant factor, with illiterate participants showing the highest rate of low physical quality of life (28.6%), whereas those with high school education had the highest proportion of high physical quality of life (87.8%) (p < .001). Residency, family income, and experiencing a bad event in the past month were not significantly associated with physical quality of life (p = .522, .272, and .315, respectively). [Table 2] The analysis of the association between participants' characteristics and their psychological domain of quality of life revealed several significant findings. Age showed a strong correlation, with older participants (35–78 years) having a higher proportion of low psychological quality of life (32.0%) compared to younger participants (15–34 years) at 13.0% (p < .001). Females were more likely to report low (27.6%) and medium (28.4%) psychological quality of life than males (8.6% and 31.5%, respectively; p < .001). Marital status was also significantly associated, with widowed/divorced individuals reporting the highest rate of low psychological quality of life (61.9%), compared to married (19.2%) and single participants (11.6%) (p < .001). Participants with more than five children experienced the highest rates of low (38.0%) and medium (41.7%) psychological quality of life (p < .001). Education significantly influenced outcomes, with illiterate participants reporting the highest rate of low psychological quality of life (29.4%), whereas those with high school education had the highest proportion of high psychological quality of life (75.7%) (p < .001). Residency, family income, and experiencing a bad event in the past month were not significantly associated with psychological quality of life (p = .224, .070, and .149, respectively). [Table 3] The analysis of the association between participants' characteristics and their social-relationship domain of quality of life revealed several significant findings. Gender showed a strong correlation, with females experiencing higher rates of low (15.2%) and medium (27.0%) social-relationship quality of life compared to males (3.2% and 21.1%, respectively; p < .001). Marital status was also significantly associated, as widowed/divorced individuals reported the highest proportion of low (38.1%) and medium (51.2%) social-relationship quality of life compared to married and single participants (p < .001). Participants with more than five children had notably higher rates of low (12.5%) and medium (33.3%) social-relationship quality of life compared to those with fewer or no children (p < .001). Residency was significant as well, with participants from Herat city showing higher rates of low social-relationship quality of life (14.1%) compared to those from the epicenter (7.6%) (p < .001). Education also played a significant role, where illiterate participants had a higher proportion of low social-relationship quality of life (12.1%) compared to those with high school education (5.5%) (p = .002). Monthly family income was significantly associated, with low-income participants reporting lower social-relationship quality of life compared to higher-income groups (p = .039). Conversely, age group and experiencing a bad event in the past month were not significantly associated with social-relationship quality of life (p = .161 and .191, respectively). [Table 4] The analysis of the association between participants' characteristics and their environment domain of quality of life revealed several significant findings. Age was significantly associated with environmental quality of life, with older participants (35–78 years) reporting higher rates of low (15.1%) and medium (55.8%) environmental quality of life compared to younger participants (p = .012). Gender differences were notable, with females experiencing higher rates of low (17.5%) and medium (57.9%) environmental quality of life than males (4.3% and 40.5%, respectively; p < .001). Marital status showed a significant impact, where widowed/divorced individuals reported the highest proportion of low (23.8%) and medium (65.5%) environmental quality of life (p < .001). Participants with more than five children reported the highest proportion of low (16.7%) and medium (55.6%) environmental quality of life (p = .007). Residency was also a significant factor, with participants from Herat city reporting higher rates of low environmental quality of life (15.0%) compared to those from the epicenter (11.0%) (p = .021). Education played a role, with illiterate participants showing the highest proportion of low environmental quality of life (14.3%), while those with high school education reported the highest proportion of high environmental quality of life (43.1%) (p = .002). Monthly family income was strongly associated with environmental quality of life, with low-income participants reporting the highest rates of low (12.5%) and medium (56.9%) environmental quality of life (p < .001). Conversely, experiencing a bad event in the past month was not significantly associated with environmental quality of life (p = .780). [Table 5] Discussion This cross-sectional study investigating health-related quality of life (HRQoL) among 902 earthquake survivors in Herat, Afghanistan assessed physical, psychological, social relationships, and environmental domains, revealing significant disparities across various socio-demographic factors. By Utilizing Dari version of the World Health Organization Quality of Life-BREF (WHOQOL-BREF) questionnaire. (19). The findings indicate that women, older adults (35–78 years), widowed/divorced individuals, those with more than five children, and those with low education and low income are disproportionately affected by poor HRQoL following the earthquake. Interestingly, experiencing a "bad event" in the past month did not significantly impact HRQoL in any domain. In the physical domain, older participants (35–78 years) were over five times more likely to report low HRQoL (30.5% vs 5.8%, p < 0.001) compared to their younger counterparts. This aligns with existing literature demonstrating that older adults are particularly vulnerable in disaster contexts, often experiencing worse survivorship outcomes due to pre-existing health conditions, reduced mobility, and limited access to resources (10)(20)(21). For instance, a study on Bam earthquake survivors found that older people faced significant challenges in maintaining a high quality of life five years post-disaster (10). Widowed/divorced individuals exhibited the highest rates of low HRQoL in the physical domain (42.9%), which could be attributed to the cumulative stress of bereavement, social isolation, and financial strain, all of which can severely impact physical well-being. Furthermore, individuals with more than five children showed a 43.5% low HRQoL, potentially reflecting increased caregiving burdens and resource allocation challenges within larger households, which can detract from personal health and recovery efforts (22). Conversely, a high-school education was associated with 87.8% high HRQoL (p < 0.001), suggesting that educational attainment may confer protective factors such as better health literacy, improved coping strategies, and enhanced access to information and support networks (23). The psychological domain highlights significant gender disparities, with women experiencing nearly three times more low HRQoL (27.6% vs 8.6%, p < 0.001) than men. This is consistent with broader research indicating that women often report higher rates of post-traumatic stress disorder (PTSD) and general anxiety disorder (GAD) following traumatic events (6)(24)(25). For instance, studies on earthquake survivors in Turkey and China have consistently shown a negative impact of traumatic events on psychological well-being and an increased prevalence of mental health issues, with gender often emerging as a significant factor (5)(6)(22)(25). Widowed/divorced individuals also had a high rate of low psychological HRQoL (61.9%), underscoring the severe mental health consequences of marital loss compounded by disaster trauma (26)(27). This points to the critical need for gender-sensitive and bereavement-informed mental health interventions in post-disaster settings. In the social relationships domain, women demonstrated five times the rate of low HRQoL compared to men (15.2% vs 3.2%, p < 0.001), and widowed/divorced individuals faced a 38.1% low HRQoL. These findings suggest that traditional social support systems, which are crucial for recovery, may be severely disrupted for these groups (28)(29). Living in Herat city was also associated with worse social HRQoL (14.1% vs 7.6%, p < 0.001). This could be attributed to a diminished sense of community or greater social fragmentation in urban environments compared to potentially more cohesive rural communities, where social networks might be stronger (30). The concept of social vulnerability, encompassing factors like lack of social support and community cohesion, has been shown to significantly impact quality of life among various populations, including cancer survivors (28)(31)(32). The breakdown of social networks can exacerbate feelings of isolation and reduce access to informal support, hindering the recovery process. The environmental domain similarly revealed that women experienced four times the rate of low HRQoL compared to men (17.5% vs 4.3%, p < 0.001). Low income and low education were strong predictors of poorer scores, and older age and Herat city residency were also significant. Environmental HRQoL encompasses aspects such as physical safety, financial resources, access to healthcare, and home environment (33). Disasters disproportionately affect individuals with limited economic resources and educational opportunities, as they often reside in less resilient housing and have fewer means to rebuild their lives (23)(34). The observation that urban residency is linked to lower environmental HRQoL might indicate inadequate access to post-disaster infrastructure, housing, and public services within the city, or possibly heightened exposure to environmental stressors such as noise or overcrowding in temporary shelters. For example, studies highlight the significant loss to healthcare networks and reduced accessibility to medical services in post-earthquake scenarios, especially in urban areas (35). A notable finding was the non-significance of experiencing a "bad event" in the past month across all domains. This contrasts with many post-disaster studies that emphasize acute stress responses and immediate psychological distress (6)(27). This could imply that for survivors in Herat, the long-term, chronic stressors related to the earthquake's aftermath—such as displacement, loss of livelihood, and ongoing instability—might overshadow the impact of more recent, acute negative events. Alternatively, it might reflect a degree of normalization or adaptation to adverse conditions in a prolonged crisis context. It is also possible that culturally specific coping mechanisms or reporting biases might influence this particular finding. Limitation: The study's focus on Herat, while providing valuable local insights, limits the generalizability of the findings to other regions of Afghanistan or different disaster contexts. Conclusion and Recommendations The findings underscore the urgent need for targeted and tailored humanitarian interventions. Firstly, relief efforts must prioritize the most vulnerable groups: women, older adults, widowed/divorced individuals, and those with low income and education. This includes providing immediate and sustained support for housing, food security, and healthcare. Secondly, gender-sensitive programming is paramount, recognizing the unique burdens faced by women in all aspects of HRQoL. This should involve creating safe spaces, ensuring access to resources, and empowering women in decision-making processes during recovery. Thirdly, mental health and psychosocial support services must be integrated into primary healthcare, with a particular focus on addressing the psychological distress of widowed/divorced individuals and women. Lastly, long-term development strategies should focus on enhancing educational opportunities and economic empowerment, as these factors are crucial protective elements for HRQoL in post-disaster settings. Future research should transition to longitudinal designs to monitor HRQoL trajectories and identify critical periods for intervention. It is imperative to investigate the interplay between chronic post-disaster stressors and acute "bad events" to better understand their differential impacts on HRQoL. Qualitative studies using in-depth interviews and focus groups could provide a richer understanding of survivors' lived experiences, coping mechanisms, and culturally specific resilience factors. Such research could also explore the specific reasons behind the observed urban-rural disparities in social and environmental HRQoL. Expanding geographic scope beyond Herat to other affected areas in Afghanistan would provide a broader picture of post-earthquake challenges. Declarations Ethical Considerations This study was conducted in collaboration with the Herat Health Department and the Afghanistan Center for Epidemiological Studies (ACES) and received ethical approval from the ACES Ethical Review Committee (Approval No. ACES-HES-23-002). Written informed consent was obtained from all adult participants, with parental consent for minors. Participation was voluntary, with the right to withdraw at any time. Data were anonymized, securely stored, and handled in accordance with the Declaration of Helsinki. Conflict of interest The authors assert that there are no conflicts of interest to disclose. Author contributions • AN and AQM designed the study. • MN, MnN, and HA contributed to the data collection of this study. • AN analyzed the data. • SD, FR, and NR prepared the draft of the manuscript. • AN critically reviewed, rewrote, edited, and finalized the manuscript. • All authors reviewed the manuscript. Funding This research received no external funding. Consent for publication Not applicable. Clinical trial number Not applicable. Data availability The datasets utilized and/or analyzed in the course of the present study are accessible from the corresponding author upon reasonable inquiry. References United Nations Office for Disaster Risk Reduction (UNDRR), Centre for Research on the Epidemiology of Disasters (CRED). Poverty & death: disaster mortality 1996–2015 [Internet]. Geneva/Brussels: UNDRR & CRED; 2016 [cited 2025 Sep 19]. Available from: https://www.preventionweb.net/files/50589_creddisastermortalityallfinalpdf.pdf Centre for Research on the Epidemiology of Disasters (CRED). EM-DAT 2023 annual report [Internet]. Brussels: CRED; 2024 [cited 2025 Sep 19]. Available from: https://files.emdat.be/reports/2023_EMDAT_report.pdf Ataya J, Soqia J, Ataya J, AlMhasneh R, Batesh D, Alkhadraa D, Albokaai H, Morjan M. Sleep quality and mental health differences following Syria-Turkey earthquakes: A cross-sectional study. International Journal of Social Psychiatry. 2024 Jun;70(4):700-8. Kim EM, Kim GS, Kim H, Park CG, Lee O, Pfefferbaum B. Health-related quality of life among older adults who experienced the Pohang earthquake in South Korea: A cross-sectional survey. Health and quality of life outcomes. 2022 Mar 4;20(1):37. Zhang X, Gao Y, Dai X, Zhou J, Yan L, Hou F, Yuan P, Wen J. Health-related quality of life among survivors in minority area 2 years after Jiuzhaigou earthquake: a cross-sectional study. Medicine. 2021 Mar 12;100(10):e25089. Zhang L, Wang Y, Huang X, Lan M, Ji H. Influence of post-traumatic status on health-related quality of life among survivors 10 years after the Wenchuan earthquake in China. Annals of Palliative Medicine. 2021 Mar;10(3):3059066-3066. Whoqol Group. Development of the World Health Organization WHOQOL-BREF quality of life assessment. Psychological medicine. 1998 May;28(3):551-8. Sharma A, Nisa BU, Bibi H, Wiggins F, Mitchell A, Prasad K, Appuhamy K, Garcia OP, Zavala GA. Factors associated with health-related quality of life in people with severe mental illness: Results from a multicountry study in South Asia. medRxiv. 2025 Aug 1:2025-08. Maheri M, Alipour M, Rohban A, Garmaroudi G. The association of resilience with health-related quality of life (HRQoL) in adolescent students. International Journal of Adolescent Medicine and Health. 2022 Feb 28;34(1):20190050. Ardalan A, Mazaheri M, Vanrooyen M, Mowafi H, Nedjat S, Naieni KH, Russel M. Post-disaster quality of life among older survivors five years after the Bam earthquake: implications for recovery policy. Ageing & Society. 2011 Feb;31(2):179-96. Liang Y, Lu P. Health-related quality of life and the adaptation of residents to harsh post-earthquake conditions in China. Disaster medicine and public health preparedness. 2014 Oct;8(5):390-6. Liang Y, Wang X. Developing a new perspective to study the health of survivors of Sichuan earthquakes in China: a study on the effect of post-earthquake rescue policies on survivors’ health-related quality of life. Health Research Policy and Systems. 2013 Oct 29;11(1):41. Neyazi A, Mohammadi B, Griffiths MD. The impact of the 2023 earthquakes on the Afghan health-care system. The Lancet. 2023 Nov 18;402(10415):1829-30. Earthquake Hazards Program. M 6.3 – 32 km NNE of Zindah Jān, Afghanistan [Internet]. 2023 [cited 2025 Sep 19]. Available from: https://earthquake.usgs.gov/earthquakes/eventpage/us6000ldpg/executive World Health Organization, Eastern Mediterranean Regional Office. Earthquake in Herat province: situation reports (Oct–Nov 2023) [Internet]. 2023–2024 [cited 2025 Sep 19]. Available from: https://www.emro.who.int/afg/information-resources/earthquake-in-herat-province-situation-reports.html United Nations Office for the Coordination of Humanitarian Affairs (OCHA). Flash update #3: earthquake in Paktika and Khost, Afghanistan (25 Jun 2022) [Internet]. 2022 [cited 2025 Sep 19]. Available from: https://www.unocha.org/publications/report/afghanistan/afghanistan-flash-update-3-earthquake-paktika-and-khost-provinces-afghanistan-25-june-2022 Maehira Y, Spencer RC. Harmonization of biosafety and biosecurity standards for high-containment facilities in low-and middle-income countries: an approach from the perspective of occupational safety and health. Frontiers in Public Health. 2019 Sep 12;7:249. Kaleem S, Ahmad T, Wahid A, Khan HH, Mallhi TH, Al-Worafi YM, Alam A, Khan A, Khan YH, Khan FU. Assessment of health-related quality of life among Afghan refugees in Quetta, Pakistan. Plos one. 2024 Feb 1;19(2):e0288834. Shayan NA, Eser E, Neyazi A, Eser S. Reliability and validity of the Dari version of the World Health Organization Quality of Life (WHOQOL-BREF) Questionnaire in Afghanistan. Turkish Journal of Public Health. 2020;19(3):263-73. Tian W, Jia Z, Duan G, Liu W, Pan X, Guo Q, Chen R, Zhang X. Longitudinal study on health-related quality of life among child and adolescent survivors of the 2008 Sichuan earthquake. Quality of Life Research. 2013 May;22(4):745-52. Adams C, Gringart E, Strobel N. Barriers to mental health help-seeking among older adults with chronic diseases. Australian Psychologist. 2024 Mar 3;59(2):154-65. Mao SJ, Shen J, Xu F, Zou CC. Quality of life in caregivers of young children with Prader–Willi syndrome. World Journal of Pediatrics. 2019 Oct;15(5):506-10. Gim J, Shin S. Disaster vulnerability and community resilience factors affecting post-disaster wellness: A longitudinal analysis of the Survey on the Change of Life of Disaster Victim. International Journal of Disaster Risk Reduction. 2022 Oct 15;81:103273. Alekozay M, Mohmand NA, Sadat SJ, Ahmadzadeh EA, Hamedi T, Rahimi T, Najm AF. Interplay of Post-Traumatic Stress Disorder, General Anxiety Disorder and Resilience among Earthquake Survivors in Zinda Jan District of Herat Province. Nangarhar University International Journal of Biosciences. 2023 Dec 30;2(04):104-14. Yıldırım E, Güdücü N. The Investigation of Quality of Life and Post-traumatic Stress Disorder Levels of Midwifery Students Experiencing an Earthquake. Disaster Medicine and Public Health Preparedness. 2024 Jan;18:e328. Farina M, Moret-Tatay C, Paloski LH, Irigaray TQ. Neuroticism and quality of life: testing for mediated effects of anxiety in older adults without cognitive impairment. Ageing International. 2021 Mar;46(1):83-94. Carlsson JM, Mortensen EL, Kastrup M. Predictors of mental health and quality of life in male tortured refugees. Nordic journal of psychiatry. 2006 Jan 1;60(1):51-7. Carnahan LR, Rauscher GH, Watson KS, Altfeld S, Zimmermann K, Ferrans CE, Molina Y. Comparing the roles of social context, networks, and perceived social functioning with health-related quality of life among self-reported rural female cancer survivors. Supportive Care in Cancer. 2021 Jan;29(1):331-40. Gruszczyńska E, Rzeszutek M. Trajectories of health-related quality of life and perceived social support among people living with HIV undergoing antiretroviral treatment: does gender matter?. Frontiers in Psychology. 2019 Jul 23;10:1664. Wippold GM, Garcia KA, Frary SG. The role of sense of community in improving the health‐related quality of life among Black Americans. Journal of community psychology. 2023 Jan;51(1):251-69. Møller JJ, la Cour K, Pilegaard MS, Dalton SO, Bidstrup PE, Möller S, Jarlbaek L. Social vulnerability among cancer patients and changes in vulnerability during their trajectories–A longitudinal population-based study. Cancer epidemiology. 2023 Aug 1;85:102401. Ang WH, Lau Y, Ngo LP, Siew AL, Ang NK, Lopez V. Path analysis of survivorship care needs, symptom experience, and quality of life among multiethnic cancer survivors. Supportive Care in Cancer. 2021 Mar;29(3):1433-41. Qu GB, Zhao TY, Zhu BW, Tzeng GH, Huang SL. Use of a modified DANP-mV model to improve quality of life in rural residents: The empirical case of Xingshisi village, China. International journal of environmental research and public health. 2019 Jan;16(1):153. Liang Y. Satisfaction with economic and social rights and quality of life in a post-disaster zone in China: evidence from earthquake-prone Sichuan. Disaster medicine and public health preparedness. 2015 Apr;9(2):111-8. Pei S, Zhai C, Hu J, Liu J, Song Z. Seismic functionality of healthcare network considering traffic congestion and hospital malfunctioning: A medical accessibility approach. International journal of disaster risk reduction. 2023 Oct 15;97:104019. Tables Tables 1 to 5 are available in the supplementary files section Additional Declarations No competing interests reported. Supplementary Files Tables.docx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 14 Apr, 2026 Reviews received at journal 20 Mar, 2026 Reviews received at journal 18 Mar, 2026 Reviewers agreed at journal 17 Mar, 2026 Reviewers agreed at journal 15 Mar, 2026 Reviews received at journal 10 Mar, 2026 Reviewers agreed at journal 09 Mar, 2026 Reviewers invited by journal 09 Mar, 2026 Editor invited by journal 16 Feb, 2026 Editor assigned by journal 16 Feb, 2026 Submission checks completed at journal 16 Feb, 2026 First submitted to journal 12 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8863086","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":603527965,"identity":"7828f0d5-fb49-4f37-abab-455a4d0e563b","order_by":0,"name":"Ahmad Neyazi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYNACAwYGfiiTH69CFC2SDRAmjCZG1wFitZiz9xh+/FHAIG98/PDDhz8Y7CQY2Hsfv8CnxbLnjLGEhAGD4bYzacbGPAzJEgw8x80s8LrnRo6BhIEBA+O2Azls0oz/mOsYJNLYDPBquf/G+EeCAYP95v437D9/MNRLENZyg8dM4oABQ+IGiRw2Bh6GwyAtzA/wajmTVmbZYCCRPOPGM2NpHobjEmw8x9jw6WAwOH54880ff2xs+/uTH378wVAtwc/exvwBrx4GDpDDJRB8oBVsEjhVgwE7psMJ2TIKRsEoGAUjDAAAePtASo5zg8UAAAAASUVORK5CYII=","orcid":"","institution":"Afghanistan Center for Epidemiological Studies","correspondingAuthor":true,"prefix":"","firstName":"Ahmad","middleName":"","lastName":"Neyazi","suffix":""},{"id":603527966,"identity":"721d124a-cf07-44df-84aa-bd2a5c3ce558","order_by":1,"name":"Mehrab Neyazi","email":"","orcid":"","institution":"Afghanistan Medical Students Association","correspondingAuthor":false,"prefix":"","firstName":"Mehrab","middleName":"","lastName":"Neyazi","suffix":""},{"id":603527967,"identity":"6469a2c1-593b-487d-988f-321ea9529cc9","order_by":2,"name":"Mehran Neyazi","email":"","orcid":"","institution":"Afghanistan Center for Epidemiological Studies","correspondingAuthor":false,"prefix":"","firstName":"Mehran","middleName":"","lastName":"Neyazi","suffix":""},{"id":603527968,"identity":"87d0b049-cf73-4e88-abf0-131e8c535079","order_by":3,"name":"Nosaibah Razaqi","email":"","orcid":"","institution":"Afghanistan Center for Epidemiological Studies","correspondingAuthor":false,"prefix":"","firstName":"Nosaibah","middleName":"","lastName":"Razaqi","suffix":""},{"id":603527969,"identity":"8f0e3833-18c1-40a9-8026-5aaf3ec4e61d","order_by":4,"name":"Farida Razaqi","email":"","orcid":"","institution":"Afghanistan Center for Epidemiological Studies","correspondingAuthor":false,"prefix":"","firstName":"Farida","middleName":"","lastName":"Razaqi","suffix":""},{"id":603527970,"identity":"21cd1134-f7b0-4715-8f1a-4c44f2d297e9","order_by":5,"name":"Selselah Dost","email":"","orcid":"","institution":"Afghanistan Center for Epidemiological Studies","correspondingAuthor":false,"prefix":"","firstName":"Selselah","middleName":"","lastName":"Dost","suffix":""},{"id":603527971,"identity":"ea34736a-d28f-4008-904f-2d1eab280f36","order_by":6,"name":"Habibah Afzali","email":"","orcid":"","institution":"Afghanistan Center for Epidemiological Studies","correspondingAuthor":false,"prefix":"","firstName":"Habibah","middleName":"","lastName":"Afzali","suffix":""},{"id":603527972,"identity":"b47aaf6a-e013-403c-a40f-eb2082c84bab","order_by":7,"name":"Abdul Qadim Mohammadi","email":"","orcid":"","institution":"Herat Regional Hospital","correspondingAuthor":false,"prefix":"","firstName":"Abdul","middleName":"Qadim","lastName":"Mohammadi","suffix":""}],"badges":[],"createdAt":"2026-02-12 14:23:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8863086/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8863086/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104473864,"identity":"748ec67a-7c5e-4bf4-8c4d-29342f25bede","added_by":"auto","created_at":"2026-03-12 07:49:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":472109,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8863086/v1/a4f3633b-0b92-4752-805f-70157b613122.pdf"},{"id":104473863,"identity":"cdca7e98-6a3e-402f-ba6a-881b6a1c168e","added_by":"auto","created_at":"2026-03-12 07:49:44","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":31148,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-8863086/v1/8d1174afc6dc9e68fdb60e06.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Post-earthquake health-related quality of life in Afghanistan: a cross- sectional study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEarthquakes are natural disasters that occur with significant frequency and magnitude globally, posing substantial threats to human life and well-being, particularly in low- and middle-income countries (LMICs) .(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) These seismic events often lead to immediate public health crises, characterized by widespread injuries, fatalities, and critical disruptions to essential health services. Beyond the immediate aftermath, earthquakes also inflict profound long-term public health consequences, including severe mental health impacts such as post-traumatic stress disorder (PTSD), anxiety, and depression, as well as mass displacement and significant compromise of health-related quality of life (HRQoL) among survivors .(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHRQoL is a multidimensional construct that encompasses an individual's subjective perception of their physical, psychological, social, and environmental well-being, extending beyond mere survival to capture the broader impact of health conditions and life circumstances on daily functioning and overall satisfaction.(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) It is a crucial outcome measure in disaster contexts because it reflects the enduring challenges faced by affected populations in regaining normalcy and achieving a satisfactory standard of living (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e)(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Evidence from diverse post-earthquake settings consistently shows that HRQoL is substantially compromised. Studies in Turkey, Pakistan, India, Iran, and China have demonstrated that physical and psychological domains are often the most severely affected, frequently intertwined with PTSD and other mental-health conditions. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). For instance, a study two years after the Jiuzhaigou earthquake in a minority area of China revealed significant HRQoL impairments, with mental health domains particularly affected due to high prevalence of PTSD (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), and similarly, a study conducted 10 years after the Wenchuan earthquake in China indicated that post-traumatic status, particularly PTSD, significantly influenced HRQoL (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). In Iran, older survivors of the Bam earthquake had compromised HRQoL five years after the disaster, underscoring age-related vulnerability and the need for tailored recovery policies.(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) Similarly, among older adults who experienced the 2017 Pohang earthquake in South Korea, HRQoL was significantly impacted, with associated factors including age, sex, and socioeconomic status (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). This is further supported by findings from a multi-country study in South Asia, which, while focusing on severe mental illness, underscores how socioeconomic and health-related factors critically interact to shape HRQoL in LMICs. Factors such as low socioeconomic status, illiteracy, insufficient healthcare providers, and lack of effective drugs contribute to lower HRQoL in vulnerable populations (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe study by Liang and Lu (2014) in Sichuan Province, China, highlighted the role of adaptation to harsh conditions in post-earthquake HRQoL, emphasizing the importance of social support and community resilience (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Furthermore, Liang and Wang also demonstrated that post-earthquake rescue policies in Sichuan, China, positively influenced survivors\u0026rsquo; HRQoL, underscoring the role of government interventions in recovery. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eAfghanistan, a country frequently affected by earthquakes, presents a unique and particularly vulnerable context for studying HRQoL. The nation experiences frequent seismic activity, often leading to devastating consequences. For example, the recent series of earthquakes in Herat province, beginning in October 2023, caused widespread destruction, claiming thousands of lives and displacing entire communities, exacerbating an already dire humanitarian situation.(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) Another significant event was the 2022 earthquake in Paktika and Khost provinces, which resulted in over 1,000 fatalities and left tens of thousands homeless, highlighting the immense and repetitive impact of these disasters(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). The country's protracted conflict, weak healthcare infrastructure, and ongoing humanitarian crises further compound the vulnerabilities of its population to natural disasters (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Displaced populations, such as Afghan refugees in Quetta, Pakistan, also experience compromised HRQoL influenced by socio-demographic factors, underscoring the broader regional challenges (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Women and children are disproportionately affected in such crises, facing heightened risks and barriers to recovery. Despite the high frequency and severe impact of earthquakes in Afghanistan, there is a notable dearth of published evidence specifically examining post-earthquake HRQoL within this context.\u003c/p\u003e \u003cp\u003eGiven these critical gaps, this study aims to assess the HRQoL among individuals affected by recent earthquakes in Herat, Afghanistan, this research will also investigate the socio-demographic factors associated with HRQoL in this highly vulnerable population, providing crucial insights to inform humanitarian response and long-term recovery efforts.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants, Study Design, and Procedure\u003c/h2\u003e \u003cp\u003e This cross-sectional study was conducted in 2024 and involved 902 participants aged between 15 and 78 years. The participants were recruited from Herat province, Afghanistan. Data collection was carried out through face-to-face interviews conducted by five trained data collectors. A cluster convenience sampling method was employed, whereby 1,500 individuals residing in Herat province were approached near their residential or workplace areas. Out of these, 902 individuals consented to participate in the study.\u003c/p\u003e \u003cp\u003eParticipants were required to meet specific eligibility criteria: they had to be (i) residents of Afghanistan, (ii) proficient in either Dari or Pashto, and (iii) capable of providing informed consent, either in written or verbal form.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eInstruments\u003c/h3\u003e\n\u003cp\u003eThe study utilized a structured survey divided into two sections. The first section gathered socio-demographic information, including age, marital status, education level, number of children, residency, and monthly family income. Additionally, participants were asked if they had experienced a \"bad event\" in the past month, defined as any incident that made them feel down or distressed; the interpretation of what constituted a \u0026ldquo;bad event\u0026rdquo; was left to the participants' discretion.\u003c/p\u003e \u003cp\u003eThe second section assessed participants' quality of life using the 26-item Dari version of the World Health Organization's Quality of Life-Bref (WHOQOL-Bref 26) instrument. This tool evaluates four domains of quality of life: physical health, psychological health, social relationships, and environment. Each item (e.g., \u0026ldquo;To what extent do you feel that physical pain prevents you from doing what you need to do?\u0026rdquo;) was rated on a five-point Likert scale ranging from 1 (\u0026ldquo;not at all\u0026rdquo;) to 5 (\u0026ldquo;an extreme amount\u0026rdquo;). Raw scores were subsequently converted to a 0\u0026ndash;100 scale for consistency with the WHOQOL-100. Scores below 46 were classified as indicating low quality of life, scores between 46 and 65 indicated moderate quality of life, and scores above 65 reflected high quality of life.\u003c/p\u003e\n\u003ch3\u003eAnalysis\u003c/h3\u003e\n\u003cp\u003eData entry was conducted using Microsoft Excel 2016, while statistical analyses were performed using IBM SPSS version 27.0 for Windows. Descriptive statistics such as means, standard deviations, frequencies, and percentages were used to summarize the data. Chi-square tests were employed to assess associations between variables, and multiple regression analysis was conducted to identify independent socio-demographic factors associated with sleep disturbances and quality of life. Statistical significance was determined using a two-tailed p-value of less than 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe study sample consisted of 902 participants, with a majority aged 15\u0026ndash;34 years (53.9%), while 46.1% were aged 35\u0026ndash;78 years. Females comprised 69.1% of the sample, whereas males accounted for 30.9%. Regarding marital status, most participants were married (71.6%), followed by single individuals (19.1%) and those who were widowed or divorced (9.3%). The number of children varied, with 50.1% having 1\u0026ndash;5 children, 25.9% having none, and 23.9% reporting more than five children. Residency distribution indicated that 60.5% lived in Herat city, while 39.5% resided in the epicenter. Educational attainment showed that 44.1% were illiterate, 13.7% had completed primary school, 14.1% secondary school, 20.1% high school, and 8.0% had university education. Most participants reported low family income (71.7%), while 22.9% had middle income and only 5.3% reported high income. Additionally, 93.0% of the sample experienced a bad event in the past month, with only 7.0% reporting no such event. \u003cstrong\u003e[Table 1]\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe association between participants\u0026apos; characteristics and their physical domain of quality of life revealed several significant findings. Age group showed a strong correlation, with older participants (35\u0026ndash;78 years) having a higher proportion of low physical quality of life (30.5%) compared to younger participants (15\u0026ndash;34 years) at only 5.8% (p \u0026lt; .001). Gender differences were also evident, with females experiencing a higher prevalence of low (19.6%) and medium (25.8%) physical quality of life compared to males (11.8% and 12.9%, respectively; p \u0026lt; .001). Marital status significantly influenced outcomes, as widowed/divorced individuals had the highest proportion of low physical quality of life (42.9%) compared to married (17.8%) and single participants (2.3%) (p \u0026lt; .001). Participants with more than five children reported notably higher rates of low (43.5%) and medium (32.4%) physical quality of life (p \u0026lt; .001). Education was also a significant factor, with illiterate participants showing the highest rate of low physical quality of life (28.6%), whereas those with high school education had the highest proportion of high physical quality of life (87.8%) (p \u0026lt; .001). Residency, family income, and experiencing a bad event in the past month were not significantly associated with physical quality of life (p = .522, .272, and .315, respectively). \u003cstrong\u003e[Table 2]\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis of the association between participants\u0026apos; characteristics and their psychological domain of quality of life revealed several significant findings. Age showed a strong correlation, with older participants (35\u0026ndash;78 years) having a higher proportion of low psychological quality of life (32.0%) compared to younger participants (15\u0026ndash;34 years) at 13.0% (p \u0026lt; .001). Females were more likely to report low (27.6%) and medium (28.4%) psychological quality of life than males (8.6% and 31.5%, respectively; p \u0026lt; .001). Marital status was also significantly associated, with widowed/divorced individuals reporting the highest rate of low psychological quality of life (61.9%), compared to married (19.2%) and single participants (11.6%) (p \u0026lt; .001). Participants with more than five children experienced the highest rates of low (38.0%) and medium (41.7%) psychological quality of life (p \u0026lt; .001). Education significantly influenced outcomes, with illiterate participants reporting the highest rate of low psychological quality of life (29.4%), whereas those with high school education had the highest proportion of high psychological quality of life (75.7%) (p \u0026lt; .001). Residency, family income, and experiencing a bad event in the past month were not significantly associated with psychological quality of life (p = .224, .070, and .149, respectively). [Table 3]\u003c/p\u003e\n\u003cp\u003eThe analysis of the association between participants\u0026apos; characteristics and their social-relationship domain of quality of life revealed several significant findings. Gender showed a strong correlation, with females experiencing higher rates of low (15.2%) and medium (27.0%) social-relationship quality of life compared to males (3.2% and 21.1%, respectively; p \u0026lt; .001). Marital status was also significantly associated, as widowed/divorced individuals reported the highest proportion of low (38.1%) and medium (51.2%) social-relationship quality of life compared to married and single participants (p \u0026lt; .001). Participants with more than five children had notably higher rates of low (12.5%) and medium (33.3%) social-relationship quality of life compared to those with fewer or no children (p \u0026lt; .001). Residency was significant as well, with participants from Herat city showing higher rates of low social-relationship quality of life (14.1%) compared to those from the epicenter (7.6%) (p \u0026lt; .001). Education also played a significant role, where illiterate participants had a higher proportion of low social-relationship quality of life (12.1%) compared to those with high school education (5.5%) (p = .002). Monthly family income was significantly associated, with low-income participants reporting lower social-relationship quality of life compared to higher-income groups (p = .039). Conversely, age group and experiencing a bad event in the past month were not significantly associated with social-relationship quality of life (p = .161 and .191, respectively). \u003cstrong\u003e[Table 4]\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The analysis of the association between participants\u0026apos; characteristics and their environment domain of quality of life revealed several significant findings. Age was significantly associated with environmental quality of life, with older participants (35\u0026ndash;78 years) reporting higher rates of low (15.1%) and medium (55.8%) environmental quality of life compared to younger participants (p = .012). Gender differences were notable, with females experiencing higher rates of low (17.5%) and medium (57.9%) environmental quality of life than males (4.3% and 40.5%, respectively; p \u0026lt; .001). Marital status showed a significant impact, where widowed/divorced individuals reported the highest proportion of low (23.8%) and medium (65.5%) environmental quality of life (p \u0026lt; .001). Participants with more than five children reported the highest proportion of low (16.7%) and medium (55.6%) environmental quality of life (p = .007). Residency was also a significant factor, with participants from Herat city reporting higher rates of low environmental quality of life (15.0%) compared to those from the epicenter (11.0%) (p = .021). Education played a role, with illiterate participants showing the highest proportion of low environmental quality of life (14.3%), while those with high school education reported the highest proportion of high environmental quality of life (43.1%) (p = .002). Monthly family income was strongly associated with environmental quality of life, with low-income participants reporting the highest rates of low (12.5%) and medium (56.9%) environmental quality of life (p \u0026lt; .001). Conversely, experiencing a bad event in the past month was not significantly associated with environmental quality of life (p = .780). \u003cstrong\u003e[Table 5]\u003c/strong\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis cross-sectional study investigating health-related quality of life (HRQoL) among 902 earthquake survivors in Herat, Afghanistan assessed physical, psychological, social relationships, and environmental domains, revealing significant disparities across various socio-demographic factors. By Utilizing Dari version of the World Health Organization Quality of Life-BREF (WHOQOL-BREF) questionnaire. (19). The findings indicate that women, older adults (35\u0026ndash;78 years), widowed/divorced individuals, those with more than five children, and those with low education and low income are disproportionately affected by poor HRQoL following the earthquake. Interestingly, experiencing a \u0026quot;bad event\u0026quot; in the past month did not significantly impact HRQoL in any domain.\u003c/p\u003e\n\u003cp\u003eIn the physical domain, older participants (35\u0026ndash;78 years) were over five times more likely to report low HRQoL (30.5% vs 5.8%, p \u0026lt; 0.001) compared to their younger counterparts. This aligns with existing literature demonstrating that older adults are particularly vulnerable in disaster contexts, often experiencing worse survivorship outcomes due to pre-existing health conditions, reduced mobility, and limited access to resources (10)(20)(21). For instance, a study on Bam earthquake survivors found that older people faced significant challenges in maintaining a high quality of life five years post-disaster (10). Widowed/divorced individuals exhibited the highest rates of low HRQoL in the physical domain (42.9%), which could be attributed to the cumulative stress of bereavement, social isolation, and financial strain, all of which can severely impact physical well-being. Furthermore, individuals with more than five children showed a 43.5% low HRQoL, potentially reflecting increased caregiving burdens and resource allocation challenges within larger households, which can detract from personal health and recovery efforts (22). Conversely, a high-school education was associated with 87.8% high HRQoL (p \u0026lt; 0.001), suggesting that educational attainment may confer protective factors such as better health literacy, improved coping strategies, and enhanced access to information and support networks (23).\u003c/p\u003e\n\u003cp\u003eThe psychological domain highlights significant gender disparities, with women experiencing nearly three times more low HRQoL (27.6% vs 8.6%, p \u0026lt; 0.001) than men. This is consistent with broader research indicating that women often report higher rates of post-traumatic stress disorder (PTSD) and general anxiety disorder (GAD) following traumatic events (6)(24)(25). For instance, studies on earthquake survivors in Turkey and China have consistently shown a negative impact of traumatic events on psychological well-being and an increased prevalence of mental health issues, with gender often emerging as a significant factor (5)(6)(22)(25). Widowed/divorced individuals also had a high rate of low psychological HRQoL (61.9%), underscoring the severe mental health consequences of marital loss compounded by disaster trauma (26)(27). This points to the critical need for gender-sensitive and bereavement-informed mental health interventions in post-disaster settings.\u003c/p\u003e\n\u003cp\u003eIn the social relationships domain, women demonstrated five times the rate of low HRQoL compared to men (15.2% vs 3.2%, p \u0026lt; 0.001), and widowed/divorced individuals faced a 38.1% low HRQoL. These findings suggest that traditional social support systems, which are crucial for recovery, may be severely disrupted for these groups (28)(29). Living in Herat city was also associated with worse social HRQoL (14.1% vs 7.6%, p \u0026lt; 0.001). This could be attributed to a diminished sense of community or greater social fragmentation in urban environments compared to potentially more cohesive rural communities, where social networks might be stronger (30). The concept of social vulnerability, encompassing factors like lack of social support and community cohesion, has been shown to significantly impact quality of life among various populations, including cancer survivors (28)(31)(32). The breakdown of social networks can exacerbate feelings of isolation and reduce access to informal support, hindering the recovery process.\u003c/p\u003e\n\u003cp\u003eThe environmental domain similarly revealed that women experienced four times the rate of low HRQoL compared to men (17.5% vs 4.3%, p \u0026lt; 0.001). Low income and low education were strong predictors of poorer scores, and older age and Herat city residency were also significant. Environmental HRQoL encompasses aspects such as physical safety, financial resources, access to healthcare, and home environment (33). Disasters disproportionately affect individuals with limited economic resources and educational opportunities, as they often reside in less resilient housing and have fewer means to rebuild their lives (23)(34). The observation that urban residency is linked to lower environmental HRQoL might indicate inadequate access to post-disaster infrastructure, housing, and public services within the city, or possibly heightened exposure to environmental stressors such as noise or overcrowding in temporary shelters. For example, studies highlight the significant loss to healthcare networks and reduced accessibility to medical services in post-earthquake scenarios, especially in urban areas (35).\u003c/p\u003e\n\u003cp\u003eA notable finding was the non-significance of experiencing a \u0026quot;bad event\u0026quot; in the past month across all domains. This contrasts with many post-disaster studies that emphasize acute stress responses and immediate psychological distress (6)(27). This could imply that for survivors in Herat, the long-term, chronic stressors related to the earthquake\u0026apos;s aftermath\u0026mdash;such as displacement, loss of livelihood, and ongoing instability\u0026mdash;might overshadow the impact of more recent, acute negative events. Alternatively, it might reflect a degree of normalization or adaptation to adverse conditions in a prolonged crisis context. It is also possible that culturally specific coping mechanisms or reporting biases might influence this particular finding.\u003c/p\u003e\n\u003cp\u003eLimitation: The study\u0026apos;s focus on Herat, while providing valuable local insights, limits the generalizability of the findings to other regions of Afghanistan or different disaster contexts.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion and Recommendations","content":"\u003cp\u003eThe findings underscore the urgent need for targeted and tailored humanitarian interventions. Firstly, relief efforts must prioritize the most vulnerable groups: women, older adults, widowed/divorced individuals, and those with low income and education. This includes providing immediate and sustained support for housing, food security, and healthcare. Secondly, gender-sensitive programming is paramount, recognizing the unique burdens faced by women in all aspects of HRQoL. This should involve creating safe spaces, ensuring access to resources, and empowering women in decision-making processes during recovery. Thirdly, mental health and psychosocial support services must be integrated into primary healthcare, with a particular focus on addressing the psychological distress of widowed/divorced individuals and women. Lastly, long-term development strategies should focus on enhancing educational opportunities and economic empowerment, as these factors are crucial protective elements for HRQoL in post-disaster settings. Future research should transition to longitudinal designs to monitor HRQoL trajectories and identify critical periods for intervention. It is imperative to investigate the interplay between chronic post-disaster stressors and acute \"bad events\" to better understand their differential impacts on HRQoL. Qualitative studies using in-depth interviews and focus groups could provide a richer understanding of survivors' lived experiences, coping mechanisms, and culturally specific resilience factors. Such research could also explore the specific reasons behind the observed urban-rural disparities in social and environmental HRQoL. Expanding geographic scope beyond Herat to other affected areas in Afghanistan would provide a broader picture of post-earthquake challenges.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthical Considerations\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in collaboration with the Herat Health Department and the Afghanistan Center for Epidemiological Studies (ACES) and received ethical approval from the ACES Ethical Review Committee (Approval No. ACES-HES-23-002). Written informed consent was obtained from all adult participants, with parental consent for minors. Participation was voluntary, with the right to withdraw at any time. Data were anonymized, securely stored, and handled in accordance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConflict of interest\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors assert that there are no conflicts of interest to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthor contributions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e•\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;AN and AQM designed the study.\u003c/p\u003e\n\u003cp\u003e•\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;MN, MnN, and HA contributed to the data collection of this study.\u003c/p\u003e\n\u003cp\u003e•\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;AN analyzed the data.\u003c/p\u003e\n\u003cp\u003e•\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;SD, FR, and NR prepared the draft of the manuscript.\u003c/p\u003e\n\u003cp\u003e•\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;AN critically reviewed, rewrote, edited, and finalized the manuscript.\u003c/p\u003e\n\u003cp\u003e•\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eClinical trial number\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData availability\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets utilized and/or analyzed in the course of the present study are accessible from the corresponding author upon reasonable inquiry.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eUnited Nations Office for Disaster Risk Reduction (UNDRR), Centre for Research on the Epidemiology of Disasters (CRED). Poverty \u0026amp; death: disaster mortality 1996\u0026ndash;2015 [Internet]. Geneva/Brussels: UNDRR \u0026amp; CRED; 2016 [cited 2025 Sep 19]. Available from: https://www.preventionweb.net/files/50589_creddisastermortalityallfinalpdf.pdf\u003c/li\u003e\n \u003cli\u003eCentre for Research on the Epidemiology of Disasters (CRED). EM-DAT 2023 annual report [Internet]. Brussels: CRED; 2024 [cited 2025 Sep 19]. Available from: https://files.emdat.be/reports/2023_EMDAT_report.pdf\u003c/li\u003e\n \u003cli\u003eAtaya J, Soqia J, Ataya J, AlMhasneh R, Batesh D, Alkhadraa D, Albokaai H, Morjan M. Sleep quality and mental health differences following Syria-Turkey earthquakes: A cross-sectional study. International Journal of Social Psychiatry. 2024 Jun;70(4):700-8.\u003c/li\u003e\n \u003cli\u003eKim EM, Kim GS, Kim H, Park CG, Lee O, Pfefferbaum B. Health-related quality of life among older adults who experienced the Pohang earthquake in South Korea: A cross-sectional survey. Health and quality of life outcomes. 2022 Mar 4;20(1):37.\u003c/li\u003e\n \u003cli\u003eZhang X, Gao Y, Dai X, Zhou J, Yan L, Hou F, Yuan P, Wen J. Health-related quality of life among survivors in minority area 2 years after Jiuzhaigou earthquake: a cross-sectional study. Medicine. 2021 Mar 12;100(10):e25089.\u003c/li\u003e\n \u003cli\u003eZhang L, Wang Y, Huang X, Lan M, Ji H. Influence of post-traumatic status on health-related quality of life among survivors 10 years after the Wenchuan earthquake in China. Annals of Palliative Medicine. 2021 Mar;10(3):3059066-3066.\u003c/li\u003e\n \u003cli\u003eWhoqol Group. Development of the World Health Organization WHOQOL-BREF quality of life assessment. Psychological medicine. 1998 May;28(3):551-8.\u003c/li\u003e\n \u003cli\u003eSharma A, Nisa BU, Bibi H, Wiggins F, Mitchell A, Prasad K, Appuhamy K, Garcia OP, Zavala GA. Factors associated with health-related quality of life in people with severe mental illness: Results from a multicountry study in South Asia. medRxiv. 2025 Aug 1:2025-08.\u003c/li\u003e\n \u003cli\u003eMaheri M, Alipour M, Rohban A, Garmaroudi G. The association of resilience with health-related quality of life (HRQoL) in adolescent students. International Journal of Adolescent Medicine and Health. 2022 Feb 28;34(1):20190050.\u003c/li\u003e\n \u003cli\u003eArdalan A, Mazaheri M, Vanrooyen M, Mowafi H, Nedjat S, Naieni KH, Russel M. Post-disaster quality of life among older survivors five years after the Bam earthquake: implications for recovery policy. Ageing \u0026amp; Society. 2011 Feb;31(2):179-96.\u003c/li\u003e\n \u003cli\u003eLiang Y, Lu P. Health-related quality of life and the adaptation of residents to harsh post-earthquake conditions in China. Disaster medicine and public health preparedness. 2014 Oct;8(5):390-6.\u003c/li\u003e\n \u003cli\u003eLiang Y, Wang X. Developing a new perspective to study the health of survivors of Sichuan earthquakes in China: a study on the effect of post-earthquake rescue policies on survivors\u0026rsquo; health-related quality of life. Health Research Policy and Systems. 2013 Oct 29;11(1):41.\u003c/li\u003e\n \u003cli\u003eNeyazi A, Mohammadi B, Griffiths MD. The impact of the 2023 earthquakes on the Afghan health-care system. The Lancet. 2023 Nov 18;402(10415):1829-30.\u003c/li\u003e\n \u003cli\u003eEarthquake Hazards Program. M 6.3 \u0026ndash; 32 km NNE of Zindah Jān, Afghanistan [Internet]. 2023 [cited 2025 Sep 19]. Available from: https://earthquake.usgs.gov/earthquakes/eventpage/us6000ldpg/executive\u003c/li\u003e\n \u003cli\u003eWorld Health Organization, Eastern Mediterranean Regional Office. Earthquake in Herat province: situation reports (Oct\u0026ndash;Nov 2023) [Internet]. 2023\u0026ndash;2024 [cited 2025 Sep 19]. Available from: https://www.emro.who.int/afg/information-resources/earthquake-in-herat-province-situation-reports.html\u003c/li\u003e\n \u003cli\u003eUnited Nations Office for the Coordination of Humanitarian Affairs (OCHA). Flash update #3: earthquake in Paktika and Khost, Afghanistan (25 Jun 2022) [Internet]. 2022 [cited 2025 Sep 19]. Available from: https://www.unocha.org/publications/report/afghanistan/afghanistan-flash-update-3-earthquake-paktika-and-khost-provinces-afghanistan-25-june-2022\u003c/li\u003e\n \u003cli\u003eMaehira Y, Spencer RC. Harmonization of biosafety and biosecurity standards for high-containment facilities in low-and middle-income countries: an approach from the perspective of occupational safety and health. Frontiers in Public Health. 2019 Sep 12;7:249.\u003c/li\u003e\n \u003cli\u003eKaleem S, Ahmad T, Wahid A, Khan HH, Mallhi TH, Al-Worafi YM, Alam A, Khan A, Khan YH, Khan FU. Assessment of health-related quality of life among Afghan refugees in Quetta, Pakistan. Plos one. 2024 Feb 1;19(2):e0288834.\u003c/li\u003e\n \u003cli\u003eShayan NA, Eser E, Neyazi A, Eser S. Reliability and validity of the Dari version of the World Health Organization Quality of Life (WHOQOL-BREF) Questionnaire in Afghanistan. Turkish Journal of Public Health. 2020;19(3):263-73.\u003c/li\u003e\n \u003cli\u003eTian W, Jia Z, Duan G, Liu W, Pan X, Guo Q, Chen R, Zhang X. Longitudinal study on health-related quality of life among child and adolescent survivors of the 2008 Sichuan earthquake. Quality of Life Research. 2013 May;22(4):745-52.\u003c/li\u003e\n \u003cli\u003eAdams C, Gringart E, Strobel N. Barriers to mental health help-seeking among older adults with chronic diseases. Australian Psychologist. 2024 Mar 3;59(2):154-65.\u003c/li\u003e\n \u003cli\u003eMao SJ, Shen J, Xu F, Zou CC. Quality of life in caregivers of young children with Prader\u0026ndash;Willi syndrome. World Journal of Pediatrics. 2019 Oct;15(5):506-10.\u003c/li\u003e\n \u003cli\u003eGim J, Shin S. Disaster vulnerability and community resilience factors affecting post-disaster wellness: A longitudinal analysis of the Survey on the Change of Life of Disaster Victim. International Journal of Disaster Risk Reduction. 2022 Oct 15;81:103273.\u003c/li\u003e\n \u003cli\u003eAlekozay M, Mohmand NA, Sadat SJ, Ahmadzadeh EA, Hamedi T, Rahimi T, Najm AF. Interplay of Post-Traumatic Stress Disorder, General Anxiety Disorder and Resilience among Earthquake Survivors in Zinda Jan District of Herat Province. Nangarhar University International Journal of Biosciences. 2023 Dec 30;2(04):104-14.\u003c/li\u003e\n \u003cli\u003eYıldırım E, G\u0026uuml;d\u0026uuml;c\u0026uuml; N. The Investigation of Quality of Life and Post-traumatic Stress Disorder Levels of Midwifery Students Experiencing an Earthquake. Disaster Medicine and Public Health Preparedness. 2024 Jan;18:e328.\u003c/li\u003e\n \u003cli\u003eFarina M, Moret-Tatay C, Paloski LH, Irigaray TQ. Neuroticism and quality of life: testing for mediated effects of anxiety in older adults without cognitive impairment. Ageing International. 2021 Mar;46(1):83-94.\u003c/li\u003e\n \u003cli\u003eCarlsson JM, Mortensen EL, Kastrup M. Predictors of mental health and quality of life in male tortured refugees. Nordic journal of psychiatry. 2006 Jan 1;60(1):51-7.\u003c/li\u003e\n \u003cli\u003eCarnahan LR, Rauscher GH, Watson KS, Altfeld S, Zimmermann K, Ferrans CE, Molina Y. Comparing the roles of social context, networks, and perceived social functioning with health-related quality of life among self-reported rural female cancer survivors. Supportive Care in Cancer. 2021 Jan;29(1):331-40.\u003c/li\u003e\n \u003cli\u003eGruszczyńska E, Rzeszutek M. Trajectories of health-related quality of life and perceived social support among people living with HIV undergoing antiretroviral treatment: does gender matter?. Frontiers in Psychology. 2019 Jul 23;10:1664.\u003c/li\u003e\n \u003cli\u003eWippold GM, Garcia KA, Frary SG. The role of sense of community in improving the health‐related quality of life among Black Americans. Journal of community psychology. 2023 Jan;51(1):251-69.\u003c/li\u003e\n \u003cli\u003eM\u0026oslash;ller JJ, la Cour K, Pilegaard MS, Dalton SO, Bidstrup PE, M\u0026ouml;ller S, Jarlbaek L. Social vulnerability among cancer patients and changes in vulnerability during their trajectories\u0026ndash;A longitudinal population-based study. Cancer epidemiology. 2023 Aug 1;85:102401.\u003c/li\u003e\n \u003cli\u003eAng WH, Lau Y, Ngo LP, Siew AL, Ang NK, Lopez V. Path analysis of survivorship care needs, symptom experience, and quality of life among multiethnic cancer survivors. Supportive Care in Cancer. 2021 Mar;29(3):1433-41.\u003c/li\u003e\n \u003cli\u003eQu GB, Zhao TY, Zhu BW, Tzeng GH, Huang SL. Use of a modified DANP-mV model to improve quality of life in rural residents: The empirical case of Xingshisi village, China. International journal of environmental research and public health. 2019 Jan;16(1):153.\u003c/li\u003e\n \u003cli\u003eLiang Y. Satisfaction with economic and social rights and quality of life in a post-disaster zone in China: evidence from earthquake-prone Sichuan. Disaster medicine and public health preparedness. 2015 Apr;9(2):111-8.\u003c/li\u003e\n \u003cli\u003ePei S, Zhai C, Hu J, Liu J, Song Z. Seismic functionality of healthcare network considering traffic congestion and hospital malfunctioning: A medical accessibility approach. International journal of disaster risk reduction. 2023 Oct 15;97:104019.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 5 are available in the supplementary files section\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Earthquake, Afghanistan, HRQoL, WHOQOL-BREF, Mental health, Disaster recovery","lastPublishedDoi":"10.21203/rs.3.rs-8863086/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8863086/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Earthquakes are among the most destructive natural disasters, causing severe physical, psychological, and social disruption. Assessing health-related quality of life (HRQoL) among survivors is essential for evidence-based recovery planning, particularly in resource-limited settings such as Afghanistan. This study evaluated HRQoL and its sociodemographic and clinical determinants among survivors of the 2023 Herat earthquake.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A community-based cross-sectional study was conducted among 902 adult survivors in five earthquake-affected districts of Herat Province. Data were collected through structured face-to-face interviews between February and March 2024. HRQoL was assessed using the WHOQOL-BREF, and associations between HRQoL domains (physical, psychological, social, environmental) and independent variables were analyzed using chi-square tests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Low HRQoL was reported by 38.3% of participants in the physical domain, 36.7% in the psychological domain, 28.3% in the environmental domain, and 25.7% in the social domain. Women reported significantly lower physical (44.2% vs. 30.3%; p = 0.002) and psychological (42.4% vs. 29.5%; p = 0.006) HRQoL compared with men. Widowed/divorced individuals had the highest prevalence of low HRQoL (physical: 51.5%; psychological: 48.5%; p \u0026lt; 0.001). Participants from households with \u0026gt;10 members reported nearly double the prevalence of low physical HRQoL compared with those from ≤5-member households (49.2% vs. 26.8%; p \u0026lt; 0.001). Low monthly income (\u0026lt;10,000 AFN), unemployment, chronic illness (physical: 56.8% vs. 33.5%; p \u0026lt; 0.001), and earthquake-related injuries (52.3% vs. 34.1%; p \u0026lt; 0.01) were also significantly associated with impaired HRQoL.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Survivors of the Herat earthquake experienced substantial impairments in physical and psychological well-being. Women, widowed/divorced individuals, low-income households, and those with injuries or chronic illnesses were disproportionately affected. Targeted psychosocial support, economic assistance, and long-term rehabilitation strategies are urgently required to improve HRQoL and strengthen community resilience in earthquake-affected regions.\u003c/p\u003e","manuscriptTitle":"Post-earthquake health-related quality of life in Afghanistan: a cross- sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-12 07:49:39","doi":"10.21203/rs.3.rs-8863086/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-14T09:29:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-20T08:18:34+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-18T17:29:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"217727686987739055873414251294510933796","date":"2026-03-17T04:51:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"12302259543322176500613647879458316211","date":"2026-03-15T07:05:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-10T04:53:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"64775798511767612414922510825242767766","date":"2026-03-09T14:20:50+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-09T14:01:49+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-16T19:00:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-16T07:42:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-16T07:38:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Public Health","date":"2026-02-12T14:13:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5b27e12a-24df-40c4-8f0d-efba1d76ad7e","owner":[],"postedDate":"March 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-04-14T09:40:51+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-12 07:49:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8863086","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8863086","identity":"rs-8863086","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}