Anemia and Cardiometabolic Risk Among University Students in India: Findings from a Health Screening Program

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Data were analyzed from 13,628 students aged 18 to 30 years who participated in the health screening program between June 2023 and May 2024, ensuring that all students were included in the study, thus eliminating the risk of self-selection bias. Body mass index, blood pressure, and hemoglobin levels were measured and categorized according to international clinical standards. The results were analyzed to determine the prevalence of anemia, high blood pressure, and overweight among students using comparative statistical tests to determine differences between the sexes, as well as to determine associations between variables using multivariable logistic regression analysis. The results showed that there was a high burden of asymptomatic anemia and cardiometabolic risk factors among students, with significant differences between the sexes, as well as associations with age and body mass index. Health Promoting University student health anemia hypertension cardiometabolic risk higher education Figures Figure 1 Introduction The transition to higher education is essential to young adults’ life courses. Many of the behaviors established during this time are health-related behaviors that shape a person's long-term health. As young adults transition into this stage of life, they are granted more autonomy, face increasing academic pressure, undergo changes in their nutrition and exercise routines, and experience heightened psychosocial stress. Thus, the combination of these factors can predispose patients to the early onset of many risk factors for NCDs. [1–4]. The majority of premature morbidity and mortality occur due to NCDs worldwide, and the determinants for many NCDs are becoming apparent during early adolescent and early adulthood [5]. In India, this global trend coincides with a rapid epidemiological shift resulting in a growing number of cardiometabolic risk factors for many of India's young people. National level data show that the prevalence of anemia, high blood pressure, and overweight or obesity among adolescents and young adults is exceedingly high [6,7]. Many of these factors may not be obvious during their initial stages, and were not diagnosed until it was often too late, preventing significant proactive intervention. Therefore, early adulthood is an intervention point to promote positive health behaviours and reduce the risk of developing a non-communicable disease. As the university setting represents a large, diverse, and formative group of people, universities will play a significant role in population health promotion. The concept of The Health Promoting University (HPU) model hypothesizes that health is influenced by the culture of the institution, as well as by both the physical and social environments and organizational policies, not just by individual behavior [8]. The American College Health Association's Healthy Campus Model also highlights the need for the integration of prevention services as well as the use of data to guide decision-making and the establishment of supportive campus environments [9]. Internationally, evidence indicates that health screening programs established in the university setting can detect health conditions in individuals before they become clinically significant, as well as support interventions specifically focused on the identified population health needs when integrated as part of integrated health promotion strategies [10–13]. While significant literature exists globally on the area of health and well-being among college students, few studies have been completed regarding this area in the higher education context in India. Most of the available studies tend to focus on individual health conditions or use voluntary participation, which creates potential sources of self-selection bias and limits their generalizability to the entire population [14–16]. Additionally, very little research has been conducted on integrated university-wide screening programs that include multiple health-related domains for the total student population. The lack of a comprehensive database significantly limits universities’ ability to develop, prioritize, and evaluate the efficacy of Health Promotion initiatives based on evidence. To close this gap, the current study aimed to evaluate the results of a mandatory university-wide annual Health Screening that was conducted within a single large Indian higher education institution. The purpose of this study was to estimate the prevalence of Anemia, Hypertension, and abnormal Body Mass Index (BMI), examine sex-based differences in these conditions, and generate institutional evidence to inform a health promotion initiative designed around a health-promoting university (HPU) model. Methods Reporting Standards This study was conducted in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for observational research. Study Design and Setting A retrospective observational study was conducted using electronic health records that were produced by virtue of the annual health check-up program from June 1, 2023, to May 31, 2024, at a private multi-campus university based in India. The campus possesses a consolidated health system that provides primary healthcare to students from all of its constituent campuses through an EHR platform. The final sample size for analysis was 13,628. Of the total population of [17656] university students, 13,628 (77.2%) participated in the screening process. Exclusion based on incomplete data was not performed because the EHR biometric registration was completed for final submission. Study Population and Period The study included undergraduate and postgraduate students aged 18–30 years who received an annual health checkup from June 1, 2023, through May 31, 2024. Students had records created during this time that made it accessible for review as the population. The only exclusion criteria used were that at least one of the major areas of data collection (hemoglobin, blood pressure, or BMI) was not included in the original record. Data Sources and Variables Anonymized data were acquired from the university's EHR system, through which selected variables were recorded for analytical purposes, as listed below: Demographics Variable: Age in years; Gender (Male or Female); Academic Level (Undergraduate or Postgraduate Direct anthropometric and physiological measurements: Height in centimeters, Weight in Kilograms, Calculated BMI (Weight in Kg divided by height in meters squared), Systolic BP in mmHg, and Diastolic BP in mmHg. Laboratory parameter: hemoglobin concentration (g/dL). Clinical advice and referrals: Recommendations made by a physician concerning possible lifestyle interventions, additional assessments and processing, referrals, etc. This occurred during the initial screening. Outcome Definitions The primary results were measured using internationally recognized clinical guidelines to ensure that they were comparable between studies and that the findings were similar across researchers. The classification of the BMI is taken from the World Health Organisation (WHO) - the WHO defines BMI as follows: underweight (<18.5Kg/m²), normal weight (18.5-24.9Kg/m²), overweight (25-29.9Kg/m²), and obese (≥30.0 Kg/m²).. Blood Pressure: Categorized according to the 2017 American College of Cardiology/American Heart Association (ACC/AHA) guidelines as normal (<120/80 mmHg), elevated (120–129/<80 mmHg), hypertension stage 1 (130–139 mmHg systolic or 80–89 mmHg diastolic), and hypertension stage 2 (≥140 mmHg systolic or ≥90 mmHg diastolic). Measurement Standardization: Height and weight were measured using calibrated stadiometers - its a manual stadiometer - Bioplus with participants in light clothing and no shoes. Blood pressure was measured using manual BP apparatus (mercury free) - Diamond led regular (BPDG 041 ). Participants were seated for at least 5 minutes prior to measurement, and a second reading was taken if the initial reading was ≥130/80 mmHg, with the average of the two recorded. Hemoglobin levels were determined via the cyanmethemoglobin method using venous blood samples.” Anemia was defined using the WHO thresholds of hemoglobin by sex: hemoglobin < 12 g/dL for females and < 13 g/dL for males. Statistical Analysis Data analyses were performed using the statistical software IBM SPSS Statistics for Windows, Version 28.0. Frequencies, percentages, means, and standard deviations were computed for descriptive statistics on participant characteristics and estimation of health condition prevalence. The incidence of sex-related differences in the prevalence of anemia and hypertension was compared using the Pearson chi-square (χ²) test. Relationships between the continuous variables of BMI, age, systolic blood pressure, and diastolic blood pressure were determined using Pearson’s correlation (r). Statistical significance was set at p < 0.05. Ethical Considerations This study adhered to the guidelines of the Declaration of Helsinki. The study was approved by the Institutional Ethics Committee (IEC) of the university participating in the study (Approval No: SIU/IEC/1137). In this study, which involved retrospective analysis using anonymized EHR data, seeking prior consent from participants was exempt, as approved by the IEC. Data confidentiality was ensured by restricting access to data by the person(s) conducting the study. Results Participant Characteristics : The analyses used results from 13628 students who completed an annual health screening from June 1, 2023, through May 31, 2024, and there were no exclusions due to missing information regarding age, body mass index (BMI), blood pressure, or hemoglobin. The group included 7012 females (51.4%) and 6616 males (48.6%). The mean age of all participants was 21.1 years (SD=2.7), with the average being 20.9 years (SD = 2.5) for females and 21.3 years (SD = 3.0) for males. Prevalence of BMI, Blood Pressure, and Anemia Based on the WHO BMI classification, 58.4% of the cohort had a normal BMI, whereas 22.1% were classified as overweight or obese (Table 1). Underweight status was observed in 19.4% of the students. Regarding blood pressure, 31.1% (n = 4,243) of the students met the 2017 ACC/AHA criteria for hypertension (≥ 130/80 mmHg). Applying WHO sex-specific hemoglobin cut-offs (< 12.0 g/dL for females; < 13.0 g/dL for males), 53.1% of students were classified as anemic. This represents a considerable hematological burden detected through routine screening. Table 1. Prevalence of BMI Categories Among University Students (N = 13,628) Category (WHO) Female (n) Male (n) Total (%) Underweight (< 18.5 kg/m²) 1,592 1,058 19.4% Normal weight (18.5–24.9 kg/m²) 4,124 3,837 58.4% Overweight (25.0–29.9 kg/m²) 982 1,257 16.4% Obesity (≥ 30.0 kg/m²) 314 464 5.7% Sex-Stratified Differences in Health Risks Marked sex-based differences were observed for both anemia and hypertension (Table 2). Contrary to the general population trends, anemia prevalence was significantly higher among males (67.4%) than among females (39.5%) when applying WHO sex-specific thresholds (χ²(1) = 1066.6, p < .001). Hypertension was also disproportionately higher in males. The prevalence of hypertension (≥ 130/80 mmHg) was 42.6% in males and 20.3% in females (χ²(1) = 801.4, p < .001). Table 2. Health Risk Prevalence by Gender Variable Total (N = 13,628) Female (n = 7,012) Male (n = 6,616) p-value * Anemia (WHO Criteria) 7,230 (53.1%) 2,771 (39.5%) 4,459 (67.4%) < .001 Hypertension (Total) 4,243 (31.1%) 1,424 (20.3%) 2,819 (42.6%) < .001 Stage 1 Hypertension 3,142 (23.1%) 1,189 (17.0%) 1,953 (29.5%) < .001 Stage 2 / Crisis 1,101 (8.1%) 235 (3.4%) 866 (13.1%) < .001 *Anemia is defined as Hb < 12.0 g/dL for females and < 13.0 g/dL for males. Correlations Between Cardiometabolic Markers Pearson’s correlation analysis demonstrated statistically significant but modest associations between anthropometric and hemodynamic variables. BMI was positively correlated with both systolic blood pressure (r = 0.186, p < .001) and diastolic blood pressure (r = 0.213, p < .001). Age showed negligible to weak correlations with systolic (r = 0.044, p < .001) and diastolic (r = 0.019, p = .028) blood pressure. Multivariable Analysis Adjusted odds ratios (aOR) were derived from multivariable logistic regression models including sex, age, BMI, and academic level. The female sex and undergraduate level were used as references. Table 3. Adjusted Logistic Regression Models for Anemia and Hypertension Outcome Predictor aOR 95% CI p-value Anemia Male (vs Female) 3.20 2.97 – 3.45 < 0.001 Age (per year) 1.02 1.00 – 1.04 0.090 BMI (per kg/m²) 1.00 0.99 – 1.01 0.615 Hypertension Male (vs Female) 1.49 1.38 – 1.60 < 0.001 Age (per year) 1.04 1.02 – 1.06 < 0.001 BMI (per kg/m²) 1.06 1.05 – 1.07 < 0.001 In the adjusted logistic regression models (Table 3), male sex was independently associated with higher odds of anemia (aOR 3.20, 95% CI 2.97–3.45) and hypertension (aOR 1.49, 95% CI 1.38–1.60). Hypertension was also associated with increasing age and BMI, whereas anemia was not independently associated with BMI. Clinical Referrals and Follow-up : Based on the screening findings, clinical advice and referrals were systematically documented in the EHR. Of the total cohort, 8.1% (n = 1,101) were identified as having stage 2 hypertension requiring immediate counseling, and 53.1% (n = 7,230) were referred to the University Health Center for further investigation of anemia. Discussion This large-scale study on an annual health screening program among university students in India identified a significant problem with anemia, BP, and overweight/obesity in early adulthood. Making the most of the full set of data with no missing values for key variables (N=13,628) represents the most robust descriptive analysis of risk profiles that have been conducted on student health to date within the context of Indian higher education. These results, interpreted within the Health Promoting University framework, confirm the key role of universities as targeted sites for early care detection and health promotion. Anemia Burden and Sex Differences In contrast to the general population trends in India, for example, NFHS-5 [17], where females always have a higher burden, the estimated significantly higher prevalence among males than females-67.4% versus 39.5%) represents a complete reversal of the expected gender gap. The inversion of expected gender gap partly reflects the strict use of WHO diagnostic thresholds (<13.0 g/dL for males vs. <12.0 g/dL for females), which captures a large proportion of young men with mild anemia, usually missed by standard screening. Beyond definitions, this 'hidden' burden may reflect gendered behavior patterns in the university setting, as male students tend to move away from home-cooked meals faster than their female peers to calorie-dense but micronutrient-poor ‘street foods’[18]. According to the results provided in Table 1, the majority (53.0%) of the students screened were found to be anemic, thus indicating the level of hematologic burden present in this young adult population. Sex stratified analysis demonstrated notable differences between males and females regarding anemia prevalence, where male students showed a substantially higher prevalence (67.4%) than female students (39.5%) (See Table 2 and Figure 1). These results differ from those collected during national population-based surveys, such as the NFHS-5, which have depicted similar results; among women of reproductive age, there is a higher overall prevalence of anemia than among male students [6]. Emerging evidence shows that anemia among young male persons continues to be underreported in both institutional and community settings, particularly when routine screening is not heavily emphasized [14,19]. The discrepancy between the national survey trends and results of the present institutional analysis underlines the significance of context-specific surveillance. College-going students may have different eating habits, stress levels, and health-seeking behaviors, including hematological outcomes. Although the current analysis cannot provide any insight into the specific reasons for this discrepancy, the relevant literature indicates that some of the contributing factors of anemia in male students in particular may include suboptimal iron diet, irregular eating patterns, and poor utilization of preventive health care facilities [20,21]. These observations stress the demand for campus-level anemia screening and counseling programs with gender-inclusive provisions, and not considering anemia as a female health problem alone. Cardiometabolic Risk in Early Adulthood A total of 31.1% of the sample were diagnosed with hypertension (≥130/80 mmHg). The majority of participants who met this definition were classified as stage 1 (23.1%). The more stringent criteria for diagnosing hypertension developed by the ACC/AHA in 2017 [22]have caused a great deal of confusion when applied to the younger adult population. There has been significant opposition to the use of more stringent guidelines to classify an otherwise healthy individual as hypertensive. However, when viewed in the context of Health Promoting University governing policies that promote healthy lifestyles and reduce health risks, the use of more sensitive criteria is scientifically valid. The use of more sensitive criteria allows us to identify individuals who are at an increased risk of developing hypertension (at-risk population) and who would not otherwise be recognized as being at risk if using the traditional 140/90 mm Hg cutoffs. Identifying students with stage 1 hypertension provides an important window of opportunity to provide primordial prevention via lifestyle changes (dietary changes, exercise, and stress management) to reverse the trajectory of developing stage 2 hypertension (of which 8.1% of the sample had) and to avoid the development of irreversible damage to target organs. The prevalence of elevated blood pressure and hypertension in our study is particularly interesting. Almost three-fifths of our subjects fulfilled the ACC/AHA [23] definition for hypertension (Stages 1 or 2), while only a quarter had normal blood pressure values (Table 1). Comparisons across both sexes revealed a higher proportion of hypertension in the male gender (66.6%) than in women (52.4%), which is in line with earlier studies showing gender variations in cardiometabolic risk in young persons [7]. The adjusted logistic regression analyses further supported these trends. Male sex independently predicted the presence of anemia and hypertension after adjusting for age, BMI, and academic level (Table 3). Additionally, increasing age and BMI independently predicted the presence of hypertension. These relationships are consistent with established pathophysiological associations between adiposity, resistance, and blood pressure homeostasis[24,25]. Although the correlation coefficients between BMI and blood pressure were not large, the significance of these associations in a large group of people attests to the impact of being overweight on the risk of cardiovascular disease at a relatively young age. Implications for the Health Promoting University Framework Collectively, these findings strengthen the assertion that colleges and universities are key intervention points for preventing noncommunicable diseases. In addition to promoting access to health services, a health-promoting university framework aims to provide environments that support healthy choices [5,9,12]. The fact that the current study found high rates of anemia and cardiometabolic risk factors demonstrates that screening alone does not adequately address them.. As such, institutional responses should create structured follow-up pathways (e.g., nutrition counselling, referral systems, and health education programs tailored to each student’s needs). When developing programs to address anemia, education related to food choices, an understanding of the micronutrients needed, and a mechanism to obtain confirmation of test results and receive treatment are recommended. Regarding hypertension and overweight/obesity, results indicate that integrating lifestyle changes into diet quality, activity level, sleep habits, and stress management is effective when delivered to college campuses [10,11]. When developing such programs, it is essential to incorporate gender-related issues, as well as social and cultural influences that affect individual attitudes towards health-related behaviors. Implications for Health Promotion Policy On the basis of the Health Promoting University, the implications of the study reveal the need for more holistic approaches to the university, shifting from screenings to a system-wide approach for health promotion [3,4]. The study suggests the need for the institutionalization of health screenings as a systematic and universal university health initiative to identify prevalent yet often asymptomatic diseases such as anemia and cardiometabolic risk factors, and to address issues of inequity in self-selection. The differences in anemia and hypertension by sex also emphasize the need for gender-sensitive and equity-oriented health promotion strategies that take into account issues of nutrition, stress, lifestyle, and sociocultural factors. Implications for Health Promotion Practice However, universities also need to promote health-supportive campus environments through improvements in the affordability and nutritional quality of food, physical activity opportunities, and mental health services. Follow-through and continuity of care also need to be addressed in effective screening practices. Finally, the application of data from routine health practices to create learning health systems would allow for monitoring and evaluation of health promotion in higher education. Strengths and Limitations The main strength of this study is its large sample size, which comes from a screening program, thereby eliminating self-selection bias and improving internal validity. The application of uniform criteria set internationally (WHO, ACC/AHA [23]) and using denominators similarly across analyses increased the reliability of the results. The application of multivariate analysis increased the depth of analysis by adjusting for significant variables. This study has several limitations that should be considered. The study had a cross-sectional design and was retrospective; therefore, it was not possible to establish causality, and data on blood pressure and hemoglobin were considered after only one screening visit rather than being considered multiple times. It is also apparent that lifestyle, dietary, or socioeconomic factors were not available in this dataset, which may affect the observed relationship. Future prospective studies incorporating behavioral and environmental data would help clarify causal pathways and inform more targeted interventions. Conclusion This paper presents an in-depth institutional level analysis of anemia and cardiometabolic risk factors among university students in India, using a comprehensive dataset collected as part of an institutional health screening event every year. The results illustrate that a large number of students are enrolled in higher education institutions carrying undetected levels of risk to their health, contrary to popular perceptions that students in higher education institutions are healthy. A high prevalence of anemia, hypertension, and overweight/obesity was found in early adulthood, in conjunction with a marked difference between sexes in terms of risk factors. Even without the ability to establish causality due to the cross-sectional study methodology, these findings show that asymptomatic morbidity can be identified through university-based screening in a life-stage in which prevention is most effective. In the context of health promotion, such evidence supports the continued significance of higher education institutions in terms of acting as pivotal social environments that can be effectively utilized for large-scale preventive interventions. It is noted that such institutions have the unique advantage of bringing together a vast number of youth from diverse backgrounds at a crucial life stage. Declarations Ethical Approval: Ethics approval was received from the Independent Ethics Committee of Symbiosis International (Deemed University), Proposal No.SIU/IEC/1137, dated August 22, 2025. Consent to participate: In this study, which involved retrospective analysis using anonymized EHR data, seeking prior consent from participants was exempt, as approved by the Independent Ethics Committee of Symbiosis International (Deemed University) (IEC). Data confidentiality was ensured by restricting access to data by the person(s) conducting the study. Funding Statement: No specific grant was received for this research from any funding body in the public, commercial, or not-for-profit sectors. Conflict of Interest Statement: The authors have no conflict of interest. Data Availability Statement: The data supporting the conclusions of this research are not publicly available as they contain information that might breach the privacy of research participants. Data can be made available upon reasonable request from the corresponding author and with the Institutional Ethics Committee permission . Author Contributions: Conceptualization: R.Y, A.C Methodology: R.Y, A.C Data Curation: A.C Formal Analysis: A.C Investigation: A.C Writing – Original Draft: A.C Writing – Review & Editing: R.Y Supervision: R.Y Project Administration: A.C References Sawyer SM, Azzopardi PS, Wickremarathne D, Patton GC. The age of adolescence. Lancet Child Adolesc. Health. 2018. https://doi.org/10.1016/S2352-4642(18)30022-1 Viner RM, Ozer EM, Denny S, Marmot M, Resnick M, Fatusi A, et al. Adolescence and the social determinants of health. The Lancet. 2012. https://doi.org/10.1016/s0140-6736(12)60149-4 Patton GC, Sawyer SM, Santelli JS, Ross DA, Afifi R, Allen NB, et al. 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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-9158044","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":622889301,"identity":"f783276e-13d6-4cd4-a2a5-fd471b5c110b","order_by":0,"name":"Dr. Rajiv Yeravdekar","email":"","orcid":"","institution":"Symbiosis International University","correspondingAuthor":false,"prefix":"Dr.","firstName":"Rajiv","middleName":"","lastName":"Yeravdekar","suffix":""},{"id":622889302,"identity":"a7ab994f-eb5f-4cb5-a7bf-e8ad9294b4a2","order_by":1,"name":"Dr. Alaka Chandak","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIie3LsQrCMBCA4SsBu5x1raD2FSKFLgWfpUWwk+AoKFgQ6iL0EXyF+gaRA12Cs+Ciu0NGBxGr4OBgWzeH/FwODvIB6HT/mABD5KsDDJ8ne00ZgSdxfydhDG9SlnWkk7jKXrRa1EnB2A9jsy4KSXM/4JvloT/MyBrYIKMwZlZQSLgELlCxYcbQAyOhnCAvIaba3NQscuboKuNeiSAnPFAAhNw24gqkKXFELbnrZoSeHWwjNykjljTX58t24jipdJWa+u20IYvJZ0H+aj/81+l0Ot2XHuObSAlZ5vfUAAAAAElFTkSuQmCC","orcid":"","institution":"Symbiosis International University","correspondingAuthor":true,"prefix":"Dr.","firstName":"Alaka","middleName":"","lastName":"Chandak","suffix":""}],"badges":[],"createdAt":"2026-03-18 10:23:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9158044/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9158044/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107097436,"identity":"7026fc52-18e3-4484-a5a2-5cd81fde04f6","added_by":"auto","created_at":"2026-04-16 17:41:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":61727,"visible":true,"origin":"","legend":"\u003cp\u003eSex-Stratified Prevalence of Anemia and Hypertension.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9158044/v1/7bdbb8d602ac313714a920c7.png"},{"id":107481798,"identity":"ac65a802-6466-49ed-b1ce-198cea4c2335","added_by":"auto","created_at":"2026-04-22 02:20:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":551192,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9158044/v1/bf185ce3-18e4-46a4-879a-9ee1bac42019.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Anemia and Cardiometabolic Risk Among University Students in India: Findings from a Health Screening Program","fulltext":[{"header":"Introduction ","content":"\u003cp\u003eThe transition to higher education is essential to young adults\u0026rsquo; life courses. Many of the behaviors established during this time are health-related behaviors that shape a person\u0026apos;s long-term health. As young adults transition into this stage of life, they are granted more autonomy, face increasing academic pressure, undergo changes in their nutrition and exercise routines, and experience heightened psychosocial stress. Thus, the combination of these factors can predispose patients to the early onset of many risk factors for NCDs. [1\u0026ndash;4]. The majority of premature morbidity and mortality occur due to NCDs worldwide, and the determinants for many NCDs are becoming apparent during early adolescent and early adulthood [5].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn India, this global trend coincides with a rapid epidemiological shift resulting in a growing number of cardiometabolic risk factors for many of India\u0026apos;s young people. National level data show that the prevalence of anemia, high blood pressure, and overweight or obesity among adolescents and young adults is exceedingly high [6,7]. Many of these factors may not be obvious during their initial stages, and were not diagnosed until it was often too late, preventing significant proactive intervention. Therefore, early adulthood is an intervention point to promote positive health behaviours and reduce the risk of developing a non-communicable disease.\u003c/p\u003e\n\u003cp\u003eAs the university setting represents a large, diverse, and formative group of people, universities will play a significant role in population health promotion. The concept of The Health Promoting University (HPU) model hypothesizes that health is influenced by the culture of the institution, as well as by both the physical and social environments and organizational policies, not just by individual behavior [8]. The American College Health Association\u0026apos;s Healthy Campus Model also highlights the need for the integration of prevention services as well as the use of data to guide decision-making and the establishment of supportive campus environments [9]. Internationally, evidence indicates that health screening programs established in the university setting can detect health conditions in individuals before they become clinically significant, as well as support interventions specifically focused on the identified population health needs when integrated as part of integrated health promotion strategies [10\u0026ndash;13].\u003c/p\u003e\n\u003cp\u003eWhile significant literature exists globally on the area of health and well-being among college students, few studies have been completed regarding this area in the higher education context in India. Most of the available studies tend to focus on individual health conditions or use voluntary participation, which creates potential sources of self-selection bias and limits their generalizability to the entire population [14\u0026ndash;16]. Additionally, very little research has been conducted on integrated university-wide screening programs that include multiple health-related domains for the total student population. The lack of a comprehensive database significantly limits universities\u0026rsquo; ability to develop, prioritize, and evaluate the efficacy of Health Promotion initiatives based on evidence.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo close this gap, the current study aimed to evaluate the results of a mandatory university-wide annual Health Screening that was conducted within a single large Indian higher education institution. The purpose of this study was to estimate the prevalence of Anemia, Hypertension, and abnormal Body Mass Index (BMI), examine sex-based differences in these conditions, and generate institutional evidence to inform a health promotion initiative designed around a health-promoting university (HPU) model.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch3\u003eReporting Standards\u003c/h3\u003e\n\u003cp\u003eThis study was conducted in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for observational research.\u003c/p\u003e\n\u003ch3\u003eStudy Design and Setting\u003c/h3\u003e\n\u003cp\u003eA retrospective observational study was conducted using electronic health records that were produced by virtue of the annual health check-up program from June 1, 2023, to May 31, 2024, at a private multi-campus university based in India. The campus possesses a consolidated health system that provides primary healthcare to students from all of its constituent campuses through an EHR platform.\u003c/p\u003e\n\u003cp\u003eThe final sample size for analysis was 13,628. Of the total population of [17656] university students, 13,628 (77.2%) participated in the screening process. Exclusion based on incomplete data was not performed because the EHR biometric registration was completed for final submission.\u003c/p\u003e\n\u003ch3\u003eStudy Population and Period\u003c/h3\u003e\n\u003cp\u003eThe study included undergraduate and postgraduate students aged 18\u0026ndash;30 years who received an annual health checkup from June 1, 2023, through May 31, 2024. Students had records created during this time that made it accessible for review as the population. The only exclusion criteria used were that at least one of the major areas of data collection (hemoglobin, blood pressure, or BMI) was not included in the original record.\u003c/p\u003e\n\u003ch3\u003eData Sources and Variables\u003c/h3\u003e\n\u003cp\u003eAnonymized data were acquired from the university\u0026apos;s EHR system, through which selected variables were recorded for analytical purposes, as listed below:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eDemographics Variable: \u0026nbsp; Age in years; Gender (Male or Female); Academic Level (Undergraduate or Postgraduate\u003c/li\u003e\n \u003cli\u003eDirect anthropometric and physiological measurements: \u0026nbsp;Height in centimeters, Weight in Kilograms, Calculated BMI (Weight in Kg divided by height in meters squared), Systolic BP in mmHg, and Diastolic BP in mmHg.\u003c/li\u003e\n \u003cli\u003eLaboratory parameter: hemoglobin concentration (g/dL).\u003c/li\u003e\n \u003cli\u003eClinical advice and referrals: Recommendations made by a physician concerning possible lifestyle interventions, additional assessments and processing, referrals, etc. This occurred during the initial screening.\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch3\u003eOutcome Definitions\u003c/h3\u003e\n\u003cp\u003eThe primary results were measured using internationally recognized clinical guidelines to ensure that they were comparable between studies and that the findings were similar across researchers.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eThe classification of the BMI is taken from the World Health Organisation (WHO) - the WHO defines BMI as follows: underweight (\u0026lt;18.5Kg/m\u0026sup2;), normal weight (18.5-24.9Kg/m\u0026sup2;), overweight (25-29.9Kg/m\u0026sup2;), and obese (\u0026ge;30.0 Kg/m\u0026sup2;)..\u003cbr\u003e\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eBlood Pressure: Categorized according to the 2017 American College of Cardiology/American Heart Association (ACC/AHA) guidelines as normal (\u0026lt;120/80 mmHg), elevated (120\u0026ndash;129/\u0026lt;80 mmHg), hypertension stage 1 (130\u0026ndash;139 mmHg systolic or 80\u0026ndash;89 mmHg diastolic), and hypertension stage 2 (\u0026ge;140 mmHg systolic or \u0026ge;90 mmHg diastolic).\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eMeasurement Standardization:\u003c/strong\u003e\u0026nbsp; \u0026nbsp;Height and weight were measured using calibrated stadiometers - its a manual stadiometer - Bioplus with participants in light clothing and no shoes. Blood pressure was measured using manual BP apparatus (mercury free) - Diamond led regular (BPDG 041 ). Participants were seated for at least 5 minutes prior to measurement, and a second reading was taken if the initial reading was \u0026ge;130/80 mmHg, with the average of the two recorded. Hemoglobin levels were determined via the cyanmethemoglobin method using venous blood samples.\u0026rdquo;\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eAnemia was defined using the WHO thresholds of hemoglobin by sex: hemoglobin \u0026lt; 12 g/dL for females and \u0026lt; 13 g/dL for males.\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch3\u003eStatistical Analysis\u003c/h3\u003e\n\u003cp\u003eData analyses were performed using the statistical software IBM SPSS Statistics for Windows, Version 28.0. Frequencies, percentages, means, and standard deviations were computed for descriptive statistics on participant characteristics and estimation of health condition prevalence.\u003c/p\u003e\n\u003cp\u003eThe incidence of sex-related differences in the prevalence of anemia and hypertension was compared using the Pearson chi-square (\u0026chi;\u0026sup2;) test. Relationships between the continuous variables of BMI, age, systolic blood pressure, and diastolic blood pressure were determined using Pearson\u0026rsquo;s correlation (r). Statistical significance was set at p \u0026lt; 0.05.\u003c/p\u003e\n\u003ch3\u003eEthical Considerations\u003c/h3\u003e\n\u003cp\u003eThis study adhered to the guidelines of the Declaration of Helsinki. The study was approved by the Institutional Ethics Committee (IEC) of the university participating in the study (Approval No: SIU/IEC/1137). In this study, which involved retrospective analysis using anonymized EHR data, seeking prior consent from participants was exempt, as approved by the IEC. Data confidentiality was ensured by restricting access to data by the person(s) conducting the study.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eParticipant Characteristics : The analyses used results from 13628 students who completed an annual health screening from June 1, 2023, through May 31, 2024, and there were no exclusions due to missing information regarding age, body mass index (BMI), blood pressure, or hemoglobin. The group included 7012 females (51.4%) and 6616 males (48.6%). The mean age of all participants was 21.1 years (SD=2.7), with the average being 20.9 years (SD = 2.5) for females and 21.3 years (SD = 3.0) for males.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrevalence of BMI, Blood Pressure, and Anemia\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the WHO BMI classification, 58.4% of the cohort had a normal BMI, whereas 22.1% were classified as overweight or obese (Table 1). Underweight status was observed in 19.4% of the students.\u003c/p\u003e\n\u003cp\u003eRegarding blood pressure, 31.1% (n = 4,243) of the students met the 2017 ACC/AHA criteria for hypertension (\u0026ge; 130/80 mmHg).\u003c/p\u003e\n\u003cp\u003eApplying WHO sex-specific hemoglobin cut-offs (\u0026lt; 12.0 g/dL for females; \u0026lt; 13.0 g/dL for males), 53.1% of students were classified as anemic. This represents a considerable hematological burden detected through routine screening.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Prevalence of BMI Categories Among University Students (N = 13,628)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003eCategory (WHO)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003eFemale (n)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003eMale (n)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003eTotal (%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003eUnderweight\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;(\u0026lt; 18.5 kg/m\u0026sup2;)\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e1,592\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e1,058\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e19.4%\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003eNormal weight\u003c/strong\u003e (18.5\u0026ndash;24.9 kg/m\u0026sup2;)\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e4,124\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e3,837\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e58.4%\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003eOverweight\u003c/strong\u003e (25.0\u0026ndash;29.9 kg/m\u0026sup2;)\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e982\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e1,257\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e16.4%\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003eObesity\u003c/strong\u003e (\u0026ge; 30.0 kg/m\u0026sup2;)\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e314\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e464\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e5.7%\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSex-Stratified Differences in Health Risks\u003c/p\u003e\n\u003cp\u003eMarked sex-based differences were observed for both anemia and hypertension (Table 2). Contrary to the general population trends, anemia prevalence was significantly higher among males (67.4%) than among females (39.5%) when applying WHO sex-specific thresholds (\u0026chi;\u0026sup2;(1) = 1066.6, p \u0026lt; .001).\u003c/p\u003e\n\u003cp\u003eHypertension was also disproportionately higher in males. The prevalence of hypertension (\u0026ge; 130/80 mmHg) was 42.6% in males and 20.3% in females (\u0026chi;\u0026sup2;(1) = 801.4, p \u0026lt; .001).\u003c/p\u003e\n\u003cp\u003eTable 2. Health Risk Prevalence by Gender\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003e\u0026nbsp;(N = 13,628)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003eFemale\u0026nbsp;\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003e(n = 7,012)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003eMale\u0026nbsp;\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003e(n = 6,616)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e*\u003cem\u003eAnemia\u003c/em\u003e\u003cbr\u003e\u003cem\u003e\u0026nbsp;(WHO Criteria)\u003c/em\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003e7,230 (53.1%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003e2,771 (39.5%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003e4,459 (67.4%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003e\u0026lt; .001\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003eHypertension (Total)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003e4,243 (31.1%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003e1,424 (20.3%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003e2,819 (42.6%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003e\u0026lt; .001\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003eStage 1 Hypertension\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e3,142 (23.1%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e1,189 (17.0%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e1,953 (29.5%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u0026lt; .001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003eStage 2 / Crisis\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e1,101 (8.1%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e235 (3.4%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e866 (13.1%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u0026lt; .001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003e*Anemia is defined as Hb \u0026lt; 12.0 g/dL for females and \u0026lt; 13.0 g/dL for males.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eCorrelations Between Cardiometabolic Markers\u003c/p\u003e\n\u003cp\u003ePearson\u0026rsquo;s correlation analysis demonstrated statistically significant but modest associations between anthropometric and hemodynamic variables. BMI was positively correlated with both systolic blood pressure (r = 0.186, p \u0026lt; .001) and diastolic blood pressure (r = 0.213, p \u0026lt; .001). Age showed negligible to weak correlations with systolic (r = 0.044, p \u0026lt; .001) and diastolic (r = 0.019, p = .028) blood pressure.\u003c/p\u003e\n\u003cp\u003eMultivariable Analysis\u003c/p\u003e\n\u003cp\u003eAdjusted odds ratios (aOR) were derived from multivariable logistic regression models including sex, age, BMI, and academic level. The female sex and undergraduate level were used as references.\u003c/p\u003e\n\u003cp\u003eTable 3. Adjusted Logistic Regression Models for Anemia and Hypertension\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003eOutcome\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003ePredictor\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003eaOR\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003eAnemia\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003eMale (vs Female)\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003e3.20\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003e2.97 \u0026ndash; 3.45\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003eAge (per year)\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e1.02\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e1.00 \u0026ndash; 1.04\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e0.090\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003eBMI (per kg/m\u0026sup2;)\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e1.00\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e0.99 \u0026ndash; 1.01\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e0.615\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003eHypertension\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003eMale (vs Female)\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003e1.49\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003e1.38 \u0026ndash; 1.60\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003eAge (per year)\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e1.04\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e1.02 \u0026ndash; 1.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u0026lt; 0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003eBMI (per kg/m\u0026sup2;)\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e1.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e1.05 \u0026ndash; 1.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u0026lt; 0.001\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eIn the adjusted logistic regression models (Table 3), male sex was independently associated with higher odds of anemia (aOR 3.20, 95% CI 2.97\u0026ndash;3.45) and hypertension (aOR 1.49, 95% CI 1.38\u0026ndash;1.60). Hypertension was also associated with increasing age and BMI, whereas anemia was not independently associated with BMI.\u003c/p\u003e\n\u003cp\u003eClinical Referrals and Follow-up : Based on the screening findings, clinical advice and referrals were systematically documented in the EHR. Of the total cohort, 8.1% (n = 1,101) were identified as having stage 2 hypertension requiring immediate counseling, and 53.1% (n = 7,230) were referred to the University Health Center for further investigation of anemia.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis large-scale study on an annual health screening program among university students in India identified a significant problem with anemia, BP, and overweight/obesity in early adulthood. Making the most of the full set of data with no missing values for key variables (N=13,628) represents the most robust descriptive analysis of risk profiles that have been conducted on student health to date within the context of Indian higher education. These results, interpreted within the Health Promoting University framework, confirm the key role of universities as targeted sites for early care detection and health promotion.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eAnemia Burden and Sex Differences\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eIn contrast to the general population trends in India, for example, NFHS-5 [17], where females always have a higher burden, the estimated significantly higher prevalence among males than females-67.4% versus 39.5%) represents a complete reversal of the expected gender gap. The inversion of expected gender gap partly reflects the strict use of WHO diagnostic thresholds (\u0026lt;13.0 g/dL for males vs. \u0026lt;12.0 g/dL for females), which captures a large proportion of young men with mild anemia, usually missed by standard screening. Beyond definitions, this \u0026apos;hidden\u0026apos; burden may reflect gendered behavior patterns in the university setting, as male students tend to move away from home-cooked meals faster than their female peers to calorie-dense but micronutrient-poor \u0026lsquo;street foods\u0026rsquo;[18].\u003c/p\u003e\n\u003cp\u003eAccording to the results provided in Table 1, the majority (53.0%) of the students screened were found to be anemic, thus indicating the level of hematologic burden present in this young adult population. Sex stratified analysis demonstrated notable differences between males and females regarding anemia prevalence, where male students showed a substantially higher prevalence (67.4%) than female students (39.5%) (See Table 2 and Figure 1). These results differ from those collected during national population-based surveys, such as the NFHS-5, which have depicted similar results; among women of reproductive age, there is a higher overall prevalence of anemia than among male students [6]. Emerging evidence shows that anemia among young male persons continues to be underreported in both institutional and community settings, particularly when routine screening is not heavily emphasized [14,19].\u003c/p\u003e\n\u003cp\u003eThe discrepancy between the national survey trends and results of the present institutional analysis underlines the significance of context-specific surveillance. College-going students may have different eating habits, stress levels, and health-seeking behaviors, including hematological outcomes. Although the current analysis cannot provide any insight into the specific reasons for this discrepancy, the relevant literature indicates that some of the contributing factors of anemia in male students in particular may include suboptimal iron diet, irregular eating patterns, and poor utilization of preventive health care facilities [20,21]. These observations stress the demand for campus-level anemia screening and counseling programs with gender-inclusive provisions, and not considering anemia as a female health problem alone.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eCardiometabolic Risk in Early Adulthood\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eA total of 31.1% of the sample were diagnosed with hypertension (\u0026ge;130/80 mmHg). The majority of participants who met this definition were classified as stage 1 (23.1%). The more stringent criteria for diagnosing hypertension developed by the ACC/AHA in 2017 [22]have caused a great deal of confusion when applied to the younger adult population. There has been significant opposition to the use of more stringent guidelines to classify an otherwise healthy individual as hypertensive. However, when viewed in the context of Health Promoting University governing policies that promote healthy lifestyles and reduce health risks, the use of more sensitive criteria is scientifically valid. The use of more sensitive criteria allows us to identify individuals who are at an increased risk of developing hypertension (at-risk population) and who would not otherwise be recognized as being at risk if using the traditional 140/90 mm Hg cutoffs. Identifying students with stage 1 hypertension provides an important window of opportunity to provide primordial prevention via lifestyle changes (dietary changes, exercise, and stress management) to reverse the trajectory of developing stage 2 hypertension (of which 8.1% of the sample had) and to avoid the development of irreversible damage to target organs.\u003c/p\u003e\n\u003cp\u003eThe prevalence of elevated blood pressure and hypertension in our study is particularly interesting. Almost three-fifths of our subjects fulfilled the ACC/AHA [23] definition for hypertension (Stages 1 or 2), while only a quarter had normal blood pressure values (Table 1). Comparisons across both sexes revealed a higher proportion of hypertension in the male gender (66.6%) than in women (52.4%), which is in line with earlier studies showing gender variations in cardiometabolic risk in young persons [7].\u003c/p\u003e\n\u003cp\u003eThe adjusted logistic regression analyses further supported these trends. Male sex independently predicted the presence of anemia and hypertension after adjusting for age, BMI, and academic level (Table 3). Additionally, increasing age and BMI independently predicted the presence of hypertension. These relationships are consistent with established pathophysiological associations between adiposity, resistance, and blood pressure homeostasis[24,25]. Although the correlation coefficients between BMI and blood pressure were not large, the significance of these associations in a large group of people attests to the impact of being overweight on the risk of cardiovascular disease at a relatively young age.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eImplications for the Health Promoting University Framework\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eCollectively, these findings strengthen the assertion that colleges and universities are key intervention points for preventing noncommunicable diseases. In addition to promoting access to health services, a health-promoting university framework aims to provide environments that support healthy choices [5,9,12]. The fact that the current study found high rates of anemia and cardiometabolic risk factors demonstrates that screening alone does not adequately address them..\u003c/p\u003e\n\u003cp\u003eAs such, institutional responses should create structured follow-up pathways (e.g., nutrition counselling, referral systems, and health education programs tailored to each student\u0026rsquo;s needs). When developing programs to address anemia, education related to food choices, an understanding of the micronutrients needed, and a mechanism to obtain confirmation of test results and receive treatment are recommended. Regarding hypertension and overweight/obesity, results indicate that integrating lifestyle changes into diet quality, activity level, sleep habits, and stress management is effective when delivered to college campuses [10,11]. When developing such programs, it is essential to incorporate gender-related issues, as well as social and cultural influences that affect individual attitudes towards health-related behaviors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImplications for Health Promotion Policy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOn the basis of the Health Promoting University, the implications of the study reveal the need for more holistic approaches to the university, shifting from screenings to a system-wide approach for health promotion [3,4]. The study suggests the need for the institutionalization of health screenings as a systematic and universal university health initiative to identify prevalent yet often asymptomatic diseases such as anemia and cardiometabolic risk factors, and to address issues of inequity in self-selection. The differences in anemia and hypertension by sex also emphasize the need for gender-sensitive and equity-oriented health promotion strategies that take into account issues of nutrition, stress, lifestyle, and sociocultural factors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImplications for Health Promotion Practice\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHowever, universities also need to promote health-supportive campus environments through improvements in the affordability and nutritional quality of food, physical activity opportunities, and mental health services. Follow-through and continuity of care also need to be addressed in effective screening practices. Finally, the application of data from routine health practices to create learning health systems would allow for monitoring and evaluation of health promotion in higher education.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eStrengths and Limitations\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe main strength of this study is its large sample size, which comes from a screening program, thereby eliminating self-selection bias and improving internal validity. The application of uniform criteria set internationally (WHO, ACC/AHA [23]) and using denominators similarly across analyses increased the reliability of the results. The application of multivariate analysis increased the depth of analysis by adjusting for significant variables.\u003c/p\u003e\n\u003cp\u003eThis study has several limitations that should be considered. The study had a cross-sectional design and was retrospective; therefore, it was not possible to establish causality, and data on blood pressure and hemoglobin were considered after only one screening visit rather than being considered multiple times. It is also apparent that lifestyle, dietary, or socioeconomic \u0026nbsp; factors were not available in this dataset, which may affect the observed relationship. Future prospective studies incorporating behavioral and environmental data would help clarify causal pathways and inform more targeted interventions.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis paper presents an in-depth institutional level analysis of anemia and cardiometabolic risk factors among university students in India, using a comprehensive dataset collected as part of an institutional health screening event every year. The results illustrate that a large number of students are enrolled in higher education institutions carrying undetected levels of risk to their health, contrary to popular perceptions that students in higher education institutions are healthy.\u003c/p\u003e\n\u003cp\u003eA high prevalence of anemia, hypertension, and overweight/obesity was found in early adulthood, in conjunction with a marked difference between sexes in terms of risk factors. Even without the ability to establish causality due to the cross-sectional study methodology, these findings show that asymptomatic morbidity can be identified through university-based screening in a life-stage in which prevention is most effective.\u003c/p\u003e\n\u003cp\u003eIn the context of health promotion, such evidence supports the continued significance of higher education institutions in terms of acting as pivotal social environments that can be effectively utilized for large-scale preventive interventions. It is noted that such institutions have the unique advantage of bringing together a vast number of youth from diverse backgrounds at a crucial life stage.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval:\u0026nbsp;\u003c/strong\u003eEthics approval was received from the Independent Ethics Committee of Symbiosis International (Deemed University), Proposal No.SIU/IEC/1137, dated August 22, 2025.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate:\u003c/strong\u003e\u0026nbsp; In this study, which involved retrospective analysis using anonymized EHR data, seeking prior consent from participants was exempt, as approved by the Independent Ethics Committee of Symbiosis International (Deemed University) (IEC). Data confidentiality was ensured by restricting access to data by the person(s) conducting the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Statement:\u0026nbsp;\u003c/strong\u003eNo specific grant was received for this research from any funding body in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest Statement:\u0026nbsp;\u003c/strong\u003eThe authors have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u0026nbsp;\u003c/strong\u003eThe data supporting the conclusions of this research are not publicly available as they contain information that might breach the privacy of research participants. Data can be made available upon reasonable request from the corresponding author and with the Institutional Ethics Committee permission\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConceptualization:\u003c/strong\u003e R.Y, A.C\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethodology:\u0026nbsp;\u003c/strong\u003eR.Y, A.C\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Curation:\u0026nbsp;\u003c/strong\u003eA.C\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFormal Analysis:\u0026nbsp;\u003c/strong\u003eA.C\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInvestigation:\u0026nbsp;\u003c/strong\u003eA.C\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWriting \u0026ndash;\u0026nbsp;\u003c/strong\u003eOriginal Draft: A.C\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWriting \u0026ndash;\u0026nbsp;\u003c/strong\u003eReview \u0026amp; Editing: R.Y\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupervision:\u003c/strong\u003e R.Y\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProject Administration:\u0026nbsp;\u003c/strong\u003eA.C\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSawyer SM, Azzopardi PS, Wickremarathne D, Patton GC. The age of adolescence. Lancet Child Adolesc. Health. 2018. https://doi.org/10.1016/S2352-4642(18)30022-1\u003c/li\u003e\n\u003cli\u003eViner RM, Ozer EM, Denny S, Marmot M, Resnick M, Fatusi A, et al. Adolescence and the social determinants of health. The Lancet. 2012. https://doi.org/10.1016/s0140-6736(12)60149-4\u003c/li\u003e\n\u003cli\u003ePatton GC, Sawyer SM, Santelli JS, Ross DA, Afifi R, Allen NB, et al. Our future: a Lancet commission on adolescent health and wellbeing. The Lancet. 2016. https://doi.org/10.1016/S0140-6736(16)00579-1\u003c/li\u003e\n\u003cli\u003eBonell C, Parry W, Wells H, Jamal F, Fletcher A, Harden A, et al. The effects of the school environment on student health: A systematic review of multi-level studies. Health Place. 2013;21. https://doi.org/10.1016/j.healthplace.2012.12.001\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Noncommunicable diseases [Internet]. 2025 [cited 2026 Jan 10]. https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases. Accessed 10 Jan 2026\u003c/li\u003e\n\u003cli\u003eManjita Satapathy M, Kumar Kar P, Bhuyan M, Kalyan Mishra D, Ranjan Lenka S, chandra Pradhan P. European Journal of Cardiovascular Medicine (EJCM) Prevalence of Obesity and Hypertension Among Adolescents: A Cross-sectional Study in an Urban Slum of Cuttack City. https://www.healthcare-bulletin.co.uk/\u003c/li\u003e\n\u003cli\u003eHaase CB, Gyuricza JV, Brodersen J. New hypertension guidance risks overdiagnosis and overtreatment. BMJ. 2019;l1657. https://doi.org/10.1136/bmj.l1657\u003c/li\u003e\n\u003cli\u003eNewton J, Dooris M, Wills J. Healthy universities: an example of a whole-system health-promoting setting. Glob Health Promot. 2016;23. https://doi.org/10.1177/1757975915601037\u003c/li\u003e\n\u003cli\u003eAmerican College Health Association. The Healthy Campus Framework. 2020; \u003c/li\u003e\n\u003cli\u003eSu FH, LSC, CHJ, YPW, LYH, \u0026amp; SKY. Analysis of the Health Checkup Data of Freshmen from a Taiwanese University. 2005; \u003c/li\u003e\n\u003cli\u003eSeilo N, Paldanius S, Autio R, Koskela T, Kunttu K, Kaila M. Association between university students\u0026rsquo; two-staged health screening and student health care utilisation: register based observational study. BMJ Open. 2022;12:e052824. https://doi.org/10.1136/bmjopen-2021-052824\u003c/li\u003e\n\u003cli\u003eDooris M. Expert voices for change: Bridging the silos-towards healthy and sustainable settings for the 21st century. Health Place. 2013;20. https://doi.org/10.1016/j.healthplace.2012.11.009\u003c/li\u003e\n\u003cli\u003eTsouros AD, Dowding G, Thompson J, Dooris M. Health promoting universities : Concept, experience and framework for action. World Health Organization. 1998. \u003c/li\u003e\n\u003cli\u003ePatel G, Parmar A, Zalavadiya D, Talati K. Tackling the menace of anemia and hemoglobinopathies among young adults \u0026ndash; Conceptualizing university-level screening. Indian Journal of Community Medicine. 2021;46:117. https://doi.org/10.4103/ijcm.IJCM_329_20\u003c/li\u003e\n\u003cli\u003eMcGrath AB, Weinstock J, Cloutier R, Christensen M, Taylor DJ, Henderson CE. Examination of college student health behaviors and self-reported executive functions. Journal of American College Health. 2023;71. https://doi.org/10.1080/07448481.2021.1904951\u003c/li\u003e\n\u003cli\u003ePeltzer K, Pengpid S, Mohan K. Prevalence of health behaviors and their associated factors among a sample of university students in India. Int J Adolesc Med Health. 2014;26:531\u0026ndash;40. https://doi.org/10.1515/ijamh-2013-0331\u003c/li\u003e\n\u003cli\u003eMinistry of Health and Family Welfare. NATIONAL FAMILY HEALTH SURVEY (NFHS-5). \u003c/li\u003e\n\u003cli\u003eHomepage J, Yadav Jagtap P, Saikia N. Insights from the National Family Health Survey (NFHS-5. Demogr. India. 2025. \u003c/li\u003e\n\u003cli\u003eKassebaum NJ, Jasrasaria R, Naghavi M, Wulf SK, Johns N, Lozano R, et al. A systematic analysis of global anemia burden from 1990 to 2010. Blood. 2014. https://doi.org/10.1182/blood-2013-06-508325\u003c/li\u003e\n\u003cli\u003eGupta R, Gaur K, Ahuja S, Anjana RM. Recent studies on hypertension prevalence and control in India 2023. Hypertension Research. 2024. https://doi.org/10.1038/s41440-024-01585-y\u003c/li\u003e\n\u003cli\u003eKotecha P. Nutritional anemia in young children with focus on Asia and India. Indian Journal of Community Medicine. 2011;36:8. https://doi.org/10.4103/0970-0218.80786\u003c/li\u003e\n\u003cli\u003eLevine GN, Al-Khatib SM, Beckman JA, Birtcher KK, Bozkurt B, Brindis RG, et al. Force on Clinical Practice Guidelines. Hypertension [Internet]. 2018;71:13\u0026ndash;115. https://doi.org/10.1161/HYP.0000000000000065/-/DC1\u003c/li\u003e\n\u003cli\u003eJohnson HM, Shimbo D, Abdalla M, Altieri MM, Bress AP, Carter J, et al. 2025 AHA/ACC/AANP/AAPA/ABC/ACCP/ACPM/AGS/AMA/ASPC/NMA/PCNA/SGIM Guideline for the Prevention, Detection, Evaluation and Management of High Blood Pressure in Adults: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2025;152:e114\u0026ndash;218. https://doi.org/10.1161/CIR.0000000000001356\u003c/li\u003e\n\u003cli\u003eHall JE, da Silva AA, do Carmo JM, Dubinion J, Hamza S, Munusamy S, et al. Obesity-induced Hypertension: Role of Sympathetic Nervous System, Leptin, and Melanocortins. Journal of Biological Chemistry. 2010;285:17271\u0026ndash;6. https://doi.org/10.1074/jbc.R110.113175\u003c/li\u003e\n\u003cli\u003eZhou B, Bentham J, Di Cesare M, Bixby H, Danaei G, Cowan MJ, et al. Worldwide trends in blood pressure from 1975 to 2015: a pooled analysis of 1479 population-based measurement studies with 19\u0026middot;1 million participants. The Lancet. 2017;389. https://doi.org/10.1016/S0140-6736(16)31919-5\u003c/li\u003e\n\u003c/ol\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":"journal-of-epidemiology-and-global-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Journal of Epidemiology and Global Health](https://www.springer.com/journal/44197)","snPcode":"44197","submissionUrl":"https://submission.nature.com/new-submission/44197/3","title":"Journal of Epidemiology and Global Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Health Promoting University, student health, anemia, hypertension, cardiometabolic risk, higher education","lastPublishedDoi":"10.21203/rs.3.rs-9158044/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9158044/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"This quantitative, retrospective observational study investigated risks of student health using electronic health records of an annual health screening program conducted at a private university in India. Data were analyzed from 13,628 students aged 18 to 30 years who participated in the health screening program between June 2023 and May 2024, ensuring that all students were included in the study, thus eliminating the risk of self-selection bias. Body mass index, blood pressure, and hemoglobin levels were measured and categorized according to international clinical standards. The results were analyzed to determine the prevalence of anemia, high blood pressure, and overweight among students using comparative statistical tests to determine differences between the sexes, as well as to determine associations between variables using multivariable logistic regression analysis. The results showed that there was a high burden of asymptomatic anemia and cardiometabolic risk factors among students, with significant differences between the sexes, as well as associations with age and body mass index.","manuscriptTitle":"Anemia and Cardiometabolic Risk Among University Students in India: Findings from a Health Screening Program","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-16 17:40:58","doi":"10.21203/rs.3.rs-9158044/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-02T18:33:24+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-28T10:02:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"225974732523420225556727569348372021509","date":"2026-04-17T02:15:46+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-16T11:11:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-16T11:11:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"17027375933937844312202762359751263819","date":"2026-04-12T19:21:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"178377853915083765510552478071372470099","date":"2026-04-11T18:58:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"271460806616217488580607407689144894874","date":"2026-04-11T16:36:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"36822862325057395528858028929952252324","date":"2026-04-09T05:04:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-08T21:00:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-07T19:27:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-06T08:15:27+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Epidemiology and Global Health","date":"2026-03-28T04:10:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-epidemiology-and-global-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Journal of Epidemiology and Global Health](https://www.springer.com/journal/44197)","snPcode":"44197","submissionUrl":"https://submission.nature.com/new-submission/44197/3","title":"Journal of Epidemiology and Global Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c6bf6929-0793-44f7-be71-fda7e798d9b9","owner":[],"postedDate":"April 16th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-02T18:33:24+00:00","index":57,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-16T17:40:58+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-16 17:40:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9158044","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9158044","identity":"rs-9158044","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}