Authors:
A. Novák Department of Health Promotion, Hungarian Defence Forces Medical Center, Budapest, Hungary

Search for other papers by A. Novák in
Current site
Google Scholar
PubMed
Close
https://orcid.org/0000-0002-7335-7735
,
Zs. Rázsó Department of Health Promotion, Hungarian Defence Forces Medical Center, Budapest, Hungary
School of Doctoral Studies, National University of Public Service, Budapest, Hungary

Search for other papers by Zs. Rázsó in
Current site
Google Scholar
PubMed
Close
,
A. Sótér Department of Health Promotion, Hungarian Defence Forces Medical Center, Budapest, Hungary
School of Doctoral Studies, National University of Public Service, Budapest, Hungary

Search for other papers by A. Sótér in
Current site
Google Scholar
PubMed
Close
, and
C. Nyakas Faculty of Health Sciences, Semmelweis University, Budapest, Hungary
University of Physical Education, Budapest, Hungary

Search for other papers by C. Nyakas in
Current site
Google Scholar
PubMed
Close
Open access

Abstract

Introduction

The continuous collection, monitoring, and analysis of morbidity data enable health professionals to plan the capacity of the care system, to organise and optimise care, to measure the burden of diseases resulting from each morbidity, and to estimate its expected evolution.

Material and methods

In our study, we analyse the data of patient flow reports for the period 2011 to 2020 for the healing and preventive basic service defined as the basic task of the primary health care system (troop health service) of the Hungarian Defence Forces.

Results

Over 850,000 doctor-patient encounters over the ten-year period were mostly due to some form of acute care need, infection, and respiratory illness. The morbidity structure has not changed significantly over the period. In all cases, the top three were diseases of the respiratory system (J00-J99), diseases of the circulatory system (I00-I99), as well as musculoskeletal and connective tissue diseases (M00-M99). In 2020, the highest number of people with restrictions for health reasons in the period under review was 131 for diseases of the circulatory system and 179 for musculoskeletal disorders. In recent years, the time spent on medical leave or on sick leave has increased significantly in terms of the number of cases of incapacity to work.

Conclusions

Accurate knowledge of morbidity and health data can also provide the military leadership with important information on combat fitness, especially when the ever-increasing task load (mission activity, border tasks, Covid-19) has to be met by an armed corps selected from an ageing population.

Abstract

Introduction

The continuous collection, monitoring, and analysis of morbidity data enable health professionals to plan the capacity of the care system, to organise and optimise care, to measure the burden of diseases resulting from each morbidity, and to estimate its expected evolution.

Material and methods

In our study, we analyse the data of patient flow reports for the period 2011 to 2020 for the healing and preventive basic service defined as the basic task of the primary health care system (troop health service) of the Hungarian Defence Forces.

Results

Over 850,000 doctor-patient encounters over the ten-year period were mostly due to some form of acute care need, infection, and respiratory illness. The morbidity structure has not changed significantly over the period. In all cases, the top three were diseases of the respiratory system (J00-J99), diseases of the circulatory system (I00-I99), as well as musculoskeletal and connective tissue diseases (M00-M99). In 2020, the highest number of people with restrictions for health reasons in the period under review was 131 for diseases of the circulatory system and 179 for musculoskeletal disorders. In recent years, the time spent on medical leave or on sick leave has increased significantly in terms of the number of cases of incapacity to work.

Conclusions

Accurate knowledge of morbidity and health data can also provide the military leadership with important information on combat fitness, especially when the ever-increasing task load (mission activity, border tasks, Covid-19) has to be met by an armed corps selected from an ageing population.

Introduction

The health care system of the Hungarian Armed Forces - as well as Hungary’s health care system - has a dual structure, in other words, it consists of primary care and specialist care (outpatient and inpatient specialist care). The care system is based on an institutional system for the differential care of patients in different conditions and on the principle of progressivity. The gatekeeper function is located at the lowest level, which ensures that higher levels of care are taken by patients only when justified, team health services responsible for primary health care.

In peacetime, the basic tasks of the team health service (troop medical service) are as follows [1]:

  1. healing, preventive, and care work (e.g., first aid, general medical care, medicine supply, referral to specialist clinics and hospitals, work up, performing screenings, care of hypertensive patients)

  2. public health - epidemiological activities (e.g., notification and declaration of infectious patients, on-site inspections, epidemiological investigations)

  3. health insurance for combat training, combat readiness, and mobilisation tasks

  4. participation in the health training of the staff and education for a healthy lifestyle

There are basically four types of methods available for monitoring morbidity in the given population and for estimating the disease burden [2]:

  1. Registries based on data from inpatient institutions (e.g., cancer registry).

  2. Population health surveys (e.g., National Population Health Survey-NPHS).

  3. Mandatory reporting and registration system for communicable diseases (e.g., Epidemiological Surveillance System and Information System-ESSIS, pulmonology network - including TBC - annual morbidity data).

  4. General practitioners/primary care morbidity monitoring system (e.g., General Practitioner Morbidity Data Collection Program - GPMDCP).

Regarding our study, the data collection methods belonging to the group of type 4 are relevant, which have spread in two versions around the world. One is case-based data collection, which records data for each physician-patient encounter, the other is the so-called sentinel-type data collection, in which designated health services collect data specifically for a specific group of diseases (e.g., flu) [3]. The team health services submit an annual report on the personal and material infrastructure of the surgeries and on the patient traffic data of primary care (data on the use of team medical care, referred to a specialist clinic, treated within the framework of inpatient care, incapacity for work, illness data) to the Health Centre of the Hungarian Defence Forces. This form of reporting is connected to case-based data collection as data is recorded during each physician-patient meeting. Patient traffic report data provide valuable information for planning the capacity of the health care system, organising care, measuring the disease burden and estimating its expected evolution, establishing force protection (e.g., planning prevention programs), and monitoring warfighting capability.

Sample and method

To perform the study, we used the data tables of the patient traffic reports used within the Hungarian Defence Forces, which were combined to create a database. We used Microsoft Excel 2010 to analyse the data and create the graphs. The following indicators were determined during the analysis.

To measure the burden of disease:

  1. a) Calculation of the morbidity distribution ratios used to analyse the development of the disease structure by staff category.
  2. b) Analysis of the data on the use of specialist care, which is both an indicator of definitive care in relation to primary care and a source of information about the frequency of cases exceeding the competence of primary care.
  3. c) Analysis of hospital days and incapacitated days by staff category, from which we can conclude the severity of some cases.

Results

Data on the use of home-defence primary health care

In the period from 2011 to 2020, the care obligation of the team doctor’s surgeries providing primary care covered 237,168 people. Vast majority of the persons to be treated medically - more than two-thirds – came from professional and contract military members each year. The proportion of civilian employees (government officials and civil servants) ranged from 11 to 27%, while that of educational students ranged from 2 to 7%. Over the ten years, 1–5% of the persons to be treated fell into the other category. The actual annual patient turnover was 850,655 cases, whose 62–75% were recorded as new cases (the number of doctor visits with a given diagnosis for the first time in the given year).

Changes in the duty of the team health service care and the composition of those to be treated, as well as the changes in the staff in need of care between 2011 and 2020 are summarised in Table 1.

Table 1.

Data on the use of military primary health care from 2011 to 2020

Year Care obligation (person)* Composition of the persons to be treated (%)** Care (%) *** Care (person)****
2011 30,439 77/11/7/5 nd. nd.
2012 21,919 80/15/1/4 19 4,163
2013 23,455 81/14/3/2 17 3,987
2014 23,688 80/15/1/4 17 4,027
2015 25,272 77/16/3/4 11 2,780
2016 20,518 70/26/3/1 13 2,667
2017 23,861 78/18/2/2 15 3,579
2018 27,592 72/19/4/2 12 331
2019 21,732 75/16/3/2 24! 5,216
2020 18,692 68/27/nd./nd. 34! 6,355

* The care obligation of the team doctor's surgeries providing primary care (person).

** Composition of the persons to be treated (%): professional and contract military members/civil servants (government officials, public servants)/school students/other.

*** Care for those in the medical care area (%).

**** Care for those in the medical area (person).

nd. No data available.

! remarkable growth.

Data of disease (morbidity)

Accurate knowledge of morbidity data (disease structure, prevalence, incidence indicators) can also provide the military leadership with important information about combat capability and maintaining combat capability. Seeing that only new cases are reported according to ICD details, it is only possible to estimate the morbidity structure of the staff from the data. The disease structure calculated from the data provides the best information on the reason for using team medical care for new cases. Prevalence-type indicators are also needed to produce a complete picture of the morbidity structure of the staff (such indicators can be obtained from test data performed during periodic suitability checks). From the new cases we have the possibility to calculate an incidence indicator, with the help of which we can estimate the absolute risk of the occurrence of a given disease in the whole population (in this case to be treated) for the given period (in this case 10 years). Patient data sheets according to the International Classification of Diseases (ICD) provide information on the reasons for using team medicine - at the same time, on the evolution of the disease structure of each staff category [4].

Before presenting the results, we should note the fact that our calculations were performed with all the indicated disease groups, however, when marking the rankings, we intentionally omitted the disease group of factors influencing health status and the relationship with health services (ICD code: Z00-Z99), which appeared with the highest proportion of all staff categories except for school students. This ICD classification has been applied so generically and widely, and with such frequency that we would have obtained statistics not supported by professional arguments. The obtained results still correspond to reality because the frequency sequences came one position ahead. The results for the morbidity structure over ten years for professional, contract officers, non-commissioned officers, and contract crew are summarised in Fig. 1. According to this, between 2011 and 2013, the respiratory system (ICD code: J00-J99) was the first, the musculoskeletal and connective tissue disorders were the second (ICD code: M00-M99), and the infectious and parasitic diseases (ICD code: A00-B99) were the third most often included in statistics. Each case could be considered an acute occurrence. In 2014, in the third place “tied”, diseases of the circulatory system (ICD code: I00-I99) were also added to the list, more than half (55%) of which being hypertensive disease (ICD code: I10-I15). From 2016, there was a higher number of doctor visits with high blood pressure within the army, so much so that this disease was in the first place in the statistics in the years 2018-19. In 2019, endocrine, nutritional, and metabolic (ICD code: E00-E90) diseases came right away in second place in the statistics, with a high proportion of diabetes (ICD code: E10-E14).

Fig. 1.
Fig. 1.

The highest number of diseases in the period 2011-2020 among professional and contract military personnel (the most common 10, the second most common 7 while the third most common disease was marked with 3 units)

* In connection with the COVID-19 pandemic, a new ICD code was created (ICD code: U0710, title: positive result with COVID-19 virus), which became current in April 2020. Respiratory diseases (J00-J99), musculoskeletal and connective tissue disorders (M00-M99), infectious and parasitic diseases (A00-B99), circulatory system diseases (I00-I99), dental and digestive system diseases (K00-K99), endocrine, nutritional, and metabolic disorders (E00-E90)

Citation: Developments in Health Sciences 4, 2; 10.1556/2066.2022.00052

If we examine the most common diseases among the students of the educational institution, it can be said that the diseases of the respiratory system (ICD code: J00-J99) are in the first place, infectious and parasitic diseases (ICD code: A00-B99) and the injury, poisoning, and certain other consequences of external causes (ICD code: S00-T98) occur second, while in third place are diseases of the musculoskeletal system and connective tissue (ICD code: M00-M99). There has been no substantial change in this population over the years. The same static state could be observed among the civilian (civil servant, public servant) staff, but the pattern was different. With exception of 2019’s, circulatory system diseases (ICD code: I00-I99) were in the first place every year, most of which was hypertension (ICD code: I10-I15). The second and third highest numbers of diseases were either musculoskeletal and connective tissue (ICD code: M00-M99) or respiratory (ICD code: J00-J99) conditions.

From the analysis of the disease structure, we can conclude that the first three most common disease groups in the military staff are mainly those requiring acute care (respiratory diseases, bone-musculoskeletal disorders, infectious and parasitic diseases), but circulatory system diseases (mainly hypertension) have appeared, as well as endocrine, nutritional, and metabolic diseases including diabetes. In the civilian population - presumably due to the higher age of the soldiers - chronic non-communicable diseases come to the fore, prominently circulatory diseases (mainly hypertension), followed by respiratory, bone-musculoskeletal, gastrointestinal, and endocrine diseases. The morbidity data show consistently the unfavourable effect of age on the increase in the disease burden and on the increase in the proportion of chronic non-communicable diseases, which can be most obviously seen in relation to diseases of the circulatory system. For this reason, professional and contract military personnel pre-employment aptitude tests are of a particular importance, periodic aptitude tests with frequency according to age, which involve the early detection of premorbid conditions, and consequently the potential for more effective complex treatment.

Data on the use of specialist care

In case the care of patients visiting primary care or making an accurate diagnosis exceeds the competence of primary care, the primary care provider refers the patients to a specialist clinic or directly to an inpatient institute. Of the 850,655 doctor-patient meetings over ten years, the number of referrals was 151,577, where 49–69% of the referrals concerned military clinics and 51–31% were referred to civilian clinics. The definitive nature of team health care seems to be confirmed by the fact that in the period examined, on average 15–18.8% of all consultation appearances were further referred to specialist appointments. The professional merits - the correct diagnosis - is informed by the fact that the specialist clinic has established a diagnosis different from the diagnosis in the referral in the average 1–3% of the referrals. General outpatient specialist care also includes ongoing specialist care for a patient with a chronic illness that does not require inpatient care. Between 2011 and 2020, 11–34% of those in the care of team doctor’s offices received care, furthermore, there was a year (2020) when more than one third of those in care had a chronic illness (Table 1). In view of the data, the three most common causes of care were: circulatory system disease, endocrine, nutritional, and metabolic disease (most of which is diabetes), as well as bone, musculoskeletal, and connective tissue disease.

Inpatient care data

During the ten years, the number of referrals from the team doctor’s offices to the Hungarian Defence Forces Health Centre was 12,732, the number of admissions was 5,484, while 17,622 people in total were referred to civilian hospitals and 10,171 were admitted. The proportion of referrals and admissions ranged from 12 to 100% over the ten years. Based on the proportions of referrals and admissions by staff categories it can be stated that almost 2/3 of the military (and student) staff were treated in civil inpatient institutions. The severity of cases admitted to inpatient care can be informed by the duration of care (number of hospital days). The total number of hospital nursing days from the beginning of 2011 to the end of 2020 was 87,341 days. The duration of the average stay in hospital, broken down into days by staff category, shows that the students of the educational institution had an average of 3 days, the contract staff 4 days, the professional and contract officers, including non-commissioned officer staff spent an average of 6 days in hospital, while civil servants and public servants spent an average of 8 days in hospital. Longer nursing days for civilian employees may be an indicator of a higher sickness burden due to a higher average age or a need for chronic care.

Data of incapacity for work

The term incapacity for work means medical leave for military personnel and sick pay for civilian personnel. The total number of cases of incapacity for work during the 10 years was 212,378 and the total time spent on sick leave/sick pay was 1,533 088 (!) days. The changes in the number of health care cases and doctor-patient meetings affecting the earning capacity of the Hungarian Defence Forces were summarised in Table 2. More than 90% of incapacity cases and incapacity days concerned military personnel (professional, contract officer, non-commissioned officer, and contract crew). Examining the average length of incapacity for work by staff category, we can set the following order: school student (average: 5.7 days), contract crew and professional, contract officer, non-commissioned officer (average: 8.9 days), and government official, public servant (average: 15 days).

Table 2.

Data on incapacity for work affecting the Hungarian Defence Forces staff from 2011 to 2020

2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Number of incapacity for work (NIW) 35,435 14,785 19,880 20,612 18,351 27,518 22,408 9,333 20,633 23,423
Time spent on sick leave/sick pay (TSSL, number of the days) 253,485 112,485 152,406 161,202 149,194 171,079 173,367 77,409 192,577 251,086
TSSL/NIW 7,15 7,61 7,67 7,82 8,13 6,22 7,74 8,30 9,33 10,71
Doctor-patient meeting (case) 103,450 88,733 81,003 77,106 82,519 76,485 74,518 82,674 88,819 95,348
Total number of hospital days 3,546 6,879 5,836 6,433 4,592 5,525 5,461 6,025 37,889* 5,155

Qualification for military service with restrictions is most often given to the tested staff due to diseases of the circulatory system (ICD code: I00-I99) and diseases of the musculoskeletal system and connective tissue (ICD code: M00-M99). The annual ratings are summarised in Table 3.

Table 3.

The number of soldiers (person) in the Hungarian Defence Forces with a qualification suitable with restrictions for health reasons from 2012 to 2020

2012 2013 2014 2015 2016 2017 2018 2019 2020
Diseases of the circulatory system (I00-I99) 66 92 76 72 58 61 104 nd. 131
Musculoskeletal and connective tissue disorders (M00-M99) 51 151 100 81 118 109 148 nd. 179

nd: No data available.

Discussion

In our study, we analysed the patient record of the team health services between 2011 and 2020, addressing two important issues. We drew conclusions based on the data of using primary and specialist care about the development of the disease burden characteristic of the personnel, which shows a close link with age. On the basis of the development of the morbidity structures according to the staff categories, the data of using primary and specialist care verified that the burden of disease shows an increasing tendency with coming of age, which in the near future - due to an unfavourable change in the pension system - can pose a challenge in terms of force planning and capability and will be an unmanageable problem for team health services, if their personal infrastructure will not be developed. The two issues are interlinked.

At an international level, persons entering the armed forces enjoy better health than the average civilian population. However, following the termination of military service the benefits of their health status decreases and their health status may become worse than that of the civilians [5–8]. The health behaviour of the demobilised soldiers will become worse than that of the civilians: they are more likely to smoke, eat less healthy food, and do less activities. The results of the longitudinal research carried out within the framework of the U. S. Army also shows that 75% of the health estimate index of the staff going to external service fell into the “very good” category while this index dropped to 60% when returning [9]. The causal deductions carried out during the examinations found out that this decrease is the consequence of pressure and challenges emerging during external service and could be traced back to the circumstances of the service. It was also examined how the level of pressure tolerance in the returning staff has changed. The results show that the level of pressure tolerance is inversely related to age; the staff over 40 years old showed twice lower pressure tolerance level than the staff between 21 and 25 years old. Within the group of men, the rates of mental diseases were higher than of women and men have sleep disturbances in greater proportion as well [9].

In Hungary, when comparing the civilian population with soldiers, it can be said that the morbidity odds ratio in the military forces increases less steeply overtime, that is, age is not as big of a burden on soldiers as on civilians [10, 11].

Conclusions

The continuous collection, (monitoring), and analysis of morbidity (disease) data gives health professionals the opportunity to plan the capacity of the care system, to organise and optimise care, to measure the burden of disease resulting from each disease, and to estimate its expected evolution. Team health services, which are subject to continuous loss of capability and capacity, still have a staff, capable of carrying out medical force protection activities almost beyond its power and possibilities, however, the system can no longer be loaded. Management of the problem cannot be postponed, as the development of human infrastructure for team health services has once again become an unavoidable problem in military health. It is also inevitable for team health professionals to create a career perspective which offers young military doctors and health professionals a competitive alternative not only in terms of civic life but compared to the career model provided by Western European countries, that is, through the implementation of certain conditions (working conditions, advancement, training, benefits, competitive income-salary reform). The rejuvenation of the personnel of the Hungarian Defence Forces is a strategic issue, which has two ways of implementation - the restoration of the post-employment pension system and the integration of young people in society into the armed forces (professional, contractual, voluntary reserve) – and simultaneous application may be the solution that produces the fastest results.

Authors’ contribution

AN conceptualised the study, reviewed the scientific literature, collected the data, carried out the statistical analyses, and summarised the results. ZR collected the data, conceptualised the study. AS supervised the data collection, critically reviewed the manuscript, and approved the final manuscript. CN conceptualised the study, supervised the data collection, and critically reviewed the manuscript.

Ethical approval

This study was conducted in accordance with the 2008 revision of the 1975 Declaration of Helsinki.

Conflict of interest/funding

The authors declare no conflicts of interest and no financial support was received for this study.

References

  • 1.

    Csapathadtáp szakutasítás az állandó harckészültség időszakára (htp/16), IV rész: A személyi állomány egészségügyi ellátása [Specialist instruction in the period of constant combat readiness, Part 4: Health care for military personnel]: Magyar Honvédség kiadványa; 1990. [Article in Hungarian].

    • Search Google Scholar
    • Export Citation
  • 2.

    Donaldson RJ , Donaldson LJ . Assessing the health of the population: information and its uses In: Donaldson RJ , Donaldson LJ . Essential public health medicine, London: Kluwer Academic; 1993.

    • Search Google Scholar
    • Export Citation
  • 3.

    Széles Gy , Fülöp Ildikó K , Bordás I , Ádány R . A krónikus nem fertőző betegségek okozta morbiditás alakulása Magyarországon a HMAP és a GYOGYINFOK adatai tükrében [Evolution of morbidity caused by chronic non-communicable diseases in Hungary in the light of HMAP and GYOGYINFOK data]. In: Ádány R , editors. A magyar lakosság egészségi állapota az ezredfordulón [The state of health of the Hungarian population at the turn of the millennium]. Budapest: Medicina Könyvkiadó Rt; 2003. 4373. [in Hungarian].

    • Search Google Scholar
    • Export Citation
  • 4.

    finanszirozas.neak.gov.hu [Internet]. Betegségek Nemzetközi Osztályozása (BNO) [International Classification of Diseases (ICD)]. Budapest: National Health Insurance Fund of Hungary (NEAK); [cited 2021 Apr 23]. Available from: http://finanszirozas.neak.gov.hu/forum/BNO/index.asp[in Hungarian].

    • Search Google Scholar
    • Export Citation
  • 5.

    MSMR . Relationships between abnormal findings during medical examinations and subsequent diagnoses of significant conditions, active components, U.S. Armed Forces, January 1998-October 2006. MSMR Med Surveill Monthly Rep 2007;13:2-6.

    • Search Google Scholar
    • Export Citation
  • 6.

    Agha Z , Lofgren RP , VanRuiswyk JV , Layde PM . Are patients at veterans affairs medical centers sicker?: a comparative analysis of health status and medical resource use. Arch Intern Med 2000;160:3252-3257. https://doi.org/10.1001/archinte.160.21.3252.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 7.

    Almond N , Kahwati L , Kinsinger L , Porterfield D . The prevalence of overweight and obesity among U.S. military Veterans. Mil Med 2008;173:544-549. https://doi.org/10.7205/milmed.173.6.544.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 8.

    Hoerster KD , Lehavot K , Simpson T , McFall M , Reiber G , Nelson KM . Health and health behavior differences: U.S. Military, veteran, and civilian men. Am J Prev Med 2012;43:483489. https://doi.org/10.1016/j.amepre.2012.07.029.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 9.

    MSMR . Mental health encounters and diagnoses following deployment to Iraq and/or Afghanistan, U.S. Armed Forces, 2001–2006. MSMR Med Surveill Monthly Rep 2007;14:28.

    • Search Google Scholar
    • Export Citation
  • 10.

    Sótér A . A magyar honvédség egészségkockázati térképe, a személyi állomány egészségmagatartásának helyőrségi különbségei [Health risk map of the Hungarian Defence Forces, garrison differences in the health behaviour of the military personnel]. Hadmérnök 2009;4:3. [Article in Hungarian].

    • Search Google Scholar
    • Export Citation
  • 11.

    KSH . Európai lakossági egészségfelmérés. [European public health survey]. [Internet]. Budapest: Hungarian Central Statistical Office; 2014. [cited 2018 Feb 23]. Available from: http://www.ksh.hu/docs/hun/xftp/stattukor/elef14.pdf[in Hungarian].

    • Search Google Scholar
    • Export Citation
  • 1.

    Csapathadtáp szakutasítás az állandó harckészültség időszakára (htp/16), IV rész: A személyi állomány egészségügyi ellátása [Specialist instruction in the period of constant combat readiness, Part 4: Health care for military personnel]: Magyar Honvédség kiadványa; 1990. [Article in Hungarian].

    • Search Google Scholar
    • Export Citation
  • 2.

    Donaldson RJ , Donaldson LJ . Assessing the health of the population: information and its uses In: Donaldson RJ , Donaldson LJ . Essential public health medicine, London: Kluwer Academic; 1993.

    • Search Google Scholar
    • Export Citation
  • 3.

    Széles Gy , Fülöp Ildikó K , Bordás I , Ádány R . A krónikus nem fertőző betegségek okozta morbiditás alakulása Magyarországon a HMAP és a GYOGYINFOK adatai tükrében [Evolution of morbidity caused by chronic non-communicable diseases in Hungary in the light of HMAP and GYOGYINFOK data]. In: Ádány R , editors. A magyar lakosság egészségi állapota az ezredfordulón [The state of health of the Hungarian population at the turn of the millennium]. Budapest: Medicina Könyvkiadó Rt; 2003. 4373. [in Hungarian].

    • Search Google Scholar
    • Export Citation
  • 4.

    finanszirozas.neak.gov.hu [Internet]. Betegségek Nemzetközi Osztályozása (BNO) [International Classification of Diseases (ICD)]. Budapest: National Health Insurance Fund of Hungary (NEAK); [cited 2021 Apr 23]. Available from: http://finanszirozas.neak.gov.hu/forum/BNO/index.asp[in Hungarian].

    • Search Google Scholar
    • Export Citation
  • 5.

    MSMR . Relationships between abnormal findings during medical examinations and subsequent diagnoses of significant conditions, active components, U.S. Armed Forces, January 1998-October 2006. MSMR Med Surveill Monthly Rep 2007;13:2-6.

    • Search Google Scholar
    • Export Citation
  • 6.

    Agha Z , Lofgren RP , VanRuiswyk JV , Layde PM . Are patients at veterans affairs medical centers sicker?: a comparative analysis of health status and medical resource use. Arch Intern Med 2000;160:3252-3257. https://doi.org/10.1001/archinte.160.21.3252.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 7.

    Almond N , Kahwati L , Kinsinger L , Porterfield D . The prevalence of overweight and obesity among U.S. military Veterans. Mil Med 2008;173:544-549. https://doi.org/10.7205/milmed.173.6.544.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 8.

    Hoerster KD , Lehavot K , Simpson T , McFall M , Reiber G , Nelson KM . Health and health behavior differences: U.S. Military, veteran, and civilian men. Am J Prev Med 2012;43:483489. https://doi.org/10.1016/j.amepre.2012.07.029.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 9.

    MSMR . Mental health encounters and diagnoses following deployment to Iraq and/or Afghanistan, U.S. Armed Forces, 2001–2006. MSMR Med Surveill Monthly Rep 2007;14:28.

    • Search Google Scholar
    • Export Citation
  • 10.

    Sótér A . A magyar honvédség egészségkockázati térképe, a személyi állomány egészségmagatartásának helyőrségi különbségei [Health risk map of the Hungarian Defence Forces, garrison differences in the health behaviour of the military personnel]. Hadmérnök 2009;4:3. [Article in Hungarian].

    • Search Google Scholar
    • Export Citation
  • 11.

    KSH . Európai lakossági egészségfelmérés. [European public health survey]. [Internet]. Budapest: Hungarian Central Statistical Office; 2014. [cited 2018 Feb 23]. Available from: http://www.ksh.hu/docs/hun/xftp/stattukor/elef14.pdf[in Hungarian].

    • Search Google Scholar
    • Export Citation
  • Collapse
  • Expand

 

The author instruction is available in PDF.
Please, download the file from HERE.
 
The Author Declaration Form is available in PDF.
Please, download the file from HERE.

 

Senior Editors

Editor-in-Chief: Zoltán Zsolt NAGY
Vice Editors-in-Chief: Gabriella Bednárikné DÖRNYEI, Ákos KOLLER
Managing Editor: Johanna TAKÁCS

Editorial Board

  • Zoltán BALOGH (Department of Nursing, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Klára GADÓ (Department of Clinical Studies, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • István VINGENDER (Department of Social Sciences, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Attila DOROS (Department of Imaging and Medical Instrumentation, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Judit Helga FEITH (Department of Social Sciences, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Mónika HORVÁTH (Department of Physiotherapy, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Illés KOVÁCS (Department of Clinical Ophthalmology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Ildikó NAGYNÉ BAJI (Department of Applied Psychology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Tamás PÁNDICS (Department for Epidemiology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • József RÁCZ (Department of Addictology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Lajos A. RÉTHY (Department of Family Care Methodology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • János RIGÓ (Department of Clinical Studies in Obstetrics and Gynaecology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Andrea SZÉKELY (Department of Oxyology and Emergency Care, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Márta VERESNÉ BÁLINT (Department of Dietetics and Nutritional Sicences, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Gyula DOMJÁN (Department of Clinical Studies, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Péter KRAJCSI (Department of Morphology and Physiology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • György LÉVAY (Department of Morphology and Physiology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Csaba NYAKAS (Department of Morphology and Physiology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Vera POLGÁR (Department of Morphology and Physiology, InFaculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • László SZABÓ (Department of Family Care Methodology, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Katalin TÁTRAI-NÉMETH (Department of Dietetics and Nutrition Sciences, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Katalin KOVÁCS ZÖLDI (Department of Social Sciences, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • Gizella ÁNCSÁN (Library, Faculty of Health Sciences, Semmelweis University, Budapest, Hungary)
  • András FALUS (Department of Genetics, Cell- and Immunbiology, Faculty of Medicine, Semmelweis University, Budapest, Hungary)
  • Zoltán UNGVÁRI (Department of Public Health, Faculty of medicine, Semmelweis University, Budapest, Hungary)
  • Romána ZELKÓ (Faculty of Pharmacy, Semmelweis University, Budapest, Hungary)
  • Mária BARNAI (Faculty of Health Sciences and Social Studies, University of Szeged, Szeged, Hungary)
  • László Péter KANIZSAI (Department of Emergency Medicine, Medical School, University of Pécs, Pécs, Hungary)
  • Bettina FŰZNÉ PIKÓ (Department of Behavioral Sciences, Faculty of Medicine, University of Szeged, Szeged, Hungary)
  • Imre SEMSEI (Faculty of Health, University of Debrecen, Debrecen, Hungary)
  • Teija-Kaisa AHOLAAKKO (Laurea Universities of Applied Sciences, Vantaa, Finland)
  • Ornella CORAZZA (University of Hertfordshire, Hatfield, Hertfordshire, United Kingdom)
  • Oliver FINDL (Department of Ophthalmology, Hanusch Hospital, Vienna, Austria)
  • Tamás HACKI (University Hospital Regensburg, Phoniatrics and Pediatric Audiology, Regensburg, Germany)
  • Xu JIANGUANG (Shanghai University of Traditional Chinese Medicine, Shanghai, China)
  • Paul GM LUITEN (Department of Molecular Neurobiology, University of Groningen, Groningen, Netherlands)
  • Marie O'TOOLE (Rutgers School of Nursing, Camden, United States)
  • Evridiki PAPASTAVROU (School of Health Sciences, Cyprus University of Technology, Lemesos, Cyprus)
  • Pedro PARREIRA (The Nursing School of Coimbra, Coimbra, Portugal)
  • Jennifer LEWIS SMITH (Collage of Health and Social Care, University of Derby, Cohehre President, United Kingdom)
  • Yao SUYUAN (Heilongjiang University of Traditional Chinese Medicine, Heilongjiang, China)
  • Valérie TÓTHOVÁ (Faculty of Health and Social Sciences, University of South Bohemia, České Budějovice, Czech Republic)
  • Tibor VALYI-NAGY (Department of Pathology, University of Illonois of Chicago, Chicago, IL, United States)
  • Chen ZHEN (Central European TCM Association, European Chamber of Commerce for Traditional Chinese Medicine)

2020  

CrossRef
Documents

9
CrossRef Cites 8
CrossRef H-index 2
Days from submission to acceptance 219
Days from acceptance to publication 176
Acceptance
Rate
47%

 

 

2019  
CrossRef
Documents
13
Acceptance
Rate
83%

 

Developments in Health Sciences
Publication Model Online only Gold Open Access
Submission Fee none
Article Processing Charge none
Subscription Information Gold Open Access

Developments in Health Sciences
Language English
Size A4
Year of
Foundation
2018
Volumes
per Year
1
Issues
per Year
2
Founder Semmelweis Egyetem
Founder's
Address
H-1085 Budapest, Hungary Üllői út 26.
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 2630-9378 (Print)
ISSN 2630-936X (Online)

Monthly Content Usage

Abstract Views Full Text Views PDF Downloads
Nov 2023 0 24 7
Dec 2023 0 46 20
Jan 2024 0 52 11
Feb 2024 0 18 8
Mar 2024 0 43 10
Apr 2024 0 56 3
May 2024 0 0 0