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Prevalence and socioeconomic correlates of chronic morbidity among elderly people in Kosovo: a population-based survey

Abstract

Background

Our aim was to assess the prevalence and demographic and socioeconomic correlates of chronic morbidity in the elderly population of transitional Kosovo.

Methods

A cross-sectional study was conducted in Kosovo in 2011 including a representative sample of 1890 individuals aged ≥65 years (949 men, mean age 73 ± 6 years; 941 women, mean age 74 ± 7 years; response rate: 83%). A structured questionnaire inquired about the presence and the number of self-reported chronic diseases among elderly people, and their access to medical care. Demographic and socioeconomic data were also collected. Binary logistic regression was used to assess the association of demographic and socioeconomic characteristics with chronic conditions.

Results

In this nationwide population-based sample in Kosovo, 42% of elderly people were unable to access medical care, of whom 88% due to unaffordable costs. About 83% of the elderly people reported at least one chronic condition (63% cardiovascular diseases), and 45% had at least two chronic diseases. In multivariable-adjusted models, factors associated with the presence of chronic conditions and/or multimorbidity were female sex, older age, self-perceived poverty and the inability to access medical care.

Conclusion

This study provides important evidence on the magnitude and distribution of chronic conditions among the elderly population of Kosovo. Our findings suggest that, in this sample of elderly people from Kosovo, the oldest-old (especially women) and the poor endure the vast majority of chronic conditions. These findings point to the urgent need to establish a social health insurance scheme including the marginalized segments of elderly people in this transitional country.

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Background

World population is ageing. The 1990–2009 period was characterized by an increase of life expectancy at birth in 165 out of 193 countries, with 29 countries having more than one fifth of their population aged over 60 years [1]. Conversely, in 51 nations, individuals born in 2009 are expected to live on average more than 75 years [1]. However, increased longevity does not necessarily point to good health for the extra years of life due to a positive relationship between age and disease occurrence which, coupled with the introduction of new health technologies and medical progress, will unavoidably lead to increased needs for health care services [2].

Kosovo, which emerged as the newest state of Europe in 2008 after ten years under United Nations’ administration following a devastating war [3], is trying to rebuild its health system [4]. Among the reforming efforts, an important aspect is the reorientation of health services to ensure basic medical care for all individuals and, particularly, for the vulnerable groups [3, 5]. Although Kosovo’s population is the youngest in the region, it is facing the ageing phenomenon as the share of people aged ≥65 years increased from 4.6% in 1966 [6] to 6.7% in 2011 and fertility rates declined [7]. Elderly people are commonly described as a vulnerable community [8] and, in a country struggling to survive, the scientific information about health situation of elderly people is sporadic [9] and they are often overlooked in spite of their growing numbers.

Transitional countries of Southeast Europe are currently considered to be similar to developed societies in terms of morbidity and mortality patterns [5]. This may suggest changes in the epidemiological profile with an increase in the morbidity and mortality from non-communicable conditions. Indeed, the leading causes of death in Southeast European countries are now the circulatory diseases accounting for more than half of all deaths, followed by cancer [10].

Socioeconomic characteristics influence the health status of individuals. Thus, there is considerable evidence on a positive relationship between education and income with a better health status [1113]. While numerous studies have highlighted the links between socioeconomic inequalities and health among elderly populations in developed [1315] and developing countries [1618], the health status of elderly people and its association with socioeconomic factors remains largely under researched in countries of the Western Balkans [1922]. This is especially the case for chronic conditions and multimorbidity.

The magnitude and demographic and socioeconomic determinants of chronic morbidity among the elderly population in Kosovo have not been reported to date. In this context, this study aimed to assess the prevalence and the demographic and socioeconomic correlates of chronic morbidity in the elderly population of Kosovo in 2011.

Methods

A nationwide cross-sectional study among elderly people aged ≥65 years was conducted in Kosovo, a country with an area of 10908 kilometre squares, which is divided into 37 administrative units, referred to as “communes”.

Study population

According to the 2011 Census [7], the total population of Kosovo is 1739825 inhabitants. Our study was conducted between January and March 2011, prior to the 2011 Census’ results.

In 2010, we retrieved (from the Kosovo Ministry of Labour and Social Welfare) a list (sampling frame) containing 140329 individuals aged ≥65 years [22]. Based on this list, we drew an age- sex-and residence-stratified sample of 2400 individuals aged ≥65 years. Twelve strata were established (based on sex-stratification [men vs. women], place of residence (urban vs. rural areas) and age-stratification [65–74 years, 75–84 years and ≥85 years]). A simple random sample of 200 individuals in each of the twelve strata was drawn [22].

Of the 2400 subjects included in the sample, 135 individuals were ineligible (69 people were dead, whereas further 66 individuals had left Kosovo at the time of the survey). Of the 2265 eligible individuals, 1890 agreed to participate in the study, with an overall response rate of 83.4% (1890/2265).

Data collection

A structured questionnaire was administered by trained interviewers at homes of elderly people who agreed to participate in the survey [22].

Participants were asked about the presence of chronic diseases (“Do you have any long-standing or chronic illness, disease or disorder?). Upon a positive response, participants were further asked to specify the type(s) of the following chronic conditions they were suffering from: cardio-vascular diseases (CVD), diabetes, stomach diseases, diseases of the liver, lung diseases, neurologic disorders, cancer, as well as an open-ended category about the possible presence of other chronic diseases. Based on this self-reported information, we calculated the number of chronic diseases for each participant (range: 1–6).

The questionnaire included also questions about access to medical care (“Are you able to access medical treatment?” – dichotomized into “able” vs. “unable” to access medical care) and barriers to access medical care (trichotomized into: “can’t afford medical costs”, “services too far away” and “too sick for seeking medical care”).

In addition, the questionnaire contained items about socio-demographic and socioeconomic characteristics of study participants including sex, age (65–74 years, 75–84 years and ≥85 years), educational level (0 years, 1–8 years and ≥9 years), place of residence (urban vs. rural area), marital status (dichotomized into: married vs. not married), and self-perceived poverty level (dichotomized into: not poor vs. poor) [22].

The study was approved by the Ethical Board of the Ministry of Health of Kosovo. All elderly people who agreed to participate in the survey signed an informed consent form prior to the interview.

Statistical analysis

Demographic and socioeconomic sample estimates were weighted for age, sex and place of residence in accordance with the respective strata from the sampling frame [22]. Absolute numbers and their respective percentages from the study sample, and sampling frame weighted percentages with their respective 95% confidence intervals (95% CIs) were reported.

Binary logistic regression was used to assess the associations of socio-demographic and socioeconomic variables with the presence of chronic conditions (dichotomized into: “none” vs. “at least one chronic condition”) and the number of chronic conditions (dichotomized into: “one chronic condition” vs. “≥2 chronic conditions”). Individuals with ≥2 chronic conditions were considered as living with multimorbidity.

Age-adjusted and multivariable-adjusted odds ratios (ORs) and their respective 95% CIs were calculated. In all cases, a p-value of ≤0.05 was regarded as statistically significant. All the logistic models were checked to comply with the requirements of Hosmer-Lemeshow goodness-of-fit test (all the reported models satisfied the goodness-of-fit criterion).

SPSS (Statistical Package for Social Sciences, version 15.0), was used for all the statistical analyses.

Results

Mean age in this sample of elderly people in Kosovo was 73.4 ± 6.3 years. The majority lived in rural areas (62%) and 55% were married at the time of the interview (Table 1). Almost half of participants perceived themselves as economically poor. About 42% of respondents reported inability to access medical care, most of whom (87.7%) couldn’t afford the costs of medical care.

Table 1 Socio-demographic and socioeconomic characteristics of a population-based sample (N = 1890) of elderly people in Kosovo, 2011

The most prevalent chronic conditions were the cardiovascular diseases followed by diseases of the stomach and liver, diabetes and lung diseases with 63%, 21%, 18% and 16%, respectively (Table 2). The maximum number of chronic conditions was six, whereas the median number of diseases was two. The prevalence of each chronic condition, considered separately, was higher among women than men, except for the cancer.

Table 2 Self-reported chronic conditions in a population-based sample (N = 1890) of elderly people in Kosovo, 2011

Women aged 65–74 years and ≥85 years were significantly more likely to report two or more chronic conditions than men (P < 0.001 and P = 0.05, respectively) [Table 3]. More than four fifths of the elderly people (83%) had at least one chronic disease, whereas the prevalence of multimorbidity (≥2 chronic conditions) was 45%.

Table 3 Number of chronic conditions by age and sex

In age-adjusted logistic regression models (Table 4), sex, age-group, education, self-perceived poverty and the ability to access medical care were all significantly associated with chronic morbidity: the presence of at least one chronic condition was significantly higher in women (OR = 1.8; 95% CI = 1.4-2.4), among the oldest-old (OR = 3.2; 95% CI = 2.3-4.6), those with 1–8 years of formal schooling (OR = 2.1; 95% CI = 1.3-3.2), individuals perceiving themselves as poor (OR = 2.2; 95% CI = 1.7-3.0), and participants unable to access medical care (OR = 4.0; 95% CI = 2.8-5.7). A similar pattern was evident for multimorbidity, where OR was 1.4 times higher among women (95% CI = 1.1-1.7), 1.9 times higher among the oldest-old (95% CI = 1.5-2.5), 1.7 times higher among individuals with 1–8 years of formal schooling (95% CI = 1.2-2.4), 1.6 times higher among individuals perceiving themselves as poor (95% CI = 1.3-1.9), and 1.9 times higher among participants unable to access medical care (95% CI = 1.6-2.4) [Table 4].

Table 4 Association of demographic and socioeconomic factors with the presence and the number of chronic conditions; age-adjusted odds ratios (ORs) from binary logistic regression

In multivariable-adjusted models (Table 5), the positive and statistically significant associations of the presence of at least one chronic condition with female sex, older age, self-perceived poverty and the inability to access medical care persisted, albeit less strongly. Furthermore, upon multivariable adjustment, the correlates of multimorbidity were generally similar to those of chronic morbidity.

Table 5 Association of demographic and socioeconomic factors with the presence and the number of chronic conditions; multivariable-adjusted odds ratios (ORs) from binary logistic regression

Discussion

This study provides novel evidence about the presence and demographic and socioeconomic correlates of chronic morbidity in the elderly population of transitional Kosovo. Older age and inability to access medical care were the most consistent correlates of chronic morbidity and/or multimorbidity in this study population.

In line with other studies using similar methods for assessing chronic diseases (i.e. self-reported data) [2326], CVD (including hypertension) was the most prevalent disease among elderly individuals in this sample. Thus, a similar prevalence of CVD has been reported among older people in the region, with a prevalence of 58% reported in Albania [21] and Serbia [20], and slightly over 50% in Macedonia [19]. Conversely, a lower prevalence varying from 28% in the Netherlands to 41% in Finland was reported by the FINE study which, however, used diagnosed rather than self-assessed measurement of chronic conditions [27].

One out of five individuals in this Kosovo sample reported diabetes, which resembles results from Albania (19%) [21], Germany (17%) [24] and USA (22.7%) [26]. Studies measuring diagnosed diabetes report a prevalence from 15% (in USA) [28] to 9% (Italy) and 6% (the Netherlands) [27]. The prevalence of cancer in our study was quite low compared to other countries in the region: 2-3% in Macedonia [19], 3% in Italy (27), about 4% in Southern Germany [24], 8% in Finland [27], and 19% among the American older people [26]. These differences could be partly explained by different methods for assessing the presence of chronic conditions (self-reported vs. diagnosed data) used in different studies, even though it has been argued that self-reports and health care records provide quite comparable estimates for diabetes, but are less concordant for chronic heart disease or other conditions [25, 29]. For example, the beyond chance agreement index (Kappa statistic) has been reported at 0.90 [25] and 0.80 [29] for diabetes, 0.67 [25] and 0.40 [29] for hypertension, but lower for other chronic conditions. Methodological issues aside, a plausible reason for the discrepancies in diabetes prevalence among the elderly people between Kosovo and developed countries such as e.g. the Netherlands could be found in the epidemiology of diabetes which suggests an increasing risk with age, lower education and socioeconomic status [30, 31] – factors which were all more prevalent in the Kosovo sample [22] compared with the study populations researched elsewhere [27]. Furthermore, another possible explanation for the particularly low prevalence of self-reported cancer in our study might come from a recent survey among cancer patients in Albanian settings, which found that most cancer patients seek medical help only in advanced stages of the illness and the cultural context is largely against diagnosis disclosure [32].

According to a recent systematic review [33], the prevalence of multimorbidity among the elderly, defined as the concomitant presence of ≥2 chronic conditions, ranges from 55%-98%, whereas in our study we noted a prevalence of 45%. The discrepancies might be due to different age-groups included in different studies, differences in the number of chronic conditions investigated, differences in the study settings and, as mentioned earlier, different means of assessing the presence of diseases. Furthermore, evidence shows that the prevalence of multimorbidity depends on the study population (e.g. population-based samples vs. primary care users, implying a higher prevalence in the later study population), the nature and the number of chronic conditions included [34, 35]. Indeed, it has been convincingly shown that the prevalence of multimorbity increases as the number of disease items included in the questionnaire increases [34, 35]. However, we tried to overcome this limitation by introducing the following option: “Please mention any other type of chronic diseases not mentioned above”.

Another potential source of variability between studies in estimating morbidity and multimorbidity pertains to education. As the education attainment progresses, the knowledge and understanding of health and disease changes too, leading thus to potentially different reporting. On the other hand, the awareness of people regarding health issues has been rising in general leading to more frequent doctor visits and diagnoses, especially in developed countries. Also, people now can talk more openly about their health problems and this implies greater willingness to report such problems when under study [34].

In general, the literature reports that morbidity and multimorbidity is significantly higher among older people, women and individuals of a low socioeconomic status [24, 33, 34, 36]. Our findings are in concordance with the international literature as regards the association with sex and age, with women and the oldest-old reporting higher rates of multimorbidity.

Conversely, the inverse association with education was significant in crude analysis only. However, this resembles prior reports from studies conducted elsewhere, which have pointed out not significant relationships between education and the number of chronic conditions and multimorbidity in multivariable-adjusted models [3740]. Thus, a study including individuals aged ≥18 years reported a non-significant association between education and multimorbidity [36], whereas a large cohort study among elderly people aged 50–75 years old reported that, upon multivariable-adjustment, the association of multimorbidity with education weakened in men, whereas in women it was not statistically significant [41].

Morbidity and multimorbidity among the elderly deserves special attention based on previous research which shows that, for certain diseases affecting the heart, lungs and circulatory apparatus, the presence of one or more chronic health conditions is significantly associated with a higher risk of death [27]. Two longitudinal studies reported that persons with poor self-reported health had an early mortality risk and late mortality risk of about three times higher compared to individuals with good health status [42, 43].

About half of the elderly subjects in this study perceived themselves as poor. This might be an indicator of the difficult situation of the elderly population in Kosovo. A prior report including this very study population in Kosovo indicated that the self-perceived poverty was significantly higher among women, those without any formal schooling, urban residents and among the elderly people living alone [22].

We found significant associations of self-reported poverty with the number of chronic conditions: the higher the poverty level, the higher the proportion of multiple diseases (Spearman’s correlation coefficient = 0.212, P = 0.01; not shown in the tables). Indeed, evidence shows that even after controlling for a number of factors, poverty remains a strong predictor of adults’ health [44]. Education and poverty seem to be part of a vicious circle: low education, which is greatly influenced by unfavourable family circumstances during childhood, might be closely linked to a lower income during adulthood favouring persistent poverty which in turn contributes to poor health outcomes later in life [44]. Since the objective and subjective measures of poverty have been reported to correlate with each-other [45], self-perceived poverty might explain a part of unfavourable health outcomes among Kosovo elderly people, too. Yet, self-perceived poverty and well-being depend on many factors other than income [46].

Some of the socioeconomic and demographic determinants of chronic morbidity and multimorbidity among the elderly have been studied extensively, but little is known about other risk factors of multimorbidity including genetic, biological, lifestyle and environmental factors [33]. Another under researched factor which could affect the health status of old people is elderly abuse, which includes “abandonment, emotional abuse, financial or material exploitation, neglect, physical abuse, and sexual abuse of the elderly” [47]. Although a considerable number of studies have highlighted the situation of elderly abuse across different populations, very little evidence is available regarding the prevention of elderly abuse [47] and how this may affect the health status of older people. Elderly abuse sets an additional heavy barrier on the shoulders of older people: besides co-living with the ageing process and physical limitations that it entails, older people have to cope with the community abuse, which might further deteriorate their health status. Elderly people in Kosovo are a marginalized part of the population [22] which might imply the existence of elderly abuse. Future investigations should take into account this aspect when assessing the complexity of factors associated with morbidity of this community [36, 48].

In our study, access to medical care was a significant and consistent predictor of both the presence and number of chronic conditions. The access and use of health services depends not only on the need for care, but also on predisposing characteristics (demographic factors, health beliefs) and enabling resources such as the availability of health personnel and health facilities, means of transport, or health insurance [49]. The overwhelming majority of Kosovo elderly people who couldn’t access medical care in this study (almost 90%) pointed to the economic barriers as the main reason for this inability. This is a reflection of the unclear situation of the elderly in Kosovo and the ongoing reforms in the health sector. Although protection of the rights of vulnerable groups and ensuring quality of care is one of the priorities of health reforms in Kosovo, the health system lags behind its optimal state. The health insurance system seems unable to function with half of the population unemployed and a high informality rate [3, 50]. People aged ≥65 years in Kosovo rely on the social security pension (which is quite low and not sufficient to meet their everyday needs) and remittances from their close family working abroad [22]. Furthermore, Kosovo is in urgent need of deep reforms as the armed conflict left the country with a very inefficient health system characterized by a lack of trained personnel and disparities in health force distribution. These factors lead to variations in access to primary care, corruption and informal payments, which are all reflected in unfavourable child and adult health indicators. In this context, the continuous reforming of the health sector has brought up a complex configuration of the stakeholders operating in the health system which contributes to unequal access to health care. The primary health care is still overlooked by health policies which often favour “high-tech” clinical medicine [3]. Furthermore, the private health sector has been expanded rapidly, but private facilities are unaffordable for the elderly [3]. The main barrier to access care is the cost of services, despite the fact that basic health services are supposed to be covered for all citizens. Under-the-table payments put a heavy burden on the shoulders of the poor. Ultimately, the reforms have resulted in lower access to health care for the poorer groups of the society [50]. Under these conditions, little attention is paid to the growing community of the elderly people in Kosovo [22] which, combined with the inadequacy of financial resources, the economic insecurity and the unclear and unstable development of the health sector, pose a serious barrier for elderly people to access medical care.

As stated by the Centre on Social Disparities in Health [51], in order to increase the chances of good health one needs to adopt a healthy lifestyle and have access to proper medical care. In a broader context, there is a need to promote a healthier living and working conditions. This should be supported by economic development, reducing poverty and enhancing education [51].

Our study has several limitations including its cross-sectional design and the differential reporting of chronic diseases among elderly people. We cannot exclude the possibility of reporting bias; however, we do not have sound reasons to assume differential reporting of chronic diseases for the elderly people’s categories differing in demographic and socioeconomic characteristics. More importantly, findings of our study should be interpreted with caution, since the observed associations from cross-sectional studies are not assumed to be causal.

Conclusions

Elderly people represent a valuable part of the society as they convey their wisdom and experience to future generations. Improving their economic situation and health status in Kosovo will require a lot of efforts. Although access to medical care is not the only element in the wide array of health determinants, based on our findings, medical care plays an important role for the control of chronic morbidity and multimorbidity. Therefore, facilitating the access to medical care of the elderly people in Kosovo through economic development, poverty reduction and the establishment of an effective social health insurance system might improve the health status of older people and protect them from catastrophic health expenditures.

In conclusion, our study provides evidence on the magnitude and demographic and socioeconomic correlates of chronic conditions among the elderly population of Kosovo. Our findings suggest that the oldest-old (especially women) and the poor segments of the elderly population endure the vast majority of chronic conditions. These salient findings point to the need for establishing an effective social health insurance scheme including the marginalized subgroups of elderly people in Kosovo.

References

  1. World Health Organization: World health statistics. 2011, Geneva, Switzerland: WHO Press

    Google Scholar 

  2. Rynning E: The ageing populations of Europe - Implications for health systems and patients’ rights. Eur J Health Law. 2008, 15: 297-306. 10.1163/157180908X338241.

    Article  PubMed  Google Scholar 

  3. Buwa D, Vuori H: Rebuilding a health care system: war, reconstruction and health care reforms in Kosovo. Eur J Public Health. 2007, 17: 226-230. 10.1093/eurpub/ckl114.

    Article  PubMed  Google Scholar 

  4. Burkle FM: Post-conflict health system recovery: the case of Kosovo. Prehosp Disaster Med. 2010, 25: 34-36.

    Article  PubMed  Google Scholar 

  5. Bjegovic V, Vukovic D, Terzic Z, Milicevic MS, Laaser UT: Strategic orientation of public health in transition: an overview of south eastern Europe. J Public Health Policy. 2007, 28: 94-101. 10.1057/palgrave.jphp.3200121.

    Article  PubMed  Google Scholar 

  6. Statistical Office of Kosova: Demographic, social and reproductive health survey in Kosovo, November 2009. 2011, Pristine, Kosovo

    Google Scholar 

  7. Kosovo Agency of Statistics: Kosovo population and housing census 2011. Final results. Main data. 2012, Pristine, Kosovo

    Google Scholar 

  8. Grundy E: Ageing and vulnerable elderly people: European perspectives. Ageing Soc. 2006, 26: 105-134. 10.1017/S0144686X05004484.

    Article  Google Scholar 

  9. Qosaj FA, Berisha MK: Transition in health and health care in Kosovo. 2010, Kosova School of: Public Health

    Google Scholar 

  10. Rechel B, Mckee M: Healing the crisis. A prescription for public health action in south-eastern Europe. 2003, London: London School of Hygiene and Tropical Medicine (The Open Society Institute)

    Google Scholar 

  11. Mackenbach JP, Stirbu I, Roskam AJ, Schaap MM, Menvielle G, Leinslau M, Kunst AE: Socioeconomic inequalities in health in 22 European countries. N Engl J Med. 2008, 358: 2468-2481. 10.1056/NEJMsa0707519.

    Article  CAS  PubMed  Google Scholar 

  12. World Health Organization: Closing the gap in a generation: health equity through action on the social determinants of health. Final report of the Commission on Social Determinants of Health. 2008, Geneva: Commission on Social Determinants of Health

    Google Scholar 

  13. Kiuila O, Mieszkowski P: The effects of income, education and age on health. Health Economics. 2007, 16: 781-798. 10.1002/hec.1203.

    Article  PubMed  Google Scholar 

  14. Tsimbos C: An assessment of socio-economic inequalities in health among elderly in Greece, Italy and Spain. Int J Public Health. 2010, 55: 5-15. 10.1007/s00038-009-0083-1.

    Article  PubMed  Google Scholar 

  15. König HH, Heider D, Lehnert T, Riedel-Heller SG, Angermeyer MC, Matschinger H, Vilagut G, Bruffaerts R, Haro JM, de Girolamo G, de Graaf R, Kovess V, Alonso J, ESEMeD/MHEDEA 2000 investigators: Health status of the advanced elderly in six european countries: results from a representative survey using EQ-5D and SF-12. Health Qual Life Outcomes. 2010, 8: 143-

    Article  PubMed  PubMed Central  Google Scholar 

  16. Pulatova G, Harun-Or-Rashid , Yoshida Y, Sakamoto J: Elderly health and its correlations among Uzbek population. Nagoya J Med Sci. 2012, 74: 71-82. 10.1292/jvms.11-0248.

    PubMed  PubMed Central  Google Scholar 

  17. Strauss J, Lei X, Park A, Shen Y, Smith JP, Yang Z, Zhao Y: Health outcomes and socioeconomic status among the elderly in China. 2010, Rand Labor & Population: Evidence from the CHARLS Pilot

    Google Scholar 

  18. Bos AM, Bos ÂJ: The socio-economic determinants of older people’s health in Brazil: the importance of marital status and income. Ageing and Society. 2007, 27: 385-10.1017/S0144686X06005472.

    Article  Google Scholar 

  19. World Health Organization: Health and nutritional status of the elderly in the Former Yugoslav Republic of Macedonia - Results of a national household survey, November 1999. 2001, Copenhagen: WHO Regional Office for Europe

    Google Scholar 

  20. Matejić B, Bjegović V, Milić N, Milićević MŠ, Terzić Z: Functional ability of elderly in Serbia: an example of assessment. 2008, Gerontology: The Internet Journal of Geriatrics and, 4-

    Google Scholar 

  21. Ylli A: Health and social conditions of older people in Albania: baseline data from a national survey. Public Health Reviews. 2010, 2: 549-

    Google Scholar 

  22. Jerliu N, Toci E, Burazeri G, Ramadani N, Brand H: Socioeconomic conditions of elderly people in Kosovo: a cross-sectional study. BMC Public Health. 2012, 12: 512-10.1186/1471-2458-12-512.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Marengoni A, Winblad B, Karp A, Fratiglioni L: Prevalence of chronic diseases and multimorbidity among the elderly population in Sweden. Am J Public Health. 2008, 98: 1198-1200. 10.2105/AJPH.2007.121137.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Kirchberger I, Meisinger C, Heier M, Zimmermann AK, Thorand B, Autenrieth CS, Peters A, Ladwig KH, Döring A: Patterns of multimorbidity in the aged population. Results from the KORA-Age study. Plos One. 2012, 7: e30556-10.1371/journal.pone.0030556.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Barber J, Muller S, Whitehurst T, Hay E: Measuring morbidity: self-report or health care records?. Fam Pract. 2010, 27: 25-30. 10.1093/fampra/cmp098.

    Article  PubMed  Google Scholar 

  26. Hung WW, Ross JS, Boockvar KS, Liu AL: Recent trends in chronic disease, impairment and disability among older adults in the United States. BMC Geriatrics. 2011, 11: 47-10.1186/1471-2318-11-47.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Menotti A, Mulder I, Nissinen A, Giampaoli S, Feskens EJ, Kromhout D: Prevalence of morbidity and multimorbidity in elderly male populations and their impact on 10-year all-cause mortality: The FINE study (Finland, Italy, Netherlands, Elderly). J Clin Epidemiol. 2001, 54: 680-686. 10.1016/S0895-4356(00)00368-1.

    Article  CAS  PubMed  Google Scholar 

  28. Selvin E, Coresh J, Brancati FL: The burden and treatment of diabetes in elderly individuals in the U.S. Diabetes Care. 2006, 29: 2415-2419. 10.2337/dc06-1058.

    Article  PubMed  Google Scholar 

  29. Tisnado DM, Adams JL, Liu H, Damberg CL, Chen WP, Hu FA, Carlisle DM, Mangione CM, Kahn KL: What is the concordance between the medical record and patient self-report as data sources for ambulatory care?. Med Care. 2006, 44: 132-140. 10.1097/01.mlr.0000196952.15921.bf.

    Article  PubMed  Google Scholar 

  30. Espelt A, Borrell C, Roskam AJ, Rodriguez-Sanz M, Stirbu I, Dalmau-Bueno A, Redigdor E, Bopp M, Martikainen P, Leinslau M, Artnik B, Rychtarikova J, Kalediene R, Dzurova D, Mackenbach J, Kunst AE: Socioeconomic inequalities in diabetes mellitus across Europe at the beginning of the 21st century. Diabetologia. 2008, 51: 1971-1979. 10.1007/s00125-008-1146-1.

    Article  CAS  PubMed  Google Scholar 

  31. Robbins JM, Vaccarino V, Zhang H, Kasl SV: Socioeconomic status and diagnosed diabetes incidence. Diabetes Res Clin Pract. 2005, 68: 230-236. 10.1016/j.diabres.2004.09.007.

    Article  PubMed  Google Scholar 

  32. Beqiri A, Toci E, Sallaku A, Qirjako G, Burazeri G: Breaking bad news in a Southeast European population: a survey among cancer patients in Albania. J Palliat Med. 2012, 15: 1100-1105. 10.1089/jpm.2012.0068.

    Article  PubMed  Google Scholar 

  33. Marengoni A, Angleman S, Melis R, Mangialasche F, Karp A, Garmen A, Meinow B, Fratiglioni L: Aging with multimorbidity: a systematic review of the literature. Ageing Res Rev. 2011, 10: 430-439. 10.1016/j.arr.2011.03.003.

    Article  PubMed  Google Scholar 

  34. Schram MT, Frijters D, van de Lisdonk EH, Ploemacher J, de Craen AJM, de Waal MWM, van Rooij FJ, Heeringa J, Hofman A, Deeg DJH, Schellevis FG: Setting and registry characteristics affect the prevalence and nature of multimorbidity in the elderly. J Clin Epidemiol. 2008, 61: 1104-1112. 10.1016/j.jclinepi.2007.11.021.

    Article  PubMed  Google Scholar 

  35. Fortin M, Hudon C, Haggerty J, Akker M, Almirall J: Prevalence estimates of multimorbidity: a comparative study of two sources. BMC Health Serv Res. 2010, 10: 111-10.1186/1472-6963-10-111.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Agborsangaya CB, Lau D, Lahtinen M, Cooke T, Johnson JA: Multimorbidity prevalence and patterns across socioeconomic determinants: a cross-sectional survey. BMC Public Health. 2012, 12: 201-10.1186/1471-2458-12-201.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Verropoulou G: Determinants of change in self-rated health among older adults in Europe: a longitudinal perspective based on SHARE data. Eur J Ageing. 2012, 9: 305-318. 10.1007/s10433-012-0238-4.

    Article  Google Scholar 

  38. Andersen FK, Christensen K, Frederiksen H: Self-rated health and age: a cross-sectional and longitudinal study of 11,000 Danes aged 45–102. Scand J Public Health. 2007, 35: 164-171. 10.1080/14034940600975674.

    Article  PubMed  Google Scholar 

  39. Franks P, Gold MR, Fiscella K: Sociodemographics, self-rated health, and mortality in the US. Soc Sci Med. 2003, 56: 2505-2514. 10.1016/S0277-9536(02)00281-2.

    Article  PubMed  Google Scholar 

  40. Bobak M, Pikhart H, Rose R, Hertzman C, Marmot M: Socioeconomic factors, material inequalities, and perceived control in self-rated health: cross-sectional data from seven post-communist countries. Soc Sci Med. 2000, 51: 1343-1350. 10.1016/S0277-9536(00)00096-4.

    Article  CAS  PubMed  Google Scholar 

  41. Nagel G, Peter R, Braig S, Herman S, Rohrmann S, Linseisen J: The impact of education on risk factors and the occurrence of multimorbidity in the EPIC-Heidelberg cohort. BMC Public Health. 2008, 8: 384-10.1186/1471-2458-8-384.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Mossey JM, Shapiro E: Self-rated health: a predictor of mortality among the elderly. Am J Public Health. 1982, 72: 800-808. 10.2105/AJPH.72.8.800.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Sargent-Cox KA, Anstey KJ, Luszcz MA: The choice of self-rated health measures matter when predicting mortality: evidence from 10 years follow-up of the Australian longitudinal study of ageing. BMC Geriatrics. 2010, 10: 18-10.1186/1471-2318-10-18.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Benzeval M, Taylor J, Judge K: Evidence on the relationship between low income and poor health: is the government doing enough?. Fiscal Studies. 2000, 21: 375-399. 10.1111/j.1475-5890.2000.tb00029.x.

    Article  Google Scholar 

  45. Nandori ES: Subjective poverty and its relation to objective poverty concepts in Hungary. Soc Indic Res. 2011, 102: 537-556. 10.1007/s11205-010-9743-z.

    Article  Google Scholar 

  46. Kindgon GG, Knight J: Subjective well-being poverty versus income poverty and capabilities poverty?. 2004, University of Oxford, UK: Economic and Social Research Council – Global Poverty Research Group

    Google Scholar 

  47. Daly JM, Merchant ML, Jogerst GJ: Elder abuse research: a systematic review. J Elder Abuse Negl. 2011, 23: 348-365. 10.1080/08946566.2011.608048.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Schäfer I, von Leitner EC, Schön G, Koller D, Hansen H, Kolonko T, Kaduszkiewicz H, Wegsheider K, Glaeske G, van den Bussche H: Multimorbidity patterns in the elderly: a New approach of disease clustering identifies complex interrelations between chronic conditions. Plos One. 2010, 5: e15941-10.1371/journal.pone.0015941.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Andersen RM: Revisiting the behavioral model and access to medical care: does it matter?. J Health Soc Behav. 1995, 36: 1-10. 10.2307/2137284.

    Article  CAS  PubMed  Google Scholar 

  50. Percival V, Sondorp E: A case study of health sector reform in Kosovo. Confl Health. 2010, 4: 7-10.1186/1752-1505-4-7.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Braveman PA, Egerter SA, Mockenhaupt RE: Broadening the focus: the need to address the social determinants of health. Am J Prev Med. 2011, 40 (S1): S4-S18.

    Article  PubMed  Google Scholar 

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Acknowledgement

This survey was conducted with financial support from The United Nations Population Fund (UNFPA), Office in Kosovo.

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Correspondence to Naim Jerliu.

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The authors declare that they have no competing interests.

Authors’ contributions

NJ contributed to the study conceptualization and design, acquisition of the data, analysis and interpretation of the data and writing of the article. ET, GB and HB contributed to the study conceptualization and design, analysis and interpretation of the data and writing of the article. NR commented on the manuscript. All authors have read and approved the submitted manuscript.

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Jerliu, N., Toçi, E., Burazeri, G. et al. Prevalence and socioeconomic correlates of chronic morbidity among elderly people in Kosovo: a population-based survey. BMC Geriatr 13, 22 (2013). https://doi.org/10.1186/1471-2318-13-22

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