37 research outputs found

    Family, Social Support and Health Status of Older People in Tehran

    Get PDF
    Iran has recently undergone an exceptionally fast fertility transition. The Total Fertility Rate decreased from 7 in 1980 to 1.8 in 2006 along with declines in adult mortality rates. Consequently, Iran is currently experiencing rapid population ageing. As these demographic changes are intertwined with huge social changes, some major challenges may be anticipated in future. One important concern is that the health status of older people, particularly their mental well-being, may be adversely affected if fewer children lead to a reduction in the support available to older people. The aim of the research described in this thesis was to examine direct and stress-buffering associations between social support and mental health in older age groups. Potential differences between men and women in the associations and the role of different sources of support were also examined. A review of the existing literature indicated that this topic is under-researched in Iran or culturally similar countries. A quantitative cross-sectional survey of a random sample of 800 people aged 60+ years resident in Tehran was conducted. In total, 644 people responded. Multilevel mixed-effects models were used to examine the hypotheses. The findings supported the hypothesis of a direct association between functional aspects of social support and mental health but not that of an association between structural aspects of social support and mental health. No strong evidence of a stress-buffering effect of social support in the association between physical functioning and mental health was found, except in the case of receipt of social support with transportation. The only type of support that showed a significant interaction with gender was receipt of support with paperwork. The source of support did not seem to matter. Implications of these findings for older people currently living in Tehran are considered and recommendations for appropriate social support interventions, taking account of the results, are made

    Determinants of health-related quality of life in elderly in Tehran, Iran

    Get PDF
    BACKGROUND: As Iran started to experience population ageing, it is important to consider and address the elderly people's needs and concerns, which might have direct impacts on their well-being and quality of life. There have been only a few researches into different aspects of life of the elderly population in Iran including their health-related quality of life. The purpose of this study was to measure health-related quality of life (HRQoL) of elderly Iranians and to identify its some determinant factors. METHODS: This was a cross-sectional survey of a random sample of community residents of Tehran aged 65 years old and over. HRQoL was measured using the Short From Health Survey (SF-36). The study participants were interviewed at their homes. Uni-variate analysis was performed for group comparison and logistic regression analysis conducted to predict quality of life determinants. RESULTS: In all, 400 elderly Iranian were interviewed. The majority of the participants were men (56.5%) and almost half of the participants were illiterate (n = 199, 49.8%). Eighty-five percent of the elderly were living with their family or relatives and about 70% were married. Only 12% of participants evaluated their economic status as being good and most of people had moderate or poor economic status. The mean scores for the SF-36 subscales ranged from 70.0 (SD = 25.9) for physical functioning to 53.5 (SD = 29.1) for bodily pain and in general, the respondents significantly showed better condition on mental component of the SF-36 than its physical component (mean scores 63.8 versus 55.0). Performing uni-variate analysis we found that women reported significantly poorer HRQoL. Multiple logistic regression analysis showed that for the physical component summary score of the SF-36, age, gender, education and economic status were significant determinants of poorer physical health-related quality of life; while for the mental component summary score only gender and economic status were significant determinants of poorer mental health-related quality of life. The analysis suggested that the elderly people's economic status was the most significant predictor of their HRQoL. CONCLUSION: The study findings, although with a small number of participants, indicate that elderly people living in Tehran, Iran suffer from relatively poor HRQoL; particularly elderly women and those with lower education. Indeed to improve quality of life among elderly Iranians much more attention should be paid to all aspects of their life including their health, and economic status

    Self-assessed health among Thai elderly

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>The ageing of the population is rapidly progressing in Thailand. Self-assessed health status can provide a holistic view of the health of the elderly. This study aims to identify the determinants of self-assessed health among older Thai people.</p> <p>Methods</p> <p>The data for this study were drawn from a national survey of older persons conducted in 2007. Stratified two-stage random sampling was used for data collection. The analysis was restricted to the population aged 60 and above. The study used univariate, bivariate, and multivariate analysis procedures to analyze the data. Bivariate analysis was used to identify the factors associated with self assessment of health status. After controlling for other variables, the variables were further examined using multivariate analysis (binary logistic regression) in order to identify the significant predictors of the likelihood of reporting poor health.</p> <p>Results</p> <p>Overall, 30,427 elderly people were interviewed in this study. More than half of the sampled respondents (53%) were aged 60-69 years and about one out of seven (13%) were aged 80 years or above. About three in five respondents (56%) reported that their health was either fair or very bad/bad. Logistic regression analysis found that age, education, marital status, working status, income, functional status, number of chronic diseases, and number of psychosocial symptoms are significant predictors in determining health status. Respondents who faced more difficulty in daily life were more likely to rate their health as poor compared to those who faced less such difficulty. For instance, respondents who could not perform 3 or more activities of daily living (ADLs) were 3.3 times more likely to assess their health as poor compared to those who could perform all the ADLs. Similarly, respondents who had 1, 2, or 3 or more chronic diseases were 1.8 times, 2.4 times, and 3.7 times, respectively, more likely to report their health as poor compared to those who had no chronic disease at all. Moreover, respondents who had 1-2, 3-4, or 5 or more psychosocial symptoms in the previous months were 1.6 times, 2.2 times, and 2.7 times, respectively, more likely to report poor health compared to those who did not have any psychosocial symptoms during the same period.</p> <p>Conclusion</p> <p>Self-assessed poor health is not uncommon among older people in Thailand. No single factor accounts for the self-assessed poor health. The study has found that chronic disease, functional status, and psychosocial symptoms are the strongest determinants of self-assessed poor health of elderly people living in Thailand. Therefore, health-related programs should focus on all the factors identified in this paper to improve the overall well-being of the ageing population of Thailand.</p

    Social and health-related predictors of family function in older spousal caregivers: a cross-sectional study

    Get PDF
    Given the benefits of adequate family function for the health and well-being of older adults, it is important to understand what factors predict adequate family function in older people who care for their spouses. Objective: Analyse predictors of family function in older spousal caregivers. Methods: A cross-sectional study design was used to investigate a non-probabilistic sample of 298 older spousal caregivers. Home-based face-to-face interviews were used to evaluate sociodemographic variables and care context, family function (Family APGAR), cognitive function, perceived stress, and depressive symptoms. Data were analysed using multiple logistic regression with stepwise forward method for variable section. Results: Older caregivers having some degree of cognitive impairment (OR=-0.160, 95%CI 0.444–0.579), depressive symptoms (OR=-0.848, 95%CI 0.726–0.992) or high levels of stress (OR=-0.955, 95%CI 0.914-0.999) had overall lower levels of family function. Having more children was linked to approximately 1.3 times higher family function (95%CI 1.080–1.057). Conclusion: Stress, depression, cognitive decline, and number of children are predictors of family function and should be considered in social and health care strategies within the family caregiving context

    Is Health Related Quality of Life (HRQoL) a valid indicator for health systems evaluation?

    Get PDF
    This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.The purpose of this review is to do a discussion about the use of the HRQoL as a health measure of the populations that enable to analyze its potential use as a measure of development and efficiency of health systems. The principal use of the HRQoL is in health technologies economics evaluation; however this measure can be use in public health when need to know the health state of population. The WHO recognizes its potential use but its necessary to do a discussion about your difficulties for its application and restrictions for its use as a performance indicator for the health systems. The review show the different aspects about the use of HRQoL how a measure of efficiency ot the health system, each aspect identified in the literature is analyzed and discussed, developing the pros and cons of their possible use, especially when it comes as a cardinal measure. The analysis allows recognize that measuring HRQoL in countries could serve as a useful indicator, especially when it seeks to measure the level of health and disease, as do most of the indicators of current use. However, the methodological constraints that do not allow comparability between countries especially when you have large socioeconomic differences have yet to be resolved to allow comparison between different regions.Romero, D.; Vivas Consuelo, DJJ.; Alvis Guzman, NR. (2013). Is Health Related Quality of Life (HRQoL) a valid indicator for health systems evaluation?. SpringerPlus. 2:664-674. doi:10.1186/2193-1801-2-664S6646742Acemoglu D, Johnson S: Disease and development: The effect of life expectancy on economic growth. J Polit Econ 2007, 115(6):925-985. 10.1086/529000Anderson J, Sayles H, Curtis JR, Wolfe F, Michaud K: Converting modified health assessment questionnaire (HAQ), multidimensional HAQ, and HAQII scores into original HAQ scores using models developed with a large cohort of rheumatoid arthritis patients. Arthritis care & research 2010, 62(10):1481-1488. Epub 2010/05/25 10.1002/acr.20265Aristotles : Nicomachean Ethics: Batoche Books Kitchener. 1999. Available from: http://www.efm.bris.ac.uk/het/aristotle/ethics.pdfAugustovski FA, Irazola VE, Velazquez AP, Gibbons L, Craig BM: Argentine valuation of the EQ-5D health states. Value in health 2009, 12(4):587-596. Epub 2009/11/11 10.1111/j.1524-4733.2008.00468.xBernert S, Fernandez A, Haro JM, Konig HH, Alonso J, Vilagut G, et al.: Comparison of different valuation methods for population health status measured by the EQ-5D in three European countries. Value in health 2009, 12(5):750-758. Epub 2009/06/06 10.1111/j.1524-4733.2009.00509.xCervellati M, Sunde U: Life expectancy and economic growth: The role of the demographic transition. Discussion Paper No 2 St. Gallen. Switzerland: Research Center for Ageing, Welfare and Labour Analysis (SCALA); 2009.Cervellati M, Sunde U: Disease and development: The role of life expectancy reconsidered. Econ Lett 2011, 113(3):269-272. 10.1016/j.econlet.2011.08.008Chatters LM: Religion and health: public health research and practice. Annual review of public health 2000, 21: 335-367. Epub 2000/07/08 10.1146/annurev.publhealth.21.1.335Chen B, Mahal A: Measuring the health of the Indian elderly: evidence from National Sample Survey data. Population health metrics 2010, 8: 30. Epub 2010/11/18 10.1186/1478-7954-8-30Cleland JA, Lee AJ, Hall S: Associations of depression and anxiety with gender, age, health-related quality of life and symptoms in primary care COPD patients. Family practice 2007, 24(3):217-223. Epub 2007/05/17 10.1093/fampra/cmm009Cook EL, Harman JS: A comparison of health-related quality of life for individuals with mental health disorders and common chronic medical conditions. Public Health Rep 2008, 123(1):45-51. Epub 2008/03/20Dolan P, Gudex C, Kind P, Williams A: Valuing health states: a comparison of methods. Journal of health economics 1996, 15(2):209-231. Epub 1996/03/08 10.1016/0167-6296(95)00038-0Evans DB, Lauer JA, Tandon A, Murray CJ: Determinants of Health System Performance: Second-Stage Efficiency Analysis. In Health systems performance assessment debates, methods and empiricism. Edited by: Murray CJ, Evans DB. Geneva: World Health Organization; 2003:693-698.Fayers PM, Machin D: Quality of life The assessment, analysis and interpretation of patient-reported outcomes. 2nd edition. John Wiley & Sons Ltda: West Sussex; 2007.Gulis G: Life expectancy as an indicator of environmental health. European Journal of Epidemiolog 2000, 16(2):161-165. 10.1023/A:1007629306606Herdman M, Gudex C, Lloyd A, Janssen M, Kind P, Parkin D, et al.: Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5 L). Quality of life research 2011, 20(10):1727-1736. Epub 2011/04/12 10.1007/s11136-011-9903-xHorsman J, Furlong W, Feeny D, Torrance G: The Health Utilities Index (HUI): concepts, measurement properties and applications. Health and quality of life outcomes 2003, 1: 54. Epub 2003/11/14 10.1186/1477-7525-1-54Institute of Medicine, National Academy of Science: Summarizing population health directions for the development and application of population metrics. Washington, D.C: Committee on Summary Measures of Population Health; 1998.Jeremic V, Seke V, Radojicic Z, Jeremic D, Markovic A, Slovic D, et al.: Measuring health of countries: a novel approach. HealthMED 2011, 5(6):1762-1766.Jia H, Moriarty DG, Kanarek N: County-level social environment determinants of health-related quality of life among US adults: a multilevel analysis. Journal of community health 2009, 34(5):430-439. Epub 2009/06/26 10.1007/s10900-009-9173-5Konerding U, Moock J, Kohlmann T: The classification systems of the EQ-5D, the HUI II and the SF-6D: what do they have in common? Quality of life research 2009, 18(9):1249-1261. Epub 2009/09/04 10.1007/s11136-009-9525-8Krabbe PF, Peerenboom L, Langenhoff BS, Ruers TJ: Responsiveness of the generic EQ-5D summary measure compared to the disease-specific EORTC QLQ C-30. Quality of life research 2004, 13(7):1247-1253. Epub 2004/10/12le Hoi V, Chuc NT, Lindholm L: Health-related quality of life, and its determinants, among older people in rural Vietnam. BMC public health 2010, 10: 549. Epub 2010/09/14 10.1186/1471-2458-10-549McDonough CM, Tosteson AN: Measuring preferences for cost-utility analysis: how choice of method may influence decision-making. PharmacoEconomics 2007, 25(2):93-106. Epub 2007/01/26 10.2165/00019053-200725020-00003McHorney CA, Ware JE Jr, Raczek AE: The MOS 36-Item Short-Form Health Survey (SF-36): II Psychometric and clinical tests of validity in measuring physical and mental health constructs. Medical care 1993, 31(3):247-263. Epub 1993/03/01 10.1097/00005650-199303000-00006McHorney CA, Ware JE Jr, Lu JF, SCD : The MOS, 36-item Short-Form Health Survey (SF-36): III. Tests of data quality, scaling assumptions, and reliability across diverse patient groups. Medical care 1994, 32(1):40-66. 10.1097/00005650-199401000-00004Molla M, Madans J, Wagener D, Crimmins E: Summary measures of population health: Report of findings on methodologic and data issues. Hyattsville, MD: National Center for Health Statics; 2003. [cited 2013. Available from: http://www.cdc.gov/nchs/data/misc/pophealth.pdfMolla M, Madans J, Wagener D, Crimmins E: Summary measures of population health: Report of findings on methodologic and data issues. Hyattsville, MD: National Center for Health Statics; 2003.Murray CJ, Frenk J: A framework for assessing the performance of health systems. Bull World Health Organ 2000, 78(6):717-731. Epub 2000/08/05Mykletun A, Stordal E, Dahl AA: Hospital Anxiety and Depression (HAD) scale: factor structure, item analyses and internal consistency in a large population. The British journal of psychiatry 2001, 179: 540-544. Epub 2001/12/04 10.1192/bjp.179.6.540NAUGHTON MJ, Shumaker SA, Anderson RT, Czajkowski SM: Psychological Aspects of Health-Related Quality of Life Measurement: Tests and Scales. In Quality of Life and Pharmaco economics in Clinical Trials. Edited by: Spilker B. New York: Lippincott-Raven; 1996:117-131.Neumann PJ, Jacobson PD, Palmer JA: Measuring the value of public health systems: the disconnect between health economists and public health practitioners. American journal of public health 2008, 98(12):2173-2180. Epub 2008/10/17 10.2105/AJPH.2007.127134OMS: Official records of the world health organization. Geneva: World Health Organization; 1948. Ginebra: Organización Mundial de la Salud; 1948 [cited 2013 Abril]; Available from: http://www.who.int/library/collections/historical/es/index3.html Ginebra: Organización Mundial de la Salud; 1948 [cited 2013 Abril]; Available from:Paternina D, Melguizo E: Calidad de vida en adultos mayores. Revisión sistemática. V encuentro institucional semilleros de investigación. Cartagena, Colombia: Universidad de Cartagena; 2010.PATRICK D, Erickson P: Health Policy, Quality of Life: Health Care Evaluation and Resource Allocation. New York: Oxford University Press; 1993.Pereira CC, Palta M, Mullahy J, Fryback DG: Race and preference-based health-related quality of life measures in the United States. Quality of life research 2011, 20(6):969-978. Epub 2010/12/25 10.1007/s11136-010-9813-3Poole JL, Steen VD: The use of the Health Assessment Questionnaire (HAQ) to determine physical disability in systemic sclerosis. Arthritis care and research 1991, 4(1):27-31. Epub 1991/03/01 10.1002/art.1790040106Prause W, Saletu B, Tribl GG, Rieder A, Rosenberger A, Bolitschek J, et al.: Effects of socio-demographic variables on health-related quality of life determined by the quality of life index–German version. Human psychopharmacology 2005, 20(5):359-365. Epub 2005/06/28 10.1002/hup.699Prieto L, Sacristan JA: Problems and solutions in calculating quality-adjusted life years (QALYs). Health and quality of life outcomes 2003, 1: 80. Epub 2003/12/23 10.1186/1477-7525-1-80Pyne JM, Sieber WJ, David K, Kaplan RM, Hyman Rapaport M, Keith WD: Use of the quality of well-being self-administered version (QWB-SA) in assessing health-related quality of life in depressed patients. Journal of affective disorders 2003, 76(1–3):237-247. Epub 2003/08/29Roset M, Badia X, Mayo NE: Sample size calculations in studies using the EuroQol 5D. Quality of life research 1999, 8(6):539-549. Epub 1999/11/05 10.1023/A:1008973731515Salomon JA, Murray CJ, Ustün TB, Chatterji S: Health state valuations in summary measures of population health. In Health systems performance assessment debates, methods and empiricism. Edited by: Murray CJ, Evans DB. Geneva: World Health Organization; 2003:693-698.Sanders BS: Measuring Community Health Levels. American journal of public health and the nation's health 1964, 54: 1063-1070. Epub 1964/07/01 10.2105/AJPH.54.7.1063Tajvar M, Arab M, Montazeri A: Determinants of health-related quality of life in elderly in Tehran Iran. BMC public health 2008, 8: 323. Epub 2008/09/24 10.1186/1471-2458-8-323Tandon A, Lauer JA, Evans DB, Murray CJ: Health system efficiency: Concepts. In Health systems performance assessment debates, methods and empiricism. Edited by: Murray CJ, Evans DB. Geneva: World Health Organization; 2003:683-692.Thacker SB, Stroup DF, Carande-Kulis V, Marks JS, Roy K, Gerberding JL: Measuring the public's health. Public Health Rep 2006, 121(1):14-22. Epub 2006/01/19Torrance GW: Toward a utility theory foundation for health status index models. Health services research 1976, 11(4):349-369.Vogels T, Verrips GH, Verloove-Vanhorick SP, Fekkes M, Kamphuis RP, Koopman HM, et al.: Measuring health-related quality of life in children: the development of the TACQOL parent form. Quality of life research 1998, 7(5):457-465. Epub 1998/08/06Von Neumann J, Morgenstern O: Theory of games and economic behavior. 3rd edition. New York: Jhon Wiley and Sons; 1967.Wang H, Kindig DA, Mullahy J: Variation in Chinese population health related quality of life: results from a EuroQol study in Beijing, China. Quality of life research 2005, 14(1):119-132. Epub 2005/03/26 10.1007/s11136-004-0612-6Ware JE Jr, Sherbourne CD: The MOS 36-item short-form health survey (SF-36) I. Conceptual framework and item selection. Medical care 1992, 30(6):473-483. Epub 1992/06/11 10.1097/00005650-199206000-00002WHO: WHOQOL: measuring quality of life. 1997. Available from: http://www.who.int/mental_health/media/68.pdfWHO: Health systems performance assessment debates, methods and empiricism. Edited by: Murray CJ, Evans DB. Geneva: World Health Organization; 2003.Wright DR, Wittenberg E, Swan JS, Miksad RA, Prosser LA: Methods for measuring temporary health States for cost-utility analyses. PharmacoEconomics 2009, 27(9):713-723. Epub 2009/09/18 10.2165/11317060-000000000-00000Zarate V, Kind P, Valenzuela P, Vignau A, Olivares-Tirado P, Munoz A: Social valuation of EQ-5D health states: the Chilean case. Value in health 2011, 14(8):1135-1141. Epub 2011/12/14 10.1016/j.jval.2011.09.00

    Selection an Appropriate Leadership Style to Direct Hospital Manpower

    No full text
    This research has tried to find most proper leadership styles based on a approved model to direct hospital manpower appropriately. The main objective of this research was the comparison between manager’s existing leadership styles and suggested styles to them in order to direct existing styles toward suggested ones. In this cross- sectional study all Qom province hospital managers participated. From the hospital the staff, 385 persons were selected by randomized stratifying sampling. Data were collected by two types of validated questionnaires, one for the staff and another for managers, and analyzed by SPSS software. The finding showed that among four types of leadership styles, 75% of manager’s leadership style was “consultative” and rest were “exploitative- authoritative” or “benevolent- authoritative”, but in the view of about 78% of the staff, manager’s leadership style was “benevolent- authoritative” and only 0.8% of them believed that manager’s style was participative .In general, based on the staff point of view, managers behaved less participative. On the other hand, Tannenbaum and Schmidt leadership style continuum model proved that the best leadership style for all the hospital managers was the “consultative” one. It can be concluded that there was 25% gap between existing leadership styles and suggested ones and it should be tried to close this gap as far as posible
    corecore