Background An earthquake measuring 6.3 on the Richter scale struck the city of Bam in Iran on the 26th of December 2003 at 5.26 A.M. It was devastating, and left over 40,000 dead and around 30,000 injured. The profound tragedy of thousands killed has caused emotional and psychological trauma for tens of thousands of people who have survived. A study was carried out to assess psychological distress among Bam earthquake survivors and factors associated with severe mental health in those who survived the tragedy.
Background
An earthquake measuring 6.3 on the Richter scale struck the city of Bam in Iran on the 26th of December 2003 at 5.26 A.M. It was devastating, and left over 40,000 dead and around 30,000 injured. The profound tragedy of thousands killed has caused emotional and psychological trauma for tens of thousands of people who have survived. A study was carried out to assess psychological distress among Bam earthquake survivors and factors associated with severe mental health in those who survived the tragedy.Methods This was a population-based study measuring psychological distress among the survivors of Bam earthquake in Iran. Using a multi-stage stratified sampling method a random sample of individuals aged 15 years and over living in Bam were interviewed. Psychological distress was measured using the 12-item General Health Questionnaire (GHQ-12).
Methods
This was a population-based study measuring psychological distress among the survivors of Bam earthquake in Iran. Using a multi-stage stratified sampling method a random sample of individuals aged 15 years and over living in Bam were interviewed. Psychological distress was measured using the 12-item General Health Questionnaire (GHQ-12).Results In all 916 survivors were interviewed. The mean age of the respondents was 32.9 years (SD = 12.4), mostly were males (53%), married (66%) and had secondary school education (50%). Forty-one percent reported they lost 3 to 5 members of their family in the earthquake. In addition the findings showed that 58% of the respondents suffered from severe mental health as measured by the GHQ-12 and this was three times higher than reported psychological distress among the general population. There were significant differences between sub-groups of the study sample with regard to their psychological distress. The results of the logistic regression analysis also indicated that female gender; lower education, unemployment, and loss of family members were associated with severe psychological distress among earthquake victims.
Results
In all 916 survivors were interviewed. The mean age of the respondents was 32.9 years (SD = 12.4), mostly were males (53%), married (66%) and had secondary school education (50%). Forty-one percent reported they lost 3 to 5 members of their family in the earthquake. In addition the findings showed that 58% of the respondents suffered from severe mental health as measured by the GHQ-12 and this was three times higher than reported psychological distress among the general population. There were significant differences between sub-groups of the study sample with regard to their psychological distress. The results of the logistic regression analysis also indicated that female gender; lower education, unemployment, and loss of family members were associated with severe psychological distress among earthquake victims.Conclusion The study findings indicated that the amount of psychological distress among earthquake survivors was high and there is an urgent need to deliver mental health care to disaster victims in local medical settings and to reduce negative health impacts of the earthquake adequate psychological counseling is needed for those who survived the tragedy.
Conclusion
The study findings indicated that the amount of psychological distress among earthquake survivors was high and there is an urgent need to deliver mental health care to disaster victims in local medical settings and to reduce negative health impacts of the earthquake adequate psychological counseling is needed for those who survived the tragedy.

Background An earthquake measuring 6.3 on the Richter scale struck the city of Bam in Iran on the 26th of December 2003 at 5.26 A.M. It was devastating, the city was destroyed, left over 40,000 dead and around 30,000 injured, as well as destroying approximately 20,000 homes, leaving more than 45,000 people homeless [ 1 ]. The profound tragedy of thousands killed has caused emotional and psychological trauma for tens of thousands of people who have survived. In general earthquakes are known to be related to increased psychological symptoms among survivors and in particular it has been shown that earthquakes might cause post-traumatic stress disorder (PTSD). Several studies on psychological morbidity have been reported following earthquakes in different parts of the world [ 2 - 5 ], but there is no report from Iran. Iran is known to be a country of frequent severe earthquakes causing thousands of deaths in recent years. Therefore for the first time a study was conducted to measure psychological distress among the survivors of Bam earthquake in Iran. The objective was to indicate prevalence of psychological distress among survivors and to specify factors associated with psychological symptoms and thus provide information for interventions needed in Bam and in similar conditions in the country. In addition it was thought this might add to a small body of existing literature on the topic from a different population.
Background
An earthquake measuring 6.3 on the Richter scale struck the city of Bam in Iran on the 26th of December 2003 at 5.26 A.M. It was devastating, the city was destroyed, left over 40,000 dead and around 30,000 injured, as well as destroying approximately 20,000 homes, leaving more than 45,000 people homeless [ 1 ]. The profound tragedy of thousands killed has caused emotional and psychological trauma for tens of thousands of people who have survived. In general earthquakes are known to be related to increased psychological symptoms among survivors and in particular it has been shown that earthquakes might cause post-traumatic stress disorder (PTSD). Several studies on psychological morbidity have been reported following earthquakes in different parts of the world [ 2 - 5 ], but there is no report from Iran. Iran is known to be a country of frequent severe earthquakes causing thousands of deaths in recent years. Therefore for the first time a study was conducted to measure psychological distress among the survivors of Bam earthquake in Iran. The objective was to indicate prevalence of psychological distress among survivors and to specify factors associated with psychological symptoms and thus provide information for interventions needed in Bam and in similar conditions in the country. In addition it was thought this might add to a small body of existing literature on the topic from a different population.Methods This was a population-based study of psychological distress among Bam earthquake survivors aged 15 years and over at five months after the event. The pre-earthquake population of Bam was reported to be 97,000 and surprisingly it was increased to around 120,000 at the post-earthquake period (listing from the authorities). This was due to the fact that because of worry many people living in rural areas were moved to the city of Bam after earthquake. At the time of screening about 80% of people stayed inside their homes and the remaining 20% were moved to four specially designated sites with around 4000 tents. However, to select a representative sample of individuals living in Bam a stratified multi-stage area sampling was applied. The stratification was used because people living in the southern region of the city were less affluent and exposed to more damage as compared to those living in the northern part of the city. Every household or tent within the city had the same probability to be sampled. For the purposes of the first stage, units (census sections) were randomly selected after stratifying by region and size of residence. Then, within each census section the homes and tents to be sampled were selected using the procedure of random routes. Finally the last stage sampling units (the individuals) were selected randomly from all persons living in the same home or tent. Random sampling was based on a list of all households (N = 23000) derived from the electricity bills. A sample of 1150 households (5%) was selected as explained. However, we were actually able to screen 1000 households, giving a success rate of 87%. The main reason for the failed attempts for contact was due to the fact that the targeted house was uninhabited because the residents had moved out and there was no possibility to trace the survivors. In addition considering logistic difficulties we did not replace them with other households. A team of trained interviewers collected data in a week and all participants were interviewed in their homes or designated camps. However, the data were collected in a disorganized environment and thus data gathering strategy was based on offering help to survivors. Since there was no validated measure of PTSD in the Iranian language, only psychological distress was measured using the Iranian version of the 12-item General Health Questionnaire, GHQ-12 [ 6 ]. The scale examines whether the respondent has experienced a particular symptom or behavior recently. Each item is rated on a four-point scale (less than usual, no more than usual, rather more than usual, or much more than usual). The GHQ-12 is brief, simple, easy to complete, and its application in research settings as a screening tool is well documented, and there is evidence that the GHQ-12 is a consistent and reliable instrument when used in general population samples [ 7 ]. The study used the original scoring method. In this method response categories score 0, 0, 1, and 1 respectively. This gives scores ranging from 0 to 12  and higher values indicate more psychological symptoms [ 8 ]. In addition, we collected information about demographic and the number of family members that died due to the earthquake. To analyze data Student's t-test and one-way analysis of variance were used to find out differences in psychological distress among different sub-groups of the study sample and the logistic regression analysis was performed to investigate factors associated with distress. For the purpose of the logistic regression analysis we used the population mean score on the GHQ-12 as cut-off point as recommended [ 9 ].
Methods
This was a population-based study of psychological distress among Bam earthquake survivors aged 15 years and over at five months after the event. The pre-earthquake population of Bam was reported to be 97,000 and surprisingly it was increased to around 120,000 at the post-earthquake period (listing from the authorities). This was due to the fact that because of worry many people living in rural areas were moved to the city of Bam after earthquake. At the time of screening about 80% of people stayed inside their homes and the remaining 20% were moved to four specially designated sites with around 4000 tents. However, to select a representative sample of individuals living in Bam a stratified multi-stage area sampling was applied. The stratification was used because people living in the southern region of the city were less affluent and exposed to more damage as compared to those living in the northern part of the city. Every household or tent within the city had the same probability to be sampled. For the purposes of the first stage, units (census sections) were randomly selected after stratifying by region and size of residence. Then, within each census section the homes and tents to be sampled were selected using the procedure of random routes. Finally the last stage sampling units (the individuals) were selected randomly from all persons living in the same home or tent. Random sampling was based on a list of all households (N = 23000) derived from the electricity bills. A sample of 1150 households (5%) was selected as explained. However, we were actually able to screen 1000 households, giving a success rate of 87%. The main reason for the failed attempts for contact was due to the fact that the targeted house was uninhabited because the residents had moved out and there was no possibility to trace the survivors. In addition considering logistic difficulties we did not replace them with other households.A team of trained interviewers collected data in a week and all participants were interviewed in their homes or designated camps. However, the data were collected in a disorganized environment and thus data gathering strategy was based on offering help to survivors. Since there was no validated measure of PTSD in the Iranian language, only psychological distress was measured using the Iranian version of the 12-item General Health Questionnaire, GHQ-12 [ 6 ]. The scale examines whether the respondent has experienced a particular symptom or behavior recently. Each item is rated on a four-point scale (less than usual, no more than usual, rather more than usual, or much more than usual). The GHQ-12 is brief, simple, easy to complete, and its application in research settings as a screening tool is well documented, and there is evidence that the GHQ-12 is a consistent and reliable instrument when used in general population samples [ 7 ]. The study used the original scoring method. In this method response categories score 0, 0, 1, and 1 respectively. This gives scores ranging from 0 to 12  and higher values indicate more psychological symptoms [ 8 ]. In addition, we collected information about demographic and the number of family members that died due to the earthquake. To analyze data Student's t-test and one-way analysis of variance were used to find out differences in psychological distress among different sub-groups of the study sample and the logistic regression analysis was performed to investigate factors associated with distress. For the purpose of the logistic regression analysis we used the population mean score on the GHQ-12 as cut-off point as recommended [ 9 ].Results Data were collected from 1000 randomly selected households (600 homes and 400 tents). In total 999 survivors were interviewed, and data for 916 respondents were complete, giving a response rate of 91.7%. The mean age of the respondents was 32.9 years (SD = 12.4), and mostly were male (53%), married (66%) and had secondary school education (50%). The mean score of the survivors on the GHQ-12 was 8.7 (SD = 3.2). The findings showed that 58% of the respondents suffered from severe psychological distress as measured by the GHQ-12. Forty-one percent of the respondents reported that they lost three to five members of their family in the earthquake. The characteristics of the respondents are shown in Table  1 . Table 1 The characteristics of the study sample (n = 916) No. % Age ≤ 20 126 14 21–30 352 38 31–40 205 23 41–50 148 16 > 50 85 9 Mean (SD) 32.9 (12.4) Gender Male 486 53 Female 432 47 Marital status Single 257 28 Married 600 66 Divorced/widowed 59 6 Educational level Illiterate 158 17 Primary 181 20 Secondary 459 50 College/university 118 13 Employment status Employed 233 25 Housewife 277 30 Student 97 11 Unemployed 275 30 Retired 34 4 Number of family loss None 185 20 < 3 261 29 3–5 377 41 > 5 93 10 GHQ score Mean (SD) 8.7 (3.2) < mean score 385 42 > mean score 531 58 To examine differences in psychological distress among sub-groups of the study sample Student's t-test and one-way analysis of variance were performed. The findings showed that there were significant differences between people with different characteristics. People with old age, females, less educated individuals, divorced or widowed and unemployed respondents, and those with loss of more family members in the earthquake reported more severe psychological distress. The results are shown in Table  2 . Table 2 The GHQ-12 score by demographic characteristics (n = 916) Mean (SD) P Age groups 0.006 ≤ 20 7.8 (3.2) 21–30 8.6 (3.3) 31–40 8.9 (3.0) 41–50 8.9 (3.1) > 50 9.3 (3.0) Gender 0.04 Male 8.5 (3.2) Female 8.9 (3.1) Marital status < 0.0001 Single 8.1 (3.3) Married 8.9 (3.1) Divorced/widowed 9.9 (2.5) Educational level < 0.0001 Illiterate 9.7 (2.7) Primary 8.7 (3.2) Secondary 8.5 (3.2) College/university 8.3 (3.1) Employment status < 0.0001 Employed 8.4 (3.2) Housewife 8.8 (3.4) Student 7.0 (3.2) Unemployed 9.3 (2.9) Retired 9.0 (3.2) Number of family loss < 0.0001 None 7.7 (3.5) < 3 8.7 (3.2) 3–5 9.1 (2.8) > 5 9.3 (2.7) To investigate factors associated with severe psychological distress all the significant findings from the univariate analysis were entered into the logistic regression analysis. The analysis indicated that being female (OR = 2.73, 95% CI 1.19–6.26, P = 0.02), illiterate (OR = 3.36, 95% CI 1.11–10.2, P = 0.03), unemployed (OR = 4.39, 95% CI 1.56–12.4, P = 0.005), and the loss of more family members (OR for loss of more than five family members = 2.11, 95% CI 1.22–3.61, P = 0.007) were associated with more severe psychological distress. The results are shown in Table  3 . Table 3 The results of logistic regression analysis OR (95% CI) P Age 0.98 (0.95–1.01) 0.25 Gender Male 1.0 (ref.) Female 2.73 (1.19–6.26) 0.02 Marital status Single 1.0 (ref.) Married 1.56 (0.71–3.41) 0.26 Divorced/widowed 2.17 (0.50–9.37) 0.30 Educational level College/university 1.0 (ref.) Secondary 1.09 (0.51–2.31) 0.82 Primary 1.02 (0.43–2.43) 0.96 Illiterate 3.36 (1.11–10.2) 0.03 Employment status Housewife 1.0 (ref.) Employed 2.29 (0.85–6.18) 0.10 Student 1.90 (0.57–6.32) 0.29 Unemployed 4.39 (1.56–12.4) 0.005 Retired 1.43 (0.33–6.17) 0.63 Number of family loss None 1.0 (ref.) < 3 1.76 (1.21–2.55) 0.003 3–5 1.98 (1.32–2.98) 0.001 > 5 2.11 (1.22–3.61) 0.007
Results
Data were collected from 1000 randomly selected households (600 homes and 400 tents). In total 999 survivors were interviewed, and data for 916 respondents were complete, giving a response rate of 91.7%. The mean age of the respondents was 32.9 years (SD = 12.4), and mostly were male (53%), married (66%) and had secondary school education (50%). The mean score of the survivors on the GHQ-12 was 8.7 (SD = 3.2). The findings showed that 58% of the respondents suffered from severe psychological distress as measured by the GHQ-12. Forty-one percent of the respondents reported that they lost three to five members of their family in the earthquake. The characteristics of the respondents are shown in Table  1 .The characteristics of the study sample (n = 916)No.%AgeGenderMarital statusEducational levelEmployment statusNumber of family lossGHQ scoreTo examine differences in psychological distress among sub-groups of the study sample Student's t-test and one-way analysis of variance were performed. The findings showed that there were significant differences between people with different characteristics. People with old age, females, less educated individuals, divorced or widowed and unemployed respondents, and those with loss of more family members in the earthquake reported more severe psychological distress. The results are shown in Table  2 .The GHQ-12 score by demographic characteristics (n = 916)Mean (SD)PAge groupsGenderMarital statusEducational levelEmployment statusNumber of family lossTo investigate factors associated with severe psychological distress all the significant findings from the univariate analysis were entered into the logistic regression analysis. The analysis indicated that being female (OR = 2.73, 95% CI 1.19–6.26, P = 0.02), illiterate (OR = 3.36, 95% CI 1.11–10.2, P = 0.03), unemployed (OR = 4.39, 95% CI 1.56–12.4, P = 0.005), and the loss of more family members (OR for loss of more than five family members = 2.11, 95% CI 1.22–3.61, P = 0.007) were associated with more severe psychological distress. The results are shown in Table  3 .The results of logistic regression analysisOR (95% CI)PAgeGenderMarital statusEducational levelEmployment statusNumber of family lossDiscussion This was a population-based study measuring psychological distress among survivors of the Bam earthquake in Iran. Psychological morbidity was higher among females, less educated respondents and unemployed individuals. Perhaps such observation might relate to the fact that these groups of people were exposed to a relatively homogenous set of psychological stressors, leading to relatively homogenous mental health outcomes [ 10 , 11 ]. In addition although in the univariate analysis there were significant differences among sub-groups of the study sample with regard to their GHQ-12 mean scores, in the logistic regression analysis age and marital status no longer remained significant. This is consistent with other research findings where female gender, lower education, and lower socio-economic status were found to be related to higher PTSD and depression among earthquake survivors [ 12 , 13 ]. However, recent findings on the topic showed a differential predictor pattern for PTSD and depression among earthquake survivors indicating that although certain factors (e.g. grater fear during the earthquake and female gender) relate to PTSD, lower education and loss of family members tend to relate to depression and not to PTSD [ 13 , 14 ]. This suggests that when interpreting the study results one might relate female gender to possible PTSD which we did not measure, and the other variables to depression which was measured using the GHQ-12. Most notably it was found that people who lost family members reported significant severe psychological distress compared to those who did not. Also there was a distinct pattern of psychological distress among those who lost their family members in the earthquake showing a dose-response relationship between loss and the risk of more psychological distress. One might argue that the relationship between loss of relatives and psychological distress may be a reflection of the relationship between severity of trauma exposure and psychopathology. Since no other variables reflecting trauma-exposure (e.g. fear during the earthquake, level of damage to home, injury, etc.) were entered in the regression equation, 'loss of relatives' was the only variable tapping that, as there is high correlation between loss of first degree relatives (with whom survivors often share the same roof) and exposure to serious damage or collapse of the house. In addition studies have indicated that loss is a strong determinant of PTSD among earthquake survivors and thus it is argued the observation that the risk of PTSD is linked to the amount of loss is an important issue that needs to be incorporated in the development of any effective preventive strategy [ 15 ]. As discussed earlier such finding has been challenged and studies have shown that PTSD and depression are distinct issues and loss only relates to depression whereas PTSD is linked to factors relating to exposure to threat or fear for life [ 14 ]. However, since in the present study only the GHQ-12 was used, there is no way of knowing which factors related to PTSD and which to depression. The GHQ-12 has items tapping depression but little is known as to how sensitive is to picking up PTSD. Psychological distress among earthquake survivors alongside experience of other problems could be considered a serious issue for people's health status living in such difficult conditions. Evidence suggests that severe earthquakes even can cause long-standing morbidity [ 12 ]. However, past psychiatric illness also might contribute to this situation [ 15 , 16 ]. Unfortunately one of the shortcomings of the present study was that we did not measure previous psychiatric conditions among survivors and thus it was not possible to comment on this further. It is recommended that the mean GHQ score for the whole population of respondents provide a rough guide to the best cut-off threshold [ 9 ]. Thus considering people who scored above the mean, the findings from the present study indicated that 58% of the respondents showed an indication of severe mental health problems. Comparing the figure with the national data this was found to be three times higher than reported mental disorders in the general population [ 17 ]. A study using the GHQ-28 measuring prevalence of psychiatric disorder following the China earthquake showed relatively a similar result where the rate of psychological morbidity for earthquake survivors was found to be 51% [ 18 ]. Thus it is argued that there is an urgent need to deliver mental health care to disaster victims in local medical settings and health care professionals who work with the earthquake victims need to be promptly and efficiently trained in mental health crisis interventions [ 19 ]. The results reported here is an estimate for the overall population experiencing the earthquake. Studies have shown that there is variation in psychological morbidity among earthquake survivors by epicenter proximity and rate of property damage [ 12 , 18 ]. However one should be aware that these variables are not the only information that is needed for studying the relationship between psychological distress and the impact of the earthquake. There is also need to obtain information from earthquake survivors on the extent of damage to their homes, experience of being buried under rubble, participation in rescue operations, and witnessing grotesque sites [e.g. see [ 13 , 14 ]]. The present study had certain methodological limitations. Firstly, the results were based on the GHQ-12 scores and we did not measure PTSD symptoms. In this respect also it is important to acknowledge that the GHQ is a general measure of mental health and it is not a measure of diagnostic depression. Thus, since depression is also common in earthquake survivors, our study is limited in not including a validated diagnostic measure of depression. Secondly, no information was obtained on important trauma-exposure variables such as extent of fear or perceived life-threat during the earthquake, rubble experience, disability or injury, et cetera. Thirdly, data on important demographic variables such as past psychiatric illness, and family psychiatric illness were not collected. However in spite of these limitations, the results from this study are useful. This study is the only paper addressing reports on the psychological consequences of the most disastrous earthquakes of the last 50 years. In addition, to our knowledge the international literature does not contain any study on the psychological status of Iranian earthquake survivors, despite the fact that Iran is an earthquake-prone country. It seems that the future research should carefully assess the psychological distress and disruption experiences of the survivors in order to implement necessary interventions. Given that Iran is a country that suffers catastrophic earthquakes relatively frequently, there is need to develop and validate standard instruments such as PTSD measures to include in the future research.
Discussion
This was a population-based study measuring psychological distress among survivors of the Bam earthquake in Iran. Psychological morbidity was higher among females, less educated respondents and unemployed individuals. Perhaps such observation might relate to the fact that these groups of people were exposed to a relatively homogenous set of psychological stressors, leading to relatively homogenous mental health outcomes [ 10 , 11 ]. In addition although in the univariate analysis there were significant differences among sub-groups of the study sample with regard to their GHQ-12 mean scores, in the logistic regression analysis age and marital status no longer remained significant. This is consistent with other research findings where female gender, lower education, and lower socio-economic status were found to be related to higher PTSD and depression among earthquake survivors [ 12 , 13 ]. However, recent findings on the topic showed a differential predictor pattern for PTSD and depression among earthquake survivors indicating that although certain factors (e.g. grater fear during the earthquake and female gender) relate to PTSD, lower education and loss of family members tend to relate to depression and not to PTSD [ 13 , 14 ]. This suggests that when interpreting the study results one might relate female gender to possible PTSD which we did not measure, and the other variables to depression which was measured using the GHQ-12.Most notably it was found that people who lost family members reported significant severe psychological distress compared to those who did not. Also there was a distinct pattern of psychological distress among those who lost their family members in the earthquake showing a dose-response relationship between loss and the risk of more psychological distress. One might argue that the relationship between loss of relatives and psychological distress may be a reflection of the relationship between severity of trauma exposure and psychopathology. Since no other variables reflecting trauma-exposure (e.g. fear during the earthquake, level of damage to home, injury, etc.) were entered in the regression equation, 'loss of relatives' was the only variable tapping that, as there is high correlation between loss of first degree relatives (with whom survivors often share the same roof) and exposure to serious damage or collapse of the house. In addition studies have indicated that loss is a strong determinant of PTSD among earthquake survivors and thus it is argued the observation that the risk of PTSD is linked to the amount of loss is an important issue that needs to be incorporated in the development of any effective preventive strategy [ 15 ]. As discussed earlier such finding has been challenged and studies have shown that PTSD and depression are distinct issues and loss only relates to depression whereas PTSD is linked to factors relating to exposure to threat or fear for life [ 14 ]. However, since in the present study only the GHQ-12 was used, there is no way of knowing which factors related to PTSD and which to depression. The GHQ-12 has items tapping depression but little is known as to how sensitive is to picking up PTSD.Psychological distress among earthquake survivors alongside experience of other problems could be considered a serious issue for people's health status living in such difficult conditions. Evidence suggests that severe earthquakes even can cause long-standing morbidity [ 12 ]. However, past psychiatric illness also might contribute to this situation [ 15 , 16 ]. Unfortunately one of the shortcomings of the present study was that we did not measure previous psychiatric conditions among survivors and thus it was not possible to comment on this further.It is recommended that the mean GHQ score for the whole population of respondents provide a rough guide to the best cut-off threshold [ 9 ]. Thus considering people who scored above the mean, the findings from the present study indicated that 58% of the respondents showed an indication of severe mental health problems. Comparing the figure with the national data this was found to be three times higher than reported mental disorders in the general population [ 17 ]. A study using the GHQ-28 measuring prevalence of psychiatric disorder following the China earthquake showed relatively a similar result where the rate of psychological morbidity for earthquake survivors was found to be 51% [ 18 ]. Thus it is argued that there is an urgent need to deliver mental health care to disaster victims in local medical settings and health care professionals who work with the earthquake victims need to be promptly and efficiently trained in mental health crisis interventions [ 19 ].The results reported here is an estimate for the overall population experiencing the earthquake. Studies have shown that there is variation in psychological morbidity among earthquake survivors by epicenter proximity and rate of property damage [ 12 , 18 ]. However one should be aware that these variables are not the only information that is needed for studying the relationship between psychological distress and the impact of the earthquake. There is also need to obtain information from earthquake survivors on the extent of damage to their homes, experience of being buried under rubble, participation in rescue operations, and witnessing grotesque sites [e.g. see [ 13 , 14 ]].The present study had certain methodological limitations. Firstly, the results were based on the GHQ-12 scores and we did not measure PTSD symptoms. In this respect also it is important to acknowledge that the GHQ is a general measure of mental health and it is not a measure of diagnostic depression. Thus, since depression is also common in earthquake survivors, our study is limited in not including a validated diagnostic measure of depression. Secondly, no information was obtained on important trauma-exposure variables such as extent of fear or perceived life-threat during the earthquake, rubble experience, disability or injury, et cetera. Thirdly, data on important demographic variables such as past psychiatric illness, and family psychiatric illness were not collected. However in spite of these limitations, the results from this study are useful. This study is the only paper addressing reports on the psychological consequences of the most disastrous earthquakes of the last 50 years. In addition, to our knowledge the international literature does not contain any study on the psychological status of Iranian earthquake survivors, despite the fact that Iran is an earthquake-prone country. It seems that the future research should carefully assess the psychological distress and disruption experiences of the survivors in order to implement necessary interventions. Given that Iran is a country that suffers catastrophic earthquakes relatively frequently, there is need to develop and validate standard instruments such as PTSD measures to include in the future research.Conclusions In conclusion the findings from this study indicated that the survivors of Bam earthquake suffer from psychological distress three times higher than the normal population. In addition female gender, lower education, unemployment, and loss of family members were found to be associated with more severe psychological morbidity among survivors. This suggests that to reduce negative health impacts of the earthquake adequate psychological counseling is needed for those who survived the tragedy.
Conclusions
In conclusion the findings from this study indicated that the survivors of Bam earthquake suffer from psychological distress three times higher than the normal population. In addition female gender, lower education, unemployment, and loss of family members were found to be associated with more severe psychological morbidity among survivors. This suggests that to reduce negative health impacts of the earthquake adequate psychological counseling is needed for those who survived the tragedy.Abbreviations GHQ-12: The 12-item General Health Questionnaire; PTSD: Post-traumatic stress disorder; SD: Standard deviation; OR: Odds ratio, CI: Confidence interval.
Abbreviations
GHQ-12: The 12-item General Health Questionnaire; PTSD: Post-traumatic stress disorder; SD: Standard deviation; OR: Odds ratio, CI: Confidence interval.Competing interests The author(s) declare that they have no competing interests.
Competing interests
The author(s) declare that they have no competing interests.Authors' contributions AM was the principle investigator and contributed to the study design, the data analysis and wrote the paper. All other investigators contributed to the study design, the data collection and analysis. All authors reviewed and contributed to the final manuscript.
Authors' contributions
AM was the principle investigator and contributed to the study design, the data analysis and wrote the paper. All other investigators contributed to the study design, the data collection and analysis. All authors reviewed and contributed to the final manuscript.Pre-publication history The pre-publication history for this paper can be accessed here:
Pre-publication history
The pre-publication history for this paper can be accessed here:


Traditional two dimensional journal publishing may no longer be enough, and may be hindering, the interpretation of the complex datasets and analyses generated by microarray experiments in medicine

“Publishing results in traditional paper based way in a journal hides too much information.” This is the verdict of Markus Ruschhaupt and colleagues who, in a paper in  Statistical Applications in Genetics and Molecular Biology  (3: article 37), discuss a paradigm for the presentation of complex data—in this case, from microarray analyses. The title of the article, “A Compendium to Ensure Reproducibility in High-Dimensional Classification Tasks,” may not lend itself easily to a clinical audience, but the underlying message to clinicians could not be more important: that, currently, studies involving large datasets, especially ones that have a clinical outcome, are so poorly reported (or possibly so poorly done) that many are not reproducible. This problem was also the topic of a recent meeting in Heidelberg, “Best Practice in Microarray Studies” ( http://www.biometrie.uni-heidelberg.de/workshops/bestpractice/index.htm ).Statistical Applications in Genetics and Molecular BiologyAs microarrays have become mainstream research tools in biology and medicine, the large datasets and complex analyses from these studies have presented challenges: for authors in analyzing the data, for reviewers and editors in deciding on the suitability of papers for publication, for journals in determining how much data needs to be presented within the paper itself, for other researchers in reproducing the data, and, finally, for readers in deciding how to assess the data presented. The results from several high-profile papers have already proved difficult to reproduce, even by those with sufficient time and computing expertise.Where do such analyses leave the new science of molecular pathology? Ruschhaupt and colleagues comment that “the literature on the induction of prognostic profiles from microarray studies is a methodological wasteland.” Much the same could be said of other applications of molecular biology to clinical samples. A systematic review of molecular and biological tumor markers in neuroblastoma (Clin Cancer Res 10: 4–12) found that its conclusions were limited by “small sample sizes, poor statistical reporting, large heterogeneity across studies…and publication bias.” John Ioannidis and colleagues (Lancet 362: 1439–1444) did a similar analysis of 30 microarray studies with major clinical outcomes in cancer. They showed that the studies were small—median sample size was 25 patients, and validation was incomplete in most studies. They recommended that molecular prognostic studies be classified as phase 1 (early exploratory probing associations), phase 2 (exploratory with extensive analyses), or phase 3 (large confirmatory studies with pre-stated hypotheses and precise quantification of the magnitude of the effect), and that only studies that had undergone phase 3 testing should be considered robust enough for use in clinical practice. Most current studies should be considered as phase 1 or, at best, phase 2.So, despite considerable hype, the published studies are far from the level of evidence that would be accepted for virtually any other medical test. In a review in 2003 (Hematology [Am Soc Hematol Educ Program] 2003: 279–293), Rita Braziel and colleagues concluded, “rapid identification and neutralization of spurious results is essential to prevent them from becoming accepted facts.”But these problems are not new in medical research. In 1994 (BMJ 308: 283–284), Doug Altman, who was instrumental in developing the CONSORT guidelines for reporting of clinical trials, said that “huge sums of money are spent annually on research that is seriously flawed through the use of inappropriate designs, unrepresentative samples, small samples, incorrect methods of analysis, and faulty interpretation,” and “that quality control needs to be built in from the start rather than the failures being discarded.”So how can we ensure that the wealth of data pouring out of microarray and other molecular diagnostic studies is turned into meaningful knowledge? The Microarray Gene Expression Data Society has proposed a set of guidelines (MIAME) for the reporting of microarray data, and that all such data should be deposited in public databases. But as Ruschhaupt and others have shown, disclosure of results and data is not enough, since there is little consensus on the appropriate statistical analyses and many are developed on a case by case basis, which may not be reproducible, even by the authors. Some researchers advocate the use of standard statistical packages, which allows the reader to repeat an entire analysis quickly and, hence, assess the robustness of the results. Some authors have produced a transcript of their statistical analyses as a supplement to their articles (e.g., Nucleic Acids Res 32: e50). At the very least authors should have a protocol with a prespecified plan for patient selection and statistical analysis—accepted practice for clinical trials, but not yet for other medical research. An ultimate aim for reporting would be the type of compendium discussed by Ruschhaupt and colleagues—“an interactive document that bundles primary data, statistical processing methods, figures, and derived data together with the textual documentation and conclusions.” One such compendium is illustrated in a paper by Robert Gentleman (Stat Appl Genet Mol Biol 4: article 2).  PLoS Medicine  is keen to work with authors towards making such reporting possible. But although the time might have gone when the two-dimensional journal article could suffice for complex papers, clinicians should nonetheless apply the same critical assessment that they would for any other clinical tool. If a result is too good to be true, it probably is.PLoS Medicine


Background Diagnostic discordance for osteoporosis is the observation that the T-score of an individual patient varies from one key measurement site to another, falling into two different diagnostic categories identified by the World Health Organization (WHO) classification system. This study was conducted to evaluate the presence and risk factors for this phenomenon in a large sample of Iranian population.
Background
Diagnostic discordance for osteoporosis is the observation that the T-score of an individual patient varies from one key measurement site to another, falling into two different diagnostic categories identified by the World Health Organization (WHO) classification system. This study was conducted to evaluate the presence and risk factors for this phenomenon in a large sample of Iranian population.Methods Demographic data, anthropometric measurements, and risk factors for osteoporosis were derived from a database on 4229 patients referred to a community-based outpatient osteoporosis testing center from 2000 to 2003. Dual-energy X-ray absorptiometry (DXA) was performed on L1–L4 lumbar spine and total hip for all cases. Minor discordance was defined as present when the difference between two sites was no more than one WHO diagnostic class. Major discordance was present when one site is osteoporotic and the other is normal. Subjects with incomplete data were excluded.
Methods
Demographic data, anthropometric measurements, and risk factors for osteoporosis were derived from a database on 4229 patients referred to a community-based outpatient osteoporosis testing center from 2000 to 2003. Dual-energy X-ray absorptiometry (DXA) was performed on L1–L4 lumbar spine and total hip for all cases. Minor discordance was defined as present when the difference between two sites was no more than one WHO diagnostic class. Major discordance was present when one site is osteoporotic and the other is normal. Subjects with incomplete data were excluded.Results In 4188 participants (3848 female, mean age 53.4 ± 11.8 years), major discordance, minor discordance, and concordance of T-scores were seen in 2.7%, 38.9% and 58.3%, respectively. In multivariate logistic regression analysis, older age, menopause, obesity, and belated menopause were recognized as risk factors and hormone replacement therapy as a protective factor against T-score discordance.
Results
In 4188 participants (3848 female, mean age 53.4 ± 11.8 years), major discordance, minor discordance, and concordance of T-scores were seen in 2.7%, 38.9% and 58.3%, respectively. In multivariate logistic regression analysis, older age, menopause, obesity, and belated menopause were recognized as risk factors and hormone replacement therapy as a protective factor against T-score discordance.Conclusion The high prevalence of T-score discordance may lead to problems in interpretation of the densitometry results for some patients. This phenomenon should be regarded as a real and prevalent finding and physicians should develop a particular strategy approaching to these patients.
Conclusion
The high prevalence of T-score discordance may lead to problems in interpretation of the densitometry results for some patients. This phenomenon should be regarded as a real and prevalent finding and physicians should develop a particular strategy approaching to these patients.

Background Osteoporosis is defined as a systemic skeletal disease characterized by low bone mass and micro-architectural deterioration of bone tissue, with a consequent increase in bone fragility and susceptibility to fracture [ 1 , 2 ]. This definition indicates that measurement of bone mineral density (BMD) is a central component to diagnosis of the disease [ 3 ]. 'T score' is a statistical definition which indicates the difference between patient's BMD and mean bone density of normal population in the age of 20 – 30 (reference population) [ 3 ]. This value shows the difference in terms of standard deviations. According to the World Health Organization (WHO) classification system, T scores under the value of -2.5 are considered as osteoporosis and between -1 and -2.5 as osteopenia. These figures are usually calculated separately for two different sites of lumbar spine and total hip. Discordance in diagnosis of osteoporosis is defined as presence of different categories of T scores (osteoporosis, osteopenia, and normal) in two skeletal sites of an individual patient [ 4 ]. This phenomenon has been divided into two groups: major and minor [ 5 ]. Minor discordance happens when the different diagnostic classes are adjacent; i.e., patient is diagnosed as osteoporotic in one site and osteopenic in the other site, or, osteopenic in one site and normal in the other site. If the diagnosis is osteoporosis in one site and the other site is in the normal range, the discordance falls into the major class. Actually, one of the reasons for measuring BMD in several sites is the presence of discordance, which can affect the diagnosis and therapeutic plan in an individual person. Various studies have analyzed the prevalence and impact of T-score discordance on different aspects of management of osteoporosis [ 5 - 9 ]. However, most of these studies did not evaluate risk factors for this phenomenon. Given this background and concerning the need for the estimation of the impact of this phenomenon in our country, we aimed to evaluate the presence and risk factors for T-score discordance in a large sample of Iranian population.
Background
Osteoporosis is defined as a systemic skeletal disease characterized by low bone mass and micro-architectural deterioration of bone tissue, with a consequent increase in bone fragility and susceptibility to fracture [ 1 , 2 ]. This definition indicates that measurement of bone mineral density (BMD) is a central component to diagnosis of the disease [ 3 ].'T score' is a statistical definition which indicates the difference between patient's BMD and mean bone density of normal population in the age of 20 – 30 (reference population) [ 3 ]. This value shows the difference in terms of standard deviations. According to the World Health Organization (WHO) classification system, T scores under the value of -2.5 are considered as osteoporosis and between -1 and -2.5 as osteopenia. These figures are usually calculated separately for two different sites of lumbar spine and total hip.Discordance in diagnosis of osteoporosis is defined as presence of different categories of T scores (osteoporosis, osteopenia, and normal) in two skeletal sites of an individual patient [ 4 ]. This phenomenon has been divided into two groups: major and minor [ 5 ]. Minor discordance happens when the different diagnostic classes are adjacent; i.e., patient is diagnosed as osteoporotic in one site and osteopenic in the other site, or, osteopenic in one site and normal in the other site. If the diagnosis is osteoporosis in one site and the other site is in the normal range, the discordance falls into the major class.Actually, one of the reasons for measuring BMD in several sites is the presence of discordance, which can affect the diagnosis and therapeutic plan in an individual person. Various studies have analyzed the prevalence and impact of T-score discordance on different aspects of management of osteoporosis [ 5 - 9 ]. However, most of these studies did not evaluate risk factors for this phenomenon.Given this background and concerning the need for the estimation of the impact of this phenomenon in our country, we aimed to evaluate the presence and risk factors for T-score discordance in a large sample of Iranian population.Methods Participants in this study were 4229 persons who underwent bone densitometry in outpatient clinic of Endocrinology & Metabolism Research Center in Tehran from 2000 to 2003. A considerable proportion of these cases were healthy post-menopausal women referred by clinicians for densitometric evaluations. All study participants signed the informed consent for any scientific approach to their medical registered data. Our Institutional Review Board approved this study. A standardized questionnaire was filled before densitometry for all participants. Demographic data (including age and sex) as well as other known or suspicious risk factors for osteoporosis (including menopause, age at menopause, age at menarche, history of osteoporotic fractures, drugs, and smoking) were collected. All participants had their standing height measured using a stadiometer to the nearest 0.5 cm. Weight was measured on a standard weighting scale with a precision of 0.5 kg. Body mass index (BMI) was calculated as weight (kg) divided by height (m) squared. All the BMD measurements were done for diagnostic purposes and none of the participants were on the treatment with bone active agents (hormone replacement therapy was not considered a bone active agent). BMD was measured at the lumbar spine and total hip with dual X-ray absorptiometry (DXA) using a Lunar DPXMD densitometer (Lunar 7164, GE, Madison, WI) by a trained operator according to the manufacturer's instruction. The instrument was calibrated weekly by using appropriate phantoms. Precision error for BMD measurements was 1–1.5% in the lumbar and 2–3% in the femoral regions. The device normative data of US population for spine BMD and NHANES III study for femur BMD were used as reference values. All the data gained from densitometry and questionnaires were entered into a comprehensive relational database. The participants with incomplete data were excluded from the study. To compare presence of various risk factors in participants with and without T-score discordance, chi-square test and independent sample t-test were used firstly. Potential risk factors were entered to a multivariate binary logistic regression analysis and the resulted odds ratios with 95% confidence intervals were reported.  P  values less than 0.05 were taken to indicate statistical significance. Statistical analyses were performed using Stata Statistical Package, version 8.0 (Stata Corporation, College Station, Tx).
Methods
Participants in this study were 4229 persons who underwent bone densitometry in outpatient clinic of Endocrinology & Metabolism Research Center in Tehran from 2000 to 2003. A considerable proportion of these cases were healthy post-menopausal women referred by clinicians for densitometric evaluations. All study participants signed the informed consent for any scientific approach to their medical registered data. Our Institutional Review Board approved this study.A standardized questionnaire was filled before densitometry for all participants. Demographic data (including age and sex) as well as other known or suspicious risk factors for osteoporosis (including menopause, age at menopause, age at menarche, history of osteoporotic fractures, drugs, and smoking) were collected. All participants had their standing height measured using a stadiometer to the nearest 0.5 cm. Weight was measured on a standard weighting scale with a precision of 0.5 kg. Body mass index (BMI) was calculated as weight (kg) divided by height (m) squared. All the BMD measurements were done for diagnostic purposes and none of the participants were on the treatment with bone active agents (hormone replacement therapy was not considered a bone active agent).BMD was measured at the lumbar spine and total hip with dual X-ray absorptiometry (DXA) using a Lunar DPXMD densitometer (Lunar 7164, GE, Madison, WI) by a trained operator according to the manufacturer's instruction. The instrument was calibrated weekly by using appropriate phantoms. Precision error for BMD measurements was 1–1.5% in the lumbar and 2–3% in the femoral regions. The device normative data of US population for spine BMD and NHANES III study for femur BMD were used as reference values.All the data gained from densitometry and questionnaires were entered into a comprehensive relational database. The participants with incomplete data were excluded from the study. To compare presence of various risk factors in participants with and without T-score discordance, chi-square test and independent sample t-test were used firstly. Potential risk factors were entered to a multivariate binary logistic regression analysis and the resulted odds ratios with 95% confidence intervals were reported.  P  values less than 0.05 were taken to indicate statistical significance. Statistical analyses were performed using Stata Statistical Package, version 8.0 (Stata Corporation, College Station, Tx).PResults In sum, 4188 persons were enrolled in the study. Characteristics of all participants are summarized in Table  1 . The main reasons of referral for BMD measurement were menopause in 49%, old age in 16%, glucocorticoid use in 9%, history of low energy fractures in 1.5%, and other reasons (such as metabolic disorders, rheumatoid arthritis, positive family history, leanness, and transplantation) in 4.5% of participants. In 20% of participants, no major risk factor was identified as the referral reason. Table 1 Characteristics of the study population* Male participants (n = 340) Female participants (n = 3848) Age (years) 49.7 (16.3) 53.8 (11.2) Weight (kilograms) 68.5 (13.1) 67.1 (11.9) Height (centimeters) 168.5 (7.7) 156.1 (6.1) Body Mass Index (kg/cm 2 ) 24.1 (4.2) 27.6 (4.7) History of osteoporotic fracture 8 (2.4) 47(1.2) Smoking 35 (10.3) 94 (2.4) Corticosteroid use 89 (26.2) 298 (7.7) Hormone Replacement Therapy 231 (6.0) Age at menarche (years) 13.6 (1.5) Menopause 2137 (55.5) Age at menopause (years) 47.2 (5.8) Femoral T score -0.93 (1.24) -1.43 (1.18) Lumbar T score -1.40 (1.48) -1.45 (1.54) * Numbers are presented as mean (standard deviation in parenthesis) for numerical variables and frequency (percentage in parenthesis) for categorical variables. Totally, 518 participants were diagnosed in osteoporotic range in hip area and 1036 participants in the lumbar area. T-score classifications are presented in Table  2 . Major discordance was observed in BMD results of 115 (2.7%) participants. Minor discordance was observed in 1631 (38.9%) participants and T-score categories of two measurement sites in other 2442 (58.3%) participants were not different. Distribution and pattern of this variable in different genders is depicted in Table  3 . Table 2 Classification of T scores according to WHO criteria in different sites* Lumbar spine Total hip No. % 95% Confidence Intervals No. % 95% Confidence Intervals Osteoporosis (T = -2.5) 1036 24.7 23.4–26.0 518 12.4 11.4–13.4 Osteopenia (-2.5 < T = -1) 1605 38.3 36.8–39.8 1592 38.0 36.5–39.5 Normal (T > -1) 1547 36.9 35.5–38.4 2078 49.6 48.1–51.1 Table 3 Distribution of diagnostic discordances according to WHO criteria in different genders* Male participants (n = 340) Female participants (n = 3848) Total (n = 4188) Major T-score Discordance 7 (2.1) 108 (2.8) 115 (2.7) Hip Osteoporosis, Normal Lumbar 5 16 21 Hip Normal, Lumbar Osteoporosis 2 92 94 Minor T-score Discordance 117 (34.4) 1514 (39.3) 1631 (38.9) Hip Osteoporosis, Lumbar Osteopenia 10 99 109 Hip Osteopenia, Lumbar Osteoporosis 39 515 554 Hip Osteopenia, Normal Lumbar 35 220 255 Hip Normal, Lumbar Osteopenia 33 680 713 T-score Concordance 216 (63.5) 2226 (57.8) 2442 (58.3) Hip and Lumbar Osteoporosis 50 338 388 Hip and Lumbar Osteopenia 93 690 783 Hip and Lumbar Normal 73 1198 1271 * Numbers are presented as frequency (percentage in parenthesis). T-score discordance was more prevalent in women than men (42.2% versus 36.5%, P = 0.042). The mean age of participants with discordance (54.8 years) was higher than the other group (52.5 years, P < 0.001). In 3848 female participants, the number of post-menopausal women with diagnostic discordances (951 of 2027) was significantly higher than pre-menopausal participants with discordance (671 of 1821; P < 0.001). In multivariate analysis (Table  4 ), two genders lost their difference in occurrence of discordance. Effects of age and menopause were established with their significant odds ratios. Participants with late menopause (age at menopause > 50) were more likely to show T-score discordances. Obesity defined as BMI over 30 was recognized as a risk factor for major discordance and smoking as a protective factor against minor discordance. Hormone replacement therapy was a significant protector against both. Table 4 Results of multivariate logistic regression analysis for risk factors of major and minor discordance getting T-score concordance at lumbar and femoral sites as the reference Variables Minor Discordance Major Discordance Gender (female) 1.09 (0.85 – 1.4) 1.02 (0.45 – 2.3) Age decade 1.2 (1.1 – 1.3)* 1.5 (1.2 – 1.9)* Age group (>65 years) 1.2 (1.01 – 1.6)* 1.4 (0.70 – 2.7) Corticosteroid use 0.89 (0.73 – 1.1) 0.71 (0.37 – 1.3) Body Mass Index (>30 kg/cm 2 ) 1.01 (0.87 – 1.2) 1.7 (1.2 – 2.6)* History of osteoporotic fracture 1.1 (0.59 – 2.0) 1.3 (0.29 – 5.5) Smoking 0.66 (0.45 – 0.97)* 0.49 (0.12 – 2.1) Menopause 1.3 (1.1 – 1.5)* 1.7 (1.01 – 2.7)* Hormone Replacement Therapy 0.37 (0.16 – 0.82)* 0.54 (0.36 – 0.82)* Age at menarche (> 13 years) 1.1 (0.90 – 1.3) 0.82 (0.50 – 1.3) Age at menopause (> 50 years) 1.4 (1.1 – 1.7)* 2.0 (1.2 – 3.4)* * indicates significant odds ratio. Numbers are presented as odds ratio (95% confidence intervals in parentheses).
Results
In sum, 4188 persons were enrolled in the study. Characteristics of all participants are summarized in Table  1 . The main reasons of referral for BMD measurement were menopause in 49%, old age in 16%, glucocorticoid use in 9%, history of low energy fractures in 1.5%, and other reasons (such as metabolic disorders, rheumatoid arthritis, positive family history, leanness, and transplantation) in 4.5% of participants. In 20% of participants, no major risk factor was identified as the referral reason.Characteristics of the study population*Male participants (n = 340)Female participants (n = 3848)Age (years)Weight (kilograms)Height (centimeters)Body Mass Index (kg/cm 2 )History of osteoporotic fractureSmokingCorticosteroid useHormone Replacement TherapyAge at menarche (years)MenopauseAge at menopause (years)Femoral T scoreLumbar T score* Numbers are presented as mean (standard deviation in parenthesis) for numerical variables and frequency (percentage in parenthesis) for categorical variables.Totally, 518 participants were diagnosed in osteoporotic range in hip area and 1036 participants in the lumbar area. T-score classifications are presented in Table  2 . Major discordance was observed in BMD results of 115 (2.7%) participants. Minor discordance was observed in 1631 (38.9%) participants and T-score categories of two measurement sites in other 2442 (58.3%) participants were not different. Distribution and pattern of this variable in different genders is depicted in Table  3 .Classification of T scores according to WHO criteria in different sites*Lumbar spineTotal hipNo.%95% Confidence IntervalsNo.%95% Confidence IntervalsOsteoporosis (T = -2.5)Osteopenia (-2.5 < T = -1)Normal (T > -1)Distribution of diagnostic discordances according to WHO criteria in different genders*Major T-score Discordance7 (2.1)108 (2.8)115 (2.7)Minor T-score Discordance117 (34.4)1514 (39.3)1631 (38.9)T-score Concordance216 (63.5)2226 (57.8)2442 (58.3)* Numbers are presented as frequency (percentage in parenthesis).T-score discordance was more prevalent in women than men (42.2% versus 36.5%, P = 0.042). The mean age of participants with discordance (54.8 years) was higher than the other group (52.5 years, P < 0.001). In 3848 female participants, the number of post-menopausal women with diagnostic discordances (951 of 2027) was significantly higher than pre-menopausal participants with discordance (671 of 1821; P < 0.001). In multivariate analysis (Table  4 ), two genders lost their difference in occurrence of discordance. Effects of age and menopause were established with their significant odds ratios. Participants with late menopause (age at menopause > 50) were more likely to show T-score discordances. Obesity defined as BMI over 30 was recognized as a risk factor for major discordance and smoking as a protective factor against minor discordance. Hormone replacement therapy was a significant protector against both.Results of multivariate logistic regression analysis for risk factors of major and minor discordance getting T-score concordance at lumbar and femoral sites as the referenceVariablesMinor DiscordanceMajor DiscordanceGender (female)Age decadeAge group (>65 years)Corticosteroid useBody Mass Index (>30 kg/cm 2 )History of osteoporotic fractureSmokingMenopauseHormone Replacement TherapyAge at menarche (> 13 years)Age at menopause (> 50 years)* indicates significant odds ratio. Numbers are presented as odds ratio (95% confidence intervals in parentheses).Discussion This study reveals that, using WHO criteria for definition of osteoporosis and osteopenia, a significant fraction of patients (41.7% in this study) would show T-score discordance between hip and spine sites. Most of these discordances (38.9%) are from minor category, presenting difference on only one class, and could be due to minor variation in BMD techniques or some minor physiologic dissimilarity. Minor discordance generally does not influence the overall prognosis of patients; however, in the case of patients with one site normal and the other osteopenic, follow up of patients with hip osteopenia seems reasonable [ 7 ]. The multivariate analysis we have implemented to the data could aid clinicians and diagnosticians to approach patients with different characteristics. According to our results, BMD measurement in both sites is necessary at least for older patients and post-menopausal women especially those with delay in menopause. Hormone replacement therapy, however, could decrease the diagnostic discordance and patients receiving estrogen and progesterone are more likely to have similar results in DXA scans of lumbar and femoral areas. This could be the result of drug effects on the BMD of lumber area [ 10 ]. Generally, five different causes have been proposed for occurrence of discordance [ 5 ]. Physiologic discordance is related to the skeleton's natural adaptive reaction to normal external and internal factors and forces. An example of this type of discordance is the difference observed between the dominant and non-dominant total hip. Pathophysiologic discordance is seen secondary to a disease. Common examples include vertebral osteophytosis, vertebral end plate and facet sclerosis, osteochondrosis, and aortic calcification. Anatomic discordance is owing to differences in the composition of bone envelopes tested. An example is the difference in T-scores found for the PA lumbar spine and the supine lateral lumbar spine in the same patient. Artifactual discordance occurs when dense synthetic substances (such as metal from zipper, coin, clip, etc) are within the field of region of interest of the test. And finally, technical discordance occurs when the technician improperly positions the patient for the test or the hardware or software used to acquire the test data is out of order. Major discordance was observed in 2.7% of our participants, which is in agreement with the results of similar studies. In both major and minor discordances, lower BMD for lumbar spine was more prevalent. This could be due to several reasons. The difference between velocities of bone loss in different parts of human body could be the main reason [ 11 ]. Trabecular bones (typical of lumbar area) are known to have a more rapid rate of deprivation in early post-menopausal state in comparison to cortical bone (typical of proximal femur) [ 12 ]. Moreover, most of the etiologies of the secondary osteoporosis (such as glucocorticoid excess, hyperthyroidism, malabsorption, liver disease, rheumatoid arthritis, and medications) first affect spinal column [ 13 ]. This will lead to higher prevalence of lumbar osteoporosis. In addition, weight bearing is a known cause of physiologic dissimilarity, which can cause rise in bone density especially in the hip and femur regions [ 14 ]. This mechanism could be the reason of more major T-score discordances observed by increment of BMI in this study. In 30% of our participants, the lumbar T-score was higher than hip T-score and this culminated in poorer hip diagnoses in 9.2% of participants. This phenomenon could be regarded as 'inverse discordance' and several factors may be involved in its occurrence. One of these reasons is the prevalent vitamin D deficiency in our participants. A recent nationwide study with random sampling from five major cities in Iran reported a high prevalence (about 80%) for vitamin D deficiency in Iranian population [ 15 ]. Other studies have confirmed this finding [ 16 , 17 ]. Basic studies have revealed that decrease in serum concentrations of vitamin D by means of raising serum parathyroid hormone (PTH) would induce reduction in density of cortical bones and may have a supportive role for density of trabecular bones [ 18 ]. The other reason for 'inverse discordance' could be due to other diseases such as minor compression fractures in lumbar area, joint sclerosis, and aortic calcification [ 19 , 20 ]. These ailments can induce errors in the estimation of lumbar BMD and falsely higher values. The observation of 'inverse discordance' could not be regarded as a direct influence of more significant bone loss in femoral region. A known phenomenon named 'birth cohort effect' can play a role [ 21 ]. This indicates that, in the particular section the data have been gathered, a specific observed finding could not be interpreted for the effects of age and time passing. In this study, the reason for lower femoral BMD can be insufficient bone gain during puberty in this area. Latest findings indicates that peak bone mass of Iranian population are about 5% lower than that of western population [ 22 , 23 ]. Decreased bone density in hip region could lead to start of bone loss from lower amounts in older ages and post-menopausal states. This can lead to femoral osteoporosis without significant decrease in lumbar BMD. This study, as every other cross-sectional study, has a number of limitations. We could not rule out the possibility of referral bias for this study. As the study was performed in a referral center affiliated to a teaching hospital, the assumption of similarity of study population to exact community is not reasonable and we could not generalize the results to the Iranian population. The other limitation is the choice of multivariate analysis used in this study. With the current analysis, prediction of the presence or absence of T-score discordances is possible. However, prediction of the situation of one site according to results of the other site or choosing one site to measure BMD need further evaluations and analyses which was behind the scope of this study. Future studies using more powerful statistical analyses with larger sample sizes are needed to establish these imperative questions. The importance of existing discordance on the prognosis and fracture risk of patients needs further prognostic studies with long follow-up designs. The high prevalence of T-score discordance could induce some problems for the physicians in decision-making regarding these patients. In general, high prevalence of discordance in this study and similar studies suggests some defects in the cut-off values for definition of osteoporosis and osteopenia proposed with the WHO [ 5 ]. To eliminate this problem, further studies to re-calculate ranges for definition of these diagnoses (considering diagnostic and therapeutic necessities) seem to be needed.
Discussion
This study reveals that, using WHO criteria for definition of osteoporosis and osteopenia, a significant fraction of patients (41.7% in this study) would show T-score discordance between hip and spine sites. Most of these discordances (38.9%) are from minor category, presenting difference on only one class, and could be due to minor variation in BMD techniques or some minor physiologic dissimilarity. Minor discordance generally does not influence the overall prognosis of patients; however, in the case of patients with one site normal and the other osteopenic, follow up of patients with hip osteopenia seems reasonable [ 7 ].The multivariate analysis we have implemented to the data could aid clinicians and diagnosticians to approach patients with different characteristics. According to our results, BMD measurement in both sites is necessary at least for older patients and post-menopausal women especially those with delay in menopause. Hormone replacement therapy, however, could decrease the diagnostic discordance and patients receiving estrogen and progesterone are more likely to have similar results in DXA scans of lumbar and femoral areas. This could be the result of drug effects on the BMD of lumber area [ 10 ].Generally, five different causes have been proposed for occurrence of discordance [ 5 ]. Physiologic discordance is related to the skeleton's natural adaptive reaction to normal external and internal factors and forces. An example of this type of discordance is the difference observed between the dominant and non-dominant total hip. Pathophysiologic discordance is seen secondary to a disease. Common examples include vertebral osteophytosis, vertebral end plate and facet sclerosis, osteochondrosis, and aortic calcification. Anatomic discordance is owing to differences in the composition of bone envelopes tested. An example is the difference in T-scores found for the PA lumbar spine and the supine lateral lumbar spine in the same patient. Artifactual discordance occurs when dense synthetic substances (such as metal from zipper, coin, clip, etc) are within the field of region of interest of the test. And finally, technical discordance occurs when the technician improperly positions the patient for the test or the hardware or software used to acquire the test data is out of order.Major discordance was observed in 2.7% of our participants, which is in agreement with the results of similar studies. In both major and minor discordances, lower BMD for lumbar spine was more prevalent. This could be due to several reasons. The difference between velocities of bone loss in different parts of human body could be the main reason [ 11 ]. Trabecular bones (typical of lumbar area) are known to have a more rapid rate of deprivation in early post-menopausal state in comparison to cortical bone (typical of proximal femur) [ 12 ]. Moreover, most of the etiologies of the secondary osteoporosis (such as glucocorticoid excess, hyperthyroidism, malabsorption, liver disease, rheumatoid arthritis, and medications) first affect spinal column [ 13 ]. This will lead to higher prevalence of lumbar osteoporosis. In addition, weight bearing is a known cause of physiologic dissimilarity, which can cause rise in bone density especially in the hip and femur regions [ 14 ]. This mechanism could be the reason of more major T-score discordances observed by increment of BMI in this study.In 30% of our participants, the lumbar T-score was higher than hip T-score and this culminated in poorer hip diagnoses in 9.2% of participants. This phenomenon could be regarded as 'inverse discordance' and several factors may be involved in its occurrence. One of these reasons is the prevalent vitamin D deficiency in our participants. A recent nationwide study with random sampling from five major cities in Iran reported a high prevalence (about 80%) for vitamin D deficiency in Iranian population [ 15 ]. Other studies have confirmed this finding [ 16 , 17 ]. Basic studies have revealed that decrease in serum concentrations of vitamin D by means of raising serum parathyroid hormone (PTH) would induce reduction in density of cortical bones and may have a supportive role for density of trabecular bones [ 18 ]. The other reason for 'inverse discordance' could be due to other diseases such as minor compression fractures in lumbar area, joint sclerosis, and aortic calcification [ 19 , 20 ]. These ailments can induce errors in the estimation of lumbar BMD and falsely higher values.The observation of 'inverse discordance' could not be regarded as a direct influence of more significant bone loss in femoral region. A known phenomenon named 'birth cohort effect' can play a role [ 21 ]. This indicates that, in the particular section the data have been gathered, a specific observed finding could not be interpreted for the effects of age and time passing. In this study, the reason for lower femoral BMD can be insufficient bone gain during puberty in this area. Latest findings indicates that peak bone mass of Iranian population are about 5% lower than that of western population [ 22 , 23 ]. Decreased bone density in hip region could lead to start of bone loss from lower amounts in older ages and post-menopausal states. This can lead to femoral osteoporosis without significant decrease in lumbar BMD.This study, as every other cross-sectional study, has a number of limitations. We could not rule out the possibility of referral bias for this study. As the study was performed in a referral center affiliated to a teaching hospital, the assumption of similarity of study population to exact community is not reasonable and we could not generalize the results to the Iranian population. The other limitation is the choice of multivariate analysis used in this study. With the current analysis, prediction of the presence or absence of T-score discordances is possible. However, prediction of the situation of one site according to results of the other site or choosing one site to measure BMD need further evaluations and analyses which was behind the scope of this study. Future studies using more powerful statistical analyses with larger sample sizes are needed to establish these imperative questions.The importance of existing discordance on the prognosis and fracture risk of patients needs further prognostic studies with long follow-up designs. The high prevalence of T-score discordance could induce some problems for the physicians in decision-making regarding these patients. In general, high prevalence of discordance in this study and similar studies suggests some defects in the cut-off values for definition of osteoporosis and osteopenia proposed with the WHO [ 5 ]. To eliminate this problem, further studies to re-calculate ranges for definition of these diagnoses (considering diagnostic and therapeutic necessities) seem to be needed.Conclusion In summary, this study indicates that about 40% of participants evaluated for bone density changes in a referral center may show diagnostic discordance, majority of them from minor class. This phenomenon should be regarded as a real and prevalent finding and physicians should become familiar with this topic. Clinicians should look for possible cause or causes of this occurrence and develop a particular strategy approaching to these patients.
Conclusion
In summary, this study indicates that about 40% of participants evaluated for bone density changes in a referral center may show diagnostic discordance, majority of them from minor class. This phenomenon should be regarded as a real and prevalent finding and physicians should become familiar with this topic. Clinicians should look for possible cause or causes of this occurrence and develop a particular strategy approaching to these patients.Competing interests This study was supported by a grant from Endocrinology & Metabolism Research Center of Tehran University of Medical Sciences.
Competing interests
This study was supported by a grant from Endocrinology & Metabolism Research Center of Tehran University of Medical Sciences.Authors' contributions In advance, suggestion of the design of the study was from AS. Data extraction and initial analysis were done by NKT and AH. AM performed additional analyses and wrote the first draft of the paper. AS and BL both had helpful and valuable comments in revising the paper. All authors read and approved the final manuscript.
Authors' contributions
In advance, suggestion of the design of the study was from AS. Data extraction and initial analysis were done by NKT and AH. AM performed additional analyses and wrote the first draft of the paper. AS and BL both had helpful and valuable comments in revising the paper. All authors read and approved the final manuscript.Pre-publication history The pre-publication history for this paper can be accessed here:
Pre-publication history
The pre-publication history for this paper can be accessed here: