Poor indoor air quality in schools is a major problem in Finland that has increasingly been assessed using questionnaires to parents and pupils on symptoms and indoor air complaints. The fact that other factors beside indoor air quality may influence symptom reporting has, however, been largely neglected in the ongoing discussions also in Finland. Previous research has clearly established that symptoms which accompany indoor air problems are associated with both physical characteristics of the building environment and various psychosocial factors (1–3). The majority of the studies, however, were conducted among adults in office settings (4–6), and very little research was done among pupils in school setting. Our study (7) was conducted to fill this gap and examine whether, in addition to indoor environmental quality (IEQ) in schools, different psychosocial factors and other pupils’ individual and allergic characteristics are associated with symptom reporting.
The main message of our study is the following: where high levels of symptoms are reported, both psychosocial factors and physical characteristics of indoor environment should be fully considered in the decision-making process of the indoor air quality in school buildings. Our paper (7), as well as our previous research (8,9), clearly demonstrates that our current findings cannot be used as a justification for ignoring physical environment in indoor air research. Below we provide our responses to the specific...
Poor indoor air quality in schools is a major problem in Finland that has increasingly been assessed using questionnaires to parents and pupils on symptoms and indoor air complaints. The fact that other factors beside indoor air quality may influence symptom reporting has, however, been largely neglected in the ongoing discussions also in Finland. Previous research has clearly established that symptoms which accompany indoor air problems are associated with both physical characteristics of the building environment and various psychosocial factors (1–3). The majority of the studies, however, were conducted among adults in office settings (4–6), and very little research was done among pupils in school setting. Our study (7) was conducted to fill this gap and examine whether, in addition to indoor environmental quality (IEQ) in schools, different psychosocial factors and other pupils’ individual and allergic characteristics are associated with symptom reporting.
The main message of our study is the following: where high levels of symptoms are reported, both psychosocial factors and physical characteristics of indoor environment should be fully considered in the decision-making process of the indoor air quality in school buildings. Our paper (7), as well as our previous research (8,9), clearly demonstrates that our current findings cannot be used as a justification for ignoring physical environment in indoor air research. Below we provide our responses to the specific comments raised by Tuuminen and colleagues in their commentary to our article.
First, for detailed discussion of the expert evaluation of indoor environmental quality, as well as the discussion of several challenges involved regarding measurement of IEQ, we refer the reader to our previous article (8). The assessment of IEQ in this study was also based on expert evaluation, during which the experts rated the schools based on several criteria previously defined by the Finnish Institute of Occupational Health, such as moisture and mould damage, insufficient ventilation, unsatisfactory temperature conditions, to name just a few. To validate the expert evaluation, several IEQ parameters were further independently assessed by two inspectors in a subsample of schools. At the moment of this study publication, the data only for moisture and mould damage was available, and a substantial agreement between experts’ and inspectors’ evaluations was found. All this information is provided in the Method section of the current article (7, p.3). Also, it was surprising to read from Tuuminen and colleagues that “There is no single mention on what data has been used…”, since the data collection process and the questionnaires are described in detail in both the current (7) and the previous study (8).
Second, Tuuminen and colleagues raised concerns whether small children can reliably “analyse their feelings and attitudes”. In fact, there is repeated evidence that children can assess and report their feelings (e.g., 9,10). We have also shown the good repeatability of children’s questionnaire response, as compared to adults (12). In our study (7), 3-6 grade primary pupils (mean age 10.7), 7-9 grade pupils (mean age 14.2) and parents of primary pupils reported worry about school IEQ, and the result were consistent across the three samples. We additionally examined whether worry reported by primary school pupils is related to respiratory symptoms reported by parents of these primary pupils, and the results were similar to those based on solely primary pupils’ sample. All psychosocial factors (including worry) in the survey were assessed using a 5-point Likert scale, which is a frequently used psychometric tool in behavioural and social sciences.
Third, the response rate of the parents was indeed very low, but this is a common problem with surveys of the present kind. What such low response rate of parents is telling us is that some new strategies are required during survey data collection to achieve adequate response rate (see our previous study for detailed discussion on this issue (8)).
Forth, the associations between IEQ in schools with respiratory, lower respiratory, eye, skin, and general symptoms were shown in our previous article (8), to which we refer Tuuminen and colleagues. The present study (7) focuses only on respiratory symptoms for two reasons: in our previous article (8) we saw the strongest association of IEQ with respiratory symptoms, as many other previous studies, and for the sake of clarity. The present study already includes three samples (i.e., parents of primary school pupils, primary pupils, and secondary pupils), therefore, presenting the results for all symptoms would be an overload for one paper.
Fifth, Tuuminen et al. can found the ethical approval in the ‘Ethical approval’ section at the end of the article (7, p.12).
Sixth, as we have already mentioned in our article (7), as well as extensively discussed before (9), also our study is cross-sectional, and therefore no direction of associations can be stated. The sentence cited by Tuuminen et al. (“Psychosocial factors, especially worry about indoor air quality explained more of the variance between schools in respiratory symptoms than … ”) refers to the fact that the variance between schools in respiratory symptoms was low (0.6%–2.4%) to begin with, which indicates that the bigger share of variance in symptom reporting is explained by individual differences between pupils than school buildings’ characteristics. This is a common use of the word 'explain' in statistics.
Tuuminen and colleagues are further speculating that “worries are more likely to be consequences because usually people cannot be afraid or worried of something if they never knew what to be afraid or worried about”. There is an extensive research on worry and other psychological factors influencing reporting of physical symptoms. At least the following sources should be consulted by anyone interested in the matter (13–15).
Finally, as Tuuminen et al. have correctly pointed out, any misinterpretations of the research findings may be harmful, and we could not agree with this more. Our article highlights the importance of both physical school indoor environment and psychosocial factors in symptom reporting of pupils, which should be considered in the decision-making process of the indoor air quality of school buildings. We tried to write the results, conclusions, and potential implications as clearly and unambiguously as possible, so that any misinterpretation of them would be unlikely.
References
1. Lahtinen M, Huuhtanen P, Reijula K. Sick building syndrome and psychosocial factors – a literature review. Indoor Air. 1998;8:71–80.
2. Lahtinen M, Lappalainen S, Reijula K. Multiprofessional teams resolving indoor-air problems—emphasis on the psychosocial perspective. SJWEH Suppl. 2008;4:30–4.
3. Norbäck D. An update on sick building syndrome. Curr Opin Allergy Clin Immunol. 2009;9:55–9.
4. Marmot AF, Eley J, Stafford M, et al. Building health: an epidemiological study of “sick building syndrome” in the Whitehall II study. Occup Environ Med. 2006;63:283–9.
5. Stenberg B, Eriksson Ni, Höög J, et al. The sick building syndrome (SBS) in office workers. A case-referent study of personal, psychosocial and building-related risk indicators. Int J Epidemiol. 1994;23:1190–7.
6. Eriksson N, Hoog J, Stenberg B, Sundell J. Psychosocial factors and the “sick building-syndrome”. A case-referent study. Indoor Air. 1996;6:101–10.
7. Savelieva K, Elovainio M, Lampi J, et al. Psychosocial factors and indoor environmental quality in respiratory symptom reports of pupils: a cross-sectional study in Finnish schools. BMJ Open. 2020;10:e036873.
8. Savelieva K, Marttila T, Lampi J, et al. Associations between indoor environmental quality in schools and symptom reporting in pupil-administered questionnaires. Environ Heal. 2019;18(1):115.
9. Nissilä J, Savelieva K, Lampi J, et al. Parental worry about indoor air quality and student symptom reporting in primary schools with or without indoor air quality problems. Indoor Air. 2019;29:865–75
10. Chorpita BF, Tracey SA, Brown TA, et al. Assessment of worry in children and adolescents: An adaptation of the Penn State Worry Questionnaire. Behav Res Ther. 1997;35:569–81.
11. Stuijfzand S, Dodd HF. Young children have social worries too: Validation of a brief parent report measure of social worries in children aged 4–8 years. J Anxiety Disord. 2017;50:87–93.
12. Lampi J, Ung-Lanki S, Santalahti P, et al. Test-retest repeatability of child’s respiratory symptoms and perceived indoor air quality – comparing self- and parent-administered questionnaires. BMC Pulm Med. 2018;18:32.
13. Pennebaker JW. Psychological factors influencing the reporting of physical symptoms. In: Stone AA, Bachrach CA, Jobe JB, Kurtzman HS, Cain VS, editors. The science of self-report: Implications for research and practice. Taylor and Francis; 2000. p. 299–315.
14. Davey GC, Wells A (Eds. ). Worry and its psychological disorders: Theory, assessment and treatment. In John Wiley & Sons; 2006.
15. Rief W, Broadbent E. Explaining medically unexplained symptoms–models and mechanisms. Clin Psychol Rev. 2007;27:821–41.
Trend analysis is always fraught with potential confounding. The authors may be unaware that the trends in life expectancy over the same period were also showing unexpected trends, see references in [1]. Even excess winter mortality has been undergoing unexpected fluctuations [1]. Total deaths have also been showing peculiar trends and 2015 in particular showed a very odd increase around the world [2,3]. I have recently suggested that it is the combined and interactive effects of multiple infectious outbreaks .including competition between pathogens which lie behind these unusual trends [4]. This can be inferred but is difficult to establish since most pregnant women are not screened for the presence of multiple pathogens, including seemingly trivial periods of unwellness, but it does suggest an interesting study.
1. Jones R. Excess winter mortality (EWM) and stalling international improvements in life expectancy and mortality rates. Brit J Healthc Manage 2020; 26(12); https://doi.org/10.12968/bjhc.2020.0020
2. Jones R. Austerity in the UK and poor health: were deaths directly affected? Brit J Healthc Manage 2019; 25(11): 337-347.
3. Jones R. Role of social group and gender in outbreaks of a novel agent leading to increased deaths, with insights into higher international deaths in 2015. FGNAMB 2017; 3(1): 1-7. doi: 10.15761/FGNAMB.1000146
4. Jones R. Multidisciplinary insights into health ca...
Trend analysis is always fraught with potential confounding. The authors may be unaware that the trends in life expectancy over the same period were also showing unexpected trends, see references in [1]. Even excess winter mortality has been undergoing unexpected fluctuations [1]. Total deaths have also been showing peculiar trends and 2015 in particular showed a very odd increase around the world [2,3]. I have recently suggested that it is the combined and interactive effects of multiple infectious outbreaks .including competition between pathogens which lie behind these unusual trends [4]. This can be inferred but is difficult to establish since most pregnant women are not screened for the presence of multiple pathogens, including seemingly trivial periods of unwellness, but it does suggest an interesting study.
1. Jones R. Excess winter mortality (EWM) and stalling international improvements in life expectancy and mortality rates. Brit J Healthc Manage 2020; 26(12); https://doi.org/10.12968/bjhc.2020.0020
2. Jones R. Austerity in the UK and poor health: were deaths directly affected? Brit J Healthc Manage 2019; 25(11): 337-347.
3. Jones R. Role of social group and gender in outbreaks of a novel agent leading to increased deaths, with insights into higher international deaths in 2015. FGNAMB 2017; 3(1): 1-7. doi: 10.15761/FGNAMB.1000146
4. Jones R. Multidisciplinary insights into health care financial risk and hospital surge capacity, Part 3: Outbreaks of a new type or kind of disease create unique risk patterns and confounds traditional trend analysis. Journal of Health Care Finance 2021; in press
This study provides an excellent comprehensive overview of unscheduled care use across a wide variety of conditions. The frequency of unscheduled care use by people in their last year of life identified in this study (94.5%) is consistent with our findings examining unscheduled care use in the last year of life by people who go on to die from cancer (1). The rates of unscheduled care use identified in this paper and in our own work are substantially greater than those reported in previous research in this field (2). Previous studies have often focused on A&E-only, rather than taking into account unscheduled care services as a whole, including GP Out-of-Hours services, and have been largely attendance-based rather than cohort-based, making population use estimates less reliable.
The trends emerging from these papers suggests that the magnitude of unscheduled care use in the last year of life is significantly greater than has been previously believed to be the case. This analysis strengthens the case for improved recognition of the substantial role that unscheduled care, particularly GPOOH, plays in meeting community care needs for people with palliative and end of life care needs, and improving resourcing, training and staffing available to in unscheduled care, in order to deliver high-quality palliative and end of life care through all unscheduled care services.
References:
1. Mills SEE, Buchanan D, Guthrie B, Donnan P, Smith BH. Factors affe...
This study provides an excellent comprehensive overview of unscheduled care use across a wide variety of conditions. The frequency of unscheduled care use by people in their last year of life identified in this study (94.5%) is consistent with our findings examining unscheduled care use in the last year of life by people who go on to die from cancer (1). The rates of unscheduled care use identified in this paper and in our own work are substantially greater than those reported in previous research in this field (2). Previous studies have often focused on A&E-only, rather than taking into account unscheduled care services as a whole, including GP Out-of-Hours services, and have been largely attendance-based rather than cohort-based, making population use estimates less reliable.
The trends emerging from these papers suggests that the magnitude of unscheduled care use in the last year of life is significantly greater than has been previously believed to be the case. This analysis strengthens the case for improved recognition of the substantial role that unscheduled care, particularly GPOOH, plays in meeting community care needs for people with palliative and end of life care needs, and improving resourcing, training and staffing available to in unscheduled care, in order to deliver high-quality palliative and end of life care through all unscheduled care services.
References:
1. Mills SEE, Buchanan D, Guthrie B, Donnan P, Smith BH. Factors affecting use of unscheduled care for people with advanced cancer: a retrospective cohort study in Scotland. British Journal of General Practice. 2019;69:e860–8.doi:10.3399/bjgp19X706637
2. Mills, SEE, Geneen LJ, Buchanan D, et al. Factors associated with unscheduled care use by cancer decedents: a systematic review with narrative synthesis. BMJ Supportive & Palliative Care. Published Online: 13 October 2020. doi: 10.1136/bmjspcare-2020-002410
We read with interest the systematic review and meta-analysis by Watts et al. published in BMJ Open [1] which reported on the prevalence of depression and anxiety in women with ovarian cancer at three time-points: pre-treatment, on-treatment and post-treatment. We agree this is an important topic but, after reviewing the article, would like to raise some concerns. We have reproduced the key components of Table 1 from that paper with additional comments to note some potential inaccuracies. Our main concerns are as follows:
First, it appears that the same women have been counted twice in some analyses. The most concerning instance of this relates to the Australian Ovarian Cancer Study, which is by far the largest study with 794 cases with data on depression and anxiety. Women in this study have been double counted (Price 2009 [2] and Price 2010 [3]) in the pre-treatment analysis, then also counted (Price 2009) in the on-treatment analysis, when in practice 79% of women in this study were post-treatment so these data (one or other of the reports) should have been included in the post-treatment analyses only (but they are not). Watts et al. also include two papers (Liavaag 2007 [4] and Liavaag 2009 [5]) from a single study at the Norwegian Radium Hospital and count these women in two separate analyses. Furthermore, they include four papers from a group with study sites in Iowa, Miami and Texas (Lutgendorf 2008 [6], Lutgendorf 2008 [7], Lutgendorf 2009 [8] and Clevenger 2...
We read with interest the systematic review and meta-analysis by Watts et al. published in BMJ Open [1] which reported on the prevalence of depression and anxiety in women with ovarian cancer at three time-points: pre-treatment, on-treatment and post-treatment. We agree this is an important topic but, after reviewing the article, would like to raise some concerns. We have reproduced the key components of Table 1 from that paper with additional comments to note some potential inaccuracies. Our main concerns are as follows:
First, it appears that the same women have been counted twice in some analyses. The most concerning instance of this relates to the Australian Ovarian Cancer Study, which is by far the largest study with 794 cases with data on depression and anxiety. Women in this study have been double counted (Price 2009 [2] and Price 2010 [3]) in the pre-treatment analysis, then also counted (Price 2009) in the on-treatment analysis, when in practice 79% of women in this study were post-treatment so these data (one or other of the reports) should have been included in the post-treatment analyses only (but they are not). Watts et al. also include two papers (Liavaag 2007 [4] and Liavaag 2009 [5]) from a single study at the Norwegian Radium Hospital and count these women in two separate analyses. Furthermore, they include four papers from a group with study sites in Iowa, Miami and Texas (Lutgendorf 2008 [6], Lutgendorf 2008 [7], Lutgendorf 2009 [8] and Clevenger 2013 [9]) and there is likely substantial overlap in the participants included in these papers (Professor Lutgendorf, personal communication).
Second, there appears to be some misclassification of the studies contributing to each analysis of treatment phase. In addition to the misclassification of Price et al. (mentioned above), it appears data from Hipkins 2004 [10] were included in the pre-treatment meta-analysis, when women in this study completed measures at completion of chemotherapy (T1) and 3 months after chemotherapy (T2). Data from Meraner 2004 [11] were also included in the pre-treatment meta-analysis, when baseline data in this study were collected after surgery at first chemotherapy cycle which could be considered on-treatment, particularly for psychological symptoms. Data from Liavaag 2007 [4] were included in the on-treatment analysis, when women in this study were at least 18 months post-diagnosis (n=130 non-relapsed and n=59 relapsed) and thus most would have been post-treatment. Data from Clevenger 2013 [9] were included in the on-treatment analysis, when women in this study completed measures before surgery (T1) and at 6 months (T2) and 1 year after diagnosis (T3) and thus are unlikely to have been on treatment at any time-point. The post-treatment results for depression that were included from Goncalves 2010 [12] are from women who are 3 months post-diagnosis and thus likely to be on-treatment. In contract, data from Goncalves 2008 [13] collected 3 months after cessation of treatment have not been included in the post-treatment analysis despite being available. Furthermore, the results for anxiety and depression on-treatment from this paper appear to have been reversed. Data from Stafford 2010 (corrected year 2011) [14] were included in the on-treatment analysis when only 14% of the 71 women with ovarian cancer were currently receiving treatment at the time of the survey (the remained were post-treatment). Additionally, data for depression from Stafford 2010/11 [14] were omitted from the post-treatment analysis.
Third, there is variation in the thresholds used to classify depression and anxiety (shown in Table 1 linked below).
Notably, data from Price (2009 [2] and 2010 [3]), Goncalves 2010 [12], Bisseling 2009 [15], and Hodgkinson 2007 [16] use the clinical threshold (HADS ≥11), while Liavaag (2007 [4] and 2009 [5]), Goncalves 2008 [13], and Hipkins 2004 [10] have used the subclinical + clinical threshold (HADS ≥8) to define cases and Urbaniec (2011) [17], Sukegawa (2008) [18] and Schulman-Green (2008) [19] use STAI cut-offs of 40, 42 and 48 respectively. Thus the range in the prevalence results between studies reflects, in part, the different thresholds used. Moreover, Sukegawa (2008) [18], Schulman-Green (2008) [19], Meraner (2012) [11], Holzner (2003) [20] and Stafford (2011) [14] only presented means and standard deviations for anxiety and depression. Watts et al. does not specify how they calculated prevalence for these studies nor what thresholds they used in their calculations.
We also noted a number of other minor inaccuracies in Table 1. For example, there are some inaccuracies in reported study size which may have affected the calculated confidence intervals for the prevalence estimates. Furthermore, Urbaniec 2011 [17] only reported anxiety and depression scores from a mix of gynaecological cancer types rather than ovarian cancer specifically with no indication if there were differences by cancer type. On this basis, we suggest this study should not have been included.
These concerns raise questions about the reliability of the prevalence estimates presented. We decided to recalculate the pooled results. To do this, we (a) removed duplicate results (and in Professor Lutgendorf papers where there was likely more than 50% overlap we selected the most recent paper with the most extensive recruitment), (b) reallocated studies to the correct treatment phase as discussed above, (c) used the HADS ≥8 threshold, which is recommended in cancer populations [21] and STAI ≥40 which is most commonly used, [22] and (d) used Z scores to estimate the proportion over the threshold value of interest (HADS=8; STAI=40; CES-D=16) when only means scores were available or a different threshold was used and the mean score was available. We have reproduced Figures 2, Figure 3 and Figure 4 (linked below) from the original paper and estimate that the true pooled estimates for depression prevalence pre-treatment was 47% (CI 42-53%), on-treatment was 29% (CI 25-33%) and post-treatment was 15% (CI 13-17%). For anxiety, the corresponding figures were pre-treatment 54% (CI 45-63%), on-treatment 43% (CI 36-50%) and post-treatment 26% (CI 24-29%). Thus in particular Watts et al’s original estimates for depression pre-treatment (25%; CI 23-28%) and for anxiety pre-treatment (19%; CI 17-21%) and on-treatment (26%; CI 22-31%) appear to be gross underestimates. We suggest our updated pooled estimates are more appropriate reference figures moving forwards.
Yours Sincerely,
Associate Professor Vanessa L Beesley, Population Health Department, QIMR Berghofer Medical Research Institute
Professor Penelope M Webb, Population Health Department, QIMR Berghofer Medical Research Institute
References
1. Watts, S., et al., Depression and anxiety in ovarian cancer: a systematic review and meta-analysis of prevalence rates. BMJ Open, 2015. 5(11): p. e007618-e007618.
2. Price, M.A., et al., Prevalence and predictors of insomnia in women with invasive ovarian cancer: anxiety a major factor. European Journal Of Cancer (Oxford, England: 1990), 2009. 45(18): p. 3262-3270.
3. Price, M.A., et al., Prevalence and predictors of anxiety and depression in women with invasive ovarian cancer and their caregivers. The Medical Journal Of Australia, 2010. 193(5 Suppl): p. S52-S57.
4. Liavaag, A.H., et al., Controlled study of fatigue, quality of life, and somatic and mental morbidity in epithelial ovarian cancer survivors: how lucky are the lucky ones? Journal Of Clinical Oncology: Official Journal Of The American Society Of Clinical Oncology, 2007. 25(15): p. 2049-2056.
5. Liavaag, A.H., et al., Morbidity associated with "self-rated health" in epithelial ovarian cancer survivors. BMC Cancer, 2009. 9: p. 2-2.
6. Lutgendorf, S.K., et al., Interleukin-6, cortisol, and depressive symptoms in ovarian cancer patients. Journal Of Clinical Oncology: Official Journal Of The American Society Of Clinical Oncology, 2008. 26(29): p. 4820-4827.
7. Lutgendorf, S.K., et al., Biobehavioral influences on matrix metalloproteinase expression in ovarian carcinoma. Clinical Cancer Research: An Official Journal Of The American Association For Cancer Research, 2008. 14(21): p. 6839-6846.
8. Lutgendorf, S.K., et al., Depression, social support, and beta-adrenergic transcription control in human ovarian cancer. Brain, Behavior, And Immunity, 2009. 23(2): p. 176-183.
9. Clevenger, L., et al., Sleep disturbance, distress, and quality of life in ovarian cancer patients during the first year after diagnosis. Cancer, 2013. 119(17): p. 3234-3241.
10. Hipkins, J., et al., Social support, anxiety and depression after chemotherapy for ovarian cancer: a prospective study. British Journal Of Health Psychology, 2004. 9(Pt 4): p. 569-581.
11. Meraner, V., et al., Monitoring physical and psychosocial symptom trajectories in ovarian cancer patients receiving chemotherapy. BMC Cancer, 2012. 12: p. 77-77.
12. Gonçalves, V., G. Jayson, and N. Tarrier, A longitudinal investigation of psychological disorders in patients prior and subsequent to a diagnosis of ovarian cancer. Journal Of Clinical Psychology In Medical Settings, 2010. 17(2): p. 167-173.
13. Gonçalves, V., G. Jayson, and N. Tarrier, A longitudinal investigation of psychological morbidity in patients with ovarian cancer. British Journal Of Cancer, 2008. 99(11): p. 1794-1801.
14. Stafford, L. and F. Judd, Long-term quality of life in Australian women previously diagnosed with gynaecologic cancer. Supportive Care In Cancer: Official Journal Of The Multinational Association Of Supportive Care In Cancer, 2011. 19(12): p. 2047-2056.
15. Bisseling, K.C.H.M., et al., Depression, anxiety and body image after treatment for invasive stage one epithelial ovarian cancer. The Australian & New Zealand Journal Of Obstetrics & Gynaecology, 2009. 49(6): p. 660-666.
16. Hodgkinson, K., et al., Long-term survival from gynecologic cancer: Psychosocial outcomes, supportive care needs and positive outcomes. Gynecologic Oncology, 2007. 104(2): p. 381-9.
17. Urbaniec, O.A., et al., Gynecological cancer survivors: assessment of psychological distress and unmet supportive care needs. Journal Of Psychosocial Oncology, 2011. 29(5): p. 534-551.
18. Sukegawa, A., et al., Anxiety and prevalence of psychiatric disorders among patients awaiting surgery for suspected ovarian cancer. The Journal Of Obstetrics And Gynaecology Research, 2008. 34(4): p. 543-551.
19. Schulman-Green, D., et al., Quality of life among women after surgery for ovarian cancer. Palliative & Supportive Care, 2008. 6(3): p. 239-247.
20. Holzner, B., et al., Fatigue in ovarian carcinoma patients: a neglected issue? Cancer, 2003. 97(6): p. 1564-1572.
21. Vodermaier, A. and R.D. Millman, Accuracy of the Hospital Anxiety and Depression Scale as a screening tool in cancer patients: a systematic review and meta-analysis. Supportive Care In Cancer: Official Journal Of The Multinational Association Of Supportive Care In Cancer, 2011. 19(12): p. 1899-1908.
22. Julian, L.J., Measures of anxiety: State-Trait Anxiety Inventory (STAI), Beck Anxiety Inventory (BAI), and Hospital Anxiety and Depression Scale-Anxiety (HADS-A). Arthritis care & research, 2011. 63 Suppl 11: p. S467-S472.
23. Wenzel, L.B., et al., Resilience, reflection, and residual stress in ovarian cancer survivorship: a gynecologic oncology group study. Psychooncology, 2002. 11(2): p. 142-53.
24. Norton, T.R., et al., Prevalence and predictors of psychological distress among women with ovarian cancer. Journal Of Clinical Oncology: Official Journal Of The American Society Of Clinical Oncology, 2004. 22(5): p. 919-926.
25. Parker, P.A., et al., The associations between knowledge, CA125 preoccupation, and distress in women with epithelial ovarian cancer. Gynecologic Oncology, 2006. 100(3): p. 495-500.
26. Costanzo, E.S., et al., Psychosocial factors and interleukin-6 among women with advanced ovarian cancer. Cancer, 2005. 104(2): p. 305-313.
27. Slovacek, L., et al., Screening for depression in survivors of metastatic ovarian cancer in a programme of palliative cancer care. Bratislavske Lekarske Listy, 2009. 110(10): p. 655-659.
Sasidharan et al. conducted a prospective study to examine the risk factors for falls among community-dwelling elderly subjects in India (1). The incidence rate of falls was 31 per 100 person-years. Adjusted odds ratios (ORs) (95% confidence intervals [CIs]) of female sex, movement disorders, arthritis, dependence in basic activities of daily living, not using antihypertensive medications, living alone during daytime, and a history of falls in the previous year for a fall in the following year were 1.48 (1.05 to 2.10), 2.26 (1.00 to 5.05), 1.48 (1.05 to 2.09), 3.49 (2.00 to 6.09), 1.53 (1.10 to 2.13), 3.27 (1.59 to 6.71), and 2.25 (1.60 to 3.15), respectively. I have some concerns about their study.
First, Tripathy et al. reported epidemiological findings of falls among older adults in India (2). The prevalence rate of fall episodes was 67 per 100 person-years. Adjusted OR (95% CI) of female sex, taking four or more medicines, and having poor body balance were 1.6 (1.0 to 2.8), 2.1 (1.2 to 3.5), 1.9 (1.0 to 3.4), respectively. Female sex was also a risk factor for fall in this study, and sex difference for predicting fall in the elderly should be specified by further studies.
Second, Susilowati et al. assessed the prevalence and related factors for falls in the past year in a sample of community-dwelling and institutionalized older Indonesians (3). The prevalence of falls in the past year was 29%, and women and institutionalized older adults had higher preval...
Sasidharan et al. conducted a prospective study to examine the risk factors for falls among community-dwelling elderly subjects in India (1). The incidence rate of falls was 31 per 100 person-years. Adjusted odds ratios (ORs) (95% confidence intervals [CIs]) of female sex, movement disorders, arthritis, dependence in basic activities of daily living, not using antihypertensive medications, living alone during daytime, and a history of falls in the previous year for a fall in the following year were 1.48 (1.05 to 2.10), 2.26 (1.00 to 5.05), 1.48 (1.05 to 2.09), 3.49 (2.00 to 6.09), 1.53 (1.10 to 2.13), 3.27 (1.59 to 6.71), and 2.25 (1.60 to 3.15), respectively. I have some concerns about their study.
First, Tripathy et al. reported epidemiological findings of falls among older adults in India (2). The prevalence rate of fall episodes was 67 per 100 person-years. Adjusted OR (95% CI) of female sex, taking four or more medicines, and having poor body balance were 1.6 (1.0 to 2.8), 2.1 (1.2 to 3.5), 1.9 (1.0 to 3.4), respectively. Female sex was also a risk factor for fall in this study, and sex difference for predicting fall in the elderly should be specified by further studies.
Second, Susilowati et al. assessed the prevalence and related factors for falls in the past year in a sample of community-dwelling and institutionalized older Indonesians (3). The prevalence of falls in the past year was 29%, and women and institutionalized older adults had higher prevalence. The adjusted ORs (95% CIs) of older age, private elderly home setting, and male sex for falls were 1.89 (1.06 to 3.37), 2.04 (1.10 to 3.78), and 0.49 (0.30 to 0.82), respectively. There were some differences in risk factors for falls between community-dwelling and institutionalized older adults, and having a joint disorder or arthritis were risk for falls in the community setting. Living environment might be associated with many socio-economic factors, and risk assessment for falls in the elderly should be made by the combination of psycho-physio-social factors.
Finally, Yeong et al. determined the prevalence and associated factors of falls among community-dwelling elderly in rural Malaysia (4). The prevalence of falls in the past 1 year was 4.07%. Adjusted ORs (95% CIs) of indigenous elderly and living alone for falls were 6.06 (1.10 to 33.55) and 2.60 (1.04 to 6.50), respectively. In contrast, there was no significant association of falls with physical activity level, number of co-morbidities and number of medications used. Compared with other studies, the prevalence of falls was low. I suppose that place of residence might be closely related to the prevalence and risk factors of falls. Anyway, further studies are needed to prevent falls and fractures among elderly subjects.
References
1. Sasidharan DK, Vijayakumar P, Raj M, et al. Incidence and risk factors for falls among community-dwelling elderly subjects on a 1-year follow-up: a prospective cohort study from Ernakulam, Kerala, India. BMJ Open 202030;10(7):e033691.
2. Tripathy NK, Jagnoor J, Patro BK, et al. Epidemiology of falls among older adults: A cross sectional study from Chandigarh, India. Injury 2015;46(9):1801-5.
3. Susilowati IH, Nugraha S, Sabarinah S, et al. Prevalence and risk factors associated with falls among community-dwelling and institutionalized older adults in Indonesia. Malays Fam Physician 2020;15(1):30-38.
4. Yeong UY, Tan SY, Yap JF, et al. Prevalence of falls among community-dwelling elderly and its associated factors: A cross-sectional study in Perak, Malaysia. Malays Fam Physician 2016;11(1):7-14.
We are interested in the recent paper from New Zealand (NZ), describing the experiences of 15 patients with abnormal uterine bleeding, by Claire Henry and others [1]. We agree that abnormal uterine bleeding deserves more attention and have documented the rapid recent increase in endometrial cancer (EC) in NZ Pacifica women [2,3]. However, some of these authors’ statements are not supported by the data they cite. They state “Studies which report on EC prevalence in NZ often link the cause of advanced stage diagnosis to ‘late presentation’...”. For this, they cite one of our studies [2] and another NZ study [4]. However, neither of these papers mentions late presentation, and in another paper which Henry et al. cite [3], we report that Māori and Pacific women did not present with higher grade or stage EC compared to other NZ women. However, both Māori and Pacific women experienced a worse disease-specific survival, which was statistically significant in Pacific women.
More importantly, Henry et al. continue with reference to these studies “… placing women at fault for not having sought more timely medical intervention. We aimed to reframe these deficit narratives....”. We strongly object to these inaccurate claims and the implication that our papers are ‘deficit narratives’ is unacceptable. Nowhere in our papers do we “place women at fault”. We feel strongly that clinicians should be supportive and more alert to sympt...
We are interested in the recent paper from New Zealand (NZ), describing the experiences of 15 patients with abnormal uterine bleeding, by Claire Henry and others [1]. We agree that abnormal uterine bleeding deserves more attention and have documented the rapid recent increase in endometrial cancer (EC) in NZ Pacifica women [2,3]. However, some of these authors’ statements are not supported by the data they cite. They state “Studies which report on EC prevalence in NZ often link the cause of advanced stage diagnosis to ‘late presentation’...”. For this, they cite one of our studies [2] and another NZ study [4]. However, neither of these papers mentions late presentation, and in another paper which Henry et al. cite [3], we report that Māori and Pacific women did not present with higher grade or stage EC compared to other NZ women. However, both Māori and Pacific women experienced a worse disease-specific survival, which was statistically significant in Pacific women.
More importantly, Henry et al. continue with reference to these studies “… placing women at fault for not having sought more timely medical intervention. We aimed to reframe these deficit narratives....”. We strongly object to these inaccurate claims and the implication that our papers are ‘deficit narratives’ is unacceptable. Nowhere in our papers do we “place women at fault”. We feel strongly that clinicians should be supportive and more alert to symptoms and we note; “It has also been suggested that clinicians should be more alert to EC symptoms in obese and/or Pacific women in their normal line of work. Currently, young obese women may not be fully investigated when they present with traditional EC symptoms; however, further investigation of symptoms is now considered mandatory in this group given their high-risk profile” [2].
Abnormal bleeding is difficult to assess and treat and we agree with Henry and her colleagues that some patients may have difficulties in obtaining adequate care. But their study, based on 15 patients, only deals with some of the issues and seems to downplay the efforts being made to improve this situation.
References
(1) Henry C, Jefferies R, Ekeroma A, Filoche S. Beyond the numbers-understanding women's experiences of accessing care for abnormal uterine bleeding (AUB): a qualitative study. BMJ Open 2020; 10(11): e041853.
(2) Scott OW, Tin Tin S, Bigby SM, Elwood JM. Rapid increase in endometrial cancer incidence and ethnic differences in New Zealand. Cancer Causes Control 2019; 30(2): 121-127.
(3) Bigby SM, Tin Tin S, Eva LJ, Shirley P, Dempster-Rivett K, Elwood JM. Increasing incidence of endometrial carcinoma in a high-risk New Zealand community. Aust NZ J Obstet Gynaecol 2020; 60(2): 250-257.
(4) Meredith I, Sarfati D, Ikeda T, Atkinson J, Blakely T. High rates of endometrial cancer among Pacific women in New Zealand: the role of diabetes, physical inactivity, and obesity. Cancer Causes Control 2012; 23(6): 875-885.
Højlund et al. conducted a 1:4 matching case-control study to examine the association between use of second-generation antipsychotics (SGA) and the risk of chronic kidney disease (CKD) (1). They defined CKD as an estimated glomerular filtration rate below 60 mL/min/1.73 m2 for 3 months or more. The adjusted odds ratios (ORs) (95% confidence intervals [CIs]) of ever and current SGA users for the risk of CKD were 1.24(1.12 to 1.37) and 1.26 (1.12 to 1.42), although there was no dose-response relationship. In addition, the adjusted ORs (95% CIs) of short-term and long-term SGA users for the risk of CKD were 1.22 (1.01 to 1.48) and 1.45 (1.19 to 1.76), respectively. Furthermore, clozapine presented the highest risk of CKD, and aripiprazole presented no significant risk of CKD. I have a comment about their study with special reference for the psychiatric diseases.
Wang et al. conducted a risk assessment of CKD between patients with schizophrenia using first and second-generation antipsychotics (2). They defined CKD as a kidney damage as albumin-to-creatinine ratio >30 mg/g or glomerular filtration rate below 60 mL/min/1.73 m2 for 3 months or more. The risks for CKD were significantly higher in patients with SGA, although the risk did not increase as the patients used SGA for longer period. As the information in the risk of CKD in patients with SGA is limited, further studies are recommended by specifying the psychiatric diseases and CKD-related comorbidities.
Højlund et al. conducted a 1:4 matching case-control study to examine the association between use of second-generation antipsychotics (SGA) and the risk of chronic kidney disease (CKD) (1). They defined CKD as an estimated glomerular filtration rate below 60 mL/min/1.73 m2 for 3 months or more. The adjusted odds ratios (ORs) (95% confidence intervals [CIs]) of ever and current SGA users for the risk of CKD were 1.24(1.12 to 1.37) and 1.26 (1.12 to 1.42), although there was no dose-response relationship. In addition, the adjusted ORs (95% CIs) of short-term and long-term SGA users for the risk of CKD were 1.22 (1.01 to 1.48) and 1.45 (1.19 to 1.76), respectively. Furthermore, clozapine presented the highest risk of CKD, and aripiprazole presented no significant risk of CKD. I have a comment about their study with special reference for the psychiatric diseases.
Wang et al. conducted a risk assessment of CKD between patients with schizophrenia using first and second-generation antipsychotics (2). They defined CKD as a kidney damage as albumin-to-creatinine ratio >30 mg/g or glomerular filtration rate below 60 mL/min/1.73 m2 for 3 months or more. The risks for CKD were significantly higher in patients with SGA, although the risk did not increase as the patients used SGA for longer period. As the information in the risk of CKD in patients with SGA is limited, further studies are recommended by specifying the psychiatric diseases and CKD-related comorbidities.
References
1. Højlund M, Lund LC, Herping JLE, Haastrup MB, Damkier P, Henriksen DP. Second-generation antipsychotics and the risk of chronic kidney disease: a population-based case-control study. BMJ Open. 2020 Aug 11;10(8):e038247.
2. Wang HY, Huang CL, Feng IJ, Tsuang HC. Second-generation antipsychotic medications and risk of chronic kidney disease in schizophrenia: population-based nested case-control study. BMJ Open. 2018 May 24;8(5):e019868.
Abbie Lane et al. (1), reported a high level of distress among medical students.
However, in the report 15 students of 161 (9%) expressed a high level of objective stress and the major cause of stress was the exams.
We do not know when the questionnaire was offered to students in relation to the date of their exams. Indeed, before the exams it is normal that a majority of students are stressed and this situation is not specific to medical students. The authors omitted that some stress was necessary and could have positive impact to be competitive. Acute stress was not differentiated from chronic psychological stress which could impact cognitive functions by decreasing the arterial cerebral blood flow related to the persistent increase of high level of plasmatic cortisol (2; 3).
The authors reported that medical students were highly stressed, they thought that it was due to medical studies. Perhaps yes, perhaps no. Maybe this situation is comparable to that of other students of other disciplines or to other young people who are not students. The absence of control group in this study leaves the question unanswered.
In addition, the small number of participants (161), makes the results difficult to analyse. Furthermore, only 15 students had a high level of objective stress. What significance could be attributed to this small subgroup, whereas the authors conclude that medical students had a high level of stress like senior doctors. This conclusion cou...
Abbie Lane et al. (1), reported a high level of distress among medical students.
However, in the report 15 students of 161 (9%) expressed a high level of objective stress and the major cause of stress was the exams.
We do not know when the questionnaire was offered to students in relation to the date of their exams. Indeed, before the exams it is normal that a majority of students are stressed and this situation is not specific to medical students. The authors omitted that some stress was necessary and could have positive impact to be competitive. Acute stress was not differentiated from chronic psychological stress which could impact cognitive functions by decreasing the arterial cerebral blood flow related to the persistent increase of high level of plasmatic cortisol (2; 3).
The authors reported that medical students were highly stressed, they thought that it was due to medical studies. Perhaps yes, perhaps no. Maybe this situation is comparable to that of other students of other disciplines or to other young people who are not students. The absence of control group in this study leaves the question unanswered.
In addition, the small number of participants (161), makes the results difficult to analyse. Furthermore, only 15 students had a high level of objective stress. What significance could be attributed to this small subgroup, whereas the authors conclude that medical students had a high level of stress like senior doctors. This conclusion could not be drawn according the data of this study. Indeed, senior doctors were not investigated in this study.
Finally, we agree that medical studies are stressful because the competition is hard. For example, in France only approximately ten percent of the newly integrated medical students during the first year can pass to the second year. However, this situation is not specific to medical studies and randomized controlled studies are highlighted to evaluate and better manage the stress during medical studies.
References
1. Lane A, McGrath J, Cleary E, Guerandel A, Malone KM. Worried, weary and worn out: mixed-method study of stress and well-being in final-year medical students. BMJ Open. 2020 Dec 10;10(12):e040245. doi: 10.1136/bmjopen-2020-040245. PMID: 33303448.
2. von Dawans B, Strojny J, Domes G. The effects of acute stress and stress hormones on social cognition and behavior: current state of research and future directions. Neurosci Biobehav Rev. 2020 7:S0149-7634(20)30666-7.
3. Lutskyi IS, Evtuchenko SK, Skoromets AA. Mechanisms of chronic stress influence on the brain hemodynamic in persons with employment-related chronic stress. Zh Nevrol Psikhiatr Im S S Korsakova. 2020;120:67-72.
Excellent study on a contemporary topic. If you are able, can I suggest you extend the study to a retrospective analysis of falls and nearness to death. I suspect that falls are one of a composite of indicators which can be used to estimate which persons are in the last year of life.
Jaleel Saunders, Nursing Student University of The Bahamas
Other Contributors:
Terry J Campbell, Lecturer
Dear Editor,
I am a fourth-year nursing student at the University of The Bahamas. I would like to share my views on “Childhood peer status and circulatory disease in adulthood, a prospective cohort study in Stockholm, Sweden.” Circulatory diseases have become somewhat of an epidemic within Bahamian society and your article enlightened me on how childhood peer status may increase the likelihood of circulatory diseases in adulthood. This study can provide some important knowledge to understanding why circulatory diseases like diabetes and hypertension are so prominent within The Bahamas.
This research on childhood experience should not be overlooked as it is quintessential to the development of an adult. Studies imply that childhood socioeconomic circumstances have a strong influence on stomach cancer and are likely to contribute, along with adult circumstances, to lung cancer through cumulative exposure to smoking (Vohra et al., 2015, p. 630). However, as socioeconomics are easily measurable, peer status amongst children is a multifaceted circumstance that one question cannot simply answer. The question used in this research to assess peer status “Whom do you best like working with at school?” can have skewed responses. The answer may have been based on a student wanting to have the best outcome in terms...
Jaleel Saunders, Nursing Student University of The Bahamas
Other Contributors:
Terry J Campbell, Lecturer
Dear Editor,
I am a fourth-year nursing student at the University of The Bahamas. I would like to share my views on “Childhood peer status and circulatory disease in adulthood, a prospective cohort study in Stockholm, Sweden.” Circulatory diseases have become somewhat of an epidemic within Bahamian society and your article enlightened me on how childhood peer status may increase the likelihood of circulatory diseases in adulthood. This study can provide some important knowledge to understanding why circulatory diseases like diabetes and hypertension are so prominent within The Bahamas.
This research on childhood experience should not be overlooked as it is quintessential to the development of an adult. Studies imply that childhood socioeconomic circumstances have a strong influence on stomach cancer and are likely to contribute, along with adult circumstances, to lung cancer through cumulative exposure to smoking (Vohra et al., 2015, p. 630). However, as socioeconomics are easily measurable, peer status amongst children is a multifaceted circumstance that one question cannot simply answer. The question used in this research to assess peer status “Whom do you best like working with at school?” can have skewed responses. The answer may have been based on a student wanting to have the best outcome in terms of a grade. This question could be used to find out who is the smartest amongst the children in that age bracket or grade.
Furthermore, findings from this article indicate an increased susceptibility of marginalized peers for circulatory disease in later life, which is in line with other studies that considered long-term impacts of peer integration (Miething & Almquist, 2020). Nevertheless, it does not consider factors that may lead to children to fall within the lower peer status group. A guide or system for categorization each tier for peer-status amongst children should be made clear to alert teachers and parents to help lift children out of this peer status, decreasing their chances of developing circulatory issues in adulthood.
Although, the article was concise and easy to read I had an issue with the way results were presented in charts. The use of graphs may be a bit easier to understand. Furthermore, the layout of the charts in a vertical view was inconvenient for readers on devices like laptops and mobile phones.
However, overall Miething & Almquist’s evaluation of childhood peer status and its relationship to adulthood circulatory disease is crucial to understanding why persons develop these kinds of diseases. Like they suggested it may be due to socioeconomics, or lower peer status, but the studies show a significant health risk for lower-status children. This should prompt invention from the schools or parents that can identify lower peer status children and give them the help they need.
Sincerely, J. Saunders
References
Miething, A., & Almquist, Y. (2020, September 01). Childhood peer status and circulatory disease in adulthood: A prospective cohort study in Stockholm, Sweden. Retrieved November 22, 2020, from https://bmjopen.bmj.com/content/10/9/e036095
Vohra, J., Marmot, M. G., Bauld, L., Hiatt, R. A., Vohra, J., Marmot, M. G., … Hiatt, R. A. (2016). in adulthood : a rapid-review. 70(6), 629–634.
Poor indoor air quality in schools is a major problem in Finland that has increasingly been assessed using questionnaires to parents and pupils on symptoms and indoor air complaints. The fact that other factors beside indoor air quality may influence symptom reporting has, however, been largely neglected in the ongoing discussions also in Finland. Previous research has clearly established that symptoms which accompany indoor air problems are associated with both physical characteristics of the building environment and various psychosocial factors (1–3). The majority of the studies, however, were conducted among adults in office settings (4–6), and very little research was done among pupils in school setting. Our study (7) was conducted to fill this gap and examine whether, in addition to indoor environmental quality (IEQ) in schools, different psychosocial factors and other pupils’ individual and allergic characteristics are associated with symptom reporting.
The main message of our study is the following: where high levels of symptoms are reported, both psychosocial factors and physical characteristics of indoor environment should be fully considered in the decision-making process of the indoor air quality in school buildings. Our paper (7), as well as our previous research (8,9), clearly demonstrates that our current findings cannot be used as a justification for ignoring physical environment in indoor air research. Below we provide our responses to the specific...
Show MoreTrend analysis is always fraught with potential confounding. The authors may be unaware that the trends in life expectancy over the same period were also showing unexpected trends, see references in [1]. Even excess winter mortality has been undergoing unexpected fluctuations [1]. Total deaths have also been showing peculiar trends and 2015 in particular showed a very odd increase around the world [2,3]. I have recently suggested that it is the combined and interactive effects of multiple infectious outbreaks .including competition between pathogens which lie behind these unusual trends [4]. This can be inferred but is difficult to establish since most pregnant women are not screened for the presence of multiple pathogens, including seemingly trivial periods of unwellness, but it does suggest an interesting study.
1. Jones R. Excess winter mortality (EWM) and stalling international improvements in life expectancy and mortality rates. Brit J Healthc Manage 2020; 26(12); https://doi.org/10.12968/bjhc.2020.0020
2. Jones R. Austerity in the UK and poor health: were deaths directly affected? Brit J Healthc Manage 2019; 25(11): 337-347.
3. Jones R. Role of social group and gender in outbreaks of a novel agent leading to increased deaths, with insights into higher international deaths in 2015. FGNAMB 2017; 3(1): 1-7. doi: 10.15761/FGNAMB.1000146
4. Jones R. Multidisciplinary insights into health ca...
Show MoreThis study provides an excellent comprehensive overview of unscheduled care use across a wide variety of conditions. The frequency of unscheduled care use by people in their last year of life identified in this study (94.5%) is consistent with our findings examining unscheduled care use in the last year of life by people who go on to die from cancer (1). The rates of unscheduled care use identified in this paper and in our own work are substantially greater than those reported in previous research in this field (2). Previous studies have often focused on A&E-only, rather than taking into account unscheduled care services as a whole, including GP Out-of-Hours services, and have been largely attendance-based rather than cohort-based, making population use estimates less reliable.
The trends emerging from these papers suggests that the magnitude of unscheduled care use in the last year of life is significantly greater than has been previously believed to be the case. This analysis strengthens the case for improved recognition of the substantial role that unscheduled care, particularly GPOOH, plays in meeting community care needs for people with palliative and end of life care needs, and improving resourcing, training and staffing available to in unscheduled care, in order to deliver high-quality palliative and end of life care through all unscheduled care services.
References:
Show More1. Mills SEE, Buchanan D, Guthrie B, Donnan P, Smith BH. Factors affe...
We read with interest the systematic review and meta-analysis by Watts et al. published in BMJ Open [1] which reported on the prevalence of depression and anxiety in women with ovarian cancer at three time-points: pre-treatment, on-treatment and post-treatment. We agree this is an important topic but, after reviewing the article, would like to raise some concerns. We have reproduced the key components of Table 1 from that paper with additional comments to note some potential inaccuracies. Our main concerns are as follows:
Show MoreFirst, it appears that the same women have been counted twice in some analyses. The most concerning instance of this relates to the Australian Ovarian Cancer Study, which is by far the largest study with 794 cases with data on depression and anxiety. Women in this study have been double counted (Price 2009 [2] and Price 2010 [3]) in the pre-treatment analysis, then also counted (Price 2009) in the on-treatment analysis, when in practice 79% of women in this study were post-treatment so these data (one or other of the reports) should have been included in the post-treatment analyses only (but they are not). Watts et al. also include two papers (Liavaag 2007 [4] and Liavaag 2009 [5]) from a single study at the Norwegian Radium Hospital and count these women in two separate analyses. Furthermore, they include four papers from a group with study sites in Iowa, Miami and Texas (Lutgendorf 2008 [6], Lutgendorf 2008 [7], Lutgendorf 2009 [8] and Clevenger 2...
Sasidharan et al. conducted a prospective study to examine the risk factors for falls among community-dwelling elderly subjects in India (1). The incidence rate of falls was 31 per 100 person-years. Adjusted odds ratios (ORs) (95% confidence intervals [CIs]) of female sex, movement disorders, arthritis, dependence in basic activities of daily living, not using antihypertensive medications, living alone during daytime, and a history of falls in the previous year for a fall in the following year were 1.48 (1.05 to 2.10), 2.26 (1.00 to 5.05), 1.48 (1.05 to 2.09), 3.49 (2.00 to 6.09), 1.53 (1.10 to 2.13), 3.27 (1.59 to 6.71), and 2.25 (1.60 to 3.15), respectively. I have some concerns about their study.
First, Tripathy et al. reported epidemiological findings of falls among older adults in India (2). The prevalence rate of fall episodes was 67 per 100 person-years. Adjusted OR (95% CI) of female sex, taking four or more medicines, and having poor body balance were 1.6 (1.0 to 2.8), 2.1 (1.2 to 3.5), 1.9 (1.0 to 3.4), respectively. Female sex was also a risk factor for fall in this study, and sex difference for predicting fall in the elderly should be specified by further studies.
Second, Susilowati et al. assessed the prevalence and related factors for falls in the past year in a sample of community-dwelling and institutionalized older Indonesians (3). The prevalence of falls in the past year was 29%, and women and institutionalized older adults had higher preval...
Show More15.12.2020
To the editors, BMJ Open
We are interested in the recent paper from New Zealand (NZ), describing the experiences of 15 patients with abnormal uterine bleeding, by Claire Henry and others [1]. We agree that abnormal uterine bleeding deserves more attention and have documented the rapid recent increase in endometrial cancer (EC) in NZ Pacifica women [2,3]. However, some of these authors’ statements are not supported by the data they cite. They state “Studies which report on EC prevalence in NZ often link the cause of advanced stage diagnosis to ‘late presentation’...”. For this, they cite one of our studies [2] and another NZ study [4]. However, neither of these papers mentions late presentation, and in another paper which Henry et al. cite [3], we report that Māori and Pacific women did not present with higher grade or stage EC compared to other NZ women. However, both Māori and Pacific women experienced a worse disease-specific survival, which was statistically significant in Pacific women.
More importantly, Henry et al. continue with reference to these studies “… placing women at fault for not having sought more timely medical intervention. We aimed to reframe these deficit narratives....”. We strongly object to these inaccurate claims and the implication that our papers are ‘deficit narratives’ is unacceptable. Nowhere in our papers do we “place women at fault”. We feel strongly that clinicians should be supportive and more alert to sympt...
Show MoreHøjlund et al. conducted a 1:4 matching case-control study to examine the association between use of second-generation antipsychotics (SGA) and the risk of chronic kidney disease (CKD) (1). They defined CKD as an estimated glomerular filtration rate below 60 mL/min/1.73 m2 for 3 months or more. The adjusted odds ratios (ORs) (95% confidence intervals [CIs]) of ever and current SGA users for the risk of CKD were 1.24(1.12 to 1.37) and 1.26 (1.12 to 1.42), although there was no dose-response relationship. In addition, the adjusted ORs (95% CIs) of short-term and long-term SGA users for the risk of CKD were 1.22 (1.01 to 1.48) and 1.45 (1.19 to 1.76), respectively. Furthermore, clozapine presented the highest risk of CKD, and aripiprazole presented no significant risk of CKD. I have a comment about their study with special reference for the psychiatric diseases.
Wang et al. conducted a risk assessment of CKD between patients with schizophrenia using first and second-generation antipsychotics (2). They defined CKD as a kidney damage as albumin-to-creatinine ratio >30 mg/g or glomerular filtration rate below 60 mL/min/1.73 m2 for 3 months or more. The risks for CKD were significantly higher in patients with SGA, although the risk did not increase as the patients used SGA for longer period. As the information in the risk of CKD in patients with SGA is limited, further studies are recommended by specifying the psychiatric diseases and CKD-related comorbidities.
R...
Show MoreAbbie Lane et al. (1), reported a high level of distress among medical students.
Show MoreHowever, in the report 15 students of 161 (9%) expressed a high level of objective stress and the major cause of stress was the exams.
We do not know when the questionnaire was offered to students in relation to the date of their exams. Indeed, before the exams it is normal that a majority of students are stressed and this situation is not specific to medical students. The authors omitted that some stress was necessary and could have positive impact to be competitive. Acute stress was not differentiated from chronic psychological stress which could impact cognitive functions by decreasing the arterial cerebral blood flow related to the persistent increase of high level of plasmatic cortisol (2; 3).
The authors reported that medical students were highly stressed, they thought that it was due to medical studies. Perhaps yes, perhaps no. Maybe this situation is comparable to that of other students of other disciplines or to other young people who are not students. The absence of control group in this study leaves the question unanswered.
In addition, the small number of participants (161), makes the results difficult to analyse. Furthermore, only 15 students had a high level of objective stress. What significance could be attributed to this small subgroup, whereas the authors conclude that medical students had a high level of stress like senior doctors. This conclusion cou...
Excellent study on a contemporary topic. If you are able, can I suggest you extend the study to a retrospective analysis of falls and nearness to death. I suspect that falls are one of a composite of indicators which can be used to estimate which persons are in the last year of life.
Jaleel Saunders, Nursing Student University of The Bahamas
Other Contributors:
Terry J Campbell, Lecturer
Dear Editor,
Show MoreI am a fourth-year nursing student at the University of The Bahamas. I would like to share my views on “Childhood peer status and circulatory disease in adulthood, a prospective cohort study in Stockholm, Sweden.” Circulatory diseases have become somewhat of an epidemic within Bahamian society and your article enlightened me on how childhood peer status may increase the likelihood of circulatory diseases in adulthood. This study can provide some important knowledge to understanding why circulatory diseases like diabetes and hypertension are so prominent within The Bahamas.
This research on childhood experience should not be overlooked as it is quintessential to the development of an adult. Studies imply that childhood socioeconomic circumstances have a strong influence on stomach cancer and are likely to contribute, along with adult circumstances, to lung cancer through cumulative exposure to smoking (Vohra et al., 2015, p. 630). However, as socioeconomics are easily measurable, peer status amongst children is a multifaceted circumstance that one question cannot simply answer. The question used in this research to assess peer status “Whom do you best like working with at school?” can have skewed responses. The answer may have been based on a student wanting to have the best outcome in terms...
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