PEER REVIEW HISTORY BMJ Open publishes all reviews undertaken for accepted manuscripts. Reviewers are asked to complete a checklist review form (http://bmjopen.bmj.com/site/about/resources/checklist.pdf) and are provided with free text boxes to elaborate on their assessment. These free text comments are reproduced below. ARTICLE DETAILS TITLE (PROVISIONAL) AUTHORS Multimorbidity prevalence and pattern in Indonesian adults: an exploratory study using national survey data Hussain, Mohammad; Huxley, Rachel; Mamun, Abdullah VERSION 1 - REVIEW REVIEWER Marjan van den Akker, Associate professor Maastricht University, School CAPHRI, dept of Family Medicine, Maastricht, the Netherlands / KU Leuven, dept of General Practice, Leuven Belgium 08-Sep-2015 Thank you for giving me the opportunity to review this interesting manuscript, concerning the multimorbidity prevalence and patterns in Indonesia. Multimorbidity has been studied rather extensively in high-income countries during the last decades. Only recently, more information is coming available from low en middle-income countries. As such, this manuscript describes a timely study. The authors refer to this in their introduction, stating this is in part due to the significance of the problem within the developed countries. I m not sure what is meant by this, because it obviously is also a significant problem in developing countries. Authors provide a clear description of their measurements. I wonder, though, whether there are many false positives for hypertension, which can be based on a single measurement? This could also explain the very high prevalence of hypertension in the study population (up to 69.8% in women older than 60 years).which proportion of the study population categorized as having hypertension also received anti-hypertensive medication? Regarding the discussion, I recognize the difficulties to compare the results with other multimorbidity studies, due to methodological differences, but it would also be helpful to compare the prevalence estimates of the separate chronic conditions with those reported in the region. This could help to validate the estimated point prevalences. REVIEWER Amaia Calderón-Larrañaga Aging Research Center - Karolinska Institutet, Sweden 09-Sep-2015 This work provides an epidemiologic insight of the prevalence of
multimorbidity in a developing country undergoing a deep epidemiologic transition. The paper is well written and the analyses seem to be rigorous, but still some issues call for further consideration by the authors. Introduction: -The authors justify their study on the grounds of the need for an effective and high-quality primary care in Indonesia. Indeed, a generalist primary care approach has been shown to assure continuity and coordination of care for patients with multimorbidity. It would be helpful if the authors could briefly describe the structure of Indonesia's health system, with a specific focus on the situation of the primary level of care. Methods: -The authors end up with a sample of 9,438 people out the 44,103 recruited in IFLS-4 (21.4%). It would be very useful if they could provide a flowchart indicating those patients that were excluded in each step. Also, they should compare the characteristics of the actual >40 years study population with the initial >40 years sample to discard selection bias. -The use of the complete case analysis (i.e. only those subjects with complete records are used for inference) has shown to have many limitations (e.g. loss of substantial information and statistical power, bias when the missing data process is related to the measurement process, etc.). The authors should justify why they discarded alternative methodologies (e.g. multiple imputation techniques) ideally by means of a sensitivity analysis. -The authors did not check for plausible interactions among variables. This could offer further insight into other variables, apart from age and sex, by which tables and figures could/should be stratified. It would moreover ensure the robustness of the regression model. Results: -In my opinion, Supplementary files S1 and S2 seem more important that Table 1 since they describe the distribution of the number of chronic conditions and of multimorbidity, which is a central aspect of the paper. I suggest authors try to merge all three tables into a bigger one. Eventually, the distribution of socio-demographic characteristics in men and women (now shown in Table 1) could be deleted. -The title of Supp. Fig 1 is: Marginal plots showing linear prediction for mean number of morbidities and probability of multimorbidity with 95% CI across age groups. Is the prediction of the probability of multimorbidity also based on a linear function? Discussion: -Given that one of the aims of the article is to enlighten health policy makers on the prevalence of the main chronic conditions contributing to Indonesia s high disease burden, I miss some discussion regarding how their numbers relate to data from other official sources, or from other comparable countries. -I also miss further discussion on the impact of the findings for health policy in Indonesia. If providing a better and more accessible primary care is one of the key solutions to face the increasing burden of chronic diseases and multimorbidity (as the authors state in the introduction), then they need to better justify this in the context of available evidence. -The authors state that the fact that there is no dominant
combination of morbid conditions is challenging from a public health perspective as most of the dyads and triads of morbid conditions will require a unique framework for the treatment and management of the conditions. I think this statement collides with the idea of a comprehensive approach inherent to primary care, which is precisely what the authors claim for in the present study. -The observed to-expected ratios used in this study to analyse multimorbidity patterns, apart from the technical difficulties implicit to the extraordinary numbers of theoretically possible combinations of diseases, depend on the prevalence of the individual diseases and do not adequately adjust for chance multimorbidity when nonrandom multimorbidity exists. This limitation is further discussed in reference 32 (Prados et al, JCE), and the authors might want to include it the paper. -The authors state the following: Hypertension was almost integral to all patterns of multimorbidity at all ages indicating that effective interventions to reduce mean population blood pressure are likely to yield substantial benefits in terms of the burden of multimorbidity in Indonesia. Results from this study do not support this speculative statement. VERSION 1 AUTHOR RESPONSE Reviewer: 1 Reviewer s comment: 1. Thank you for giving me the opportunity to review this interesting manuscript, concerning the multimorbidity prevalence and patterns in Indonesia. Multimorbidity has been studied rather extensively in high-income countries during the last decades. Only recently, more information is coming available from low en middle-income countries. As such, this manuscript describes a timely study. The authors refer to this in their introduction, stating this is in part due to the significance of the problem within the developed countries. I m not sure what is meant by this, because it obviously is also a significant problem in developing countries. Author's response and changes in the paper: Thank you. We agree with reviewer s concern that multimorbidity is obviously a significant problem in developing countries as well and have amended the introduction to reflect this. Changes in the paper: Previously, the study of the burden of multimorbidity has largely been confined to developed countries due to the availability of relevant data with which to examine this issue. But, there is increasing recognition that the burden of multimorbidity is of increasing importance to populations in lower and middle-income countries. Historically, the pattern of mortality in these countries has largely been dominated by communicable diseases; But, substantive successes in public health over the past several decades in these countries has led not only to marked gains in life expectancy but an increase in the prevalence of chronic conditions placing additional strain on healthcare systems that are ill-equipped for coping with the growing widespread demand for chronic disease care. Reviewer's comment 2: Authors provide a clear description of their measurements. I wonder, though, whether there are many false positives for hypertension, which can be based on a single measurement? This could also explain the very high prevalence of hypertension in the study population (up to 69.8% in women older than 60 years).which proportion of the study population categorized as having hypertension also received anti-hypertensive medication? Author's response and changes in the paper:
Thank you for pointing this out and we apologise for the confusion. Blood pressure measurements were measured three times and averaged. High blood pressure was defined based on the mean values for systolic and diastolic pressure. Thus, the chance of bias is less. This has been updated in the methods section [measurements- Three blood pressure (BP) measurements were obtained using self-inflating sphygmomanometers with a digital read-out and total cholesterol was measured using CardiochekPA system ] Hypertensive status was ascertained based on self-report and the mean blood pressure value of the three measurements. Respondents were classified as hypertensive if they met the JNC VII criteria of having a mean systolic blood pressure (SBP) 140 mmhg and/or mean diastolic blood pressure (DBP) 90 mmhg, or currently taking hypertension medication. Only 25.7% of the study population (19.9% men and 30.2% women) who were hypertensive also received anti-hypertensive medication (Unpublished data) Reviewer's comment 3: Regarding the discussion, I recognize the difficulties to compare the results with other multimorbidity studies, due to methodological differences, but it would also be helpful to compare the prevalence estimates of the separate chronic conditions with those reported in the region. This could help to validate the estimated point prevalences. Author s response and changes in the paper: Thank you. As the main objective of the study was to estimate the burden of multimorbidity we had limited our discussion to multimorbidity only rather than focusing on the individual prevalence of chronic conditions (which are shown in the tables in the paper). Comparing prevalence estimates for each of the individual chronic conditions across countries in the region is beyond the scope of this paper. However, in a previous publication we have examined the sex-specific prevalence of 5 major chronic disease risk factors including hypertension, hypercholesterolaemia, diabetes and obesity between 10 countries in the region (that did not include Indonesia) and our current findings in terms of the prevalence of these conditions in the Indonesian adult population are comparable with those reported in this review article (Huxley et al. Circulation Journal 2015). Reviewer -2 1. Introduction: -The authors justify their study on the grounds of the need for an effective and high-quality primary care in Indonesia. Indeed, a generalist primary care approach has been shown to assure continuity and coordination of care for patients with multimorbidity. It would be helpful if the authors could briefly describe the structure of Indonesia's health system, with a specific focus on the situation of the primary level of care. Author s response and changes in the paper: Thank you. As suggested we have added a brief discussion about the health care delivery system in Indonesia in introduction. Additionally we have incorporated the implications of the study results in the Indonesian context especially in the discussion section. The last paragraph of introduction section now read as follows: Although Indonesia has an extensive primary health care structure that is largely delivered through a network of community health centres (Puskesmas), auxiliary health centres (Pustu) and private medical practice, recent evidence suggests that the country has limited capacity in its public health system to cope with any further increases in health-care demand. The purpose of the current study is therefore to inform on the prevalence, patterns and risk factors associated with multimorbidity in the Indonesian population; such information is a vital pre-requisite for the design and implementation of an effective primary health care system that is capable of delivering a comprehensive continuum of
care to patients with multiple morbidities. Reviewer's comment 2: Methods: The authors end up with a sample of 9,438 people out the 44,103 recruited in IFLS-4 (21.4%). It would be very useful if they could provide a flowchart indicating those patients that were excluded in each step. Also, they should compare the characteristics of the actual >40 years study population with the initial >40 years sample to discard selection bias. Author's response and changes in the paper: We have added a new figure (Figure-1), a flowchart showing the inclusion of participants. Additionally, we have added the following text to the result section to describe the selection of study subjects and the comparison between complete cases and incomplete cases. Participant s characteristics Of 11712 participants aged 40 years or over interviewed in the survey, 2014 (17.5%) did not have complete information related to all chronic diseases and thus they were excluded from further analysis (Figure 1). We analysed data from 9438 (51.6% women) respondents for whom complete information on all included chronic diseases were available. The respondents with complete information were on average three years younger than those with incomplete information (54.1 years vs. 57.2 years; p<0.001). Participants with complete information were more likely to be female (AOR: 1.2; 95% CI: 1.1-1.4), currently married (AOR: 1.3; 1.1-1.5), high school or above educated (AOR: 1.3; 1.2-1.5), from rural area (AOR: 1.1; 1.0-1.2), and of Javanese ethnicity (AOR: 1.1; 1.0-1.3). However, respondents with complete information did not differ significantly from those with incomplete information in terms of per-capita expenditure. Reviewer's comment 3: The use of the complete case analysis (i.e. only those subjects with complete records are used for inference) has shown to have many limitations (e.g. loss of substantial information and statistical power, bias when the missing data process is related to the measurement process, etc.). The authors should justify why they discarded alternative methodologies (e.g. multiple imputation techniques) ideally by means of a sensitivity analysis. Author's Response: We agree with the reviewer that the use of complete case analysis has been shown to be a limitation and produces biased estimates if the excluded individuals are systematically different from those included. We re-analysed our data using inverse probability weighted (IPW) method and complete cases were weighted by the inverse of their probability of being a complete case. IPW method provides results similar to multiple imputation (MI) method provided the missingness model in IPW is correctly specified. In this case the missingness model was a good fit (Hosmer-Lemeshow goodnessof-fit test value =7.64; p-value >0.4). The revised estimates were similar to the estimates obtained previously except for changes in decimal places and thus figures in the tables remain unchanged. We have added the following text to the methods and discussion section For analysis involving complete cases only we used inverse probability weighted method and complete cases are weighted by the inverse of their probability of being a complete case. We performed a complete case analysis which has the potential to introduce attrition bias. However, we used inverse probability weighted method to directly analyse only the complete cases with special weights assigned to those cases based on estimated probabilities of completeness, thereby minimising the possibility of attrition bias. Moreover, the prevalence of individual diseases did not vary significantly across participants with complete and incomplete information..
Reviewer's comment 4: The authors did not check for plausible interactions among variables. This could offer further insight into other variables, apart from age and sex, by which tables and figures could/should be stratified. It would moreover ensure the robustness of the regression model. Author's Response: Thank You. We have checked the possible interaction of other variables such as education and percapita expenditure; however, the interaction term was not statistically significant in the model and thus removed from the final model. Reviewer's comment 5: 5. Results: In my opinion, Supplementary files S1 and S2 seem more important that Table 1 since they describe the distribution of the number of chronic conditions and of multimorbidity, which is a central aspect of the paper. I suggest authors try to merge all three tables into a bigger one. Eventually, the distribution of socio-demographic characteristics in men and women (now shown in Table 1) could be deleted. As per reviewer s suggestion we have prepared the revised table combining supplementary files S1 and S2 and Table -1 from the previous version of the manuscript is now placed in the supplementary file. Reviewer's comment 6: The title of Supp. Fig 1 is: Marginal plots showing linear prediction for mean number of morbidities and probability of multimorbidity with 95% CI across age groups. Is the prediction of the probability of multimorbidity also based on a linear function? The prediction of multimorbidity is based on logistic regression. Reviewer's comment 7: Discussion: Given that one of the aims of the article is to enlighten health policy makers on the prevalence of the main chronic conditions contributing to Indonesia s high disease burden, I miss some discussion regarding how their numbers relate to data from other official sources, or from other comparable countries. Please see response to Reviewer-1, Point-1 Reviewer's comment 8: I also miss further discussion on the impact of the findings for health policy in Indonesia. If providing a better and more accessible primary care is one of the key solutions to face the increasing burden of chronic diseases and multimorbidity (as the authors state in the introduction), then they need to better justify this in the context of available evidence. Thank you. We have added a brief discussion on the implication of this study in Indonesian context in the last paragraph of the discussion section. Reviewer's comment 9: The authors state that the fact that there is no dominant combination of morbid conditions is
challenging from a public health perspective as most of the dyads and triads of morbid conditions will require a unique framework for the treatment and management of the conditions. I think this statement collides with the idea of a comprehensive approach inherent to primary care, which is precisely what the authors claim for in the present study. We agree with the reviewer that a comprehensive approach is needed for management of patients with multimorbidity. We apologise for any confusion and have rephrased the statement to read as follows: From a public health perspective, this is challenging and requires a development of comprehensive and contextualized clinical practice guidelines offering clinical management and treatment decision support for patients with multiple chronic diseases. Reviewer's comment 10: The observed to-expected ratios used in this study to analyse multimorbidity patterns, apart from the technical difficulties implicit to the extraordinary numbers of theoretically possible combinations of diseases, depend on the prevalence of the individual diseases and do not adequately adjust for chance multimorbidity when nonrandom multimorbidity exists. This limitation is further discussed in reference 32 (Prados et al, JCE), and the authors might want to include it the paper. Author's response; Thanks for your suggestion. We have added this at the end of the limitation paragraph in the discussion section: Lastly, we used observed-to-expected ratios to analyse patterns of multimorbidity, which apart from the technical difficulties implicit to the extraordinary numbers of theoretically possible combinations of diseases, depend on the prevalence of the individual diseases and do not adequately adjust for chance multimorbidity when non-random multimorbidity exists Reviewer's comment 11: The authors state the following: Hypertension was almost integral to all patterns of multimorbidity at all ages indicating that effective interventions to reduce mean population blood pressure are likely to yield substantial benefits in terms of the burden of multimorbidity in Indonesia. Results from this study do not support this speculative statement. Author's response Thank you. We have revised the sentence to match with the results : the sentence now read as : Hypertension was almost integral to all patterns of multimorbidity at all ages indicating that effective interventions to reduce mean population blood pressure should be given high priority in the Indonesian population. VERSION 2 REVIEW REVIEWER Marjan van den Akker Maastricht University, dept of Family Medicine, School Caphri, the Netherlands 16-Oct-2015 I'm sastisfied by the authors' responses and the changes made in the manuscript.
REVIEWER Amaia Calderón-Larrañaga Aging Research Center - Karolinska Institutet 25-Oct-2015 Most of the comments have been adequately responded by the authors. However, some additional clarification is still needed for the following points: -Comment 6. The title of Supp. Fig 1. As it stands now, it seems as if the prediction of the probability of multimorbidity was also based on a linear function. -Comment 7. As also stated by Reviewer 1, the authors should compare their prevalence numbers of individual conditions with figures from other studies in the same or from comparable countries. This is essential to validate their estimations. Additional comments: -The manuscript needs extensive copy editing. -Make sure that all abbreviations are properly described the first time they appear in the text. -The authors should pay attention to the bibliography. Some sentences lack references while others carry far too many. VERSION 2 AUTHOR RESPONSE Reviewer: 1 Reviewer Name: Marjan van den Akker Institution and Country: Maastricht University, the Netherlands. Please leave your comments for the authors below I'm satisfied by the authors' responses and the changes made in the manuscript. Our Response: Thank you for your valuable comments and feedback. Reviewer: 2 Reviewer Name: Amaia Calderón-Larrañaga Institution and Country: Aging Research Center - Karolinska Institutet Please leave your comments for the authors below Most of the comments have been adequately responded by the authors. However, some additional clarification is still needed for the following points: -Comment 6. The title of Supp. Fig 1. As it stands now, it seems as if the prediction of the probability of multimorbidity was also based on a linear function. Our Response: Yes, the predicted probability of multimorbidity was estimated using a logistic regression. We have added this information in the statistical analysis section of the manuscript for greater clarity. (Page no.7, statistical analysis: 2nd Paragraph) -Comment 7. As also stated by Reviewer 1, the authors should compare their prevalence numbers of individual conditions with figures from other studies in the same or from comparable countries. This is essential to validate their estimations. Our Response: Thank you for this comment. As the main objective of the study was to estimate the
burden of multimorbidity we had purposefully restricted our discussion to multimorbidity rather than describing the individual prevalence of chronic conditions (which are shown in the tables in the paper). Comparing prevalence estimates for each of the individual chronic conditions across countries in the region is beyond the scope of this paper. However, in a previous publication that we have referenced in the Discussion, we did examine the sex-specific prevalence of five major chronic disease risk factors including hypertension, hypercholesterolaemia, diabetes and obesity between 10 Asian countries in the region (although not include Indonesia) and our current findings in terms of the prevalence of these conditions in the Indonesian adult population are comparable with those reported in this review article (Huxley et al. Circulation Journal 2015). (Page no. 13, discussion: 2nd Paragraph) Additional comments: -The manuscript needs extensive copy editing. Our Response: Thank you we have revised the manuscript where necessary and corrected any grammatical errors. Reviewer: Make sure that all abbreviations are properly described the first time they appear in the text. Our response: We have carefully checked the manuscript and made necessary changes where necessary. Reviewer: The authors should pay attention to the bibliography. Some sentences lack references while others carry far too many. Our response: Thank you. We agree and have updated the references as suggested. VERSION 3 REVIEW REVIEWER Amaia Calderón-Larrañaga Aging Research Center - Karolinska Institutet, Sweden 02-Nov-2015 The authors adequately responded to all of my previous comments.