The Spatial Equilibrium Model of Elderly Care Facilities with High Spatiotemporal Sensitivity and Its Economic Associations Study
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThis study attempts to develop a spatial model of elderly care facilities using spatial methods. The interests on spatiotemporal sensitivity by analysing the spatial accessibility rate and supply-demand ratio of the care facilities. This study using spatial methods such as spatial autocorrelation and new geostatistical method, namely geodetector.
However, the novelty of this study is unclear. Although the introduction is sufficient to highlight the importance to model the care facilities due to the aging population issues, the contribution of this study/paper compared to others is not mentioned. the gap they want to addressed whether in the spatial method, the discipline or the context is unclear. What are the research questions that this study attempts to address also not clearly stated in specific paragraph, including the variables/parameter they want to investigate (must put in table so that easy to refer back). line 283.
Please also include in other area outside China, other research that have produce similar methods or models to produce the final model. could be added in the introduction /literature before methodology sections.
this manuscript also use many abbreviations that is not common and not easy to recall such as UCLC where the common abv is land use land cover (LULC) which kind of confusing. Please mention again the full of the abbreviation use particularly in discussion and conclusion section so that readers easy to trace back what is the short form meaning.
this study also mentioned two objectives - the first one is first, to develop a spatial equilibrium model of elderly care facilities with high spatiotemporal sensitivity (SEM-HSTS). (see line 93). so where is the second objective? please state the word 'second objective or next objective' for clarity.
In the analysis of the Spatial Correlations between SEECF and Economic Development, the variables use are GDP and land use - in line 613, you did mention about correlation, but where is the correlation tables, the significant of all land use categories is not there. You did mention in line 615, This also indirectly reflected that the in- 615 the influence of ULUC on SEECF was smaller than that of GDP. (how you drew this conclusion, how from average data you generate the imbalance/balance statement?). the purpose to investigate the SEECF with economic development by using land use categories also need be concluded in lay man sentences, what we can understand from the analysis in the context of study.
This study also write several equations - but not clear whether the equations are developed by the authors or it actually was adopted (if yes, please include the references to the equations).
The tool use in this study to run the equations and to develop the model is not mentioned in the text, so not easy for others to replicate. For example, what is the reference for geodetector so that reader can refer back?
The diagram in Figure 1 need to improve the font size/style.
Table 4 mention the q value- please describe in the texts why is q value? or put reference so that reader can refer back.
and p-value (should be in small letter case). (e.g. line 499). what is LR statistic? please put reference
line 515 and 516 - spacing need to be improved.
please check back the references- some spacing issue between words
Table 1 : what is the basis of the score? is it 5 minutes is still relevant or achievable to get the highest score?
In line 366, the number of physician, doctors and beds is mentioned in the attribute but why is not considered in the equation (line 193)?
line 385- what is the source/reference of standard?
Figure- in the caption, list which figure is accessibility and SEECF.
Figure 5 - Bilisa cluster map? have you mentioned somewhere in the text about bilisa?
Line 587 - about risk- have this being introduced in the text before?
Comments for author File: 
Comments.pdf
Author Response
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Response to Reviewer 1’s Comments Dear Editors and Reviewer, Thank you for your letter and for the reviewer’s comments concerning our manuscript entitled “The Spatial Equilibrium Model of Elderly Care Facilities with High Spatiotemporal Sensitivity and Its Economic Associations Study” (ijgi-3006202). Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our researches. During the past few days, we have considered these comments carefully and highlighted the corresponding modifications in the revised manuscript. Based on these comments and suggestions, we have made careful modifications to the original manuscript, and carefully proof-read the manuscript to minimize typographical and grammatical errors. The reviewer’s comments are laid out below and specific concerns have been numbered. Our response is given in normal font and changes/additions to the manuscript are given in blue text. We believe that the manuscript has been greatly improved and hope it has reached your magazine’s standard. Once again, many thanks for considering possible publication of our manuscript.
List of main corrections:1. In the abstract, we have made revision to highlight the problem that this study aims to address and the contribution compared to other studies, so that the innovativeness of the study is clearer. 2. In the introduction, we have added some literature from the study area abroad, as well as literature that constructs models or methods similar to this study. Added a description of the current research questions and revised the last paragraph of the introduction. 3. In the methods, We have supplemented the definition of spatial equilibrium of elderly care facilities (SEECF) and revised the technology roadmap. 4. In section 2.2.1., we've revised the titles, supplemented the detailed explanations of the LR statistic, and organized the variables in the panel threshold model into a table. 5. In section 2.2.2. and 2.2.3., we've revised the titles and added a detailed explanation of the 4 detectors in the Geodetector. 6. In section 3.2.1., we've organized data name, source, year, and type into a table. 7. In section 3.2.2, we've revised the table of scores of service scope of elderly care service facilities. 8. In section 4.1., we have added the definitions of spatial equilibrium of elderly care facilities (SEECF) and spatial equilibrium state of elderly care facilities (SESECF), and added a table of correspondences between the two. At the same time, the description of the spatiotemporal sensitivity indicators, which were previously in sections 4.1.1 and 4.1.2, were moved to before section 4.1.1. 9. In section 4.1.1., we've revised the figure of SEECF (spatial equilibrium of elderly care facilities)(a,b,c) and accessibility(d,e,f) distribution maps of elderly care facilities in 2010, 2015 and 2020. 10. In section 4.2., 4.2.1., and 4.2.2., we've revised the titles and added an explanation of LISA cluster to Section 4.2.2. 11. In the discussion and conclusions, we added the full name of each abbreviation and supplemented the conclusions on the spatial association between GDP and SESECF under the influence of ULUC. 12. In section 5.3. in the Discussion, We have added future work contents based on the reviewers' comments. 13. We modify all formulas to MathType format.
Responses to reviewer 1’s commentsReviewer: 1Comments 1: The novelty of this study is unclear. Although the introduction is sufficient to highlight the importance to model the care facilities due to the aging population issues, the contribution of this study/paper compared to others is not mentioned. the gap they want to addressed whether in the spatial method, the discipline or the context is unclear. What are the research questions that this study attempts to address also not clearly stated in specific paragraph, including the variables/parameter they want to investigate (must put in table so that easy to refer back). line 283. Response 1: Thanks for your suggestion and reminder. The abstract and the last paragraph of introduction have been revised to highlight the issues to be addressed and the contribution of this study compared to other studies, so as to make the innovative nature of the study clearer. The details are shown in the following table. In addition, in order to make it easier for readers to read the variables that each part of the study wants to investigate, we have changed the "variables" in the title of section 2.2.1.-2.2.3. to the specific variable names, and there is no separate table because the number of variables is small, and it is more convenient to write directly.
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Abstract：“However, current researches focus on the supply of elderly care facilities and primarily uses administrative divisions as a scale, which leads to the weak sensitivity of the spatial equilibrium model of elderly care facilities. And the relationship between the spatial equilibrium of elderly care facilities (SEECF) and economic development is not clear. In response to these problems, we proposed ...”（line 12-15）
Introduction：“ Current research on the SEECF varies in terms of the types of elderly care facilities, research methods, and spatial scale.” （line 57-58）
“The deficiencies in different types of research have brought severe challenges to the spatiotemporal sensitivity measurement of regional SEECF, making it difficult to conduct a refined study of the SEECF. The refined analysis of the SEECF is the basis for providing decision-making basis for the scientific planning and management of elderly care facilities[49, 50]. It is necessary to propose a fine-scale spatial equilibrium model of elderly care facilities that takes into account the types of elderly care facilities and the relationship between supply and demand.” （line 69-75）
“At present, the research on the spatial equilibrium model of elderly care facilities is limited to service-type elderly care facilities. In the process of model construction, the focus is on the supply capacity of elderly care facilities and the actual needs of the elderly population are weakened. The spatial scale of the research is mostly based on administrative divisions. This large-scale regional setting makes the spatial equilibrium evaluation of elderly care facilities low in spatiotemporal sensitivity. Most of the research on the SEECF and economic development has only explored the relationship between numerical distribution, and rarely involved the analysis of spatial association relationships. At the same time, the impact of ULUC on the SEECF has not been considered. Therefore, it is urgent to construct a fine-scale spatial equilibrium model of elderly care facilities that takes into account different types of elderly care facilities and supply-demand relationships, and further quantitatively analyze its spatial association with economic development and ULUC.” （line 97-109）
“To solve the above problems, this study firstly took into account different types of elderly care facilities such as service-oriented and medical care-oriented, and considered the supply capacity of elderly care facilities and the actual needs of the elderly population to construct a spatial equilibrium model of elderly care facilities with high spatiotemporal sensitivity (SEM-HSTS). At the 100 m fine grid scale, considering the supply capacity of elderly care facilities and the actual needs of the elderly population, we proposed constructing two factors, the spatial accessibility rate of elderly care ser-vices (SARecs) and the spatiotemporal supply-demand ratio for elderly care services (STSDRecs). By employing the modified two-step floating catchment area (M2SFCA), we obtained the spatiotemporal availability of medical services (STAms) factor. Facing the needs of per capita resource fairness and facility accessibility efficiency, the coordination degree model was introduced to calculate the SEECF with high spatiotemporal sensitivity. On this basis, considering the high spatiotemporal sensitivity of the SEM-HSTS, this study further explored its comprehensive association with economic development. Considering that the elderly population factor and the SEECF will have an impact on GDP at the same time, we investigated the phased influence relationships among the population aging, SEECF, and GDP based on the threshold effect test. Through bivariate local spatial autocorrelation analysis and risk factor detection, we quantitatively analyzed the spatial associations among SEECF, GDP, and ULUC.” （line 110-128）
Comments 2: Please also include in other area outside China, other research that have produce similar methods or models to produce the final model. could be added in the introduction /literature before methodology sections.
Response 2:
Thank you for your good suggestion. We agree that the introduction needs to add some literature from the study area abroad, as well as literatures that construct models or methods similar to this study. After searching and reading, we have added literature[17] on accessibility to primary health care services, literatures[33,34] on various accessibility model construction methods, and literatures[68,69] on the relationship between economic development and land use types in the introduction.
- Guagliardo, M.F. Spatial accessibility of primary care: concepts, methods and challenges. Int J Health Geogr 3. 2004, 3. https://doi.org/10.1186/1476-072X-3-3.
- Launay, L. Methodology for building a geographical accessibility health index throughout metropolitan France. PLoS One. 2019, 8, 1-15. https://doi.org/10.1371/journal.pone.0221417.
- McGrail, M.; Humphreys, J. Measuring spatial accessibility to primary health care services: utilising dynamic catchment sizes. Appl. Geogr. 2014, 54, 182–188. https://doi.org/10.1016/j.apgeog.2014.08.005.
- Chumachenko, O.; Openko, I.; Kryvoviaz, Y.; Zhuk, O. Modeling of Indicators of Economic Efficiency of Sectoral Land Use. Scientific Papers. Series E. Land Reclamation, Earth Observation & Surveying, Environmental Engineering. 2022, 11, 95–106.
- Chowdhury, P.; Sikder, M.B. Shoreline dynamics in the reserved region of meghna estuary and its impact on lulc and socio-economic conditions: a case study from nijhum dwip, Bangladesh. J Coast Conserv. 2024, 28, 1-24. https://doi.org/10.1007/s11852-023-01000-7.
Comments 3: This manuscript also use many abbreviations that is not common and not easy to recall such as UCLC where the common abv is land use land cover (LULC) which kind of confusing. Please mention again the full of the abbreviation use particularly in discussion and conclusion section so that readers easy to trace back what is the short form meaning.
Response 3:
Thank you for pointing this out. We agree with this comment. UCLC is an abbreviation for Urban Land Use Categories(mentioned in line 26) which is different from land use land cover (LULC). To make it easy for readers to trace back what is the short form meaning, we mention again the full of each abbreviation use in discussion and conclusion section.
Comments 4: This study also mentioned two objectives - the first one is first, to develop a spatial equilibrium model of elderly care facilities with high spatiotemporal sensitivity (SEM-HSTS). (see line 93). so where is the second objective? please state the word 'second objective or next objective' for clarity.
Response 4:
Thanks for your suggestions and reminder. As you said, our study does have two objectives. We have revised the Introduction section. The first goal is: “ this study firstly took into account different types of elderly care facilities such as ser-vice-oriented and medical care-oriented, and considered the supply capacity of elderly care facilities and the actual needs of the elderly population to construct a spatial equilibrium model of elderly care facilities with high spatiotemporal sensitivity (SEM-HSTS).” （line 110-114） The second goal is: “considering the high spatiotemporal sensitivity of the SEM-HSTS, this study further explored its comprehensive association with economic development.” （line 121-123）
Comments 5: In the analysis of the Spatial Correlations between SEECF and Economic Development, the variables use are GDP and land use - in line 613, you did mention about correlation, but where is the correlation tables, the significant of all land use categories is not there. You did mention in line 615, This also indirectly reflected that the in- 615 the influence of ULUC on SEECF was smaller than that of GDP. (how you drew this conclusion, how from average data you generate the imbalance/balance statement?). the purpose to investigate the SEECF with economic development by using land use categories also need be concluded in lay man sentences, what we can understand from the analysis in the context of study.
Response 5:
Thanks for your suggestions and reminder. This is a lapse caused by a misunderstanding of spatial correlation and spatial association. What we want to express in this study is to analyze the spatial association between SEECF and economic development, and at first we thought that spatial correlation and spatial association can express “spatial association”, so we chose to use spatial correlation. Obviously the misuse of spatial correlation can easily lead to misunderstandings, so we changed it to spatial association (except for the bivariate local spatial autocorrelation part).
The spatial associations analysis in this study included spatial correlation analysis (bivariate local spatial autocorrelation2.2.2) and spatial impact analysis (geographic detector interaction detection2.2.3). Based on the above research contents, we used bivariate spatial autocorrelation analysis to explore the spatial association between GDP and SEECF in spatial correlation analysis(Figure 5). In the spatial impact analysis, the impact of urban land use categories (ULUC) and GDP on SEECF was explored by using the interaction detection of geodetector(Figure 6), so there was no need for correlation analysis and display in this part.
In addition, the average of SEECF in Table 13 represented the average spatial balance of elderly care facilities for each ULUC. Table 6 showed the correspondence between SEECF and SESECF. And we got that he maximum difference in average values of SEECF among all ULUC was approximately 0.15, with all being in a state of imbalance, indicating an insignificant difference. It was evident from Figure 5 that SEECF under different GDP levels obviously have different spatial balance and imbalance states, and the differences were obvious. That's the basis for drawing this conclusion-the influence of ULUC on SEECF was smaller than that of GDP.
Regarding the purpose to investigate the SEECF with economic development by using ULUC, we mentioned in original article(Furthermore, due to the strong association between ULUC and economic development, as well as its influence on the spatial configuration of elderly care facilities, we employed Geodetector to examine the relative influences of ULUC, GDP, and their interactionon different SESECF). We revise it to: After the previous analysis, we can see that there were phased hierarchical influence relationships and spatially related differences between economic development and SESECF, and the spatial impact analysis will be carried out below. At present, many studies have explored and found that there is a significant spatial correlation between GDP and different ULUC, so ULUC are likely to affect the spatial allocation of elderly care facilities. In this study, geographic detectors are used to study the relative effects of urban land use type, GDP and the interaction between the two on the SESECF.
“After the previous analysis, it can be seen that there are phased hierarchical impact relationships and spatial correlation differences between economic development and SEECF. At present, many studies have explored and found that there is a significant spatial association between GDP and different ULUC, so ULUC are likely to affect the spatial allocation of elderly care facilities. In this study, Geodetector was used to study the relative effects of ULUC, GDP and the interaction between the two on the SESECF.” （line 608-613）
Comments 6: This study also write several equations - but not clear whether the equations are developed by the authors or it actually was adopted (if yes, please include the references to the equations).
Response 6:
Thanks for your suggestions and reminder. Equations (1)-(4) in this article were proposed by us, and equations (5)-(15) were based on existing models or principles, and relevant references were given in the introduction of each method. For a clearer understanding, we cite the references again in the statement where the formulas (5)-(15) are given.
Comments 7: The tool use in this study to run the equations and to develop the model is not mentioned in the text, so not easy for others to replicate. For example, what is the reference for geodetector so that reader can refer back?
Response 7:
Thanks for your suggestions and reminder. Calculations for SecsAR, TSecsSDR, TSmsA, and development of the HTSSecfSE were in ArcGIS. The panel threshold effect model was constructed in Stata software. The bivariate local spatial autocorrelation analysis and the calculation of the number of significant regions of local spatial autocorrelation were completed in GeoDa software. The q-value of the geodetector was calculated using the Geographical detector tool in the QGIS software. We've added descriptions to the result section so that readers can repeat them. At the same time, we have summarized the following table:
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Model/Variables |
Tools/Website |
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SecsAR, TSecsSDR, TSmsA, HTSSecfSE |
ArcGIS10.8 |
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panel threshold effect model |
StataMP 18 |
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(bivariate) local spatial autocorrelation |
GeoDa (https://geodacenter.github.io) |
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Geodetector |
QGIS3.36.3 (http://www.geodetector.cn/) |
Comments 8: The diagram in Figure 1 need to improve the font size/style.
Response 8:
Thanks for your suggestions. We have changed the font in Figure 1 to Times New Roman and added a legend to improve readability.
Comments 9: Table 4 mention the q value- please describe in the texts why is q value? or put reference so that reader can refer back. and p-value (should be in small letter case). (e.g. line 499). what is LR statistic? please put reference
Response 9:
Thanks for your suggestions and reminder. The q-value mentioned in Table 7 are described in detail in section 2.2.3 of Methodology, explaining why is q-value and references have been given; We've changed the p-value to lowercase; The likelihood ratio LR is the ratio of the value of the likelihood function of the unconstrained model to the value of the likelihood function of the constrained model, which we have explained and referenced in the methodology.
“Subsequently, a test is conducted on the threshold values by constructing the Likeli-hood Ratio (LR) statistic to examine their significance. LR is the ratio of the value of the likelihood function of the unconstrained model to the value of the likelihood function of the constrained model.” （line 291-293）
Comments 10: line 515 and 516 - spacing need to be improved.
Response 10:
Thanks for the reminder. We've changed the spacing of the mentioned paragraph.
感谢您的提醒。我们已更改了相应段落的行距。
Comments 11: please check back the references- some spacing issue between words.
Response 11:
Thanks for the reminder. We have double-checked the spaces between words in the references.
感谢您的提醒。我们已再次详细检查了参考文献中单词间的空格。
Comments 12: Table 1 : what is the basis of the score? is it 5 minutes is still relevant or achievable to get the highest score?
Response 12:
Thank you for your comment. The score in Table 3 is based on our comprehensive references, and the 5 minutes is included in the first time period, i.e., the score is 10, and we have modified the time period in Table 3 to the interval format.
Table 3. Variable selection in the panel threshold model.
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Time period |
Score |
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[0 , 5] min |
10 |
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(5 , 10] min |
9 |
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(10 , 15] min |
8 |
|
(15 , 30] min |
6 |
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(30 , 60] min |
3 |
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> 60 min |
0 |
Comments 13: In line 366, the number of physician, doctors and beds is mentioned in the attribute but why is not considered in the equation (line 193)?
Response 13:
Thanks for the reminder. In line 366, the number of physicians, nurses and beds is mentioned in the attribute. At the same time, we give an explanation in equations (5)-(7): represents the total supply scale at primary healthcare facility j at time T, precisely the number of beds. For primary healthcare facilities without designated beds or experiencing data deficiencies, virtual bed counts are calculated based on the proportional relationship between bed counts and the number of medical staff. Perhaps the use of the word “medical staff” has led you to think that we are not using the number of physicians and nurses attribute, so we have changed the word to “physicians and nurses”.
Comments 14: line 385- what is the source/reference of standard?
Response 14:
Thanks for your reminder. The source of the standard is the modified revision of the national standard "Code for planning of city and town facilities for the aged" GB50437-2007 (2018 Edition). We've added reference and citation.
- Announcement of the Ministry of Housing and Urban-Rural Development on the modified revision of the national standard "Code for planning of city and town facilities for the aged" No. 334 of 2018. Engineering Construction Standardization. 2019, 02, 38-39. https://doi.org/10.13924/j.cnki.cecs.2019.02.015.
Comments 15: Figure- in the caption, list which figure is accessibility and SEECF.
Response 15:
Thanks for the reminder. We have added in the caption of Figure 3 that the subplots (a, b, c) are SEECF and the subplots (d, e, f) are accessibility.
Figure 3. SEECF (spatial equilibrium of elderly care facilities)(a,b,c) and accessibility(d,e,f) distribution maps of elderly care facilities in 2010, 2015 and 2020.
Comments 16: Figure 5 - Bilisa cluster map? have you mentioned somewhere in the text about bilisa?
Response 16:
Thanks for your reminder. The BiLISA cluster map is the result plot of bivariate spatial autocorrelation analysis. We have added a note in Section 4.2.2 of the results: Local Spatial Autocorrelation Analysis results to obtain BiLISA cluster map, LISA (Local Indicators of Spatial Association) is a method for spatial data analysis to identify spatial cluster patterns. Based on the similarity of data in geographic space, it calculates the local spatial correlation index of each region, so as to judge the local spatial autocorrelation. （line 580-584）
Comments 17: Line 587 - about risk- have this being introduced in the text before?
Response 17:
Thanks for your reminder. We didn't mention the two risk detectors on line 619 earlier, which does cause confusion for readers. Therefore, we add the corresponding explanation in section 2.2.3 of the method: The Geodetector includes four detectors: (1) Differentiation and risk factor detection, the detection of the spatial differentiation of Y and the extent to which the detection of a factor X explains the spatial differentiation of attribute Y; (2) Interaction detection, which identifies the interaction between different risk factors, i.e., assesses whether factors X1 and X2 increase or decrease the explanatory power of the dependent variable Y when they work together, or whether the effects of these factors on Y are independent of each other; (3) Risk zone detection, which is used to determine whether there is a significant difference in the mean value of attributes between the two sub-regions; (4) Ecological detection, which is used to compare whether there is a significant difference in the effects of two factors X1 and X2 on the spatial distribution of attribute Y. （line 328-337）
Comments 18: Other comments noted in PDF
Response 18:
Thank you for your professional suggestions. For the annotations in the PDF, we have modified them one by one as follows.
(1)
ULUC is not a TYPO. The corresponding explanation is given in the Response 3.
(2)
The full name of SARecs, STSDRecs and STAms have been given in abstract. In detail，SARecs is an abbreviation of the spatial accessibility rate of elderly care services, STSDRecs is an abbreviation of the spatiotemporal supply-demand ratio for elderly care services, STAms is an abbreviation of the spatiotemporal accessibility of medical services. In addition, “coordination degree model”, “Geodetector”, and “panel threshold model” are the methods used in the study, which are described in detail in sections 2.1.4., 2.2.3. and 2.2.1. of the methodology, respectively.
(3)
We've changed the font in Figure 1 to make it look clearer (Response 8). Based on the panel threshold model, we use the advantages of high temporal sensitivity of spatial equilibrium of elderly care facilities to analyze the influence relationship between SEECF and economic development, rather than combining the two. The M2SFCA method is an modified two-step floating catchment area method used in the calculation of STAms, which is described in detail in section 2.1.3 of the method
(4)
The formula for calculating STSDRecs was proposed by us through comprehensive references, and the elderly care service facilities were clearly indicated in the parameter setting in 3.2.2, including nursing homes, homes for the elderly, elderly care homes, senior apartments, daycare centers, elderly daycare centers, and senior activity centers. signifies the average supply of beds within radius of elderly care service facilities at time . The number of beds used in this study represents the service capacity of elderly care facilities, so it is significant. The number of doctors will be used in the calculation of STAms.
(5)
The additional distance decay function means that M2SFCA modifies the original model with a fixed distance from the numerator, and uses the distance decay function instead of the original numerator.
(6)
Thank you very much for your advice. However, the structure of the paper is to divide the method and parameter setting part into two parts for description, and the method should be proposed first, and the parameters should be set according to the obtained data in the subsequent experiments. In this way, readers can set the corresponding parameters according to the research method and combine their own data.
(7)
Here we propose to use the distance of the road network to calculate the STAms based on the M2SFCA model. Therefore there are no references. The use of road network distances to calculate the records of the elderly and health facilities has more practical significance than Euclidean distances.
(8)
Thanks for your advice. We have organized the variables in the panel threshold model as shown in the following table and modified the text.
“The selection of variables in the model is shown in Table 1 below, and logarithmic transformations are applied to GDP, population size, and road network length to mitigate endogeneity and multicollinearity.” （line 300-304）
Table 1. Variable selection in the panel threshold model.
|
Variable type |
Variable name |
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Dependent variable |
GDP |
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Core explanatory variables |
SEECF; Population aging |
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Control variables |
Population size; Road network length |
(9)
Geodector means geographical detector, and Ref. [80] proposed and named Geodector.
(10)
The first sentence of the paragraph gives the source of the data, the "Analysis of Population Aging Situation in Wuhan in 2018" report released by the Civil Affairs Bureau of Wuhan, but because there is no standard citation format for the government report, no references are indicated here.
(11)
An explanation has been given in Response 13.
(12)
An explanation has been given in Response 12.
(13)
Because in section 2.1.1 of Methodology, the time imdepences are proposed earlier than the scores, we want to sort time in order from smallest to largest
(14)
An explanation has been given in Response 14.
(15)
We have put them in the legend of Figure 3 to illustrate according to your advice.
(16)
A revision has been given in Response 15.
(17)
A revision has been given in Response 9.
(18)
A revision has been given in Response 10.
(19)
We have already replace "." with "," to ensure the flow and correctness of the sentence.
(20)
A revision has been given in Response 5.
(21)
A revision has been given in Response 17.
(22)
This is a translation error, and what we want to say is "it can be obtained by analyzing in conjunction with Figure 7". The text has been amended to “Analyzing in conjunction with Figure 7”. （line 630）
(23)
An explanation has been given in Response 5.
(24)
At first, we thought that the conclusion of the part " The spatial association between GDP and SESECF under the influence of ULUC " was too much, so we wanted to replace it with a more general word "diverse". Based on your suggestion, we have revised the article to describe the conclusions more clearly: “The types of transportation stations, commercial offices, business office, commercial service, and sport and cultural showed that the spatial balance of elderly care facilities correlated with high GDP. The airport facility type, medical type, administrative type, and park and green type have the phenomenon of spatial imbalance correlated with low GDP. Educational type showed no significant association between SEECF and GDP.” （line 776-781）
We appreciate for Editors and Reviewer’s warm work earnestly and hope that the correction will meet with approval.
Once again, thank you very much for your comments and suggestions.
Author Response File: 
Author Response.docx
Reviewer 2 Report
Comments and Suggestions for AuthorsFigure no. 1 is not clear, I think the text format should be changed.
Line 49 - ypographical error, "y-demand" should likely be "supply-demand."
Line 66 - Awkward construction; could be revised for clarity and conciseness. A smoother alternative might be This leads to less accurate simulations of real-world scenarios.
line 161 - The error in the text is the phrase "𝛼0 denoting the standard of an aging society, namely 7%" . The correct term "denoting" is misspelled as "denothing."
in lines 554, 652, 714,731 where "SESECF" appears. This seems to be a typographical error, and it should be corrected to "SEECF," which stands for "Spatial Equilibrium Model of Elderly Care Facilities."
Providing more detailed descriptions of the data used in the study, including sources and methods of collection, can enhance the transparency and reproducibility of the research.
Author Response
Dear Editors and Reviewer,
Thank you for your letter and for the reviewer’s comments concerning our manuscript entitled “The Spatial Equilibrium Model of Elderly Care Facilities with High Spatiotemporal Sensitivity and Its Economic Associations Study” (ijgi-3006202). Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our researches.
During the past few days, we have considered these comments carefully and highlighted the corresponding modifications in the revised manuscript. Based on these comments and suggestions, we have made careful modifications to the original manuscript, and carefully proof-read the manuscript to minimize typographical and grammatical errors. The reviewer’s comments are laid out below and specific concerns have been numbered. Our response is given in normal font and changes/additions to the manuscript are given in blue text.
We believe that the manuscript has been greatly improved and hope it has reached your magazine’s standard. Once again, many thanks for considering possible publication of our manuscript.
List of main corrections:
- In the abstract, we have made revision to highlight the problem that this study aims to address and the contribution compared to other studies, so that the innovativeness of the study is clearer.
- In the introduction, we have added some literature from the study area abroad, as well as literature that constructs models or methods similar to this study. Added a description of the current research questions and revised the last paragraph of the introduction.
- In the methods, We have supplemented the definition of spatial equilibrium of elderly care facilities (SEECF) and revised the technology roadmap.
- In section 2.2.1., we've revised the titles, supplemented the detailed explanations of the LR statistic, and organized the variables in the panel threshold model into a table.
- In section 2.2.2. and 2.2.3., we've revised the titles and added a detailed explanation of the 4 detectors in the Geodetector.
- In section 3.2.1., we've organized data name, source, year, and type into a table.
- In section 3.2.2, we've revised the table of scores of service scope of elderly care service facilities.
- In section 4.1., we have added the definitions of spatial equilibrium of elderly care facilities (SEECF) and spatial equilibrium state of elderly care facilities (SESECF), and added a table of correspondences between the two. At the same time, the description of the spatiotemporal sensitivity indicators, which were previously in sections 4.1.1 and 4.1.2, were moved to before section 4.1.1.
- In section 4.1.1., we've revised the figure of SEECF (spatial equilibrium of elderly care facilities)(a,b,c) and accessibility(d,e,f) distribution maps of elderly care facilities in 2010, 2015 and 2020.
- In section 4.2., 4.2.1., and 4.2.2., we've revised the titles and added an explanation of LISA cluster to Section 4.2.2.
- In the discussion and conclusions, we added the full name of each abbreviation and supplemented the conclusions on the spatial association between GDP and SESECF under the influence of ULUC.
- In section 5.3. in the Discussion, We have added future work contents based on the reviewers' comments.
- We modify all formulas to MathType format.
Responses to reviewer 2’s comments
Reviewer: 2
Comments 1: Figure no. 1 is not clear, I think the text format should be changed.e?
Response 1:
Thanks for the suggestion. We have changed the font in Figure 1 to Times New Roman to improve readability.
Comments 2: Line 49 - ypographical error, "y-demand" should likely be "supply-demand."
Response 2:
Thanks for your reminder.It's possible that word wrap adds a hyphen that makes you read it wrong. The word "supply-demand" in the original text is correct.
Comments 3: Line 66 - Awkward construction; could be revised for clarity and conciseness. A smoother alternative might be This leads to less accurate simulations of real-world scenarios.
Response 3:
Thanks for the suggestion. As you suggested, we've changed the redundancy section " Without considering the spatiotemporal sensitivity of the elderly population. Thus resulting in less accurate simulations of real-world scenarios." to " This leads to less accurate simulations of real-world scenarios ".（line 68-69）
Comments 4: line 161 - The error in the text is the phrase "?0 denoting the standard of an aging society, namely 7%". The correct term "denoting" is misspelled as "denothing."
Response 4:
Thanks for the reminder. We have rechecked, and the word "denoting" in the original text is correct.
Comments 5: in lines 554, 652, 714,731 where "SESECF" appears. This seems to be a typographical error, and it should be corrected to "SEECF," which stands for "Spatial Equilibrium Model of Elderly Care Facilities."
Response 5:
Thanks for the comment. The word "SESECF" in the original text is correct, which means the spatial equilibrium state of elderly care facilities, and different from the spatial equilibrium of elderly care facilities (SEECF). They are two variables, the former is literal variable. The latter is numerical variable. We have described them in section 4.1.1. of the results. And in Section 4.1, it is supplemented as described below:
“The spatial equilibrium of elderly care facilities (SEECF) is an index to quantify the balance of supply and demand distribution of elderly care facilities. It is a numeric variable with a value range of [0,1]; The spatial equilibrium state of elderly care facilities (SESECF) is an index to evaluate the balance of supply and demand distribution of elderly care facilities, which is a text variable, and its correspondence with the SEECF is shown in Table 4 below. The larger the value of the SEECF, the more unbalanced, and the smaller the value of the SEECF, the more unbalanced. This indicates that there is a negative correlation between the SEECF and the SESECF.” （line 420-428）
Table 4. Table of correspondence between SEECF and SESECF.
|
SEECF |
SESECF |
|
[0 , 0.2] |
well balanced |
|
(0.2 , 0.4] |
moderately balanced |
|
(0.4 , 0.5] |
mildly balanced |
|
(0.5 , 0.6] |
mildly imbalanced |
|
(0.6 , 0.8] |
moderately imbalanced |
|
[0.8 , 1] |
severely imbalanced |
Comments 6: Providing more detailed descriptions of the data used in the study, including sources and methods of collection, can enhance the transparency and reproducibility of the research.
Response 6:
Thanks for your suggestion. We have given in Section 3.2.1. the sources, descriptions, and acquisition methods of all the data used in the study. Reorganized into table 2 for easier reference by readers. However, it should be noted that due to the restriction of data access permissions, the data of primary healthcare facilities provided by the Wuhan Municipal Health Commission will not be disclosed. All other data is open source and can be downloaded and experimented on by themselves.
Table 2. Name, source, year, and type of the experimental data.
|
Name |
Source |
Year |
Type |
|
population |
WorldPop (https://hub.worldpop.org) |
2010, 2015, 2020 |
Raster (100m) |
|
elderly population |
WorldPop (https://hub.worldpop.org) |
2010, 2015, 2020 |
Raster (100m) |
|
POI |
Amap (https://ditu.amap.com/) |
2010, 2015, 2020 |
Point |
|
road network |
Amap (https://ditu.amap.com/) |
2010, 2015, 2020 |
Line |
|
GDP |
https://doi.org/10.6084/m9.figshare.17004523.v1[72] |
2010, 2015, 2020 |
Raster (1000m) |
|
primary healthcare facilities |
Wuhan Municipal Health Commission |
2021 |
Point |
|
elderly care facilities |
https://www.yanglaocn.com/ |
2023 |
Point |
|
ULUC |
http://data.ess.tsinghua.edu.cn/[73] |
2018 |
Polygon |
We appreciate for Editors and Reviewers’ warm work earnestly and hope that the correction will meet with approval.
Once again, thank you very much for your comments and suggestions.
Author Response File: Author Response.docx
Reviewer 3 Report
Comments and Suggestions for Authors1. The study discusses the influence of GDP on SEECF without clarifying the mechanisms
or pathways through which GDP affects elderly care facilities.
2. How is the "spatial equilibrium" of elderly care facilities defined and measured in this
study?
3. The study suggests selecting suitable locations for elderly care facilities based on
population aging without specifying the criteria or factors considered in the selection
process.
4. The conclusion that regional economic development has a significant influence on
SEECF lacks a detailed explanation of the causal relationships between economic
development and elderly care facilities.
5. What are the key assumptions underlying the recommendations for selecting suitable
locations for elderly care facilities based on population aging?
6. How are the "precise threshold values and degrees of influence" on economic
development quantitatively determined in the model?
2
7. Provide more details on the methodology used to analyze the "spatial sensitivity" of the
SEM-HSTS model.
8. The study discusses the spatial correlations between SEECF, GDP, and ULUC without
detailing the methodology or statistical techniques used to analyze these correlations.
9. The study outlines a technical process without providing a clear overview of the specific
methods or tools employed in each stage of the analysis.
10. What specific measures or strategies are proposed to enhance the SESECF and achieve
spatial equilibrium in elderly care facility distribution?
Comments on the Quality of English LanguageModerate editing of English language required
Author Response
Dear Editors and Reviewer,
Thank you for your letter and for the reviewer’s comments concerning our manuscript entitled “The Spatial Equilibrium Model of Elderly Care Facilities with High Spatiotemporal Sensitivity and Its Economic Associations Study” (ijgi-3006202). Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance to our researches.
During the past few days, we have considered these comments carefully and highlighted the corresponding modifications in the revised manuscript. Based on these comments and suggestions, we have made careful modifications to the original manuscript, and carefully proof-read the manuscript to minimize typographical and grammatical errors. The reviewer’s comments are laid out below and specific concerns have been numbered. Our response is given in normal font and changes/additions to the manuscript are given in blue text.
We believe that the manuscript has been greatly improved and hope it has reached your magazine’s standard. Once again, many thanks for considering possible publication of our manuscript.
List of main corrections:
- In the abstract, we have made revision to highlight the problem that this study aims to address and the contribution compared to other studies, so that the innovativeness of the study is clearer.
- In the introduction, we have added some literature from the study area abroad, as well as literature that constructs models or methods similar to this study. Added a description of the current research questions and revised the last paragraph of the introduction.
- In the methods, We have supplemented the definition of spatial equilibrium of elderly care facilities (SEECF) and revised the technology roadmap.
- In section 2.2.1., we've revised the titles, supplemented the detailed explanations of the LR statistic, and organized the variables in the panel threshold model into a table.
- In section 2.2.2. and 2.2.3., we've revised the titles and added a detailed explanation of the 4 detectors in the Geodetector.
- In section 3.2.1., we've organized data name, source, year, and type into a table.
- In section 3.2.2, we've revised the table of scores of service scope of elderly care service facilities.
- In section 4.1., we have added the definitions of spatial equilibrium of elderly care facilities (SEECF) and spatial equilibrium state of elderly care facilities (SESECF), and added a table of correspondences between the two. At the same time, the description of the spatiotemporal sensitivity indicators, which were previously in sections 4.1.1 and 4.1.2, were moved to before section 4.1.1.
- In section 4.1.1., we've revised the figure of SEECF (spatial equilibrium of elderly care facilities)(a,b,c) and accessibility(d,e,f) distribution maps of elderly care facilities in 2010, 2015 and 2020.
- In section 4.2., 4.2.1., and 4.2.2., we've revised the titles and added an explanation of LISA cluster to Section 4.2.2.
- In the discussion and conclusions, we added the full name of each abbreviation and supplemented the conclusions on the spatial association between GDP and SESECF under the influence of ULUC.
- In section 5.3. in the Discussion, We have added future work contents based on the reviewers' comments.
- We modify all formulas to MathType format.
Responses to reviewer 3’s comments
Reviewer: 3
Comments 1: The study discusses the influence of GDP on SEECF without clarifying the mechanisms or pathways through which GDP affects elderly care facilities.
Response 1:
Thank you very much for your comment. In Section 5.2.2., we discuss the spatial associations of GDP, ULUC, and SEECF. The correlation analysis between GDP and SEECF (bivariate local spatial autocorrelation analysis) was carried out in the first part of the experiment in section 4.2.2 is not impact analysis. The impact analysis of GDP and ULUC on the SEECF was carried out in the latter part of the experiment in section 4.2.2, and the joint effect of GDP and ULUC cannot be disassembled into the separate role of GDP. Your comments are very meaningful and can be a part of our future work. We have added relevant content in Section 5.3. of the Discussion: “When this study explored the impact of GDP and ULUC on the SEECF, it only analyzed how the combined effect of the two affected the SEECF, and did not analyze their individual effects. Future research can consider using more rigorous and scientific influencing factor analysis methods to explore the individual and combined effects of GDP and ULUC on the SEECF. It can also look for other relevant influencing factors for analysis, and further find the specific impact mechanisms or pathways of each factor on the elderly care facilities.”（line 726-732） Thank you again!
Comments 2: How is the “spatial equilibrium” of elderly care facilities defined and measured in this study?
Response 2:
Thank you for your comment. In this article, we take "SEECF" as a whole and add its definition at the beginning of the method section: “The spatial equilibrium of elderly care facilities(SEECF) is an index to quantify the balance of supply and demand distribution of elderly care facilities.”（line 137-139） We hope it can answer your questions.
Comments 3: The study suggests selecting suitable locations for elderly care facilities based on population aging without specifying the criteria or factors considered in the selection process.
Response 3:
Thank you very much for your valuable comment. The goal of this study is to construct a computational model for the spatial equilibrium of elderly care facilities and analyze its relationship with economic development. Your comments are parts of our next steps. We have added relevant content in Section 5.3. of the Discussion: “In future work, we can set key parameters in site selection analysis or facility optimization analysis based on the spatial equilibrium model of elderly care facilities proposed in this study and the analysis of the correlation between the SEECF and economic development under the background of population aging, and enhance the existing models, so as to provide a more scientific reference for the comprehensive optimization of urban elderly care services and facility planning layout.”（line 735-740）Thank you again!
Comments 4: The conclusion that regional economic development has a significant influence on SEECF lacks a detailed explanation of the causal relationships between economic development and elderly care facilities.
Response 4:
Thank you very much for your valuable comment. This study only explores the correlation and influence between economic development and the SEECF. But your comment is also one of the main part of our next study. We have added relevant content in Section 5.3. of the Discussion: “At the same time, it is also necessary to explore the causal relationship between various factors and the spatial equilibrium of elderly care facilities in the next step of work, so as to obtain a more comprehensive understanding and lay a solid foundation for the development of practical work.”（line 732-735）Thank you again!
Comments 5: What are the key assumptions underlying the recommendations for selecting suitable locations for elderly care facilities based on population aging?
Response 5:
Thank you very much for your valuable comment. We have added relevant content in Section 5.3. of the Discussion: “In future work, we can set key parameters in site selection analysis or facility optimization analysis based on the spatial equilibrium model of elderly care facilities proposed in this study and the analysis of the correlation between the SEECF and economic development under the background of population aging, and enhance the existing models, so as to provide a more scientific reference for the comprehensive optimization of urban elderly care services and facility planning layout.”（line 735-740）Thank you again！
Comments 6: How are the “precise threshold values and degrees of influence” on economic development quantitatively determined in the model?
Response 6:
Thank you for your comment. The precise values of the threshold variables and the degrees of influence on GDP in Tables 10 and 12 were calculated by the panel threshold effect model We explained them in Section 4.2.1: In the Equations (11) and (12), represent threshold values. denotes GDP, represent the degree of the influence of core variables on GDP at different threshold levels, denotes the parameter capturing the influence of control variables, represent control variables. Equation (11) examines the influence of population aging on GDP with as the threshold variable. At the same time, Equation (12) investigates the influence of on GDP with population aging as the threshold variable. The residual sum of squares is computed for Equations (11) and (12) to calculate threshold values.
Comments 7: Provide more details on the methodology used to analyze the “spatial sensitivity”; of the SEM-HSTS model.
Response 7:
Thank you for your comment. In sections 4.1.1. and 4.1.2, the methods for analyzing spatial and temporal sensitivity are described in detail. According to your suggestion, in order to give the reader a clearer understanding of the method details, we have moved it to the beginning of section 4.1.
Comments 8: The study discusses the spatial correlations between SEECF, GDP, and ULUC without detailing the methodology or statistical techniques used to analyze these correlations.
Response 8:
Thank you for your comment. In this study, the impact of urban land use categories (ULUC) and GDP on SEECF was explored by using the interaction detection of Geodetector (Figure 6).Then, the SEECF and GDP were statistically analyzed by ULUC to obtain Table 13 and Figure 8. Analyzing in conjunction with Figure 7, it was evident that the type with the lowest average value of SEECF, indicating the most balanced, was transportation stations. Simultaneously, this type exhibited the highest average GDP, corresponding to the phenomenon of spatial balance in the core areas correlated with high GDP as mentioned earlier. Similar patterns were observed for business office type, commercial service type, and sport and cultural type. Conversely, the urban land type with the highest average value of SEECF, indicating the most imbalanced, was the airport facility type. Additionally, this type showed the lowest average GDP, corresponding to the phenomenon of spatial imbalance in the peripheral areas with low GDP correlation as mentioned earlier. Similar patterns were observed for medical type, administrative type, and park and green type. Industrial type near the Qingshan district exhibited spatial imbalance correlated with high GDP, while those near Hanyang district exhibited spatial balance correlated with low GDP. Residential type in the Jiang’an district exhibited spatial imbalance correlated with high GDP, whereas most residential type in other areas exhibited spatial balance correlated with low GDP. Educational type showed no significant correlation between SEECF and GDP. The maximum difference in average values of SEECF among all ULUC was approximately 0.15, with all being in a state of imbalance, indicating an insignificant difference. This also indirectly reflected that the influence of ULUC on SEECF was smaller than that of GDP.
Comments 9: The study outlines a technical process without providing a clear overview of the specific methods or tools employed in each stage of the analysis.
Response 9:
Thank you for your comment. The specific methods or tools used for each analysis have been shown in the technical flowchart in this article, but perhaps you may not be able to see it clearly because there is no legend. Therefore, we added legend to the technical roadmap to illustrate what the various shapes represent. The methods and tools used in each analysis are summarized in the following table:
|
Analysis step |
Tools/Model |
|
Calculation of SecsAR, TSecsSDR, TSmsA, HTSSecfSE |
Coordination Model |
|
Comparison spatiotemporal sensitivity |
Standard Deviation, Geodetector, the Number of Significant Regions with Local Spatial Autocorrelation |
|
Analysis of the influence relationships between SEECF and economic development |
panel threshold effect model |
|
Analysis of the spatial associations between SEECF and economic development |
Geodetector, Bivariate Local Spatial Autocorrelation |
Comments 10: What specific measures or strategies are proposed to enhance the SESECF and achieve spatial equilibrium in elderly care facility distribution?
Response 10:
Thank you very much for your valuable comment. This study added the following content to Section 5.1. of the Discussion: “By observing the three factors (SARecs, STSDRecs, and STAms) and the three indicators (standard deviation, q-value of Geodetector, and the number of significant clusters in spatial autocorrelation) to evaluate the spatiotemporal sensitivity of the model proposed in this study, we can know where are the problems. Further corrections are made to achieve spatial balance.”（line 670-674）
Author Response File: Author Response.docx
