Comparison of complete and spatial sampling frames for estimation of the prevalence of hypertension and diabetes mellitus
A complete sampling frame (CSF) is needed for the development of probability sampling structures; utilisation of a spatial sampling frame (SSF) was the objective of the present study. We used two sampling methods, simple random sampling (SRS) and stratified random sampling (STRS), to compare the pr...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
PAGEPress Publications
2022-11-01
|
| Series: | Geospatial Health |
| Subjects: | |
| Online Access: | https://www.geospatialhealth.net/index.php/gh/article/view/1097 |
| _version_ | 1811320710753157120 |
|---|---|
| author | Vasna Joshua Kamaraj Pattabi Yuvaraj Jeyaraman Prabhdeep Kaur Tarun Bhatnagar Suresh Arunachalam Sabarinathan Ramasamy Venkateshprabhu Janagaraj Manoj V Murhekar |
| author_facet | Vasna Joshua Kamaraj Pattabi Yuvaraj Jeyaraman Prabhdeep Kaur Tarun Bhatnagar Suresh Arunachalam Sabarinathan Ramasamy Venkateshprabhu Janagaraj Manoj V Murhekar |
| author_sort | Vasna Joshua |
| collection | DOAJ |
| description |
A complete sampling frame (CSF) is needed for the development of probability sampling structures; utilisation of a spatial sampling frame (SSF) was the objective of the present study. We used two sampling methods, simple random sampling (SRS) and stratified random sampling (STRS), to compare the prevalence estimates delivered by a CSF to that by a SSF when applied to self-reported hypertension and diabetes mellitus in a semi-urban setting and in a rural one. A CSF based on Geodatabase of all households and all individuals was available for our study that focused on adults aged 18-69 years in the two settings. A single digitized shapefile of solely household regions/structures as SSF was developed using Google Earth and employed for the study. The results from the two sampling frames were similar and not significantly different. All 95%CI calculations contained the prevalence rates of the two medical conditions except for one occasion based on STRS and CSF. The SRS based on CSF showed a minimum 95% CI width for diabetes mellitus, whereas SSF showed a minimum 95% CI width for hypertension. The coefficient of variation exceeded 10.0% on six occasions for CSF but only once for SSF, which was found to be as efficient as CSF.
|
| first_indexed | 2024-04-13T13:02:41Z |
| format | Article |
| id | doaj.art-509d12ba92894c2bba19e1e5b6f54cd8 |
| institution | Directory Open Access Journal |
| issn | 1827-1987 1970-7096 |
| language | English |
| last_indexed | 2024-04-13T13:02:41Z |
| publishDate | 2022-11-01 |
| publisher | PAGEPress Publications |
| record_format | Article |
| series | Geospatial Health |
| spelling | doaj.art-509d12ba92894c2bba19e1e5b6f54cd82022-12-22T02:45:51ZengPAGEPress PublicationsGeospatial Health1827-19871970-70962022-11-0117210.4081/gh.2022.1097Comparison of complete and spatial sampling frames for estimation of the prevalence of hypertension and diabetes mellitusVasna Joshua0Kamaraj Pattabi1Yuvaraj Jeyaraman2Prabhdeep Kaur3Tarun Bhatnagar4Suresh Arunachalam5Sabarinathan Ramasamy6Venkateshprabhu Janagaraj7Manoj V Murhekar8National Institute of Epidemiology (ICMR), Ayapakkam, Chennai, Tamil NaduNational Institute of Epidemiology (ICMR), Ayapakkam, Chennai, Tamil NaduNational Institute of Epidemiology (ICMR), Ayapakkam, Chennai, Tamil NaduNational Institute of Epidemiology (ICMR), Ayapakkam, Chennai, Tamil NaduNational Institute of Epidemiology (ICMR), Ayapakkam, Chennai, Tamil NaduNational Institute of Epidemiology (ICMR), Ayapakkam, Chennai, Tamil NaduNational Institute of Epidemiology (ICMR), Ayapakkam, Chennai, Tamil NaduNational Institute of Epidemiology (ICMR), Ayapakkam, Chennai, Tamil NaduNational Institute of Epidemiology (ICMR), Ayapakkam, Chennai, Tamil Nadu A complete sampling frame (CSF) is needed for the development of probability sampling structures; utilisation of a spatial sampling frame (SSF) was the objective of the present study. We used two sampling methods, simple random sampling (SRS) and stratified random sampling (STRS), to compare the prevalence estimates delivered by a CSF to that by a SSF when applied to self-reported hypertension and diabetes mellitus in a semi-urban setting and in a rural one. A CSF based on Geodatabase of all households and all individuals was available for our study that focused on adults aged 18-69 years in the two settings. A single digitized shapefile of solely household regions/structures as SSF was developed using Google Earth and employed for the study. The results from the two sampling frames were similar and not significantly different. All 95%CI calculations contained the prevalence rates of the two medical conditions except for one occasion based on STRS and CSF. The SRS based on CSF showed a minimum 95% CI width for diabetes mellitus, whereas SSF showed a minimum 95% CI width for hypertension. The coefficient of variation exceeded 10.0% on six occasions for CSF but only once for SSF, which was found to be as efficient as CSF. https://www.geospatialhealth.net/index.php/gh/article/view/1097complete sampling framespatial sampling framehypertensiondiabetes mellitusTamil Nadu |
| spellingShingle | Vasna Joshua Kamaraj Pattabi Yuvaraj Jeyaraman Prabhdeep Kaur Tarun Bhatnagar Suresh Arunachalam Sabarinathan Ramasamy Venkateshprabhu Janagaraj Manoj V Murhekar Comparison of complete and spatial sampling frames for estimation of the prevalence of hypertension and diabetes mellitus Geospatial Health complete sampling frame spatial sampling frame hypertension diabetes mellitus Tamil Nadu |
| title | Comparison of complete and spatial sampling frames for estimation of the prevalence of hypertension and diabetes mellitus |
| title_full | Comparison of complete and spatial sampling frames for estimation of the prevalence of hypertension and diabetes mellitus |
| title_fullStr | Comparison of complete and spatial sampling frames for estimation of the prevalence of hypertension and diabetes mellitus |
| title_full_unstemmed | Comparison of complete and spatial sampling frames for estimation of the prevalence of hypertension and diabetes mellitus |
| title_short | Comparison of complete and spatial sampling frames for estimation of the prevalence of hypertension and diabetes mellitus |
| title_sort | comparison of complete and spatial sampling frames for estimation of the prevalence of hypertension and diabetes mellitus |
| topic | complete sampling frame spatial sampling frame hypertension diabetes mellitus Tamil Nadu |
| url | https://www.geospatialhealth.net/index.php/gh/article/view/1097 |
| work_keys_str_mv | AT vasnajoshua comparisonofcompleteandspatialsamplingframesforestimationoftheprevalenceofhypertensionanddiabetesmellitus AT kamarajpattabi comparisonofcompleteandspatialsamplingframesforestimationoftheprevalenceofhypertensionanddiabetesmellitus AT yuvarajjeyaraman comparisonofcompleteandspatialsamplingframesforestimationoftheprevalenceofhypertensionanddiabetesmellitus AT prabhdeepkaur comparisonofcompleteandspatialsamplingframesforestimationoftheprevalenceofhypertensionanddiabetesmellitus AT tarunbhatnagar comparisonofcompleteandspatialsamplingframesforestimationoftheprevalenceofhypertensionanddiabetesmellitus AT suresharunachalam comparisonofcompleteandspatialsamplingframesforestimationoftheprevalenceofhypertensionanddiabetesmellitus AT sabarinathanramasamy comparisonofcompleteandspatialsamplingframesforestimationoftheprevalenceofhypertensionanddiabetesmellitus AT venkateshprabhujanagaraj comparisonofcompleteandspatialsamplingframesforestimationoftheprevalenceofhypertensionanddiabetesmellitus AT manojvmurhekar comparisonofcompleteandspatialsamplingframesforestimationoftheprevalenceofhypertensionanddiabetesmellitus |