Data · dataset · 2022
Dataset of depression and anxiety among the elderly derived from The Nottingham Longitudinal Study of Activity and Ageing (NLSAA) project
Listed in ScienceDB
This dataset is derived from The Nottingham Longitudinal Study on Activity and Ageing (NLSAA).
Description
NLSAA is an 8-year survey for people aged 65 and above, which collects demographic information and a large amount of life data of this population. The baseline survey (T1) was conducted in the summer of 1985.
During this period, the data collection team randomly sampled 1,299 people aged 65 and above according to the list provided by general practitioners in Nottinghamshire, and interviewed them. After that, every four years, the population was followed up at T2 (in the summer of 1989) and T3 (in the summer of 1993). The NLSAA data finally contains 1263 variables and 1042 observations.
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The data describes the prevalence of depression and anxiety among the elderly in NLSAA is extracted and used to form this dataset.In NLSAA, we take the sample with depression and anxiety (psych_=1) as positive, and the sample without depression and anxiety (psych_=0) as negative. In order to balance the categories of sample in the dataset, we extract the positive samples and the negative samples from the T1 survey and only positive samples from the T2 and T3 surveys as the observations of the dataset.
Then, according to the relevant literature, we extract the risk variables of depression and anxiety in the elderly from NLSAA as the variables of the dataset. As a result, there are 1152 valid observations and 54 risk variables of depression and anxiety in the elderly in this dataset.
Note
To access the original NLSAA dataset, please contact Professor Kevin Morgan (lboro.ac.uk/departments/ssehs/staff/kevin-morgan/, E-mail Address: K.Morgan@lboro.ac.uk) to get permission for accessing and the copy of the dataset.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.06263 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Longitudinal study 75%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.06263 | 10 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[method].local:method:longitudinal-study | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license_text | source · scidb cn | connector:scidb_cn@1.0.0 | |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |