The study on the factors of Hypertension in Nottingham Longitudinal Study of Activity and Ageing (NLSAA) dataset.
SPSS output file download: https://github.com/bobleer/NLSAA_Hypertension/raw/master/SPSS_output.spv
Nottingham Longitudinal Study of Activity and Ageing (NLSAA) is an 8-year society survey on the dwellers who aged 65 or over. Specifically, three interviews were conducted in 1985, 1989, and 1993 respectively. In the first time, the number of interviewees is 1042, thereinto the ratio of age had been intentionally adjusted ([65-74]:[75+]≈1:1). According to the results of interviews, NLSAA dataset had been generated and included 1256 variables which covered numerous aspects of sociological statistics.
In effects to further reducing the effects of hypertension in the UK, this study has two purposes: to describes the latent risk factors for this disease, and to explain this by developing and testing theory through NLSAA dataset.
| Data type | Sub-type | Variable | Value scale | Description | Method | Sig. |
|---|---|---|---|---|---|---|
| Discrete | Nominal | hi_bp_85 |
(0,1) | High Blood Pressure? | Dependent variable | |
| Discrete | Nominal | heart_85 |
(0,1) | Heart trouble? | Chi-squared | 0.002 |
| Discrete | Nominal | smoke_do |
(0,1) | Do you smoke? | Chi-squared | 0.063 |
| Discrete | Nominal | sex_85 |
(1,2) | Gender | Chi-squared | 0.001 |
| Continuous | Interval | age_85 |
(Numeric) | Age | KS → MW-U | 0.977 |
| Continuous | Ratio | wght_85 |
(Numeric/Kgs) | Weight | KS → MW-U | 0.009 |
| Continuous | Interval | tmasl_85 |
(Numeric/Min) | Time Asleep | KS → MW-U | 0.278 |
| Continuous | Interval | t_rlx_85 |
(Numeric/Min) | Leisure Time | KS → MW-U | 0.046 |
| Discrete | Ordinal | anx_85 |
(Score/0,21) | Anxiety | MW-U | 0.031 |
| Discrete | Ordinal | dep_85 |
(Score/0,21) | Depression | MW-U | 0.013 |
| High blood pressure? (Percentage of correct prediction: 78%) | 95% C.I. for EXP(B) | |||||||
|---|---|---|---|---|---|---|---|---|
| B | S.E. | Wald | df | Sig. | Exp(B) | Lower | Upper | |
| Heart trouble? (1) | -.563 | .185 | 9.304 | 1 | .002 | .569 | .396 | .818 |
| Sex of Respondent (1) | -.748 | .189 | 15.604 | 1 | .000 | .473 | .327 | .686 |
| Body weight (Kg) | .023 | .006 | 13.821 | 1 | .000 | 1.023 | 1.011 | 1.036 |
| Leisure Activities (Mins/week) | -.001 | .000 | 3.258 | 1 | .071 | .999 | .998 | 1.000 |
| Anxiety Score (1985) | .020 | .046 | .187 | 1 | .665 | 1.020 | .932 | 1.116 |
| Depression Score (1985) | .029 | .048 | .363 | 1 | .547 | 1.029 | .937 | 1.131 |
| Constant | -2.060 | .438 | 22.139 | 1 | .000 | .127 | ||
This study selects nine variables from NLASS dataset which are possibly relevant to high blood pressure. After conducting appropriate and specific statistical analyses, heart_85, sex_85, wght_85, t_rlx_85, anx_85 and dep_85 are taken for the causes of hypertension. The result of this study partly confirms the experiences from previous researches. Furthermore, heart_85, sex_85, wght_85 have significant correlations with hi_bp_85 in the regression model. Therefore, employing these three variables can effectively predict the risk of suffering from high blood pressure in the future.