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[SPSS] The study on the factors of High Blood Pressure in population over 65 years old.

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NLSAA_Hypertension

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

What is NLSAA

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.

Research Aim

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.

Potential Factor & Research Methods

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

Binary Logistic Regression

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

Result

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.

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