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Table 3 Coefficients from the logit regression on probability of functional limitation

From: Impact of socioeconomic status and medical conditions on health and healthcare utilization among aging Ghanaians

Variables

  
 

Model 1

Model 2

Model 3

Model 4

Model 5

Age

.1327[.1060]

.0670 [.1020]

.0301[.1038]

.0398 [.1031]

.0358 [.0991]

Age2

-.0006[.0007]

-.0002 [.0007]

.0000 [.0007]

-.0000 [.0007]

-.0000 [.0006]

Married

-.3863*** [.0909]

-.3464 *** [.0898]

-.2767 *** [.0879]

-.2611*** [.0919]

-.2418 *** [.0924]

Akan

-.0179 [.1274]

-.0520 [.1224]

-.0272 [.1165]

-.0477 [.1186]

.0172 [.1160]

Hypertension

 

.1995*** [.0927]

.1838** [.0927]

.1733* [.0931]

.1992** [.0925]

Diabetics

 

.1370[.2256]

.0667 [.2229]

.0811[.2236]

.1150 [.2182]

Angina

 

.05157 [.3008]

.0878 [.3007]

.0854 [.2863]

.1048 [.2826]

Arthritis

 

.6874***[.1251]

.5315***[.1245]

.5385***[.1230]

.4836***[.1242]

Stroke

 

1.1707 *** [.2434]

1.0579*** [.2300]

1.0555*** [.2341]

1.0228*** [.2368]

Visual Impairment

 

.5355*** [.0991]

.4805*** [.0957]

.4770*** [.0967]

.4579 *** [.0967]

Obese

 

.0903 [.1923]

.3608* [.1973]

.3557* [.1933]

.3691** [.18967]

Memory

  

.4933*** [.1189]

.4958*** [.1187]

.4939*** [.1213]

Visual diff

  

.4573*** [.1244]

.4490*** [.1249]

.4489*** [.1242]

Sleep diff

  

1.0132*** [.1236]

1.003*** [.1224]

.9911*** [.1226]

Employment status

   

.0697 [.1392]

.0484 [.1371]

Low income

   

.2959** [.1504]

.3334** [.1486]

High income

   

.2810* [.1653]

.3529** [.1675]

Higher income

   

.0505 [.1593]

.1594 [.1629]

Highest income

   

-.0007 [.1697]

.1600 [.1769]

Urban/rural

   

-.1056 [.1313]

-.1042 [.1305]

Illiteracy

    

.0636 [.1112]

Social class

    

-.3813*** [.1132]

Observation

2142

2142

2142

2142

2142

F-statistic

17.87

15.55

18.56

14.79

13.50

D.F

213

213

213

213

213

Prob > F

0.0000

0.0000

0.0000

0.0000

0.0000

  1. Note: ***, ** and *indicates1%, 5% and 10% significance level respectively.
  2. Firstly, ageing Ghanaians experience significantly poorer self-rated health after controlling for married Ghanaians as a predisposing factor (model 1). This is because many are on low incomes and possibly living in rural settings where public utilities are difficult to access and hence worse health state. After controlling for chronic illness, the effect of diabetes, angina and visual impairment, statistically significantly influence on self-rated health (model 2) which implies that the differential exposure of ageing Ghanaians to these chronic conditions cannot explicitly explain gender differences. Interestingly, as we continue to control for functioning assessment.
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BMC Public Health

ISSN: 1471-2458

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