Aging in Sub-Saharan Africa Recommendations for Furthering Research (2006) / Chapter Skim
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9. Interactions Between Socioeconomic Status and Living Arrangements in Predicting Gender-Specific Health Status Among the Elderly in Cameroon
9. Interactions Between Socioeconomic Status and Living Arrangements in Predicting Gender-Specific Health Status Among the Elderly in Cameroon
Pages 276-313
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From page 276... ...
has resulted in improvements in life expectancy. Recent estimates suggest that the aggregate proportions of the elderly population in sub-Saharan Africa will grow rather modestly as a result of continued high fertility in many countries, but the size of the elderly population is expected to increase by 50 percent, from 19.3 to 28.9 million people from 2000 to 2015 (National Research Council, 2001)
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From page 277... ...
The causes and consequences of aging in this region within and between countries are complex, multifactorial, and intertwined. Their study is difficult and demands an interdisciplinary approach, given the complexity of the interactions among social, economic, and environmental variables and their effect on health status and functional limitations.
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From page 278... ...
There are several plausible ways in which certain aspects of gender inequality, socioeconomic status, and living arrangements may influence health and functional status at older ages. For many of these influences, however, empirical studies are lacking that can confirm the importance of particular intermediate variables.
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From page 279... ...
In an area of approximately 274 sq km, this region combines the features of a highly modernized environment with a typical traditional Cameroonian society. The urban and semiurban localities of Bandjoun have one of the country's universities, three public hospitals, two private hospitals in operation since the early 1950s, about a dozen public health centers, several traditional healers attracting people from various social strata, several high schools and professional schools, infrastructures for communication and transportation, and entertainment sites.
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From page 280... ...
Variables N % N % N % Outcome Variables Self-Rated Health Excellent/very good/good/fair 474 77.3 227 84.1 247 72.0 Poor 139 22.7 43 15.9 96 28.0 Physical Functional Limitations No 309 50.4 167 61.9 142 41.4 Yes 304 49.6 103 38.1 201 58.6 Poor Health and Functional Limitations No 506 82.5 238 88.1 268 78.1 Yes 107 17.5 32 11.9 75 21.9 Exposure Variables Gender Female 343 56.0 -- -- -- -- Male 270 44.0 -- -- -- -- Level of Education None 452 73.7 133 49.3 319 93.0 Some education 161 26.3 137 50.7 24 7.0
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From page 281... ...
Economic Activity Status Paid work 162 26.4 108 40.0 54 15.7 Unpaid work 111 18.1 54 20.0 57 16.6 Retired/at home 253 41.3 70 25.9 183 53.4 Unemployed 87 14.2 38 14.1 49 14.3 Marital Status Single/widowed/divorced 218 35.6 31 11.5 187 54.5 Married polygamous 211 34.4 109 40.4 102 29.8 Married monogamous 184 30.0 130 48.1 54 15.7 Age at First Marriage (continuous variable) Mean = 23.2 SD = 8.68 Mean= 29.15 SD = 9.26 Mean = 18.33 SD = 3.71 Kinship Size Less than 6 348 56.8 150 55.6 198 57.7 6 or more 265 43.2 120 44.4 145 42.3 Age Cohort (in years)
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From page 282... ...
For most studies, odds ratios for subsequent mortality ranged from 1.5 to 3.0 among individuals reporting poor health compared with those reporting excellent health. Self-reported health has been demonstrated in longitudinal studies to predict the onset of physical disability and functional or activity limitations (Farmer and Ferraro, 1997; Ferraro, Farmer, and Wybraniec, 1997; Idler and Benyamini, 1997; Idler and Kasl, 1995; Mor et al., 1989; Wilcox, Kasl, and Idler, 1996)
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From page 283... ...
We also created a third outcome variable measuring the simultaneous reporting of poor health and functional limitations coded 1 if an elderly person reported as being in poor health also had a limitation in activity and 0 otherwise. Methods of Analysis The methods of data analysis in this paper include the description of variables, followed by an examination of the association between each risk or protective factor and the three outcome variables (bivariate analyses)
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From page 284... ...
Living arrangements are empirically assessed using three indicators: marital status by type of union, timing of first marriage in the life cycle, and family size support network. The effects of gender, socioeconomic status, and living arrangements on self-reported health and physical functional limitations are estimated with logistic regression models.
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From page 285... ...
individuals age 50 or older and 6 (1.9 percent) individuals age 65 or older, and functional limitations were missed in 14 (2.2 percent)
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From page 286... ...
Notwithstanding a few nonsignificant differences in kinship size and region of residence, all other differences in postulated risk and protective factors of poor health and activity limitations are statistically significant. In particular, these bivariate analyses show that significantly higher proportions of female respondents report being in poor health, having functional limitations, or both than male respondents.
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From page 287... ...
Covariates of Poor Health Table 9-3a presents the estimated odds ratios for the effects of postulated covariates on the probability of reporting poor health, functional limitations, or both. Poor perceived health is associated with low socioeconomic status (i.e., no/lower educational attainment, no labor force participation)
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From page 288... ...
P < 0.01 P < 0.05 P < 0.01 50-64 16.6 11.7 20.2 65-75 28.1 17.3 34.0 75-96 29.3 21.1 39.1 Main Region of Residence P < 0.05 NS NS Djaa/Pete/Yom 26.3 19.2 30.4 Demdeng/Sedembom/Haa 25.6 18.4 31.8 Djiomghouo/Famleng/Tsela 20.9 14.0 26.4 Tsela/Famla II/Bagang Fodji 13.1 10.2 16.7 stantiate that gender differences in self-reported health among the elderly in Cameroon are entirely explained by their socioeconomic status. The data show that there appears to be a dose-response gradient in the odds ratios for poor health across levels of socioeconomic indicators.
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From page 289... ...
However, when the activity limitations are included in the model, no statistically significant difference is found between workers and nonworkers. This finding may suggest that the observed significant advantage of workers compared with nonworkers may be a reflection of the healthy worker effect.
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From page 290... ...
50-64 0.50* 65-96 1.00 Main Region of Residence Djaa/Pete/Yom 1.00 Demdeng/Sedembom/Haa 0.72 Djiomghouo/Famleng/Tsela 1.03 Tsela/Famla II/Bagang/Fodji 0.45§ Functional Limitations No Yes -2Loglikelihood 643.45 646.90 641.14 624.74 634.08 635.38 Model Chi-square 12.86 9.41 15.17 31.57 22.23 20.93 (df)
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From page 291... ...
(13) than 1.5 times as likely to assess their health as poor compared with those in monogamous marriages (model 5)
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From page 292... ...
A useful way of looking at the interactions of gender with socioeconomic status and living arrangements in predicting health and functional status is to carry out separate analyses by gender for those postulated factors. Table 9-3b presents the gender-specific estimated odds ratios for the effects of the postulated covariates on the probability of reporting poor health, functional limitation, or both.
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From page 293... ...
As in the case with self-rated health, gender differences exist in functional limitations, with older women at least twice as likely to have activity limitations as older men. Unlike the case with self-rated health, the effects of gender remain robust to all controls, so that the most complete model (Model 12)
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From page 294... ...
Similarly, older people who are working are less likely to report having functional limitations; in contrast, those "at home" or retired are more likely to have functional limitations. As the gender-specific models show, the disadvantage associated with being "at home" is mainly a female disadvantage (see Table 9-4b, Models 1, 4, 6, and 7)
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. Any residual effect of polygamy on the probability of reporting functional limitations is captured by socioeconomic status (see Models 8 and 11)
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From page 296... ...
Finally, the effects of region of residence emerge strongly, with respondents from all rural regions reporting fewer functional limitations than urban and semiurban dwellers from Pete, Djaa, and Yom. Table 9-4b shows the gender-specific odds ratios of covariates of functional limitations, so their interactions with gender can be assessed.
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Regional differences in functional limitations are statistically noticeable only among elderly women. Overall, there are significant interactions among gender, socioeconomic status, and
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In sum, gender differences in activity limitations are apparent, with older women being at least twice as likely to report functional limitations as older men. Here, these differences remain robust to controls to all postulated risk and protective factors.
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From page 299... ...
men. The effects of socioeconomic status are also quite robust, showing that low socioeconomic status is associated with functional limitations, just like substandard living arrangements in the study context (being widowed/ single/divorced elderly or living in polygamous marriages)
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As in the case of self-reported health, these gender differences are entirely explained by socioeconomic status (Model 7, Table 9-5a) and not by living arrangement TABLE 9-5a Odds Ratios for Influences of Gender, Socioeconomic Status, and Living Arrangements on Poor Health with Functional Limitations of Older Cameroonians Variables Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Gender Female 1.00 Male 0.48*
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. The influences of socioeconomic status on poor health with functional limitations are present (Model 2, Table 9-5a)
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From page 302... ...
The health disadvantage of widowhood remains strong, and to some extent older people in polygamous marriages tend to report being in poor health with functional limitations. As in Tables 9-3a and 9-3b, gender explains the effects of being in polygamous marriages on the odds of reporting poor health with activity limitations (see Models 3 and 8, Table 9-5a)
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From page 303... ...
As in previous models, the younger the age at first marriage, the higher the odds of reporting poor health with functional limitations (Models 8 and 11, Table 9-5a) but the significance of such a relationship is largely restricted to older women (Models 2 and 5-7, Table 9-5b)
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From page 304... ...
The influences of socioeconomic status on poor health and functional limitations are mediated at least partly through age and the socioeconomic context of communities of residence. The disadvantage associated with widowhood is unaltered, and gender inequality explains the deleterious effects of living in polygamous unions on self-assessed health and functional status.
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From page 305... ...
These factors appear to exert independent effects on self-rated health and functional limitations in most instances. Overall, there are significant interactions among gender, socioeconomic status, and living arrangements in predicting poor health, functional limitations, or both.
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From page 306... ...
. Similarly, older women tend to report being in poor health with functional limitations more than men, but the female disadvantage again is entirely explained by differences in their socioeconomic status relative to older men.
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From page 307... ...
In contrast, age at marriage has a trivial effect on older men's health and functional status. Since early marriage is associated with high fertility, which in turn is strongly correlated with short birth intervals, it is likely that the effects of age at marriage on poor health and functional limitations at older ages operate through the maternal depletion syndrome, which has been well documented in the literature on women's health in Cameroon (KuateDefo, 1997)
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From page 308... ...
are significantly less likely to report poor health, before controlling for functional limitations (odds ratio of 0.58, p < 0.05)
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From page 309... ...
. Measures of social deprivation are appropriate for assessing health differences among those living in absolute poverty.
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From page 310... ...
Coordination of public and clinic policies relevant to health promotion and disease prevention among the elderly is essential if these policies are to have the desired positive effects on the health status of older people. Again, the most effective means of obtaining the information necessary for such crossnational research is representative household surveys of older people, like the CFHS panel surveys, which so far have been fielded in 140 localities in western and northwestern Cameroon.
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From page 311... ...
. Symptom sensitivity and sex differences in physical morbidity: A review of health surveys in the United States and the Netherlands.
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From page 312... ...
. Gender differences in adult health: An international comparison.
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From page 313... ...
. Educational attainment and tran sitions in functional status among older Taiwanese.
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