Abstract
This chapter reviews mortality trends during the twentieth century in selected countries of Latin America and the Caribbean (LAC). The chapter focuses only on female and male mortality patterns over age 5 during the period 1900–2000. For some countries, we reconstruct the trajectory from very high mortality prevailing at the beginning of the century to high levels of life expectancy attained by the year 2000. For others, we are able to estimate trajectories starting in 1950. Somewhat surprisingly, current levels of life expectancies in some of these countries are lower than those experienced in high-income countries.
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Notes
- 1.
These theories are distinct from classificatory frameworks such as those proposed by Omran (1982) in that they explicitly seek identification of the ultimate causes of changes in mortality and morbidity regimes.
- 2.
Overstatement of ages in the population always leads to underestimates of the mortality rates provided that (a) the proportion overstating ages is invariant or increases with age and (b) the age distribution slopes downward as age increases. The effect of age overstatement of ages at death is not straightforward, since it depends on three factors: (a) the age-dependency of the proportion of deaths whose ages are overstated, (b) the magnitude of the downward slope of the age distribution at older ages, and (c) the magnitude of the upward slope of the force of mortality at older ages. In most countries of the regions, there are conditions that translate overstatement of ages at death into under (not over) estimation of mortality rates at older ages. If so, age overstatement of population and deaths will have offsetting effects and may actually lead to overstatement (not under) of mortality rates.
- 3.
In a companion paper (Palloni and Pinto 2004), we justify the choice of Bennet-Horiuchi methods as the one producing minimum errors over a variety of simulated conditions.
- 4.
Note that we are not requiring that the level of age misstatement be the same as the Costa Rican but only the age pattern.
- 5.
To save space, we only provide a brief evaluation based on tables and figures that are available on request from the authors.
- 6.
We used mortality rates due to TB for age groups 0–19, 20–39, 40–59, and 60+ with lags of 5 and 10 years. Rates were averaged over 5 and then over 10 years prior to the time for which we had the measure of model pattern deviation. We used pooled estimators of effects and in no case did we obtain a positive and significant effect of mortality rates due to TB and magnitude of the deviations. On the assumption that the observed deviation could be due to age overstatement and mortality rates due to TB, we also estimated a fixed effect model (that assumes that effects of age overstatement are invariant over time). But the expected patterns did not materialize.
- 7.
If α is held constant, sub-estimation of Mx produced by age overstatement should lead to overestimates of β. However, when both parameters are free to vary, the best linear fit is always achieved at the expense of a more negative value of α and an estimate of β that is smaller than one.
- 8.
- 9.
It will not go unnoticed that the trends in both groups of countries are almost linear, with a slight but noticeable decreased slope in the last 10 years among forerunners. The same applies to trends of life expectancy at age 60 (see Part VIII). These regularities, combined with the fact that the rate of decline in infant and child mortality has decreased in the last 10 years, imply that the trajectory of life expectancy cannot be linear but rather must follow a quadratic form. This goes against inferences made by Oppen and Vaupel (2002) from a pooled sample of life expectancies using a mixture of countries with wildly heterogeneous mortality regimes.
- 10.
The graph for males is omitted since it leads to the same conclusions.
- 11.
Estimates in the table are from pooled sample. Fixed effects models yield somewhat different values for the estimates but lead to the same conclusions and are not presented here. The addition of lag 2 (10 years) does not improve model fit and was ignored.
- 12.
If the category “ill-defined” had a distribution of cause of deaths proportional to the observed one, none of the inferences drawn before would change. There is no evidence to suggest that the observed distribution is unlike that of “ill-defined causes” and even less reason to assume that deaths categorized as ill-defined are attributable to causes that are difficult to diagnose. It is more likely that the ill-defined causes are composed disproportionately of deaths associated with mortality among the poorest segments of the population, namely, infectious diseases.
- 13.
The effect of education we are posing here is broader than and distinct from the effect usually identified in the literature that is reflected in the association between individual level of education and mortality. What we have in mind is that the aggregate level of education (in this case literacy) represents not just the average individual effects, but an added and more important influence of the strength of social institutions.
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Acknowledgment
This research was supported by National Institute on Aging grants R37 AG025216, R03 AG15673, and R01 AG18016. Research work for University of Wisconsin-Madison researchers is supported by core grants to the Center for Demography and Ecology, University of Wisconsin (R24 HD47873) and to the Center for Demography of Health and Aging, University of Wisconsin (P30 AG017266).
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Palloni, A., Pinto-Aguirre, G. (2011). Adult Mortality in Latin America and the Caribbean. In: Rogers, R., Crimmins, E. (eds) International Handbook of Adult Mortality. International Handbooks of Population, vol 2. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9996-9_5
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