This study revealed that, on average, around 42% of men and 36% of women workers that reported P-SPH from the 15 countries could avoid it if all the groups received a high level of education, and that around 35% of men and 30% of women could avoid P-SPH if they had the working and employment conditions of the workers with non-manual skilled jobs. This magnitude of inequity among groups indicates the scale of the possible improvement in the countries, and demonstrates what is feasible for other social groups to attain.
The most privileged group had the best health and it would be desirable for the other groups to be equally healthy. Nevertheless, the results show that the widest range of P-SPH observed is among the reference (healthiest) groups in the different countries. Hence, it would also be desirable to lessen the gap between countries. For example, in education level, the most privileged group of women in Nicaragua (those whose level of education was high) showed a higher prevalence of P-SPH than the worst groups of women in Argentina, Colombia, Chile, Guatemala, and Uruguay (whose level of education was less than low). Likewise, by occupation, the most privileged group of women in Nicaragua and Honduras had a higher prevalence of P-SPH than the worst category in most of the countries in this study. This means that most of the workers in the least-favored occupational category in Uruguay or Chile are in better health than most of the workers in the most-favored occupational category in Honduras or Nicaragua.
Actually, the fact that some countries have low inequity indexes should not obscure the results since, overall, the higher the prevalence of P-SPH, the lower the inequity index. For example, Nicaragua’s and Honduras’ Keppel index values related to occupation are under 7% for women, and these two countries show the highest prevalence of P-SPH in the region, while Uruguay’s Keppel index is over 34% in the same category, even though it has the lowest P-SPH prevalence. In general, this means that inequity across social groups is low, but this is mainly because most of the working population reports P-SPH. Therefore, health conditions in those countries where more than one-third of the total working population reported P-SPH demand urgent intervention, with special focus on the most vulnerable groups, which in some countries reach a P-SPH prevalence of over 60%.
The worker´s health gaps among countries were bigger than those associated with differences in sex, age, education level, or occupation, suggesting that workers’ health is determined to a greater extent by the country where they work. Similar patterns of inequity are observed with diverse health indicators among the general population worldwide (20), supporting the idea that borders generate more inequality than any other variable and could be related to social, economic, and political factors but, most essentially, to international differences in regulations and laws (21). An alternative explanation could be ascribed to the methodologies used in the various countries’ surveys. It is known that there are differences among working-condition surveys (4), while health surveys are more standardized (22). However, in Central America, where the methodology was the same, we found a wide difference among countries’ prevalence of P-SPH, ranging from 19.5 in women from Guatemala to 50.4 in women from Nicaragua.
Regarding gender inequity, as many studies have shown (23), the prevalence of P-SPH in the overwhelming majority of the countries was higher in women (29% of women and 24% of men in LAC as a whole). This has also been found in Europe, where women over 16 years old reported 3.7% more P-SPH than men (30% of women and 26.3% of men). Regardless, the inequity gap was larger among men in the three equity stratifiers. The highest relative differences by sex were found in Chile, in which the prevalence in women was 85% higher than in men and the lowest differences were in Mexico, where P-SPH was 4.4% higher in women. Guatemala and Honduras were an exception; nevertheless, the prevalence of P-SPH was almost the same for both sexes. These results are probably influenced by cultural factors that these neighboring countries (Mexico, Guatemala, and Honduras) share and that are mainly linked to the beliefs and behavior related to gender roles (24). The patriarchal culture still predominates and exposes men to risk behaviors that could be detrimental to their health (25). Another possible explanation could be the high index of criminal violence and drug trafficking in these countries, which mainly affects men. The SPH could be influenced by differences in culture, ethnicity, and sex (26). To better understand these results, more studies of these possible influences are needed.
This study, as any other, has limitations, mainly related to the comparability of the data. The most recent national surveys on working conditions and health were used. We consider them to have the best and most reliable data available on SPH in each country. However, as the data come from different countries and therefore from different sources, the education categories may vary slightly between countries, as may the scale used to collect the SPH data. Thus, the comparison between countries must be made with caution. Though not all countries were included in this study because no data were found for Bolivia, Paraguay, Venezuela and others, the sample analyzed does represent most of the working population in the region. Finally, ethnic group was not used as an equity stratifier because the data were not included in all the countries‘ surveys. Nevertheless, to our knowledge, this is the first study to use large national datasets from LAC countries to study health inequity and provide the first cross-country comparisons of the health status in the working population. SPH has been shown to be a strong and independent predictor of mortality and strongly associated with morbidity (27), even demonstrating better reliability than objective measures of morbidity and psychological well-being in some studies (28).
The questionnaires used in each national survey were administered in face-to-face interviews at the workers’ homes (except in Puerto Rico, where the interviews were conducted by telephone), and the final datasets and results will ultimately be made available to the scientific community for future, high-quality studies, useful to researchers and policy makers alike. The micro-data used for this analysis are a small portion of the information available from the countries’ surveys. These data are not always accessible and, in many cases, the shift to open access takes several years. So, given the relevance of this information to the region, it is essential to allow access to this data to researchers from different fields and countries, as well to find mechanisms to ensure the comparability of questions and methodology among the countries’ surveys to allow comparison and monitoring of changes over time. The dissemination of these findings may contribute to planning, implementing, monitoring, and evaluating public policies.
This analysis may be a first step in monitoring occupational health inequity in the region, but periodic updates to track changes in working conditions over time and the progress of health improvements in closing the gaps among social groups will be essential. In this regard, strong national health monitoring systems are fundamental. To face this encouraging challenge, international and regional collaboration will be necessary.