Results
Among all eight indigenous communities, 35% of the total population surveyed had experienced musculoskeletal pain during the previous seven days, and 45% had experienced such pain at some point during their lifetimes.
The most prevalent rheumatic diseases among this population—61% female—were low back pain and osteoarthritis, 13.3% and 9.7%, respectively. These were followed by rheumatic regional pain syndromes (5.9%), rheumatoid arthritis (1.3%), undifferentiated arthritis (0.2%) and spondyloarthritis (0.1%). Overall prevalence and prevalence for individual conditions varied widely by community.
Prevalence of comorbidities included 17.5% with obesity, 16% with depression, 13.7% with high blood pressure, 13.3% with gastritis, 6.8% with type 2 diabetes mellitus and 4.9% with peripheral vascular disease.
Prevalence of behavioral health issues included 22.5% reporting drinking alcohol and 13.3% reporting smoking.
Current physical limitations due to rheumatic diseases impaired 15.5% of respondents, and 9.7 “were not coping with discomfort,” according to the report.
But there were large differences in these findings among the eight communities. For example, 65.3% of both the Mixteco and Chontal communities reported historical pain, compared with 14.7% of the Raramuri.
“This is a population that really needs to be targeted with interventions on the prevention level, as well as treatment,” says Dr. Callahan. “Thirty-three percent have no healthcare at all. And some [entire communities] had no healthcare.”
“Only 3% reported having complete social insurance [i.e., insurance that covers all necessary health-related expenses],” according to the report. Despite the fact that 59.8% were covered by some form of national health insurance, “… only half of participants reported seeking medical care to manage their [rheumatic disease], and 40.6% have never sought medical or traditional treatment despite the high prevalence of severe [musculoskeletal] pain, disability and poor coping.”
Network Analysis
The investigators used network analysis to examine the relationship between socioeconomic and clinical variables. (See https://ard.bmj.com/content/77/10/1397.full.) The network analysis confirmed that rheumatic diseases are complex, chronic and often associated with other disease, says principal investigator Ingris Peláez-Ballestas, MD, PhD, researcher in medical sciences, General Hospital of Mexico, Mexico City. She adds that these conditions harm people—especially indigenous people—socioeconomically, in part because geographical and linguistic challenges, as well as economic limitations often put medical care out of their reach.
“Non-inflammatory [musculoskeletal] disorders … are associated with high physical demand, overweight and obesity, and pose a risk of accelerating degenerative process of the joints,” according to the report. “This is further exacerbated by healthcare inequity, fragmented healthcare systems and high vulnerability of the population, which is true for many indigenous communities in countries lacking public health strategies to prevent or reduce disability.”
Thus, these conditions—both physical and socioeconomic—undermine ability to work. That’s doubly harmful because work is fundamental to sense of self within these indigenous communities, says Dr. Peláez-Ballestas.
Not surprisingly, Dr. Callahan notes that of the myriad variables in this analysis, working had the greatest “authority.” Authority is a function of the number of people to whom a variable applies—who work, for example—and the number of connections that variable has to other variables. For example, rheumatic diseases result in varying degrees of disability—a variable to which work is strongly connected in the network analysis—as it is to smoking, to alcoholism, to “other comorbidities,” and to other rheumatic and medical conditions.
One of the beauties of the network analysis is that it raises new questions. “Do people with back pain drink more?” says Dr. Gastelum-Strozzi. The network analysis shows a strong connection between the two variables. But, he adds, to confirm a hypothesis, one must do a study.
Another advantage of the network analysis is that it can identify oft-differing challenges faced by different communities of indigenous people. “That allows us to design tailored community-based interventions,” says Dr. Peláez-Ballestas.
