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JOURNAL ARTICLE
RESEARCH SUPPORT, N.I.H., EXTRAMURAL
RESEARCH SUPPORT, NON-U.S. GOV'T
RESEARCH SUPPORT, U.S. GOV'T, NON-P.H.S.
Determining osteoporosis risk in older Colono adults from rural Amazonian Ecuador using calcaneal ultrasonometry.
OBJECTIVE: Low bone density and osteoporosis prevalence, while well-documented in wealthy nations, are poorly studied in rural, non-clinical contexts in economically developing regions such as Latin America. This study contributes preliminary osteoporosis risk data for a rural Colono (mestizo) population from Amazonian Ecuador.
METHODS: Anthropometrics were collected for 119 adult participants (74 females, 45 males [50-90 years old]). Heel bone density and T-scores were recorded using calcaneal ultrasonometry
RESULTS: Approximately, 33.6% of the participants had low bone density and were at high-risk for osteoporosis. Four times as many females as males were considered high-risk. Consistent with epidemiological literature, advancing age was significantly associated with lower bone density values (P = 0.001).
CONCLUSIONS: Low bone density and osteoporosis prevalence are expected to increase in this and other economically transitioning populations, yet infrastructure to monitor this changing epidemiological landscape is almost non-existent. Human biologists are uniquely positioned to contribute data from remote populations, a critical step toward initiating increased resource allocation for diagnosis and prevention.
METHODS: Anthropometrics were collected for 119 adult participants (74 females, 45 males [50-90 years old]). Heel bone density and T-scores were recorded using calcaneal ultrasonometry
RESULTS: Approximately, 33.6% of the participants had low bone density and were at high-risk for osteoporosis. Four times as many females as males were considered high-risk. Consistent with epidemiological literature, advancing age was significantly associated with lower bone density values (P = 0.001).
CONCLUSIONS: Low bone density and osteoporosis prevalence are expected to increase in this and other economically transitioning populations, yet infrastructure to monitor this changing epidemiological landscape is almost non-existent. Human biologists are uniquely positioned to contribute data from remote populations, a critical step toward initiating increased resource allocation for diagnosis and prevention.
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