Dietary assessment can be based on pattern recognition rather than recall.

Diet is the leading predictor of health status, including all-cause mortality, in the modern world, yet is rarely measured; whereas virtually every adult in a developed country knows their approximate blood pressure, hardly any knows their objective diet quality. Leading authorities have called for the inclusion of nutrition in every electronic health record as one of the many remedial steps required to give dietary quality the routine attention it warrants. Existing tools to capture dietary intake are based on either real-time journaling or recall. Journaling, or logging, is time and labor intensive. Recall is notoriously unreliable, as humans are notably bad at remembering detail. Even allowing for the challenge of recall, these dietary intake methods are labor and time intensive, and require analysis at the n-of-1 level. We hypothesize that dietary intake assessment can be "reverse engineered"-predicating assessment on the recognition of fully formed dietary patterns-rather than endeavoring to assemble such a representation one food, meal, dish, or day at a time. This pattern recognition-based method offers potential advantages over existing methods, including speed, efficiency, cost, and applicability. We have developed and provisionally tested such a system, and the results thus far support our hypothesis. We are convinced that leveraging pattern recognition to make dietary assessment quick, user-friendly, economical, and scalable can allow for the conversion of dietary quality into a universally measured and routinely managed vital sign. In this paper, we present the supporting case.

Health risk behaviors and health perceptions in the Peruvian Amazon.

Behavioral health risk factor and health belief data for the indigenous population of the Peruvian Amazon are unavailable. Therefore, we conducted structured interviews of adults living in 5 towns in the remote Amazon region of Peru. Respondents (n = 179) were 67% women with a mean age of 35.4 years. The average household size was 6.7 people. A majority (72%) were unable to see a doctor when needed because of lack of money and distance. Only 6% reported excellent health, and nearly half (49%) reported fair health. Forty-eight percent drank alcohol and 73% smoked. Only 34% thought mosquitoes cause malaria, but 98% were using mosquito nets. In conclusion, our findings indicate the indigenous population of the Peruvian Amazon has limited access to basic health care. Although most of those surveyed use mosquito netting, few know that mosquitoes transmit malaria. Tobacco and alcohol use are major behavioral health risk factors.

An integrated residency in internal and preventive medicine.

The importance of preventive and population-based principles in clinical practice is widely acknowledged. The challenge of imparting these principles in either undergraduate or postgraduate medical education has, however, not been fully met. The necessary skills are provided comprehensively by preventive medicine residency programs, but at the expense of clinical training. Sequential residencies in primary care and preventive medicine, the currently available means of obtaining thorough preparation in both clinical and population-based principles, represent an inefficient, generally unappealing, and non-integrated approach. In response to these concerns, and in an effort to make preventive medicine training appeal to a wider audience, the authors developed and implemented a residency program fully integrating internal and preventive medicine. The program meets, and generally exceeds, the requirements of both specialty boards over a four-year period. The program provides extensive training in clinical, preventive, and public health skills, along with case management and cost-effective care, conferring the MPH degree and leading to dual board eligibility. The model is ideally wed to the demands of the modern health care environment in the United States, is extremely attractive to applicants, and may warrant replication both to train academic and administrative leaders and to raise the standards of preventive and public health practice in primary care.

Dietary fat consumption in a cohort of American adults, 1985-1991: covariates, secular trends, and compliance with guidelines.

PURPOSE: To examine compliance with the guideline for dietary fat (i.e., 30% of total daily colonies) and covariates of fat intake in a cohort of adults using both 24-hour recall and food frequency questionnaire (FFQ). DESIGN: Prospective, observational cohort study over 5 years. SETTING: Community-based sample in Reno, Nevada. SUBJECTS: Equal numbers of male and female, lean and overweight adults (n = 508), recruited from 1985 to 1986, of whom 348 completed all relevant surveys. MEASURES: Subjects underwent repeated anthropometric measures and completed extensive surveys on diet, weight cycling, lifestyle, and physical activity. RESULTS: Mean fat intake by 24-hour recall declined from 36.9% to 33.6% of calories between years 1 and 5 (p < .001), while calorie intake increased (p = .2). As measured by FFQ at year 2, mean fat intake was 39.1% of calories, and only 11.8% of subjects were in compliance with the guideline for dietary fat intake. Fat intake by FFQ at year 2 was statistically higher than by 24-hour recall in year 1 for lean women (p = .02) and lean men (p = .02), but not for the overweight of either gender, and was significantly higher than the year 5 24-hour recall for all categories of gender and weight (p < .001). Calorie intake, gender, and body mass index were significant in regression models that explained less than 10% of total variability in fat intake (r2 = .08; p < .01). CONCLUSIONS: Compliance with the nationally recommended level of dietary fat intake was poor in this cohort, especially as measured by FFQ. Variability in fat intake was largely unexplained by host characteristics, including education. Further study is required to corroborate secular trends in population fat intake, elucidate the determinants of such intake, and identify cost-effective strategies for reducing the consumption of dietary fat.