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Most studies that have focused on the costs of obesity have ignored the direct effects of obesity-related patterns of diet and physical activity. This study reviews the full effects of each component--poor dietary and physical activity patterns and obesity--on morbidity, mortality and productivity. The direct healthcare costs are based on a review of the effects of these factors on key diseases and the related medical care costs of each disease. The indirect costs on reduced disability, mortality and sickness during the period of active labour force participation prior to retirement are also examined. A case study is prepared for China to provide some guidance in the utilization of this review for economic analysis of obesity. The case study shows that the indirect costs are often far more important than the direct medical care costs. The Chinese case study found that the indirect effects of obesity and obesity-related dietary and physical activity patterns range between 3.58% and 8.73% of gross national product (GNP) in 2000 and 2025 respectively.

This study fills a gap in the literature by providing an analysis of the daily water intake of middle-old and oldest-old adults. We found that the total water intake for the middle-old and oldest-old was significantly lower than that for the young-old. Future research needs to investigate the clinical outcomes associated with declining water intakes of community-dwelling older adults.

Poor sleep quantity and quality may predispose FI adults to adverse health outcomes.

Results. Individuals with body mass indexes (BMIs) of 35 kg/m 2 or above, those with BMIs of 30 to 34 kg/m 2 , and those with BMIs of 25 to 29 kg/m 2 had crude length-of-stay rates greater than those of normal-weight individuals. Association between BMI and length of stay varied over time.Conclusions. Obese individuals experience longer hospital stays than normalweight individuals. (Am J Public Health. 2004;94:1587-1591 ship. In most of these studies, data on weight and hospital use were collected concurrently, and in some, information regarding weight was actually collected after information regarding hospitalizations. [3][4][5][7][8][9][10] In addressing factors that are part of the causal pathway between obesity and hospitalization, prospective studies have included assessments of data on health conditions. 6,8 Statistical control of such health conditions (e.g., type II diabetes) constitutes overadjustment 11 ; studies including health conditions in their analyses have shown no effect of obesity, leading to the erroneous inference that obesity is not an important risk factor for hospitalization. 6,8 Our objective in this study was to estimate, by means of a longitudinal analysis, lengths of hospital stay among individuals categorized according to their weight status. Our data were derived from the First National Health and Nutrition Examination Survey (NHANES I) Epidemiologic Followup Survey (NHEFS). METHODS Survey DescriptionThe baseline for the NHEFS was NHANES I, conducted between 1971 and 1975. 12 In NHANES I, data were collected from a national probability sample of the United States civilian noninstitutionalized population, and the survey included a standardized medical examination and questionnaires covering various health-related topics. The NHEFS cohort consisted of 14 407 individuals who were aged 25 years or older at their baseline interview. A series of 4 follow-up surveys was conducted during 1982 through 1984 and in 1986, 1987, and 1992. Body Mass Index MeasurementRespondents' weight status was classified according to National Heart, Lung and Blood Institute (NHLBI) criteria. Body mass indexes (BMIs; weight in kilograms divided by height in meters squared) were calculated at baseline and categorized as follows: less than 18.5 kg/m 2 , 18.5 to 24.9 kg/m 2 , 25.0 to 29.9 kg/m 2 , 30.0 to 34.9 kg/m 2 , and 35 kg/m 2 or above (as described in the NHLBI guidelines). 13 Respondents with a BMI of 18.5 to 24.9 kg/m 2 were the reference group in the analysis. Women who were pregnant at baseline were excluded (n = 124). HospitalizationsNumber of inpatient hospitalization days was the outcome measure of interest. Respondents reported hospital admissions that occurred between their baseline and final interviews. Reports of hospital stays were elicited through a series of questions in the NHEFS interviews. Respondents were asked to report the dates of all overnight facility stays since their most recent interview. With respondents' permission, all reported facilities were contacted by mail and asked t...

ZIZZA, CLAIRE A., AMY HERRING, JUNE STEVENS, AND BARRY M. POPKIN. Obesity affects nursing-care facility admission among whites but not blacks. Obes Res. 2002;10:816 -823. Objective: This study examines whether obese individuals have a greater rate of nursing care facility admission than normal weight individuals. Research Methods and Procedures: Data from the National Health and Nutrition Examination Survey Epidemiological Follow-up Survey were analyzed. Cox proportional hazards models were used to examine the relationship between baseline weight status and subsequent time to first nursing home admission while adjusting for sex, age, race, marital status, height, presence of children, smoking status, education, region, urban residence, income, and physical activity. Results: Of 5960 adults 45 to 74 years old, 989 individuals were admitted to a nursing care facility over the subsequent 20 years. Body mass index (BMI) was studied using five categories: Ͻ 18.5, 18.5 to Ͻ25, 25.0 to Ͻ30, 30.0 to Ͻ35, Ն35 kg/m 2 . The effects of BMI differed by race: compared with those with a BMI of 18.5 to Ͻ 25 kg/m 2 , adults with a BMI Ն30 kg/m 2 or a BMI Ͻ18.5 kg/m 2 had a greater rate of nursing home admission in whites, whereas no relationship was found in blacks. The inclusion of time to death with nursing home admission as a joint outcome yielded similar results. Discussion: The large increase in the prevalence of obesity coupled with the rapid expansion of the number of older Americans will likely increase the demand for nursing facility use. More research is needed to understand differences in factors related to nursing home admission among ethnic groups.

We examined the association between food insecurity and total daily energy intakes in American men and women. We estimated the number of daily snacks and meals consumed by individuals in different food security categories. Also, we calculated the energy contribution, energy density, and food group sources of those snacks and meals. Using the 1999-2002 National Health and Nutrition Examination Survey (NHANES), we examined the Food Security Survey Module (FSSM) and dietary information from the 24-h recall. Differences in energy intakes between groups were not significant. Women who were food insecure without hunger (FIWOH) and food insecure with hunger (FIWH) had significantly fewer meals than food secure (FS) women. The energy contribution of each meal and the total energy contributed from snacking were both significantly greater for FIWOH women than for FS women. The number of meals was significantly lower whereas the daily number of snacking occasions and the total energy from snacking were significantly increased for FIWOH men relative to FS men. FIWOH men consumed snack foods that had significantly lower energy density than those consumed by FS men. Among men and women, the major sources of meal energy were the grain group, the meat, poultry, and fish group, and the sugar, sweets, and beverages group whereas the major source of snacking energy was the sugar, sweets, and beverages group. Total energy intakes were not different for FI individuals; however, their meal and snack behaviors were different. Focusing solely on total energy intake would miss important consequences of food insecurity.