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The objectives of this paper are to predict life years lost associated with obesity-related diseases (ORDs) for U.S. non-smoking adults, and to examine the relationship between those ORDs and mortality. Data from the National Health Interview Survey, 1997–2000, were used. We employed mixed proportional hazard models to estimate the association between those ORDs and mortality and used simulations to project life years lost associated with the ORDs. We found that obesity-attributable comorbidities are associated with large decreases in life years and increases in mortality rates. The life years lost associated with ORDs is more marked for younger adults than older adults, for blacks than whites, for males than females, and for the more obese than the less obese. Using U.S. non-smoking adults aged 40 to 49 years as an example to illustrate percentage of the life years lost associated with ORDs, we found that the mean life years lost associated with ORDs for U.S. non-smoking black males aged 40 to 49 years with a body mass index above 40 kg/m2 was 5.43 years, which translates to a 7.5% reduction in total life years. White males of the same age range and same degree of obesity lost 5.23 life years on average – a 6.8% reduction in total life years, followed by black females (5.04 years, a 6.5% reduction in life years), and white females (4.7 years, a 5.8% reduction in life years). Overall, ORDs increased chances of dying and lessened life years by 0.2 to 11.7 years depending on gender, race, BMI classification, and age. [ABSTRACT FROM AUTHOR]

In the absence of reliable systems for registering rare types of vital events large surveys are required to measure changes in their rates. However some events such as maternal deaths are widely known about in the community. This study examined the utility of asking respondents about events in their neighbourhood as an efficient method for measuring relative rates of rare health events such as maternal and infant deaths. A survey was conducted in the health and demographic surveillance system (HDSS) in Matlab, Bangladesh, which includes two areas with different health care regimes. Adult women were asked about any maternal deaths; multiple births; infant deaths, live births and some other events they knew of in a small specified area around their home. Agreement between HDSS records and survey responses was moderate or better (kappa≥0.44) for all the events and greatest for maternal deaths (kappa = 0.77) with 84% being reported. Most events were more likely to be reported if they were recent (p<0.05). Infant mortality rate in one area was 0.56 times that in the other which was well reflected by the ratio of survey results (0.53). Simulations were used to study the ability of the method to detect differences in maternal mortality ratio. These suggested that a sample size around 5000 would give 80% power to detect a 50% decrease from a baseline of 183 which compared well with an estimated sample size around 10 times larger using the direct sisterhood method. The findings suggest that the Neighbourhood Method has potential for monitoring relative differences between areas or changes over time in the rates of rare demographic events, requiring considerably smaller sample sizes than traditional methods. This raises the possibility for interventions to demonstrate real effects on outcomes such as maternal deaths where previously this was only feasible by indirect methods. [ABSTRACT FROM AUTHOR]