Frans Willekens

Obesity in adulthood and its consequences for life expectancy: a life-table analysis.

Context Middle-aged adults who are overweight or obese may have shorter life expectancies than normal-weight adults, but how much shorter? Contribution This analysis of data from the Framingham Heart Study from 1948 to 1990 showed that, on average, adults who were obese (body mass index [BMI] 30 kg/m2) at age 40 years lived 6 to 7 years less than their normal-weight counterparts. Adults who were overweight (BMI, 25 to 29.9 kg/m2) and did not smoke lived about 3 years less than normal-weight nonsmokers. Adults who were obese and smoked lived 13 to 14 years less than normal-weight nonsmokers. Cautions Descriptions of lost life expectancy do not necessarily predict length of life that could be gained from obesity prevention or treatment programs. The Editors The increasing prevalence of overweight and obesity, coupled with their associations with death, disability, and disease, has led to their identification as a major, potentially preventable cause of premature morbidity and death (1-9). However, it is difficult to estimate the public health impact of overweight and obesity because of complex interactions with age; smoking; and obesity-related risk factors, such as diabetes, hypertension, and lipid disorders (8, 10-12). The observed relationship between body mass index (BMI) and mortality has been described as J-shaped; mortality increases as a result of underweight, overweight, and obesity. However, preexisting illness and inadequate control of smoking may cause at least part of the increased mortality at very low weight (8). Consequently, there have been no robust estimates of life expectancy lost as a result of obesity. A primary reason is the lack of understanding of probable, healthy, or unhealthy weight trajectories over the life course. Conclusions regarding appropriate weight trajectories between adulthood and older age are complicated by uncertainties about age-appropriate measurements of obesity and the effects of smoking, obesity-associated risk factors for cardiovascular disease, and unintended weight loss (13, 14). We provide an estimate of the effect of obesity and overweight in adulthood on life expectancy, implicitly taking into account the various possible weight trajectories throughout the life course. We take advantage of the cohort follow-up made available by the Framingham Heart Study to analyze the differences in life course for various BMI groups. We make no assumptions about the relationship between BMI and mortality at older ages. Our primary objective was to analyze the reductions in life expectancy associated with overweight and obesity at 40 years of age. Methods Data Source The Framingham Heart Study is a longitudinal study with excellent follow-up on mortality. The original study cohort involved 5209 adults, age 28 through 62 years, residing in Framingham, Massachusetts, between 1948 and 1951 (15). To examine the effect of overweight and obesity in adulthood, we used the data from more than 40 years of follow-up (examinations 1 through 21) on age at death for persons 30 through 49 years of age at baseline (n = 3607). Height and weight were measured at baseline (7, 15). Smoking status at baseline was defined categorically as self-reported current smoker or nonsmoker. No information was available on smoking status before study entry. Information on all three variables was available for 3582 participants (99%). Because the relationship between weight and mortality is affected by underlying disease (8, 14, 16), we excluded participants who had cardiovascular disease (17) at baseline or died within 4 years of follow-up (63 participants, including 50 deaths). Because our analysis focused on the risk for death associated with overweight and obesity, we also excluded 62 underweight persons (BMI < 18.5 kg/m2). The final analyses involved 3457 participants (1550 men and 1907 women). We analyzed the effect of potential confounders on the relationship between obesity and mortality (6, 8, 18). Of the 3457 participants examined, hypertension and diabetes status was available for all participants, and physical activity level was available for 2893 (84%) participants. Total serum cholesterol level was available for 2127 (62%) participants and was therefore not taken into account. We defined hypertension at baseline as either systolic blood pressure of 160 mm Hg or greater or diastolic blood pressure of 95 mm Hg or greater in two repeated measurements. Physical activity (a continuous index derived from hours of activity and rest) was not available until examination 4 (approximately 8 years after baseline). Level of education at baseline was available for 3350 (97%) participants. Potential confounders were analyzed by using only complete cases. BMI Group Classification Body mass index at baseline was calculated as weight in kg/height in m2. We defined three BMI categories based on World Health Organization guidelines (2): group I (normal weight), BMI of 18.5 to 24.9 kg/m2; group II (overweight), BMI of 25 to 29.9 kg/m2; and group III (obese), BMI greater than or equal to 30 kg/m2 (including 19 people with BMI > 40 kg/m2). Survival Analysis We used S-Plus 2000 (MathSoft, Inc., Seattle, Washington) for all statistical analyses. Survival curves for each BMI group were compared by using KaplanMeier plots. We assessed the association between BMI group at baseline and mortality over the 40 years of follow-up by using Cox proportional-hazards analysis, with age as the time scale. The effect of BMI was analyzed separately within strata defined by sex and smoking status at baseline. We tested the proportionality of hazards assumption by analysis of the Schoenfeld residuals (19, 20). Statistical significance was set at the 5% level. Life Course Analysis Within each stratum, we estimated age-specific mortality rates for each BMI group by using Poisson regression analysis; age at follow-up and BMI group at baseline were categorical variables. Although the hazard ratios estimated for BMI group from this analysis are equivalent to those estimated from the Cox analyses, Poisson regression also optimizes the hazard associated with each age at follow-up. Life tables were derived for each BMI group, representing populations that were 40 years of age and free of cardiovascular disease at study entry. Conversions between mortality rates and probabilities assumed that within each single age interval, the hazard is constant. The life expectancy at 90 years of age was assumed to be a constant 4.53 for men and 5.05 for women for each BMI group (based on life expectancies of the total Framingham Study sample [21]). The main outcome measure, life expectancy at 40 years of age, was calculated as the mean age at death within a life-table population. Confidence intervals for the life table measures were calculated by using a bootstrap procedure, based on 10 000 replicates. We report the bootstrap biascorrect, adjusted 95% CIs (using the bias-corrected accelerated percentile interval algorithm) (22). Although computationally demanding, the bootstrap procedure is easier than an analytical alternative that includes both the variance of the Poisson model and the variance of the life table. Role of the Funding Source The Framingham Heart Study was conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with the Framingham Heart Study Investigators. The NHLBI reviewed this article for scientific content and consistency of data interpretation with previous Framingham Heart Study publications; significant comments were incorporated into the text before submission for publication. The NHLBI had no role in the design, conduct, analyses, and reporting of the study or in the decision to submit the manuscript for publication. The Netherlands Heart Foundation and the Netherlands Organization for Scientific Research funded our study. Neither had any role in the design, conduct, analyses and reporting of the study or in the decision to submit the manuscript for publication. Results The characteristics at baseline within the Framingham Study cohort were generally as expected: The probability of death increased with each higher category of BMI group, the relationship between the prevalence of smoking and BMI group was inverse (Table 1), and age generally increased with each higher category of BMI group (7, 8, 23). Although male nonsmokers were a small group and may represent an unusual cohort for that time, they were analyzed in the same way as the other groups. We did this because male nonsmokers had BMI-related risks similar to those of female nonsmokers and to findings in previous studies examining the relationship between BMI and mortality. Table 1. Characteristics of Original Framingham Heart Study Participants, Age 30 to 49 Years at Baseline (19481951) BMI and Survival With participants categorized by BMI at baseline, we used Cox proportional-hazards analysis to determine the relative rate of death over the 40 years of follow-up. We found that sex did not significantly modify the effect of BMI but that smoking status at baseline did, as has been previously described (10, 12, 24, 25). Additional analyses were performed separately for strata defined by sex and smoking status at baseline. The Figure illustrates the empirical survival curves for each BMI group within each of the four strata: female nonsmokers, female smokers, male nonsmokers, and male smokers. The survival disadvantage associated with BMI group II compared with BMI group I is apparently smaller in smokers than in nonsmokers. The hazard ratios for mortality associated with BMI group were generally consistent between strata, although neither male nor female smokers in BMI group II showed an increased mortality risk (Table 2). The proportional hazards assumption seemed appropriate for BMI, both by analysis of the Schoenfeld residuals and by comparison of the Cox- derived hazard ratios for two distinct follow-up periods with approximately

Smoking Kills, Obesity Disables: A Multistate Approach of the US Health and Retirement Survey

Increasing BMI causes concerns about the consequences for health care. Decreasing cardiovascular mortality has lowered obesity‐related mortality, extending duration of disability. We hypothesized increased duration of disability among overweight and obese individuals. We estimated age‐, risk‐, and state‐dependent probabilities of activities of daily living (ADL) disability and death and calculated multistate life tables, resulting in the comprehensive measure of life years with and without ADL disability. We used prospective data of 16,176 white adults of the Health and Retirement Survey (HRS). Exposures were self‐reported BMI and for comparison smoking status and levels of education. Outcomes were years to live with and without ADL disability at age 55. The reference categories were high normal weight (BMI: 23–24.9), nonsmoking and high education. Mild obesity (BMI: 30–34.9) did not change total life expectancy (LE) but exchanged disabled for disability‐free years. Mild obesity decreased disability‐free LE with 2.7 (95% confidence limits 1.2; 3.2) year but increased LE with disability with 2.0 (0.6; 3.4) years among men. Among women, BMI of 30 to 34.9 decreased disability‐free LE with 3.6 (2.1; 5.1) year but increased LE with disability with 3.2 (1.6;4.8) years. Overweight (BMI: 25–29.9) increases LE with disability for women only, by 2.1 (0.8; 3.3) years). Smoking compressed disability by high mortality. Smoking decreased LE with 7.2 years, and LE with disability with 1.3 (0.5; 2.5) years (men) and 1.4 (0.3; 2.6) years (women). A lower education decreased disability‐free life, but not duration of ADL disability. In the aging baby boom, higher BMI will further increase care dependence.

Understanding the Interdependence Between Parallel Careers

“Scientific inquiry is concerned not only with discovering quantitative relations between variables, but also with interpreting these relations in terms of underlying causal mechanisms that produced them. Without a knowledge of these mechanisms, we cannot predict how variables will co-vary when the structure of the system under study is altered, either experimentally or by changes in the world around us.” (Simon, 1979, p. 79). Increasingly, demographers emphasize the need to identify the underlying or intervening mechanisms linking demographic variables and suggest ways to accomplish the difficult task (Burch, 1980, p. 2; Caldwell and Hill, 1988, p. 1; Birg, 1988). The search for causal mechanisms is part of an attempt to develop a substantive theory of demographic behaviour. This paper is written in the same spirit. The aim is to explore the nature of the interdependencies between parallel careers. The fertility and labour force participation careers of women serve as an example. For no other set of two careers, the interdependence is as pronounced as for the fertility and employment careers. The basis for the interdependence is generally conflict or incompatibility, because “the timing of critical career-building phases does not accommodate women’s biological life cycle” (Regan and Roland, 1985, p. 986).

The burden of mortality of obesity at middle and old age is small: a life table analysis of the US Health and Retirement Survey

The evidence of effect of overweight and obesity on mortality at middle and old age is conflicting. The increased relative risk of cardiovascular disease and diabetes for overweight and obese individuals compared to normal weight is well documented, but the absolute risk of cardiovascular death has decreased spectacularly since the 1980s. We estimate the burden of mortality of obesity among middle and old aged adults in the Health and Retirement Survey (HRS), a US prospective longitudinal study. We calculate univariate and multivariate age-specific probabilities and proportional hazard ratios of death in relation to self-reported body mass index (BMI), smoking and education. The life table translates age specific adjusted event rates in survival times, dependent on risk factor distributions (smoking, levels of education and self reported BMI). 95% confidence intervals are calculated by bootstrapping. The highest life expectancy at age 55 was found in overweight (BMI 25–29.9), highly educated non smokers: 30.7 (29.5–31.9) years (men) and 33.2 (32.1–34.3) (women), slightly higher than a BMI 23–24.9 in both sexes. Smoking decreased the population life expectancy with 3.5 (2.7–4.4) years (men) and 1.8 (1.0–2.5) years (women). Less than optimal education cost men and women respectively 2.8 (2.1–3.6) and 2.6 (1.6–3.6) years. Obesity and low normal weight decreased population life expectancy respectively by 0.8 (0.2–1.3) and 0.8 (0.0–1.5) years for men and women in a contemporary, US population. The burden of mortality of obesity is limited, compared to smoking and low education.

Multi-state analysis of marital status life tables: Theory and application

Abstract A multi-state life table, also known as a multi-dimensional or an increment-decrement life-table, is a generalization of the conventional life table. Members of a birth cohort are followed as they age, and move between various states of life. In this paper, the mathematical theory of multi-state life table construction is reviewed. It is shown that the mathematics becomes simple if the matrix approach, initiated by Rogers for the design of multi-regional life tables, is adopted. The theory is used to construct a multi-state nuptiality table for Belgium. An innovative feature of multi-state analysis is that the life tables obtained for each of the marital states are interrelated, since an individual leaving a particular status enters another which eventually may be left again. Life table functions not only depend on age but also on current and/or previous marital status. In the paper it is shown how the patterns of marital change, experienced by Belgian women as they age, differ with their marital...

The life course: models and analysis

The life course perspective has proven to be extremely useful in studies of social and demographic change. In this perspective, life is viewed as an evolving process and demographic events are milestones or critical transitions. Major research questions include (a) how people organize their lives around these life events, and (b) what that means at the population level. The paper aims at contributing to an integration of life course theorizing and methods of analysis. The approach is to reduce life course theories and methods to a few basic and universal elements and to investigate the use of these elements in studies of life histories. Basic elements are life event, time, risk and uncertainty, exposure, and interaction. A better understanding of the conceptual and analytical significance of these concepts will guide theory development, data collection, and modeling.

Multistate Analysis: Tables of Working Life:

The demographers approach to the study of the labor force includes the calculation of life tables for the active population. Although this tool is extensively used and many countries publish working-life tables, and although they rely on very restrictive assumptions, the technique for constructing such tables has not improved since its development about thirty years ago. This paper reviews the conventional method for the construction of working-life tables and proposes a multistate approach which does not rely on restrictive assumptions such as the unimodality of the labor-force participation curve. Instead of focusing on changes in stocks, the actual flows of people between active and inactive life are considered. The technique is compared with a similar procedure recently developed by Hoem and Fong. The increment–decrement table of working life serves as a basis for a multistate model for labor-force projection. The proposed model is compared with conventional approaches. The methods presented in this paper are illustrated using Danish data.

Compression of Women's Reproductive Spans in Andhra Pradesh, India

CONTEXT The total fertility rate in Andhra Pradesh, India, has recently decreased to near-replacement level; however, the reasons for the fertility decline are unknown. METHODS Data from the second round of the National Family Health Survey were used to examine the reproductive span-the duration between first marriage and menopause or sterilization-among 4,032 ever-married women aged 15-49 living in Andhra Pradesh in 1998-1999. RESULTS Between 1992-1993 and 1998-1999, the median age at which women married remained at 15.1, whereas the age at which they adopted sterilization decreased from 24.5 to 23.6. In life-table analyses, reproductive spans of successive cohorts of women decreased-from 22 years among those who married during the 1960s to 15 years among those who married in the 1970s, 10 years among those who married in the 1980s and five years among those who married in 1990-1996. Proportional hazards regression analyses that controlled for demographic and social characteristics, as well as reproductive attitudes, confirmed this cohort effect (hazard ratios, 1.5-2.6). CONCLUSIONS These findings suggest that women are making the decision to end childbearing faster than older generations did. The gradual compression in reproductive spans is attributable mainly to sterilization acceptance among younger women.

Imposing age and spatial structures on inadequate migration-flow datasets

Abstract With the elimination of the long-form questionnaire from future decennial censuses and its replacement by a much smaller continuous monthly sampling survey (the American Community Survey), students of territorial mobility may find it necessary to deal with inadequate, missing, or inaccurate sample data on migration by adopting an approach that “improves” such data using information from different geographical areas, time periods, and data sources. We develop such an approach in this article and illustrate it with interregional migration flow data reported by the U.S. decennial censuses of 1980 and 1990 and by the 1985 Current Population Survey. *This research is being supported by a grant from the National Science Foundation (BCS-9986203).

International Migration in Europe

International migration in Europe , International migration in Europe , کتابخانه دیجیتال جندی شاپور اهواز