Body weight and coronary heart disease mortality: An analysis in relation to age and smoking habit. 15 years follow-up data from the Whitehall Study

Division of Community Health, United Medical School of Guy's Hospital, London, UK.
International Journal of Obesity (Impact Factor: 5). 03/1992; 16(2):119-23.
Source: PubMed


18,403 male civil servants aged 40-64 years were examined in London between 1968 and 1970. Mortality from all causes and specifically from coronary heart disease (CHD) over 15 years of follow-up was initially analysed in relation to deciles of body mass index (BMI = weight/height2) at entry into the study. In older men all causes mortality tended to be higher in those with a low BMI, but this was not so for CHD mortality. The latter was further studied after dividing the population into sub-groups according to age and cigarette smoking. With BMI distribution divided into fifths and five year age groups there were significant positive trends of CHD mortality across the BMI distribution in all age groups except the youngest (40-44 years) and oldest (60-64 years). For analysis by smoking category--never, ex- and current cigarette smoker--three age-specific groups were used: 40-49, 50-59 and 60-64 years. In men aged less than 60 years there were significant positive trends of CHD mortality and BMI in five of the six age and smoking categories, the exception being ex-smokers aged 40-49 years. Associations were strongest in the current smokers. By contrast in men aged 60-64 years there was a significant association between BMI and CHD mortality only in ex-smokers and this was of low order (P = 0.04). The data are compatible with some reports of a lesser association of obesity with mortality risk in older persons and in this data set the observation is not confounded by smoking habit.

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    • "However, another study has reported that weight gain was observed in current smokers, ex-smokers, and non-smokers, which seemed to indicate that factors that promote weight gain had overcome the inverse effect of smoking [46]. Although this study found non-smokers had the greatest risk of obesity, smoking has been previously reported to have a greater impact on morbidity and mortality than obesity [47,48]. "
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    ABSTRACT: Background Obesity increases the risk of many diseases. However, there has been little literature about the epidemiology of obesity classified by body mass index (BMI) or waist (abdominal obesity) among urban Chinese adults. This study is to fill the gap by assessing the prevalence of obesity and associated risk factors among urban Chinese adults. Methods A representative sample of 25,196 urban adults aged 18 to 74 years in Northeast China was selected and measurements of height, weight and waist circumference (WC) were taken from 2009–2010. Definitions of overweight and obesity by the World Health Organization (WHO) were used. Results The overall prevalence rates of general obesity and overweight classified by BMI were 15.0% (15.7% for men and 14.3% for women, p<0.01) and 19.2% (20.8% for men and 17.7% for women, p<0.01), respectively, and the overall prevalence rate of abdominal obesity was 37.6% (31.1% for men and women 43.9% for women, p<0.01). Multivariable logistic regression showed that the elderly and those who had a history of parental obesity, alcohol drinking, or former cigarette smoking were at high risk of obesity classified by BMI or WC, whereas those with a higher level of education, higher family income, or a healthy and balanced diet were at low risk of obesity. Analysis stratified by gender showed that men with a higher level education level, a white-collar job, a cadre job, or higher family income were the high risk group, and women with a higher level of education or higher family income were the low risk group. Conclusions Obesity and overweight have become epidemic in urban populations in China; associations of risk factors with obesity differ between men and women.
    BMC Public Health 11/2012; 12(1):967. DOI:10.1186/1471-2458-12-967 · 2.26 Impact Factor
    • "Furthermore, obese individuals are susceptible to the many cardiovascular, metabolic, pulmonary, musculo-skeletal, gastrointestinal and psychosocial disorders that accompany increased adiposity such as hypertension, diabetes, sleep apnea, osteoarthritis, fatty liver disease and depression. Obesity has been reported to be associated with higher mortality and morbidity (Lew and Garfinkel, 1979; Waaler, 1984; Fitzgerald and Jarrett, 1992 and Kopelman, 2007) and morbidity (Chaing et al., 1969; Noppa et al., 1978; Garrison et al., 1980; Hubert et al., 1983; Kannel et al., 1991; Guh et al., 2009. Studies on the various aspects of obesity have been done earlier by many workers, Reports pertaining to obesity in Asia and particularly in India are few some of them are Janghorbani and Parvin, 1998); Parizkova and Hills (2001); Shahbazpour (2003); Afridi, et al (2003); Weiss et al., (2004); Jazayeri (2005); Barkail (2006); Hadaegh et al., (2007); Gholamreza and Mohsen, 2007); Veghari and Golalipour, (2007); Alhamdan (2008). "
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    ABSTRACT: Obesity is a medical condition characterized by accumulation of excess body fat leading to negative health consequences and reduced life expectancy. The latter could be attributed to various diseases, particularly cardiovascular diseases, diabetes mellitus type 2, obstructive sleep apnea, certain types of cancer and osteoarthritis. The present investigation was undertaken to evaluate obesity, appraised by BMI, in the Raipur District of Chhattisgarh State, India. A multiphase stratified random sampling method was performed on 688 adults of both sexes, with mean age 34yrs ± 16, from June to September 2011. Anthropometric measurements were recorded using standard instruments (weight scale and stadiometer). BMI was calculated using the statistical software SPSS version 20.0. The results divulged 19.91% of the adults to be overweight and 57% of them as obese. Amongst the male subjects, 23.55% and 7.97 %; and in case of females, 17.47% and 8.90 % were marked as overweight and obese respectively. As evident from the results, 8.5% were obese and another 20% are being overweight which could lead to future obesity, which is significantly associated with increased likelihoods of having depressive symptoms and an array of other cardiac diseases. Thus, lifestyle and mental health status could well be monitored and evaluated in the obese and overweight subjects in order to prevent the several disorders associated with obesity.
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    • "Some studies show that obesity is related to impaired function (Ferraro and Booth 1999; Galanos et al. 1994), while others find no ' The majority of large, well-designed, epidemiological studies show that obesity is associated with higher morbidity and mortality in adulthood (NHLBI 1998; Sjostrom 1992). Evidence comes from a variety of sources based on samples from the United States (e.g., National Center for Health Statistics 1991; Tayback et al. 1990) as well as in other nations (e.g., on the United Kingdom , see Fitzgerald and JarreU 1992; on Finland, see Rissanen et al. 1989). such link (Kaplan et al. 1993; Lawrence and Jette 1996). "
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    ABSTRACT: Drawing from cumulative disadvantage theory, the health consequences of obesity are considered in light of the accumulation of risk factors over the life course. Two forms of compensation are also examined to determine if the risk due to obesity is persistent or modifiable. Analyses make use of data from a national survey to examine the consequences of obesity on disability among respondents 45 years of age or older, tracked across 20 years (N = 4,106). Results from tobit models indicate that obesity, especially when experienced early in life, is consistently related to lower-body disability. The results also show that obesity has long-term health consequences during adulthood, altering the life course in an enduring way. Compensation was not manifest from risk-factor elimination (weight loss), but rather through regular exercise. Although there is evidence for long-term consequences of risk factors on health, the findings suggest that more attention should be given to compensatory mechanisms in the development of cumulative disadvantage theory.
    American Sociological Review 10/2003; 68(5):707-729. DOI:10.2307/1519759 · 4.42 Impact Factor
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