Body mass index and risk of all‐cause and cardiovascular mortality in hospitalized elderly patients with diabetes mellitus

Aims Obesity is linked to increased morbidity and mortality risk in both the general population and in patients with diabetes mellitus; however, recent reports suggest that, in hospitalized elderly individuals, the association between body mass index (BMI) and mortality may be inverse. The present study sought to investigate the association between BMI and survival in hospitalized elderly individuals with diabetes mellitus. Methods The medical records of 470 patients (226 males, mean age of 81.5 ± 7.0 years) admitted to an acute geriatric ward between 1999 and 2000 were reviewed. Of the 140 patients with diabetes mellitus, 122 had more than 6 months of follow‐up and were included in this analysis. Patients were followed up until 31 August 2004. Mortality data were extracted from death certificates. Results During a mean follow‐up of 3.7 ± 1.6 years, 69 (56.6%) subjects died, 31 (25.4%) from cardiovascular causes. Those who died from any cause had lower baseline BMI than those who survived (24.0 ± 4.0 vs. 27.1 ± 4.3 kg/m²; P < 0.0001). Similarly, those who died of cardiovascular causes had lower baseline BMI than those who did not (23.7 ± 3.6 vs. 25.9 ± 4.5, P = 0.01). BMI was inversely associated with all‐cause [relative risk (RR) 0.89, 95% confidence interval (CI) 0.83–0.96, P = 0.002] and cardiovascular death (RR 0.83, 95% CI 0.74–0.93, P = 0.002) even after controlling for age, sex, smoking, dyslipidaemia and reason for hospital admission. Conclusions In very elderly subjects with diabetes mellitus, increased BMI was associated with reduced mortality risk.     

Body mass index and nine-year mortality in disabled and nondisabled older U.S. individuals

OBJECTIVES: To investigate the relationship between body mass index (BMI) and 9-year mortality in older (≥65) Americans with and without disability.
DESIGN: Cohort study.
SETTING: The unique disability-focused National Long Term Care Survey (NLTCS) data that assessed the health and well-being of older individuals in 1994 were analyzed.
PARTICIPANTS: Four thousand seven hundred ninety-one individuals in the 1994 survey.
MEASUREMENTS: BMI (kg/m²) was calculated from self- or proxy reports of height and weight. The analysis was adjusted for 1-year change in BMI and demographic and health-related factors, as well as reports by proxies, and death occurring during the first 2 years after the interview.
RESULTS: The relative risk of death as a function of BMI formed a nonsymmetric U-shaped pattern, with larger risks associated with lower BMI (<22.0) and minimal risks for BMI of 25.0 to 34.9. (BMI 22.0–24.9 was the reference.) Adjustments for demographic and health-related factors had little effect on this pattern. Nondisabled individuals exhibited a similar U-shaped pattern but with lower risks associated with lower BMI. For disabled individuals, the mortality–risk pattern was higher for lower BMI (<22.0) and flat for higher BMI, thus exhibiting an inverse J shape. BMI patterns were age sensitive, with disability status affecting sensitivity.
CONCLUSION: Overweight or mild (grade 1) obesity was not a risk factor for 9-year mortality in older Americans participating in the 1994 NLTCS. A flatter BMI pattern of the relative risk of death for disabled than for nondisabled individuals suggests that optimal body weight can be sensitive to age and health and well-being.     

Body mass index is inversely related to mortality in older people after adjustment for waist circumference

OBJECTIVES: To examine the individual and combined influence of body mass index (BMI) and waist circumference (WC) on mortality risk in older people. DESIGN: Longitudinal cohort study. SETTING: Cardiovascular Health Study, a longitudinal study of cardiovascular disease and its risk factors in older people. PARTICIPANTS: Five thousand two hundred men and women aged 65 and older. MEASUREMENTS: BMI and WC were measured at baseline. The risks of all-cause mortality associated with BMI and WC were examined using Cox proportional hazards models over 9 years of follow-up. RESULTS: When examined individually, BMI and WC were both negative predictors of mortality, but when BMI and WC were examined simultaneously, BMI was a negative predictor of mortality, whereas WC was a positive predictor of mortality. After controlling for WC, mortality risk decreased 21% for every standard deviation increase in BMI. After controlling for BMI, mortality risk increased 13% for every standard deviation increase in WC. The patterns of associations were consistent by sex, age, and disease status. CONCLUSION: Higher BMI values indicated a lower mortality risk once the risk attributable to WC was accounted for, whereas higher WC values indicate a higher mortality risk once the risk attributable to BMI was accounted for. Both BMI and WC should be measured in the clinical setting, but in older adults higher BMI is associated with lower mortality rates.     

Associations between body mass index and all-cause mortality: A systematic review and meta-analysis

Fasting insulin and c-reactive protein confound the association between mortality and body mass index. An increase in fat mass may mediate the associations between hyperinsulinemia, hyperinflammation, and mortality. The objective of this study was to describe the “average” associations between body mass index and the risk of mortality and to explore how adjusting for fasting insulin and markers of inflammation might modify the association of BMI with mortality. MEDLINE and EMBASE were searched for studies published in 2020. Studies with adult participants where BMI and vital status was assessed were included. BMI was required to be categorized into groups or parametrized as non-first order polynomials or splines. All-cause mortality was regressed against mean BMI squared within seven broad clinical populations. Study was modeled as a random intercept. β coefficients and 95% confidence intervals are reported along with estimates of mortality risk by BMIs of 20, 30, and 40 kg/m². Bubble plots with regression lines are drawn, showing the associations between mortality and BMI. Splines results were summarized. There were 154 included studies with 6,685,979 participants. Only five (3.2%) studies adjusted for a marker of inflammation, and no studies adjusted for fasting insulin. There were significant associations between higher BMIs and lower mortality risk in cardiovascular (unadjusted β −0.829 [95% CI −1.313, −0.345] and adjusted β −0.746 [95% CI −1.471, −0.021]), Covid-19 (unadjusted β −0.333 [95% CI −0.650, −0.015]), critically ill (adjusted β −0.550 [95% CI −1.091, −0.010]), and surgical (unadjusted β −0.415 [95% CI −0.824, −0.006]) populations. The associations for general, cancer, and non-communicable disease populations were not significant. Heterogeneity was very large (I² ≥ 97%). The role of obesity as a driver of excess mortality should be critically re-examined, in parallel with increased efforts to determine the harms of hyperinsulinemia and chronic inflammation.     

Body mass index, body cell mass, and 4-year all-cause mortality risk in older nursing home residents

OBJECTIVES: To investigate the relationship between body composition (assessed using body mass index (BMI) and body cell mass (BCM)) and all-cause mortality in a sample of older nursing home residents. DESIGN: Prospective study with a median follow-up period of 3.5 years. SETTING: Istituto di Riposo per Anziani, Padua, Italy. PARTICIPANTS: A total of 344 participants (79.1% women) aged 65 and older at baseline. MEASUREMENTS: Anthropometric, nutritional, and metabolic parameters were measured at baseline. BCM was measured using tetrapolar bioelectric impedance analysis. Up to 4 years of follow-up data for vital status were available. Survival analysis was conducted using Kaplan-Meier curves and multivariate Cox proportional hazards models. RESULTS: During the follow-up period, there were 179 deaths. After adjustment for age and sex, subjects with low BMI and low BCM (lowest sex-specific tertiles) had significantly higher mortality than those with higher BMI or BCM levels. In a fully adjusted regression model, there was no association between BMI levels and risk of mortality, with subjects in the top tertile having the same likelihood of mortality as subjects in the lowest tertile (relative risk (RR)=0.94, 95% confidence interval (CI)=0.61-1.43). Conversely, there was a strong and significant inverse association between BCM levels and mortality (RR for tertile III=0.55, 95% CI=0.35-0.87; P<.01). Furthermore, participants who had high BCM had comparable survival rates in all BMI tertiles. CONCLUSION: In this sample of older nursing home residents, BCM was a strong and independent risk factor for mortality. BCM assessment might provide more useful prognostic information for clinicians than BMI.     

A dose‐response meta‐analysis of the impact of body mass index on stroke and all‐cause mortality in stroke patients: a paradox within a paradox

The obesity paradox is often attributed to fat acting as a buffer to protect individuals in fragile metabolic states. If this was the case, one would predict that the reverse epidemiology would be apparent across all causes of mortality including that of the particular disease state. We performed a dose‐response meta‐analysis to assess the impact of body mass index (BMI) on all‐cause and stroke‐specific mortality among stroke patients. Data from relevant studies were identified by systematically searching PubMed, OVID and Scopus databases and were analysed using a random‐effects dose‐response model. Eight cohort studies on all‐cause mortality (with 20,807 deaths of 95,651 stroke patients) and nine studies of mortality exclusively because of stroke (with 8,087 deaths of 28,6270 patients) were evaluated in the meta‐analysis. Non‐linear associations of BMI with all‐cause mortality (P < 0.0001) and mortality by stroke (P = 0.05) were observed. Among overweight and obese stroke patients, the risk of all‐cause mortality increased, while the risk of mortality by stroke declined, with an increase in BMI. Increasing BMI had opposite effects on all‐cause mortality and stroke‐specific mortality in stroke patients. Further investigations are needed to examine how mortality by stroke is influenced by a more accurate indicator of obesity than BMI.     

High body mass index does not predict mortality in older people: analysis of the Longitudinal Study of Aging

OBJECTIVE: To determine the excess mortality associated with obesity (defined by body mass index (BMI)) in older people, with and without adjustment for other risk factors associated with mortality and for demographic factors. DESIGN: Retrospective cohort analysis of the Longitudinal Study of Aging (LSOA). SETTING: Nationally representative sample of community-dwelling older people. PARTICIPANTS: Seven thousand five hundred and twenty-seven participants age 70 and older in 1984. MEASUREMENTS: We used Cox regression to calculate proportional hazards ratios for mortality over 96 months. We tested the hypothesis that increased BMI (top 15%) increased mortality rates in older people. RESULTS: Death occurred in 38% of the cohort: 54% of the thin (lowest 10% of the population, BMI <19.4 kg/m(2)), 33% of the obese (highest 15%, BMI> 28.5 kg/m(2)), and 37% of the remaining participants (normal) died. Adjustment for demographic factors, health services utilization, and functional status still demonstrated reduced mortality in obese older people (hazard ratio 0.86, 95% confidence interval (CI) = 0.77-0.97) compared with normal. After adjustment, thin older people remained more likely to die (hazard ratio 1.46, 95% CI = 1.30-1.64) than normal older people. Sensitivity analyses for income, mortality during the first two years of follow-up, and medical comorbidities did not substantively alter the conclusions. CONCLUSION: Obesity may be protective compared with thinness or normal weight in older community-dwelling Americans.     

Body mass index and risk of pneumonia: a systematic review and meta‐analysis

The aims of our meta‐analysis were to examine the pattern and gender's influence on body mass index (BMI) – pneumonia relationship. Published studies were searched from PubMed, Web of Science, Cochrane Library databases using keywords of pneumonia, BMI and epidemiologic studies. Random‐effects analysis was applied to estimate pooled effect sizes from individual studies. The Cochrane Q‐test and index of heterogeneity (I²) were used to evaluate heterogeneity, and Egger's test was used to evaluate publication bias. Random‐effects meta‐regression was applied to examine the pattern and gender's influence on BMI–pneumonia relationship. A total of 1,531 studies were initially identified, and 25 studies finally were included. The pooled relative risk (RR) and meta‐regression model revealed a J‐shaped relationship between BMI and risk of community‐acquired pneumonia (underweight, RR 1.8, 95% confidence interval [CI], 1.4–2.2, P < 0.01; overweight, 0.89, 95%CI, 0.8–1.03, P, 0.1; obesity, 1.03, 95% CI, 0.8–1.3, p. 8) and U‐shaped relationship between BMI and risk of influenza‐related pneumonia (underweight, RR 1.9, 95% CI, 1.2–3, P < 0.01; overweight, 0.89, 95% CI, 0.79–0.99, P, 0.03; obesity, 1.3, 95% CI, 1.05–1.63, p. 2; morbidity obesity, 4.6, 95% CI, 2.2–9.8, P < 0.01); whereas, no difference in risk of nosocomial pneumonia was found across the BMI groups. Gender difference did not make significant contribution in modifying BMI–pneumonia risk relationship.     

Body mass index and healthcare costs: a systematic literature review of individual participant data studies

Excess weight is associated with increased total healthcare costs, but it is less well known how the associations between excess weight and costs vary across different types of healthcare service. We reviewed studies using individual participant data to estimate associations between body mass index and healthcare costs, and summarized how annual healthcare costs for overweight (body mass index 25 to <30 kg/m²) and obese (≥30 kg/m²) individuals compared with those for healthy weight individuals (18.5 to <25 kg/m²). EMBASE and MEDLINE were searched from January 1990 to September 2016, and 75 studies were included in the review. Of these, 34 studies presented adequate information to contribute to a quantitative summary of results. Compared with individuals at healthy weight, the median increases in mean total annual healthcare costs were 12% for overweight and 36% for obese individuals. The percentage increases in costs were highest for medications (18% for overweight and 68% for obese), followed by inpatient care (12% and 34%) and ambulatory care (4% and 26%). Percentage increases in costs associated with obesity were higher for women than men. The substantial costs associated with excess weight in different healthcare settings emphasize the need for investment to tackle this major public health problem.     

Association of sarcopenic obesity with the risk of all‐cause mortality: A meta‐analysis of prospective cohort studies

Many prospective studies have investigated the relationship between sarcopenic obesity (SO) and risk of mortality. However, the results have been controversial. The aim of the present study was to evaluate the association between SO and all‐cause mortality in adults by a meta‐analysis of prospective cohort studies. A systematic literature search was carried out through electronic databases up to September 2014. A total of nine articles with 12 prospective cohort studies, including 35 287 participants and 14 306 deaths, were included in the meta‐analysis. Overall, compared with healthy subjects, subjects with SO had a significant increased risk of all‐cause mortality (pooled HR 1.24, 95% CI 1.12–1.37, P < 0.001), with significant heterogeneity among studies (I² = 53.18%, P = 0.0188), but no indication for publication bias (P = 0.7373). Heterogeneity became low and no longer significant in the subgroup analyses by three SO definitions. More importantly, SO, defined by mid‐arm muscle circumference and muscle strength criteria, significantly increased the risk of mortality (HR 1.46, 95% CI 1.23–1.73 and 1.23, 1.09–1.38, respectively). The risk of all‐cause mortality did not appreciably change considering the geography (USA cohorts and non‐USA cohorts) or the duration of follow up (≥10 years and <10 years). However, the risk estimate was only significant in men (HR 1.23, 95% CI 1.08–1.41, P = 0.0017), not in women (HR 1.16, P = 0.1332). The results of the present study show that subjects with SO are associated with a 24% increase risk of all‐cause mortality, compared with those without SO, in particular in men; the significant association was found independent of geographical location and duration of follow up. Geriatr Gerontol Int 2016; 16: 155–166.     

离休干部237例体质量指数与全因死亡的分析研究

目的 分析第二军医大学离休干部体质量指数（BMI）与全因死亡的关系。方法 收集2000年1月至2013年10月于长海医院老年病科住院的我校离休干部共237例的临床资料,并进行随访,随访截止时间为2014年10月31日。根据BMI分为4组：低体质量组,BMI＜20kg/m2;理想体质量组,BMI 20～24.9 kg/m2;超重组,BMI 25～27.9 kg/m2;肥胖组,BMI≥28kg/m2。采用Cox回归方法分析各组的全因死亡风险。结果 中位随访时间59个月,均无失访,随访结束时发生全因死亡115例。Cox回归分析不同BMI分组的全因死亡风险,校正混杂因素后,相对于低体质量组,理想体质量组、超重组和肥胖组的全因死亡风险分别下降53.6%（HR＝0.464,95%CI：0.239～0.901,P＜0.05）、65.2%（HR＝0.348,95%CI：0.162～0.749,P＜0.05）、74.2%（HR＝0.258,95%CI：0.103～0.644,P＜0.05)。结论 随着BMI增加,离休干部全因死亡风险呈下降趋势。     

A quantitative analysis of body mass index and colorectal cancer: findings from 56 observational studies

To perform a systematic review of studies reporting on the association between body mass index (BMI) and the risk of colorectal cancer, we conducted a meta-analysis and meta-regression analysis. The identified 56 studies were conducted among 7 213 335 individuals including 93 812 cases. Compared with BMI <  23.0 kg m⁻², BMI of 23.0–24.9, 25.0–27.4, 27.5–29.9 and ≥30.0 kg m⁻² were associated with 14%, 19%, 24% and 41% increased risks, respectively. Asians and premenopausal women had sharply increased risk from BMI < 23 kg m⁻² to general 'normal' range (23–25 kg m⁻²). Each 5 kg m⁻² increment was associated with 18% increased risk. Meta-regression analysis indicated that the association was stronger for colon than rectal cancer ( P  < 0.001), for men than women ( P  < 0.001), for self-reported BMI than directly measured BMI ( P  < 0.001), and for studies adjusting for physical activity than not adjusting ( P  < 0.001). The variation of the reported risk estimates for the association can be partly explained by cancer site, sex, women menopausal status, BMI assessment and adjustment of confounding variables.