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Background: Literature on the effect of community social capital on health is inconsistent and could be related to differences in social capital measures, health outcomes, population groups and locations studied. Therefore this study examines the diversity in associations between community social capital and health by investigating different diseases, populations groups and locations., Methods: Mortality records and individual data on sex, age, marital status, ethnic origin and place of residence were available for 6 years (1995-2000). Neighbourhood data, i.e. community social capital, socio-economic level and urbanicity, were linked through postcode information. Community social capital was indicated by measures of community interaction, belongingness, satisfaction and involvement. Variations in all-cause and cause-specific mortality across low and high social capital neighbourhoods were estimated through Poisson regression. In addition, analyses were stratified according to population group and to urbanization level., Results: In the total population, community social capital was not related to all-cause mortality (RR = 1.00; CI: 0.99-1.01). However, residents of high social capital neighbourhoods had lower mortality risks for cancer [especially lung cancer (RR = 0.92; CI: 0.89-0.96)] and for suicide (RR = 0.90; CI: 0.83-0.98). Slightly lower mortality risks were also found for men (RR = 0.98; CI: 0.97-0.99), married individuals (RR = 0.96; CI: 0.94-0.97) and for residents living in socially strong neighbourhoods located in large cities (RR = 0.95; CI: 0.91-0.99)., Conclusions: The association between community social capital and health differs per health outcome, study population and location studied. This underlines the need to take such diversity into account when aiming to conceptualize the relation between community social capital and health.

Background: Urban residents have higher mortality risks than rural residents. These urban-rural differences might be more pronounced within certain demographic subpopulations., Aim: To determine urban-rural differences in all-cause and cause-specific mortality within specific demographic subpopulations of the Dutch population., Method: Mortality records with information on gender, age, marital status, region of origin and place of residence were available for 1995 through 2000. Neighbourhood data on address density and socioeconomic level were linked through postcode information. Variations in all-cause and cause-specific mortality between urban and rural neighbourhoods were estimated through Poisson regression. Additionally, analyses were stratified according to demographic subpopulation., Result: After adjustments for population composition, urban neighbourhoods have higher all-cause mortality risks than rural neighbourhoods (RR = 1.05; CI 1.04 to 1.05), but this pattern reverses after adjustment for neighbourhood socioeconomic level (RR = 0.98; CI 0.97 to 0.99). The beneficial effect of living in an urban environment applies particularly to individuals aged 10-40 years and 80 years and above, people who never married and residents from non-Western ethnic origins. The beneficial effect of urban residence for non-married people is related to their lower cancer and heart disease mortality. The beneficial effect of urban residence for people of non-Western ethnic origin is related to their lower cancer and suicide mortality., Conclusion: In The Netherlands, living in an urban environment is not consistently related to higher mortality risks. Young adults, elderly, single and non-Western residents, especially, benefit from living in an urban environment. The urban environment seems to offer these subgroups better opportunities for a healthy life.

Background: Migrant populations consist of migrants with differences in generational status and length of residence. Several studies suggest that health outcomes differ by generational status and duration of residence. We examined the association of generational status and age at immigration of the mother with infant mortality in migrant populations in The Netherlands., Methods: Data from Statistics Netherlands were obtained from 1995 through 2000 for infants of mothers with Dutch, Turkish and Surinamese ethnicity. Mothers were categorized by generational status (Dutch-born and foreign-born) and by age at immigration (0-16 and >16 years). The associations of generational status and age at immigration of the mother with total and cause-specific infant mortality were examined., Results: The infant mortality rate in Turkish mothers rose with lower age at immigration (from 5.5 to 6.4 per 1000) and was highest for Dutch-born Turkish mothers (6.8 per 1000). Infant death from perinatal and congenital causes increased with lower age at immigration and was highest in the Dutch-born Turkish women. In contrast, in Surinamese mothers infant mortality declined with lower age at immigration (from 8.0 to 6.3 per 1000) and was lowest for Dutch-born Surinamese mothers (5.5 per 1000). Generational status and lower age at immigration of Surinamese women were associated with declining mortality of congenital causes., Conclusions: Total and cause-specific infant mortality seem to differ according to generational status and age at immigration of the mother. The direction of these trends however differs between ethnic populations. This may be related to acculturation and selective migration.

We examined ethnic differences in infant mortality and the contribution of several explanatory variables. Data of Statistics Netherlands from 1995 to 2000 were studied (1,178,949 live borns). Proportional hazard analysis was used to show ethnic differences in total and cause-specific infant mortality. Obstetric, demographic and -geographical variables, and socio-economic status were considered as possible determinants. The four major ethnic minority groups showed an elevated risk of infant mortality, ranging from 1.28 in Turkish infants to 1.50 in Antillean/Aruban infants. In the early neonatal period, risks were elevated for Surinamese (hazard ratio [HR] 1.48, 95% confidence intervals [CI] 1.23, 1.78) and Antilleans/Arubans (HR 1.43, 95% CI 1.06, 1.92). In the post-neonatal period, risks were only elevated for Turkish (HR 2.20, 95% CI 1.80, 2.69) and Moroccan infants (HR 2.06, 95% CI 1.67, 2.55). Surinamese and Antillean/Aruban infants had an elevated risk of dying from perinatal causes (HR 1.62, 95% CI 1.33, 1.98 and 1.69, 95% CI 1.24, 2.29 respectively), Turkish and Moroccan infants had an elevated risk of dying from congenital anomalies (HR 1.42, 95% CI 1.16, 1.73 and 1.46, 95% CI 1.20, 1.79 respectively). Inequalities as a result of socio-economic position and demographic factors, such as marital status and maternal age, partially explain the ethnic differences in infant mortality. We conclude that ethnic minority groups in The Netherlands have a higher infant mortality than the native population, which in part seems preventable by reducing inequalities in socio-economic status. Marital status and age of the mother are important other risk factors of infant mortality.

Objective: To establish whether the practice of end-of-life decision-making for neonates and infants under the age of 1 in the Netherlands in 2000 was different from that in 1995., Design: Retrospective descriptive and comparative study., Methods: In both years, all deaths of children under the age of one year that took place in August-November (1995: n = 338; 2001: n = 347) were studied. The response rate was 96% in 1995 and 84% in 2001. The questionnaires which were sent to the physicians who reported the deaths, included structured questions about whether or not death had been preceded by end-of-life decisions, i.e. decisions to withhold or withdraw potentially life-prolonging treatment or to administer (potentially) life-shortening drugs, and questions about the decision-making process., Results: The proportion of end-of-life decisions increased slightly from 62% to 68% of all deaths in the first year of life, but the difference was not statistically significant. The large majority of these decisions involved withholding or withdrawing life-sustaining treatment. The frequency of decisions to actively terminate the life of an infant who was not dependent on life-sustaining treatment remained stable at 1%. The proportion of decisions that had been discussed with the parents increased slightly, from 91% in 1995 to 97% in 2001; similar percentages of the decisions had been discussed with other physicians. The percentage of decisions that had been discussed with the nursing staff decreased from 40 in 1995 to 28 in 2001., Conclusion: The findings suggest that the practice of end-of-life decision-making in neonatology was rather stable between 1995 and 2001. The frequency of the active termination of life had not increased, despite the new euthanasia regulation in the Netherlands.

Background: By describing ethnic differences in age- and cause-specific mortality in The Netherlands we aim to identify factors that determine whether ethnic minority groups have higher or lower mortality than the native population of the host country., Methods: We used data for 1995-2000 from the municipal population registers and cause of death registry. All inhabitants of The Netherlands were included in the study. The mortality of people who themselves or whose parent(s) were born in Turkey, Morocco, Surinam, or the Dutch Antilles/Aruba was compared with that of the native Dutch population. Mortality differences were estimated by Poisson regression analyses and by directly standardized mortality rates., Results: Compared with native Dutch men, mortality was higher among Turkish (relative risk [RR] = 1.21, 95% CI: 1.16, 1.26), Surinamese (RR = 1.24, 95% CI: 1.19, 1.29), and Antillean/Aruban (RR = 1.25, 95% CI: 1.15, 1.36) males, and lower among Moroccan males (RR = 0.85, 95% CI: 0.81, 0.90). Among females, inequalities in mortality were small. In general, mortality differences were influenced by socio-economic and marital status. Most minority groups had a high mortality at young ages and low mortality at older ages, a high mortality from ill-defined conditions (which is related to mortality abroad) and external causes, and a low mortality from neoplasms. Cardiovascular disease mortality was low among Moroccan males (RR = 0.51, 95% CI: 0.44, 0.59) and high among Surinamese males (RR = 1.13, 95% CI: 1.05, 1.21) and females (RR = 1.14, 95% CI: 1.06, 1.23). Homicide mortality was elevated in all groups., Conclusion: Socio-economic factors and marital status were important determinants of ethnic inequalities in mortality in The Netherlands. Mortality from cardiovascular diseases, homicide, and mortality abroad were of particular importance for shifting the balance from high towards low all-cause mortality.

The purpose of this study was to investigate whether the presence of a malignant tumor influences energy metabolism of the host. Resting energy expenditure (REE) was measured in 104 gastric and colorectal (GCR) cancer patients and in 47 non-small cell lung cancer patients and was compared with REE values in 40 healthy controls. REE expressed per kilogram of fat-free mass (FFM) in lung cancer patients was elevated, in comparison with healthy controls (33.6 +/- 4.6 and 29.6 +/- 2.9 kcal, respectively; P less than 0.001), in contrast to REE/FFM in GCR cancer patients, which showed no difference, compared with these controls (29.8 +/- 4.3 kcal). In 47 patients with GCR cancer and in 14 patients with lung cancer, REE was also determined after tumor resection. REE in GCR cancer patients measured 1.5 years after tumor resection showed a small but significant increase. No differences were observed between GCR cancer patients with or without signs of tumor recurrence. REE in lung cancer patients with no signs of tumor recurrence measured 1 year after tumor resection had a significant decrease in REE (REE/FFM, -6.8%; P less than 0.05), while patients who had evidence of tumor recurrence showed no change in REE or even an increase. After curative surgery REE returned to a normal level in the lung cancer patients. These results suggest that tumor type is a major determinant of an increased energy expenditure in cancer patients.

The aim of the current study was to determine the contribution of increased resting energy expenditure (REE) and/or decreased energy intake (EI) to the development of weight loss in gastric and colorectal (GCR) and lung cancer patients. REE was measured in 22 GCR cancer patients and 17 lung cancer patients and was compared with REE values in 40 apparently healthy controls. REE in lung cancer patients expressed per kg fat free mass (REE/FFM) was significantly increased when compared to healthy controls (33.5 +/- 5.4 and 29.6 +/- 2.9 kcal, respectively; p < 0.01). GCR cancer patients had no elevated REE compared to these healthy controls. No significant differences in EI were established between the three groups. Eight GCR cancer patients reported a decrease in food intake compared to pre-disease intake, in contrast to only one lung cancer patient. Semi-starving GCR cancer patients showed a significant weight loss (8.7 +/- 8.1%), a low respiratory quoteint (RQ) (0.76 +/- 0.04) and a high beta-hydroxybutyrate level (259 +/- 192 mumol/l), but they showed no difference in REE compared to patients with a normal EI. The current study suggests that weight loss in GCR cancer patients is initiated by decreased food intake, whereas weight loss in lung cancer patients represents a combination of an increased REE and a relatively low EI.

An estimate of a patient's energy needs is usually derived from equations, which predict energy expenditure (EE) by considering sex, age and body weight. Due to the increasing number of elderly people in a hospital population, more data on energy requirements in this age-group are needed. In this study resting energy expenditure (REE) of 40 healthy men and women, aged 51-82 years, was measured using a ventilated hood system. The results showed that some commonly used prediction equations underestimated REE by approximately 6 per cent. REE was highly correlated with fat free mass (FFM) (r = 0.88; P less than 0.001) and body weight (r = 0.85; P less than 0.001). A stepwise multiple regression analysis showed that the combination of body weight, sex and age resulted in the best prediction for REE; REE (kcal) = 1641 + 10.7 weight (kg)--9.0 age (years)--203 sex (1 = male, 2 = female) (r = 0.92). However, REE of an individual may be over- or underestimated by +/- 225 kcal (10-20 per cent) due to large between-subject variations. We suggest therefore that the energy requirements of elderly people should be measured rather than predicted. Due to small within-subject variations (including measurement error) a single REE measurement would suffice. Sleeping energy expenditure (SEE) was 7 per cent lower than REE.