METHODS: Data from the University Sains Malaysia (USM) Pregnancy Cohort which consists of 153 mother-offspring pairs were used. Data were collected using interview-administered questionnaires and anthropometric measurements were also obtained. Multiple linear regression and generalised equation estimation (GEE) were used to examine the direction and impact of the association between parental BMI and child growth and body composition (weight for age, height for age, body mass index for age, weight for height and fat mass at age 2m, 6m, and 12m). Potential confounders, including validated measures of maternal diets and physical activity during pregnancy, were considered.
RESULTS: Of 153 parents, one-quarter of the mothers and 42.2% of the fathers, respectively, were overweight or obese before pregnancy. A significant association was found between maternal BMI and child's weight for height z-score (WHZ) and body mass index for age z-score (BAZ).
CONCLUSIONS: Having high pre-pregnancy BMI may increase BMI and WAZ of offspring in early life. Findings from this study emphasise the importance of monitoring maternal weight status, particularly before and during pregnancy and early life of offspring among Malaysians.
METHODS: Data from World Health Survey conducted in 2002-2004 in low-middle- and high-income countries were used. Participants aged 18 years and over were selected using multistage, stratified cluster sampling. BMI was used as an outcome variable. Culture of the countries was measured using Hofstede's cultural dimensions: Uncertainty avoidance, individualism, Power Distance and masculinity. The potential determinants of individual-level BMI were participants' sex, age, marital status, education, occupation as well as household-wealth and location (rural/urban) at the individual-level. The country-level factors used were average national income (GNI-PPP), income inequality (Gini-index) and Hofstede's cultural dimensions. A two-level random-intercepts and fixed-slopes model structure with individuals nested within countries were fitted, treating BMI as a continuous outcome variable.
RESULTS: A sample of 156,192 people from 53 countries was included in this analysis. The design-based (weighted) mean BMI (SE) in these 53 countries was 23.95(0.08). Uncertainty avoidance (UAI) and individualism (IDV) were significantly associated with BMI, showing that people in more individualistic or high uncertainty avoidance countries had higher BMI than collectivist or low uncertainty avoidance ones. This model explained that one unit increase in UAI or IDV was associated with 0.03 unit increase in BMI. Power distance and masculinity were not associated with BMI of the people. National level Income was also significantly associated with individual-level BMI.
CONCLUSION: National culture has a substantial association with BMI of the individuals in the country. This association is important for understanding the pattern of obesity or overweight across different cultures and countries. It is also important to recognise the importance of the association of culture and BMI in developing public health interventions to reduce obesity or overweight.