Biology or behavior : which is the strongest contributor to weight gain?

Combating unhealthy weight gain is a major public health and clinical management issue. The extent of research into the etiology and pathophysiology of obesity has produced a wealth of evidence regarding the contributing factors. While aspects of the environment are ‘obesogenic’, weight gain is not inevitable for every individual. What then explains potentially unhealthy weight gain in individuals living within an environment where others remain lean? In this paper we explore the biological compensation that acts in response to a reduced energy intake by reducing energy needs, in order to defend against weight loss. We then examine the evidence that there is only a weak biological compensation to surplus energy supply, and that this allows behavior to drive weight gain. The extent to which biology impacts behavior is also considered.

Prevalence of malnutrition in community-dwelling adults with Parkinson's disease

People with Parkinson’s disease (PD) have been reported to be at higher risk of malnutrition than an age-matched population due to PD motor and non-motor symptoms and pharmacotherapy side effects. The prevalence of malnutrition in PD has yet to be well-defined. Community-dwelling people with PD, aged > 18 years, were recruited (n = 97, 61 M, 36 F). The Patient-Generated Subjective Global Assessment (PGSGA) was used to assess nutritional status, the Parkinson’s Disease Questionnaire (PDQ-39) was used to assess quality of life, and the Beck’s Depression Inventory (BDI) was used to measure depression. Levodopa equivalent doses (LEDs) were calculated based on reported Parkinson’s disease medication. Weight, height, mid-arm circumference (MAC) and calf circumference were measured. Cognitive function was measured using the Addenbrooke’s Cognitive Examination. Average age was 70.0 (9.1, 35–92) years. Based on SGA, 16 (16.5%) were moderately malnourished (SGA B) while none were severely malnourished (SGA C). The well-nourished participants (SGA A) had a better quality of life, t(90) = −2.28, p < 0.05, and reported less depressive symptoms, t(94)= −2.68, p < 0.05 than malnourished participants. Age, years since diagnosis, cognitive function and LEDs did not signifi cantly differ between the groups. The well-nourished participants had lower PG-SGA scores, t(95) = −5.66, p = 0.00, higher BMIs, t(95) = 3.44, p < 0.05, larger MACs, t(95) = 3.54, p < 0.05 and larger calf circumferences, t(95) = 2.29, p < 0.05 than malnourished participants. Prevalence of malnutrition in community-dwelling adults with PD in this study is comparable to that in other studies with community-dwelling adults without PD and is higher than other PD studies where a nutritional status assessment tool was used. Further research is required to understand the primary risk factors for malnutrition in this group.

Comparison of two methods to assess malnutrition in community-dwelling people with Parkinson's disease

Nutritional status in people with Parkinson’s disease (PD) has previously been assessed in a number of ways including BMI, % weight loss and the Mini-Nutritional Assessment(MNA). The symptoms of the disease and the side effects of medication used to manage them result in a number of nutrition impact symptoms that can negatively influence intake. These include chewing and swallowing difficulties, lack of appetite, nausea, and taste and smell changes, among others. Community-dwelling people with PD, aged >18 years, were recruited (n=97, 61 M, 36 F). The Patient-Generated Subjective Global Assessment(PG-SGA) and (MNA) were used to assess nutritional status. Weight, height, mid-arm circumference(MAC) and calf circumference were measured. Based on SGA, 16(16.5%) were moderately malnourished (SGA B) while none were severely malnourished (SGA C). The MNA identified 2(2.0%) as malnourished and 22(22.7%) as at risk of malnutrition. Mean MNA scores were different between the three groups,F(2,37)=7.30,p<.05 but not different between SGA B (21.0(2.9)) and MNA at risk (21.8(1.4)) participants. MAC and calf circumference were also different between the three groups,F(2,37)=5.51,p<.05 and F(2,37)=15.33,p<.05 but not between the SGA B (26.2(4.2), 33.3(2.8)) and MNA at risk (28.4(5.6), 36.4(4.7)) participants. The MNA results are similar to other PD studies using MNA where prevalence of malnutrition was between 0-2% with 20-33% at risk of malnutrition. In this population, the PG-SGA may be more sensitive to assessing malnutrition where nutrition impact symptoms influence intake. With society’s increasing body size, it might also be more appropriate as it does not rely on MAC and calf circumference measures.

An exploratory study of associations between Australian-Indian mothers’ use of controlling feeding practices, concerns and perceptions of children’s weight and children’s picky eating

Aim This cross-sectional study explores associations between migrant Indian mothers’ use of controlling feeding practices (pressure to eat, restriction and monitoring) and their concerns and perceptions regarding their children’s weight and picky eating behaviour. Methods Two hundred and thirty mothers with children aged 1-5 years, residing in Australia for 1-8 years, participated by completing a self-reported questionnaire. Results Perceptions and concerns regarding children’s weight were not associated with any of the controlling feeding practices. A positive association was noted between pressure feeding and perceptions of pickiness after adjusting for covariates: children’s age, gender and weight-for-age Z-score. Girls, older children, and children with higher weight-for-age z scores were pressure fed to a greater extent. Conclusions This study supports the generalisation of findings from Caucasian literature that pressure feeding and perceptions of pickiness are positively related.