While the phenomenon of depression during and following pregnancy in women is widely appreciated (and often associated with weight gain and/or antenatal weight retention), the effect of pregnancy on mood of fathers is less appreciated.

A recent study by James Paulson and Sharnail Bazemore from the Virginia Medical School, Norfolk, VA, just published in the Journal of the American Medical Association, throws new light on this interesting issue.

The researchers performed a meta-analysis of 43 studies that documented depression in fathers between the first trimester and the first postpartum year involving 28 004 participant.

Although there was substantial heterogeneity between the rates of paternal depression between studies, the average rate of paternal depression in the antenatal period (during pregnancy) was abour 10% but increased to about 25% during the 3 to 6-month postpartum period (after birth).

While paternal depression was more likely in the presence of maternal depression, this was by no means a strong predictor of paternal mood disorder.

These findings have important implications.

Not only is it important to also be wary of mood disorders in expecting and new fathers (especially if the mother has mood problems), but these mood disorders in fathers may need to be addressed.

This is of particular importance given the emerging evidence that paternal depression may have substantial emotional, behavioural and developmental effects on the infant.

Furthermore, it may well be that paternal peripartum depression could contribute to weight gain in dads.

Thus, prevention, screening and interventions for depression should likely be focussed on the couple rather than on the individual parent.

AMS
Oslo, Norway

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Paulson JF, & Bazemore SD (2010). Prenatal and postpartum depression in fathers and its association with maternal depression: a meta-analysis. JAMA : the journal of the American Medical Association, 303 (19), 1961-9 PMID: 20483973

No worries, I am already holding my ears to avoid the screams of protest that I expect to get in response to this post.

But the idea that working moms may well play a noticeable role in the development of childhood obesity is indeed one that is suggested by Angela Pinot de Moira and colleagues from University College London, UK, in a paper just published online in the American Journal of Epidemiology.

The premise is simple: one of the most dramatic demographic shifts in the last decades has been the proportion of moms that work. From being the exception in the 60s, to becoming pretty much the norm for the majority of mothers today, this demographic shift has undoubtedly had profound effects on family life.

Not surprisingly, some have argued, that not having a parent at home (and traditionally this used to be the mom) may very much increase the risk of weight gain in offspring.

Thus, not only do “latchkey kids” have more freedom to eat unhealthy foods and spend afternoons slumped in front of the TV or computer, but long hours at work can also leave moms (or dads) short of time to prepare healthy family meals (ergo the dramatic rise in fastfood and family restaurants).

In addition, working mothers (or dads) may also have to drive their children to school rather than have the time to walk them there and working partents certainly don’t have the time to watch over their kids on the playground all afternoon or be at home in case their kids scrape a leg falling off their bikes or get beaten up by the neighbourhood bully.

So is this hypothesis borne out by the data?

To address this question, the authors examined members of a 1958 British birth cohort (age 7 years, n=8,552) and offspring (ages 4-9 years, n=1,889) born to mothers under age 30 years to establish whether risk factors for childhood obesity have changed over time (1965-1991).

The authors found that the prevalence of overweight/obesity had increased by more than 50% between generations and that parental BMI was strongly associated with offspring BMI.

But perhaps more interestingly, full-time maternal employment turned out to be positively associated with offspring BMI in childhood with an increase of 0.4-0.5 units in kids with working moms. This relationship was in fact stronger in the offspring than in the original cohort.

Maternal employment was found to have increased by more than 30% across generations, as a result of which, the population attributable risk maternal employment increased from 3.1% to 7.8% across generations.

In addition, the authors noted that smaller family size and fewer younger siblings were also associated with increased childhood BMI.

As argued by Elizabeth Warren and Amelia Warren Tyagi in their bestseller “The Two Income Trap: Why Middle-Class Mothers and Fathers Are Going Broke“, even if all kinds of issues may be linked to working moms, simply asking moms to stay at home is neither feasible nor socially desirable (incidentally, both authors are working moms).

Rather, other measures, including proper and affordable day care, accessible and supervised after-school activities and more flexibility in working hours may help moms (and dads) better meet the demands of their kids, thereby hopefully reducing their risk for obesity.

I wonder what my readers think of this hypothesis and what (if anything) can (should) be done about it.

AMS
Edmonton, Alberta

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de Moira AP, Power C, & Li L (2010). Changing Influences on Childhood Obesity: A Study of 2 Generations of the 1958 British Birth Cohort. American journal of epidemiology PMID: 20488872

A study by Silvia Stinghini and colleagues from Villejuif, France, published in this week’s edition of JAMA re-examines the relationship between socioeconomic status and mortality in the famous British Whitehall study.

This longitudinal cohort study includes around 10,000 English civil servants, aged 35 to 55 years, 654 of whom have died since the study began 24 years ago.

When adjusted for sex and year of birth, civil servants in the lowest civil service employment grade (as a surrogate for socioeconomic status) had a 1.60 times higher risk of death from all causes than those with the highest employment grade. The risk for cardiovascular mortality was in fact 3 times higher for the lowest socioeconomic group.

However, this apparently strong impact of socioeconomic position declined remarkably when data was adjusted for repeated measures of health behaviours like smoking, alcohol consumption, diet, and physical activity.

Thus, when these behaviours were entered as time-dependent covariates the increased risk was reduced by 45% for cardiovascular mortality and 94% for noncancer and noncardiovascular mortality.

Thus clearly, a large part of the association between socioeconomic status and mortality is not due to the difference in socioeconomic status per se, but rather due to the poorer health behaviours associated with this status.

There are three possible inferences from these findings:

1) Poor people tend to make poor health “choices” because they are poor. (direct causality)

2) Poor people tend to be poor because they make poor health “choices”. (reverse causality)

3) Certain people tend to be both poor and make poor health “choices”. (no causality)

Reasoning 1) would imply that if people were less poor they would perhaps make better health “choices”.

Reasoning 2) would imply that if people made healthier “choices” they would perhaps be less poor.

Reasoning 3) would imply that that there is something else happening that makes people both poorer and (independently) more likely to make poorer health “choices”.

As pointed out in an accompanying editorial by James Dunn, McMaster University, Hamilton, Canada, most people tend to simplify the debate by explaining the poorer health “choices” of lower socioeconomic status with the greater “stress” of lower socioeconomic status.

But an emerging view could be that both health behaviours and lower socioeconomic status may well be independent expression of factors such as early childhood development, which are well known to affect self-regulation (the ability to guide goal-directed activities over time and across changing circumstances) or higher executive functions (like the skills involved in organisation, planning, self-monitoring, or self-control).

Deficits in these abilities or functions would not only make someone less likely to achieve a higher socioeconomic status but would also influence their ability to adopt and sustain healthy behaviours.

Obviously with obesity these lines of reasoning become far more complex. For e.g. in developing countries, it is often the people in the higher socioeconomic strata that gain weight. Even in Canada, middle class men rather than men in the lower economic group appear to be at higher risk for obesity.

Certainly interesting stuff to ponder on over the long weekend.

AMS
Edmonton, Alberta

Regular readers will recall previous posts on the important influence of social networks on behaviours and risk of weight gain.

Now a study by Sarah-Jeanne Salvy and colleagues from the State University of New York at Buffalo, NY, published in the Annals of Behavioral Medicine, examines whether social activities can potentially affect eating behaviours in kids.

Fifty-four (24 males and 30 females) overweight and non-overweight youth aged 9 to 11 years old were tested using a behavioral choice paradigm which involved participants coming to the laboratory for one session to work on a computer game in pairs, either together with a friend or together with a kid that they did not know. In the game, the kids could earn points exchangeable either for food or for free-play time - as a result of the study design, the play time would either be with their friend or with the unfamiliar kid.

For half of the sample, during the game, the cost of food points increased, while the cost of time playing with another child remained constant. For the other half of the sample, the cost of points for social play increased, while the cost of food points remained constant.

When matched with an unfamiliar kid, the participants substituted food for social activities when the cost of social time with an increased and substituted food for social activities when the cost of food increased - in other words, the kids chose whatever was easier to get.

In contrast, when interacting with a friend, participants did not substitute food for social interactions irrespective of wether or not the choices became easier or difficult.

The results of this experiment clearly support the notion that social interactions may play a key role in food choices and that social interactions with a friend can well serve as a substitute for food in both lean and overweight youth.

Importantly, I would imagine that the reverse also holds true: i.e. kids who don’t get enough time to spend with their friends can substitute this friendship with food. The key word here is probably “friends” as it is apparently not enough to just spend time with any old kid - it’s got to be a friend to be valued as much as food.

So could the fact that our kids don’t get enough time to hang out with their friends be an important driver of the childhood obesity epidemic?

I certainly welcome views on this from my readers!

AMS
Edmonton

Readers of these pages will probably recall the work by Christakis and Fowler demonstrating the “contagious” spread of obesity in a large social network (NEJM 2007).

In a paper appearing in this month’s issue of OBESITY, David Bahr and colleagues from Denver, Colorado, USA, use computer simulation to determine if these findings can be exploited to reverse the obesity epidemic by intervening in social networks.

The paper makes a fascinating read, although the key message is very sobering (despite the rather optimistic interpretation by the authors).

In essence, the simulations suggest that because clusters dominate individual behaviours, once a large cluster of obese individuals has formed it becomes self-sustaining, because an individual in the middle of the cluster (e.g., social network of obese friends) will have a very difficult time sustaining weight loss. The surrounding sea of obesity ensures that even a temporary loss of weight in a few individuals is rapidly reversed, a result that remarkable resembles what is frequently observed in weight loss intervention studies.

Rather than recruiting friends to help with weight loss, the simulations suggest that it may be a better strategy to recruit friends of friends, who help establish contacts to members of other networks.

From a population perspective, one of the more effective strategies could be to target well-connected individuals on the edge of a cluster (i.e., those whose social network contains individuals of more than one BMI cluster). In contrast, targeting poorly connected individuals in a tight network of other obese individuals is likely doomed to failure.

Unfortunately, given the high prevalence of obesity in the US (not so different from that in Canada), the majority of the population already lives in social networks that are obese rather than normal weight. Therefore, finding a critical mass of key “agents of change” will pose challenging, even if the simulations show that these key individuals only have to make up around 1% of the population across BMI ranges.

While all of this sounds great in theory, the paper of course is based on computer simulations - whether or not this knowledge can actually be exploited in real life remains to be seen.

Given my natural skepticism, I am certainly not holding my breath.

AMS
Hamilton, Ontario