There are a total of 307,677 participants in the sample, centered on schoolchildren born from 1930 to 1987, attended school in Copenhagen, Denmark, women and men ages range from 7 to 13 years old with continuation of follow up before or after 55 years. The research question that was addressed is childhood body mass index and change in body mass index associated with adult ischemic stroke and whether it is dependent on age or birth weight? The hypothesis stated obesity at younger ages increases likelihood of early ischemic stroke. If a child is obese at a younger age, then that child may be more likely to have ischemic stroke. The dependent variable is ischemic stroke and independent variable is obesity at younger ages.
The study was based on data of computerized information of 372,636 children born from 1930 to 1989 and measured from 1936 to 2002, with follow up through national health registers from 1977 to 2012 from the Copenhagen School Health Records Register in Denmark. Children who attended public or private schools in Copenhagen, Denmark, before 1983 will undergo annual examination, examined at school entry and exit. Trained school physicians and nurses will measure each child’s weight and height throughout the entire period. Individuals born from 1936 forwards will have their information of name, date of birth, identification number, and birth weight recorded on a health card by their parents. The body mass index (BMI) recorded will be calculated as weight in kilograms divided by height in meters squared and transformed into BMI z score centered on specific age and specific sex reference chosen from a period when the prevalence of obesity was low and stable.
Information on stroke events from Danish National Cause of Death Register, computerized in 1970, and Danish National Hospital Register, established in 1977 will be acquired to support the study. During that period, International Classification of Diseases (ICD) 8th Revision before 1994 and 10th Revision will be used to classify ischemic stroke and unspecific stroke. Before the 1990’s, clinical assessment were used to diagnose ischemic stroke, but after 1990’s imaging were created. Women and men who corresponds to the birth years of 1930 to 1987 were followed up to the date of first ischemic stroke diagnosis, then the date of death. Statistical Analysis were conducted separately for women and men using Cox proportional hazards regression model, age as the core of time axis, to estimate hazard ratios (HRs) and 95% Cis for ischemic stroke according to BMI z scores at ages 7 to 13 years.
This type of research is correlational research and quantitative as researchers use existing information available through public and private schools in Copenhagen from specific date of birth, their weight and height. Also through school health register, national health register, Danish national cause of death register, and Danish national hospital register. The study involved 307,677 participants, about 49% female and 51% male. In this period, 3,529 women and 5,370 men were diagnosed having ischemic stroke, 23% for women and 23.4% for men, correspondingly, happen at 55 years or younger. The incidence rate of ischemic stroke increased with advancing age in both sexes. Men have a higher rate of ischemic stroke occurrence up until age 75, in the meantime after age 75, the rate would rapidly increase in women.
Results of the study reveal that increase in BMI during childhood are certainly associated with ischemic stroke happening before or at age 55. The hypothesis was confirmed that the rise of ischemic stroke incidence is due to obesity at younger age. The study’s result can be of use to scientists as they can create medicine or treatments to reduce the risk of early stroke among individuals of childhood obesity, as well weight reduction or maintenance. Ischemic stroke can affect memory, speech and movement, so it’s important to eat a healthy diet/ balance of nutritious meal and exercise to maintain a healthy body. To avoid having a stroke in the future, it’s best to quit smoking, excess alcohol consumption and physical inactivity. It’s good to be conscious of your health by going to the doctor for body checkup. If you’re overweight or obese, you can practice stroke preventions or go see your doctor.
Health Belief Model theory can be related to the study and components emphasized are perceived susceptibility to stroke and perceive benefit of exercise, quit smoking and excess alcohol intake to reduce risk. Two research questions that ought to be considered for future studies are how does exercising related to having a stroke? Does being underweight decrease your chances of having a stroke? My hypothesis is, if you exercise vigorously, then you may be more likely to have a stroke.
I have chosen this illness/ disease group (stroke), because I have a friend who had a stroke before when she was obese in her childhood. I have heard about adults getting strokes, but not as often as having a stroke at a younger age with obesity. I thought children in childhood would be more active thus having less chances of getting a stroke as compared to adults who are less active. What I disliked about the article is all the numbers involved. There’s a population group, number of cases, BMI z score percentile, percentage, decimal, ratio, model and graph. It gets me all confused, thinking where these number came from and why is it hard for me to understand what the author is trying to say. I’m not good at math, hence the reason why I get confused easily. It seems like every table and graph is about different things and the article does not explain much, such as how do they get these ratio numbers and where do you get 95% CIs from or what does it mean. An example of that would be: BMI z score of 1 at 13 years was associated with hazard ratio 1.21 (95% CI, 1.10-1.33). This one is especially hard for me to understand.
The results and conclusion are useful, but will be more useful if I understood the hazard ratio part. Overall, the greater the BMI z score for a certain age group, the ratio number gets higher as a result the risk of stroke occurs earlier before the age of 55 rather than after the age of 55. If it were my research project, I would do a case study on childhood BMI and change in BMI with first adult ischemic stroke. I prefer detailed description of the event over a bunch of data/number. I would want to know from the beginning of childhood where the participant is getting obese then leading up to getting a stroke. The cautions/limitations I would use about the results of the research is that
The researcher is unable to get accurate cardiovascular disease diagnoses in the Danish National Cause of Death Register. Also, ischemic stroke analyses is combined with unspecified strokes together, which may not be accurate due to the shift in diagnoses usage. As I have mentioned, before a certain period of time, ischemic stroke is diagnosed through clinical assessment, after 1994, everything was done with imaging. We could be careful about using the information they generated by picking the specific date of birth when ischemic stroke is diagnosed by imaging. Instead of studying the time period of 1930 to 1987, start from 1994. Since this study proves the risk of ischemic stroke is associated with obesity at a younger age, then stroke awareness and prevention should be taken to avoid the population increase of stroke. Parents and children should watch carefully over their weight to maintain a normal healthy weight and lifestyle.
This type of research is correlational research as process of empirical and quantitative study were used. Correlation research of linear plot graph on figure 1 shows positive correlation also is based on age among women and men who experienced ischemic stroke. The y-axis is Incidence Rate per 1000 Person-years, starting from 0 to 14, while x-axis is Age at Diagnosis, starting from 25 to 85. This plot graph demonstrates: Incidence Rate of Adult Ischemic Stroke per 1000 Person-years. In figure 1, linear plot graph, 3529 ischemic strokes were among 151955 women and 5370 ischemic strokes among 155722 men. Furthermore, Table 1 demonstrates: BMI, Change in BMI z Score, and Birth Weight Among Women and Men. In the left column, a list of variables were provided Women, BMI at age 7, BMI at age 13, Change in BMI z score between ages 7 and 13, Birth weight, kg, then a repeat of that for Men. The right column would be a list of Mean (SD – Score Distribution).