Assessment of food intake and activity

Assessment of food intake and activity
Introduction
Issues related to food intake values like malnutrition has been well researched in the past decades. It is a common issue in the
developing or the under-developed countries. The following study is an analysis of the data to find out about the health condition
among women. Women have different nutritional needs due to their menstrual health, pregnancy, breastfeeding and menopause.
Micronutrients and mineral are essential to maintain hormone flow in the body. As a result, women may need higher quantities of
nutrients than men. Moreover, the prevalence of dieting and weight-related food intake variation is also more popular among women.
The interplay of hormones may result in cravings of certain food items that also impact the health and nutrition among them 1. It
becomes even more difficult to manage their normal diet in such cases. Due to their menstrual flow, women have an increased
requirement of iron. Calcium is another mineral that is essential for regulating the thyroid hormone which is again associated with
reproductive health2.
Methods
The sample size of 221 students was chosen but 43 of them were males and were excluded since this analysis focuses only on the
nutritional demands among women. The rest data collected from 178 females have been included in the analysis. The average age of
the students was 24 (SD 6.0). Age of the respondents was within 19 to 51 years. The consent of the students was gained and they were
also asked to present their acknowledgement through a written form. They were briefed about the process and were asked to maintain
to close watch on the food items and its quantity they were having for the three days. They were asked to eat according to their normal
preference and habit rather than maintaining a healthier diet only for the 3 days. A form was provided to the students, that allowed
them to record the food they ate in a systematic manner. They were also asked to fill a set of questionnaires that recorded their
demographics, height, weight and any health issues.
In order to analyse the statistical data, STATA SE 15 was used. The statistical significance was p < 0.05. In order to assess the
differences between the means obtained through various assessments, t-test was used. Pearson’s Correlation Coefficient was used for

the correlation process and the inadequacy of micronutrients like calcium, folate, vitamin C and zinc was measured through the EAR
cut-point method.

Results
Statistic
Energy intake
(kJ/d) - 3 day
food record
Number (N) 169
mean 7546.2
standard deviation (SD) 187.1
standard error (SE) 2432.5
p25 6112.0
p50 (median) 7300.0
p75 8672.0
Interquartile range (IQR) (e.g. Q3 - Q1 =
IQR) 2560.0
min 1400.0
max 19748.0

Percentage energy derived from fat, carbohydrate, protein and micronutrient intakes
Statistic
Daily
%
energy
from
fat - 3
day
food
record
Daily %
energy from
carbohydrate
- 3 day food
record
Daily %
energy
from
protein -
3 day
food
record
Calcium
intake
(mg/d) -
3 day
food
record
Iron
intake
(mg/d)
- 3 day
food
record
Folate
intake
(ug/d) -
3 day
food
record
Vitamin
C intake
(mg/d) -
3 day
food
record
Zinc
intake
(mg/d) -
3 day
food
record
Number (N) 169 169 169 169 169 169 169 169
mean 32.6 41.5 21.0 756.4 12.1 406.6 111.9 10.6
standard deviation (SD) 0.7 1.0 0.8 36.8 0.5 14.4 7.5 0.7
standard error (SE) 8.6 12.7 10.0 477.9 7.0 187.5 97.5 9.3
p25 27.0 35.0 16.0 506.0 8.0 300.0 54.0 7.0
p50 (median) 33.0 42.0 19.0 715.0 11.0 384.0 90.0 9.0
p75 38.0 48.0 23.0 910.0 14.0 500.0 134.0 11.0
Interquartile range (IQR) (e.g. Q3 -
Q1 = IQR) 11.0 13.0 7.0 404.0 6.0 200.0 80.0 4.0
min 3.0 2.0 1.0 0.0 0.0 0.0 0.0 0.0
max 60.0 90.0 89.0 4973.0 52.0 1000.0 842.0 91.0