Abstract
The global burden of cancer, with deaths projected to increase from 7.6 million to 13.1 million by 2030, calls for urgent research into potential mitigating factors, such as Vitamin D levels. This study specifically addresses the correlation between Vitamin D and cancer prevalence among women of reproductive age, scrutinizing variables like age, socioeconomic background, and geographic location. Conducted at Fauji Foundation Hospital's Oncology department through detailed questionnaires, the study analyzes Vitamin D levels in newly diagnosed female cancer patients. While a significant direct association with cancer occurrence was not established, an alarming rate of Vitamin D deficiency and high obesity risk were noted. Furthermore, the study indicates an inverse relation between Vitamin D levels, sun exposure, and certain patient demographics. These findings underscore the necessity of considering environmental and lifestyle factors in cancer prevention strategies.
keywords
Malignancy, Reproductive age, Vitamin D levels, Prevention, Apoptosis, Prognosis
Introduction
Vit-D, a vital nutrient, serves as a precursor to a potent steroid hormone that regulates a wide array of biological functions in the body. Beyond its traditional role in bone metabolism, recent research has elucidated Vit-D's significant involvement in the regulation of disease processes, particularly in the onset and progression of various chronic diseases, including cancer. The antitumor properties of Vit-D are increasingly recognized, influencing cancer development and progression. However, it has been observed that Vit-D metabolism is often altered in different types of cancer, affecting its tumor-suppressing abilities and consequently influencing cancer growth and spread. This alteration in Vit-D metabolism is a critical factor in cancer development, highlighting the potential for new Vit-D-based therapeutic strategies in cancer treatment (Jeon & Shin, 2018). Worldwide, Vit-D deficiency (VDD) and insufficiency (VDI) are on the rise, correlating with an increased risk of various diseases. According to data from the National Health and Nutrition Examination Survey (NHANES) from 2001-2010, the prevalence of VDD and VDI was reported at 28.9% and 41.4%, respectively. These deficiencies were particularly prominent among underprivileged, less educated, overweight adults who had limited physical mobility and low milk consumption. A study in Pakistan among female university students showed that severe VDD was not prevalent, with Vit-D levels remaining above 18.0 ng/ml across different age groups. Vit-D deficiency, defined as serum 25-hydroxy Vit-D levels below 25 nmol/l, is a global issue, especially in regions like the Middle East, China, Mongolia, and India. Less than half of the global population maintains satisfactory Vit-D levels, particularly during winter. The deficiency of Vit-D is a contributing factor to several chronic diseases, including cancer. Addressing Vit-D deficiency is crucial in reducing the risk of cancer development and aiding recovery during cancer treatment. Preventing Vit-D deficiency can mitigate its adverse impact on cancer incidence, prognosis, and survival.
In this research, we tried to describe the relationship between multiple malignancies and Vit-D in females of reproductive age by utilizing proportions of occurrence and pervasiveness as per statistical attributes, such as age, sex, financial status, geographical area, and timeframe. We likewise examine the inconstancy of disease events in connection to changes in hazard aspects, such as decreases in Vit-D levels.
The research objectives are to assess the Vitamin D25 (OH) level in newly diagnosed cancer patients and to evaluate the relationship between vitamin D levels and different malignancies.
The rest of the paper is organized as follows: section 2 has the latest literature, section 3 has the methodology, section 4 has results and discussion, and the last section has the conclusion and future work.
Literature Review
The biological and environmental studies recognized colorectal carcinoma primarily as UVB-sensitive. Ecologically research done in the U.S showed a converse association between sun exposure and colorectal carcinoma, it has been found that elevated levels of Vit-D and high UVB radiation exposures decrease the prevalence and enhance survival rate same was found that more daily sunlight exposure and Vit-D serum 25 (OH ) D levels greatly decrease the risk and occurrence rate of breast malignancy (Ogawa et al., 2022). Several years ago, it was postulated that the decreased incidence and mortality of colorectal, breast, and several other cancers at lower latitudes are due to increased ambient sunlight exposure, which the Garlands postulated acts by producing Vit-D (Miller et al., 2017).
So, we came to know from the latest and previous research and met analysis that vitamin deficiency is one of the non-negligible factors in females' reproductive tumors and in other malignancies, A converse relationship exists among flowing Vit-D 25 (OH) D deficiency, colorectal and breast cancer which could be overcome by Vit-D supplementation, by changing our lifestyle pattern or could be overcome by improving sun exposure. Past randomized controlled trials (RCTS) on cancer occurrence and low administration of Vit-D unfortunately gave inconsistent results. However, high levels of Vit-D supplementation > 1100?IU/day reduce the mortality results.
Methodology
The methodology section explores the link between Vit-D levels and cancer in reproductive-age females at FFH Rawalpindi, Pakistan. Employing an analytical and observational approach, it involves study design and questionnaires to assess factors like dietary habits impacting cancer incidence.
Study Design
Analytical hospital-based observational study. The hypotheses are:
i. Null hypothesis: No relation exists between serum Vit-D (25 (OH) D) level and different malignancies.
ii. Alternative Hypothesis: Relation exists between serum Vit-D (25 (OH) D) and different malignancies.
Study Locale
The study took place in the oncology department of Fauji Foundation Hospital Rawalpindi, a well-equipped 220-bed facility. It focused on examining Vit-D levels in female patients of reproductive age attending the hospital's oncology outpatient department.
Study Population
The research was done among newly diagnosed female cancer patients of the reproductive age group reported in the oncology department. Females belonging to different localities at the time of cancer diagnosis reported between July 2018 to April 2019 were studied.
Sample Size
To make the study more significant, 101 patients with different malignancies were taken. Samples were collected randomly among targeted females reporting in OPD on their regular visits. In this way, 101 samples were collected from 500 populations.
Sampling Technique
The purposive sampling technique, a non-random sampling technique, was applied to choose cancer patients. Focused on particular characteristics of a population and the objective of the study.
Inclusion Criteria
Females of the reproductive age group were focused on any type of malignancy.
Exclusion Criteria
i. Patients on chemotherapy and radiotherapy.
ii. Females of non-reproductive age groups.
iii. Male subjects.
Ethical Issues
The study was approved by the hospital's ethical committee. After obtaining consent, subjects were briefed about the study, and its purpose was explained.
Data Collection
Demographic and risk factor data, including name, sex, age, marital status, education, family history of cancer, chronic illness, physical activity, BMI, waist-to-hip ratio (WPR), Vit-D supplementation, and daily sun exposure, were collected using a structured questionnaire.
The questionnaire is comprised of the following parts.
i. Socio-Demographic Variables.
ii. Lifestyle data.
iii. Dietary intake.
iv. History of chronic illnesses.
v. Biochemical Data
Study Instruments
A customized, pretested questionnaire was used to collect data on various factors influencing disease rates, including age, socio-demographic profile, dietary intake, education, marital status, physical activity, sun exposure, family cancer history, chronic illnesses, and vitamin D and calcium supplementation. The researcher administered this questionnaire to randomly selected participants.
Body Mass Index (BMI)
Body index is specified as body mass index (BMI) and is one of the markers of body fat, and it is used to measure obesity. Obesity was classified into three different groups as per the Asian Pacific Corpulence Arrangement 2018, weight was characterized into three distinct gatherings as:
i. Normal weight (BMI) = 18.5-22.9kg/m2
ii. Overweight (BMI) = 23-24.9 kg/m2
iii. Obese (BMI > 25 kg/m2)
Waist Pelvic Ratio
The waist-hip (WHR) or waist-pelvic ratio (WPR) ratio is the ratio of the circumference of the waist to that of the hips. Calculated as waist size divided by hip size in cm.
Waist Circumference
The waist circumference was recorded by the researcher with the help of a female worker in OPD. It was measured using measuring tape and was measured by placing the tape around the belly button or approximately just above the belly button
Pelvic Circumference
Pelvic circumference was measured by placing the measuring tape at the level of the hip bone and wrapping the tape around the buttock, the widest part of the hip bone.
Dietary Intake
The questionnaire consists of food items that are good sources of vitamin D. Subjects were interviewed about their regular eating habits during the preceding year of the present-onset situation. FFQ was used to estimate the frequency (Days/weeks), frequency times/day, and amount /portion size of the selected food groups.
H/P Reports
Histopathology, defined by The National Cancer Institute as the microscopic examination of diseased cells and tissues, involves a pathologist assessing biopsy samples. These samples, obtained through biopsy or minor surgery, are prepared in a histopathology lab into thin slices and stained for detailed analysis under a microscope. This process helps in identifying specific tissue characteristics, which is crucial for determining the nature of a tumor and guiding cancer treatment.
Biochemical Evaluation of Vit-D Level (Immunoassay Kit)
The active form of Vit-D in the blood is measured using the Enzyme-Linked Immunosorbent Assay (ELISA) technique, a process taking around 1 hour and 30 minutes. The ELISA kit, used for quantifying both Vit-D3 and D2 in serum, is a standard tool in fields like immunology and cancer research. Vit-D levels are determined in nmol/l using this method and categorized according to Endocrine Society guidelines:
i. Deficient: < 20ng /ml and or <50nmol/l
ii. Insufficient: 21 – 29ng /ml or 52nmol/l - 73nmol/l
iii. Sufficient: > 30ng/ml or > 74nmol/l
Statistical Methods for Data Analysis
Data was coded and entered SPSS Version 22 for analysis. Chi-square tests examined the relationship between serum Vit-D and various malignancies, while ANOVA assessed the mean serum 25 (OH) Vit-D levels across different variables. Results were compared with standard outcomes, considering a p-value of < 0.050 as significant.
Results and Discussion
The research findings emphasize the importance of data analysis as a crucial step in research. The collected data was analyzed using SPSS-22. Descriptive statistics such as means, frequencies, and ratios were employed for data interpretation. After analysis and tabulation, critical examination led to clear conclusions. The Chi-square test was used to determine relationships between dependent and independent variables, while ANOVA was applied to assess significant differences, with a significance threshold set at p < 0.05.
Prevalence of Cancer in Females of Reproductive Age Group
The occurrence of malignancies in women of reproductive age group in the presence of the following characteristics, i.e. family history, parity and education status, sun exposure, physical activities, obesity, dietary habits, and chronic illnesses, were studied.
The rate of occurrence of different malignancies in females of reproductive age group, among 101 respondents, a maximum of 60% cases were of a breast, and only 1% case of RCC was documented.
Table 1
Descriptive Analysis of Vitamin –D Levels in Cancer Patients border="1" cellspacing="0" cellpadding="0" width="100%">
width="9%">
Num
width="13%">Minimum
width="14%">Maximum
width="11%">Mean
width="28%">Std. Deviation
Vitamin- D Levels
width="9%">101
width="13%">7.50
width="14%">141
width="11%">39.0
width="28%">21.96215
Table depicts the descriptive analysis of serum 25 (0H) Vit-D in cancer patients. Patients had a mean value of 39.0, the lowest value of 7.50, and the highest value of 141.
Table 1
Table 1>Frequency Distribution of Vitamin –D Levels in Cancer Patients border="1" cellspacing="0" cellpadding="0" width="100%">
less than 50nmol/l or < 20ng/ml very deficient
width="33%">50 nmol/l - 73nmol/l or 21 -29ng/ml insufficient
width="33%">74-150 nmol/l or 30 -100 ng/ml sufficient
81(80.2%)
width="33%">12(11.9%)
width="33%">8(7.9%)
Table 1 depicts the overall frequency distribution of 25(OH) Vit-D levels in female cancer patients were found, where a maximum of 80.2% of Vit-D levels were lying at very deficient levels.
Table 2
Table 2>Frequency distribution of Vit-D levels in multiple malignancies border="1" cellspacing="0" cellpadding="0" width="100%">
VIT-D LEVELS P-value: 0.80
Clinical Diagnosis
width="21%">less than 50nmol/l or < 20ng/ml very deficient
width="22%">> 50 nmol/l - 73nmol/l or 21 -29ng/ml insufficient
width="20%">74-150 nmol/l or 30 -100 ng/ml sufficient
width="10%">Total
CA BREAST
width="21%">48
width="22%">10
width="20%">3
width="10%">61
CA LUNG
width="21%">1
width="22%">0
width="20%">0
width="10%">1
H.L
width="21%">1
width="22%">0
width="20%">0
width="10%">1
SOL Brain
width="21%">1
width="22%">1
width="20%">0
width="10%">2
CA OVARY
width="21%">9
width="22%">0
width="20%">1
width="10%">10
CA CERVIX
width="21%">4
width="22%">0
width="20%">1
width="10%">5
CA ENDOMETRIUM
width="21%">5
width="22%">0
width="20%">1
width="10%">6
RECTUM
width="21%">2
width="22%">0
width="20%">0
width="10%">2
OESOPHAGUS
width="21%">1
width="22%">1
width="20%">0
width="10%">2
SARCOMA
width="21%">4
width="22%">0
width="20%">1
width="10%">5
NHL
width="21%">6
width="22%">0
width="20%">0
width="10%">6
TOTAL
width="21%">81
width="22%">12
width="20%">7
width="10%">101
Table 2 depicts the frequency distribution of Vit-D levels in multiple malignancies. In total, 81% of cases were at very deficient levels, 48% of which were cases of breast cancer. The significance of the non-significant P value is 0.80.
Table 3
Descriptive Statistics and Characteristics of Cancer Patients border="1" cellspacing="0" cellpadding="0" width="100%">
Descriptive Statistics
width="62%" colspan="4">Mean ± SD
AGE
width="62%" colspan="4">40.59±7.63
BMI
width="62%" colspan="4">2.72±0.82
WPR
width="62%" colspan="4">2.74±0.54
Characteristics OF Patient
Variables
width="32%" colspan="2">Frequency
width="29%" colspan="2">Percent Frequency
BMI
width="32%" colspan="2">n
width="29%" colspan="2">%
<18.5under-wt
width="32%" colspan="2">9
width="29%" colspan="2">8.9
18.5-24.9 healthy
width="32%" colspan="2">25
width="29%" colspan="2">24.8
25.0- 29.9 over-wt
width="32%" colspan="2">52
width="29%" colspan="2">51.5
> 30 obese
width="32%" colspan="2">15
width="29%" colspan="2">14.9
WPR
0.80 or low risk
width="32%" colspan="2">5
width="29%" colspan="2">5.0
0.81- .84moderaste risk
width="32%" colspan="2">16
width="29%" colspan="2">15.8
0.85 or high risk
width="32%" colspan="2">80
width="29%" colspan="2">79.2
Family History
Yes
width="32%" colspan="2">10
width="29%" colspan="2">9.9
No
width="32%" colspan="2">80
width="29%" colspan="2">79.2
Other than this
width="32%" colspan="2">10
width="29%" colspan="2">9.9
Marital Status
Single
width="32%" colspan="2">13
width="29%" colspan="2">12.9
Married
width="32%" colspan="2">83
width="29%" colspan="2">82.2
Divorce
width="32%" colspan="2">5
width="29%" colspan="2">5.0
Parity Status
Nulli
width="32%" colspan="2">13
width="29%" colspan="2">12.9
Primi
width="32%" colspan="2">10
width="29%" colspan="2">9.9
Multi
width="32%" colspan="2">78
width="29%" colspan="2">77.2
Type of Housing
Indoor
width="32%" colspan="2">25
width="29%" colspan="2">24.8
Outdoor
width="32%" colspan="2">76
width="29%" colspan="2">75.2
Exposure to Sunlight
Yes
width="32%" colspan="2">80
width="29%" colspan="2">79.2
No
width="32%" colspan="2">21
width="29%" colspan="2">20.8
Average Sun Exposure
less than 5 min /day
width="32%" colspan="2">4
width="29%" colspan="2">4.0
5-15 min /day
width="32%" colspan="2">13
width="29%" colspan="2">12.9
15 30 min /day
width="32%" colspan="2">31
width="29%" colspan="2">30.7
>30 min /day
width="32%" colspan="2">53
width="29%" colspan="2">52.5
Use of Veil
Yes
width="32%" colspan="2">23
width="29%" colspan="2">22.8
No
width="32%" colspan="2">78
width="29%" colspan="2">77.2
Exercise /Physical Activity
Yes>No
width="33%" colspan="2">21 align="center">80
width="28%">20.8 align="center">79.2
Chronic Illness
Yes
width="33%" colspan="2">21
width="28%">20.7
No
width="33%" colspan="2">80
width="28%">79.2
Table 3 shows BMI and WPR in female cancer patients: 51.5% overweight, 14.9% obese, and 79.2% at high risk. Of breast cancer patients, 8% had a family history of cancer, with 11% overall. Sun exposure was daily for 79.2%, over 30 minutes for 52.5%, 77.2% didn't wear veils, 77.2% were multiparous, and 79.2% didn't exercise.
Table 4
Mean ±SD Serum Levels of Vit-D with respect to Lifestyle border="1" cellspacing="0" cellpadding="0" width="100%">
Variables
width="36%">Vit-D levels. (Mean ± SD)
width="32%">P value
Body Mass Index
width="36%">width="32%">
0.16*
>18.5 under-wt
width="36%">57.4333±23.100
width="32%">
18.5-24.9 healthy
width="36%">38.5160±22.6
width="32%">
25.0- 29.9 over-wt
width="36%">36.17692±0.98
width="32%">
< 30 obese
width="36%">38.6067±20.22
width="32%">
Waist pelvic ratio (WPR)
width="36%">width="32%">
0.20*
0.80 or low low-risk
width="36%">67.180±09.50
width="32%">
.81-.84 moderate-risk
width="36%">41.6438±25.7
width="32%">
.85 or high high-risk
width="36%">36.7238±20.5
width="32%">
Average Sun Exposure/wk
width="36%">width="32%">
0.26*
less than 5 min /day
width="36%">38.0000±31.32
width="32%">
5-15 min /day
width="36%">39.0769±24.65
width="32%">
15- 30 min /day
width="36%">39.9516±19.47
width="32%">
>30 min /day
width="36%">38.5208±22.60
width="32%">
USED VEIL
width="36%">width="32%">
0.29*
Yes
width="36%">38.6391±21.24
width="32%">
No
width="36%">39.1205±22.30
width="32%">
Sun Screen
width="36%">width="32%">
0.12*
Yes
width="36%">70.2000
width="32%">
No
width="36%">38.6990±21.84
width="32%">
Exercise
width="36%">width="32%">
0.33*
Yes
width="36%">49.9190±32.59
width="32%">
No
width="36%">36.1475±17.36
width="32%">
Type of Housing
width="36%">width="32%">
0.51*
Indoor
width="36%">38.6520±22.03
width="32%">
in and out the door both access
width="36%">39.1289±22.08
width="32%">
Vit-D with Ca
width="36%">width="32%">
0.05**
yes/dose IU/day
width="36%">41.5000±25.16
width="32%">
No
width="36%">38.9021±22.11
width="32%">
Table 4 depicts the association of different variables with serum vitamin D levels. Statistical non-significant values are found between BMI, WPR, average sun exposure, and daily physical drills. Between serum 25(OH) vitamin D level and serum 25(OH) vitamin D and calcium supplements, there is a statistically significant p-value of 0.05.
Table 5
Using One-Way ANOVA, while Percentages were compared using Chi-square
| ANOVA | > width="20%"> Sum of Squares width="10%">Df width="17%">Mean Square width="10%">F width="8%">Sig | > Body Mass Index width="15%">Between Groups width="20%">63.571 width="10%">86 width="17%">.739 width="10%">2.218 width="8%">.048 | > Within Groups width="20%">4.667 width="10%">14 width="17%">.333 width="10%">width="8%">
| > Total width="20%">68.238 width="10%">100 width="17%">width="10%"> width="8%">
| > Waist Pelvic Ratio width="15%">Between Groups width="20%">27.307 width="10%">86 width="17%">.318 width="10%">2.223 width="8%">.048 | > Within Groups width="20%">2.000 width="10%">14 width="17%">.143 width="10%">width="8%">
| > Total width="20%">29.307 width="10%">100 width="17%">width="10%"> width="8%">
| > Family History width="15%">Between Groups width="20%">14.823 width="10%">86 width="17%">.172 width="10%">.391 width="8%">.996 | > Within Groups width="20%">6.167 width="10%">14 width="17%">.440 width="10%">width="8%">
| > Total width="20%">20.990 width="10%">100 width="17%">width="10%"> width="8%">
| > Average Sun Exposure/wk width="15%" rowspan="3">Between Groups>Within Groups>Total width="20%">64.861 width="10%">86 width="17%">.754 width="10%">1.508 width="8%">.196 | > 7.000 width="10%">14 width="17%">.500 width="10%">width="8%">
| > 71.861 width="10%">100 width="17%">width="10%"> width="8%">
| |||||||
*Means in two groups were compared using one-way ANOVA, while percentages were compared using chi-square as shown in Table 5.
Table 6
Frequency Distribution of Intake of Meat in Cancer Patients border="1" cellspacing="0" cellpadding="0" width="100%">
width="12%">
Daily %
width="15%">1-2/wkly %
width="18%">Once/2wkly %
width="26%">1/2Times/monthly%
width="15%">Never %
Mutton
width="12%">width="15%">
12.9
width="18%">6.9
width="26%">29.7
width="15%">50.5
Beef
width="12%">width="15%">
16.8
width="18%">12.9
width="26%">32.7
width="15%">37.6
Chicken
width="12%">1.0
width="15%">45.5
width="18%">21.8
width="26%">17.8
width="15%">13.9
Fish
width="12%">width="15%">
5.9
width="18%">5.0
width="26%">49.5
width="15%">36.6
Table 6 depicts the frequency of intake of four meat products: mutton, beef, chicken, and fish. The chicken weekly intake (45.5 %) is the most frequent, whereas the mutton intake is the least, at 29.7 % monthly.
Table 7
Frequency Distribution of Intake of Dairy Products in Cancer Patients border="1" cellspacing="0" cellpadding="0" width="100%">
width="12%">
Daily %
width="15%">1-2/wkly %
width="18%">Once/2wkly %
width="26%">1-2 Times/Monthly %
width="19%">Never %
Egg
width="12%">16.8
width="15%">32.7
width="18%">7.8
width="26%">13.9
width="19%">18.8
Milk
width="12%">width="15%">
42.6
width="18%">14.9
width="26%">6.9
width="19%">32.7
Lassie
width="12%">width="15%">
9.9
width="18%">19.8
width="26%">6.9
width="19%">5.0
Yogurt
width="12%">width="15%">
61.4
width="18%">1.0
width="26%">73.3
width="19%">26.7
Table 7 depicts the frequency of intake of eggs, milk, lassie, and yogurt. The frequent intake of eggs is weekly (32.7%) and yogurt (73.3%) monthly, whereas the intake of milk is (42.6%) weekly and lassie (19.8%) 2wkly.
Table 8
Association (Chi-Square Asymp. Sig.2-sided) between Vit-D levels and Food Group Consumption in Cancer Patients border="1" cellspacing="0" cellpadding="0" width="100%">
Vit-D Status
width="76%" colspan="5">Meat Products
width="12%">
Mutton align="center">0.30*
width="16%">Beef align="center">0.47*
width="16%">Chicken align="center">0.20*
width="30%" colspan="2">Fish align="center">0.17*
Dairy /poultry products
width="12%">
Eggs align="center">0.39*
width="16%">Milk align="center">0.51*
width="16%">Lassie align="center">0.31*
width="16%">Yogurt align="center">0.24*
width="13%">Cheese align="center">0.17*
Fruits / Nuts
width="12%">
Nuts align="center">0.71*
width="16%">Peach align="center">0.78*
width="16%">Oranges align="center">0.16*
width="16%">Apricots align="center">0.57*
width="13%">Others align="center">0.20*
Table 8 depicts the association between food groups and vitamin D levels. No statistically significant values are found between meat, dairy, poultry, and fruits and vitamin D levels.
Discussion
This research involved 101 female patients, with 60% having breast cancer, 10% ovarian, 6% endometrial and non-Hodgkin’s lymphoma, 5% cervical and sarcoma, 2% rectal, esophageal and brain, and 1% each Hodgkin lymphoma, lung cancer, and renal cell carcinoma (RCC). Most cancers were reproductive system-related. Globally, breast cancer is the leading cause of female mortality. (Ullah, Nadeem, Abrar, Amin, Salam, & Khan, 2023). A Karachi study found that 24.9% of 402 female participants had breast cancer, with a majority being illiterate and from lower socioeconomic backgrounds (Saeed et al., 2019). In our study, Vit-D deficiency (<50 nmol/l) was common, affecting nearly half the population. At Aga Khan University Hospital, 75% of patients were Vit-D deficient, 16% insufficient, and 9% sufficient (Khan et al., 2015). Our study found an average serum Vit-D level of 39.0 nmol/l, with 80.2% deficient and 11.9% insufficient.
Table 2 shows Vit-D levels across various cancers in females of reproductive age: 48% with breast cancer, 9% with ovarian, and 5% with endometrial cancer were Vit-D deficient. Additionally, 4% with cervical cancer and 6 cases of non-Hodgkin's lymphoma showed deficiency. 81% of cancer cases were Vit-D deficient, 12% insufficient, and 7% sufficient, with a non-significant p-value of 0.80.
One of the studies showed that in a country like Pakistan, which is situated near the equator with plenty of sunlight, it is unforeseen to have such an elevated incidence of Vit-D deficiency and cancer incidence, several sociodemographic and lifestyle factors have been reported to be linked with Vit-D deficiency (Safari et al., 2017).
Table 4 A study with participants averaging 44.4 years found no significant difference in vitamin D levels between those who exercised and those who didn't. (Heald, 2023) study on breast cancer patients, average age of 40, showed 64.8% had no family cancer history, and 99.2% were married at diagnosis, suggesting cancer occurrence might be influenced by environmental rather than familial factors. Despite sufficient sunlight, most of Pakistan's population is deficient in vitamin D. Table 4 indicates that 79.2% of female cancer patients are at high obesity risk, correlating obesity and Vit-D deficiency with cancer occurrence. Another study on breast cancer patients found varied BMI distributions, while a thyroid cancer study revealed a higher obesity rate in older women.
Table 4 Mean ±SD of Vit–D level with respect to lifestyle depicted in this, and only a significant p-value of 0.05 is seen in Vit– D with Ca.
One of the clinical randomized trials was done in the past on intake of Vit-D supplementation signal reduction in cancer death rather than in incidence. However, it was surprising to know that a greater reduction was seen among the participants who were average weight or lower weight.
In Table 5, a one-way ANOVA and chi-square tests analyzed the relationship between various variables and Vit-D. Table 7 shows that 45.5% of female cancer patients consume chicken weekly, and 49.5% eat fish monthly, indicating these as primary Vit-D sources. Red and processed meats are associated with higher breast cancer risks. Table 8 reveals limited dairy consumption among these patients, with 42.6% drinking milk daily. High dairy intake potentially reduces colorectal and breast cancer risks. Table 9 finds no significant correlation between Vit-D levels and food consumption. The study highlights the need for more research on VDD in diverse socio-economic groups in Pakistan, where low education and unhealthy lifestyles are prevalent. Despite limited data, the rising cancer prevalence in Pakistan and the lack of family cancer history in most cases suggest environmental factors' role in cancer development.
Conclusion and Future Work
The study confirms a link between Vit-D deficiency and multiple malignancies in reproductive-age females. While cancer isn't solely dependent on Vit-D levels, it's associated with lifestyle factors like obesity and environmental influences. High cancer risk in premenopausal females is attributed to obesity and lack of physical activity, with poor dietary habits and insufficient Vit-D intake as contributing factors. This necessitates national surveys to better understand this issue and emphasizes the need for lifestyle changes, including diet modifications and increased physical activity. Further research on environmental and genetic interactions is essential, particularly regarding the role of Vit-D in cancer prognosis and recurrence. Education about Vit-D-rich foods and supplementation is vital, as 80.2% of the study participants were Vit-D deficient. This research paves the way for further studies on the critical role of Vit-D in cancer among Pakistani females, especially considering their adequate sun exposure but high cancer incidence without a family history.
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Cite this article
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APA : Naseer, R., Cheema, N. H., & Ikram, Q. (2023). Multiple Malignancies in Relation to Vitamin D Levels Among Women of Reproductive Age. Global Drug Design & Development Review, VIII(IV), 34-45. https://doi.org/10.31703/gdddr.2023(VIII-IV).04
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CHICAGO : Naseer, Rashida, Naseer Haider Cheema, and Quratulain Ikram. 2023. "Multiple Malignancies in Relation to Vitamin D Levels Among Women of Reproductive Age." Global Drug Design & Development Review, VIII (IV): 34-45 doi: 10.31703/gdddr.2023(VIII-IV).04
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HARVARD : NASEER, R., CHEEMA, N. H. & IKRAM, Q. 2023. Multiple Malignancies in Relation to Vitamin D Levels Among Women of Reproductive Age. Global Drug Design & Development Review, VIII, 34-45.
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MHRA : Naseer, Rashida, Naseer Haider Cheema, and Quratulain Ikram. 2023. "Multiple Malignancies in Relation to Vitamin D Levels Among Women of Reproductive Age." Global Drug Design & Development Review, VIII: 34-45
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MLA : Naseer, Rashida, Naseer Haider Cheema, and Quratulain Ikram. "Multiple Malignancies in Relation to Vitamin D Levels Among Women of Reproductive Age." Global Drug Design & Development Review, VIII.IV (2023): 34-45 Print.
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OXFORD : Naseer, Rashida, Cheema, Naseer Haider, and Ikram, Quratulain (2023), "Multiple Malignancies in Relation to Vitamin D Levels Among Women of Reproductive Age", Global Drug Design & Development Review, VIII (IV), 34-45
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TURABIAN : Naseer, Rashida, Naseer Haider Cheema, and Quratulain Ikram. "Multiple Malignancies in Relation to Vitamin D Levels Among Women of Reproductive Age." Global Drug Design & Development Review VIII, no. IV (2023): 34-45. https://doi.org/10.31703/gdddr.2023(VIII-IV).04