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"Domestic Water Usage in Relation to Household Income in New Jersey" by Nayyab Farooq

Domestic Water Usage in Relation to Household Income in New Jersey

Nayyab Farooq, Fairleigh Dickinson University


Abstract: This paper studies how household water consumption correlates with household income. The study focuses only on New Jersey and assessed the relationships of water usage with age, gender, household size, township of residence, and cultural background. A survey was distributed in two rounds to collect quantitative data. The first round received 328 responses and the second round received 15 responses. After the data was analyzed, no specific correlation between income and water consumption could be concluded; however, there was a direct relationship between household size and water usage. In addition, there were statistical significances of water usage in relation to age and cultural background. The experiment is important because it shows that household size, age and cultural background must be addressed when planning solutions for more sustainable water consumption to combat water insecurity. Additionally, more than 70% of the respondents made conscious choices about water consumption, which can be considered when organizing educational programs to promote low water consumption.


 

Introduction


Water security is a luxury that is not distributed evenly throughout society. According to the Dictionary of Environmental Science and Technology, the average household consumes “600 litres of water a day” (Water Usage (Domestic), 2008).More specifically, 200 liters are used for showers and drinking, and a washing machine can use up to one hundred liters per wash (Water Usage (Domestic), 2008). This shows that since the early 2000s, people who have access are consuming copious amounts of water. While a household’s daily routines consume copious amounts of water, many families across the globe struggle to find enough water to fulfill their necessities. According to a report by UNICEF in 2021, “1.42 billion people – including 450 million children – live in areas of high or extremely high-water vulnerability.”

 

One of the most imperative problems regarding sustainability and the economy is that of water “in which the management of water resources is an important point of debate for the future,” (Diniz & Bermann, 2012).Water usage is not a singular issue, as it is related to the economy and areas of sustainability, such as zero hunger, wellness, and no poverty. Water usage, zero hunger, good health, and no poverty are all included in the 17 United Nations sustainability goals (THE 17 GOALS | Sustainable Development, n.d., p. 17). Considering other areas of sustainability is an important factor to consider when discussing the issue of water shortage and constructing solutions.

 

It is essential to define water security in this paper as it affects certain groups of people more than others and is connected to several factors. According to the study, “Water Security in Native American Communities of Nevada,” water security is defined as “…having reliable access to enough water of an acceptable quality to support community health, livelihoods, and commodity production.” Water security in a household describes the availability of water resources for hygiene, hydration, and cooking.

 

Water security is related to household income and home ownership. In their study, Bandala’s team explains that “Native American households are 19 times more likely than white households not to have indoor plumbing” (Bandala et al., 2022). This indicates that there is a significant disparity in water security based on race and ethnicity in the community. This is a consequence of the systemic segregation of certain racial groups in the United States, which puts minority groups at an automatic disadvantage. This is caused by explicit segregation instituted against these groups in history (The Origins of Urban Segregation in the United States, n.d.). Now moving abroad, in the study by Olufemi O. Aluko’s team, access to drinking water in the Osun State of Nigeria was directly related to home ownership (Aluko et al., 2022). Homeownership is one indicator of a person’s wealth. This means that there is a potential correlation between water consumed and the financial status of a person or household, however, the study did not investigate this relationship, let alone its presence in the United States.

 

Just as homeownership may affect water consumption, food demand may also suggest a correlation between water usage and income. In another study, Dr. Yuhan Liang, from Guangdong University of Technology, examined water management in relation to food demand on a regional level in China. Liang and his team found that when the standard of living increased, the demand for food rose, causing more water scarcity. They predicted that finding a method to decrease meat consumption would reduce water scarcity in the region (Liang et al., 2021). Therefore, it appears that more wealth in a household can lead to more water usage, as the demand for food is higher in those. However, Liang and his colleagues did not research the relationship between financial status and water consumption.

 

While standard living may affect water use, the following study suggests a relationship between access and water usage. In 2014, Dr. Rebecca Sultana, from the University of Dhaka, Bangladesh, surveyed the water usage for personal and domestic hygiene in low-income urban communities in Dhaka. Her team collected observations and conducted interviews from the East Arichpur area of Tongi Township from September 2014 to June 2016. They found that “Participants with access to water 24 h a day used more water (48 LCPD) than the participants who had <24 h access to water (38 LCPD) in the households” (Sultana et al., 2022). LCPD stands for liter per capita per day. This indicates that people who had access to water all day utilized more water than those who did not. Therefore, it appears that people who had ready access to water must have been financially secure and physically situated near a water supply. However, Sultana's team did not focus on the specific correlation between wealth and water consumption.

 

Global water security is affected by individual water consumption. It is reported in the Atlas of Water that the use of a shower head can waste 2,900 gallons of water every year, which is equivalent to sufficient energy to power their home for 13 days and 70 US dollars per year (Water at Home, 2016). Furthermore, it is predicted that by 2025, “4 billion people will be living in areas of water stress” (Water Shortage, 2016). This is alarming, as currently, the world population is approximately 8 billion (U.S. and World Population Clock, 2024), meaning that by the end of next year, fifty percent of the world's population will struggle to find water. Therefore, families must conserve and use water responsibly today so that it can be saved for the future. Moreover, in the U.S, “40 out of 50 state water managers expect water shortages under average conditions in some portion of their states over the next decade” (US EPA, 2017).


In New Jersey alone, it was predicted that “the state’s population will increase by nearly 1 million people by 2020. This population growth in New Jersey would place additional demand on the state’s water resources and infrastructure, particularly in areas that have not experienced high water demand before” (New Jersey Water Fact Sheet, 2010). Indeed, the population grew from roughly eight million in 2010 to nine million in 2024 (New Jersey Population 2024 (Demographics, Maps, Graphs), n.d.). To understand factors for high water usage, I will examine the relationship between a household's socioeconomic status and its water consumption in New Jersey. My research question is: “What is the relationship between a household’s socioeconomic status and water consumption in New Jersey?”

 

According to a study by Hassaan Furqan Khan, from Tufts University, “wealthier households use more water” than poorer households in Karachi Pakistan (Khan et al., 2023). Similarly, I hypothesize that people with lower incomes will consume less water than those with higher incomes in New Jersey.

 

Methods

 

Experiment Survey 

 

My experiment consisted of a survey that was conducted to gather information about an individual’s demographics, socioeconomic status, and water usage. To learn the demographics of the individual, I attempted to address possible factors that can have a relationship with an individual’s water usage. These included age, gender, township of residence, household size, cultural background, and income. Additionally, I included a question about where the individual lived, so that I could filter the responses to only those who lived in New Jersey. To learn the water consumption pattern of an individual, I asked several questions that related to water usage in one’s daily routine. Water consumption was measured by a water usage score which was the total water used over all the routine tasks asked about in the survey. Each option in the water usage questions in the survey was assigned a specific score. At the end of the study, the scores for all the choices the respondent selected were tallied up into a total score. This total score defined the water usage score. The score ranged from one (little water usage) to eight (heavy water usage). A score of four and five indicated moderate water usage. At the end of the survey, I also included a question about individuals’ consciousness about their water usage, which may be interesting to analyze in the future. The questions were simply worded, so that various age groups could easily answer them. Furthermore, the questions were multiple choice (except the fourth question) so that I could tabulate and produce graphs because, without this format, there can be a lot of variety in answers, which will complicate the condensing and organization of the data. My survey is provided in Appendix A at the end of this paper (the score for each option is listed in the brackets).

 

 

Distribution 

 

I received a total of 343 responses for my survey, which was distributed to as many people as possible in the community. There was no set number of distributed forms. The 328 responses were received initially. Ten days later, after adding a question about household size and a few more about water usage, the second distribution of the survey received 15 more responses. I used Qualtrics to make my survey. The form was completely anonymous so that people felt comfortable answering the questions. I sent the form out to the public through social media platforms, such as Facebook and Instagram. Additionally, I asked friends and relatives to spread the survey, and I requested the honors department at Fairleigh Dickinson University (FDU) to send the form to the FDU Community through an email blast. This allowed me to reach as many people from New Jersey as possible. Most of the people I was able to reach were from Central Jersey.

 

Analysis Method 

 

To analyze the data, I compared certain independent variables to the water usage score that was counted in the survey. This allowed to account for an individual’s overall water usage, instead of a specific task. One way I analyzed the data was by plotting the individual’s income range (independent variable) against the individual’s score (dependent variable), to visualize a relationship between the two conditions. Another way was that I computed the average score of each income range and its standard deviation. Then I used these values and an unpaired T-test assuming equal variance to observe a relationship between income and water usage. 


Secondly, I calculated the average water usage score for each township and its standard deviation. Then, I arranged the data on a map to visualize how overall water consumption differed in various parts of New Jersey.    

 

Thirdly, I computed the average score and its standard deviation for each “potential factor,” which included age group, gender, cultural background, and household size. Then I observed the trends between each factor and the water usage score using an unpaired T-test assuming equal variance.  

 

Lastly, using the method stated in the previous paragraph, I observed the relationship between respondents’ conscious choices of water usage (independent variable) and their scores (dependent variable). I also observed the relationship between an individual’s income (independent variable) and conscious choices of water consumption (dependent variable). 

 

Results

 

This paper aims to study the relationship between an individual’s (or household’s) income and an individual’s routine water consumption. The data presented in the following subsections show the results of the survey responses.

 

Income and Water Usage Score 

 

Figure 1, Table 1, and Table 2 present data showing the relationship between income range and water usage. The data for this subsection was taken from the first survey, which received 328 responses. Out of the 328 responses, 292 were used in the analysis, as the others got filtered out due to out-of-state residence or incompletion of the survey. The following box and whisker plot in Figure 1 shows the relationship between income range and water usage. Additionally, Table 1 presents the average water usage and standard deviations for the 4 income ranges. Table 2 presents the results of the T-tests conducted between different income ranges.

 

As shown in Figure 1, the median water usage score for income groups $40,000 or less, $40,001- $60,000, $60,001- $100,000, and $100,001 or more was approximately 4. There was more variance in the data for the income group of $40,000 or less.




 As shown in Table 1, the average water usage score for income groups $40,000 or less, $40,001- $60,000, $60,001- $100,000, and $100,001 or more was approximately 4. The standard deviation for the income group of $40,000 or less was higher than the other groups by about 0.5, showing that there was more variance in the scores for this group. The sample size for the $100,001 or more income range was the greatest and was very large compared to the other groups. The larger sample size conveys that it is more representative of the population with this income level in comparison to the other groups.        



As shown in Table 2, all tests reported no significant difference in the data.

Water Usage in Various Parts of New Jersey 


The map below shows the average water usage score in various townships of New Jersey on a spectrum: yellow represented high water usage and blue represented low water usage. Areas shaded in grey were not included in the survey, as the survey did not reach a resident from that township.

 

Based on the map in Figure 2, there is no correlation between the water usage score and the area of New Jersey (Figure 2). Most of the townships included in the survey had a moderate score of 4, which is depicted by green shading. There was only one township, Howell Township, that had the highest water usage score of 8. Howell Township is located centrally on the map and is the only area on the map that is completely yellow. There were 4 areas north of Howell that had high scores. Randolph, Passaic, Dunellen, and Hillsborough had an average score of 7, while Plainsboro had an average score of 6.



 

 “Potential Factors” and Water Consumption 

 

Figure 3, Table 3, and Table 4 present data showing the relationship between age group and water usage. The data used for age group, gender, and cultural background was taken from the first survey. The following box and whisker plot in Figure 3 shows the relationship between age group and water usage. Additionally, Table 3 presents the average water usage and standard deviations for the 4 age groups. Table 4 presents the results of the T-tests conducted between different age groups.

 

As shown in Figure 3, the median water usage score for age groups 7-14 years, 15-24 years, and 65 years and older was approximately 4.5 to 5. The median water usage score for age groups 25-44 years and 45-64 years was approximately 4. There was more variance in the data for age groups 7-14 years and 65 years and older.



As shown in Table 3, the average water usage score for 7-14 years, 15-24 years, and 65 years and older was about 5. The average water usage score for 25-44 years and 45-64 years was about 4. By combining groups, the average water usage score for 7-24 years was 5 and that for 25-65 years and older was 4. The sample sizes for age groups 7-14 and 65 years and older were very small. The smaller sample size conveys that it is less representative of the population with this age in comparison to the other groups.    



As shown in Table 4, there was a significant difference in the data between age groups 15-24 years and 25-44 years. There was also a significant difference in the data between 7-24 years and 25-65 years and older.



Figure 4, Table 5, and Table 6 present data showing the relationship between gender and water usage. The following box and whisker plot in Figure 4 shows the relationship between gender and water usage. Additionally, Table 5 presents the average water usage and standard deviations for the 4 options below. Table 6 presents the results of the T-tests conducted between men and women.

 

As shown in Figure 4, the median water usage score for men and women was approximately 4. The median water usage score for non-binary respondents was 5. There was more variance in the data for women. 


As shown in Table 5, the average water usage score for men and women was about 4. The sample sizes for non-binary individuals and individuals who did not report their gender were 2. This sample size was too small to analyze.

As shown in Table 6, the T-test reported no significant difference in the data.

Figure 5, Table 7, and Table 8 present data showing the relationship between cultural background and water usage. The following box and whisker plot in Figure 5 shows the relationship between cultural background and water usage. Additionally, Table 7 presents the average water usage and standard deviations for the 9 options below. Table 8 presents the results of the T-tests conducted between different cultural backgrounds.

As shown in Figure 5, the median water usage score for cultural groups East Asian, European, Middle Eastern, and other/multiple was approximately 5. The median water usage score for African, South Asian, North American, and individuals who preferred not to answer was about 4. The median water usage score for South American cultural background was about 3.  There was more variance in the data for East Asians, other/multiple backgrounds and the prefer not to answer group. Because the other/multiple and prefer not to answer groups were nonspecific, they were not included in the analysis.



As shown in Table 7, the average water usage score for cultural groups East Asian, European, and Middle Eastern was about 5. The average water usage score for Africans South Asian and North Americans was about 4. The South American cultural background had the lowest average water usage score of 3. The South American cultural background had the smallest sample size. The smaller sample size conveys that it is less representative of the population with this age in comparison to the other groups.  The South Asian cultural background had the largest sample size. The larger sample size conveys that it is more representative of the population with this age in comparison to the other groups. 



As shown in Table 8, there was a significant difference in the data between North American and Middle Eastern backgrounds. There was also a significant difference in the data between Middle Eastern and South Asian backgrounds.  



Water Usage Consciousness Related to Income and Water Usage Score 

 

Figure 6, Table 9, and Table 10 present data showing the relationship between making conscious choices about water consumption and water usage score. The data used for this subsection was taken from the first survey. The following box and whisker plot in Figure 6 shows the relationship between conscious decision-making and water usage. Additionally, Table 9 presents the average water usage and standard deviations for the 2 options. Table 10 presents the results of the T-tests conducted between making and not making conscious choices about water usage.


According to Figure 6, the median water usage score for the group that made conscious choices for water consumption was about 5. The median water usage score for the group that did not make conscious choices for water consumption was about 4. There was more variation in the data for the group that did not make conscious choices.



According to Table 9, the average water usage score for the group that made conscious choices for water consumption was about 5. The average water usage score for the group that did not make conscious choices for water consumption was about 4. There was sample size for the group that made conscious choices was very large. The larger sample size conveys that it is more representative of the population with this income level in comparison to the other groups. 



As shown in Table 10, the T-test reported no significant difference in the data.



Table 11 and Figure 7 present the relationship between income range and making conscious decisions about water consumption. Table 11 tallies the number of individuals who make and do not make conscious choices within each income range. Figure 7 visually depicts this by showing the percentage of respondents from each income range that make and do not make conscious choices.

 

As shown in Table 11 and Figure 7, in the income range of $40,000 or less, about 70% of respondents make conscious choices about water consumption and about 30% do not. In the income range of $40,001 - $60,000, about 70% of respondents make conscious choices about water consumption and about 30% do not. In the income range of $60,001 - $100,000, about 85% of respondents make conscious choices about water consumption and about 15% do not. In the income range of $100,001 or more, about 80% of respondents make conscious choices about water consumption and about 20% do not.



 

Discussion

 

Income and Water Usage Score 

 

All income ranges had a moderate average score of 4 (Table 1). However, there was more variance in data for the income range of $40,000 or less. This may be caused by different levels of understanding about water conservation as households may not be able to afford or have access to quality education on sustainability. This may also be caused by varying levels of dependence on water due to financial needs.  After conducting a T-test on the data, it was found that there was no significant difference in the data (Table 2). Therefore, no conclusion about the relationship between income and water usage can be made from the data. More research will need to be done to find a relationship between income and water usage. Future studies should consider household water consumption based on income relative to household size.  Future studies should also consider equal sample sizes in their experiment, as unequal sample sizes may have affected the significance of the results of this paper.

 

Water Usage in Various Parts of New Jersey 

 

Water usage may be related to income range based on water consumption levels in different areas of New Jersey. Based on the map, there is no correlation between the water usage score and the area of New Jersey (Figure 2). Most of the townships included in the survey had a moderate score of 4. Although there was no overall relationship between water usage score and the area of New Jersey, some townships in New Jersey had high water usage scores. Howell Township had the highest average score of 8 (Figure 2). Howell is reported to have a high median household income in comparison to the rest of the United States (ZIP Code 07731 Map, Demographics, More for Howell, NJ, n.d.). Randolph, Passaic, Dunellen, and Hillsborough had the second highest water usage score of 7, and Plainsboro had a high water usage score of 6, According to UnitedStatesZipcodes.org, the median household income is also extremely high in comparison to the rest of the U.S. in Randolph, Dunellen, Hillsborough, and Plainsboro. However, The median household income in Passaic is “low compared to the rest of the country” (ZIP Code 07055 Map, Demographics, More for Passaic, NJ, n.d.)This website gets its data from the United States Postal Service, the U.S. Census Bureau, Yahoo, and the IRS. The information suggests that high incomes can result in high water consumption. However, because this survey did not account for all the areas in New Jersey, more research is needed on this topic to access water consumption across the whole state.

 

More research can be done on whether a township’s wealth is related to water usage to assess whether water usage score is related to a school’s curriculum on sustainability. Because township wealth affects a school district’s curriculum, studies should investigate whether a township school district’s curriculum impacts water usage among residents. Research should also be done on how private and parochial schools’ education affects individuals’ water usage. This may convey a relationship between household income, education on sustainability, and household water usage.

 

For conducting future studies on this topic, researchers should consider using ZIP code information instead of township information, for more specificity and ease when constructing the map (as it was only programmed to use zip codes).

 

 “Potential Factors” and Water Consumption 

 

Age groups 7-14 years, 15-24 years, and 65 years and older used more water than age groups 25-44 years and 45-64 years (Table 3). Adolescents and young adults used more water than mature adults and elderly people (Table 3). There was more variation in routine water consumption for age groups 7-14 years old and 65 years and older (Figure 3). This may be caused by different levels of understanding about water conservation for young children and different needs based on medical reasons for older adults. This can also be caused by the need to use more water in relation to physical activity and sports in younger ages. Individuals 15-24 years used significantly more water than individuals 25-44 years (Table 4). This may be because teens ages 15-24 years are usually negligent in understanding the importance of conserving water, not only for sustainability but also for saving money. Meanwhile, adults ages 25-44 years are becoming independent and making a family. Because they must pay water usage bills and model good practices for their children, they are more careful about how much water they use. Adolescents and young adults used significantly more water than mature adults and elderly people (Table 4). Again, this may be caused by the lack of maturity and responsibility in adolescents and young adults. More research can be done to investigate this.

 

All genders used a moderate amount of water in their routine practices, having an average score of 4 (Table 5). There was no significant difference in the amount of water men and women used (Table 6). More research can be done to consider people of other identifications.

 

East Asian, European, and Middle Eastern backgrounds on average used more water than African, South Asian, North American, and South American backgrounds (Table 7). Individuals of North American background used significantly less water than those of Middle Eastern background, and individuals of South Asian background used significantly less water than individuals of Middle Eastern background. (Table 8). This difference may be caused by the different ideas of how to use water across different cultures. It may also be caused by different amounts of education on sustainable practices across cultural groups. In future studies, using closer sample sizes for each cultural background would provide more accurate results.

           

Because household size was addressed only in the second survey with 15 responses, the results for the data were insignificant compared to that of the data from the first survey. Lacking a large sample size for the data in household size was one of the most impactful errors in this paper.

 

Water Usage Consciousness Related to Income and Water Usage Score 

 

People who make and do not make conscious decisions for water usage use the same amount of water. (Table 9). No significant difference was found between these two groups’ water usage (Table 10). It was also found that more individuals did not make conscious decisions about water usage in the groups who had an income range of $40,000 or less and $40,000 to $60,000 (Figure 7). This may be because of a dependency on water for specific financial disadvantages. It also may be possible that less education about sustainable practices is given to these groups. More research would be needed to conclude a relationship between financial need and high water usage or between less education and high water usage.

 

Conclusion

           

In contrast to Hassan Furqan Khan’s finding that wealthier people use more water in Karachi, Pakistan, it cannot be concluded that wealthier people use more water in New Jersey. However, like the studies of Aluko and Dr. Liang, a direct relationship between income and water consumption could only be suggested. Yet more research is required to conclude it.


The hypothesis of this paper was not supported, as no conclusion could be made about the correlation between income and water usage of a household in New Jersey. However, the results suggest that higher income levels cause high water usage, as in subsection 4.2, it was found that wealthier areas of New Jersey included in the survey used the most water. In addition, as in subsection 4.3, younger people used more water than older people. Regarding decision-making, more people with higher incomes made conscious choices about water consumption than people with lower incomes. Lacking a consideration of household size was a significant error that future research should address. A potential error that future research should consider is that a more standardized way should be used to measure water usage; the water usage score assigned to each value should be weighed against how much water a task used. As shown in Appendix A, each of the higher options for tasks in the survey was assigned a higher score by 1 unit. This system was not practical. For example, doing 1-2 loads of laundry in a week, used significantly more water than keeping the faucet on while brushing teeth; however, both were assigned a score of 1. Future studies should assess the relationship between wealth, education on sustainability, and water usage. Future studies should also investigate why people from certain cultural backgrounds use more water than others. Future research needs to consider collecting equal sample sizes for categories, so the most accurate comparison can be made. Furthermore, future research should consider studying water usage patterns across the United States, so that changes to water usage sustainable development initiatives can be made on the federal level.

           

This paper is important because it shows that household size, age, and cultural background must be addressed when planning solutions for more sustainable water consumption to combat water insecurity. This study can be implemented in sustainable development departments when trying to understand why certain households use more water than others. They can also use this study’s findings when trying to produce solutions to balancing water usage in a community. Based on the findings in this paper, more than 70 % of people (from all income groups) make conscious choices about water usage. This means that if proper and convincing education were given about adopting sustainable water consumption routines most people would choose to conserve water.


 

Appendix A. Water Usage Survey


1. What is your age? 

a. 7-14 years old

b. 15-24 years old

c. 25-44 years old

d. 45-64 years old

e. 65 years and older 


2. What is your gender? 

a. Man

b. Woman

c. Non-Binary

d. Prefer not to answer


  1. Do you live in the state of New Jersey? 

a. Yes

b. No


4. In which township do you live? ______


5. What is your cultural background? 

a. North American

b. South American

c. European

d. African 

e. Middle Eastern

f. East Asian

g. South Asian

h. Other / Multiple

i. Prefer not to answer


6. In which range does your household’s yearly income fall? 

a. $40,000 or less

b. $40,001-$60,000

c. $60,001-$100,000

d. $100,001 or more


7. In what range does your household size fall?

a. 1-3 people

b. 4-6 people

c. 7-9 people

d. 10 or more people


8. Do you turn the faucet off while brushing your teeth?

a. Yes [1]

b. No [0]


9. How long do you take in the shower?

a. 2 minutes-5 minutes [0]

b. 6 minutes-10 minutes [1]

c. 11 minutes-20 minutes [2]

d. 21 minutes-40 minutes [3]


10. How long does your family take to wash or rinse dishes in a day?

a. 10 minutes-15 minutes [0]

b. 16 minutes-25 minutes [1]

c. 26 minutes- 40 minutes [2]


11. How many cycles of the dishwasher do you run in a week?

a. 0 [0]

b. 1-2 [1]

c. 3-4 [2]

d. 5 or more [3]


12. How many loads of laundry does your household do in a week?

a. 1-2 loads [0]

b. 3-4 loads [1]

c. 5 or more loads [2]


13. In the summer, do you have a service that waters your lawn/backyard?

a. No [0]

b. Yes, but not frequently [1]

c. Yes, and frequently [2]


14. Do you make conscious choices about water usage? In other words, do you think about

the amount of water you consume during your daily routines?

a. Yes

b. No


15. If you answered yes to the previous question, please select possible reasons for you

answer. 

a. Environmental concern

b. Financial concern

c. Religious reasons

d. Cultural reasons

e. Other


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ZIP Code 07731 Map, Demographics, More for Howell, NJ. (n.d.). Retrieved April 16, 2024, from https://www.unitedstateszipcodes.org/07731/

 

“Water Security for All.” Unicef. March 2021. https://www.unicef.org/media/95241/file/water-security-for-all.pdf.


 

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